Write a research paper that analyzes methods used to ethically manage teams and groups within organizations. In your research paper, be sure to include the following elements:

• Distinguish between a group and a team.
• Discuss ethical decision-making in team leadership that promotes social responsibility.
• Discuss leadership styles and traits that are effective for successful management of groups and teams.
• Include a discussion on any aspect of leadership covered in the course that was of particular interest to you. All topics do not need to be included; yet, followership, ethics, leadership styles, multicultural leadership, and conflicts of interest are all topics that have been studied, and any one (or more) that you found particularly interesting could be incorporated into the discussion.

Your research paper should be a minimum of three pages in length, not including the title and references pages. Utilize the CSU Online Library to locate a minimum of three sources to use as references that support your research paper. All sources used must be cited and referenced according to APA guidelines.

Be sure to include the rubric elements from the guidelines below.

• Your introduction should engage the reader and clearly present the thesis and a summary of the main points to clarify your point of view.
• The review of the literature should present a critical analysis and synthesis of the existing research.
• The discussion should reveal insightful analysis of research.
• A summary should be present that reviews or summarizes key points and provides a smooth transition between sections.
• The writing should be clear and concise with proper sentence structure, grammar, and punctuation, and it should be free from spelling errors.
• The number of academically credible sources should meet the requirements and should be properly cited, per APA standards.

RESEARCH Open Access

Obstacles open the door — Negative
shocks can motivate individuals to focus on
opportunities
Jin Feng, Wenxia Zhou, Shuoyu Li and Mengyi Li*

* Correspondence: ellenli@ruc.edu.
cn
School of Labour and Human
Resources, Renmin University of
China, No.59 Zhongguancun Street,
Beijing 100872, China

Abstract

By responding to the call for research on negative career shocks and future time
perspective, this study regarded internal social capital as a tool of resource retention
which shifts attention to negative career shocks’ positive effects. We test a
moderated mediation model which illustrates the effect of negative career shocks on
focus on opportunities—positive dimension of occupational

future time perspective.

Results

revealed that internal social capital acts as the mediator between negative
career shocks and focus on opportunities, and organizational embeddedness
moderats the mediation effect. The relationship is stronger when individuals are
highly embedded in organizations.

Keywords: Career shocks, Future time perspective, Focus on opportunities, Internal
social capital,

Organizational embeddedness

“Whatever does not kill them makes them stronger. —— Friedrich Nietzsche”

“Trouble is only opportunity in work clothes. —— Henry J. Kaiser”

Recent career research has argued that career development is becoming more dynamic,

complex, unpredictable and flexible (Vuori and Okkonen 2012; Baruch 2004). The

increasingly complex and unpredictable nature of contemporary careers will be accom-

panied by increased unpredictable career events such as layoffs, bankruptcy or family

issues that may change individual’s career path. In research, these events are repre-

sented by terms such as happenstance, serendipity, or chance events (Miller 1983;

Betsworth and Hansen 1996; Bright et al. 2005; Akkermans et al. 2018). Hirschi (2010)

indicates that such major events that happen in people’s lives have a significant impact

on their career paths. Shocks (e.g. an important mentor or colleague’s departure or

organizational change) have been shown to predict organizational turnover (Hom

et al. 2017; Lee et al. 2017; Seibert et al. 2013), and better clarify why people leave

or stay.

Lee and Mitchell (1994) proposed career shock as a jarring event that evokes a per-

son to pause and think about the meaning of their jobs and in turn, provokes some

considerations of leaving their jobs. Recently, Akkermans et al. (2018) described career

shock as a disruptive and extraordinary event. Shocks can be positive, neutral or

© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International
License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

Frontiers of Business
Research in China

Feng et al. Frontiers of Business Research in China (2020) 14:1
https://doi.org/10.1186/s11782-019-0067-9

http://crossmark.crossref.org/dialog/?doi=10.1186/s11782-019-0067-9&domain=pdf

http://orcid.org/0000-0001-9873-5109

mailto:ellenli@ruc.edu.cn

mailto:ellenli@ruc.edu.cn

http://creativecommons.org/licenses/by/4.0/

negative, expected or unexpected, and personal or organizational (Holtom et al. 2005).

As one of the most important factors predicting employees’ voluntary turnover, career

shock has been proven to influence individuals’ work behaviors and career planning

(Burton et al. 2010; Holtom et al. 2005), and alter employee’s career path (Bright et al.

2005). However, not enough attention has been paid to individual career trajectories in

this (Akkermans et al. 2018). Hence, investigating the role of career shocks on individ-

uals’ career decision-making can help organizations to predict work behaviors such as

work engagement, performance, and turnover.

Future time perspective is a core construct in socioemotional selectivity theory

(Carstensen et al. 1999), and is defined as an individual’s “subjective sense of future

time” (Carstensen, 2006). From socioemotional selectivity theory, age is the major fac-

tor to predict future time perspective (Fung et al. 2001), and younger adults focus more

on opportunities compared to older adults (Zacher & de Lange, 2011). Occupational fu-

ture time perspective is conceptually distinguished in two related dimensions, “per-

ceived remaining time” and “focus on opportunities.” Perceived remaining time is

defined as individuals’ perception of restrictions in future career and concentration on

losses and limitations. Focus on opportunities is defined as individuals’ perceptions of

new work-related goals and possibilities that are foreseen in the future (Zacher and

Frese, 2009). Researchers have supported the relationship between occupational future

time perspective and job related outcomes, such as career maturity, career planning

and career decidedness (e.g. Taber and Blankemeyer 2015). The way how individuals

perceive their future can influence their career decisions, career maturity (Cheng et al.

2016), job satisfaction (Weikamp and Göritz 2016), occupational self-efficacy, career

commitment and turnover intention (Park and Jung 2015). However, there is a lack of

research in how constraining job factors such as negative life events and hindering job

demands impact employees’ future time perspective (Rudolph et al., 2018). Examining

and discussing constraining job factors as antecedents can enrich the understanding of

future time perspective.

Our study aims to examine the effect of negative career shocks for three reasons.

First, in daily life, people believe that the more positive life events, the better. However

events evoke different emotional intensities, so more may not always be better (Seta

et al. 2008). Researchers suggest that “bad is better than good,” and suggest that nega-

tive events may exert stronger influence on individual’s career development by provid-

ing greater motivation compared with positive events (Baumeister et al. 2001; Larsen

and Ketelaar 1991; Holtom et al. 2012). Second, previous research indicates that, due to

the effect of mood, each person can react differently towards negative shocks (Weiss

and Cropanzano 1996), so that rather than reducing work effort, highly embedded em-

ployees are possible to re-focus on the job and increase organizational citizenship be-

havior (OCB) after experiencing negative shocks (Burton et al. 2010). Last but not least,

negative shocks appear more often than positive shocks (Holtom et al. 2012). People

may not be sensitive to positive shocks, but are sensitive to negative shocks. Therefore,

discovering the effects of negative shocks can advance the research and theory in career

development.

Exploring the predictors of both dimensions of occupational future time perspective

is very important (Henry et al., 2017; Rudolph et al. 2018). However, the predictors of

focus on opportunities are lacking in current research. Job complexity and job control

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 2 of 17

are the main antecedents that has been studied so far (Zacher and Frese 2009, 2011;

Rudolph et al. 2018). In order to find the antecedents of focus on opportunities, we

proposed and tested a moderated mediation model in which we posit that negative

shocks indirectly influences people’ s future time perspective through the effect of so-

cial capital, and organizational embeddedness acts as a boundary condition of this rela-

tionship. Fig. 1 presents our proposed research model.

Conceptual development and hypotheses development

The unfolding model of voluntary employee turnover (Lee and Mitchell 1994; Lee et al.

1996) proposed the construct of career shock from Beach’s (1990) decision-making

model and image theory, to understand the processes of employees’ decisions to quit.

According to the image theory, individuals constantly obtain information that could

potentially lead to changes in their behavior. Some sorts of unexpected events, which

have been defined as shocks to the system, lead individuals to pause and think about

the meaning or implication in relation to their job (Lee and Mitchell 1994). Based on

this unfolding model of voluntary employee turnover, shocks can alter individuals’

psychological processes. If it recalls prior memory and violates individuals’ value image,

then people would choose a preexisting plan to leave. Seibert et al. (2013) showed that

positive shocks instead of negative shocks can motivate individuals to pursue to gradu-

ate education, which helps to understand the benefits of shocks. Also, job embedded-

ness has been proven to buffer the negative effect of negative shocks during the

workplace (Holtom and Inderrieden 2006; Burton et al., 2010; Holtom et al. 2012).

These studies enable us to analyze the benefits of negative shocks and address the

research question: How can negative shocks motivate employees?

Hobfoll’s (1988, 1989) model of conservation of resources proposes that individuals

strive to retain, protect, and build resources, and then apply them to improve well-

being and personal development over time. Resources are defined as assets and goods

that people value, with an emphasis on objects, states, and conditions; almost anything

good can be considered a resource (Gorgievski et al. 2011). Job security (Selenko et al.

2013), autonomy (Chen et al. 2009), social support (Zimmermann et al. 2011; Liu et al.

2013; Diestel and Schmidt 2012), self-esteem, self-efficacy, locus of control, and core

self-evaluation (Chen et al., 2009; Xanthopoulou et al., 2009) are examples of psycho-

logical resources reported in the organizational literature. Therefore, to open the black

box of negative shocks’ impact, resource loss and retrieval can be considered as critical

for analyzing the psychological process.

Fig. 1 Proposed research model

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 3 of 17

Mediating influence of internal social capital

When people experience negative shocks which threaten their resources and diminish

their well-being, they are likely to have a sense of insecurity and lack of support,

making people feel that they lose important psychological resources (Koopmann et al.,

2016). According to conservation of resources theory, in the face of stressful resource

loss, individuals may use other resources to offset net loss and attempt to conserve

remaining resources (cf. Pearlin et al. 1981; Halbesleben 2010; Halbesleben and

Wheeler 2011). An effective strategy to mitigate the situation is very important to one’s

career path. During career shocks, social capital provides an effective way to shift atten-

tion to career management strategies (Seibert et al. 2001; Wayne et al. 1999). Social

capital can be used to help employees find new job alternatives or positions both inside

and outside the organization (Granovetter, 1973; Marsden & Hurlbert, 1988; Zippay,

2001).

The construct of internal social capital is a critical dimension of political skill and

refers to developing and using networks of people (Ferris et al. 2005). It mainly indi-

cates establishment of social ties within the organization, especially among supervisors

or managers, and advances career success inside the company. Individuals with high

level of internal social capital easily develop friendship and build strong and beneficial

alliances and coalitions. They ensure that they are well positioned in order to both cre-

ate and take advantage of opportunities (Pfeffer 1992). Through internal social capital,

people retain, protect, and build valued social capital resources by developing relation-

ships with others who have the potential to assist them in their careers (Forret and

Dougherty 2004). Therefore, internal social capital can meet individuals’ needs and serve

as intrinsic motivation to achieve their innate goal. In this paper, internal social capital is

considered as resources in Hobfoll’s model (Hobfoll 1988, 1989).

When individuals have more friends and build good relationship with influential

colleagues through internal social capital, they gain social support (Diestel and Schmidt

2012) and build a resource-rich environment beneficial for career development. Social

support has been shown to be an effective strategy to deal with stressful life events, and

close dyadic relationships offer well-established psychological benefits (Collins and Feeney

2000), which protect individuals’ valued identities (Petriglieri, 2011) and strengthen their

career goals. This reasoning is in line with the process known as a “gain cycle” from the

conservation of resources model (Hobfoll 1989). Based on the social support in the work

environment, individuals would be better able to predict their future career development.

The more resource-rich the work environment, the more opportunities an individual per-

ceives for their future work (Rudolph et al. 2018). Therefore, we propose that:

Hypothesis 1: Internal social capital mediates the relationship between negative shocks

and focus on

opportunities.

Moderating influence of organizational Embeddedness

Mitchell et al. (2001) used three dimensions for job embeddedness: links, fit and sacrifice.

Links describes the number of ties employees have within the organization, i.e., the formal

or informal connections between a person and institutions or other people. Fit means the

compatibility or comfort between employees and the organization, or environment. While

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 4 of 17

sacrifice stands for the potential cost or benefits of leaving the job, this construct has later

been developed more broadly to indicate organizational and community embeddedness

(Ng and Feldman 2010a). Crossley et al. (2007) proposed a reflective measure for job em-

beddedness which has better psychometric properties, as a measure for organizational em-

beddedness. This measure has equivalent prediction in comparison with the original one

(Lee et al., 2014), and has been adopted to predict social capital and human capital (Ng

and Feldman 2010a).

Studies show that organizational identification has a positive influence on individuals’

emotions (Avanzi et al. 2015; Avanzi et al. 2018; Frisch et al. 2014), and on turnover

(e.g. Van Dick et al. 2004; Lee et al. 2015). However, as we concentrate on the adverse

impact of negative career shocks and organizational embeddedness has shown to have

a buffer effect (Burton et al. 2010; Holtom et al. 2012), we decide to include

organizational embeddedness in our model.

Organizational embeddedness represents a broad constellation of influences on

employee retention (Lee et al. 2014; Mitchell et.al., 2001). In this study, we focus on

organizational embeddedness that is more closely related to individuals’ career develop-

ment, and it shows a strong link between career plans and the present job (Ng & Feld-

man, 2010a). Employees who are highly embedded in organizations will have more job

security, employment stability and professional success (Ng and Feldman 2007) and re-

duced likelihood of looking for alternative jobs (Holtom and Inderrieden 2006). In

order to reduce the negative influence of turnover, researchers study the buffer effect

of organizational embeddedness (Holtom and Inderrieden 2006; Burton et al. 2010;

Holtom et al. 2012). Therefore, high level of organizational embeddedness could help

to reduce turnover and turnover intention, or improve job related outcomes such as

core task performance and citizenship behaviors (Crossley et al. 2007; Wijayanto and

Kismono 2004).

From the escalation of commitment literature (Brockner 1992; Staw 1981), highly

embedded individuals will continue to exert efforts, increase their efforts to cement

their relationship with the organization even under negative shocks (Burton et al.

2010). Highly embedded individuals tend to set goals within their organizations, are

motivated to stay and work in their organizations, and have a high degree of fit with

their organization. Thus, these individuals have a higher degree of interconnectedness

with their peers, and more social capital leading to increase in focus on opportunities.

In addition, when individuals develop a high degree of fit with their organizations and

perceive higher cost of leaving, they may be motivated to deploy skills that could help

them stay, and therefore reduce the effect of negative shocks and shift the attention to

opportunities.

Hypothesis 2 : Organizational embeddedness moderates the strength of the mediated

relationship between negative shocks and focus on opportunities through internal social

capital such that the mediated relationship is stronger when organizational

embeddedness is high.

Hypothesis 3 : Organizational embeddedness moderates the strength of the

mediated relationship between negative shocks and focus on opportunities through

internal social capital such that the mediated relationship is weaker when

organizational embeddedness is low.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 5 of 17

Method

Sample and procedure

We conducted a time-lagged study in which we collected two-wave data in June (wave 1)

and December (wave 2) 2018. In wave 1 (T1) we measured negative career shocks and

demographic varibles, and in wave 2 (T2) we measured internal social capital,

organizational embeddedness and occupational future time perspective. Since we were in-

terested in career shocks and future time perspective of general population in China, we

avoided collecting data within companies in case to obtain a biased sample. Instead, we

used a snowball sampling method through a Chinese social network App (Wechat).

Wechat was created in 2011 by a Chinese Internet giant Tencent as a chat App with fea-

tures and functionality similar to WhatsApp. According to Wechat data report (2018, re-

leased by Wechat official), about 1.08 billion of which 63 million were over 55 years old

are monthly active users of Wechat.

We received a total of 352 responses in T1. Each participant received RMB5 for par-

ticipation. Six months later, the T2 survey invitation was sent to same participants,

each participant receive another RMB5 as gratitude. After matching the telephone

number, email address and name, our samples contained 230 participants. In order to

ensure the quality of survey, we set three testing questions in both surveys which were

“if you are answering the questions carefully, please choose 5 (strongly agree)” “if you

are answering the questions carefully, please choose 4 (relatively agree)” and “if you are

answering the questions carefully, please choose 3 (sometimes).” 20 responses that

failed these testing questions were eliminated and the final sample size was 210.

Average age was 31.48 years old (SD = 5.63) and 31.80% of them were female. Average

tenure with the current employer was 8.10 years (SD = 6.09). The participants worked in

varied organizations such as state-owned enterprises (23.20%), party and government

organizations or public institutions (22.70%), private enterprises (19.10%), institutions of

higher learning (15.00%), foreign-owned enterprises (8.60%), strategic response unit

(2.30%) among others (9.10%). 56.80% of the participants in our sample had a bachelor

degree, 28.60% had a master degree, 5.90% had a doctor degree, still 8.60% among others.

Measures

Negative career shocks

We use the career shocks scale developed by Seibert et al. (2013) mainly because this

scale was specifically related to individual’s career management. The scale contains four

items to measure both positive shocks and negative shocks. In this study, since we only

focus on negative shocks, only the two items about negative career shocks were used

(see

Appendix

). Participants were asked whether they experienced the career shock or

not (coded as 1 or 0), since a career shock is a formal construct that implies employees’

turnover intention. In order to test the validity, we conducted the regression effect on

participants’ turnover intention (β = 0.47, p < 0.01). The result supported the use of this

measure for career shocks by definition and in accordance with previous research.

Internal social capital

We used three items out of the six items from the Political Skill Inventory which is

measured on a 5-point Likert-format scale (from 1 = strongly disagree to 5 = strongly

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 6 of 17

agree) (Ferris et al. 2005). Before the wave 1 survey (T1), we pruned several items to

simplify our questionnaire. As a result, we used three high loading items to measure

internal social capital (see Apendix). The Cronbach’s α was acceptable at 0.71.

Organizational embeddedness

We used the global organizational embeddedness scale (Crossley et al. 2007) (see Appendix).

The original scale consisted of seven items, we deleted one item (“I feel tied to this

organization”) for semantic repetition with other items such as “I am tightly connected to this

organization”. All items were measured on a 5-point Likert scale (from 1 = strongly disagree

to 5 = strongly agree). This scale had an acceptable reliability of 0.76.

Focus on opportunities

We measured focus on opportunities with three items from Zacher and Frese’s (2009)

occupational future time perspective scale (see Appendix). Participants were asked to

rate on a 5-point scale (from 1 = strongly disagree to 5 = strongly agree) with a Cron-

bach’s α = 0.75. Some researchers found that perceived remaining time may be an ante-

cedent of focus on opportunities (Kooij et al. 2014). In addition, perceived remaining

time and focus on opportunities were counterparts, so in this study we controlled for

the effect of perceived remaining time (see Appendix). To test whether perceived

remaining time and focus on opportunities were two distinct dimensions, we conducted

confirmatory factor analyses (CFA) comparing results of one-factor and two-factor

model. The two-factor model fit the dataset better, with χ2/df = 1.49, TLI = 0.95, CFI =

0.97, RMSEA = 0.05, SRMR = 0.03. This result indicated that the two dimensions should

be distinguished.

Control variables

Individual characteristics are important sources of occupational future time perspective

(for a review see Kooij et al. 2018; Rudolph et al. 2018). Among all the antecedents of

occupational future time perspective, age was highly important (Froehlich et al. 2016;

Zacher and Frese 2009). Because people in different life stages have different percep-

tions of time and this would end up in various perspectives about future (Lang and

Carstensen 2002), in this study we controlled for demographic characteristics such as

gender, age, organizational tenure and education. Other demographic characteristics

such as company size and company type were not controlled because they were not

personal resources or time-related characteristics.

Data analysis

We used SPSS 22.0 to conduct descriptive statistics and correlation analysis. Before

testing the hypotheses and the model, CFA was conducted using Mplus 7.0. In

order to test indirect effects, Preacher and Hayes (2004) recommended a resam-

pling method such as bootstrapping to increase power and decrease Type I error.

We performed bootstrapping using Model 14 of Process bootstrapping approach

provided by Hayes (http://www.afhayes.com/spss-sasand-mplus-macros-and-code.

html) to test direct, indirect, and moderated mediation model.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 7 of 17

http://www.afhayes.com/spss-sasand-mplus-macros-and-code.html

http://www.afhayes.com/spss-sasand-mplus-macros-and-code.html

Results
Descriptive statistics and correlations

Table 1 presented the means, standard deviations and correlations for main variables.

We found that negative career shocks were positively related with focus on opportun-

ities (r = 0.16, p < 0.05) and internal social capital (r = 0.19, p < 0.01). Internal social cap-

ital was positively related with focus on opportunities (r = 0.27, p < 0.001).

Organizational embeddedness was not significantly related with focus on opportunities

(r = −0.13, p > 0.05). Finally, the results showed internal social capital had a stronger re-

lation with focus on opportunities compared with other factors.

Confirmatory factor analysis

CFA was used to test discriminant validity of the multi-dimension scale (internal

social capital, organizational embeddedness and focus on opportunities). Before

CFA, we conducted the Kaiser-Meyer-Olkin (KMO) test and the Bartlett’s test of

sphericity. The KMO value of 0.72 and the result of Bartlett’s test sphericity (p <

0.001) indicated that the sample was suitable for factor analysis.

Following established practice (Byrne 2013; Hu and Bentler 1999), we used various fit

indices to evaluate the fit of the model: χ2/df should be less than 3.00, SRMR (Standard-

ized Root-Mean-Square Residual) should be close to 0.08, CFI (Comparative Fit Index)

and TLI (Tucker-Lewis Index) should be close to 0.95, and RMSEA (Root Mean Square

Error of Approximation) should be close to 0.06.

In this study, we used item pairs to conduct CFA for higher reliability (Cattell and Burdsal

Jr 1975; Kishton and Widaman 1994), normal distribution (Bagozzi and Heatherton 1994)

and less idiosyncratic variance (Little et al. 2002). The results of CFA were shown in Table 2.

The three-factor model fit the data best compared with two-factor model and one-factor

model. This result suggested that hypothesized model of three factors was better than

others. Distinctiveness of all scales used in this study was ensured.

Test of hypotheses

Hypothesis 1 indicated that internal social capital mediates the effect of negative career

shocks on focus on opportunities. Table 3 showed the result of indirect effect. For the

Table 1 Descriptive statistics and correlations (N = 210)a

Mean SD 1 2 3 4 5 6 7 8 9 10

1 Gender 1.69 0.47 1.00

2 Age 31.28 5.44 −0.01 1.00

3 Tenure 7.88 5.89 −0.02 0.92** 1.00

4 Education 3.35 1.29 0.04 0.22** −0.02 1.00

5 Company scale 3.33 0.73 0.07 −0.12 −0.09 −0.04 1.00

6 Company type 3.30 2.04 −0.04 −0.21** −0.15* −0.25** 0.11 1.00

7 NCS 0.81 0.39 −0.09 −0.11 −0.11 0.00 0.08 0.18** 1.00

8 ISC 3.47 0.82 −0.06 −0.10 −0.09 −0.11 −0.05 0.13 0.19** 1.00

9 FTP-O 3.45 0.92 −0.03 −0.23** −0.24** 0.03 −0.04 0.12 0.16* 0.27** 1.00

10 OE 3.37 0.77 0.04 0.03 0.04 0.01 0.11 −0.06 −0.15* 0.01 −0.13 1.00
aNotes. NCS = negative career shocks. ISC = internal social capital. FTP-O = focus on opportunities of future time
perspective. OE = organizational embeddedness. *p < 0.05, **p < 0.01, ***p <0 .001

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 8 of 17

total effect, negative shocks can not predict focus on opportunities (β = 0.21, 95%CI =

[−0.002, 0.63]). Internal social capital positively predicted focus on opportunities

(β = .27, 95%CI = [0.03, 0.41]). The indirect effect of negative shocks on focus on oppor-

tunities was significant (β = .10, 95%CI = [0.02, 0.25]). The explained variance changed

from .06 to .13. This result indicated that internal social capital mediates the effect of

negative career shocks on focus on opportunities. Thus, Hypothesis 1 was supported.

Hypotheses 2 and 3 proposed that organizational embeddedness moderates the

strength of the mediated relationship between negative shocks and focus on opportun-

ities through internal social capital. We further conducted the simple slope test to illus-

trate this result according to Aiken and West (1991). Table 4 showed the moderated

mediation results. Fig. 2 depicted the relationship between internal social capital levels

and focus on opportunities at both low and high levels of organizational embeddedness.

The results showed that when organizational embeddedness was higher (one SD above

the mean), the relationship between internal social capital and focus on opportunities

was stronger (β = 0.16, 95% CI = [0.03, 0.36]), and when organizational embeddedness

was lower (one SD below the mean), the relationship became non-significant (β = 0.03,

95% CI = [−0.03, 0.16]). Thus the relationship between internal social capital and focus

on opportunities is only significant when organizational embeddedness was high. This

result provided support for Hypothesis 2 but not for Hypothesis 3.

Discussion

There has been studies on how career shocks influence voluntary turnover. We examine

the effects of career shocks on occupational future time perspective because the study

about antecedents of occupational future time perspective is especially rare and the

underlying mechanism is not clear. This results support a model in which internal social

capital mediates the effect of negative career shocks on the dimension of focus on oppor-

tunites. Even negative shocks can not directly predict future time perspective, but they do

Table 2 CFA of the items (N = 210)

χ2 df χ2/df SRMR CFI TLI RMSEA

CFA-three factors 39.75 24 1.66 0.05 0.96 0.94 0.06

CFA-two factors 247.63 26 9.52 0.14 0.41 0.19 0.20

CFA-one factor 284.64 27 10.54 0.16 0.32 0.09 0.21

Table 3 Regression results for testing mediation in Hypothesis 1a

Variable and statistic Outcome: Internal social capital Outcome: Focus on opportunities

Constant 3.43*** 2.86***

Gender −0.08 −0.02

Age 0.02 −0.02

Tenure −0.03 −0.01

Education −0.15 0.10

Negative career shocks 0.38** 0.21

Internal social capital 0.27***

F 2.48 5.22

R2 0.06 0.13
aNotes. Bootstrap sample size = 5000. Results were reported after controlling for age, gender, tenure, education and
perceived remaining time. *p < 0.05, **p < 0.01, ***p < 0.001

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 9 of 17

still relate with focus on opportunities which may help to find other mechanisms in the

future. As individuals become more embedded in the organization, this mediation effect

would be stronger. However, for people less embedded within their organization, there is

no effect. The result could be seen as in line with the previous studies showing that

organizational embeddedness could buffer the negative effect of negative shocks (Burton

et al. 2010; Holtom et al. 2012).

Implications for theory development

We obtain a novel result showing that negative career shocks can motivate people to

be open for future career development through internal social capital. This positive

effect was unexpected since negative career shocks usually generate negative effects

such as turnover (Holtom et al. 2005).

This research shows the mechanisms by which negative career shocks motivate indi-

viduals to focus on opportunities and under what circumstances this effect exists. We

incorporated negative career shocks within a conservation of resources theory frame-

work in response to a calls for the use of this theory to study career shocks (Akkermans

et al. 2018). We demonstrate the significance of internal social capital as a mediator of

the negative relationship of career shocks to focus on opportunities by using the con-

servation of resource theory to explain the resource loss and retention.

Table 4 Moderated mediation results for career shocks across levels of organizational
embeddednessa

Moderator Level Effect Boot SE Boot LLCI Boot ULCI

Organizational embeddedness −1 SD (−.77) 0.03 0.05 −0.03 0.16

0.00 0.09 0.05 0.02 0.23

+ 1 SD (.77) 0.16 0.08 0.03 0.36
aNotes. Bootstrap sample size = 5000. Results were reported after controlling for age, gender, tenure, education and
perceived remaining time

Fig. 2 Interactive effect between internal social capital and organizational embeddedness on focus on
opportunities Notes. Low organizational embeddedness and low internal social capital were defined as at
least one standard deviation below the mean; high organizational embeddedness and high internal social
capital were defined as at least one standard deviation above the mean. High numbers indicated more
focus on opportunities. ISC = internal social capital

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 10 of 17

Moreover, while social links are important antecedents of employees’ attachment to

the current organization (Mitchell et al., 2001), only few studies has examined the role

of social links on career shocks. Based on the unfolding model of voluntary employee

turnover (Lee and Mitchell 1994; Lee et al. 1996), shocks can alter individuals’ psycho-

logical processes by recalling prior memories and violating individuals’ value image. In

this case people would probably choose a preexisting plan to leave. Our result offers a

new explanation of the initial process of the unfolding model of voluntary employee

turnover and addresses the buffering effect of negative shocks by introducing the role

of internal social capital, showing the importance of social capital in the workplace.

Furthermore, organizational embeddedness plays an important role in why people

stay, as a supplement to turnover research. It explains a lot of variance in the turnover

decision (Hom et al. 2017; Mitchell and Lee 2001). In prior studies, organizational

embeddedness has been studied as a moderator or mediator and plays an important

role in improving individuals’ work outcomes (Lee et al. 2014). Empirical studies have

already shown that organizational embeddedness can attenuate shocks’ deleterious

consequences such as employee turnover and job performance (Burton et al. 2010. Ng

and Feldman 2010a, 2010b). Our results show that in terms of individuals’ career devel-

opment, the more they are embedded, the more likely they are to focus on opportun-

ities through internal social

capital.

Although researchers recommend studying occupational future time perspective in

two separate dimensions, rather than combining into one (Rudolph et al., 2018; Cate

and John 2007; Henry et al., 2017), there has been very little research focusing on this

construct in detail. We mainly integrate conservation of resources theory and the

unfolding model of voluntary employee turnover to analyze how negative career shocks

alter employees’ occupational future time perspective, especially how negative shocks

motivate employees to focus on opportunities. This study shows that as a contextual

factor, negative career shocks motivate employees to be optimistic through the influ-

ence of social links. The study also expands the research of occupational future time

perspective to career studies.

Limitations and future research

The first limitation is that our research is conducted in Chinese culture. Since China is a

highly collectivistic country, relationship or guanxi plays an important role in workplace. In-

ternal social capital and organizational embeddedness both are crucial for employees. This

may help to support the effects whereas in other individualist countries this mechanism

may not work. Future studies can test this mechanism in other cultures, exploring whether

building social relationships is useful for retaining psychological resources. In addition, our

study only focuses on internal social capital, while external social capital can also be a sup-

plemental resource to individuals. Based on a perspective within the organization, this study

concerns only individuals’ internal social capital so as to discuss the moderating effect of

organizational embeddedness on the relationship between internal social capital and focus

on opportunities. Future studies should be conducted from a different perspective to under-

stand the functions of external social capital in the process of career shocks.

Lee and Mitchell (1994) defined a shock as “an event that generates information or

has meaning about a person’s job. A shock must be interpreted and integrated into the

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 11 of 17

person’s system of beliefs and images.” In this sense, whether a shock is positive or

negative should depend on individuals’ perception of it. If a negative career shock could

be perceived as a motivating factor, then it is inappropriate to define it as negative. As

career shocks matter a lot to employees’ turnover intentions or behaviors and company

operations, more research should be done to clarify its definition and effects. Career

shocks can often “jar an individual into psychological process of reappraising the trajec-

tory of their current career path” (Seibert et al. 2013) or “jar employees toward deliber-

ate judgements about their careers” (Slay et al., 2004). However, we did not discuss the

psychological process aroused by negative career shocks and this process may serve as

a mediator between negative career shocks and internal social capital. Future studies

should take these mechanisms into account to better explain that in what psychological

state individuals will conduct social capital development behaviors.

Future research can expand to the whole turnover process to uncover the mecha-

nisms present throughout the process and contribute to our understanding of turnover.

Once employees focus on opportunities, they are more likely to have job search behav-

iors, therefore increasing the likelihood of voluntary turnover.

We collect the second wave data 6 months after the first wave; a two-wave study

could avoid common method variance to a certain degree. However, occupational

future time perspective is part of an individual’s cognition which may not be altered in

the short term. Future research can expand the lagging period to at least 1 year, trying

to depict the varying picture of occupational future time perspective. For example,

future research could follow up individuals’ reactions on shocks in different career

periods. Another limitation of the study is our use of snowball or chain referral

sampling method to collect data, which leads to 91% of our sample holding a bachelor’s

degree. Although snowball sampling is often applied when objects are not easily avail-

able or the focus of study is on a sensitive issue (Noy 2008), it is obviously a drawback

that research results may suffer by relatively greater homogeneity of participants.

Highly educated individuals may influence the future time perspective even experien-

cing the negative shocks, so the result may be difficult to generalize to different kinds

of population (Biernacki and Waldorf 1981).

Conclusion

This research responds to the call for study in career shocks using conservation of re-

sources theory (Akkermans et al. 2018), and separating future time perspective into

two separate dimensions (Rudolph et al., 2018; Cate and John 2007; Henry et al., 2017).

While negative career shocks may not directly motivate individuals to focus on oppor-

tunities, internal social capital could mediate the effect, with highly organizationally

embedded employees experiencing this indirect effect more strongly.

Appendix
Career shocks scale (Seibert et al. 2013)

1. Visible job success. (measuring positive career shocks, not used)

2. Quick raise or promotion. (measuring positive career shocks, not used)

3. Had a mentor or colleague that was important to you leave the company.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 12 of 17

4. Your organization went through a significant negative event such as a reduction-

in-workforce, bankruptcy, or major ethical scandal.

Items measuring internal social capital from political skill inventory (Ferris et al. 2005)

1. I spend a lot of time and effort at work networking with others.

2. I am good at building relationships with influential people at work.

3. At work, I know a lot of important people and am well connected.

4. I spend a lot of time at work developing connections with others. (not used

because of

relatively lower loading)

5. I am good at using my connections and network to make things happen at work.

(not used because of relatively lower loading)

6. I have developed a large network of colleagues and associates at work whom I can

call on for support when I really need to get things done. (not used because of

relatively lower loading)

In their paper, Ng and Feldman (2010a, 2010b) used 6 items in Political Skill Inventory

(Ferris et al. 2005) to measure internal social capital development behaviors. In this study,

we chose three items with higher loadings out of those six items to measure internal social

capital.

Global organizational embeddedness scale (Crossley et al. 2007)

1. I feel attached to this organization.

2. It would be difficult for me to leave this organization.

3. I’m too caught up in this organization to leave.

4. I simply could not leave the organization that I work for.

5. It would be easy for me to leave this organization.

(reverse coded)

6. I am tightly connected to this organization.

7. I feel tied to this organization. (not used because of semantic repetition)

Occupational future time perspective scale (Zacher and Frese 2009)

Focus on opportunities:

1. Many opportunities await me in my occupational future

2. I expect that I will set many new goals in my occupational future

3. My occupational future is filled with possibilities

Perceived remaining time:

1. Most of my occupational life lies ahead of me. (reverse coded)

2. My occupational future seems infinite to me. (reverse coded)

3. As I get older, I begin to experience time in my occupational future as limited.

(reverse coded)

Acknowledgements

Not applicable.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 13 of 17

Authors’ contributions

In preparing this manuscript, JF and ML worked together to propose the research topic and developed the theoretical
model. In addition, JF provided the preliminary research design, conducted the literature review, offered explanation
of the hypotheses, collected data and demonstrated the limitations and implications of this study. ML analysed the
data. WZ drafted the manuscript and improved the introduction and discussion sections dramatically. SL participated
in the discussion of the research model and helped to draft the manuscript, updated the literature and hypotheses
development. All authors read and approved the final manuscript.

Funding

No funding was received.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on
reasonable request.

Competing interests

The authors declare that they have no competing interests.

Received: 17 July 2019 Accepted: 29 November 2019

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage. https://doi.org/10.

1037/0021-9010.84.6.897.
Akkermans, J., Seibert, S. E., & Mol, S. T. (2018). Tales of the unexpected: Integrating career shocks in the contemporary careers

literature. SA Journal of Industrial Psychology, 44, 1–10. https://doi.org/10.4102/sajip.v44i0.1503.
Avanzi, L., Fraccaroli, F., Castelli, L., Marcionetti, J., Crescentini, A., Balducci, C., & van Dick, R. (2018). How to mobilize social

support against workload and burnout: The role of organizational identification. Teaching and Teacher Education, 69, 154–
167. https://doi.org/10.1016/j.tate.2017.10.001.

Avanzi, L., Schuh, S. C., Fraccaroli, F., & van Dick, R. (2015). Why does organizational identification relate to reduced employee
burnout? The mediating influence of social support and collective efficacy. Work and Stress, 29(1), 1–10. https://doi.org/
10.1080/02678373.2015.1004225.

Bagozzi, R. P., & Heatherton, T. F. (1994). A general approach to representing multifaceted personality constructs: Application
to state self-esteem. Structural Equation Modeling: A Multidisciplinary Journal, 1(1), 35–67. https://doi.org/10.1080/
10705519409539961.

Baruch, Y. (2004). Transforming careers: From linear to multidirectional career paths: Organizational and individual
perspectives. Career Development International, 9(1), 58–73. https://doi.org/10.1108/13620430410518147.

Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology,
5(4), 323–370. https://doi.org/10.1037/1089-2680.5.4.323.

Beach, L. R. (1990). Image theory: Decision making in personal and organizational contexts. Wiley. https://doi.org/10.1002/job.
4030130509.

Betsworth, D. G., & Hansen, J. I. C. (1996). The categorization of serendipitous career development events. Journal of Career
Assessment, 4(1), 91–98. https://doi.org/10.1177/106907279600400106.

Biernacki, P., & Waldorf, D. (1981). Snowball sampling: Problems and techniques of chain referral sampling. Sociological
Methods & Research, 10 (2), 141–163. https://doi.org/10.1177/004912418101000205.

Bright, J. E., Pryor, R. G., & Harpham, L. (2005). The role of chance events in career decision making. Journal of Vocational
Behavior, 66(3), 561–576. https://doi.org/10.1016/j.jvb.2004.05.001.

Brockner, J. (1992). The escalation of commitment to a failing course of action: Toward theoretical progress. Academy of
Management Review, 17(1), 39–61. https://doi.org/10.5465/AMR.1992.4279568.

Burton, J. P., Holtom, B. C., Sablynski, C. J., Mitchell, T. R., & Lee, T. W. (2010). The buffering effects of job embeddedness on
negative shocks. Journal of Vocational Behavior, 76(1), 42–51. https://doi.org/10.1016/j.jvb.2009.06.006.

Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge. https://
doi.org/10.4324/9780203807644.

Carstensen, L. L. (2006). The influence of a sense of time on human development. Science, 312(5782), 1913–1915. https://doi.
org/10.1126/science.1127488.

Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity.
American Psychologist, 54(3), 165. https://doi.org/10.1037//0003-066X.54.3.165.

Cate, R. A., & John, O. P. (2007). Testing models of the structure and development of future time perspective: Maintaining a
focus on opportunities in middle age. Psychology and Aging, 22 (1), 186–201. https://doi.org/10.1037/0882-7974.22.1.186.

Cattell, R. B., & Burdsal Jr., C. A. (1975). The radial parcel double factoring design: A solution to the item-vs-parcel controversy.
Multivariate Behavioral Research, 10(2), 165–179. https://doi.org/10.1207/s15327906mbr1002_3.

Chen, S., Westman, M., & Eden, D. (2009). Impact of enhanced resources on anticipatory stress and adjustment to new
information technology: A field-experimental test of conservation of resources theory. Journal of Occupational Health
Psychology, 14(3), 219–230. https://doi.org/10.1037/a0015282.

Cheng, C., Yang, L., Chen, Y., Zou, H., Su, Y., & Fan, X. (2016). Attributions, future time perspective and career maturity in
nursing undergraduates: Correlational study design. BMC Medical Education, 16 (1),26. https://doi.org/10.1186/s12909-
016-0552-1.

Collins, N. L., & Feeney, B. C. (2000). A safe haven: An attachment theory perspective on support seeking and caregiving in
intimate relationships. Journal of Personality and Social Psychology, 78(6), 1053–1073. https://doi.org/10.1037/0022-3514.78.
6.1053.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 14 of 17

Crossley, C. D., Bennett, R. J., Jex, S. M., & Burnfield, J. L. (2007). Development of a global measure of job embeddedness and
integration into a traditional model of voluntary turnover. Journal of Applied Psychology, 92(4), 1031–1042. https://doi.org/
10.1037/0021-9010.92.4.1031.

Diestel, S., & Schmidt, K. H. (2012). Lagged mediator effects of self-control demands on psychological strain and absenteeism.
Journal of Occupational and Organizational Psychology, 85(4), 556–578. https://doi.org/10.1111/j.2044-8325.2012.02058.x.

Ferris, G. R., Treadway, D. C., Kolodinsky, R. W., Hochwarter, W. A., Kacmar, C. J., Douglas, C., & Frink, D. D. (2005). Development
and validation of the political skill inventory. Journal of Management, 31, 126–152. https://doi.org/10.1177/
0149206304271386.

Forret, M. L., & Dougherty, T. W. (2004). Networking behaviors and career outcomes: Differences for men and women?
Journal of Organizational Behavior, 25, 419–437. https://doi.org/10.2307/4093697.

Frisch, J. U., Häusser, J. A., van Dick, R., & Mojzisch, A. (2014). Making support work: The interplay between social support and
social identity. Journal of Experimental Social Psychology, 55, 154–161. https://doi.org/10.1016/j.jesp.2014.06.009.

Froehlich, D. E., Beausaert, S., & Segers, M. (2016). Aging and the motivation to stay employable. Journal of Managerial
Psychology, 31(3), 756–770. https://doi.org/10.1108/JMP-08-2014-0224.

Fung, H. H., Lai, P., & Ng, R. (2001). Age differences in social preferences among Taiwanese and mainland Chinese: The role of
perceived time. Psychology and Aging, 16(2), 351–356. https://doi.org/10.1037//0882-7974.16.2.351.

Gorgievski, M. J., Halbesleben, J. R., & Bakker, A. B. (2011). Expanding the boundaries of psychological resource theories.
Journal of Occupational and Organizational Psychology, 84, 1–7. https://doi.org/10.1111/j.2044-8325.2010.02015.x.

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380. https://doi.org/10.1086/
225469.

Halbesleben, J. R. (2010). The role of exhaustion and workarounds in predicting occupational injuries: A cross-lagged panel
study of health care professionals. Journal of Occupational Health Psychology, 15(1), 1–16. https://doi.org/10.1037/
a0017634.

Halbesleben, J. R., & Wheeler, A. R. (2011). I owe you one: Coworker reciprocity as a moderator of the day-level
exhaustion-performance relationship. Journal of Organizational Behavior, 32, 608–626. https://doi.org/10.1002/
job.748.

Henry, H., Zacher, H., & Desmette, D. (2017). Future time perspective in the work context: a systematic review of quantitative
studies. Frontiers in Psychology, 8, Article 413. https://doi.org/10.3389/fpsyg.2017.00413.

Hirschi, A. (2010). The role of chance events in the school-to-work transition: The influence of demographic, personality and
career development variables. Journal of Vocational Behavior, 77, 39–49. https://doi.org/10.1016/j.jvb.2010.02.002.

Hobfoll, S. E. (1988). The ecology of stress. Washington, DC: Hemisphere Publishing Corp.
Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513–

524. https://doi.org/10.1037/0003-066X.44.3.513.
Holtom, B. C., Burton, J. P., & Crossley, C. D. (2012). How negative affectivity moderates the relationship between

shocks, embeddedness and worker behaviors. Journal of Vocational Behavior, 80(2), 434–443. https://doi.org/10.
1016/j.jvb.2011.12.006.

Holtom, B. C., & Inderrieden, E. J. (2006). Integrating the unfolding model and job embeddedness model to better
understand voluntary turnover. Journal of Managerial Issues, 18, 435–452. http://link.galegroup.com/apps/doc/
A158388761/GPS?u=wash_main&sid=GPS&xid=d427ed31.

Holtom, B. C., Mitchell, T. R., Lee, T. W., & Inderrieden, E. J. (2005). Shocks as causes of turnover: What they are and how
organizations can manage them. Human Resource Management, 44, 337–352. https://doi.org/10.1002/hrm.20074.

Hom, P. W., Lee, T. W., Shaw, J. D., & Hausknecht, J. P. (2017). One hundred years of employee turnover theory and research.
Journal of Applied Psychology, 102(3), 530–545. https://doi.org/10.1037/apl0000103.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new
alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118.

Kishton, J. M., & Widaman, K. F. (1994). Unidimensional versus domain representative parceling of questionnaire items: An
empirical example. Educational and Psychological Measurement, 54(3), 757–765. https://doi.org/10.1177/
0013164494054003022.

Kooij, D. T., Kanfer, R., Betts, M., & Rudolph, C. W. (2018). Future time perspective: A systematic review and meta-analysis.
Journal of Applied Psychology, 103(8), 867–893. https://doi.org/10.1037/apl0000306.

Kooij, D. T. A. M., Bal, P. M., & Kanfer, R. (2014). Future time perspective and promotion focus as determinants of
intraindividual change in work motivation. Psychology and Aging, 29, 319–328. https://doi.org/10.1037/a0036768.

Koopmann, J., Lanaj, K., Bono, J., & Campana, K. (2016). Daily shifts in regulatory focus: The influence of work events and implications
for employee well‐being. Journal of Organizational Behavior, 37(8), 1293–1316. https://doi.org/10.1002/job.2105.

Lang, F. R., & Carstensen, L. L. (2002). Time counts: Future time perspective, goals, and social relationships. Psychology and
Aging, 17, 125. https://doi.org/10.1037/0882-7974.17.1.125.

Larsen, R. J., & Ketelaar, T. (1991). Personality and susceptibility to positive and negative emotional states. Journal of
Personality and Social Psychology, 61, 132–140. https://doi.org/10.1037/0022-3514.61.1.132.

Lee, E. S., Park, T. Y., & Koo, B. (2015). Identifying organizational identification as a basis for attitudes and behaviors: A meta-
analytic review. Psychological Bulletin, 141(5), 1049–1080. https://doi.org/10.1037/bul0000012.

Lee, T. W., Burch, T. C., & Mitchell, T. R. (2014). The story of why we stay: A review of job embeddedness. Annual
Review of Organizational Psychology and Organizational Behavior, 1, 199–216. https://doi.org/10.1146/annurev-
orgpsych-031413-091244.

Lee, T. W., Hom, P. W., Eberly, M. B., Li, J. J., & Mitchell, T. R. (2017). On the next decade of research in voluntary employee
turnover. Academy of Management Perspectives, 31, 201–221. https://doi.org/10.5465/amp.2016.0123.

Lee, T. W., & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of
Management Review, 19, 51–89. https://doi.org/10.5465/amr.1994.9410122008.

Lee, T. W., Mitchell, T. R., Wise, L., & Fireman, S. (1996). An unfolding model of voluntary employee turnover. Academy of
Management Journal, 39, 5–36. https://doi.org/10.5465/256629.

Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question,
weighing the merits. Structural Equation Modeling, 9(2), 151–173. https://doi.org/10.1207/S15328007SEM0902_1.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 15 of 17

Liu, J., Kwan, H. K., Fu, P. P., & Mao, Y. (2013). Ethical leadership and job performance in China: The roles of workplace friendships
and traditionality. Journal of Occupational and Organizational Psychology, 86, 564–584. https://doi.org/10.1111/joop.12027.

Marsden, P. V., & Hurlbert, J. S. (1988). Social resources and mobility outcomes: A replication and extension. Social Forces,
66(4), 1038–1059. https://doi.org/10.1093/sf/66.4.1038.

Miller, M. J. (1983). The role of happenstance in career choice. Vocational Guidance Quarterly, 32, 16–20. https://doi.org/10.
1002/j.2164-585X.1983.tb01552.x.

Mitchell, T. R., Holtom, B. C., Lee, T. W., Sablynski, C. J., & Erez, M. (2001). Why people stay: Using job embeddedness to predict
voluntary turnover. Academy of Management Journal, 44(6), 1102–1121. https://doi.org/10.5465/3069391.

Mitchell, T. R., & Lee, T. W. (2001). The unfolding model of voluntary turnover and job embeddedness: Foundations for a
comprehensive theory of attachment. Research in Organizational Behavior, 23, 189–246. https://doi.org/10.1016/S0191-
3085(01)23006-8.

Ng, T. W., & Feldman, D. C. (2010a). The effects of organizational embeddedness on development of social capital and
human capital. Journal of Applied Psychology, 95(4), 696–712. https://doi.org/10.1037/a0019150.

Ng, T. W., & Feldman, D. C. (2010b). The impact of job embeddedness on innovation-related behaviors. Human Resource
Management, 49(6), 1067–1087. https://doi.org/10.1002/hrm.20390.

Ng, T. W. H., & Feldman, D. C. (2007). Organizational embeddedness and occupational embeddedness across career stages.
Journal of Vocational Behavior, 70(2), https://doi.org/10.1016/j.jvb.2006.10.002.

Noy, C. (2008). Sampling knowledge: The hermeneutics of snowball sampling in qualitative research. International Journal of
Social Research Methodology, 11(4), 327–344. https://doi.org/10.1080/13645570701401305.

Park, I. J., & Jung, H. (2015). Relationships among future time perspective, career and organizational commitment,
occupational self-efficacy, and turnover intention. Social Behavior and Personality: An International Journal, 43(9), 1547–
1561. https://doi.org/10.2224/sbp.2015.43.9.1547.

Pearlin, L. I., Menaghan, E. G., Lieberman, M. A., & Mullan, J. T. (1981). The stress process. Journal of Health and Social Behavior,
22(4), 337–356. https://doi.org/10.2307/2136676.

Petriglieri, J. L. (2011). Under threat: Responses to and the consequences of threats to individuals’ identities. Academy of
Management Review, 36(4), 641–662. https://doi.org/10.5465/amr.2009.0087.

Pfeffer, J. (1992). Managing with power. Boston: Harvard Business School Press.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models.

Behavior Research Methods, Instruments, & Computers, 36(4), 717–731. https://doi.org/10.3758/BF03206553.
Rudolph, C. W., Kooij, D. T., Rauvola, R. S., & Zacher, H. (2018). Occupational future time perspective: A meta-analysis of

antecedents and outcomes. Journal of Organizational Behavior, 39(2), 229–248. https://doi.org/10.1002/job.2264.
Seibert, S. E., Kraimer, M. L., Holtom, B. C., & Pierotti, A. J. (2013). Even the best laid plans sometimes go askew: Career self-

management processes, career shocks, and the decision to pursue graduate education. Journal of Applied Psychology,
98 (1), 169–182. https://doi.org/10.1037/a0030882.

Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). A social capital theory of career success. Academy of Management Journal,
44, 219–237. https://doi.org/10.2307/3069452.

Selenko, E., Mäkikangas, A., Mauno, S., & Kinnunen, U. (2013). How does job insecurity relate to self-reported job
performance? Analysing curvilinear associations in a longitudinal sample. Journal of Occupational and Organizational
Psychology, 86, 522–542. https://doi.org/10.1111/joop.12020.

Seta, J. J., Haire, A., & Seta, C. E. (2008). Averaging and summation: Positivity and choice as a function of the number and
affective intensity of life events. Journal of Experimental Social Psychology, 44(2), 173–186. https://doi.org/10.1016/j.jesp.
2007.03.003.

Slay, H. S., Taylor, M. S., & Williamson, I. O. (2004). Midlife transition decision processes and career success: The role of identity,
networks, and shocks. Austin: In annual meeting of the Academy of Human Resource Development http://citeseerx.ist.psu.
edu/viewdoc/download?doi=10.1.1.574.1046&rep=rep1&type=pdf.

Staw, B. M. (1981). The escalation of commitment to a course of action. Academy of Management Review, 6(4), 577–587.
https://doi.org/10.2307/257636.

Taber, B. J., & Blankemeyer, M. S. (2015). Time perspective and vocational identity statuses of emerging adults. The Career
Development Quarterly, 63(2), 113–125. https://doi.org/10.1002/cdq.12008.

Van Dick, R., Christ, O., Stellmacher, J., Wagner, U., Ahlswede, O., Grubba, C., et al. (2004). Should I stay or should I go?
Explaining turnover intentions with organizational identification and job satisfaction. British Journal of Management, 15(4),
351–360. https://doi.org/10.1111/j.1467-8551.2004.00424.x.

Vuori, V., & Okkonen, J. (2012). Knowledge sharing motivational factors of using an intra-organizational social media platform.
Journal of Knowledge Management, 16(4), 592–603. https://doi.org/10.1108/13673271211246167.

Wayne, S. J., Liden, R. C., Kraimer, M. L., & Graf, I. K. (1999). The role of human capital, motivation, and supervisor sponsorship
in predicting career success. Journal of Organizational Behavior, 20(5), 577–595. https://doi.org/10.2307/3100430.

Weikamp, J. G., & Göritz, A. S. (2016). Organizational citizenship behavior and job satisfaction: The impact of occupational
future time perspective. Human Relations, 69(11), 2091–2115. https://doi.org/10.1177/0018726716633512.

Weiss, H. M., & Cropanzano, R. (1996). Affective events theory: A theoretical discussion of the structure, causes and
consequences of affective experiences at work. Research in Organizational Behavior, 18, 1–74.

Wijayanto, B. R., & Kismono, G. (2004). The effect of job embeddedness on organizational citizenship behavior: The mediating
role of sense of responsibility. Gadjah Mada International Journal of Business, 6(3), 335–354. https://doi.org/10.22146/
gamaijb.5554.

Xanthopoulou, D., Bakker, A. B., Demerouti, E., & Schaufeli, W. B. (2009). Work engagement and financial returns: A diary study
on the role of job and personal resources. Journal of Occupational and Organizational Psychology, 82, 183–200. https://
doi.org/10.1348/096317908X285633.

Zacher, H., & de Lange, A. H. (2011). Relations between chronic regulatory focus and future time perspective: Results of a
cross-lagged structural equation model. Personality and Individual Differences, 50(8), 1255–1260. https://doi.org/10.1016/j.
paid.2011.02.020.

Zacher, H., & Frese, M. (2009). Remaining time and opportunities at work: Relationships between age, work characteristics,
and occupational future time perspective. Psychology and Aging, 24(2), 487–493. https://doi.org/10.1037/a0015425.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 16 of 17

Zacher, H., & Frese, M. (2011). Maintaining a focus on opportunities at work: The interplay between age, job complexity, and
the use of selection, optimization, and compensation strategies. Journal of Organizational Behavior, 32(2), 291–318.
https://doi.org/10.1002/job.683.

Zimmerman, B. K., Dormann, C., & Dollard, M. F. (2011). On the positive aspects of customers: Customer-initiated support and
affective crossover in employee–customer dyads. Journal of Occupational and Organizational Psychology, 84(1), 31–57.
https://doi.org/10.1111/j.2044-8325.2010.02011.x.

Zippay, A. (2001). The roles of social capital in reclaiming human capital: A Longitudinal study of occupational mobility
among displaces steelworkers. Journal of Sociology and Social Welfare, 28, 99.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Feng et al. Frontiers of Business Research in China (2020) 14:1 Page 17 of 17

© 2019. This work is published under
http://creativecommons.org/licenses/by/4.0/(the “License”). Notwithstanding

the ProQuest Terms and Conditions, you may use this content in accordance
with the terms of the License.

Abstract
Conceptual development and hypotheses development
Mediating influence of internal social capital
Moderating influence of organizational Embeddedness
Method
Sample and procedure
Measures
Negative career shocks
Internal social capital
Organizational embeddedness
Focus on opportunities
Control variables
Data analysis
Results
Descriptive statistics and correlations
Confirmatory factor analysis
Test of hypotheses
Discussion
Implications for theory development
Limitations and future research
Conclusion
Appendix
Career shocks scale (Seibert et�al. 2013)
Items measuring internal social capital from political skill inventory (Ferris et�al. 2005)
Global organizational embeddedness scale (Crossley et�al. 2007)
Occupational future time perspective scale (Zacher and Frese 2009)
Acknowledgements
Authors’ contributions
Funding
Availability of data and materials
Competing interests
References
Publisher’s Note

InternationalJournal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

185

THEORETICAL ANALYSIS OF MANAGING CORPORATE SOCIAL

RESPONSIBILITY IN DEVELOPING COUNTRIES

Huguette Bura Sifa
1

and Corneille Luboya Tshiunza
2

1 School of Economics, Management and Business Administration, Central China Normal University,

Wuhan, China (huguettebura@yahoo.com)

2. School of Education, Educational Economy and Management, Central China Normal University,

Wuhan, China (Corneilleluboya@outlook.fr)

Abstract

A Corporate Social Responsibility, generally noted by “CSR”, refers to a corporation’s initiatives to
assess and take responsibility for the company’s effects on environmental and social well-being. It
generally applies to efforts that go beyond what may be required by regulators or environmental
protection groups. Governments seeking to advance sustainable development are increasingly turning to
policies and strategies that encourage, support, mandate, or directly demonstrate more socially and
environmentally sound business practices. A central component of these policies involves promoting
increased transparency of economic activities. The purpose of this study is to analyze how companies i

n

developing countries manage their business processes to produce an overall positive impact on
society. This is to evaluate the sustainability, social impact and ethics, and done correctly should be
about core business and to determine how companies make their money, not just add-on extras such
as philanthropy. The documentary research is the most method used to conduct this study. The results
showed that CSR in developing countries is a rich and fascinating area of enquiry, which is
becoming ever more important in managing a CSR theory and practice. The findings also showed
that managing CSR in developing countries is a tremendous opportunity for improving knowledge
and getting a profoundly understanding about social responsibility of an organization or a corporate.

Key words: corporate social responsibility, ethics, stakeholders, shareholders, marketplace.

1. Introduction

Corporate social responsibility is a movement aimed at encouraging companies to be more aware of
the impact of their business on the rest of society, including their own stakeholders and the environment
(Financial Times Definition, 2018). Since many years ago, the social groups are confronted with several
problems that threaten the world till now and can lead it to the ruin. We can hold up as an example: the
corruption, the nepotism, the patronage, absence of democracy and fairness, the impunity, ethnical
conflicts, bad management of enterprises, fraud, theft, and so one. All these phenomena are based
generally on the good management of spending to realize and receipts to collect in order to improve the
living conditions of populations and to respond to their societal demands in the eyes of their degradation.
Each society needs more useful strategies and resources to reply on collective needs. This issue remains
difficult to reach for countries, commonly called “developing countries” that are very far from reaching
these objectives.

As the opening vignette illustrates, determining how to conduct business in a corporate appropriately
can be challenging. Wrong doing by businesses has focused public attention, managers and government
involvement to encourage more acceptable business conduct. Any business decision may be judged as
right or wrong, ethical or unethical, legal or illegal, responsible or not.

In this writing, the aim of this study is to analyze the social responsibility of managing corporate in
developing countries. This is to have a look at the role of ethics and social responsibility in business

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

186

decision making. The challenge for corporate social responsibility (CSR) in developing countries is
framed by a vision that was distilled in 2000 into the Millennium Development Goals ‘a world with less
poverty, hunger and disease, greater survival prospects for mothers and their infants, better educated
children, equal opportunities for women, and a healthier environment’ (UN, 2006, p.3). Unfortunately,
these global aspirations remain far from being met in many developing countries today.

This research is undertaken in three stages: First, making a state of the literature places related to this
study. This is to investigate whether any similar studies had been conducted before, determine the nature
of any existing documents and gain an overview of the main arguments. Second, data is collected in a
program drawing on the views of key commentators and practitioners and propose a set of indices for
CSR auditing. Finally, data analysis is conducted using an established scientific approach.

The methodology used as the basis of this study is the qualitative approach, which is defined as the
discovery of theory from data systematically obtained from social research (Glaser and Strauss 1967).
This method was chosen because of its capacity to generate theoretical explanations from largely
qualitative information of the sort captured from reports and other documents. It is also a robust scientifi

c

approach that provides results from diverse and unstructured data.

Therefore, to achieve this purpose, this study would like to answer the following main research
question: What is the role of business in tackling the critical issues of human development and
environmental sustainability in developing countries?

2. Critical analysis on Managing a corporate social responsibility

2.1.Conceptual framework of analysis

Corporate social responsibility (CSR) is a business approach that contributes to sustainable
development by delivering economic, social and environmental benefits for all stakeholders. The way it is
understood and implemented differs greatly for each company and country. Moreover, CSR is a very
broad concept that addresses many and various topics such as human rights, corporate governance, health
and safety, environmental effects, working conditions and contribution to economic development.

In fact, the broadest definition of CSR is concerned with what is or should be the relationship
between global corporations, governments of countries and individual citizens. More locally, this is
concerned with the relationship between a corporation and local society in which it resides or operates.
Another definition is concerned with the relationship between a corporation and its stakeholders.

There is no clear or agreed definition of Corporate Social Responsibility (CSR), so this raises the
question as to “what exactly can be considered to be corporate social responsibility.”

According to the European Commission (2002, p.347) manages CSR is “the responsibility of
enterprises for their impacts on society.” In other words, “…CSR is a concept whereby companies
integrate social and environmental concerns in their business operations and in their interaction with their
stakeholders on a voluntary basis.”

Carroll (1991) presented CSR as a multi-layered concept that consists of four interrelated aspects:
economic, legal, ethical and philanthropic responsibilities. For her, companies are created to provide
goods and services to the public and to make a profit. CSR is an equally contested concept (Moon,
2002b).

Whatever the definition is, the purpose of managing a CSR is to drive change towards sustainability.
Although some companies may achieve remarkable efforts with unique CSR initiatives, it is difficult to be
on the forefront on all aspects of CSR.

To begin with, it is worth clarifying the use of the terms developing countries and CSR. There is an
extensive historical and generally highly critical debate in the development literature about the
classification of countries as developed and less developed or developing. Without reviving that debate
here, suffice to say that the study use developing countries because it is still a popular term used to
collectively describe nations that have relatively lower per capita incomes and are relatively less
industrialized.

From the outset , the study uses CSR in developing countries to represent ‘the formal and informal

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

187

ways in which business makes a contribution to improving the governance, social, ethical, labor and
environmental conditions of the developing countries in which they operate, while remaining sensitive to
prevailing religious, historical and cultural contexts’ (Visser et al., 2007). Considering this, the example
below provides good practices on one aspect of CSR environmental sustainability.

Figure 1: Diagram of Managing a corporate social responsibility

Source: Mallen Baker on CSR (2004).

Social responsibility has become an important topic on the corporate agenda in the light of corporate
scandals, concerns about globalization and a growing mistrust of business. It pays attention to all
stakeholders who are affected by their actions. Today, special interest groups continue to be one of the
largest stakeholders concerns that companies face. Environmental responsibility has become a primary
issue as both business and the public acknowledge the damage that has been done to our natural
environment. The most important stakeholders known are the government and the community, which
have become increasingly important in recent years. On one hand, most corporations exist only under the
proper charter and license, and operate within the limits of safety laws, environmental protection
requirements, antitrust regulations, antibribery legislation and other types of laws and regulations in the
government sector. On the other hand, the community includes local government, the natural and physical
environments and the quality of life for residents.

Thus, companies need to answer to two aspects of their operations: (i) the quality of their
management both in terms of people and processes (the inner circle), (ii) the nature of, and quantity of
their impact on society in the various areas.

Outside stakeholders are taking an increasing interest in the activity of the company. Most look to
the outer circle what the company has actually done, good or bad, in terms of its products and services, in
terms of its impact on the environment and on local communities, or in how it treats and develops its
workforce. Out of the various stakeholders, it is financial analysts who are predominantly focused as well
as past financial performance on quality of management as an indicator of likely future performance.

2.2.Overview on CSR in the world

2.2.1. Dimensions of CSR
Business and academic researchers have shown increasing levels of interest in Corporate

Social

Responsibility (CSR) during recent years (Maignan, 2002). The theme of environmental and social
responsibility appears in a number of political and legal documents and is gaining ever-greater
importance at the international level. Today, corporate leaders face a dynamic and challenging task in
attempting to apply societal ethical standards to responsible business practice. Companies, especially
those operating in global markets, are increasingly required to balance the social, economic and
environmental components of their business, while building shareholder value.

Management is responsible for creating and sustaining conditions in which people are likely to
behave themselves. Managers must take active steps to ensure that the company stays on an ethical

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

188

footing. This management should consider the Ethical and social responsibility business practices. These
depend on individual managers and the organization’s values, policies, and practices. So, managers must
use the three pillars that support an ethical organization: ethical individuals, ethical leadership and
organizations, structures and systems.

The socio economic view stated that management’s social responsibility of a corporate goes beyond
making: (i) profits to include protecting and improving society’s welfare, (ii) corporations are not
independent entities responsible only to stockholders: complex set of goals, (iii) firms have a moral
responsibility to larger society to become involved in social, legal and political issues, (iv) to do the right
thing and (v) the myth of shareholder capitalism.

The management of CSR covers a wide range of issues which are ambiguous as to what is right or
wrong. What about two companies engaged in intense competition? Is it socially responsible for a strong
company to drive a weak company out of business? A company’s environmental impact must also be
taken in consideration. The table below presents some arguments “for” and “against” social
responsibility:

Table 1: Arguments for and against social responsibility in an organization

Arguments “for” Social Responsibility Arguments “against” Social Responsibility

Public expectation Violation of profit maximization
Long-run profits Dilution of purpose

Public image Costs
Better environment Too much power

Government regulation Lack of skills
Responsibility and power Lack of accountability

Stockholder interest
Possession of resources
Prevention over cures

Source: Author adapted from Maignan, 2002
In the visualization of the above table, the main concern of this point is to determine whether social

responsibility in managing a corporate pays or not. The following reasons below explain the advantages
and disadvantages of driving a social responsibility in a business company: (i) positive relationship
between social involvement and the economic performance of firms, but the (ii) difficulties in defining
and measuring “social responsibility” and “economic performance raise issues of validity and causation in
the studies, (iii) mutual funds using social screening in investment decisions slightly outperformed other
mutual funds, (iv) firm’s social actions do not harm its long-term performance and (v) align values and
competences= social responsibility enlightened self-interest. Doing well by doing good (Michael Porter).
This means that “managing social responsibility in an organization” implies:

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

189

Figure 2: Managing Social Responsibility paths

Source: Author adapted from Maignan, 2002.

2.2.2. Corporate Social Responsibility Audit and its Steps

Many successful companies have become world-renowned for incorporating social causes and social
initiatives into their cultures, their values, and business strategies. Increased customer preference for
social responsibility points to the importance of understanding how this type of philosophy can enhance
your business. The audit helps to measure the company’s actual social performance against the social
objectives it has set for itself. In other words, “Is your company a good global citizen? How do you know?
What can you do to improve your positioning?” This is to evaluate the integrating business strategy and
corporate social responsibility contributes to: (i) positive brand awareness, (ii) increased

employee

satisfaction, (iii) reduced operating costs, (iv) improved community relations and (v) corporate
accountability. This means that corporate social audit is: 1. Tool for the evaluation of social responsibility
effectiveness; 2. Formal and thorough analysis and 3. Conducted by task force.

When making payroll and finding your next customer are top priorities, it may at times seem
difficult, if not impossible, to focus on your corporate social responsibilities. But there is no better time to
integrate a socially responsible corporate culture into your organization than right now. This is especially
true in early-stage companies and start-ups, when business practices and organizational norms are just
being formed.

In other words, the major perception of CSR is that it can be an excellent tool for enhancing the
legitimacy of the firm among its stakeholders and the development of a positive corporate image. A key
vehicle for enhancing corporate image is the social report (Hess 1999). The value of the social report is
perceived as residing in the creation of social transparency as well as in institutionalizing responsible
decision-making and creative thinking in management. Effective development of social reporting can be
seen in the recent success of non-mandatory environmental auditing.

Building on this progress, Hess (1999) argues that there is a need to establish an audit system that
includes all aspects of a firm’s social performance. On the evidence discovered to date in the literature,
CSR seems to be perceived by many as the social strand of sustainable development, including the World
Business Council for Sustainable development, and the European Parliament. However, there is far less
agreement regarding its measurement. The literature review indicates that developing an applied CSR

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

190

auditing procedure will be a challenging task. This is mainly due to the lack of formal study of the topic,
despite the widespread debate it has engendered. However, several current measurement procedures for
CSR exist, which gives a promising indication that there is sufficient experience to develop appropriate
methods and indices for a comprehensive auditing system. Chronologically, this study consists of: (i)
define social goals, (ii) analyze resources devoted to each goal, (iii) determine degree of achievement for
each goal and (iv) make recommendations for the future.

2.3.Overview on Managing Corporate Social Responsibility in developing countries

The rationale for focusing on CSR in developing countries as distinct from CSR in the developed

world is fourfold: (1) Developing countries represent the most rapidly expanding economies, and hence

the most lucrative growth markets for business (IMF, 2006); (2) Developing countries are where the

social and environmental crises are usually most acutely felt in the world (WRI, 2005; UNDP, 2006); (3)

Developing countries are where globalization, economic growth, investment, and business activity are

likely to have the most dramatic social and environmental impacts (both positive and negative) (World

Bank, 2006); (4) Developing countries present a distinctive set of CSR agenda challenges which are

collectively quite different to those faced in the developed world.

2.3.1. Classification of literature on CSR in developing countries

In part, this reflects the fact that corporate social responsibility is the preferred term in the literature

to describe the role of business in developing countries, as opposed to, say, business ethics, corporate

citizenship, corporate sustainability, or stakeholder management. More than this, however, social issues

are generally given more political, economic, and media emphasis in developing countries than

environmental, ethical, or stakeholder issues (Schmidheiny, 2006). And there is also still a strong

emphasis on the philanthropic tradition in developing countries, which is often focused on community

development (figure 5 et 6).

Source: Author adapted from World Bank, 2006.

Lockett et al. (2006) also classify CSR papers by epistemological approach and find a roughly even split

between theoretical and empirical research, which is also the case in the literature on CSR in developing

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

191

countries, although the latter has a slight weighting towards empirical work. What is interesting is that,

whereas Lockett et al. (2006) find that 89%of theoretical CSR papers are non-normative, in the CSR in

developing countries literature; the balance is far more evenly split. This is largely due to the relatively

large number of papers on the role of business in development, which tend to adopt a normative, critical

perspective (Blowfield and Frynas, 2005).

Figure 7: Global context of CSR in developing countries

By analysis level

Source: Author adapted from World Bank, 2006.

In terms of empirical research, there are also differences. According to Lockett et al. (2006), the

CSR literature is dominated by quantitative methods (80%). In contrast, CSR papers on developing

countries are more likely to be qualitative.

There is very little empirical research on the nature and extent of CSR in developing countries. One

notable exception is Baskin’s (2006) research on the reported corporate responsibility behavior of 127

leading companies from 21 emerging markets across Asia, Africa, Latin America, and Central and Eastern

Europe, which he compares with over 1,700 leading companies in high-income OECD

countries.

2.3.2. Current trends in CSR

Corporate reporting whether mandated or voluntary on environmental, social, labor and human

rights issues is a relatively new phenomenon. While a small number of firms have irregularly published

information on their nonfinancial performance, more systematic and standardized systems of social and

environmental reporting only emerged in the late-1980s and early-1990s.

Since the 1980s, governments, firms, and NGOs around the world have developed a wide range of

reporting systems with goals as diverse as reducing pollution, mitigating health and safety risks,

spotlighting (and thus rooting out) corruption, improving public service delivery, and protecting civil

rights. With each new initiative in public reporting, public demands for fuller information and a deeper

“right-to-know” appear to solidify.

These initiatives have been driven by a range of pressures and demands from: consumers, NGOs,

unions, investors, governments, community members, and firms themselves.

2.3.3. Drivers of CSR in developing countries

There are several types of CSR’ drivers in developing countries, regrouped in two main categories

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

192

such as:

1. Internal drivers

These are : (i) the Political reform. The CSR in developing countries cannot be divorced from the

socio-political reform process, which often drives business behavior towards integrating social and ethical

issues. (ii) The Crisis response can be analyzed by various kinds of crises associated with developing

countries. These often have the effect of catalyzing CSR responses. These crises can be economic, social,

environmental, health-related, or industrial. Catastrophic events with immediate impact are often more

likely to elicit CSR responses, especially of the philanthropic kind. The corporate response to the Asian

tsunami is a classic case in point (Fernando, 2007). However, industrial accidents may also create

pressure for CSR. (iii) The Cultural tradition: many believe CSR is a Western invention (and this may

be largely true in its modern conception). CSR in developing countries draws strongly on deep-rooted

indigenous cultural traditions of philanthropy, business ethics, and community embeddedness. Indeed,

some of these traditions go back to ancient times. (iv) the Socioeconomic priorities: CSR in developing

countries is most directly shaped by the socio-economic environment in which firms operate and the

development priorities this creates. (v) the Governance gaps: CSR as a form of governance or a response

to governance challenges is discussed elsewhere in this book (Levy and Kaplan, Chapter 19). However, of

particular relevance for developing countries is the fact that CSR is often seen as a way to plug the

‘governance gaps’ left by weak, corrupt, or under-resourced governments that fail to adequately provide

various social services (housing, roads, electricity, health care, education, etc.). This as part of a wider

trend in developing countries with weak institutions and poor governance, in which responsibility is often

delegated to private actors, be they family, tribe religion, or, increasingly, business. Furthermore, ‘as

many developing country government initiatives to improve living conditions falter, proponents of [CSR

and bottom of the pyramid] strategies argue that companies can assume this role’. The Market access:

The flipside of the socio-economic priorities driver is to see these unfulfilled human needs as an untapped

market. This notion underlies the now burgeoning literature on ‘bottom of the pyramid’ strategies, which

refer to business models that focus on turning the four billion poor people in the world into consumers

(Prahalad and Hammond, 2002; London and Hart, 2004; Rangan et al., 2007). As study has previously

noted, this straying of business into the development arena is not without its critics or problems

(Hardcourt, 2004). CSR may also be seen as an enabler for companies in developing countries trying to

access markets in the developed world.

2. External drivers

These are (i) the International standardization: Despite the debate about the Western imposition of

CSR approaches on the global South, there is ample evidence that CSR codes and standards are a key

driver for CSR in developing countries. Codes are also frequently used as a CSR response in sectors that

are prevalent in developing countries, such as horticulture (Dolan and Opondo, 2005), cocoa (Schrage and

Ewing, 2005), and textiles (Kaufman et al., 2004), as well as to deal with pressing social issues in

developing countries, such as child labor (Kolk and Van Tulder, 2002) or the role of women in the

workplace (Prieto-Carron, 2004). Often, CSR is driven by standardization imposed by multinationals

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

193

striving to achieve global consistency among its subsidiaries and operations in developing countries; (ii)

The Supply chain: another significant driver for CSR in developing countries, especially among small

and medium-sized companies, is the requirements that are being imposed by multinationals on their

supply chains. This trend began with various ethical trading initiatives (Blowfield, 2003, 2004), which led

to the growth of fair trade auditing and labeling schemes for agricultural products sourced in developing

countries (Dolan and Opondo, 2005; Schrage and Ewing, 2005). Allegations of poor labor conditions and

human rights abuses in several high profile multinational supply chains in the sporting and clothing

sectors were also a significant catalyst for greater attention to CSR requirements (Hussain-Khaliq, 2004;

Kaufman et al., 2004; Nielsen, 2005). One response has been the development of certifiable standards

like SA 8000, which is now widely used as a screening mechanism for multinationals in selecting their

suppliers in developing countries (Kolk and Van Tulder, 2002). Major change has also been achieved

through sector-based initiatives such as the Forest Stewardship Council for sustainable forestry and the

Marine Stewardship Council for sustainable fishing. More recently, this driver has been scaled up due to

the so called ‘Wal-Mart effect’ whereby major global and national retailers are committing to promoting

sustainability and responsibility through their suppliers (Johnson, 2004). (iii) the Investment incentives:

the belief that multinational investment is inextricably linked with the social welfare of developing

countries is not a new phenomenon (Gabriel, 1972). However, increasingly these investments are being

screened for CSR performance. Hence, socially responsible investment (SRI) is becoming another driver

for CSR in developing countries. As one indicator of this, Baskin (2006) notes that approximately 8% of

emerging market companies on the Dow Jones World Index are included in the Dow Jones Sustainability

Index, compared with around 13% of high-income companies. Exchange also launched its own tradable

SRI Index, the first of its kind in an emerging market (Sonnenberg et al., 2004). and (iv) the Stakeholder

activism: in the absence of strong governmental controls over the social, ethical, and environmental

performance of companies in developing countries, activism by stakeholder groups has become another

critical driver for CSR. Lund-Thomsen (2004) describes this as ‘an outcome of micro-level struggles

between companies and communities over the distribution of social and environmental hazards which are

created when global political and economic forces interact with local contexts around the world’ (p. 106).

In developing countries, four stakeholder groups emerge as the most powerful activists for CSR,

namely development agencies (Jenkins, 2005), trade unions (Kaufman et al., 2004), international

NGOs

(Christian Aid, 2005), and business associations (WBCSD, 2000). These four groups provide a platform

of support for local NGOs, which are not always well developed or adequately resourced to provide

strong advocacy for CSR. The media is also emerging as a key stakeholder for promoting CSR in

developing countries (Vivarta and Canela, 2006). Stakeholder activism in developing countries takes

various forms, such as civil regulation, litigation against companies, and international legal instruments.

2.3.4. Metric aspects of CSR in developing countries

1. Meaning of Metric aspects of CSR

Clark et al. (1975) stated that the attraction of CSR, as defined, is that of a systems approach which states

that the problem is defined and the systems boundary delineated so that all important influences on

resolving the problem are taken into consideration to the issue of business in society. With hundreds of

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

194

corporation now producing reports, a wide range of laws being implemented around the world, and

dozens of non-governmental initiatives on transparency and reporting emerging, there is staggering

variation in what is reported, in what forms, and for which audiences.

The definition that is most appealing is the stakeholder definition, as put forward by Hopkins: “CSR is

concerned with treating the stakeholders of the firm ethically or in a socially responsible manner.

Stakeholders exist both within a firm and outside. The aim of social responsibility is to create higher and

higher standards of living, while preserving the profitability of the corporation, for its stakeholders both

within and outside the corporation”. (Hopkins, 2003). Indeed, this definition begs the question what is

meant by ‘ethical’ and what is meant by ‘stakeholder’.

On one hand, this study defined corporate social responsibility (CSR) and, on the other hand, it sets up a

framework to measure it. To date, the measurement systems used and the various concepts of CSR have

no systematic basis. Indicators seem to be chosen on the whim of the moment. However, at least some

data now exist to measure progress on social aspects of corporate behavior. In fact, it is even possible to

use some of the available data that companies now make available in order to hazard a guess to whether

CSR is getting better or worse.

Unfortunately, the measurement systems used (of CSR, corporate responsibility or corporate

sustainability or business ethics or business in society or corporate citizenship) have no systematic

conceptual basis, rarely define concepts and choose indicators based on the whim of the moment. On the

other hand, at least some data now exist to measure progress on social aspects of corporate behavior.

In fact, the measurement of CSR has much improved since the late 1990s, as purported by Hopkins

(1997). It is even possible to use some of the data that companies now make available to hazard a guess as

to whether CSR is getting better or worse. However, firstly, it is important to have a look at what is meant

by a conceptual framework and, then, examine some of the major indicator sets in some detail.

2. Major indicator sets of CSR measurement

The Global Reporting Initiative “GRI” carried out an extensive consultation of specialists to define

indicators to measure progress on social reporting. It recognizes that developing a globally accepted

reporting framework is a long-term endeavor. It notes that, in comparison, financial reporting is well over

half a century old and still evolving amidst increasing public attention and scrutiny. The methodology is

extensively and clearly presented in their report. In fact, the GRI uses the term ‘sustainability reporting’

synonymously with citizenship reporting, social reporting, triple-bottom line reporting and other terms

that encompass the economic, environmental, and social aspects of an organization’s performance.

The table 2 below summarizes the main indicator systems and the study takes Cisco Company as a

case study example. It is not easy to get in behind the methodologies and indicator sets used by analysts

and one can wonder what is really being measured.

Table 2: Main indicator systems of CSR measurement “Workplace, Diversity and Social impact

indicators”

Indicat

ors

FY05 FY06 FY07 FY08 FY09

WORKPLACE

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

195

Employee

satisfaction

Percentage of

employee who

agreed with seven

statements about

Cisco as a place to

work (average)

81% 85% 86% 87% 90%

Voluntary

employee

attrition

Total voluntary

attrition as

percentage of

ending headcount

4.59% 5.45% 4.52% 5.01% 3.22%

Health and

Safety

(operations

only US and

Canada)

Number of nonfatal

injuries and

illnesses

129 107 93 137 145

DIVERSITY

Women Women as

percentage of

total global

employees

21.8% 22.1% 23% 23.5% 23.4%

Women in

VP positions

or above as

percentage of

global VP

and above

employees

13.2% 14.0% 12.7% 15.5% 15.5%

Ethnic

minorities

(US only)

Ethnic

minorities as

percentage of

total US

employees

42.3% 42.8% 43.7% 44.7% 45.6%

Ethnic

minorities in

VP positions

and above as

percentage of

total US. VP

and above

17.6% 17.5% 15.6% 22.2% 20.8%

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

196

employees

SOCIAL IMPACT

Social

investment

Total corporate

wide and

foundation cash

and in-kind

contributions

$65

million

$115.5

millio

n

$116.8

million

$92

million

$128.6

million
Employee

volunteerism

Number of

active students

in

Cisco

networking

academy

courses

235,00

0

160,0

00

130,000 88,870 78,000

Cisco
networking
academy

Cisco leaders

who share their

expertise with

nonprofit

organizations

596,84

0

597,0

85

637,304 716,936 810,000

Leadership

fellows

Number of

countries or

regions where

Cisco currently

invests or

manages

programs

5 8 17 20 13

Social and

economic

investment

Significant

collaborations

with corporate

partners,

nonprofits and

NGOs

160 160+ 160+ 160+ 165+

Strategic

partners

31 36 34 41 58

Source: Corporate Social Responsibility Report (2009), “CSR Key Performance Indicators”, Cisco

Systems, Inc.

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

197

Table 3: Main indicator systems of CSR measurement “Environmental management; GHG

emissions; energy and electricity usage; product return and recycling; and water consumption

indicator”

Indicators FY06 FY07 FY08 FY09

ENVIRONMENTAL MANAGEMENT

Number of Cisco sites with ISO

14001 EMS certification

19 25 25 26

Employee base covered by ISO

14001 EMS certification

75% 73% 71% 68%

GHG EMISSIONS

Total gross GHG emissions:

Scope 1 (metric tonne CO2 c)

27,586 52,496 52,084 53,216

Total gross GHG emissions:

Scope 2 (metric tonne CO2 c)

317,666 467,478 550,312 579,183

Total contractual GHG emissions:

Scope 2 (metric tonne CO2 c)

316,893 403,188 310,961 226,733

Total air travel GHG emissions:

Scope 3 (metric tonne CO2 c)

190,940 205,797 197,872 115,995

Change in air travel GHG emissions

from FY06 (CGI global goal: 10%

absolute reduction against FY06

baseline)

+8% +4% +3%

Total contractual GHG emissions:

Scope 1, 2 and 3 1 metric tonne CO2

c

535,419 661,483 560,917 395,944

Change in Scope 1, 2 and 3 from

FY07 (EPA global 26% absolute

reduction against CY07 baseline)

– – -15% -40% (goal

year is

2012)

ENERGY AND ELECTRICITY USAGE

Energy usage (GWh) 889
tc

1281 1438 1507

Electricity usage (GWh) 749
tc

1053 1203 1275

PRODUCT RETURN AND RECYCLING

Product return (million pounds) – – 22.1 23.6

Materials to landfill (percent of

returned product not reused or

recycled)

– – 0.46% 0.44%

WATER CONSUMPTION

Total water consumption (m
3
) Not

available

1,726,618 1,570,831 1,654,030

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

198

Source: Corporate Social Responsibility Report (2009), “CSR Key Performance Indicators”, Cisco
Systems, Inc.

Although data are not generally available for many companies at once individual companies often

present comprehensive sets no consistent pattern of data collection and presentation has emerged. As the

CSR community has become more watchful and social investment funds more demanding, the need for

an overall index of progress on CSR has emerged. Several of the above-mentioned data systems have

attempted to provide indices and rankings of companies.

Initial attempts to measure progress on CSR based upon these indices have also emerged. However,

the indices that have emerged measure averages across companies. And, as noted in this paper,

consistency of application remains a problem. Moreover, the challenge that is more and more being

presented is how to embed the ideas of CSR throughout an organization. This is the problem that many

companies face. It is possible to obtain indicators that show a good record ‘on average’ but difficult to

embed the ideas of CSR throughout an organization and no one to date has produced disaggregated

indicators across the company. The lack of indicators of a consistent and disaggregated level leads to poor

monitoring and evaluation systems. That is probably why scandals will continue to erupt in supposedly

‘clean’ organizations.

For organizations to have relatively good data on the economic aspects but very poor information

on the social dimensions implies that the basic conceptual model has been weak. Hence, for the future, a

better model of social data, to be based upon hard or interval scale data is a necessary requisite. Much of

today’s information is founded upon weaker nominal or, at best, ordinal scale data and the proposed

framework is no exception. Therefore, in order to ensure the same type of robust yardsticks found in

economics, such as profit, sales, costs and so on though problems can arise with these it is important to

develop, through a significant effort for the social arena, new conceptual models from which harder data

can be derived. For corporate social responsibility, it is still the early days of relevant performance

measurement and ‘metrics’ in societal terms.

2.4.Challenges of CSR in developing countries

There are a number of major challenges to making CSR reporting effective. Questions remain in

different sectors and countries on what to report, in what form, to what level of detail, to what audiences,

and for what uses. There are also weaknesses and problems with current systems of CSR reporting, and

important barriers to expanding public disclosure systems around the world. These include problems of: (i)

metrics and Materiality; (ii) timeliness and Usefulness of Information; (iii) incentives to Disclose; (iv)

supply Chain Monitoring; (v) costs to Information Producers and Users; and (vi) analyzing and

Translating Information for end users.

3. Theoretical and empirical Evidences of CSR in developing countries

3.1.Theoretical model of CSR in developing countries

Indeed, taking into account two main variables of this study (CSR and developing countries), the

study proposed a theoretical model adapted to these two variables. This model is used to analyze the

management of CSR in developing countries as a tools and strategies of sustainable development and also

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

199

to the data available to meet the concerns of the study. Thus, the theoretical model proposed by Carroll

could be presented as the figure below is presented. This consists of four-part model construct that can be

useful to look at how CSR is manifested in a developing country context:

Figure 9: Model construction of CSR in developing countries (Carroll, 1991)

Source: Author adapted from Carroll, 1991

3.1.1. Economic responsibilities

It is well known that many developing countries suffer from a shortage of foreign direct investment,

as well as from high unemployment and widespread poverty. It is no surprise, therefore, that the economic

contribution of companies in developing countries is highly prized, by governments and communities

alike. This should not be seen in a negative light, but rather as a more development-oriented approach to

CSR that focuses on the enabling environment for responsible business in developing countries and that

brings economic and equity aspects of sustainable development.

Hence, in developing countries, CSR tends to stress the importance of ‘economic multipliers’,

including the capacity to generate investment and income, produce safe products and services, create jobs,

invest in human capital, establish local business linkages, spread international business standards, support

technology transfer and build physical and institutional infrastructure (Nelson, 2003).

For this reason, companies that operate in developing countries increasingly report on their

economic responsibilities by constructing ‘economic value added’ statements. It is worth re-emphasizing

as a caveat that economic responsibility has two faces economic contribution on the one side and

economic dependence on the other.

When communities or countries become overly dependent on multinationals for their economic

welfare, there is the risk of governments compromising ethical, social, or environmental standards in

order to retain their investment, or suffering huge social disruption if those businesses do decide to

disinvest.

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

200

3.1.2. Philanthropic responsibilities

Although philanthropy generally gets an even higher priority as a manifestation of CSR,

philanthropic responsibility tends more often to be more compulsory via the legal framework than

discretionary acts of successful companies or rich capitalists as USA. This is a result of strong indigenous

traditions of philanthropy in developing countries. There are several other reasons as well:

Firstly, the socio-economic needs of the developing countries in which companies operate are so

great that philanthropy is an expected norm it is considered the right thing to do by business.

Secondly, companies realize that they cannot succeed in societies that fail, and philanthropy is seen

as the most direct way to improve the prospects of the communities in which their businesses operate. For

example, the HIV/AIDS disease is a case in point, where the response by business is essentially

philanthropic (it is not an occupational disease), but clearly in companies’ own medium- to long-term

economic interest.

Thirdly, over the past 50 years, many developing countries have become reliant on foreign aid or

donor assistance. Hence, there is often an ingrained culture of philanthropy.

And a final reason for developing countries’ prioritization of philanthropy is that they are generally

still at an early stage of maturity in CSR, sometimes even equating CSR and philanthropy, rather than

embracing the more embedded approaches now common in developed countries.

3.1.3. Legal responsibilities

In developing countries, legal responsibilities generally have a lower priority than in developed

countries. This does not necessarily mean that companies flaunt the law, but there is far less pressure for

good conduct. This is because, in many developing countries, the legal infrastructure is poorly developed,

and often lacks independence, resources, and administrative efficiency.

Many developing countries are also behind the developed world in terms of incorporating human

rights and other issues relevant to CSR into their legislation (Mwaura 2004). Admittedly, there are

exceptions and some developing countries have seen significant progress in strengthening the social and

environmental aspects of their legislation (Visser, 2005b). However, government capacity for enforcement

remains a serious limitation, and reduces the effectiveness of legislation as a driver for CSR.

Hence, several scholars argue that tax avoidance by companies is one of the most significant

examples of irresponsible business behavior in developing countries, often contradicting their CSR claims

of good conduct (Christensen and Murphy, 2004).

3.1.4. Ethical Responsibilities

In developing countries, however, ethics seems to have the least influence on the CSR. This is not to

say that developing countries have been untouched by the global trend towards improved governance

(Reed, 2002). For example, the 1992 and 2002 King Reports on Corporate Governance in South Africa

have both led the world in their inclusion of CSR issues (IoD, 1992, 2002). On one hand, the 1992 King

Report was the first global corporate governance code to talk about ‘stakeholders’ and to stress the

importance of business accountability beyond the interests of shareholders. On the other hand, the 2002

revised King Report was the first to include a section on ‘integrated sustainability reporting’, covering

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

201

social, transformation, ethical, safety, health, and environmental management policies and practices.

This progress is certainly encouraging, but in general, it is still the exception rather than the rule.

For instance, in “Transparency International’s annual Corruption Perception Index and Global Corruption

Barometer”, developing countries usually make up the bulk of the most poorly ranked countries.

Furthermore, survey respondents from these countries generally agree that corruption still affects business

to a large extent. The World Bank’s (2005) Investment Climate Survey paints a similar picture. For

example, the corruption in developing countries has been the “UK-led Extractive Industries Transparency

Initiative (EITI)”, which aims to increase transparency over payments by companies to governments and

government-linked entities, as well as transparency over revenues by those host country governments.

This is clearly a step in the right direction, but the refusal of countries like Angola to even

participate shows that there is still a long way to go in embedding ethical responsibilities in developing

countries.

3.2.Government implication on CSR in developing countries

To date, CSR in developing countries has largely been driven from the north, often by large

multinational firms, private investors, or non-governmental organizations. Nonetheless, there are

important roles for governments, and particularly developing country governments, to play in further

advancing reporting systems. The World Bank has previously grouped government roles in supporting

corporate social responsibility into five categories of action: mandating, facilitating, partnering, endorsing,

and demonstrating.

Each of these strategies of action can support improvements of CSR in developing countries.

Governments, and their citizens, however, must decide how they can most effectively support an

environment for socially responsible business, and specifically advance CSR reporting.

3.2.1. Pilot project on CSR in developing countries

There is clear potential for government action, particularly in developing countries, to advance and

strengthen CSR reporting. However, in thinking about designing an appropriate and effective disclosure

system in a developing country, it is also critical to recognize that there are no perfect systems, no easily

replicable programs, and no one-size-fits-all standards for reporting.

By starting with a small set of core indicators, verifying that they are material to stakeholders,

evaluating uses of the information, and soliciting feedback on the quality of the data, it would be possible

to gradually expand and deepen CSR indicators to include sector specific issues. By having reporting be

driven by local concerns and capacities, it would also be possible to gradually connect to and compare

against global reporting schemes.

Government agencies and NGOs could play a key role in verifying CSR reporting information in

developing countries, and gradually working to improve the credibility and accountability of reporting.

Finally, a government agency could work to aggregate data, and to produce a national CSR report.

This information would support future comparisons of country-level performance on CSR issues. The

program could also help local firms establish and demonstrate their social and environmental performance,

and facilitate socially and environmentally responsible firms connecting into high value supply chains.

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

202

Nowadays, governments take steps to advance CSR in developing countries or to experiment with

reporting as strategy of governance and economic development. This study is meant as a starting point for

thinking about steps needed to pilot test CSR reporting in a developing country. Countries interested in

CSR reporting might: (i) Interview local stakeholders and investors about the information: they need to

make critical decisions; (ii) establish a central coordinating office to set guidelines for reporting, then

collect, collate, quality check, and compare information on facility performance; (iii) require firms to

publicly disclose locations of factories; (iv) require firms to annually report performance criteria in a

standardized format; (v) establish a central database accessible over the internet which would contain

performance information on factories and simple means for comparing firms along selected criteria, such

as wages, health and safety, labor practices, environmental performance, etc.; (v) create mechanisms for

public comparison of firm performance; (vi) publish lists of “best practices” and the firms that employ

them; (vi) publish a CSR sourcing book of leading local firms and distribute this to multinational

corporations, investors and trade associations for assistance in matching MNCs with local suppliers that

meet their CSR standards; (vii) Use publicity to motivate firms to improve performance to match the best

practices identified in their industry; (viii) support capacity building of non-governmental groups to verify

reporting; (ix) aggregate firm level performance data to show overall compliance rates, regional

variations, improvements over time, and best practices in social and environmental performance within

the country in investment marketing to foreign firms.

An effective pilot project should be designed as an open system that invites key stakeholders to take

part in discussions about measures of performance and systems of reporting. For the sake of providing a

starting point for further discussions, firms might disclose a number of standards “core indicators” of

facility performance, and indicators specific to sectorial issues and concerns (World Bank, 2005).

3.2.2. Toward the Strategies for improving CSR in developing countries

There are some basic principles which can support efforts to advance and improve CSR reporting: (i)

reporting initiatives should seek to increase the quality of information disclosed; (ii) they should work to

increase the uses of the information and the benefits to users; (iii) they should create mechanisms for

learning and continuously improving disclosure systems.

These goals can be supported through explicit efforts to target information to specific stakeholders

and decision-making processes. Information should be reported in formats useful to specific users. And

efforts should be made to verify that information is used by stakeholders to inform their decisions.

1. Standardized metrics

Continued work is needed on standardized metrics and indicators for reporting. However, metrics in

general should be: (i) Agreed upon by key stakeholders (representing what matters to them); (ii) Factual,

accurate, and verifiable; (iii) Reported at regular intervals in relatively simple language or data; (iv)

Comparable across locations, firms, and products; (v) Flexible/dynamic, so that metrics can change over

time; (vi) Usable by key stakeholders; (vii) Easily accessible.

2. Incentives for continuous improvement

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

203

Efforts are also needed to support continuous improvements in reporting. As mentioned,

intermediary groups are critical to analyzing and deploying information, and perhaps more importantly, to

creating demands for improved reporting.

Stakeholder groups with built-in incentives for using, analyzing, and monitoring the quality of the

information are central to the long-term sustainability of reporting schemes. In financial disclosure,

investors play this role of demanding high quality, verifiable information upon which to base their

investments. In environmental disclosure (such as the TRI), environmental groups use the data, translate it

for wider consumption, and keep pressure on the government and firms to improve reporting. No

equivalent group currently exists for CSR in developing countries, or indeed social reporting. Disclosure

systems can also be designed to create incentives and benefits for leading disclosers. Governments can

foster certain kinds of disclosure through a range of traditional economic incentives, and through

regulatory flexibility mechanisms.

Finally, in any system of disclosure it is critical to establish mechanisms to track changes in

practices over time, their impacts, and whether learning is occurring from reporting. All of these strategies

can be supported or directly advanced through government actions.

3. Possible “core indicators”

These are: (i) name and location of factory and number of employees; (ii) incidence of violations of

local laws, penalties, legal proceedings, etc. in the last year; (iii) wages and benefits paid to workers

(averages, minimum, highest), and incidence of violations of minimum wage laws; (iv) working hours

and overtime worked: incidence of violations of maximum working hour laws and overtime pay laws; (v)

policies for identification and elimination of harassment and discrimination: data on diversity in

management and work areas; (vi) policies for identification and elimination of child, forced , and

compulsory labor (including system for determining accurate age of workers); (vii) indicators of respect

for workers’ rights to freedom of association: percent of workers in a union, union-management relations,

work stoppages, lock-outs, strikes, etc.; (viii) health and safety performance: rates of accident, injuries,

occupational diseases and deaths; (ix) policies for monitoring compliance with local laws and codes of

conduct.

4. An ideal CSR’ management for developing countries

The descriptive approach adopted in the previous sections was used to illustrate how CSR actually

manifests in developing countries, rather than presenting an aspirational view of what CSR in developing

countries should look like. For example, it is not proposed that legal and ethical responsibilities should

get such a low priority, but rather that they do in practice.

By contrast, if the study is to work towards an ideal CSR model for CSR in developing countries,

we would argue that improved ethical responsibilities, incorporating good governance, should be assigned

the highest CSR priority in developing countries. It is my contention that governance reform holds the

key to improvements in all the other dimensions, including economic development, rule of law, and

voluntary action. Hence, embracing more transparent, ethical governance practices should form the

foundation of CSR practice in developing countries, which in turn will provide the enabling environment

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

204

for more widespread responsible business (figure 8).

Figure 8: Map of CSR in developing countries

Source: World Bank’s (2005)

4. Conclusion

From the outset, it should be recalled that this study focused on the demonstration of the

management of a CSR in developing countries across the world for a sustainable development. The

results gathered from this research allow us to highlight the essential ideas closely related to the two

essential aspects of the field of the study analysis. As we can see from above, it has been about presenting,

analyzing and interpreting the results to allow us to test the central research question and their different

research hypotheses.

According to the different findings, this study is summarizing CSR in developing countries in the

five distinctive characteristics: (i) CSR tend to be less formalized or institutionalized in terms of the CSR

benchmarks commonly used in developed countries, i.e. CSR codes, standards, management systems and

reports; (ii) where formal CSR is practiced, this is usually by large, high profile national and

multinational companies, especially those with recognized international brands or those aspiring to global

status; (iii) formal CSR codes, standards, and guidelines that are most applicable to developing countries

tend to be issue specific (e.g. fair trade, supply chain, HIV/AIDS) or sector-led (e.g. agriculture, textiles,

mining); (iv) In developing countries, CSR is most commonly associated with philanthropy or charity, i.e.

through corporate social investment in education, health, sports development, the environment, and other

community services and (v) making an economic contribution is often seen as the most important and

effective way for business to make a social impact, i.e. through investment, job creation, taxes, and

technology transfer.

Business often finds itself engaged in the provision of social services that would be seen as

government’s responsibility in developed countries, for example, investment in infrastructure, schools,

hospitals, and housing.

The issues being prioritized under the CSR banner are often different in developing countries, for

example, tackling HIV/AIDS, improving working conditions, provision of basic services, supply chain

integrity, and poverty alleviation. Many of the CSR issues in developing countries present themselves as

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

205

dilemmas or trade-offs, for example, development versus environment, job creation versus higher labor

standards, and strategic philanthropy versus political governance.

The spirit and practice of CSR is often strongly resonant with traditional communitarian values and

religious concepts in developing countries, for example, African humanism (ubuntu) in South Africa and

harmonious society (xiaokang) in China. The focus on CSR in developing countries can be a catalyst for

identifying, designing and testing new CSR frameworks and business models, for example, Praha lad’s

Bottom of the Pyramid model and Visser’s CSR Model for Developing Countries.

References

Baker, M. (2004) Corporate Social Responsibility: What does it mean? Available

at: http://www.mallenbaker.net/csr/definition.php

Baskin, J. (2006). Corporate Responsibility in Emerging Markets. Journal of Corporate Citizenship, 24, winter: 29–47.

Blowfield, M. and Frynas, J. G. (2005). ‘Setting New Agendas: Critical Perspectives on Corporate Social Responsibility in the

Developing World’. International Affairs, 81(3): 499–513.

Clark, J., Cole, S., Curnow, R. and Hopkins, M. (1975) Global Simulation Models, John Wiley, New York.

Carroll, A. B. (1991). ‘The Pyramid of Corporate Social Responsibility: Toward the Moral Management of Organizational

Stakeholders’. Business Horizons, 34: 39–48.

Christensen, J., and Murphy, R. (2004). ‘The Social Irresponsibility of Corporate Tax Avoidance: Taking CSR to the Bottom

Line’. Development, 47(3): 37–44.

Dolan, C. S., and Opondo, M. (2005). Seeking Common Ground: Multi-stakeholder Processes in Kenya’s Cut Flower Industry’.

Journal of Corporate Citizenship, 18, summer: 87–98.

Fig, D. (2005). Manufacturing Amnesia: Corporate Social Responsibility in South Africa’. International Affairs, 81(3): 599–

617.

Frynas, J. G. (2006). Corporate Social Responsibility in Emerging Economies’. Journal of Corporate Citizenship, 24, winter:

16–19.

Gabriel, P. P. (1972). ‘MNCs in the Third World: Is Conflict Unavoidable?’ Harvard Business Review. 50(4): 93–102.

Glaser, B.G. and Strauss, A.L.: 1967, The discovery of Grounded Theory: strategy for Qualitative Research (Weidenfed and

Nicolson).

Graves, S. and Waddock, S. (1999) Beyond Built to Last … Stakeholder Relations in ‘Built-to-Last’ Companies, Boston

College Carroll School of Management, Chestnut Hill, MA.

Hardcourt, W. (2004). ‘Editorial: Is CSR Rewriting Development?’ Development, 47(3): 1–2.

Hoffman, A. J. (2005). ‘Climate Change Strategy: The Business Logic Behind Voluntary Greenhouse Gas Reductions’.

California Management Review, 47(3): 21–46.

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

206

Hess, D.: 1999 ‘Social Reporting: A reflexive law approach to corporate social responsiveness’ Journal of Corporate Law, Fall,

25 (1), 41-85.

Hopkins, M. (1997) ‘Defining indicators to assess socially responsible enterprises’, Futures, Vol. 29, No. 7, pp.581–603.

Hopkins, M. (1999) The Planetary Bargain – Corporate Social Responsibility Comes of Age, Macmillan Press, Basingstoke.

Hopkins, M. (2003) The Planetary Bargain – Corporate Social Responsibility Matters, Earthscan, London.

Hopkins, M.: 2000, ‘The measurement of corporate social responsibility’ MHC International Limited News November 2000.

IMF (2006). World Economic Outlook: Financial Systems and Economic Cycles. Brussels: International Monetary Fund.

IoD (1992). King Report on Corporate Governance in South Africa. Johannesburg: Institute of Directors in Southern Africa.

– (2002). King Report on Corporate Governance in South Africa. Johannesburg: Institute of Directors in Southern Africa.

Ite, U. E. (2004). ‘Multinationals and Corporate Social Responsibility in Developing Countries: A Case Study of Nigeria’.

Corporate Social Responsibility and Environmental Management, 11(1): 1–11.

Jenkins, R. (2005). ‘Globalization, Corporate Social Responsibility and Poverty’. International Affairs, 81(3): 525–40.

Johnson, M. (2004). ‘Marks & Spencer Implements an Ethical Sourcing Program for its Global Supply Chain’. Journal of

Organizational Excellence, 23(2): 3–16.

Kaufman, A., Tiantubtim, E., Pussayapibul, N., and Davids, P. (2004). ‘Implementing Voluntary Labour Standards and Codes

of Conduct in the Thai Garment Industry’. Journal of Corporate Citizenship, 13, spring: 91–9.

Kolk, A., and Van Tulder, R. (2002). ‘Child Labour and Multinational Conduct: A Comparison of International Business and

Stakeholder Codes’. Journal of Business Ethics, 36: 291–301.

Lockett, A., Moon, J., and Visser, W. (2006). ‘Corporate Social Responsibility in Management Research: Focus, Nature,

Salience, and Sources of Influence’. Journal of Management Studies, 43(1): 115–36.

London, T., and Hart, S. L. (2004). ‘Reinventing Strategies for Emerging Markets: Beyond the Transnational Model’. Journal

of International Business Studies, 35(5): 350–70.

Lund-Thomsen, P. (2004) Towards a Critical Framework on Corporate Social and Environmental Responsibility in the South:

The Case of Pakistan. Development, 47(3): 106–113.

Malan, D. (2005) Corporate Citizens, Colonialists, Tourists or Activists? Ethical Challenges facing South African Corporations

in Africa. Journal of Corporate Citizenship, 18, summer: 49–60.

Moon, J. (2002b). ‘Corporate Social Responsibility: An Overview. In C. Hartley, The International Directory of Corporate

Philanthropy. London and New York: Europa Publications, 3–14.

Mwaura, K. (2004). Corporate Citizenship: The Changing Legal Perspective in Kenya. Interdisciplinary CSR Research

Conference, Nottingham, International Centre for Corporate Social Responsibility (ICCSR).

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

207

Nielsen, M. E. (2005). ‘The Politics of Corporate Responsibility and Child Labour in the Bangladeshi Garment Industry’.

International Affairs, 81(3): 559–80.

Okana, “Course of Management”, Catholic University of Congo, Kinshasa, 2011-2012.

Prahalad, C. K., and Hammond, A. (2002). ‘Serving the World’s Poor, Profitably’. Harvard Business Review, 80(9): 48–57.

Prasad, B. C. (2004). ‘Globalisation, Free Trade and Corporate Citizenship in Pacific Forum Island Countries’. Journal of

Corporate Citizenship, 13, spring: 65–76.

Prieto-Carron, M. (2004). ‘Is there Anyone Listening? Women Workers in Factories in Central America, and Corporate Codes

of Conduct’. Development, 47(3): 101–5.

Rangan, V. K., Quelch, J. A., Herrero, G., and Barton, B. (eds.) 2007. Business Solutions for the Global Poor: Creating Social

and Economic Value. San Franciso: Jossey-Bass.

Reed, D. (2002). ‘Corporate Governance Reforms in Developing Countries’. Journal of Business Ethics, 37: 223–47

Schmidheiny, S. (2006). ‘A View of Corporate Citizenship in Latin America’. Journal of Corporate Citizenship, 21, spring:

21–4.

Schrage, E. J., and Ewing, A. P. (2005). ‘The Cocoa Industry and Child Labour’. Journal of Corporate Citizenship, 18,

summer: 99–112.

UN, (2006). Millennium Development Goals Report 2006. Brussels: United Nations.

UNDP, (2006). Beyond Scarcity: Power, Poverty and the Global Water Crisis. Brussels: United Nations Development

Programe.

Visser, W.:

– (2005a). ‘Corporate Citizenship in South Africa: A Review of Progress Since Democracy’. Journal of Corporate

Citizenship, 18, summer: 29–38.

– (2005b). ‘Is South Africa World Class in Corporate Citizenship?’ in A. Freemantle (ed.), The Good Corporate Citizen.

Johannesburg: Trialogue.

– (2006a). ‘Research on Corporate Citizenship in Africa: A Ten-Year Review (1995–2005). In Visser et al. (2000b).

– (2006b). ‘Revisiting Carroll’s CSR Pyramid: An African Perspective’. In Pedersen and Huniche (2006), 29–56.

– (2007b). ‘Revisiting Carroll’s CSR Pyramid’. In Crane and Matten.

Visser, W. and Macintosh, A. (1998) A Short Review of the Historical Critique of Usury’. Accounting, Business & Financial

History, 8(2): 175–89.

Vivarta, V., and Canela, G., (2006). Corporate Social Responsibility in Brazil: The Role of the Press as Watchdog. Journal of

Corporate Citizenship, 21, spring: 95–106.

International Journal of Information, Business and Management, Vol. 12, No.2, 2020

ISSN 2076-9202

208

WBCSD (2000). Corporate Social Responsibility: Making Good Business Sense. Geneva: WBCSD.

Willi, A. (2014). Corporate Social Responsibility in Developing Country: An illustrate analysis”, University of Bath,

September.

Wood, D. (1994) Business and Society, Harper Collins, New York.

World Bank (2005). Investment Climate Survey. Washington: World Bank.

– (2006) World Development Report 2007: Development and the Next Generation. Washington: World Bank.

WRI (2005). World Resources 2005: The Wealth of the Poor: Managing Ecosystems to Fight Poverty. Washington: D.C.,

World Resources Institute, UNDP, UNEP, World Bank.

Reproduced with permission of copyright owner. Further reproduction
prohibited without permission.

Vol:.(1234567890)

Experimental Economic

s

(2020) 23:154–180
https://doi.org/10.1007/s10683-019-09604-3

1 3

O R I G I N A L PA P E R

Strategic decisions: behavioral differences between CEOs
and other

s

Håkan J. Holm1  · Victor Nee2 · Sonja Opper1

Received: 17 March 2018 / Revised: 16 February 2019 / Accepted: 19 February 2019 /
Published online: 25 February 2019
© The Author(s) 2019

Abstract
We study whether CEOs of private firms differ from other people with regard to
their strategic decisions and beliefs about others’ strategy choices. Such differ-
ences are interesting since CEOs make decisions that are economically more rel-
evant, because they affect not only their own utility or the well-being of household
members, but the utility of many stakeholders inside and outside of the organization.
They also play a central role in shaping values and norms in society. We expect
differences between both groups, because CEOs are more experienced with strate-
gic decision making than comparable people in other professional roles. Yet, due to
the difficulties in recruiting this high-profile group for academic research, few stud-
ies have explored how CEOs make incentivized decisions in strategic games under
strict controls and how their choices in such games differ from those made by oth-
ers. Our study combines a stratified random sample of 200 CEOs of medium-sized
firms with a carefully selected control group of 200 comparable people. All subjects
participated in three incentivized games—Prisoner’s Dilemma, Chicken, Battle-of-
the-Sexes. Beliefs were elicited for each game. We report substantial and robust dif-
ferences in both behavior and beliefs between the CEOs and the control group. The
most striking results are that CEOs do not best respond to beliefs; they cooperate
more, play less hawkish and thereby earn much more than the control group.

A preliminary version of this paper has been presented at the Department of Sociology at Cornell
University, the ESA European Meeting in Prague, the Nordic Conference on Behavioral and
Experimental Behavior in Aarhus, the Department of Economics at the University of Würzburg,
the Meeting of the French Experimental Economic Association in Paris, the Department of
Economics at the University of Rostock, the Berlin Behavioral Economics Seminar at WZB and
at the Workshop on Experimental Economics and Entrepreneurship at CBS in Copenhagen. We
are grateful for valuable comments from the audience on these presentations. Financial support is
gratefully acknowledged from the Jan Wallander’s and Tom Hedelius’ Foundation, the Crafoord
Foundation, the Knut Wicksell Center of Financial Studies, The Swedish Competition Authority,
and the John Templeton Foundation.

Electronic supplementary material The online version of this article (https ://doi.org/10.1007/s1068
3-019-09604 -3) contains supplementary material, which is available to authorized users.

Extended author information available on the last page of the article

http://orcid.org/0000-0001-5783-2463

http://crossmark.crossref.org/dialog/?doi=10.1007/s10683-019-09604-3&domain=pdf

https://doi.org/10.1007/s10683-019-09604-3

https://doi.org/10.1007/s10683-019-09604-3

155

1 3

Strategic decisions: behavioral differences between CEOs…

Keywords CEOs · Strategic decision-making · Belief elicitation

JEL Classification C70 · C90 · D22 · L26

1 Introduction

One aim of game theory is to understand the strategic decisions of important actors
in the economy (e.g., Von Neumann and Morgenstern 1944; Tirole 1988). Yet, only
a few experimental studies have employed subject pools representing important
decision-makers. In this paper, we focus on business leaders and compare their strat-
egy choices and beliefs with those of a control group of other professionals. The
study of CEOs’ strategic decisions is a natural choice given their prominent role in
economic decision making as firm leaders whose actions have significant implica-
tions for other stakeholders (employees, suppliers, clients, and the local economy at
large).1 They are also likely to play an important role in transmitting values, norms
and beliefs to other economic actors (e.g., employees, politicians and business part-
ners).Their greater experience in strategic performance would suggest that they
could differ in their strategic decision making from other people. For sure, people
who are not CEOs also make strategic decisions, but the type and impact of these
decisions tend to be more limited, influencing the well-being of individuals living in
the same household rather than a large number of external stakeholders.

Whether and how CEOs differ behaviorally from others is an empirical question.2
A priori, one can think of many mechanisms that might make a CEO’s strategic
behavior different from that of other people. Overall, one would expect that com-
petitive forces weed out irrational CEOs so that surviving CEOs choose strategies
which are best responses to each other; that is, they constitute Nash equilibria. Such
a mechanism is plausible if the Nash equilibria are evolutionary stable strategies
(Maynard Smith 1982). There are also strategic situations (e.g., prisoner’s dilemmas)
where individually rational choices according to the non-cooperative Nash paradigm
lead to a detrimental outcome for the involved parties, and where instead prosocial
or efficiency-oriented choices are favored (Bowles and Gintis 2011). Examples of
situations where the benefit of cooperation and prosocial behavior are evident for
CEOs include joint ventures and investments in infrastructure. Hence, another mech-
anism is social norms favoring efficient strategy choices that maximize the sum of
the involved parties’ payoffs. Such behavior can be sustained by welfare-maximizing

1 Although this paper investigates differences between CEOs and others, we do not claim that CEOs
comprise a homogenous group, for of course CEOs differ from each other in various respects, including
management style, and that this may affect how they run their firms (e.g., Bertrand and Schoar 2003). We
also alert readers who associate the term “CEO” with an externally recruited top manager to the fact that
most of our CEOs, in contrast, both own and have founded their firms.
2 It is not difficult to find two opposing perspectives: one warm and bright—portraying business lead-
ers as socially responsible actors who contribute to social welfare —and, one cold and dark, portraying
entrepreneurs as selfish profiteers (e.g., Van de Ven et al. 2007; Benabou and Tirole 2010).

156 H. J. Holm et al.

1 3

norms in close-knit groups (Ellickson 1991) and/or altruistic preferences through
assortative matching (Bergstrom 2002; Alger and Weibull 2013).

Various empirical studies have investigated the strategic decision making of
professionals (e.g., Cooper et  al. 1999; Palacios-Huerta and Volij 2008, Fréchette
2015); but because high-level professionals are hard to recruit, few studies (e.g.,
Fehr and List 2004) investigate incentivized choices in well-defined strategic games
with CEOs. The present study is the first to investigate CEOs’ choices in not just one
but several incentivized strategic situations that capture fundamental problems of
cooperation and coordination in business. In addition, this study is also the first to
combine group comparisons with belief elicitations allowing us to study the impact,
accuracy of beliefs and best responses to beliefs. This will allow us to test if expe-
rienced CEOs best respond to their own beliefs, which is a fundamental implicit
assumption in many modern models of industrial organization. Our sampling strat-
egy lends high credibility to the results presented here. In contrast to earlier studies
that use convenience samples (for the obvious reason that business leaders are dif-
ficult to recruit to perform experimental tasks), we use a stratified random sample of
CEOs managing firms with ten or more full-time employees. The control group of
other professionals was sampled to match core demographics of the CEOs. Finally,
our samples are relatively large compared to earlier studies.

For our study, we have data for 200 CEOs from private firms in two cities in the
Yangzi delta region of China and 200 control group individuals from the same cit-
ies. To capture the multiple dimensions of strategic behavior, we used three differ-
ent games to observe aspects of cooperativeness (Prisoner’s Dilemma), coordination
(Battle-of-the-Sexes) and anti-coordination (Chicken). We also included incentiv-
ized elicitations of beliefs about others’ choices, asking the subjects to guess the
behavior of others in their respective group.

Our first main result is that in all games the behavior of the CEOs differed sub-
stantially from the behavior of the control group. The CEOs cooperated more in the
Prisoner’s Dilemma game and played less hawkishly in the Battle-of-the-Sexes and
Chicken games. This result is significant in all games not only when we make raw
comparisons of proportions of the strategy choices between the groups but also when
we include control variables in regressions. When calculating the expected payoffs,
the differences are substantial between the groups, with CEOs earning from 11 to 44
percent more than the control group in these games. Remarkably, however, CEOs
did not out-compete the control-group members by being more rational (in the nar-
row textbook sense) or more selfish, but by being more cooperative and less aggres-
sive. Furthermore, CEOs believed in significantly higher cooperation levels than the
control group in the Prisoner’s Dilemma game. Overall and again contradicting the
rational “textbook CEO”, beliefs were frequently inconsistent with behavior. Under
the assumption of selfish preferences, compared to the control group, CEOs did not
best respond more frequently to their beliefs. However, the CEOs’ beliefs about
other CEOs’ behavior were on average more accurate than the corresponding beliefs
the control group held about other control-group members’ behavior.

The aim of this paper is to study the strategic behavior and beliefs of CEOs com-
pared to others. We perceive the identification of underlying causal mechanisms as
a natural second step and beyond the scope of the present paper. Nevertheless, our

157

1 3
Strategic decisions: behavioral differences between CEOs…

research design comparing the behavior of two distinct groups invites methodologi-
cal questions about the subjects’ background characteristics, their selection into the
study and other factors that could hypothetically bias our results. We have therefore
scrutinized our findings with a large battery of robustness tests exploring the influ-
ence of recruitment method, income differences, the definition of CEO and other
factors. Results of these tests consistently confirm our baseline results.

2 Related literature

This paper connects to two different strands of research. First, there is a growing
body of literature that explores how market transactions shape individual behavior
and preferences (see Bowles 1998 for a review). Some research in this area suggests
that property rights and market integration play an important role in the develop-
ment of efficient and prosocial behavior (Henrich et al. 2001),3 which would lead us
to think that CEOs—being more intensely involved with the market than others—
should display distinctly efficient and prosocial behavioral strategies. On the other
hand, it has also been observed that specific market mechanisms may trigger dis-
regard for third parties, which is normally seen as anti-social (e.g., Falk and Szech
2013; Bartling et al. 2015). Partly, these seemingly contradictory results are due to
different definitions of prosociality, but they may also be associated with the differ-
ent research methods used.4 Economic transactions take place in very different mar-
ket environments that can have diverse mediating impacts on individual behavior.
In the ‘idealized’ competitive market where anonymous buyers and sellers transact,
there is no obvious room for prosocial behavior, and this may encourage ethically
questionable conduct (Shleifer 2004). In real-world market environments, how-
ever, transactions are typically personalized and anonymity absent. Repeat transac-
tions and cultivation of long-time business relations clearly represent the standard
rather than the exception for corporate transactions. Hence, this paper contributes to
research on the potential impact of non-anonymous market activities by studying if
and how experienced business leaders differ from people otherwise sharing the same
cultural and local setting, but not the same extent of market exposure.

Secondly, our study relates to the literature about behavioral preferences of busi-
ness leaders and entrepreneurs. This research area includes theories about why these

3 The finding by Ockenfels and Weimann (1999) that student subjects who grew up in socialist Eastern
Germany contributed less in a public good game and showed less solidarity than similar subjects who
grew up in market-oriented West Germany is in the same spirit.
4 For instance, higher accepting rates in the ultimatum game in Henrich et al. (2001) are interpreted as
cooperative and prosocial, whereas a higher accepting rate (at a given price) in the double auction in Falk
and Szech (2013) increases the efficiency in terms of the monetary reward for the two bidders, but since
the third party (the mouse) is worse off when a bid is accepted, it is interpreted as a sign of moral ero-
sion. The method used by Henrich et al. (2001) is based on comparing behavior in experimental games
of widely different groups in the field relying on the hypothesis that different habits and cultures “spill
over” into the groups’ behavior in the games, whereas Falk and Szech (2013) and Bartling et al. (2015)
induce different “institutional” settings in strictly controlled laboratory experiments of given and rela-
tively homogenous subject pools.

158 H. J. Holm et al.

1 3

groups should differ from other people (e.g., Kihlstrom and Laffont 1979; Van de
Ven et  al. 2007) and studies investigating whether such differences can be empiri-
cally established (e.g., Van Praag and Cramer 2001; Holm et  al. 2013; Hvide and
Panos 2015; Åstebro et  al. 2014; Koudstaal et  al. 2016). The latter literature is
extensive but typically focuses on personality characteristics such as risk and uncer-
tainty preferences, overconfidence, the locus of control and desire for achievement.

Only a few studies have explored CEOs’ strategic behavior in controlled settings
using incentivized games, where behavior is interactive and where the outcome is
predicted by the theoretical concepts of equilibrium. If we use a ‘generous’ defi-
nition including not only CEOs but also high-ranking managers and professionals,
we obtain a small set of eight studies on strategic behavior with similarities to the
present one (see Table  1). These studies compare the behavior of business leaders
under various definitions (e.g., CEOs, entrepreneurs, managers, self-employed) with
control-group members (e.g., students, salary workers) in distinct controlled and
incentivized strategic settings. Most closely related to ours is a study by Fehr and
List (2004), who conducted a trust game experiment with CEOs in the Costa Rican
coffee industry and undergraduate students. They found that the CEOs were more
trusting and reciprocated more than the students.

While the results of the studies listed in Table  1 naturally vary due to differ-
ences in design and subject groups, one can draw some highly tentative conclusions.
For one, the self-employed tend to be more willing to take decisions on their own
(Cooper and Saral 2013; Masclet et  al. 2009). Furthermore, managers are more
willing to cooperate (in team production and in trust relations) than control sub-
jects (Fehr and List 2004; Holm et al. 2013; Montmarquette et al. 2004). However,
Cooper and Saral (2013) detect no differences in free-riding.

Our study contributes to this literature in a number of ways. None of the above
studies links behavior to general theoretical constructs (like Nash equilibrium)
across more than one game. By having three different games in our design, we put
any theoretical hypothesis about differences between CEOs and the control group
to a tougher test, since the set of theoretical mechanisms that are consistent with
an observed pattern of differences shrinks the more potential differences we can
observe. Furthermore, the present study is the first that elicits subjects’ beliefs about
others’ choices, which allows us to identify to what extent behavior is associated
with specific beliefs regarding others’ behavior. The belief elicitations also make it
possible to study the accuracy of beliefs and whether actions are best responses to
beliefs.

We also make a methodological contribution by using a stratified random sam-
pling technique for recruiting CEOs and the comparison group. By including CEOs
from five different manufacturing industries, we reduce the risk of industry-specific
results, yet limit the risk of noise linked to different background conditions. Further,
by excluding CEOs operating very small firms, we ascertain that our subjects are
used to exercising strategic decisions that have a certain economic relevance. Many
of the above studies use specific comparison groups (most often students) who dif-
fer significantly from the CEOs along multiple dimensions (e.g., age, professional
experience, income). We have reduced these differences substantially by matching
the CEOs more closely with the control group in terms of age, gender, education and

159

1 3
Strategic decisions: behavioral differences between CEOs…

Ta
bl

e
1

S
tu

di
es

o
n

st
ra

te

gi

c
de

ci
si

on
s

w
ith

b
us

in
es

s
le

ad
er

s

A
a

bs
tr

ac
t f

ra
m

e,
F

fi
el

d
fr

a

m
e,

S
A

s
em

i a
bs

tr
ac

t f
ra

m
e,

N
R

n
on

-r
an

do
m

s
am

pl
e,

S
R

s
tr

at
ifi

ed
ra

nd
om

, U
u

nd
er

gr
ad

ua
te

, S
E

s
el

f-
em

pl
oy

ed
)

Pa
pe

r
Fo

cu
s

gr
ou

p
C

om
pa

ri
so

n
gr

ou
p

G
am

e
Fr

am
e

B
el

ie
f e

lic
it.

Sa
m

p-
lin

g
M

ai
n

fin
di

ng

C
oo

pe
r e

t a
l.

(1
99

9)
M

an
ag

er
s

an
d

fo
re

m
en

in

te
xt

ile
in

du
st

ry

(N
=

1
50

,

C
hi

na
)

U
. s

tu
de

nt
s

(N
=

1
60

,

C

hi
na

)
R

at
ch

et
e

ff
ec

t

g
am

e
A

+
F

N
o

N
R

Fi
el

d

co

nt
ex

t i
nc

re
as

es

m
an

ag
er

s’
b

ut
n

ot
s

tu
–

de
nt

s’
s

tr
at

eg
ic

p
la

y
C

oo
pe

r

(

20

06
)

E
xe

cu
tiv

e
M

B
A

s
tu

de
nt

s

(N

=
1

9,
U

SA
)

U
. s
tu
de
nt
s
(N
=

2
0,

U

SA
)

W
ea

ke
st

li
nk

g
am

e
SA

N
o
N
R
E
xe

c.
M

B
A
s
tu
de
nt

s
be

tte
r

at
o

ve
rc

om
in

g
co

or
di

na
–

tio
n

fa
ilu

re
s

C
oo

pe
r a

nd
S

ar
al

(2
01

3)
SE

(N
=

4
4,

U
SA

)
St

ud
en

ts
, a

lu
m

ni

(N
=

1
40

, U
SA

)
Te

am
p

ro
du

ct
io

n
A

N
o
N
R

SE
le

ss
w

ill
in

g
to

jo
in

te

am
, n

o
di

ff
er

en
ce

in

fr
ee

-r
id

in
g

E
ls

to
n

et
 a

l.
(2

00
6)

SE
v

is
ito

rs
a

t a
c

on
ve

n-
tio

n
(N

=
8

2,
U

SA
)

N
on

-S
E

v
is

ito
rs

a
t a

co

nv
en

tio
n
(N
=

9
0,

U
SA
)

M
ar

ke
t e

nt
ry

g
am
e
A
N
o
N
R

Pa
rt

-t
im

e
SE

le
ss

w
ill

in
g

to
c

om
pe

te

Fe
hr

a
nd

L
is

t (
20

04
)

C
E

O
s

fr
om

c
off

ee
in

du
s-

tr
y

(N
=

7
6)

St
ud

en
ts

(N
=

1
26

)
Tr

us
t g

am
e

A
N

o
N

R
C

E
O

s
m

or
e

tr
us

tin
g

an
d
tr
us

tw
or

th
y

H
ol

m
e

t a
l.
(2
01

3)
C

E
O

s
fr

om
fi

ve
d

iff
er

en
t

in
du

st
ri

es
(N

=
7

00
,

C
hi
na
)

Su
bj

ec
ts

s
am

pl
ed

to

m
at

ch
C

E
O
s
(N

=
2

00
,
C
hi
na
)

Tr
us

t e
lic

ita
tio

n
+

W
ill

–
in

gn
es

s
to

c
om

pe
te

A
N

o
SR

C
E
O
s

m
or

e
tr

us
tin

g
an

d
m

or
e
w
ill
in
g
to
c
om
pe
te

M
as

cl
et

e
t a

l.
(2

00
9)

SE
(N

=
1

4,
F

ra
nc

e)
Sa

la
ry

w
or

ke
rs

a
nd

st

ud
en

ts
(N

=
1

30
,

Fr
an

ce
)

R
is

k-
ta

ki
ng

d
ec

is
io

n
on

th

ei
r o

w
n

or
in

g
ro

up
A

N
o
N
R

SE
p

ay
m

or
e

fo
r t

ak
in

g
de

ci
si
on
s

on
th

ei
r o

w
n

M
on

tm
ar

qu
et

te
e

t a
l.

(2
00

4)
M

an
ag
er
s
fr
om

p
ha

r-
m

ac
eu

tic
al

c
om

pa
ny

(N

=
3

6,
F

ra
nc

e,

G
er

m
an

y)

St
ud
en
ts
(N
=

7
2,

C

an
ad

a,
F

ra
nc

e)
Te

am
e

ff
or

t t
as

k
A

N
o
N
R

M
an

ag
er
s
m
or
e

co
op

er
a-

tiv
e

th
an

s
tu
de
nt
s

160 H. J. Holm et al.

1 3

residential living area. The present samples of CEOs and control group subjects are
also relatively large compared to most previous studies.5

3 Theory and hypotheses

We analyze decisions in three simple 2 × 2 games—Prisoner’s Dilemma, Battle-of-
the Sexes, and Chicken (see Tables  2, 3 and 4)—that capture situations requiring
cooperation, coordination and anti-coordination.

These three games involve strategic elements that differ along important dimen-
sions and are likely to be more important in the context of running a firm than in
other settings. Because these situations occur at a higher frequency for CEOs and
are also likely to have greater economic consequences for them than for other pro-
fessionals, we expect on average different behavioral strategies between CEOs and
the control group (henceforth denoted as “CG”). At this early stage, the identifica-
tion of the exact causal mechanism explaining different strategies goes beyond the
scope of this paper. Potential mechanisms include self-selection of distinct types
into professional roles, a weeding out of distinct behavioral strategies through com-
petitive pressure, or social learning through repeat experience in similar or related
situations. In the following subsections, we discuss in more detail why each of the
games was chosen and why the CEOs’ behavior may differ from responses by other
professional groups.

3.1 Prisoner’s Dilemma

Situations analogous to the Prisoner’s Dilemma (henceforth denoted as PD) are
common between the CEO and employees, where free-riding opportunities fre-
quently co-exist with possible benefits of cooperation. Similar strategic situations
emerge between firms horizontally, e.g., in terms of price-setting (collusion),
recruitment and joint investments. A priori, one can think of different mechanisms
that would make a CEO’s strategic behavior different from that of other people in
PD—recognizing, however, that these alternative mechanisms imply both more and
less defection in such a game.

From a traditional economic perspective, one can argue that competitive forces
ought to weed out irrational CEOs so that surviving CEOs choose strategies that
constitute Nash equilibria.6 As noted in the introduction such a mechanism is plau-
sible when the Nash equilibria are evolutionary stable strategies (Maynard Smith

6 It is well-known (e.g., Fehr and Schmidt 1999; Engelmann and Strobel 2004) that the Nash equilibrium
prediction is contingent on the underlying (possibly social) preferences assumed. To simplify the presen-
tation and theoretical conceptualization, we assume standard selfish materialistic preferences (i.e., play-
ers only care about their own payoff) when referring to Nash equilibrium and socially optimal outcomes.

5 The only larger sample of CEOs on incentivized strategic decision-making besides the present study
is in Holm et al. (2013), which is based on data from a study conducted in 2009 containing two strategic
situations (in terms of trust and willingness to compete). However, the objective there was to investigate
differences between CEOs and a control group in behavior relating to uncertainty preferences.

161

1 3
Strategic decisions: behavioral differences between CEOs…

1982). However, social norms favoring efficient strategy choices that maximize the
sum of the involved parties’ payoffs might constitute an alternative mechanism.
Such behavior can be sustained by the development of welfare-maximizing norms
in well-defined social groups characterized by mutual monitoring and social reward
and punishment (Ellickson 1991; Bowles and Gintis 2011) and/or altruistic prefer-
ences through assortative matching (Bergstrom 2002; Alger and Weibull 2013). If
this is the case one can expect that CEOs will be more cooperative in their strategic
decision making than others and that the population as a whole consists of different
strategic ‘types’ (e.g., Kurzban and Houser 2005). Assuming that these two mecha-
nisms are more prominent for CEOs than for others, we can expect differences in
behavior between CEOs and others on average. In PD these alternative mechanisms
have both straightforward (diametrically opposite) predictions since there is a unique
Nash equilibrium (both players Defect) and a unique social optimum (both players
Cooperate).

3.2 Battle‑of‑the‑sexes

The Battle-of-the-Sexes game (henceforth denoted as BSS) captures situations
where subjects can choose to act more or less aggressively, while coordination
would lead to preferable outcomes. From a general management perspective coor-
dination problems are fundamental. Inside the organization, leadership tasks for the
CEO include the management of beliefs (Foss 2001) and the alignment of incentives
with the adoption of new information (Bolton et  al. 2013) in order to solve aris-
ing coordination problems. In inter-organizational dilemmas, coordination situations
with the flavor of BSS are likely to emerge with upstream and downstream firms,
specifically if decisions involve the implementation of new technology, (re-)loca-
tion, and changes of market linkages.

In BSS coordinating on one of the two pure Nash-equilibria, where both players
choose the same strategy (A, A) or (B, B), is obviously preferable for both players.
At the same time, (player) Row prefers coordination on Strategy A and (player) Col-
umn prefers coordination on Strategy B. Hence, the players need to strike a balance
between coordination and “domination” motives. In the following, we will also refer
to Strategy A (B) for Row (and Column, respectively) as the “hawkish” strategy,
since by choosing this strategy the player has excluded all outcomes where he is
dominated by his opponent in terms of payments. With the same logic, we will also
refer to Strategy B (A) for Row (and Column, respectively) as the “dovish” strat-
egy, since this strategy will always give the opponent at least as much payoff as the
player himself.

The motives of coordination and domination would most likely be reflected in a
negotiation between the Row and Column player if they could communicate. How-
ever, in our game communication is not possible and there are no obvious coor-
dination devices. Given the difficulty of coordination on the pure strategy Nash
equilibria, it is reasonable to expect that players with selfish preferences play the
unique mixed strategy where Row and Column play A with probability 0.6 and 0.4,
respectively.

162 H. J. Holm et al.

1 3

There are reasons to believe that CEOs differ in the way they play BSS com-
pared to others. For one thing, leading business people may have a strong preference
for relative domination. Alfred Marshall (1890/1920, p. 23) claimed that “a manu-
facturer or a trader is often stimulated much more by the hope of victory over his
rivals than by the desire to add something to his fortune.” If this holds for our CEOs,
we would expect more hawkish play among them in BSS than among those in CG.
Other possible mechanisms relate to the experience, skill and, motive to coordinate
mentioned above. If CEOs as leaders of private firms are more exposed and experi-
enced than others in detecting and handling coordination situations compared to oth-
ers they may well differ from others in how they form beliefs and act in BSS.

Our research focus is not on focal points. We will simply assume that the players
do not intend to coordinate through focal points.7 As a consequence, all our subjects

Table 2 The prisoner’s dilemma

The payoffs to the subjects in Chinese Yuan, CNY

Defect Cooperate

Defect 100, 100 400, 50
Cooperate 50, 400 250, 250

Table 3 The Battle-of-the-sexes

The payoffs to the subjects in Chinese Yuan, CNY

Strategy A Strategy B

Strategy A 600, 400 0, 0
Strategy B 0, 0 400, 600

Table 4 Chicken

The payoffs to the subjects in Chinese Yuan, CNY

Hawk Dove

Hawk 0, 0 600, 150
Dove 150, 600 300, 300

7 The analysis of BSS is more complicated since it is an asymmetric game. In a standard matching pro-
tocol (e.g. in a computer lab) half the subjects would have been randomly assigned the Row and Column
player role. In such a setting it would be possible to calculate if they were able to coordinate by the
use of coordination cues (i.e., focal points) like strategy labels (see Schelling, 1960). Although, it has
been shown that focal points based on strategy labels are successfully used in symmetric (pure) coordina-
tion games, when introducing asymmetries as in the BSS, the coordination through focal points more or
less vanishes (see Crawford et al. 2008 and Parravano and Poulsen 2015). Furthermore, the use of focal
points is often context or culture-specific. We can not rule out that some try to use “A” as a focal point
since it is the first letter in the alphabet. However, given results from the cited literature and noting that
our Chinese subjects do not have an alphabet similar to the English, we believe that this focal point is not
likely to be salient.

163

1 3
Strategic decisions: behavioral differences between CEOs…

were given the Row player role. (The limited number of opponents matched for real
payoffs, denoted as X-players, had the Column player role, see Sect. 4).

3.3 Chicken

The Chicken game illustrates elements of situations characterized by anti-coordi-
nation where it is vital (contrary to the coordination games) that the players do not
choose the same strategy. CEOs are likely to encounter ‘Chicken-like’ situations in
private markets where some valuable capacity, resource or demand are scarce and
where there is competition for it. One relevant example would be a market-entry
decision where it is only profitable for one firm to serve the market.

In this game, there are two pure equilibria where one of the players plays Hawk
and the other Dove. If the players could communicate, one would expect that the
players would try to convince each other (e.g., with threats) that they would play
Hawk. However, in our game, they cannot communicate, which means that it is rea-
sonable to expect that the players (with selfish preferences) play the unique mixed
strategy where Row and Column play Hawk with probability 0.67.

As in the previous games there are reasons to believe that CEOs may differ in the
way they play Chicken compared to others and that the direction of this difference
is not obvious a priori. It has been argued that private business leaders and entrepre-
neurs are more optimistic than others or may even be overconfident. The theoretical
literature draws on this to explain excessive market entry (see e.g., Bernardo and
Welch, 2001; Hayward et  al. 2006; Wu and Knott, 2006). These arguments would
suggest that CEOs are more hawkish in Chicken games than other comparable peo-
ple. At the same time, if CEOs will be more used to and trained to handle such situ-
ations, it may be that they have learned the cost of hawkishness the hard way and
therefore will be more inclined to guarantee a non-zero payoff by playing Dove than
others with less experience. In addition, Dove would also be an attractive strategy
for less selfish subjects with a strong preference for fairness, since it can lead to the
non-zero equal payoff (300, 300).

3.4 Hypotheses

In the preceding sections, we have discussed some potential mechanisms that would
lead to behavioral differences between CEOs and CGs. However, as there were no
unambiguous directional predictions we use the null hypothesis that there are no dif-
ferences in behavior or beliefs. Hence our hypotheses are as follows:

1. On average, the CEOs and the CGs choose strategies similarly in the different
games.

2. On average, the CEOs’ beliefs about others’ behavior are similar to those of the
CGs.

3. On average, the CEOs’ best responses to their beliefs are similar to those of the
CGs.

164 H. J. Holm et al.

1 3

4 Research strategy and design

In this section, we briefly present the research strategy and design of our study in
terms of tasks, treatments, sampling strategy and implementation.8

4.1 Tasks and treatments

Initially, the subjects received general information about the tasks (see Instructions
in the Appendix provided in the online Supplementary Material) and payments.
They were also informed that in some tasks they would play against another anony-
mous person, who was denoted as X. To mitigate potential order effects, the CEOs
and the CGs were divided into six different treatment groups based on the order
and frames of the games, so that each game with a given frame had the 1st, 2nd and
3rd position exactly once (see Appendix  1C). Hence, each subject participated in
six different tasks (three games and the belief elicitations). One of the games was
randomly selected at the end of the experimental session as the money-earning task.
By paying for only one task (a strategy choice in a game or a guess in a belief elici-
tation), we follow Blanco et al. (2010) to avoid the ‘hedging problem’ of the belief
elicitations.

The framing of a game can affect behavior (Tversky and Kahneman 1981; for a
review Levin et  al. 1998). Increasing awareness of these framing effects has moti-
vated many researchers to increase the “field content” that subjects are exposed to
(Harrison and List 2004).9 We investigate this link by presenting each game with
both an abstract frame and a field frame, which introduces the game as a common
type of business decision that could also be easily grasped by non-CEOs without
managerial experience. Both frames were randomly assigned, with half of the sub-
jects in each group receiving an abstract frame and half a field frame.10 If our results
are robust with respect to the frame, we can claim that the results generalize beyond
the situational construct and decision domain.

The decisions in the three games were to choose between strategies ‘A’ and ‘B’.
In the abstract frame, the game explanation focused on the payoff information. In the
field frame, three scenarios preceded the payoff information (see Instructions in the
Appendix for details). The belief elicitation tasks were to guess the percentage of
other players who chose either strategy in the game respondents had just played. The
closer the subject’s guess was to the observed frequency, the higher the earnings.11

8 Comments on the design and more details are provided in the Appendix.
9 In fact, Cooper et al. (1999) find that managers (in the textile industry in China) become more strategic
when exposed to field frames than students. However, the result from Cubitt et al. (2011) appears to go in
the opposite direction, indicating that experienced subjects tend to be less susceptible to framing.
10 The descriptions of the frames are available in the Instructions.
11 To limit the cognitive load and due to time constraints, we used a simple scoring rule rather than a
proper continuous scoring rule like the quadratic one. Subjects earned 500 CNY if they were ± 2 percent-
age points from the correct answer; and gradually less the further away the answer was from the correct
one. While such a simplistic scoring rule may tilt beliefs slightly away from true beliefs, they should do
so in the same way for all subjects. The choice of scoring rule should therefore be unproblematic in stud-
ies like ours where the main focus is not point predictions but between-subjects comparisons. Simplistic

165

1 3
Strategic decisions: behavioral differences between CEOs…

By eliciting beliefs about the percentage of other players choosing a certain strategy
we get more precise information about beliefs than if we had elicited beliefs about
the opponent’s binary choice.

To be able to pay out cash rewards on the spot immediately after the experimental
tasks, we obtained choices from a small additional group of 11 CEOs and another
small group of 9 CGs who took the role as X persons in the experiment before we
approached the 200 CEOs and 200 CGs in the main study.12

4.2 Sampling and descriptive statistics

For this study, we recruited 100 CEOs and 100 CGs from each of the two Chinese
coastal cities of Shanghai and Wenzhou for a total of 400 participants.13 CEOs were
sampled from firms stratified according to industry.14 Industries range from labor-
intensive to technology-intensive and include textile, ordinary machinery, vehicle
and auto parts, medical and pharmaceutical products, and computer and commu-
nication equipment. So as not to end up with a sample of managers running small-
scale marginal firms, the sample was stratified by firm size. More specifically, we
over-sampled ‘large’ (more than 300 employees) and ‘medium-size’ (100–300)
firms. Finally, to avoid fresh start-ups and self-employed businesses our sampling
frame included only firms that had survived for at least three years. The CGs were
randomly selected from household registers to match the CEOs with respect to gen-
der, age, education. To get a reasonable match with respect to income, we added
the restriction that CG subjects should live in the residential areas where the CEOs
themselves lived. In this way, we avoided having a very select control group (for
instance, a specific group of highly paid professionals), and we avoided having a
sample of people who differed very much from the CEOs.

Footnote 11 (continued)
scoring rules for beliefs are not uncommon in the experimental literature; see, e.g., Gächter and Renner
(2010).
12 The behavior of the X subject is of no interest to the study, but is necessary to avoid deception of the
subjects in the main study. Each X subject was matched to more than one subject. Some information
given to this group was adapted to their role (e.g., that they got paid after the main study was finalized).
To test the design, we also had 39 additional CEOs who were matched to the ‘XCEOs’ in a pilot study.
13 The games employed in this paper were appended to a firm survey conducted in 2012 including 7
cities and a total of 700 entrepreneurs. Games were conducted in 5 cities, with a total of 500 CEOs (100
CEOs in each city). For the purpose of a comparative study we recruited 200 CGs in two of the five cit-
ies. To get a clean design for this paper focusing on differences in strategic behavior between CEOs and
CGs, the data used here is based on the two cities, in which we have matching CEO and CG data for 200
subjects. The behaviors of the remaining 300 CEOs (together with the 200 CEOs used in this paper) will
be used to explore questions of within-subject/within-firm variation and to explore the external validity
of revealed game behavior. Experimental data collected in connection with an earlier firm survey (2009)
was analysed in studies by Holm et al. (2013), Opper et al. (2017) and Nee et al. (2018).
14 Specific aspects of conducting this study in China are commented in the Appendix.

166 H. J. Holm et al.

1 3

Table 5 summarizes the descriptive statistics for the 400 participants in our study
according to gender, age, income, and education.15 The matching of gender and age
in the CG worked well. There is also virtually no difference in education between
the two groups.16 The average household income of the entrepreneurs is—as can
be expected—more than twice as high compared to the average of the CG. While
this is a large difference, it would be much larger without a residential selection of
the control group.17 To minimize the risk that income is driving the results we will
complement our basic group comparison analysis with regressions where we control
for income.

4.3 Execution

A key to recruiting very busy people for a study like this is to make it easy to par-
ticipate and to be persistent. We relied on 20 professional interviewers of Shang-
hai Yihong Business Consulting (a local company specializing on survey research),
each with multiple years of field experience, to conduct the survey, after making
individual appointments.18 For the CEOs, the interviews and experimental tasks
were conducted at the firm site, usually in a conference room or at the CEO’s private
office, by a team of two interviewers. The CEOs were first asked questions about
their background (education, demographics) and the firm (start-up capital, firm rev-
enues, etc.). The CGs were also visited by a team of two interviewers at their private
residence where they were asked the same set of questions, except for those regard-
ing the firm and business development.19 Each subject was then presented with the
three games and the belief elicitation tasks. Both CEOs and the GGs made their
task choices using a paper-and-pencil format. As interviewers were in charge of col-
lecting the questionnaires once completed, interviewers were naturally able to see
their choices, but choices were not observable by others, such as employees and staff
members or family members in the case of CGs. Hence, the degree of anonymity

19 The difference of location of the interviews and experimental tasks (at work versus at home) might
affect results. However, we can exclude this possibility since we find that the subgroup of “CGCEOs”
who did the interview and tasks at home differ from the other CGs in the same way as the CEOs who
were visited at their firms (see the robustness check in Sect. 5.3).

15 These are standard demographic variables often controlled for in empirical studies. There is also evi-
dence that these variables may matter for incentivized strategic behavior. Earlier research suggests that
gender affects social and competitive preferences as well as risk preferences (Croson and Gneezy 2009;
Dohmen et al. 2011). Education and age have been reported to matter for trust, cooperation and ultima-
tum game behavior (Glaeser et al. 2000; Güth et al. 2007 and Thöni et al. 2012). A subject’s income will
affect the salience of experimental earnings and the stakes that a subject confronts. Stakes have been
demonstrated to affect strategic behavior in ultimatum games (Andersen et al. 2011).
16 When the CGs were just randomly selected from the household registers in the same cities as the
CEOs, the latter group had significantly more years of education (Holm et al. 2013). In Appendix 5 we
provide additional detailed information on the matching between the CEOs and the CGs.
17 In Holm et al. (2013), where the control group was just randomly selected from the household regis-
ters in the same cities as the entrepreneurs, the median income of the entrepreneur was eight times higher
than that of one of the CGs.
18 If a CEO had to cancel a meeting, the assistants would try to reschedule it at some other time. This is
one reason that it took these 20 assistants over four months to collect the data.

167

1 3
Strategic decisions: behavioral differences between CEOs…

is the same for the two subject groups and corresponded to a single blind experi-
ment.20 Afterward, one task was randomly selected as the money-earning task. The
earnings were calculated and the subject received the payment immediately. The
average subject in our experiment earned 247 CNY (or USD 39) on the behavioral
tasks that took only 18  min on average, which corresponds to hourly earnings of
USD 130.21 The main experiment took place during a period of about four and a half
months, starting with the first subject on August 25, 2012, and ending with the last
subject on January 9, 2013.

5 Results

In this section, we report observations of the subjects’ behavior on the experimental
tasks. We start with the strategy choices in the games, after which we analyze the
subjects’ beliefs.

5.1 Behavior in the games

Results presented in Table  6 show significant differences between the average
behavior of the CEOs and the CGs in terms of strategic choices in each game. The
differences are also substantial in percentage points, ranging between 13 percentage
points and 25 percentage points in one game. Clearly, the CEOs are significantly
more cooperative in PD and play significantly less hawkishly in BSS and Chicken.22
This suggests that null hypothesis 1, stating that on average the CEOs and the CGs
will choose strategies similarly in the different games, can be rejected. However, to
reach a final conclusion we need to confirm that the observed differences between
the groups are not due to confounding effects. We return to this concern in the fol-
lowing sections.

It should be evident from Table  6 that the Nash equilibrium (NE) predictions
are not always consistent with the groups’ behaviors. The CEOs are close to the
mixed NE in BSS and the CGs are close to the mixed NE in Chicken, but in PD both
groups are far from the NE.23 Hence, the groups alternate in being close to the NE,

20 This is important since the degree of anonymity may be an important factor for social desirable
behavior (see e.g., Bernheim 1994; Andreoni and Bernheim 2009).
21 This translates to an average hourly experimental earning of around 220 USD if we correct for pur-
chasing power according to the Big Mac index (which was 1.68 in January 2014). It should be stressed
that the income of CEOs in successful firms in China is relatively low from an international perspective,
which makes it possible to provide salient incentives in the games and belief elicitations at a reasonable
cost. Though even moderately successful CEOs are a high-income group in China, their median annual
family income in our sample was only around USD 75,000 (according to the exchange rate 6.38 CNY/
USD in August 2012).
22 Note that the game was presented to the subjects in the BSS so that they were Row players (in
Table  3), which means that Strategy A is interpreted as the hawkish strategy. The X-players had the
reversed payoffs and the Column player role.
23 The fact that NE does not point predict one shot behavior in PD is in line with many other studies
using different subject groups (e.g., Kagel and Roth 1995).

168 H. J. Holm et al.

1 3

and the CGs are closer to the NE in four out of six versions of the games. Therefore
we cannot convincingly state that CEOs and the CGs differ in how they behave in
playing NE. In fact, nothing in the data suggests that the CEOs are “more” consist-
ent with the standard textbook predictions of economics (based on selfishness and
Nash equilibrium) than are the CGs.

5.1.1 Probabilities for outcomes and expected payoffs

We will now elaborate on the relative probabilities of the outcomes for the CEOs
and CGs end up in given their behavior (in Table 6). This will also help us to under-
stand the substantial differences in expected payoffs between the groups. By using
the proportions of chosen strategies among CEOs and CGs, while assuming that
players are randomly matched (and cannot use any coordination devices etc. as
explained in Sects.  3.2 and 3.3), it is possible to calculate the probability for the
various outcomes in the games for the respective group. To simplify the presen-
tation, we merge the abstract and field frame proportions given in Table  6 (which
means, e.g., that the proportions playing Defect among CEOs and CGs are 0.42
and 0.56, respectively). The probability for ending up in an outcome where both
players play Defect in PD is then given by prob(DD) = q2

D
, where qD is the propor-

tion in the group that play Defect. The probability that both cooperate is given by
prob(CC) =

(

1 − qD
)2

and the probability that they play different strategies is given
by prob(DC, CD) = 2qD

(

1 − qD
)

. If the probability for each outcome is multiplied
by the sum of the two players’ payoffs (given in the parentheses in Table  7) and
these terms are added together we get the expected earnings for a pair of players in
the game. Clearly, the same logic can be applied when calculating the probabilities
and expected earnings in BSS and Chicken.

One general pattern in Table  7 is that the probabilities for CEOs to end up in
high payoff outcomes are in most cases substantially higher than for the CGs. For
instance, in PD, the probability that CEOs end up in the outcome where both play-
ers cooperate is 72% higher than the corresponding probability for CGs. Conversely,
the probabilities that CGs will have low payoff outcomes are higher compared to
the CEOs. For instance, in the Chicken game, the probability for the zero payoff
outcome where both players play Hawk is 85 percent higher for CGs. Naturally,
these distributions of outcomes are reflected in the expected payoffs of the different

Table 5 Descriptive
characteristics of the subjects

Standard deviations in parentheses

Variable CEOs Control Group

Gender (proportion males) .85 (.36) .82 (.39)
Age (year, mean) 45.77 (7.79) 41.30 (6.80)
Yearly household income (mil-

lion CNY, mean)
.55 (.47) .24 (.25)

Years in school (mean) 13.64 (3.22) 13.84 (2.78)
Number of observations 200 200

169

1 3
Strategic decisions: behavioral differences between CEOs…

groups. Compared to the CGs, the CEOs expected payoffs are 11%, 35%, and 44%
higher in PD, BSS and Chicken, respectively.

5.1.2 Regression analysis

In Table  8 we present marginal effects from logistic regressions where we control
for likely confounders, such as gender, education, age and income (reported in:
Glaeser et  al. 2000; Güth et  al. 2007; Croson and Gneezy 2009; Andersen et  al.
2011; Dohmen et al. 2011; Thöni et al. 2012; see also Table 5).24 We also control for
location (Shanghai) to take into account possible cultural differences between both
municipalities.

All results presented in Table  6 appear robust. The CEOs are more cooperative
in PD and less hawkish in BSS and the Chicken game compared to the CGs, even
when we control for conceivable confounding effects. The main variable of interest
is the dummy variable CEOs, which is significant for PD and BSS at the 5% level
and at 1% for Chicken. The direction is the one expected from the previous analysis.
All effects are substantial. Keeping all other variables at their averages, the prob-
ability for defection in PD decreases by 0.12 when a CEO makes the strategic choice
compared to the probability for defection by the CGs. The probabilities for Hawk in
BSS and Chicken are even further reduced, namely by 0.13 and 0.18.

Except for the CEO variable, none of the other variables is consistently signifi-
cant. Family income has a significant negative effect on hawkish behavior in BSS,
which may reflect a higher degree of generosity or lack of care for the experimen-
tal money in this game. However, there is no significant income effect in the other
games, suggesting that we should be cautious not to draw too strong conclusions

Table 6 Average percentage play of strategies in the games

The suffix letter in the game acronyms indicates frame: A abstract, F field. Number of observations in
parentheses. Significance levels in Chi square tests, *p value < 0.1; **p value < 0.05; ***p value < 0.01

Game and frame CEOs: Average playing
Defect or Hawk

CGs: Average playing
Defect or Hawk

Nash Equilib-
rium Predic-
tionNE

PDA** 44.6 (101) 59.4 (101) 100
PDF* 39.3 (99) 52.5 (99) 100
BSSA** 62.4 (101) 75.2 (101) 60
BSSF*** 61.2 (99) 79.8 (99) 60
CA*** 48.5 (101) 73.3 (101) 67
CF* 56.6 (99) 69.7 (99) 67

24 Note that the effects of these variables could either be direct or indirect. For instance, education might
correlate with cognitive ability and gender with risk aversion which indirectly can affect the behavior
in the strategic games. Note that even if we have matched our sample groups insofar as possible with
respect to these variables, there is still individual variation that might correlate with the dependent vari-
able.

170 H. J. Holm et al.

1 3

from this observation.25 The frame is insignificant in all games, which suggests that
the underlying game is more important in explaining individual behavior than the
framing of the decision.

5.2 Beliefs

The observed behavioral differences may simply reflect different preferences.
Another possibility is that players’ beliefs about others’ choices differ and that sub-
jects aim to optimize their own choices in response to these beliefs with or with-
out regard to social preferences. We use data from the belief elicitation task to shed
some light on the question of what is more likely to guide players’ behavior.

In Table 9 we present the average percentage the subjects believed that the other
players choose Defect or Hawk in the respective games.26 Compared to the CGs, the
CEOs believe that other subjects defect on average less and are less hawkish. Hence,
the CEOs’ beliefs about others’ behavior differ from the CGs in the same way as
they play the games. The difference in beliefs is significant in four out of the six
tasks. The difference is especially strong in PD.

With regard to the closeness to NE there is no consistent pattern. The beliefs
of the CEOs and the CGs are on average almost equally close to NE in BSS and
Chicken when abstractly framed. When there is a significant difference, the CGs’
beliefs about others’ choices are closer to NE than those of the CEOs.

5.2.1 Difference in beliefs: a regression analysis

We now inspect whether these inter-group differences in beliefs about others’ behav-
ior are robust to the inclusion of the demographic variables introduced earlier. Since
the dependent variable is proportional, we run a fractional response regression as
suggested by Papke and Wooldridge (1996).

Table 10 presents the regression results in terms of average partial effects, which
have a similar interpretation as linear regression coefficients without compromis-
ing the non-linear relationship (Gallani et al. 2016). The negative sign for the CEO
variable indicates that the CEOs generally tend to believe that co-players defect less
and play less hawkishly than the CG believe, even when we control for demographic

25 It can also be noted that if family income is interacted with the CEO variable the interaction term is
insignificant for all games.
26 In the abstract frame subjects were asked to guess how many percent of subjects chose “Option A” in
the game they just had played. In the field frame subjects guessed about the corresponding field alterna-
tives (e.g., “City”). Option A and the paralell field alternatives corresponded to “Cooperate” and “Hawk”
in PD, BSS, and Chicken, respectively. It is then assumed that the subjects’ believed that the residual
percentage chose Defect and Dove, respectively. We use “belief of average percentage belief in Defect/
Hawk” to simplify the presentation, but the reader should know that framing effects may play a role in
how such questions are formulated. The reader should also know that because of the asymmetry in BSS
(discussed in Sect.  3.2) it is assumed that if a subject believes that q percent played strategy A (i.e.,
Hawk) as Row players, it implies that the subject believes that the same percent play strategy B (Hawk)
as Column players. We do not claim that such an assumption is entirely without complications but we
think it is the most natural interpretation given how the instructions were formulated.

171

1 3
Strategic decisions: behavioral differences between CEOs…

factors. The variable is strongly significant in PD, but not significant in the other
games. The frame appears to have affected beliefs in Chicken substantially, with the
field frame inducing the players to form more hawkish beliefs. There are no other
strong predictors of beliefs. The conclusion is that the difference in beliefs between
CEOs and the CG is a robust finding in PD, and for this game, we can firmly reject
null hypothesis 2. For the other games, the CEOs’ beliefs appear somewhat less

Table 7 Probabilities for outcomes and expected payoffs

2nd, 3rd and 4th column contain probabilities for different possible outcomes and the numbers in paren-
theses are the sum of both players’ payoffs in the outcome. 5th column contains expected earnings for the
two-player pair. *Different strategies in BSS presumes that strategies are referred to as hawkish or dovish
(see Sect. 3.2)

Game/group Probability that both
play Defect or Hawk
(pair payoff, SEK)

Probability that both
play cooperate or
dove

Probability that play-
ers choose different
strategies*

Expected payoff
for a pair (SEK)

PD/CEO 0.176 (200) 0.336 (500) 0.487 (450) 423
PD/CG 0.314 (200) 0.194 (500) 0.493 (450) 381
BSS/CEO 0.384 (0) 0.144 (0) 0.471 (1000) 471
BSS/CG 0.601 (0) 0.051 (0) 0.349 (1000) 349
C/CEO 0.276 (0) 0.226 (600) 0.499 (750) 509
C/CG 0.511 (0) 0.081 (600) 0.408 (750) 354

Table 8 Behavior: marginal
effects

Results from logistic regressions. Robust standard errors in paren-
theses, *p < 0.1, **p < 0.05, ***p < 0.01

(1) (2) (3)
Defect Hawk_BSS Hawk_Chicken

CEO − 0.123**
(0.056)

− 0.127**
(0.051)

− 0.177***
(0.054)

Male 0.044
(0.067)

− 0.078
(0.057)

− 0.053
(0.065)

Age − 0.001
(0.004)

0.005
(0.003)

− 0.000
(0.003)

School − 0.013
(0.011)

0.008
(0.010)

0.019*
(0.011)

Income − 0.006
(0.008)

− 0.015***
(0.006)

− 0.003
(0.007)

Shanghai − 0.010
(0.065)

− 0.113*
(0.060)

− 0.030
(0.064)

Frame Abst 0.064
(0.051)

− 0.016
(0.047)

− 0.024
(0.050)

Wald chi2 13.189 25.414 19.758
Prob > chi2 0.068 0.001 0.006
Pseudo R2 0.025 0.049 0.039
N 400 400 400

172 H. J. Holm et al.

1 3

hawkish compared to the CGs’, but the statistical relationships are too weak to reject
null hypothesis 2 in these games. It is difficult to know exactly why this difference
exists, but one possibility is that in PD the trade-off between self-interest and effi-
ciency is more evident than in BSS and Chicken, where issues of coordination are
also involved. The additional complexity in the latter situations may blur the rela-
tionship between beliefs and behavior. We will return to this idea in the next section.

5.2.2 Beliefs and behavior

The impact of beliefs on behavior in games is not straightforward but depends on
underlying motivations and preferences. Hence, the individual response to a cer-
tain belief depends on preferences and the underlying model of behavior assumed.
However, when controlling for beliefs in a logit regression, the results indicate that
beliefs do in fact matter for the behavior in PD and BSS (see Appendix 2A).

5.2.3 Best responses to beliefs

One measure of strategic sophistication is a player’s ability to best respond to his
own beliefs about other players’ strategy choices. Our design with belief elicitation
allows for non-trivial analyses of best responses in BSS and the Chicken game since
in these games both strategies are possible best responses contingent on the subject’s
belief. If selfish preferences are assumed, then Hawk is the best response in BSS if
the subject believes that less than 60 percent of their co-players play Hawk (given
the assumptions outlined in Sect.  3.2.). The corresponding number for Chicken is
67 percent. In BSS only 45 percent of the CEOs and 41 percent of the CGs best
responded. The percentages for Chicken are 51 and 62, respectively. In Chicken, the
difference in proportions is significant, which suggest that CEOs best respond less
frequently than the CGs in Chicken. However, when controlling for other variables

Table 9 Descriptive data on beliefs

A abstract, F field. Number of observations in parentheses. Significance levels in the leftmost column
concern differences in means in beliefs of Defect and Hawk between CEOs and CGs (t-tests). The 2nd
and 3rd column contain the average percentages the subjects believed that the other players choose
Defect or Hawk. Significance levels in the rightmost column indicate differences in mean deviation in
beliefs from NE (t tests). *p value < 0.1; **p value < 0.05; ***p value < 0.01

Game and frame CEOs: belief of average
playing Defect or Hawk

CGs: belief of average play-
ing Defect or Hawk

Average deviation
from NE CEOs/
CGs

PDA*** 46.3 (101) 54.2 (101) 53.7/45.8***
PDF*** 47.0 (99) 55.7 (99) 53.0/44.3***
BSSA 57.2 (101) 60.0 (101) 14.1/15.8
BSSF** 56.8 (99) 62.8 (99) 12.6/12.9
CA 49.7 (101) 50.7 (101) 19.5/19.0
CF** 54.0 (99) 59.3 (99) 17.8/13.1***

173

1 3
Strategic decisions: behavioral differences between CEOs…

there is no significant difference in best responses in any of the two games (see
Appendix  2B). To sum up, the statistical evidence for differences in selfish best
responses to belief is weak. For a given set of beliefs, there is some evidence that
neither CEOs nor CGs is especially inclined to selfish best responses. This means
that hypothesis 3 cannot be rejected.

5.2.4 Accuracy of beliefs

In a final step, we compare the accuracy of the CEOs’ beliefs with the accuracy
of those of the CGs. Accurate beliefs about others’ behavior are essential in order
to generate realistic business plans and profitable strategies for firms. Our findings
indicate that the CEOs have more accurate beliefs about their co-player’s behavior
than the CGs (see Appendix  2C). Here it is important to stress that the beliefs for
CEOs concerned other CEOs, while beliefs for the CG concerned fellow citizens,
we are comparing the accuracy of beliefs in reference to different groups. Hence,
the question posed is whether CEOs have developed behavior and systems of beliefs
that make them more accurate in their predictions of other CEOs’ strategic behav-
ior than the CGs are in their predictions about the strategic behavior of the general
population. Further investigation into this matter (see Appendix  2C) suggests that
the CEOs’ superiority in accuracy depends on the target group for the beliefs. Thus,
CEOs are better in predicting the average behavior of their own group, but they are
not better at predicting the average behavior of society at large. One might think that
since the CEOs are a more homogenous group the superior accuracy might be linked
to a substantially higher variance of beliefs in the GG group, but this is not the case.

5.3 Concerns and robustness tests

We conduct a number of additional tests to scrutinize the robustness of our main
findings along various dimensions (tests and results are available online as Sup-
plementary Material). First, we have explored the potential influence of the defined
focus groups. As can be expected in a random sample, the CG did also include a
number of individuals (n = 43) who indicated that they are currently employed as
CEOs. To test whether our results are robust if we exclude these 43 CEOs from the
CGs and include them in the sample of CEOs, we run regressions similar to those
reported in Table  8 above. Our results show that the magnitude of the CEO coef-
ficients increases for all games, and in BSS the significance level increases from the
5% level to 1% (see Appendix 3, Table A7). We report similar tests on differences in
beliefs and find that the results are robust (see Appendix 3, Tables A8 and A9).

Further, a skeptic may be concerned about a potential ‘location effect’, as CEOs
‘played’ the strategic games and made their choices in their workplaces, whereas
CGs did so in their homes. There were also subtle differences in the way the oppo-
nent was described, with the CEOs being informed that X “is a CEO of a Chinese
firm and is a Chinese citizen”, while the CGs were informed that X “is a Chinese
citizen” (see the instructions). Theoretically, referring to a more exclusive group
may create stronger in-group emotions, which in principle can drive differences in

174 H. J. Holm et al.

1 3

results. To explore whether these effects are likely to influence our results we have
compared the behavior of control group CEOs with non-CEO control group mem-
bers (both interviewed in their home and both stating beliefs regarding other fellow
citizens), but did not detect substantive differences in comparison with our baseline
results (see Appendix 4, Table A10–A12).

Then, we have explored whether differences in average cooperativeness and qual-
ity of education between both groups may have influenced our results (see Appen-
dix 5). Yet we can show that both factors are unlikely to have a significant influence
on our baseline findings. Further, we have ruled out that extreme values (Appen-
dix 6) or interviewer effects (Appendix 7) explain our findings. Further, we have also
applied narrower definitions of the CEOs, as many of the subjects are also owners or
even founders of their companies. A focus on these sub-groups, however, does not
generate substantively different results (Appendix  8). Finally we have explored the
possible effect of differences in the CEOs’ competitive environment on the strategic
choices made in the game but could not identify such association (Appendix 9).

In sum, we feel confident that our results accurately reflect differences between
CEO behavior and the behavior of others, less familiar and experienced with strate-
gically relevant decisions.

Table 10 Beliefs: average
partial effects

Results from fractional response regressions. Belief_PD, Belief_
BSS, Belief_C represent the subjects’ belief of the proportion play-
ing Defect (PD) and Hawk (BSS and Chicken), respectively. Coef-
ficients represent average partial effects. Robust standard errors in
parentheses, *p < 0.1, **p < 0.05, ***p < 0.01

(1) (2) (3)
Belief_PD Belief_BSS Belief_C

CEO − 0.231***
(0.051)

− 0.082
(0.050)

− 0.049
(0.045)

Male − 0.032
(0.065)

− 0.029
(0.067)

0.019
(0.056)

Age 0.002
(0.003)

0.001
(0.003)

0.001
(0.003)

School − 0.003
(0.010)

− 0.001
(0.011)

0.013
(0.009)

Income 0.039
(0.084)

− 0.101
(0.078)

− 0.113*
(0.062)

Shanghai − 0.089
(0.056)

− 0.024
(0.056)

0.016
(0.049)

Frame_Abst − 0.029
(0.045)

− 0.028
(0.045)

− 0.159***
(0.041)

Wald chi2 25.930 9.178 28.087
Prob > chi2 0.001 0.240 0.000
Pseudo R2 0.006 0.002 0.005
N 400 400 400

175

1 3
Strategic decisions: behavioral differences between CEOs…

6 Explanations and implications

One of the strongest results of this study is that CEOs tend to be more oriented
towards cooperation and non-aggressive behavior than other people, which leads
to substantial differences in expected earnings. As shown in Table  7, the expected
payoffs of the CEOs were substantially higher than for the CGs. If these observed
behavioral differences reflect how CEOs and CGs interact in real strategic settings,
then this implies the existence of a “CEO culture” of norms and beliefs generating
substantial returns, not only to the CEOs’ own firms but also to society as a whole.27

Given that the orientation towards efficiency among CEOs outside experimental
tasks is real it is natural to ask why this is so. Our data is not designed to offer con-
clusive answers, but we can speculate as to some possible underlying factors in addi-
tion to the mechanisms discussed in Sect. 3. First, the observed behavioral difference
may be linked to market activity per se. Virtually all transactions on private markets
involve voluntary agreements of at least two parties, which means that such trans-
actions are inherently prosocial and may generate—or may attract and reinforce—
a mindset oriented towards identifying efficiency enhancing win–win solutions.28
The observed behavioral differences may also be related to the CEO’s leadership
role within an organization. Social image and identification with the organization
may be crucial for a business leader to mobilize support and loyalty from employees
and business partners. Such experience may frame a CEO’s mindset and generate
less aggressive and more prosocial choices in our experimental tasks (Akerlof and
Kranton 2005; Benabou and Tirole 2006). Finally, CEOs may generally pay more
attention to the responses of their ‘followers’ to their own actions. If this is the case,
CEOs may have developed a certain style to lead ‘by example’ or ‘by sacrifice’
(Hermalin 1998), which can involve costly cooperative or non-hawkish actions.29

What are the implications of our findings? How do our results inform the lit-
erature on the interplay between institutions and moral values and norms (Bowles
1998)? Key ingredients for a successful institutional structure are what Douglass
North denotes as “informal constraints”, which among other things, consist of
“conventions and codes of behavior”, including norms (North 1990/2007, p. 4).
To explain the development of norms is a highly complex problem involving the
interplay between formal rules and informal constraints. However, as North points
out: “Even if we do not possess a good explanation for social norms, we can model
wealth-maximizing norms in a game theoretic context. That is, we can test, empiri-
cally, what sorts of informal constraints are most likely to produce cooperative

27 We do not claim that choosing certain strategies in experimental games necessarily reflects how CEOs
run their firms. It is possible that the game choices reflect personal attitudes, which are unrelated to the
choices made for their firms. In any case the potential connection between game choices and firm charac-
teristics and outcomes is an interesting empirical question that ought to be addressed in future research.
28 It should be stressed that our use of the term “prosocial” and win–win solutions only concerns the
involved parties. We cannot say anything about potential prosocial behavior if a passive third party is
affected by a negative externality, as in Falk and Szech (2013) and Bartling et al. (2015).
29 This mechanism has gotten support in experiments where one player is assigned the leader role and
the other the follower role (Potters et al. 2007).

176 H. J. Holm et al.

1 3

behavior….” (Ibid., p. 43). We partly follow this approach by using games to study
cooperative and non-aggressive behavior. We then analyze how the norms indirectly
revealed by the strategy choices in these games differ between subjects embedded
in different environments or “cultures”: Those heavily involved in strategic private
market decisions (the CEOs) and those who are less likely to make socially relevant
strategic decisions (the CG). While we did not strive to identify a definite causal
explanation, the findings open the way for hypotheses as to how familiarity with
strategic decision-making in private markets can affect soft institutions in a society.
One can hypothesize that a frequent encounter with strategic market decisions fos-
ters the emergence of norms favoring efficiency. Furthermore, if the within-group
interaction is more pronounced than the interaction between distinct social groups,
it would be reasonable to assume that cultures relying heavily on strategic market
exchange will grow faster than others and may “export” wealth-creating norms to
the rest of the society.30

The orientation towards efficiency among our private company CEOs could
imply that they also, by generating efficient informal constraints and within-group
norms of cooperation, they can also shape institutions in the rest of the economy
over time. Our finding may serve as a step in increasing our understanding of how
economic institutional development can be “channelled” through private markets in
transition economies such as China.31

7 Conclusion

As the health of most economies depends on the aggregate behavior of their busi-
ness leaders and CEOs, it is a crucial task for economic theory to understand and
predict the behavior of these individuals. Equally important, it is of interest to learn
in what way CEOs may influence the norms in the societies they live in. This ques-
tion can be related to the broader debate as to how private markets and a frequent
reliance on market exchange affect norms and values.

We investigate the strategic decision-making of private-firm CEOs in well-
defined games. In particular, we study whether CEOs differ from that of other com-
parable subjects, in what we believe to be the most ambitious study of CEO’s behav-
ior in strategic games thus far. For this research, we recruited a stratified random
sample of 200 CEOs and a carefully selected sample of 200 control group members
to participate in three incentivized strategic games, the Prisoner’s Dilemma, the Bat-
tle-of-the-Sexes, and the Chicken game. We find substantial differences in behavior

30 This efficiency orientation among private CEOs is likely to be transmitted to actors in the surrounding
society, both because its relative success may stimulate others to imitate their strategies and also because
as the private sector grows in importance, its leaders have the ability and power to persuade others to
accept their own norms and values (e.g., politicians, bureaucrats employees).
31 Nee and Opper (2012) argue that much of the recent institutional change in China is a bottom up pro-
cess, driven by private entrepreneurs. This conclusion is supported by a multitude of historical facts, reg-
istry data and observations from interviews. A more formal agent-based model of this bottom-up process
is offered in DellaPosta et al. (2017).

177

1 3
Strategic decisions: behavioral differences between CEOs…

between the CEOs and the control group, but not in the way many would expect.
The CEOs were not in general closer to the Nash equilibrium prediction (assum-
ing selfish preferences). On the contrary, the average control group behavior was
closer to the Nash equilibrium in the majority of the games and did not best respond
less frequently to their beliefs. The most striking and consistent pattern was that the
CEOs had higher expected earnings than the comparison group in all the games. The
CEOs cooperated more and played less hawkishly compared to the control group,
no matter how the game was framed (abstractly or with a narrative). Compared to
the control group the CEOs’ also had significantly higher average beliefs that others
would cooperate in the Prisoner’s Dilemma.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 Interna-
tional License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution,
and reproduction in any medium, provided you give appropriate credit to the original author(s) and the
source, provide a link to the Creative Commons license, and indicate if changes were made.

References

Akerlof, G., & Kranton, R. (2005). Identity and the economics of organizations. Journal of Economic
Perspectives, 19, 9–32.

Alger, I., & Weibull, J. W. (2013). Homo moralis—preference evolution under incomplete information
and assortative matching. Econometrica, 81, 2269–2302.

Andersen, S., Ertac, S., Gneezy, U., Hoffman, M., & List, J. A. (2011). Stakes matter in ultimatum games.
American Economics Review, 101, 3427–3439.

Andreoni, J., & Bernheim, B. D. (2009). Social image and the 50–50 norm: A theoretical and experimen-
tal analysis of audience effects. Econometrica, 77, 1607–1636.

Åstebro, T., Herz, H., Nanda, R., & Weber, R. A. (2014). Seeking the roots of entrepreneurship: Insights
from behavioral economics. Journal of Economic Perspectives, 28, 49–69.

Bartling, B., Weber, R. A., & Yao, L. (2015). Do markets erode social responsibility? Quarterly Journal
of Economics, 119, 219–266.

Benabou, R., & Tirole, J. (2006). Incentives and prosocial behavior. American Economic Review, 96,
1652–1678.

Benabou, R., & Tirole, J. (2010). Individual and corporate social responsibility. Economica, 77, 1–19.
Bergstrom, T. C. (2002). Evolution of social behavior: Individual and group selection. Journal of Eco-

nomic Perspectives, 16, 67–88.
Bernardo, A. E., & Welch, I. (2001). On the evolution of overconfidence and entrepreneurs. Journal of

Economics & Management Strategy, 10, 301–330.
Bernheim, B. D. (1994). A theory of conformity. Journal of Political Economy, 102, 841–877.
Bertrand, M., & Schoar, A. (2003). Managing with style: The effect of managers on firm policies. Quar-

terly Journal of Economics, 118, 1169–1208.
Blanco, M., Engelmann, D., Koch, A. K., & Normann, H.-T. (2010). Belief elicitation in experiments: Is

there a hedging problem? Experimental Economics, 13, 412–438.
Bolton, P., Brunnermeier, M. K., & Veldkamp, L. (2013). Leadership, coordination, and corporate cul-

ture. The Review of Economic Studies, 80, 512–537.
Bowles, S. (1998). Endogenous preferences: The cultural consequences of markets and other economic

institutions. Journal of Economic Literature, 36, 75–111.
Bowles, S., & Gintis, H. (2011). A cooperative species: Human reciprocity and its evolution. Princeton,

NJ: Princeton University Press.
Cooper, D. J. (2006). Are experienced managers experts at overcoming coordination failure? B.E. Jour-

nal of Economic Analysis & Policy (Advances), 6.
Cooper, D. J., Kagel, J. H., Lo, W., & Gu, Q. L. (1999). Gaming against managers in incentive systems:

Experimental results with Chinese students and chinese managers. American Economic Review, 89,
781–804.

http://creativecommons.org/licenses/by/4.0/

178 H. J. Holm et al.

1 3

Cooper, D. J., & Saral, K. J. (2013). Entrepreneurship and team participation: An experimental study.
European Economic Review, 59, 126–140.

Crawford, V. P., Gneezy, U., & Rottenstreich, Y. (2008). The power of focal points is limited: Even
minute payoff asymmetry may yield large coordination failures. American Economic Review, 98,
1443–1458.

Croson, R., & Gneezy, U. (2009). Gender differences in preferences. Journal of Economic Literature, 47,
1–27.

Cubitt, R. P., Drouvelis, M., & Gächter, S. (2011). Framing and free riding: Emotional responses and
punishment in social dilemma games. Experimental Economics, 14, 254–272.

DellaPosta, D., Nee, V., & Opper, S. (2017). Endogenous dynamics of institutional change. Rationality
and Society, 29, 5–48.

Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. (2011). Individual risk attitudes:
Measurement, determinants, and behavioral consequences. Journal of the European Economic
Association, 9, 522–550.

Ellickson, R. (1991). Order without law. Cambridge, MA: Harvard University Press.
Elston, J. A., Harrison, G. W., & Rutström, E. E. (2006). Experimental economics, entrepreneurs and the

entry decision. UCF Economics Department Working Paper No. 6, 2006.
Engelmann, D., & Strobel, M. (2004). Inequality aversion, efficiency, and maximin preferences in simple

distribution experiments. American Economic Review, 94, 857–869.
Falk, A., & Szech, N. (2013). Morals and markets. Science, 340, 707–711.
Fehr, E., & List, J. (2004). The hidden costs and returns of incentives: Trust and trustworthiness among

CEOs. Journal of the European Economic Association, 2, 743–771.
Fehr, E., & Schmidt, K. M. (1999). A theory of fairness, competition, and cooperation. Quarterly Journal

of Economics, 114, 817–868.
Foss, N. J. (2001). Leadership, beliefs and coordination: An explorative discussion. Industrial and Cor-

porate Change, 10, 357–388.
Fréchette, G. R. (2015). Laboratory experiments: Professionals versus students. In G. R. Fréchette & A.

Schotter (Eds.), Handbook of experimental economic methodology (360–390). Oxford: Oxford Uni-
versity Press.

Gächter, S., & Renner, E. (2010). The effect of (incentivized) belief elicitation in public good experi-
ments. Experimental Economics, 13, 364–377.

Gallani, S., Krishnan, R., & Wooldridge, J. M. (2016). Applications of fractional response model to the
study of bounded dependent variables in accounting research. Harvard Business School working
paper, 016.

Glaeser, E. L., Laibson, D. I., Scheinkman, J. A., & Soutter, C. L. (2000). Measuring trust. The Quarterly
Journal of Economics, 115, 811–846.

Güth, W., Schmidt, C., & Sutter, M. (2007). Bargaining outside the lab: A newspaper experiment of a
three-player ultimatum game. Economics Journal, 117, 449–469.

Harrison, G. W., & List, J. (2004). Field experiments. Journal of Economic Literature, 42, 1009–1055.
Hayward, M. L., Shepherd, D. A., & Griffin, D. (2006). A hubris theory of entrepreneurship. Manage-

ment Science, 52, 160–172.
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Gintis, H., McElreath, R., et al. (2001). In search of homo

economicus: Experiments in 15 small-scale societies. American Economic Review, 91, 73–79.
Hermalin, B. (1998). Toward a theory of leading by example. American Economic Review, 88,

1188–1206.
Holm, H. J., Opper, S., & Nee, V. (2013). Entrepreneurs under uncertainty: An economic experiment in

China. Management Science, 59, 1671–1687.
Hvide, H. K., & Panos, G. A. (2015). Risk tolerance and entrepreneurship. Journal of Financial Econom-

ics, 111, 200–223.
Kagel, J., & Roth, A. (1995). The handbook of experimental economics. Princeton, NJ: Princeton Univer-

sity Press.
Kihlstrom, R. E., & Laffont, J.-L. (1979). A general equilibrium entrepreneurial theory of firm formation

based on risk aversion. Journal of Political Economy, 87, 710–748.
Koudstaal, M., Sloof, R., & Van Praag, M. (2016). Risk, uncertainty, and entrepreneurship: evidence

from a lab-in-the-field experiment. Management Science, 62, 2897–2915.
Kurzban, R., & Houser, D. (2005). Experiments investigating cooperative types in humans: A comple-

ment to evolutionary theory and simulations. Proceedings of the National Academy of Sciences of
the United States of America, 102, 1803–1807.

179

1 3
Strategic decisions: behavioral differences between CEOs…

Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and
critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76,
149–188.

Marshall, A. (1890/1920). Principles of economics, 8th ed. London: Macmillan & Co.
Masclet, D., Colombier, N., Denant-Boemont, L., & Lohéac, Y. (2009). Group and individual risk prefer-

ences: A lottery-choice experiment with self-employed and salaried workers. Journal of Economic
Behavior & Organization, 70, 470–484.

Montmarquette, C., Rullière, J.-L., Villeval, M. C., & Zeiliger, R. (2004). Redesigning teams and incen-
tives in a merger. An experiment with managers and students. Management Science, 50, 1379–1389.

Nee, V., Holm, H. J., & Opper, S. (2018). Learning to trust: From relational exchange to generalized trust
in China. Organization Science, 29, 969–986.

Nee, V., & Opper, S. (2012). Capitalism from below: Markets and institutional change in China. Cam-
bridge, MA: Harvard University Press.

North, D. (1990/2007). Institutions, institutional change, and economic performance. Cambridge, UK:
Cambridge University Press.

Ockenfels, A., & Weimann, J. (1999). Types and patterns: An experimental East-West-German compari-
son of cooperation and solidarity. Journal of Public Economics, 71, 275–287.

Opper, S., Nee, V., & Holm, H. J. (2017). Risk aversion and guanxi activities: A behavioral analysis of
CEOs in China. Academy of Management Journal, 60, 1504–1530.

Palacios-Huerta, I., & Volij, O. (2008). Experentia docet: Professionals play minimax in laboratory
experiments. Econometrica, 76, 71–115.

Papke, L. E., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with
an application to 401 (K) plan participation rates. Journal of Applied Econometrics, 11, 619–663.

Parravano, M., & Poulsen, O. (2015). Stake size and the power of focal points in coordination games:
Experimental evidence. Games and Economic Behavior, 94, 191–199.

Potters, J., Sefton, M., & Vesterlund, L. (2007). Leading by example and signaling in voluntary contribu-
tion games: An experimental study. Economic Theory, 33, 169–182.

Schelling, T. C. (1960). The strategy of conflict. Cambridge, USA: Harvard University Press.
Shleifer, A. (2004). Does competition destroy ethical behavior? American Economic Review Papers and

Proceedings, 94, 414–418.
Smith, J. M. (1982). Evolution and the theory of games. Cambridge, UK: Cambridge University Press.
Thöni, C., Tyran, J.-R., & Wengström, E. (2012). Microfoundations of social capital. Journal of Public

Economics, 96, 636–643.
Tirole, J. (1988). The theory of industrial organization. Cambridge, MT: MIT Press.
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science,

211, 453–458.
Van de Ven, A. H., Sapienza, H. J., & Villanueva, J. (2007). Entrepreneurial pursuits of self- and collec-

tive interests. Strategic Entrepreneurship Journal, 1, 353–370.
Van Praag, M., & Cramer, J. S. (2001). The roots of entrepreneurship and labour demand: Individual abil-

ity and low risk aversion. Economica, 68, 45–69.
Von Neumann, J., & Morgenstern, O. (1944). The theory of games and economic behavior. Princeton,

NJ: Princeton University Press.
Wu, B., & Knott, A.-M. (2006). Entrepreneurial risk and market entry. Management Science, 52,

1315–1330.

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published
maps and institutional affiliations.

180 H. J. Holm et al.

1 3

Affiliations

Håkan J. Holm1  · Victor Nee2 · Sonja Opper1

* Håkan J. Holm
Hakan.Holm@nek.lu.se

Victor Nee
Victor.Nee@cornell.edu

Sonja Opper
Sonja.Opper@nek.lu.se

1 Department of Economics, School of Economics and Management, Lund University, P.O.
Box 7082, 22007 Lund, Sweden

2 Department of Sociology, Cornell University, Ithaca, USA

http://orcid.org/0000-0001-5783-2463

Reproduced with permission of copyright owner.
Further reproduction prohibited without permission.

• Strategic decisions: behavioral differences between CEOs and others

Abstract
1 Introduction
2 Related literature
3 Theory and hypotheses
3.1 Prisoner’s Dilemma
3.2 Battle-of-the-sexes
3.3 Chicken
3.4 Hypotheses
4 Research strategy and design
4.1 Tasks and treatments
4.2 Sampling and descriptive statistics
4.3 Execution
5 Results
5.1 Behavior in the games
5.1.1 Probabilities for outcomes and expected payoffs
5.1.2 Regression analysis
5.2 Beliefs
5.2.1 Difference in beliefs: a regression analysis
5.2.2 Beliefs and behavior
5.2.3 Best responses to beliefs
5.2.4 Accuracy of beliefs
5.3 Concerns and robustness tests
6 Explanations and implications
7 Conclusion
References

O R I G I N A L P A P E R

How Does Ethical Leadership Trickle Down? Test
of an Integrative Dual-Process Model

Zhen Wang1 • Haoying Xu1 • Yukun Liu2

Received: 29 April 2016 / Accepted: 13 October 2016 / Published online: 20 October 2016

� Springer Science+Business Media Dordrecht 2016

Abstract Although the trickle-down effect of

ethical

leadership has been documented in the literature, its

underlying mechanism still remains largely unclear. To

address this gap, we develop a cross-level dual-process

model to explain how the effect occurs. Drawing on social

learning theory, we hypothesize that the ethical

leadership

of high-level managers could cascade to middle-level

supervisors via its impact on middle-level supervisors’ two

ethical expectations. Using a sample of 69 middle-level

supervisors and 381 subordinates across 69 sub-branches

from a large banking firm in China, we found that middle-

level supervisors’ ethical efficacy expectation and unethi-

cal behavior–punishment expectation (as one form of eth-

ical outcome expectations) accounted for the trickle-down

effect. The explanatory role of middle-level supervisors’

ethical behavior–reward expectation (as the other form of

ethical outcome expectations), however, was not sup-

ported. The theoretical and practical implications are

discussed.

Keywords Ethical leadership � Ethical efficacy
expectation � Ethical outcome expectation �
Social learning theory

Introduction

Recent years have seen an onslaught of cases relating to

corporate fraud and scandals, inflicting great pain on

organizations and society. Against this background, an

increasing amount of attention has been paid to the topic of

ethical leadership in organizational research (Brown and

Treviño 2006; Treviño et al. 2014). Being defined as ‘‘the

demonstration of normatively appropriate conduct through

personal actions and interpersonal relationships, and the

promotion of such conduct to followers through two-way

communication, reinforcement, and decision making’’

(Brown et al. 2005, p. 120), ethical leadership has been

found to be positively related to a wide range of beneficial

outcomes, including task performance, citizenship behav-

iors, ethical conducts, and so forth (for systematic reviews,

see Bedi et al. 2015; Ng and Feldman 2015). Given these

positive outcomes, both researchers and practitioners have

engaged in identifying the antecedents of ethical leadership

and thus have accumulated a considerable body of evi-

dence (den Hartog 2015; Treviño and Brown 2014).

Among several streams of research, there is one suggesting

a ‘‘trickle-down’’ effect of ethical leadership, which argues

that ethical leadership of high-level leaders could cascade

downward and influence the ethical leadership of middle-

level supervisors (Mayer et al. 2009; Ruiz et al. 2011a, b;

Schaubroeck et al. 2012).

However, these accumulated studies on the trickle-down

effect of ethical leadership are limited in a critical way.

Although almost all studies have relied on social learning

& Yukun Liu
liuyukun@u.nus.edu

Zhen Wang

wangzhen@cufe.edu.cn

Haoying Xu

xuyingzhongshan@163.com

1
Department of Organization and Human Resources

Management, Business School, Central University of Finance

and Economics, 39 South College Road, Haidian District,

Beijing 100081, People’s Republic of China

2
Department of Management and Organization, NUS Business

School, National University of Singapore, B2-03, Biz 2

Building, 1 Business Link, Singapore 117592, Singapore

123

J Bus Ethics (2018) 153:691–705

https://doi.org/10.1007/s10551-016-3361-x

http://crossmark.crossref.org/dialog/?doi=10.1007/s10551-016-3361-x&domain=pdf

http://crossmark.crossref.org/dialog/?doi=10.1007/s10551-016-3361-x&domain=pdf

https://doi.org/10.1007/s10551-016-3361-x

theory to explain the mechanisms underlying the effect,

none of them has used social learning-related constructs to

test this account. As noted in a recent article by Sumanth

and Hannah (2014, p. 46), ‘‘in investigating the effects of

ethical leadership of higher level organizational leaders on

lower level leaders…though frequently theorized, we are
not aware of any research that has actually tested social

learning as a mediator in the cascading process.’’ The lack

of such research results in an unclear understanding of the

intermediate process through which the trickle-down effect

occurs. Given this research gap, the current study intends to

continue the momentum of research on the trickle-down

effect of ethical leadership and advance further to examine

its underlying mechanism, aiming to provide a better

understanding of how ethical leadership cascades from

high-level managers to middle-level supervisors within an

organization.

Specifically, we propose ethical efficacy expectation and

ethical outcome

expectation

1

as mediators to disentangle

the cascading process of ethical leadership. Social learning

theory emphasizes the importance of individual’s cognition

in the regulation of human behaviors and posits that ‘‘most

external influences affect behavior through intermediary

cognitive processes’’ (Bandura 1977, p. 160). In particular,

the changes in efficacy expectation and outcome expecta-

tion are the most important intermediate cognitive pro-

cesses that link external influences to behavioral changes

(Bandura 1977; Manz and Sims 1981). Given that our

focus is on the ethical realm, we concentrate on ethical

efficacy expectation and ethical outcome expectation in the

current research. Ethical efficacy expectation (i.e., ethical

efficacy) refers to ‘‘individuals’ belief in their ability to

mobilize the motivation, cognitive resources, and courses

of action necessary to execute ethical behavior’’ (Mitchell

and Palmer 2010, p. 92); ethical outcome expectation

represents ‘‘individuals’ perception of the likelihood that

an [ethical/unethical] behavior will lead to a particular

[reward or punishment] outcome’’ (Ashkanasy et al. 2006,

p. 450). Social learning theory holds that an individual’s

efficacy expectation and outcome expectation are suscep-

tible to the influence of role models (e.g., leaders) through

a vicarious learning process (Manz and Sims 1981). Thus,

it is reasonable to suggest that, the ethical leadership of

high-level managers, who oftentimes are regarded as role

models, will exert an influence on the ethical efficacy

expectation and ethical outcome expectation of middle-

level supervisors, which will in turn elicit their ethical

leadership

behaviors.

We tested our theoretical model using a sample from a

large banking firm. Results generally provided support to

our hypotheses. By conducting this research, we contribute

to the extant literature in three ways. First, this study

advances the existing research on the trickle-down effect of

ethical leadership by delineating the underlying mecha-

nisms. By considering ethical efficacy expectation and

ethical outcome expectation as mediators, the present study

provides a direct examination of the trickle-down effect of

ethical leadership from the social learning perspective.

Second, this study extends the research on ethical efficacy

by providing further insights into its nomological network.

