How can companies decrease the disruptive effects of stretch goals? The moderating role of interpersonal- and informational- justice climates

Abstract

This article attempts to determine whether stretch goals disrupt organizations and, if so, how organizations minimize those disruptions. We consider how two different kinds of justice climates − interpersonal and informational − interact to influence employees’ unethical behavior and relationship conflicts in the face of stretch goals. The results from 117 departments (including a total of 351 employees and 117 managers) in six Chinese banks support our hypotheses that stretch goals foster unethical behavior and intensify relationship conflict among employees. Furthermore, we find that informational-justice climates greatly reduce the disruptive effect of stretch goals on unethical behavior, and we find that interpersonal-justice climates greatly reduce the disruptive effect of stretch goals on relationship conflict. Implications and suggestions for future research are discussed.

Keywords

informational-justice climate interpersonal-justice climate relationship conflict stretch goals unethical behavior

When employees behave in undesirable ways, it’s a good idea to look at what you’re encouraging them to do. (Bazerman and Tenbrunsel, 2011: 60)

Introduction

A large amount of literature addresses the benefits of setting goals. Especially with respect to motivation theory, goal-setting has become an important and effective managerial tool (Locke and Latham, 1990) because people are prone to exert more effort and work more persistently to meet difficult goals than they are when they face less difficult goals. However, difficult goals may not have the same power anymore − several researchers attribute ‘stretch goals’ (goals that are extremely difficult and extremely novel, according to Sitkin et al., 2011) to false sales reports and other relevant wrongdoing (Jensen, 2001).

Part of the problem is that stretch goals are seemingly impossible goals, but their use remains fairly common (Collins and Porras, 1994; Takeuchi et al., 2008; Thompson et al., 1997). They are common because they may promote new ways of thinking and acting (Hamel and Prahalad, 1993; Rousseau, 1997), and they can therefore enhance tangible performance outcomes (Cyert and March, 1963). As Rousseau (1997: 528) suggests, ‘stretch goals motivate high performance by mandating creativity and assumption-breaking thinking.’

The stretch goal literature carefully examines the relationships among stretch goals, organizational performance (Lant and Shapira, 2008; Raisch and Birkinshaw, 2008; Sitkin, 1992), and learning (Barnett and Pratt, 2000; Baumard and Starbuck, 2005; D’Aveni and MacMillan, 1990; Kim, 1998). However, managing the aforementioned unintended ethical perils of stretch goals, as well as other disruptive effects, is beyond the scope of the prior research.

This article focuses on two unintended perils associated with stretch goals: unethical behavior and relationship conflicts. Unethical behavior is by definition morally unacceptable to the larger community (Jones, 1991); it refers to cognition-driven behavior ‘from the head’. It is also an instrumental inference that one makes from information about others’ behavior under specific circumstances (Kish-Gephart et al., 2010). Using Jones’ (1991) definition, in this article unethical behavior includes procrastinating, lying, stealing, concealing the truth, harming those who are defenseless, and so on. Several papers suggest that setting difficult and specific performance goals for employees may have unintended consequences (Latham, 1986; Latham and Wexley, 1981; Locke and Latham, 1990), but only a handful suggest a link between goal-setting and unethical behavior (Barsky, 2008; Jensen, 2003; Locke, 2004; Ordonez et al., 2009; Schweitzer et al., 2004).

By contrast, relationship conflict is interpersonal strife associated with differences in personalities or matters unrelated to the job (Jehn, 1995); it refers to affect-driven behaviors ‘from the heart’. It is a disruptive behavior that hampers emotional bonds among employees (Bell and Song, 2005). