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Group Ethical Decision Making Process in Chinese Business: Analysis From Social Decision Scheme and

Cultural Perspectives

Jianfeng Yang

Research Center of Cluster and Enterprise Development Jiangxi University of Finance and Economics

Hao Ji

School of Management Zhejiang University

Conor O’Leary

Griffith Business School Griffith University

Literature concerning group ethical decision making in a business setting has traditionally focused on directly comparing group versus individual decisions and then investigating differences. Analysis of the interactive process of group ethical decision making appears sparse. This study addresses the gap by investigating group decision making from a social decision scheme (SDS) perspective in a Chinese cultural setting. A cohort of Chinese accountancy students evaluated ethical business scenarios individually and then in a group context. Group responses could be explained in terms of both the SDS and the Chinese cultural perspective (zhongyong). Specifically, groups did not select the most ethical choice but rather the most moderate of all choices advocated by the majority (zhongyong). These results show the application of SDS theory in a culturally specific (Chinese) environment and note the impact of culturally specific factors (zhongyong) on business decision making. The implications are significant for business. If ethical decisions are entrusted to groups, the impact of culturally specific factors must be fully appreciated in evaluating the final decision.

Keywords: group ethical decision making, social decision scheme, culture, zhongyong

INTRODUCTION

Because of the complex nature of business decisions, groups are often perceived as a better way with which to arrive at the optimum decision, rather than entrusting the decision to an individual

Correspondence should be addressed to Jianfeng Yang, Research Center of Cluster and Enterprise Development, Jiangxi University of Finance and Economics, Nachang Province, Jiangxi, China. E-mail: [email protected]

ETHICS & BEHAVIOR, 27(3), 201–220

Copyright © 2017 Taylor & Francis Group, LLC

ISSN: 1050-8422 print / 1532-7019 online

DOI: 10.1080/10508422.2016.1157690

(Nichols & Day, 1982). Therefore, business decisions are usually made by groups rather than individuals in organizations (Abdolmohammadi, Gabhart, & Reeves, 1997; Sarker, Sarker, Chatterjee, & Valacich, 2010). Business decisions often involve moral components and as such can be seen as ethical decisions (Jones, 1991). Hence the process of group ethical business decision making appears critical and in need of significant research (Treviño, Nieuwenboer, & Kish-Gephart, 2014).

Business ethics has been examined intensively on an individual level (e.g., DeGrassi, Morgan, Walker, Wang, & Sabat, 2012; Pearsall & Ellis, 2011; Stenmark, 2013). However, there are only a few empirical studies that have examined the outcomes and antecedents of group ethical decision making (GEDM; e.g., Abdolmohammadi & Reeves, 2003; O’Leary & Pangemanan, 2007; Sarker et al., 2010). Studies such as O’Leary and Pangemanan (2007) found that a group ethical decision is not significant stricter than the average of individuals’ ethical decisions. Conversely, other studies showed that group ethical decisions are stricter than the average of individuals’ ethical decisions (Abdolmohammadi et al., 1997; Abdolmohammadi & Reeves, 2003; Nichols & Day, 1982). They were still found to be less ethical than the decision of the most ethical group member (Abdolmohammadi & Reeves, 2003; Nichols & Day, 1982). Some other studies showed that factors such as group diversity (DeGrassi et al., 2012), leader- ship (Schminke, Wells, Peyrefitte, & Sebora, 2002), and moral microcosms (Brief, Buttram, & Dukerich, 2001) can impact GEDM significantly.

Although those studies have supplied much important knowledge on the outcomes and antecedents of GEDM, they have two imperative shortcomings. The first is that they cannot help us understand the exact process of GEDM (Treviño et al., 2014). This could help us understand both why a consistent positive group effect on ethical decisions has not been noted and how those antecedents impact on the outcomes of GEDM. Second, previous studies are implemented in America, the United Kingdom, and Australia. No empirical study on GEDM has been conducted in China, where the culture is much different from those three countries (Hofstede, 2003). Previous studies have demonstrated that nationality/cultural backgrounds have important impacts on factors such as ethical reasoning (Flaming, Agacer, & Uddin, 2010; Koning, Van, Van, & Steinel, 2010; Zheng, Gray, Zhu, & Jiang, 2014), the selection of a decision model, and decision preference (Weber & Hsee, 2000). Therefore, it is unclear whether the results of previous studies would be valid in China, a country that is becoming increasingly important in the global business environment.

China is now a country of huge global economic importance and unfortunately, the occa- sional business scandal. China is the world’s second largest economy with a gross domestic product of US$9–10 trillion (Bergmann & Yellin, 2013). Countries from all over the world, including the European Union, the United States, and Japan, are investing in China (Bloomberg, 2013). Similarly, the International Institute for Sustainable Development (2013) noted how Chinese business entities are expanding their investments overseas, especially in Africa and Latin America. It follows therefore that business interactions between and within multinational companies, international governments, and their Chinese equivalents are already at a significant level and are predicted to increase. These business interactions will invariably involve ethical decision making. Furthermore, like many other countries China has recently experienced incidences of unethical business practices leading to negative reactions. To avoid any further accounting scandals, Interactive Brokers Group Inc. forbade its customers from investing in more than 130 Chinese public companies (Spicer & Giannone, 2011). Similarly, after some false

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accounting was noted in some of its Chinese clients, Deloitte & Touche was investigated by the U.S. Securities and Exchange Commission. Deloitte & Touche subsequently announced it would strengthen audit procedures for new clients in the Chinese region (Sanchanta & Mavin, 2013). These events highlight issues with business ethics in China.

This study attempts to address these two shortcomings of previous research, just noted, by pursuing two objectives. First, the main objective is to develop a new social decision scheme (SDS; zhongyong scheme), based upon extant SDS theory, but incorporating an important Chinese cultural feature (zhongyong). Current SDS theory is now a key concept in current group decision making research (Laughlin, 2011). It is hoped the new scheme will help to better explain the GEDM process in a Chinese business context. Second, the results of GEDM in a Chinese business context will be compared to those obtained from Western countries, as noted in the earlier studies. Specifically, the following four questions are evaluated in a Chinese context:

1. Are group ethical decisions stricter than individual ethical decisions? 2. Is the ethical decision of the most ethical group member stricter than group ethical

decisions? 3. Do all-female groups make stricter ethical decisions than all-male groups? 4. Would diversity enhance GEDM?

LITERATURE REVIEW

When we consider group decision making in a Chinese business ethics environment, there are three topics to discuss:

1. Whether groups perform better than individuals in ethical decision making. 2. Effects of gender and diversity on GEDM. 3. The process that groups apply in order to make ethical decisions.

The first two topics have received some examination in the past 30 years; however, few studies have explored the process of GEDM in detail. Therefore, this study tests whether the results of the first two topics are as valid in a Chinese context as in other countries. Critically, the study also extends research into the third topic, the process of GEDM. Let us now examine the extant literature in each of the three topic areas.

GEDM versus Individual Ethical Decision Making

Since group judgment is usually more accurate than individual judgment (Sniezek & Henry, 1990), group ethical reasoning is considered to be at a higher level than individual ethical reasoning (Abdolmohammadi & Reeves, 2003; Nichols & Day, 1982). These researchers argued that group members might be highly influenced and persuaded by individuals whose ethical reasoning is at a high level and might become more sensitive to morality via group interaction and discussion (Nichols & Day, 1982). This should then lead to a group decision that would be stricter than an individual’s in ethical judgment. Some empirical studies support this view; for example, Nichols and Day (1982) and Abdolmohammadi and Reeves (2003) found that groups got a significantly higher score than individuals in Defining Issues Tests, a widely used

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instrument to assess moral reasoning and moral development (see, e.g., Rest, Bebeau, & Volker, 1986). However, O’Leary and Pangemanan (2007) did not get a similar result in Australia. Furthermore, Abdolmohammadi et al. (1997) found that groups improved male students’ P-scores (an index of ethical cognition, which can be calculated from the scores of Defining Issues Tests) significantly but decreased female students’ scores. They also noted the difference between group ethical decisions to be marginally but not significantly stricter than average member ethical decisions. Regarding whether groups outperform the best members, groups usually fall short of their best member (Kerr & Tindale, 2004; Steiner, 1972). Furthermore, previous business ethics studies consistently found groups being outperformed by their best group member on ethical tasks (Abdolmohammadi & Reeves, 2003; Nichols & Day, 1982).

Effects of Gender and Diversity on GEDM

For the antecedents of GEDM, some factors have been examined. Among those factors, gender and diversity have been studied most extensively. First, regarding gender, women are usually found to be stricter than men on ethical decision making (You, Maeda, & Bebeau, 2011). Women are concerned with caring, and men place more emphasis on justice (Gilligan, 1982). Furthermore, according to social role theory (Eagly, Wood, & Diekman, 2000), men have more “agentic” characteristics, and their typical role is as a provider. Therefore, men are more assertive, aggressive, and competitive than women. On the other hand, women have more “communal” characteristics, and the domestic role is their more typical role. Therefore, women are more caring, friendly, and unselfish than men. In the context of GEDM, gender composition could therefore influence a group’s final decision (LePine, Hollenbeck, Ilgen, Colquitt, & Ellis, 2002).

Regarding group diversity, heterogeneous groups have at least two advantages for ethical decision making. First, heterogeneous groups have more links to diverse external stakeholders and have more channels to get information for decision making which could lead to a better understanding of external stakeholders’ needs (Hillman, Cannella, & Paetzold, 2000). Therefore, heterogeneous groups could consider the benefit of more external stakeholders when they make ethical decisions. On the other hand, homogeneous groups have common background, char- acters, and experience, so members can reach conclusions faster than heterogeneous groups (DeGrassi et al., 2012). However, those similarities would limit groups’ moral imagination (Yang, 2013).

Second, diverse groups can have a wider range of skills, knowledge, and styles to apply decision information (Ali, Ng, & Kulik, 2014). For example, women tend to be more risk averse and detail oriented; they want to know more about their decision tasks. Women always try to consider all the relevant factors in a decision making process (Stendardi, Graham, & O’Reilly, 2006). On the other hand, men always use heuristic ways to process information in a more comprehensive way. This helps men to focus their attention on the most dominant and available information (Stendardi et al., 2006). Integrating the advantages of both men and women, gender diverse group may better understand external stakeholders and so arrive at a stricter decision.

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Process of GEDM: SDS Theory

Regarding the GEDM process, three studies that mentioned it have noted two approaches (Abdolmohammadi & Reeves, 2003; DeGrassi et al., 2012; O’Leary & Pangemanan, 2007). The first approach is to use the four-step individual ethical decision making model (Rest et al., 1986) directly to represent GEDM process without supplying any theoretical supports (DeGrassi et al., 2012). The second one is to suggest that groups appear more likely to make a “neutral” decision in order to compromise, rather than the most strictly ethical decision (Abdolmohammadi & Reeves, 2003; O’Leary & Pangemanan, 2007). Although the second way has given us a valuable insight into the GEDM process, this does not answer an important further question: how groups “compromise.” This is the main research question, which is addressed through the perspectives of SDS theory and Chinese culture in this study.

SDS theory (Davis, 1973) is considered to be one of the most prominent theories in current group decision making literature (Laughlin, 2011). This theory has been applied to explain group decision on many tasks, such as jury decision making (e.g., Davis, 1973; Stasser, 1999), intellective tasks (e.g., Laughlin & Ellis, 1986), risk judgment (e.g., Laughlin & Earley, 1982), value judgment (e.g., Green & Taber, 1980), and attitude judgment (e.g., Kerr, Davis, Meek, & Rissman, 1975).

SDS theory divides the group decision making process into four subprocesses. These are individual preference, group distribution, group interaction process, and group response (Stasser, 1999). First, when individuals receive a group decision task, they form a personal preference for a choice or option before group discussion. Second, the group distribution reflects the distribu- tion of group members’ initial preferences. Third, individual initial choices may shift through group interaction, and the group would update its distribution according to individual new choices. Furthermore, the way individual initial choices shift would be determined by the different means (social decision schemes) to reach consensus. Finally, group response involves selecting a choice or option from multiple alternatives as a group decision.

Basing on SDS, group decision making outcomes can be predicted by analyzing the group members’ choice distributions and group interactions (the SDS; Davis, 1973; Stasser, 1999). After individual and group choices have been arrived, the group interaction process for a group decision making task can be identified by statistically comparing predicted group decisions with

FIGURE 1 Schematic of the predictive process of social decision scheme theory. Note. P1, P2, P3, . . ., Pe = probabilities of distinguishable group choices. β1, β2, β3, . . ., βf = probabilities of distinguishable distributions of member decisions. [dfe] = decided by social decision schemes.

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their corresponding actual group decisions (Stasser, 1999). Then an explanation can be found as to how group members reached a consensus for the group decision. This predictive scheme of SDS theory is summarized in Figure 1.

Two basic schemes of SDS have been identified: majority-wins scheme (Hinsz, 1990; Ohtsubo, Masuchi, & Nakanishi, 2002) and truth-wins scheme (Ohtsubo et al., 2002; Tindale & Sheffey, 2002). Under majority-wins scheme, the group choice will be decided by the majority of group members (Davis, 1973). For example, if a five-member group evaluate the risk of a project on a 5-point Likert scale and three members support 3, one supports 1, and the last member supports 4, under the process of majority-wins, group members will ultimately select 3 as the group answer because most members support it. Under truth-wins process, the most correct option will always be accepted by the group (Davis, 1973) even though it is proposed by only one or just a few group members. For example, if other group members in the preceding scenario are convinced by the member who supports 4 and ultimately consider 4 is the correct answer, then they will select 4 as the group answer. This correct option may actually be the really true answer (such as the answer to a math problem) or may just be perceived as the correct option by all group members.

Why do some groups make decision by truth-wins scheme but others by majority-wins scheme? The main reason refers to an important feature of decision making tasks: demonstrability (Swol, 2008). Demonstrability is “how easy it is to demonstrate to group members that an alternative is the correct response” (Hinsz, 1990). Demonstrability has four dimensions (Laughlin & Ellis, 1986). First, group members have a common language to communicate their judgments with each other. Second, group members must have sufficient information to determine the correct answer. Third, uncorrected group members can recognize and accept the correct answer when it is presented by other members. Fourth, the correct members can and will communicate the correct answer with other members.

Typical high demonstrability tasks are intellective tasks where the correct answers can be communicated and recognized easily by group members, such as logic or mathematic questions; in contrast, typical low demonstrability tasks are judgmental tasks that usually have no abso- lutely correct answer, such as behavioral or aesthetic judgments (Laughlin & Ellis, 1986). Generally, groups would apply truth-wins scheme to solve high demonstrability tasks and use majority-wins scheme to solve low demonstrability tasks (Swol, 2008).

Moral tasks are judgmental tasks because they are low in most dimensions of demonstrability. Group members might be different from each other in many moral-related field, such as on major, moral development stages (Kohlberg, 1969), moral attentiveness (Reynolds, 2008), and mental models (Werhane, 1999). Those differences make group members analyze tasks through difference perspectives, emphasize different elements, and cause difficulty in persuading others. Furthermore, a business context is very complex and dynamic, and it will be difficult, if not impossible, to determine which answer is the most strictly ethical one. Therefore, even members who have ethical answers and are willing and able to tell others their answers may lack a common language, information, and possibility for other members to recognize and accept their answers.

SDS may be used to explain the decision making process. However the basic SDS may not be accurate enough to describe the process of group decision making homogeneously in every environ- ment. As mentioned previously, cultural factors impact group decision making, so in reviewing the ability of SDS to explain group decision making in a culturally specific (Chinese) setting, a group behavior mode culturally specific (to China) must be considered. Let us now consider the doctrine of zhongyong, which may dominate group decision making processes in this environment.

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Zhongyong

Zhongyong is the ancient Confucian doctrine of mean (Cheung et al., 2006). It heavily influences Chinese thinking, judgment, and behavior in everyday life (Wang, Tang, Kao, & Sun, 2013; Yao, Yang, Dong, & Wang, 2010), such as Chinese students are more likely than Canada and American students to choose midpoint regarding the use habit of rating scales (Chen, Lee, & Stevenson, 1995). About 850 years ago, Chu Hsi, a Chinese philosopher, explained “Zhong” as “avoiding extremes,” because “to go beyond is as wrong as to fall short.” “Yong” is explained as mediocre or ordinary (Hsi, 1985).

Originally, ancient zhongyong is a kind of Confucian philosophy, which includes moral components (Xu, 1998). However, modern zhongyong implies a mode of action suggesting that people need to think things thoughtfully from different perspectives, seek an appropriate point (i.e., the middle) rather than extremes, and maintain interpersonal harmony in the interac- tion system (Cheung et al., 2003; Ji, Lee, & Guo, 2010; Yang, 2010). Zhongyong, as a mode of action, does not have an intrinsic relationship with the substantive moral principles of Confucianism (Cheung et al., 2003). This mode of action even can be distinguished and isolated from the substantive values of Confucianism (Cheung et al., 2003). Therefore, this study treats zhongyong as the mode of action rather than a kind of Confucius philosophy.

Zhongyong therefore encourages people to make holistic consideration (Ji et al., 2010; Yang, 2010; Yao et al., 2010). Many researchers have found that Chinese regularly behave and make decisions in the way of zhongyong. For example, Chinese are more likely than other cultures to make moderate responses (Chen et al., 1995; Hamamura, Heine, & Paulhus, 2008), take a holistic approach to cognition situations (Ji, Peng, & Nisbett, 2000), engage in dialectical thinking rather than take extreme views (Lee, 2000), and reach a compromised solution that can be accepted by most people if contradictory alternatives exist (Cheung et al., 2003). Therefore, the main effect of zhongyong in a group context is to develop or keep harmony, which can result in the majority or median decision being selected. From the perspective of SDS theory, zhongyong is similar to the majority-wins scheme; however, they operate differently when more than one option is advocated by a similar number of group members. Under zhongyong, the group will tend to take the median choice, whereas all options that gain same number of supporters have an equal chance of being selected under the majority-wins scheme. For example, considering the scenario raised previously, when two members support 2, two support 5, and one supports 3, under the “majority-wins” scheme, the group has a 50% probability of selecting 2 or 5 as the group answer. But under the zhongyong scheme, the group has a 100% probability of choosing 3 as the group answer, because the 3 is the median of options 2 and 5.

METHODOLOGY

Participants

Two hundred domestic undergraduate students majoring in accounting at a Chinese University participated in this study. There were 68 (34%) male subjects and 132 (66%) female subjects. The mean age was 18.8 years. They all had completed similar courses relating to business and

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economics up to this point in their degree program. Therefore it could be anticipated that they all had a similar knowledge of business and ethical decision making at tertiary level.

Sixty-one groups (10 all-male, 20 all-female, and 31 mixed-gender) took part in this study. Mixed-gender groups were composed of three to five members, and all-female and all-male groups were composed of three to four members, except for four groups, which had only two participants. These four groups were formed simply to use all participants, as they had been left out when dividing up the cohorts. They were removed from the subsequent analysis. Therefore, there are valid data for 57 groups (nine all-male, 20 all-female, and 28 mixed-gender). In this university, classmates of each class live in the same hostel (four classmates share a living room); these participants had spent at least 1 year together to get to this point in their degree program. Therefore, all group members within each group knew each other well, so these groups are considered good proxies for real work groups.

Measures

Ethical Decisions

Five ethical accounting scenarios adopted from O’Leary and Pangemanan (2007) were used to assess ethical decisions. In each scenario, subjects were given a business dilemma followed by five options, from which they had to choose one only. A sample scenario is shown in Appendix.

Following Jones’s (1991) definition of ethicality, the ethicality of each option is determined by the extent to which it is both legally and morally acceptable to the larger community. For example, the first option in all scenarios was the most unethical option (illegal and morally unacceptable by society), the third option is neutral (legal but morally unaccepted by society), and the fifth option was the most strictly ethical option (legal and morally acceptable by society). The five options were scored on a 5-point Likert scale with the first option scored as 1 and the fifth option scored as 5. The sum of scores of all five scenarios represented a total score for ethical decision making. Whereas the scoring may not be a perfect measure of the range of ethical behavior, the justification for its use lies in the fact it has been used in similar studies, such as Jones (1991), mentioned previously; Haines and Leonard (2007); and White and Lean (2008). Also, as we employed SDS theory to explore the process of GEDM, scores were needed to compare individual group members’ preferences to group decisions, to enable identification of any social decision schemes in operation.

As the ethical scenarios and scoring section were translated from English to Chinese, translation equivalence (Mullen, 1995) was established. First the scenarios were translated into Chinese by one author, then back into English by a PhD candidate who is familiar with business ethics but was independent of the study. The researchers then performed a final revision to ensure there were no misunderstandings. The Cronbach’s alpha score for responses to the five scenarios was 0.61, which is considered acceptable for this type of experimental study (Caldwell & Moberg, 2007).

Gender and Diversity

The participants were randomly divided into three types of groups: all-female groups, all- male groups, and mixed-gender groups. In the subsequent analysis section, differences between

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all-female groups and all-male groups were used to reflect gender effect on GEDM, and distinction between same-gender groups, including all-female groups and all-male groups, and mixed-gender groups to represent the impact of (gender) diversity on GEDM.

Procedure

For the purpose of reducing self-selection bias, participants were not informed of the real research aim and were simply invited to attend an experiment about business decision making during free class time. Furthermore, to avoid possible framing effects, the words “moral” and “ethics” were not mentioned to participants until they finished the whole experiment. Before the experiment research, assistants read the instructions aloud to all participants, answered partici- pants’ questions, and told participants that they could leave at any time if they felt uncomfortable with the experiment. No one dropped out during the experiment procedures.

Procedures involved two steps. First, all participants completed a survey instrument in which they make decisions for the five ethical scenarios by themselves as individuals and provided the basic demographic details of gender and age. Any communication among participants was forbidden at this step. Second, they were subsequently randomly divided into groups and were informed to complete a further copy of the same survey instrument as groups. Each group was composed of three to five group members rather than by a fixed number of group members. Only at this step were group members allowed to communicate with each other and reach a consensus on each scenario. However, intergroup communication was forbidden. Ample time was given at both the individual and the group steps. When participants finished all experimental tasks, they were given a small gift as compensation for their time.

RESULTS

Individual versus GEDM Results

Figure 2 shows the range of responses for the combined five scenarios, both for individuals and groups. The proportions of individual responses across the choice of options from 1 (most unethical) to 5 (most ethical) were, respectively, 13%, 13%, 27%, 38%, and 8%. The compara- tive group responses were 9%, 14%, 29%, 46%, and 2%. There was no significant difference between those two distributions (χ2 = 0.29, p > .05). Consistent with those results, Table 1 shows no statistically significant difference between individual and group ethical decision.

At the same time, the difference between groups and each group’s strictest member in ethical decision were compared (n = 57). The group member who had the highest total score on individual ethical decision making was chosen as the strictest group member. If a group had more than one strictest member (i.e., two or more group members had the same highest total score), the mean score on each scenario of those strictest members was taken. The score reveals that the strictest group member was significantly stricter than his or her corresponding group in four of the five scenarios and for the combined response. The strictest member also outperformed his or her group in the remaining scenario (Scenario 2) just not to a statistically significant level.

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Gender and Diversity Effects on GEDM Results

Table 2 highlights significant differences between female and male students as regards ethical decision making on both individual and group levels. Individual female responses are signifi- cantly stricter than their male counterparts (t = –2.85, p < .01). Similarly, multiple comparison showed that all-female groups significantly outperformed both diverse gender and all-male groups in ethical decision making; however, there is no significant difference between mixed- gender and all-male groups. In total, mixed gender groups perform similarly to homogeneous groups (t = 0.21, p > .05).

GEDM Process

All groups are included in the following analysis to explore GEDM process in a Chinese business context. Three social decision schemes are described in Table 3. In Table 3, a four- person group is given five options and examples of two different distributions are supplied in the upper two matrices. A three-person group with five options and two different distributions is supplied in the lower two matrices. Those examples provide four possible distributions of group members’ initial preferences on five options of one item are given as scheme examples, and

FIGURE 2 Decision distribution–individual versus group.

TABLE 1 Individual and Group Responses

Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Total

Individuals M 3.10 3.81 2.52 3.09 3.20 15.73 SD 1.34 .65 .89 1.12 1.29 3.40

Group M 3.23 3.82 2.59 3.11 3.11 15.87 SD 1.09 0.50 0.76 0.95 1.17 2.66

Best members M 3.80** 3.98 3.08** 3.77** 3.80** 18.43** SD 1.16 0.70 0.76 0.84 1.09 3.32

**p < .01.

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scheme’s treatment of each distribution (i.e., the predicted possibility of a group adapting each option).

According to SDS, the best social decision scheme can be identified to describe group decision making process by comparing the distributions of group-observed decisions to pre- dicted decisions (Laughlin, 2011). The goodness of fit between observed and predicted distribu- tions was then tested by examining three indexes. These are Dmax, deviation, and accuracy (Kerr et al., 1975; Ohtsubo et al., 2002; Stasser, 1999).

First, Dmax, which is calculated by one-sample Kolmogorov-Smirnov goodness-of-fit test, was employed as it is commonly used in SDS theory research (e.g., Ohtsubo et al., 2002; Stasser, 1999). The Dmax reflects the maximum difference between predicted and observed distributions. The second column of Table 4 shows the Dmax for observed and predicted distributions as per the three decision scheme schemes, for the five different scenarios. Except for the truth-wins scheme, both the majority-wins and the zhongyong schemes were accepted by the one-sample Kolmogorov-Smirnov test. However the Dmax of the zhongyong scheme was less than that of the majority-wins scheme in all five scenarios, which supports the idea that the zhongyong scheme is a better predicting scheme.

Second, the overall deviation of group decision’s predicted and observed distributions for each scenario were counted. One example was given to show how to calculate those deviations. For example, if the predicted distribution is (0.00, 0.08, 0.12, 0.44, 0.36), and the observed

TABLE 2 Gender Differences in Ethical Decision Making

n M SD

Individual Women 132 16.20 3.11 t = –2.85** Men 67 14.78 3.75

Group Women 20 16.81 2.99 F = 4.57* Diverse 28 15.10 2.29 Men 9 14.50 2.49

Note. One participant eliminated from individual responses due to incomplete survey.