In the early 1990s, Bandura (1991) suggested that moral/

ethical beliefs could be applied to ethical situations, sug-

gesting the existence of ethical efficacy. It is only recently,

however, that a few studies have formally conceptualized

and operationalized this construct and studied its relevance

to ethics (Arnaud and Schminke 2012; Hannah and Avolio

2010). Even so, research on ethical efficacy still remains

largely in its infancy, and thus warrants further investiga-

tion (Hannah et al. 2011). This said, the present study

addresses this call and enriches our understanding of eth-

ical efficacy. Third, this study also highlights the role of

ethical outcome expectation and advances the literature by

contextualizing it in the ethical leadership context (Ash-

kanasy et al. 2006; Treviño and Youngblood 1990), illu-

minating another important psychological mechanism that

could explain the function of ethical leadership. Taken

together, using social learning theory as a theoretical

framework, our research aims to answer the question how

ethical leadership of high-level managers trickles down to

influence the ethical leadership of middle-level supervisors.

Our research model is depicted in Fig. 1 as shown below.

Theory and Hypotheses

Manager Ethical Leadership and Supervisor Ethical

leadership

Social learning theory is based on the idea that an indi-

vidual learns by paying attention to and emulating the

attitudes, values, and behaviors of role models (Bandura

1977). As to the learning of ethical conducts in organiza-

tions, although individuals can rely on organization’s for-

mal regulations or norms to gain ethics-related knowledge,

they can also learn ethical conducts via a modeling process,

in which they look for role models in the organization and

emulate their ethical attitudes, values, and behaviors

(Brown et al. 2005). This modeling process not only

applies to followers who regard their leaders as role

models, but also applies to leaders themselves, who also

learn from their role models. Indeed, as Brown and Treviño

1
Consistent with the common practices in the management field

(e.g., Mitchell and Palmer 2010; Treviño et al. 2006), we used the

terms ethical and moral interchangeably in this paper.

692 Z. Wang et al.

123

(2006, p. 600) highlighted, ‘‘followers are not the only ones

who learn from models. Leaders learn from models too. By

observing an ethical role model’s behavior as well as the

consequences of their behavior, leaders should come to

identify with the model, internalize the model’s value and

attitudes, and emulate the modeled behavior.’’ Then it

comes to the question who would be leaders’ ethical role

models. A few studies have answered this question and

suggested that top managers or top executives in an orga-

nization could serve as ethical role models for middle-level

supervisors (see examples in Mayer et al. 2009; Ruiz et al.

2011a). The reasons supporting supervisors as ethical role

models for frontline employees, as suggested by existing

studies (Brown et al. 2005; Brown and Treviño 2006),

could also be extended to the dyadic relationships between

high-level managers and middle-level supervisors, in

which supervisors become followers of high-level man-

agers. Just like supervisors, having power, status, and the

control over the reward/punishment system, as well as

having personal characteristics such as being honest and

trustworthy, high-level managers are legitimate, attractive,

and credible to be regarded as ethical role models, from

whom supervisors could emulate the ethical conducts

(Bandura 1977). Based upon the above reasoning as well as

the findings in several existing studies (e.g., Mayer et al.

2009; Ruiz et al. 2011a, b; Schaubroeck et al. 2012), we

propose the trickle-down effect of ethical leadership of

high-level managers on their immediate supervisors. By

using high-level managers, we refer to managers whom

middle-level supervisors work closely and communicate

frequently with, but not those distant top executives. Our

rationale is that ethical role modeling is a ‘‘side by side’’

phenomenon (Weaver et al. 2005), and middle-level

supervisors have more chances to observe and imitate

ethical behaviors of their intimate leaders (i.e., high-level

managers), rather than those of top or executive managers

(Brown and Treviño 2014). We propose that:

Hypothesis 1 High-level managers’ ethical leadership

relates positively to middle-level supervisors’ ethical

leadership.

The Mediating Effect of Ethical Efficacy

Expectation

As an ethical cognition (Schaubroeck et al. 2012), ethical

efficacy expectation (i.e., ethical efficacy) represents indi-

viduals’ confidence in their ability to execute ethical

behaviors (Hannah and Avolio 2010; Mitchell and Palmer

2010). Unlike the trait-like general

efficacy expectation

which is more stable, ethical efficacy expectation is more

state-like, which indicates that it could be influenced to

change. Existing research has found that ethical efficacy

expectation is susceptible to external influences (Fischbach

2015; Hannah and Avolio 2010; May et al. 2013) and could

play an important role in ethics-relevant situations (Arnaud

and Schminke 2012; Lee et al. 2015). In the present study, we

consider ethical efficacy expectation as a crucial factor that

contributes to the cascading of high-level managers’ ethical

leadership. We analyze its role from two aspects as follows.

In one aspect, given that an ethical role model plays a

critical role in developing and strengthening one’s ethical

efficacy beliefs (Bandura 1991), we believe that high-level

managers’ ethical leadership would exert a positive influence

on middle-level supervisors’

ethical efficacy expectation.

According to the social learning theory, expectations of

efficacy are based on four sources of information: perfor-

mance accomplishments, vicarious experience, verbal per-

suasion, and emotional arousal, and these four sources could

be further influenced by different modes of induction (Ban-

dura 1977). Bandura presented a framework in which many

external factors induce sources of efficacy, which in turn

impacts efficacy. For instance, he argued that participant

modeling, performance desensitization, performance expo-

sure, and self-instructed performance could lead to

Research Model

Manager’s
Ethical

Leadership

Ethical Efficacy Expectation

Supervisor’s Ethical Efficacy Expectation

Ethical Outcome Expectation

Supervisor’s Ethical Behavior-Reward Expectation
Supervisor’s Unethical Behavior-Punishment Expectation

Supervisor’s

Ethical Leadership

Level 2

Level 1

Fig. 1 Research model

How Does Ethical Leadership Trickle Down?… 693

123

individuals’ performance accomplishments, which in turn

increase their efficacy, while suggestions, exhortation, self-

instruction, and interpretive treatments are inducements of

verbal persuasion, which in turn impacts efficacy. That said,

these four sources are not sub-dimensions of efficacy, rather,

they are more like the determinants of efficacy and the

mechanisms through which external factors influence effi-

cacy. In our research, based on this ‘‘mode of induc-

tion ? sources of efficacy ? efficacy’’ framework and the
function of ethical leadership as the mode of induction (e.g.,

participant modeling, suggestions), we theorized that ethical

leadership would induce individuals’ performance accom-

plishments, vicarious experience, verbal persuasion, and

emotional arousal, which would ultimately increase their

ethical

efficacy.

First, high-level managers’ ethical leadership can

enhance middle-level supervisors’ ethical efficacy expecta-

tion through performance accomplishments. Ethical man-

agers set high moral standards and hold their followers

accountable for ethical issues through using proactive and

effective measures (e.g., using reward systems, conveying

ethics-related messages) (Brown et al. 2005). These tactics

can ultimately help supervisors to achieve ethical perfor-

mance and thus enable them to have more opportunities to

obtain personal attainment and success in an ethics-related

domain. Second, supervisors’ ethical efficacy expectation

can be enhanced through their own vicarious experience

(Bandura 1991). In other words, supervisors can strengthen

their ethical efficacy expectation by vicariously observing

what others do when being faced with an ethics-related issue.

Ethical managers, given their legitimacy, attractiveness, and

credibility, of course are the role models whom supervisors

would learn from when facing an ethical issue (Brown et al.

2005). Third, verbal persuasion from ethical managers can

ameliorate supervisors’ ethical efficacy expectation. Ethical

managers usually would discuss business ethics or values

openly with their immediate supervisors and encourage them

to ask ‘‘what is the right thing to do’’ when making decisions

(Brown et al. 2005). Through this communication process,

ethical managers verbally convey the message to their

immediate supervisors that ethical behaviors are appropriate

and should be encouraged, hence enhancing supervisors’

ethical efficacy expectation (Bandura 1977). Fourth, ethical

managers define success not only by outcomes, but also by

the ways how the outcomes are achieved. This philosophy

helps alleviate followers’ affective concerns (e.g., anxiety or

stress) that usually relate to outcomes and thus enables fol-

lowers to pay more attention to the ethicality of their

approaches in achieving goals (Lee et al. 2015; Walumbwa

et al. 2011). Additionally, ethical managers expect, appre-

ciate, and support their immediate supervisors’ ethical

behaviors. Such expectations, appreciation, and support may

make supervisors feel proud and emotionally delighted when

exhibiting ethical behaviors, thus enhancing their ethical

efficacy expectation. Apart from the above four sources,

Hannah and Avolio (2010) recently added another one,

which involves providing and articulating organizational

support measures that could equip leaders with the confi-

dence to take ethical actions. By setting the ethical tone of the

work unit, stressing the importance of ethical behaviors and

using a reward system to incentivize ethical behaviors, eth-

ical managers can establish a social environment that pro-

vides the necessary support for their immediate supervisors

to adhere to ethical standards and engage in ethical behav-

iors. Such an ethical social environment could boost super-

visors’ confidence to behave ethically, thus enhancing their

ethical efficacy expectation (Schaubroeck et al. 2012).

In the other aspect, we propose that enhanced ethical

efficacy expectation will motivate middle-level supervisors

to exhibit ethical leadership behaviors. According to Ban-

dura (1997), how people behave is better predicted by their

beliefs about their capabilities rather than by their actual

capabilities. The same logic has also been extended to the

realm of moral behavior regulation by Bandura (1991),

who contended that ethical efficacy expectation is a critical

cognitive process for moral thoughts and behaviors. Ethical

efficacy expectation instills in supervisors a sense of con-

fidence in their capabilities to organize and mobilize the

cognitive resources to attain moral performance and regu-

late their behaviors to meet inner moral standards, thus

ensuring that they will engage in ethical behaviors even in

an ethically adverse situation (Hannah and Avolio 2010;

Mitchell and Palmer 2010). Extending to the case of

middle-level ethical supervisors, given that they bear the

‘‘moral manager’’ responsibility to hold followers

accountable for their ethical/unethical behaviors (Brown

et al. 2005), ethical efficacy expectation will be more

necessary for supervisors’ exhibition of ethical leadership

behaviors.

Summarizing the above two aspects of theorizing, we

conjecture that ethical efficacy expectation would serve as

an intermediate factor linking high-level managers’ ethical

leadership and their immediate supervisors’ ethical lead-

ership. We propose that:

Hypothesis 2 The relationship between high-level man-

agers’ ethical leadership and middle-level supervisors’

ethical leadership is mediated by middle-level supervisors’

ethical efficacy expectation.

The Mediating Effect of Ethical Outcome

Expectation

Outcome expectation is the other intermediate cognition in

social learning theory. Distinguished from efficacy expec-

tation, which represents one’s perceived ability to execute

694 Z. Wang et al.

123

a behavior, outcome expectation is one’s judgment con-

cerning the likelihood of outcomes resulting from a specific

behavior (Manz and Sims 1981). According to Bandura

(1977), the consequences of a behavior, which inform

individuals about the benefits of an appropriate conduct

and the costs of an inappropriate conduct, can facilitate

individuals’ learning from their role models. Extending this

notion to the ethical leadership area, we consider ethical

outcome expectation as a key factor in the trickle-down

process of ethical leadership and argue that high-level

managers’ ethical leadership can promote their immediate

supervisors’ ethical leadership through shaping their

expectations of ethical outcomes.

According to the social learning perspective, individuals

form their ethical outcome expectations through two ways:

(1) being rewarded for their own ethical behaviors or pun-

ished for their own unethical behaviors (direct learning) and

(2) observing or hearing about the consequences of others’

ethical or unethical behaviors in the workplace (vicarious

learning). The latter way, which stresses the role of models

in the process of learning, is the primary learning approach

(Bandura 1977). Having said that ethical leaders would

serve as role models for supervisors to learn ethical con-

ducts and given the above arguments on ethical outcome

expectations, we reason that ethical managers would play a

crucial role in affecting immediate supervisors’ ethical

outcome expectations. First, being ethical role models for

their immediate supervisors, ethical managers would lead

them to believe that managers’ ethical leadership has been

rewarded in the past. Indeed, as Bandura suggested, which

was also noted in Weiss (1977), a role model’s (i.e., leader)

attributes such as status, power, or perceived competence

would lead observers (i.e., followers) to believe that the

model’s behaviors have been rewarded in the past or are

appropriate in the situation, and this information would

affect observers’ expectations that engaging in similar

behaviors would lead to eventual rewards. Second, ethical

managers will shape immediate supervisors’ ethical out-

come expectations through rewarding those who behave

ethically and punishing those who behave unethically in the

workplace (Detert et al. 2007). When supervisors observe

the consequences of ethical behaviors and unethical

behaviors, they will learn what is considered appropriate

and inappropriate concerning ethical issues in the organi-

zation (Davis and Luthans 1980; Manz and Sims 1981). In

other words, these social cues would convey a message to

supervisors that behaving ethically is appropriate and will

be rewarded, whereas behaving unethically is inappropriate

and will be punished (Brown et al. 2005; Brown and Tre-

viño 2006). Accordingly, these outcome

expectations

would facilitate supervisor’s learning in an anticipatory

ethical manner and influence them to engage in more ethical

leadership behaviors.

To summarize, the reasoning above suggests that the

relationship between high-level managers’ ethical leader-

ship and middle-level supervisors’ ethical leadership could

be mediated by the ethical outcome expectations of middle-

level supervisors. To examine this mediating mechanism in

more depth, we further differentiate ethical outcome

expectation into two types: ethical

behavior–reward

expectation, which refers to the perceived likelihood of

getting rewards for ethical behaviors; and unethical

behavior–punishment expectation, which refers to the

perceived likelihood of getting punished for unethical

behaviors. We propose that:

Hypothesis 3 The relationship between high-level man-

agers’ ethical leadership and middle-level supervisors’
ethical leadership is mediated by middle-level supervisors’

ethical behavior–reward expectation.

Hypothesis 4 The relationship between high-level man-

agers’ ethical leadership and middle-level supervisors’
ethical leadership is mediated by middle-level supervisors’

unethical behavior–punishment expectation.

Method

Sample and Procedure

We collected multilevel and multi-source data from a large

banking company in China. This banking company has 120

sub-branches and 976 employees (including front desk

clerks and back office staff) in total. At the most basic level

of the bank, each sub-branch runs independently as a

standard operating team that consists of one supervisor

(i.e., middle-level supervisor in the organizational hierar-

chy) and several subordinates. Each sub-branch is under

the control of a high-level manager from the corresponding

regional branch of the bank. We chose to conduct the

research in the banking industry for a few reasons. First, it

provides a suitable context for researchers to do ethics-

related research. The banking industry is more likely to

induce employees to conduct unethical behaviors than

other industries because it is characterized by higher stress

and less regulation (Ruiz-Palomino et al. 2013). Although

ethics in this industry has garnered tremendous public

attention and urged government to adopt strict regulation

measures, the number of fraud and scandals is still on the

rise (Boatright 2010). As ethical leadership has been rec-

ognized as an effective way to restrain unethical conduct

and elicit ethical behaviors in the banking industry (e.g.,

Ruiz-Palomino et al. 2011, 2013; Sims and Brinkman

2002; Walumbwa and Schaubroeck 2009), it would be

meaningful to examine why and how ethical leadership

behavior cascades downward to shape a collective ethical

How Does Ethical Leadership Trickle Down?… 695

123

leadership culture in such an industry (Treviño et al. 2003).

Second, although most banking firms have ethics-related

policies, norms, or codes that regulate supervisors’

behaviors (Treviño et al. 2003), the boundaries between

ethical and unethical behaviors in many banks are still

quite vague, which makes supervisors more likely to learn

from their direct leaders (i.e., high-level managers) about

what is right and what is wrong in the organization. This

said, the cross-level influences of leadership on employees’

ethics become very relevant a phenomenon in banking

firms. Third, most banking firms have a typical hierarchical

structure in which managers in charge of higher-level

branches have control over resource allocation, goal set-

ting, and reward/punishment system, while supervisors in

charge of lower-level branches report directly to these

managers. This difference in authority between higher-

level managers and lower-level supervisors, along with the

frequent interactions between them, meet the prerequisite

of social learning process, making the trickle-down effect

of ethical leadership possible in the context of banking

firms.

Through personal social network and alumni contacts,

we approached 79 sub-branches. Our research assistants

communicated with the branch directors by phone and

explained the purpose of the survey in the hope of

obtaining their support. Three sub-branches refused to

participate, resulting in 76 sub-branches that participated.

To ensure the effectiveness of the survey, with the branch

supervisor’ help, we distributed and collected the ques-

tionnaires in person. Date collection was conducted during

the regular early meeting before business hours. Before

completing the questionnaires, all respondents were

informed of the research purpose and assured of confi-

dentiality. To reduce common method bias, we adminis-

tered two different sets of questionnaires, one for sub-

branch supervisors and the other one for their subordi-

nates. Specifically, sub-branch supervisors reported their

perceived ethical leadership of high-level managers, their

own ethical efficacy expectation and ethical outcome

expectation, whereas subordinates reported their perceived

ethical leadership of sub-branch supervisors. After com-

pleting the survey, each respondent forwarded his or her

questionnaire (enclosed in a sealed envelope) to the

researchers.

After excluding responses from seven sub-branches with

only one or two subordinates, we finally collected a sample

of 69 sub-branch supervisors (57.5 % of all sub-branch

supervisors) and 381 subordinates (39.0 % of all employ-

ees). In this matched sample, the average number of par-

ticipating subordinates per sub-branch supervisors was

5.52. Of the 69 supervisors, 47.8 % were women, 81.2 %

had a college degree, the average age was 39.61 years

(SD = 5.97), and the average tenure as a sub-branch

supervisor was 2.33 years (SD = 1.22). Among the sub-

ordinates, 61.9 % were women, 79.0 % had a college

degree, the average age was 31.49 years (SD = 6.37), and

the average dyadic tenure with the supervisor was

2.32 years (SD = 1.14).

Measures

Except for ethical outcome expectation, all other measures

in the study were originally in English. Applying the

standard translation and back-translation procedure (Brislin

1986), we translated the English scales into Chinese ver-

sions. Unless otherwise indicated, the measures were rated

by the respondents on a five-point Likert-type scale. The

anchors for the scale were from strongly disagree (1) to

strongly agree (5).

Manager Ethical Leadership and Supervisor Ethical
Leadership

To capture leadership in the eyes of beholders, we asked

followers to rate the ethical leadership behaviors of their

immediate leaders. Specifically, high-level manager’s eth-

ical leadership was rated by middle-level supervisors (i.e.,

sub-branch supervisors); middle-level supervisor’s ethical

leadership was evaluated by their immediate subordinates.

This approach has been used in a number of leadership

studies (e.g., Li and Sun 2015; Liu et al. 2012). We used

the six-item version (Detert et al. 2007) of the ethical

leadership scale (ELS; Brown et al. 2005) in this study (see

Appendix). We chose to use this short version instead of

the original 10-item version as we found that some of the

items (e.g., has the best interests of employees in mind, can

be trusted) in the original 10-item scale are redundant and

have obvious content overlapping with some other con-

structs such as consideration and trust, and this has been

pointed out by a few recent studies (Mayer et al. 2012;

Yukl et al. 2013). We concurred with these studies and

believed that we should use the most representative items

for ethical leadership in our current study. Sample items for

the six-item scale include ‘‘My leader defines success not

just by results but also by the way that they are obtained’’

and ‘‘My leader disciplines employees who violate ethical

standards.’’ As supervisor ethical leadership scores were

essentially aggregated based on subordinates’ ratings in the

multilevel analyses, we calculated the ICC(2) and mean of

Rwg for supervisors’ ethical leadership, which were .84 and

.91, respectively, and were above the suggested cutoff

point (Bliese 2000; James et al. 1993), supporting the

aggregation for supervisor ethical leadership in the multi-

level analyses. The Cronbach’s as were .89 for manager
ethical leadership and .93 for supervisor ethical leadership.

696 Z. Wang et al.

123

Ethical Efficacy Expectation

Ethical efficacy expectation was measured with a five-item

moral efficacy sub-scale from the Moral Potency Ques-

tionnaire (MPQ) developed by Hannah and Avolio (2010).
2

Sample items include ‘‘I am confident that I can confront

others who behave unethically to resolve the issue’’ and ‘‘I

am confident that I can determine what needs to be done

when I face moral/ethical decisions.’’ In the present study,

the Cronbach’s a of the scale was .89.

Ethical Outcome Expectation

Since there was no existing scale of ethical outcome

expectation in the organizational context, we developed the

items based on the theory. Specifically, ethical behavior–

reward expectation was measured through three items,

including ‘‘In our work unit, those who behave ethically

will be rewarded,’’ ‘‘In our work unit, those who follow

ethical standards will be given priority in promotion,’’ and

‘‘In our work unit, those who follow ethical principles will

be respected by others,’’ Unethical

behavior–punishment

expectation was measured via another three items,

including ‘‘In our work unit, those who behave unethically

will be punished,’’ ‘‘In our work unit, it will be difficult for

those who violate ethical standards to get promoted,’’ and

‘‘In our work unit, those who violate ethical principles will

be despised by others.’’ The anchors for both measures

ranged from 1 (very unlikely) to 5 (very likely). The

Cronbach’s as were .90 and .73, respectively. To check the
construct validity, we performed exploratory factor analy-

sis using the principal component method with the number

of factors not specified. The results based on oblimin

rotation revealed the emergence of two distinct dimensions

of ethical outcome expectation, with items loaded nicely on

the two proposed factors, without any cross-loadings. The

two factors explained 77.22 % of the total variance in

ethical outcome expectation.

Control Variables

We controlled for middle-level supervisor’s age, gender,

education, and position tenure. Age and position tenure

were measured by the number of years. Gender was coded

as 1 = male and 2 = female. Education was coded into

four categories (1 = high school or lower, 2 = associate’s

degree, 3 = bachelor’s degree, 4 = master’s degree or

higher).

Analysis Strategy

Given the nested nature of the data, to account for potential

non-independence effects, we conducted multilevel mod-

eling to test the hypotheses. Specifically, we tested

Hypothesis 1 through hierarchical linear modeling using

HLM 6.08 (Raudenbush and Bryk 2002). Following the

recommendations of Hofmann and Gavin (1998), we cen-

tered the predictor according to its grand mean in per-

forming these analyses to control for multicollinearity.

To test the cross-level mediation effects (Hypotheses

2–4), we conducted multilevel path analyses using Mplus

7.0 (Muthén and Muthén 1998–2012). Specifically, we

followed the method suggested in Zhang et al. (2009) and

estimated the indirect effects based on a 2–2–1 path-ana-

lytical model (2 refers to variables at level 2, while 1 refers

to variables at level 1). To examine the significance of each

indirect effect we estimated, we followed Selig and

Preacher’s (2008) method and conducted a Monte Carlo

simulation (i.e., a form of parameter bootstrapping) with

20,000 replications, which provided an estimate of the

confidence interval (CI) for each effect.

Results

Discriminant Validity Tests

Before hypotheses testing, we conducted a series of con-

firmatory factor analyses to examine the distinctiveness of

the four supervisor-reported variables (manager’s ethical

leadership, ethical efficacy expectation, ethical behavior–

reward expectation, and unethical behavior–punishment

expectation). As shown in Table 1, the theorized four-

factor model provided an acceptable fit to the data

(v2 = 186.32, df = 113, CFI = .93, TLI = .91,
SRMR = .08) and showed a significantly better fit than the

three-factor model (Dv2ð3Þ = 73.46, p \ .01), the two-factor

model (Dv2ð5Þ = 179.51, p \ .01), and the single-factor

model (Dv2ð6Þ = 432.75, p \ .01). Given these results, the
theorized four-factor model was superior in fit to all

alternative models, and therefore, we can continue to

examine these variables as distinct constructs.

To provide further support for the discriminant validity

of the constructs, we also computed the square root of

average variance extracted, another widely used index for

establishing the discriminant validity of constructs (Fornell

and Larcker 1981). As was shown in Table 2, the square

root of AVEs for all major constructs in our study was

above .81, which was higher than any of the inter-construct

correlations, suggesting that all constructs have good dis-

criminant validity.

2
The MPQ (copyright 2010 by Sean T. Hannah and Bruce J. Avolio)

was used with the permission of Mind Garden, Inc. All rights

reserved.

How Does Ethical Leadership Trickle Down?… 697

123

Descriptive Statistics

The means, standard deviations, and correlations among

variables are presented in Table 2. As shown in the table,

high-level managers’ ethical leadership was positively

related to middle-level supervisors’ ethical efficacy

(r = .56, p \ .01) and unethical behavior–punishment
expectation (r = .38, p \ .01). Additionally, middle-level
supervisors’ ethical efficacy (r = .62, p \ .01) and uneth-
ical behavior–punishment expectation (r = .51, p \ .01)
were positively related to their ethical leadership (aggre-

gated from subordinates’ ratings). In what follows, we

develop a multilevel model to test the hypotheses.

Hypotheses Testing

Hypothesis 1 predicted that high-level managers’ ethical

leadership would be positively related to the middle-level

supervisors’ ethical leadership. Before testing this

hypothesis, we examined whether there was significant

between-group variance in subordinates’ perceived ethical

leadership of middle-level supervisors. The results revealed

a significant between-group variance [r2 = 0.21,
s00 = 0.19, v2 = 404.69, p \ .01; ICC(1) = .48, indicat-
ing that 48 % of the variance can be attributed to level 2],

justifying the appropriateness of the use of hierarchical

linear modeling to test the hypotheses.

To test Hypothesis 1, we estimated an intercepts-as-

outcomes model in HLM 6.08, in which we used high-level

managers’ ethical leadership (level 2 predictor) to predict

the intercept of middle-level supervisors’ ethical leadership

(level 1 outcome). As shown in Table 3, after controlling

for middle-level supervisors’ age, gender, education, and

position tenure, high-level managers’ ethical leadership

related positively to middle-level supervisors’ ethical

leadership (B = 0.40, p \ .01). Thus, Hypothesis 1 was
supported.

Hypotheses 2–4 proposed that middle-level supervisors’

three ethical expectations (level 2) would mediate the

relationship between high-level managers’ ethical leader-

ship (level 2) and middle-level supervisors’ ethical

leadership (level 1). We tested these three mediation

effects simultaneously in the same multilevel path-analyt-

ical model, in which there were three level 2 paths linking

high-level managers’ ethical leadership and middle-level

supervisors’ three ethical expectations (paths a1, a2, and a3,

respectively), and another three level 1 paths linking

middle-level supervisors’ ethical expectations and ethical

leadership (paths b1, b2, and b3, respectively). The pro-

posed mediation effects were examined by estimating the

three indirect effects linking high-level managers’ ethical

leadership and middle-level supervisors’ ethical leadership:

a1b1, a2b2, and a3b3, respectively. As shown in Table 4, the

indirect effect of high-level managers’ ethical leadership

on middle-level supervisors’ ethical leadership through

middle-level supervisor’s ethical efficacy expectation was

0.13, with a 95 % Monte Carlo CI being [0.01, 0.26],

which did not include zero, suggesting that the indirect

effect was significant, supporting Hypothesis 2. The indi-

rect effect through unethical behavior–punishment expec-

tation was also significant (estimate = 0.09, 95 % Monte

Carlo CI [0.01, 0.18]). Thus, Hypothesis 4 was supported.

However, the indirect effect through ethical behavior–re-

ward expectation was not significant (estimate = -0.02,

95 % Monte Carlo CI [-0.07, 0.01]), which did not sup-

port Hypothesis 3.

Discussion

Although past research has recognized the trickle-down

effect of ethical leadership, the underlying mechanism

delineating the cascading process still remains largely

unclear. Building upon social learning theory, which sug-

gests that a role model influences an observer’s behaviors

through shaping his or her cognitive expectations (Bandura

1977; Manz and Sims 1981), we proposed and tested an

integrative dual-process model in which the trickle-down

effect of high-level managers’ ethical leadership on mid-

dle-level supervisors’ ethical leadership was mediated by

middle-level supervisors’ cognitive expectations about

their ethical efficacy and the potential outcomes of their

Table 1 Results of confirmatory factor analyses

Models Factors v2 df Dv2 SRMR CFI TLI

Model 0 Theorized four factors 186.32 113 .08 .93 .91

Model 1 Three factors ethical behavior–reward expectation and unethical behavior–

punishment expectation were merged as one factor (ethical outcome

expectation)

259.78 116 73.46** .14 .88 .86

Model 2 Two factors ethical efficacy expectation, ethical behavior–reward expectation, and

unethical behavior–punishment expectation were merged as one factor (ethical

expectation)

365.83 118 179.51** .13 .80 .77

Model 3 One factor: all variables were merged as a single factor 619.07 119 432.75** .16 .71 .66

** p \ .01

698 Z. Wang et al.

123

ethical or unethical behaviors. Results from a survey study

of 69 middle-level supervisors and 381 subordinates from a

large banking company largely supported the model we

proposed. We discuss the implications, limitations, and

future directions of our findings as follows.

Theoretical Implications

First, through exploring the mediating roles of ethical

expectations, we disentangled the intermediate psycho-

logical processes underlying the trickle-down effect of

Table 2 Means, standard deviations, and correlations among variables

M SD HAVE 1 2 3 4 5 6 7 8

(1) Supervisor age 39.61 5.97 –

(2) Supervisor gender 1.48 0.50 – -.04

(3) Supervisor education 2.99 0.44 – -.35** -.04

(4) Supervisor position tenure 2.33 1.22 – .40** -.19 -.02

(5) Manager’s ethical leadership 3.99 0.67 .84 -.03 .14 -.05 -.14

(6) Supervisor’s ethical efficacy expectation 3.88 0.62 .82 -.21 .31** -.02 -.23 .56**

(7) Supervisor’s ethical behavior–reward

expectation

4.41 0.59 .89 -.22 .05 -.15 -.01 .19 .32**

(8) Supervisor’s unethical behavior–punishment

expectation

4.20 0.66 .81 -.01 -.05 .13 .12 .38** .41** .41**

(9) Supervisor’s ethical leadership (aggregated) 4.12 0.49 .92 -.08 .09 .01 -.14 .61** .62** .15 .51**

HAVE square root of the average variance extracted (AVE)

** p \ .01, * p \ .05

Table 3 Results of cross-level regressions

Variables Mediators and dependent variables

Supervisor’s
ethical
leadership

Supervisor’s ethical

efficacy expectation
Supervisor’s ethical
behavior–reward
expectation

Supervisor’s unethical

behavior–punishment
expectation
Supervisor’s
ethical
leadership

Control variable

Supervisor age -0.002 -0.02
�

-0.04* -0.002 -0.001

Supervisor gender -0.01 0.27* 0.03 -0.09 -0.06

Supervisor education 0.04 -0.07 -0.36* 0.22* -0.04

Supervisor position tenure -0.02 -0.03 0.08 0.09 -0.02

Independent variable

Manager’s ethical

leadership

0.40** 0.47** 0.17
�

0.41**

0.21*

Mediators

Supervisor’s ethical
efficacy expectation

0.27*

Supervisor’s ethical
behavior–reward
expectation

-0.12

Supervisor’s unethical
behavior–punishment
expectation
0.21*

Level 2 residual variance 0.12** 0.23** 0.29** 0.35** 0.09**

Nlevel 2 = 69, Nlevel 1 = 381

B unstandardized regression coefficients, level 2 residual variance unexplained variance at level 2. The smaller the level 2 residual variance, the

greater amount of variance explained by the model

** p \ .01, * p \ .05, � p \ .10

How Does Ethical Leadership Trickle Down?… 699

123

ethical leadership. Resonating with several recent studies

on ethical leadership (Mayer et al. 2009; Ruiz et al.

2011a, b; Schaubroeck et al. 2012), our study also revealed

a positive relationship between high-level managers’ ethi-

cal leadership and middle-level supervisors’ ethical lead-

ership, providing further support for this trickle-down

effect of ethical leadership. Going beyond that, the sig-

nificant mediating effects of ethical expectations as we

found in the current study clearly delineated the underlying

mechanism of how ethical leadership cascades downward

in an organization. Specifically, we found that high-level

managers’ ethical leadership could facilitate middle-level

supervisors’ exhibition of ethical leadership behaviors

through influencing their ethical efficacy expectation and

unethical behavior–punishment expectation. According to

social learning theory, efficacy expectation and outcome

expectation are the two major cognitive processes influ-

encing human functioning (Bandura 2012; Manz and Sims

1981). Our research extended the expectation-related per-

spectives of social learning theory into the ethical leader-

ship context and thus provided a novel and meaningful

understanding of the social learning process of ethical

leadership. As theorized in the current study, ethical effi-

cacy expectations instill followers with a ‘‘can-do’’ moti-

vation for their ethical behavior regulations, while ethical

outcome expectations instill them with a ‘‘reason-to-do’’

motivation. The findings of our research, to some extent,

provided direct support for the well-recognized social

learning account of the trickle-down effect of ethical

leadership.