TABLE 3 Examples of the Three Schemes

Four group member preference distributions in five options Options A1 A2 A3 A4 A5 A1 A2 A3 A4 A5

N 2 1 0 1 0 1 1 1 0 1 Truth-win 0 0 0 1 0 0 0 0 0 1 Majority-win 1 0 0 0 0 1/4 1/4 ¼ 0 1/4 Zhongyong 1 0 0 0 0 0 1/2 ½ 0 0

Three group member preference distributions in five options N 1 0 1 0 1 1 0 2 0 0 Truth-win 0 0 0 0 1 0 0 1 0 0 Majority-win 1/3 0 1/3 0 1/3 0 0 1 0 0 Zhongyong 0 0 1 0 0 0 0 1 0 0

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distribution is (0.10, 0.15, 0.23, 0.48, 0.05) then the distances are (0.10, 0.07, 0.11, 0.04, 0.31) resulting in an overall distance of 0.63. The distance rankings of each decision scheme within each scenario were counted. The decision scheme that had the minimum distance is ranked 1, and so on. The results are summarized in the second column of Table 5. The prediction of the zhongyong scheme revealed the minimum distance in all five scenarios (rank = 1 in each scenario, sum of ranks = 5). Therefore, the zhongyong scheme (sum of ranks = 5) was again proved better than the truth-wins (sum of ranks = 15) and majority-wins schemes (sum of ranks = 10). For the similar reason, the majority-wins scheme is better than the truth-wins scheme.

Third, accuracy, which represents what percentage of observed group decisions have been correctly predicted by each social decision scheme, was outlined in Table 6. As the second column of Table 6 shows, the prediction of the zhongyong scheme was the most accurate for all five scenarios, and the majority-wins scheme is better than the truth-wins scheme.

In summary, the truth-wins scheme failed to describe the process of GEDM in Chinese business context. The majority-wins scheme is better than the truth-wins scheme in accordance with goodness-of-fit tests. However, the zhongyong scheme is much more accurate than the majority-wins scheme in all three tests.

TABLE 4 Observed and Predicted Probability of Distribution Under Each Option

Total All-Female All-Male Mixed

Dmax T M Z T M Z T M Z T M Z

Scenario 1 .32** .10 .06 .32* .11 .07 .33 .09 .06 .55** .15 .10 Scenario 2 .23* .04 .02 .18 .07 .04 .33 .00 .00 .25 .03 .03 Scenario 3 .42** .08 .06 .32* .07 .07 .33 .15 .67** .60** .17 .20 Scenario 4 .35** .05 .04 .29* .08 .04 .33 .22 .22 .55** .01 .03 Scenario 5 .35** .06 .04 .21 .05 .04 .45* .22 .33 .55** .11 .10

Note. T = truth-scheme; M = majority-win scheme; Z = zhongyong scheme. *p < .05. **p < .01.

TABLE 5 Overall Deviation and Deviation Ranking of Three Schemes

Total All-Female All-Male Mixed

SR SD SR SD SR SD SR SD

Truth-win 15 3.18 15 2.64 14 4.45 15 5 Majority-win 10 1.06 10 1.26 6 2.26 8 1.31 Zhongyong 5 0.67 5 0.64 8 3.55 6 1.20

Note. SR = sum of ranks; SD = sum of deviation.

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Further Exploring Gender, Diversity, and Group Size Effects on GEDM Process

To explore gender and diversity effects on GEDM process, group samples were separated into all-female, all-male, and mixed-gender groups. By contrasting the GEDM processes of all- female and all-male groups, gender effects can be identified. Similarly, diversity effect can be identified by contrasting the GEDM processes of mixed-gender groups to those of all-female and all-male groups together. The last three columns of Tables 4–6 provide indexes for the goodness of fit for all-female, all-male, and mixed-gender groups.

For all-female groups, the Dmax, deviation, and accuracy measurements reveal truth-wins scheme is the worst one among three schemes in describing GEDM process and zhongyong scheme is a better predictor than the truth-wins and majority-wins scheme. For all-male groups, it’s also clear that the truth-wins scheme is the worst one. The zhongyong scheme is better than majority-wins scheme on two of the three indicators. It is better than the majority-wins scheme on both Dmax and accuracy but not so on deviation. For mixed-gender groups, the truth-wins scheme is the worst predictor. The zhongyong scheme is better than the majority-wins scheme on all three indexes although the majority-wins scheme is better than the zhongyong scheme on Dmax for two out of the five scenarios (Scenarios 3 and 4). Therefore, gender and diversity did not seem to influence which decision scheme was utilized by groups to make ethical decisions.

Regarding the effect of group size on the process of GEDM, there was only one five-person group in our sample. This five-person group was excluded in the following analysis, and we examined the goodness of fit of the three social decision schemes in three-person (n = 35) and four-person (n = 21) groups separately. Zhongyong decision scheme performed best for both three-person and four-person groups. In detail, the average Dmax for truth-wins, majority-wins, and zhongyong decision scheme are .28, .08, .07 in three-person groups and .44, .08, .07 in four- person groups; the sum of rank for truth-wins, majority-wins, and zhongyong decision scheme are 15, 10, 5 in three-person groups and 15, 8, 5 in four-person groups; and the sum of deviation for truth-wins, majority-wins, and zhongyong decision scheme are 2.74, 1.45, 0.97 in three- person groups and 4.40, 1.22, 1.05 in four-person groups. Therefore, group size was not found to influence the process of GEDM.

TABLE 6 Accuracy of Three Schemes

Total All-Female All-Male Mixed

T M Z T M Z T M Z T M Z

Scenario 1 0.42 0.69 0.75 0.54 0.83 0.88 0.44 0.54 0.72 0.25 0.56 0.61 Scenario 2 0.67 0.88 0.92 0.64 0.88 0.96 0.67 1.00 1.00 0.70 0.83 0.87 Scenario 3 0.40 0.70 0.77 0.50 0.73 0.88 0.56 0.78 0.67 0.20 0.62 0.71 Scenario 4 0.44 0.75 0.80 0.50 0.71 0.79 0.56 0.67 0.67 0.30 0.83 0.92 Scenario 5 0.37 0.65 0.75 0.50 0.70 0.84 0.11 0.41 0.56 0.30 0.69 0.74 Average 0.46 0.73 0.80 0.54 0.77 0.87 0.47 0.68 0.72 0.35 0.70 0.73

Note. T = truth- scheme; M = majority-win scheme; Z = Zhongyong scheme.

GROUP ETHICAL DECISION MAKING IN BUSINESS 213

DISCUSSION

Business is now transacted globally at an ever increasing rate. However, the quality of business ethics comes under attack regularly and concern for their future continues (De George, 2013). As most business decisions are made by groups (Weiner, Schmitt, & Highhouse, 2012), under- standing the GEDM is therefore critical to enhance business ethics. This is also an increasing area of theoretical importance that is not particularly well understood (DeGrassi et al., 2012; Pearsall & Ellis, 2011). This study addresses this gap through the SDS perspective. Specifically, groups are found to take a zhongyong scheme in Chinese business context. That is, groups tend to choose the most moderate option among the alternative options advocated by group members rather than the most ethical option.

Furthermore, the four major conclusions on GEDM of previous Western empirical studies were tested to see whether they are still valid in a Chinese business context. The results were mixed. Some Western studies’ conclusions, such as that of O’Leary and Pangemanan (2007), were supported. Group decisions were not found to be significantly ethical than those of individuals. Groups appeared more likely to compromise and choose neutral options rather than more ethical options. The strictest group members were also found to be stricter than groups. This finding is similar to results of studies such as Forsyth (2009). All-female groups made stricter ethical decisions than all-male groups, which supports previous conclusions (e.g., Abdolmohammadi & Reeves, 2003; Baker & Hunt, 2003; Sarker et al., 2010).

However, other results did not agree with those of similar Western studies. For example, diversity did not impact group ethical decisions, whereas a study by DeGrassi et al. (2012) had discovered this. The reason this study did not find significant positive effects of diversity might be due to the fact that a different way to operationalize diversity was used. DeGrassi et al. operationalized diversity based upon race, whereas we operationalized diversity based upon gender. Therefore, these results might imply that different types of diversity have different effects on GEDM.

This is the first empirical study focusing on the process of business GEDM in a Chinese cultural context. We consider that it may contribute to relevant research in three ways. First, our findings update GEDM literature by opening the black box—the process of GEDM. The debate on whether groups or individuals are stricter decision makers in an ethical decision making context is continuing over the past three decades (Abdolmohammadi et al., 1997; Abdolmohammadi & Reeves, 2003; Nichols & Day, 1982; O’Leary & Pangemanan, 2007). The present study reconciles these conflicting theories and findings by opening the process mechanism of GEDM. In so doing, groups are found to take the perspective of zhongyong so that the outcome of GEDM is not significantly different with individual ethical judgment. This finding echoes the calls of Treviño et al. (2014) for deep examination of GEDM process rather than just comparing the outcome of group and individual ethical decision.

Second, SDS theory is introduced to study the process of GEDM as a theoretical perspective. Studying how groups make ethical decision is critical in understanding collective ethical decision making in organizations (Treviño et al., 2014), but the issue appears underexplored in the current literature. This shortcoming may be due to a lack of appropriate theory to examine the process of GEDM. Most relevant studies have to infer the process of GEDM indirectly through comparing the outcome of GEDM and individual ethical decision making (e.g., Nichols & Day, 1982; O’Leary & Pangemanan, 2007). To deal with this shortcoming, this study employs

214 YANG, JI, O’LEARY

the SDS theory to explore the process of GEDM. This approach helps examine how individual preferences translate into group decisions and may inspire future studies.

Third, this study adds to current group decision research by demonstrating the effect of a cultural characteristic on GEDM. To focus on the ethical decision making process at group level in a Chinese business context, this study came up with the zhongyong scheme (based on both existing SDS theory and a Chinese cultural factor, the zhongyong doctrine). Results indicate that the zhongyong scheme is better than majority-wins and truth-wins schemes in predicting GEDM. Although many scholars emphasize the impact of national culture (e.g., Hofstede, 2003), scant empirical studies demonstrate this cultural effect on decision making processes, especially for group decision making. Our results highlight the importance of cultural influence on the process of group decision making.

This study also has implications for managerial practice. First, the results of this study suggest that if we really want to promote Chinese GEDM, all individual group members’ ethical levels have to be enhanced, rather than hoping that one ethics expert, such as a chief ethic officer, can influence the others to reach the most ethical option. This is because results suggest that Chinese groups will not choose the most ethical option. Rather, they will choose the most moderate of all choices advocated by the majority (the zhongyong scheme). Second, as more and more foreign companies have entered China to do business, they should be aware of any unique cultural factors that may impact the decision making processes. This study can help them understand how Chinese groups make ethical business decisions and how zhongyong would impact on those decisions.