Second, we contributed to the growing, yet still limited,

body of literature on ethical efficacy. To explain an indi-

vidual’s ethical behaviors, earlier studies have highlighted

the importance of moral judgment (Blasi 1980; Kohlberg

1969). The association between moral judgment and ethical

behaviors, however, remains weak and inconsistent. This is

also called as the ‘‘judgment-action gap’’ (Jennings et al.

2015; Walker 2004). As such, an individual’s judging a

situation as ethical or unethical and understanding of what

should be done and what should not be done does not

necessarily translate into ethical behaviors. In this sense,

understanding how to motivate ethical behaviors is criti-

cally important (Treviño et al. 2006). Defined as individ-

uals’ beliefs about their abilities to execute ethical

behaviors, ethical efficacy is a relevant construct that could

help address the ‘‘judgment-behavior gap’’ (Hannah and

Avolio 2010; Hannah et al. 2011; Mitchell and Palmer

2010; Sweeney et al. 2015). However, despite its close

relevance with ethical behaviors, insofar only a few studies

have investigated the role of ethical efficacy in the ethics

domain. For instance, Schaubroeck et al. (2012) found that

ethical leadership could influence followers’ ethical effi-

cacy through ethical culture. Lee et al.’s (2015) recent

research found that followers’ ethical efficacy could

mediate the effect of ethical leadership on followers’ moral

voice behaviors. By providing support for the intermediary

role of ethical efficacy in the trickle-down process of high-

level managers’ ethical leadership, the current research

added to the ongoing exploration of ethical efficacy in the

organizational ethics context, advancing the knowledge of

ethical efficacy’s antecedents and consequences. However,

it should also be noted that the research on ethical efficacy

is still in its infancy, and thus more research is needed to

further the understanding of this construct.

Third, we contributed to the research on ethical outcome

expectation by extending it to the area of ethical leadership.

Despite its important role in the regulation of moral

behaviors (Ashkanasy et al. 2006; Treviño and Young-

blood 1990), expectations of ethical outcomes received

little attention from researchers. Drawing on earlier work

by Treviño and Youngblood (1990), we took a pioneering

step to differentiate two important types of ethical outcome

expectations: the expectation of getting rewards for ethical

behaviors and the expectation of getting punished for

unethical conducts. Furthermore, we found evidence sup-

porting the intermediary role of middle-level supervisor’s

unethical behavior–punishment expectation in the cascad-

ing process of high-level managers’ ethical leadership,

which suggested that ethical leaders could influence their

followers to become ethical leaders through shaping their

expectations that behaving unethically would be punished.

However, the study lent no support to the mediating effect

of ethical behavior–reward expectation. We argue that

there might be three possible reasons for this unsupported

effect. First, prior research suggested that, in the short term,

using rewards to elicit ethical behaviors may be frustrating.

As posited by Treviño and Brown (2004, p. 79), ‘‘Can we

really reward ethical behavior? In the short term, we

probably cannot. For the most part, ethical behavior is

simply expected, and people don’t expect or want to be

Table 4 Results of the
mediating effects of ethical

expectations

Indirect effects via Estimates t test Monte Carlo 95 % CI

Low end High end

Path 1 ethical efficacy expectation 0.13 p = .048 0.01 0.26

Path 2 ethical behavior–reward expectation -0.02 p = .299 -0.07 0.01

Path 3 unethical behavior–punishment expectation 0.09 p = .027 0.01 0.18

700 Z. Wang et al.

123

rewarded for doing their jobs the right way.’’ Second, it has

been posited that a transactional leadership approach,

characterized by managing by exception and contingent

reinforcement, is more likely to draw followers’ attention

to oughts, duties, and losses (Kark and van Dijk 2007), thus

making them more sensitive to behaviors that they should

not do. Given that ethical leaders usually use a transac-

tional approach to hold followers accountable (Brown et al.

2005; Treviño and Brown 2014), it could be reasoned that

supervisors working under ethical managers might pay

more attention to losses, such as punishments for behaving

unethically, rather than to gains, such as rewards for

behaving ethically. In indirect support of our finding, Shao

et al. (2011) suggested that ethical leadership is more likely

to induce employees’ ethical prevention focus, a construct

that to some extent is similar to unethical behavior–pun-

ishment expectation. Finally, the unsupported mediating

role of ethical behavior–reward expectation might also be

attributed to the measurement of ethical leadership in the

current research. Although Brown et al. (2005) contended

that ethical leaders use rewards and punishments to hold

followers accountable for their conducts, the ELS (Brown

et al. 2005; Detert et al. 2007) we used only captured the

‘‘punishment’’ component (e.g., disciplining employees

who violate ethical standards), yet neglected the ‘‘reward’’

component.

Fourth, as a reply to a recent study by Wo et al. (2015),

the present study defended the legitimacy of using social

learning theory to explain trickle-down effects in organi-

zation studies. Wo et al. explored the mechanisms under-

lying the cascading process of interactional justice

perception through three perspectives: social learning,

social exchange, and displaced aggression. Through two

studies, they found no support for the social learning per-

spective, thereby casting doubt on its validity in explaining

the trickle-down effect. Responding to their call for a re-

evaluation of the social learning perspective, we used

ethical efficacy expectation and ethical outcome expecta-

tion, two core variables rooted in social learning theory, to

examine the validity of this theory in explaining the cas-

cading effect of ethical leadership. Based on our findings,

the current research defended the legitimacy of using social

learning theory in explaining the trickle-down effect.

Indeed, different theories may have different power in

explaining the trickle-down process of an organizational

phenomenon. According to our observations, when study-

ing the trickle-down effect of behaviors (e.g., leadership

behaviors, citizenship behaviors, creativity), researchers

primarily used social learning theory (e.g., Jaussi and

Dionne 2003; Li and Sun 2015; Liu et al. 2012; Yaffe and

Kark 2011); when explaining the trickle-down effect of

exchange relationships (e.g., leader–member exchange,

perceived organizational support) or justice perceptions

(e.g., Aryee et al. 2007; Tepper and Taylor 2003;

Venkataramani et al. 2010), social exchange theory was

mostly used; the displaced aggression perspective is mainly

adopted to account for the cascading effect of negative

leaderships (e.g., abusive supervision) and injustice per-

ception (e.g., Aryee et al. 2007; Hoobler and Brass 2006;

Tepper et al. 2006). Taken together, it could be reasoned

that social exchange theory and displaced aggression per-

spective might have stronger power than social learning

theory in explaining the trickle-down effect of justice

perceptions, as examined in Wo et al.’s study; yet when it

comes to the cascading effect of ethical leadership

behaviors, social learning theory might be a more

suitable perspective.

Finally, from the results of our data analyses, we found

some effects relating to the control variables of our study

interesting and we believe these small yet interesting

findings could indicate potential research questions to be

examined in the future. As was shown in Table 3, super-

visor gender was positively (B = .27, p \ .05) associated
with their ethical efficacy expectation, such that females

tend to have higher ethical efficacy scores than males.

Given that existing research suggested that women should

be more likely to conduct ethical behaviors and avoid

unethical behaviors than men (see Franke et al. 1997; Kish-

Gephart et al. 2010; Pan and Sparks 2012 for meta-ana-

lytical reviews) and men are more than two times as likely

as women to engage in actions regarded as unethical (Betz

et al. 1989), the finding that women have higher belief in

their ability to execute ethical behaviors is not surprising.

Besides, supervisor’s level of education was negatively

(B = -.36, p \ .05) related to supervisors’ ethical
behavior–reward expectation yet positively (B = .22,

p \ .05) associated with supervisors’ unethical behavior–
punishment expectation. A possible explanation could be

that those highly educated people, due to their higher levels

of morality or their higher levels of conscience, may view

conducting ethical behaviors as something normal in their

life. Under this circumstance, they may not expect any

rewards for their good deeds and sometimes, they might

even dislike the rewards given for good deeds. However, in

terms of unethical behaviors, highly educated individuals

might be more likely to have a strong belief in norms or

principles, which essentially requires a punishment for

unethical behaviors.

Practical Implications

This research also has practical implications for organiza-

tion management, especially for the ethics management in

the banking industry where ethical scandals have happened

so frequently and have caused severe consequences. First,

consistent with other explorations of trickle-down effects

How Does Ethical Leadership Trickle Down?… 701

123

of leadership, the present study highlighted the importance

of the role modeling of leadership and indicated that high-

level leaders should set examples for middle-level super-

visors in the practice of ethical leadership. Moreover,

supervisors can act either as transmitters of ethical

behaviors or as inhibitors of unethical behaviors due to

their role as linking-pins in the organization. Therefore, the

role of middle-level supervisors in promoting the trickle-

down effect of ethical behaviors should deserve greater

attention in organizational ethics management. Second, our

findings of the intermediate mechanisms underlying the

trickle-down effect offered deeper insights into how the

trickle-down effect occurs, providing practical recom-

mendations for facilitating the trickle-down effect. For

instance, high-level managers should serve as ethical role

models for middle-level supervisors to bolster their per-

ceived abilities to execute ethical behaviors and to shape

their ethical outcome expectations, which would in turn

transform those supervisors into ethical leaders.

Limitations and Future Directions

Our research is not without limitations. First, although we

have theoretically delineated the causal relationships

among variables, the cross-sectional data used in the cur-

rent study still limited us in making causal inferences. The

use of multi-source ratings in the current study could help

alleviate the common method variance to some extent, yet

future research could use more advanced design to provide

more conservative and robust support for the proposed

relationships among variables. For example, a multi-wave

longitudinal design with the ratings for ethical leadership

and the mediators separate in time would help establish

more robust findings. Second, in this study, we only col-

lected our sample from the banking industry, the general-

izability of our findings to other contexts remains to be

further investigated. Although ethical leadership research

does not primarily focus on any specific sector or generate

conclusions that were only applicable to any given sector,

future research should still consider the generalizability of

the trickle-down effect to other research settings. Third, in

theorizing on the proposed mechanisms linking manager’s

ethical leadership and followers’ ethical efficacy expecta-

tion, we relied heavily on social learning theory and sug-

gested that the four sources of efficacy, as suggested

originally by Bandura (1977), to be the focal determinants

of ethical efficacy. However, due to the lack of a valid

scale, we did not measure the four sources of efficacy

directly in the current study, which is an obvious limitation

of our study. This said, future research should develop a

reliable and valid scale to measure the four sources of

efficacy.

The fourth limitation concerned with the use of self-

developed measure of ethical outcome expectations. As

suggested by Bandura (1977), outcome expectation is very

specific to the research context. Bearing this in mind, we

indeed tried to find an existing measure for ethical outcome

expectations. Although there have been a few studies that

operationalized ethical outcome expectations (Ashkanasy

et al. 2006; Treviño and Youngblood 1990), the measure-

ment approach used in these studies, either designed for an

experimental setting or based on a general assessment (i.e.,

not differentiating two types of expectations), did not fit

well with the context and the purpose of our research.

Given the lack of an appropriate scale to measure ethical

outcome expectations, we considered the alternative of

using a self-developed measure instead. We realized that,

however, many researchers have developed measures

according to their research purposes. For instance, Yuan

and Woodman (2010) developed three items to assess

employees’ expected positive performance outcomes from

innovative behaviors; Lian et al. (2011) developed a five-

item scale to assess employees’ perceptions of the likeli-

hood that abusive behaviors would be rewarded; Schau-

broeck et al. (2016) recently used a self-developed three-

item scale to evaluate employees’ beliefs about the benefits

of engaging in desired customer service behaviors. In light

of these studies, we built upon our theorizing of ethical

outcome expectations and developed a six-item measure

for the current study. Although the self-developed measure

has demonstrated good reliability and validity, we still

encourage future research to further develop and validate a

rigorous measure for ethical outcome expectations.

Finally, we examined the trickle-down effect of ethical

leadership and its ‘‘black box’’ solely from the social

learning perspective, leaving other potential perspectives

uncharted. The theories of ethical leadership and the earlier

work on the trickle-down effect of leadership in combi-

nation suggested that there may be more than one reason

explaining why ethical leadership cascades in organiza-

tions. For instance, according to social exchange theory

and the observation that ‘‘imitation is the sincerest form of

flattery’’ (Liden et al. 2014, p. 1436), middle-level super-

visors are expected to feel a sense of indebtedness to high-

level ethical managers because of their trustworthy,

humane, and fair nature (Mayer et al. 2012), and such a

sense of indebtedness might drive middle-level supervisors

to reciprocate ethical managers by emulating their ethical

leadership behaviors. Besides social exchange theory,

social identity theory may also be an alternative explana-

tion. This theory holds that followers who identify with

their leaders are more sensitive to and active in meeting

leaders’ expectations (Aron 2003; Li and Sun 2015; Pratt

1998). In this sense, it could be possible that high-level

managers’ ethical leadership could elicit middle-level

702 Z. Wang et al.

123

supervisors’ personal identification with managers (e.g.,

Walumbwa et al. 2011), which would in turn influence

them to display behaviors that are consistent with high-

level managers’ ethical expectations. This said, future

research should continue investigating alternative expla-

nations for the trickle-down effect of ethical leadership,

which could help provide a more comprehensive under-

standing of this phenomenon.

Acknowledgments This study was funded by the National Natural
Science Foundation of China (Grant Number 71302129).

Compliance with Ethical Standards

Conflict of Interest The authors declare that they have no conflict of
interest.

Ethical approval All procedures performed in this study were in
accordance with the ethical standards of the Institutional Research

Committee and with the 1964 Helsinki Declaration and its later

amendments or comparable ethical standards.

Informed consent Informed consent was obtained from all individ-
ual participants included in this study.

Appendix

Items from the six-item ELS

(1) Disciplines employees who violate ethical standards;

(2) Conducts his/her personal life in an ethical manner;

(3) Discusses business ethics or values with employees;

(4) Sets an example of how to do things the right way in

terms of ethics;

(5) Defines success not just by results but also the way

that they are obtained;

(6) When making decisions, asks ‘‘what is the right

thing to do.’’

Note The above six-item ELS was from Detert et al. (2007)

and was adapted based on the original 10-item ELS

developed by Brown et al. (2005).

References

Arnaud, A., & Schminke, M. (2012). The ethical climate and context

of organizations: A comprehensive model. Organization

Science, 23(6), 1767–1780.

Aron, A. (2003). Self and close relationships. In M. R. Leary & J.

P. Tagney (Eds.), Handbook of self and identity (pp. 442–461).

New York: The Guilford Press.

Aryee, S., Chen, Z. X., Sun, L. Y., & Debrah, Y. A. (2007).

Antecedents and outcomes of abusive supervision: Test of a

trickle-down model. Journal of Applied Psychology, 92(1),

191–201.

Ashkanasy, N. M., Windsor, C. A., & Treviño, L. K. (2006). Bad

apples in bad barrels revisited: Cognitive moral development,

just world beliefs, rewards, and ethical decision making.

Business Ethics Quarterly, 16(4), 449–473.

Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ:

Prentice-Hall.

Bandura, A. (1991). Social cognitive theory of moral thought and

action. In W. M. Kurtines & J. L. Gewwirtz (Eds.), Handbook of

moral behavior and development (pp. 45–103). Hillsdale, NJ:

Lawrence Erlbaum.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York:

Freeman.

Bandura, A. (2012). On the functional properties of perceived self-

efficacy revisited. Journal of Management, 38(1), 9–44.

Bedi, A., Alpaslan, C. M., & Green, S. (2015). A meta-analytic

review of ethical leadership outcomes and moderators. Journal

of Business Ethics,. doi:10.1007/s10551-015-2625-1.

Betz, M., O’Connell, L., & Shepard, J. M. (1989). Gender differences

in proclivity for unethical behavior. Journal of Business Ethics,

8(5), 321–324.

Blasi, A. (1980). Bridging moral cognition and moral action: A

critical review of the literature. Psychological Bulletin, 88(1),

1–45.

Bliese, P. D. (2000). Within-group agreement, non-independence, and

reliability: Implications for data aggregation and analysis. In K.

J. Klein & S. W. Kozlowski (Eds.), Multilevel theory, research,

and methods in organizations (pp. 349–381). San Francisco:

Jossey-Bass.

Boatright, J. R. (2010). Finance ethics: Critical issues in theory and

practice. Hoboken, NJ: Wiley.

Brislin, R. W. (1986). The wording and translation of research

instruments. In W. J. Lonner & J. W. Berry (Eds.), Field methods

in cross-cultural research (pp. 136–164). Newbury Park, CA:

Sage.

Brown, M. E., & Treviño, L. K. (2006). Ethical leadership: A review

and future directions. Leadership Quarterly, 17(6), 595–616.

Brown, M. E., & Treviño, L. K. (2014). Do role models matter? An

investigation of role modeling as an antecedent of perceived

ethical leadership. Journal of Business Ethics, 122(4), 587–598.

Brown, M. E., Treviño, L. K., & Harrison, D. A. (2005). Ethical

leadership: A social learning perspective for construct develop-

ment and testing. Organizational Behavior and Human Decision

Processes, 97(2), 117–134.

Davis, T. R. V., & Luthans, F. (1980). A social learning approach to

organizational behavior. Academy of Management Review, 5(2),

281–290.

den Hartog, D. N. (2015). Ethical leadership. Annual Review of

Organizational Psychology and Organizational Behavior, 2,

409–434.

Detert, J. R., Treviño, L. K., Burris, E. R., & Andiappan, M. (2007).

Managerial modes of influence and counterproductively in

organizations: A longitudinal business-unit-level investigation.

Journal of Applied Psychology, 92(4), 993–1005.

Fischbach, S. (2015). Ethical efficacy as a measure of training

effectiveness: An application of the graphic novel case method

versus traditional written case study. Journal of Business Ethics,

128(3), 603–615.

Fornell, C., & Larcker, D. E. (1981). Evaluating structural equation

models with unobserved variables and measurement error.

Journal of Marketing Research, 18(1), 39–50.

Franke, G. R., Crown, D. F., & Spake, D. F. (1997). Gender

differences in ethical perceptions of business practices: A social

role theory perspective. Journal of Applied Psychology, 82(6),

920–934.

How Does Ethical Leadership Trickle Down?… 703

123

http://dx.doi.org/10.1007/s10551-015-2625-1

Hannah, S. T., & Avolio, B. J. (2010). Moral potency: Building the

capacity for character-based leadership. Consulting Psycholog-

ical Journal: Practice and Research, 62(4), 291–310.

Hannah, S. T., Avolio, B. J., & May, D. R. (2011). Moral maturation and

moral conation: A capacity approach to explaining moral thought

and action. Academy of Management Review, 36(4), 663–685.

Hofmann, D. A., & Gavin, M. B. (1998). Centering decisions in

Hierarchical Linear Models: Theoretical and methodological

implications for organizational science. Journal of Management,

24(5), 623–641.

Hoobler, J., & Brass, D. (2006). Abusive supervision and family

undermining as displaced aggression. Journal of Applied Psy-

chology, 91(5), 1125–1133.

James, L. R., Demaree, R. J., & Wolf, G. (1993). Rwg: An assessment

of within-group interrater agreement. Journal of Applied

Psychology, 78(2), 306–309.

Jaussi, K. S., & Dionne, S. D. (2003). Leading for creativity: The role

of unconventional leader behavior. Leadership Quarterly,

14(4–5), 475–498.

Jennings, P. L., Mitchell, M. S., & Hannah, S. T. (2015). The moral

self: A review and integration of the literature. Journal of

Organizational Behavior, 36(S1), S104–S168.

Kark, R., & Van Dijk, D. (2007). Motivation to lead, motivation to

follow: The role of the self-regulatory focus in leadership

processes. Academy of Management Review, 32(2), 500–528.

Kish-Gephart, J. J., Harrison, D. A., & Treviño, L. K. (2010). Bad

apples, bad cases, and bad barrels: Meta-analytic evidence about

sources of unethical decisions at work. Journal of Applied

Psychology, 95(1), 1–31.

Kohlberg, L. (1969). Stage and sequence. The cognitive develop-

mental approach to socialization. In D. Goslin (Ed.), Handbook

of socialization theory (pp. 347–480). Chicago: RanMcNally.

Lee, D., Choi, Y., Youn, S., & Chun, J. K. (2015). Ethical leadership

and employee moral voice: The mediating role of moral efficacy

and the moderating role of leader–follower value congruence.

Journal of Business Ethics,. doi:10.1007/s10551-015-2689-y.

Li, Y., & Sun, J. M. (2015). Traditional Chinese leadership and

employee voice behavior: A cross-level examination. Leadership

Quarterly, 26(2), 172–189.

Lian, H., Ferris, D. L., & Brown, D. J. (2011). Does power distance

exacerbate or mitigate the effects of abusive supervision? It depends

on the outcome. Journal of Applied Psychology, 97(1), 107–123.

Liden, R. C., Wayne, S. J., Liao, C. W., & Meuser, J. D. (2014).

Servant leadership and serving culture: Influence on individual

and unit performance. Academy of Management Journal, 57(5),

1434–1452.

Liu, D., Liao, H., & Loi, R. (2012). The dark side of leadership: A

three-level investigation of the cascading effect of abusive

supervision on employee creativity. Academy of Management

Journal, 55(5), 1187–1212.

Manz, C. C., & Sims, H. P. (1981). Vicarious learning: The influence

of modeling on organizational behavior. Academy of Manage-

ment Review, 6(1), 105–113.

May, D. R., Luth, M. T., & Schwoerer, C. E. (2013). The influence of

business ethics education on moral efficacy, moral meaningful-

ness, and moral courage: A quasi-experimental study. Journal of

Business Ethics, 124(1), 67–80.

Mayer, D. M., Aquino, K., Greenbaum, R. L., & Kuenzi, M. (2012).

Who displays ethical leadership and why does it matter? An

examination of antecedents and consequences of ethical leader-

ship. Academy of Management Journal, 55(1), 151–171.

Mayer, D. M., Kuenzi, M., Greenbaum, R., Bardes, M., & Salvador,

R. (2009). How low does ethical leadership flow? Test of a

trickle-down model. Organizational Behavior and Human

Decision Processes, 108(1), 1–13.

Mitchell, M. S., & Palmer, N. F. (2010). The managerial relevance of
ethical efficacy. In M. Schminke (Ed.), Managerial ethics:

Managing the psychology of morality (pp. 89–108). New York:

Routledge.

Muthén, L. K. & Muthén, B. O. (1998–2012). Mplus user’s guide (7th

ed). Los Angeles: Muthén and Muthén.

Ng, T. W., & Feldman, D. C. (2015). Ethical leadership: Meta-

analytic evidence of criterion-related and incremental validity.

Journal of Applied Psychology, 100(3), 948–965.

Pan, Y., & Sparks, J. R. (2012). Predictors, consequence, and

measurement of ethical judgments: Review and meta-analysis.

Journal of Business Research, 65(1), 84–91.

Pratt, M. G. (1998). To be or not to be: Central questions in

organizational identification. In D. A. Whetton & P. C. Godfrey

(Eds.), Identity in organization: Building theory through con-

versations (pp. 171–208). Thousand Oaks,

CA: Sage.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear

models: Applications and data analysis methods. Newbury Park,

CA: Sage.

Ruiz, P., Ruiz, C., & Martı́nez, R. (2011a). Improving the ‘‘leader-

follower’’ relationship: Top manager or supervisor? The ethical

leadership trickle-down effect on follower job response. Journal

of Business Ethics, 99(4), 587–608.

Ruiz, P., Ruiz, C., & Martı́nez, R. (2011b). The cascading effect of

top management’s ethical leadership: Supervisors or other lower-

hierarchical level individuals? African Journal of Business

Management, 5(12), 4755–4764.

Ruiz-Palomino, P., Martı́nez-Ruiz, M. P., & Martı́nez-Cañas, R.

(2013). Assessing ethical behaviours in the Spanish banking and

insurance industries: Evidence and challenges. International

Journal of Human Resource Management, 24(11), 2173–2196.

Ruiz-Palomino, P., Ruiz-Amaya, C., & Knörr, H. (2011). Employee

organizational citizenship behaviour: The direct and indirect

impact of ethical leadership. Canadian Journal of Administrative

Sciences, 28(3), 244–258.

Schaubroeck, J. M., Hannah, S. T., Avolio, B. J., Kozlowski, S. W. J.,

Lord, R. G., Treviño, L. K., et al. (2012). Embedding ethical

leadership within and across organization levels. Academy of

Management Journal, 55(5), 1053–1078.

Schaubroeck, J. M., Lam, S. S. K., & Peng, A. C. (2016). Can peers’

ethical and transformational leadership improve coworkers’

service quality? A latent growth analysis. Organizational

Behavior and Human Decision Processes, 133(1), 45–58.

Selig, J. P., & Preacher, K. J. (2008). Monte Carlo method for

assessing mediation: An interactive tool for creating confidence

intervals for indirect effects [Computer software]. http://

quantpsy.org/.

Shao, P., Resick, C. J., & Schaubroeck, J. (2011). Ethical leadership

and motivation: Examining promotion and prevention regulatory

foci. In Paper presented at the annual conference of the

Academy of Management, San Antonio, TX.

Sims, R. R., & Brinkman, J. (2002). Leaders as moral role models:

The case of John Gutfreund at Salomon Brothers. Journal of

Business Ethics, 35(4), 327–339.

Sumanth, J., & Hannah, S. (2014). Developing leadership capacity:

An integration and exploration of ethical and authentic leader-

ship antecedents. In L. Neider & C. Schriesheim (Eds.),

Advances in authentic and ethical leadership (pp. 25–74).

Charlotte, NC: Information Age Publishing.

Sweeney, P. J., Imboden, M. W., & Hannah, S. (2015). Building

moral strength: Bridging the moral judgment-action gap. New

Directions for Student Leadership, 146, 17–33.

Tepper, B. J., Duffy, M. K., Henle, C. A., & Lambert, L. S. (2006).

Procedural injustice, victim precipitation, and abusive supervi-

sion. Personnel Psychology, 59(1), 101–123.

704 Z. Wang et al.

123

http://dx.doi.org/10.1007/s10551-015-2689-y

http://quantpsy.org/

http://quantpsy.org/

Tepper, B. I., & Taylor, E. C. (2003). Relationships among

supervisors’ and subordinates’ procedural justice perceptions

and organizational citizenship behaviors. Academy of Manage-

ment Journal, 46(1), 97–105.

Treviño, L. K., & Brown, M. (2004). Managing to be ethical:

Debunking five business ethics myths. Academy of Management

Executive, 18(2), 69–83.

Treviño, L. K., & Brown, M. E. (2014). Ethical leadership. In D.

V. Day (Ed.), The Oxford handbook of leadership and organi-

zations (pp. 524–538). Oxford: Oxford University Press.

Treviño, L. K., Brown, M., & Hartman, L. P. (2003). A qualitative

investigation of perceived executive ethical leadership: Percep-

tions from inside and outside the executive suite. Human

Relations, 56(1), 5–37.

Treviño, L. K., den Nieuwenboer, N. A., & Kish-Gephart, J. J. (2014).

(Un)ethical behavior in organization. Annual Review of Psy-

chology, 65, 635–660.

Treviño, L. K., Weaver, G. R., & Reynolds, S. J. (2006). Behavioral

ethics in organizations: A review. Journal of Management,

32(6), 951–990.

Treviño, L. K., & Youngblood, S. A. (1990). Bad apples in bad

barrels: A causal analysis of ethical decision-making behavior.

Journal of Applied Psychology, 75(4), 378–385.

Venkataramani, V., Green, S. G., & Schleicher, D. J. (2010). Well-

connected leaders: The impact of leaders’ social network ties on

LMX and members’ work attitudes. Journal of Applied Psy-

chology, 95(6), 1071–1084.

Walker, L. J. (2004). Gus in the gap: Bridging the judgment-action

gap in moral functioning. In D. Lapsley & D. N. Narvaez (Eds.),

Moral development, self and identity (pp. 1–20). Mahwah, NJ:

Lawrence Erlbaum.

Walumbwa, F. O., Mayer, D. M., Wang, P., Wang, H., Workman, K.,

& Christensen, A. L. (2011). Linking ethical leadership to

employee performance: The roles of leader–member exchange,

self-efficacy, and organizational identification. Organizational

Behavior and Human Decision Processes, 115(2), 204–213.

Walumbwa, F. O., & Schaubroeck, J. (2009). Leader personality traits

and employee voice behavior: Mediating roles of ethical

leadership and work group psychological safety. Journal of

Applied Psychology, 94(5), 1275–1286.

Weaver, G. R., Treviño, L. K., & Agle, B. (2005). ‘‘Somebody I look

up to’’: Ethical role models in organzations. Organizational

Dynamics, 34(4), 313–330.

Weiss, H. M. (1977). Subordinate imitation of supervisor behavior:

The role of modeling in organizational socialization. Organiza-

tional Behavior and Human Performance, 19(1), 89–105.

Wo, D. X. H., Ambrose, M. L., & Schminke, M. (2015). What drives

trickle-down effects? A test of multiple mediation processes.

Academy of Management Journal, 58(6), 1848–1868.

Yaffe, T., & Kark, R. (2011). Leading by example: The case of leader

OCB. Journal of Applied Psychology, 96(4), 806–826.

Yuan, F., & Woodman, R. W. (2010). Innovative behavior in the

workplace: The role of performance and image outcome

expectations. Academy of Management Journal, 53(2), 323–342.

Yukl, G., Mahsud, R., Hassan, S., & Prussia, G. E. (2013). An

improved measure of ethical leadership. Journal of Leadership

and Organizational Studies, 20(1), 38–48.

Zhang, Z., Zyphur, M. J., & Preacher, K. J. (2009). Testing multilevel

mediation using hierarchical linear models: Problems and

solutions. Organizational Research Methods, 12(4), 695–719.

How Does Ethical Leadership Trickle Down?… 705

123

Journal of Business Ethics is a copyright of Springer, 2018. All Rights Reserved.

• How Does Ethical Leadership Trickle Down? Test of an Integrative Dual-Process Model

Abstract
Introduction
Theory and Hypotheses
Manager Ethical Leadership and Supervisor Ethical leadership
The Mediating Effect of Ethical Efficacy Expectation
The Mediating Effect of Ethical Outcome Expectation
Method
Sample and Procedure
Measures
Manager Ethical Leadership and Supervisor Ethical Leadership
Ethical Efficacy Expectation
Ethical Outcome Expectation
Control Variables
Analysis Strategy
Results
Discriminant Validity Tests
Descriptive Statistics
Hypotheses Testing
Discussion
Theoretical Implications
Practical Implications
Limitations and Future Directions
Acknowledgments
Appendix
References

Feng, J., Zhou, W., Li, S., & Li, M. (2020). Obstacles open the door — negative shocks can motivate individuals to focus on opportunities. Frontiers of Business Research in China, 14(1), 1-17. doi:http://dx.doi.org.libraryresources.columbiasouthern.edu/10.1186/s11782-019-0067-9

Sifa, H. B., & Tshiunza, C. L. (2020). THEORETICAL ANALYSIS OF MANAGING CORPORATE SOCIAL RESPONSIBILITY IN DEVELOPING COUNTRIES. International Journal of Information, Business and Management, 12(2), 185-208. Retrieved from

https://search-proquest-com.libraryresources.columbiasouthern.edu/docview/2348381966?accountid=33337

Holm, H., Nee, V., & Opper, S. (2020). Strategic decisions: Behavioral differences between CEOs and others. Experimental Economics, 23(1), 154-180. doi:http://dx.doi.org.libraryresources.columbiasouthern.edu/10.1007/s10683-019-09604-3

Wang, Z., Xu, H., & Liu, Y. (2018). How Does Ethical Leadership Trickle Down? Test of an Integrative Dual-Process Model. Journal of Business Ethics, 153(3), 691–705. https://doi-org.libraryresources.columbiasouthern.edu/10.1007/s10551-016-3361-x