Limitations and Directions for Future Research

Despite some important contributions, there are some potential methodological and theore- tical limitations in this study that could be addressed by future studies. Regarding methodo- logical limitations, whether the answering scale offered to participants after each scenario truly reflects the full range of ethical options available is debatable. However, within the confines of the current study it was deemed the only practical way to evaluate and assess results (Abdolmohammadi & Reeves, 2003; O’Leary & Pangemanan, 2007). Second, stu- dents were used as participants in the study as proxies for actual business people. Whereas there is no reason to think their group decision process would be different to that of experienced business people (Randall & Gibson, 1990), the possibility must still be recog- nized. Third, the format of options is fixed across five scenarios, that is, the first option is always a response to act most unethically and the last option is always a response to act most morally. So the possibility of demand characteristics should be concerned. Forth, participants were divided into groups through random assignment, which could attenuate some individual and group’s differences, such as personality, collectivism, confidence, and self-efficacy. However, this random assignment may limit the generalizability of our results. Future researchers could use self-select groups to explore their decision making process and use more sophistical means to control or test the effects of individual and group characteristics on the process of GEDM.

Fifth, the effect of group size on GEDM process was tested by comparing the GEDM process of three- and four-member groups. However, larger groups would have more unique information (Stasser & Stewart, 1992) and would mention shared information more

GROUP ETHICAL DECISION MAKING IN BUSINESS 215

frequently than smaller groups (Stasser, Taylor, & Hanna, 1989). Furthermore, social “loaf- ing” would be more intensive in larger groups (Lu, Yuan, & McLeod, 2012). Therefore, group size would influence group information and the process that is applied by groups to handle this information. It might be possible that the variance of group size is too small to detect group size effect in this study. Future researchers could enlarge the variance of group size to explore group size effect on the process of GEDM. Sixth, all group members had equal status in their group in this study. However, there is usually at least one leader in a real business group environment, and leaders have more opportunity to influence group decisions (Westphal & Milton, 2000). This is especially true in a Chinese business context because Chinese culture is high on power distance (Hofstede, 2003). Therefore, there may be a gap between our results and real Chinese business GEDM, which needs be addressed in further research. Seventh, participants responded to the same scenarios twice in this study; therefore, demand effects may be introduced. However, because the social decision scheme theory was employed to examine the process of GEDM, we have to investigate both individual prefer- ences and group decision. Therefore, repeated measurement is inevitable in SDS approach. This kind of study process has been applied in examining the group decision process in a body of studies (e.g., Laughlin & Earley, 1982, 1986; Stasser, 1999), but demand effect should not be neglected. Future researchers could try to examine whether demand effect really matters in studies that follow SDS approach. Finally, only gender diversity is manipu- lated in this study, and gender and race diversity (DeGrassi et al., 2012) have shown different effects on GEDM. Future research could attempt to address this difference and go beyond surface-level diversity to test the effect of deep-level diversity on GEDM.

Regarding theoretical limitations, this study claimed that the zhongyong scheme can explain GEDM in Chinese business contexts. However, it was tested only within Chinese culture rather than between cultures. Therefore, it is too early to conclude that the zhongyong scheme is specific to a Chinese context. Future research could compare the GEDM process between China and other countries to consider if the zhongyong could be generalized to other countries. As many other countries or regions are affected intensively by Confucian culture, such as Hong Kong, Taiwan, and Japan, it could work there as well. Second, there might be interactive effects of gender and issue characteristics on the GEDM process. This could also be explored further, as could the possible impact of moral intensity (Jones, 1991) on GEDM. Similarly, given fault lines or diversity may foster subgroup hostility and competition in groups (Bezrukova, Thatcher, Jehn, & Spell, 2012; Meyer, Shemla, Li, & Wegge, 2015). The process of GEDM may be influenced by fault lines. Furthermore, decision ambiguity could also be addressed in future studies by offering scenarios with more alternative solutions. In general, exploring antecedents of the process of GEDM may be a meaningful avenue for future research.

FUNDING

This research was supported by Grant No. 71562017 and Grant No. 71262001 from the National Natural Science Foundation of China.

216 YANG, JI, O’LEARY

ORCID

Jianfeng Yang http://orcid.org/0000-0001-9851-7523

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APPENDIX

Example Ethical Scenario

You have completed your degree and have spent six months in your first job, as a trainee accountant in a medium-sized accounting firm. Much of the firm’s revenues come from a few large local clients. One of these has approached your firm to prepare a set of accounts as part of a long-term bank loan application. You perform ratio calculations and find the “times interest earned” ratio, appears low. This implies your firm’s client will probably have its bank loan application rejected. You report this to your superior, and a meeting with the client is arranged. During the meeting, the client company requests that accountants from your accounting firm working on this case make necessary ‘adjustments’ so that the ratio will look better than it actually is. They appeal to you and your colleagues’ sense of loyalty saying they need this loan and that this quarter’s low profit will improve in the next. Your firm sympathises, and then agrees to make the necessary adjustments. Subsequent sets of financial statements will be sent to the bank over the life of the loan.

Please circle one option:

Would you: Agree with your fellow accountants and make the necessary adjustments? Agree with your fellow accountants and make the necessary adjustments this time, but insist the practice stops then? Disagree with your fellow accountants, resign from the firm and tell no one? Disagree with your fellow accountants and advise them to inform the relevant corporate and professional authorities (but inform them you won’t pursue the matter if they don’t)? Disagree with your fellow accountants and immediately inform relevant corporate and profes- sional authorities?

220 YANG, JI, O’LEARY

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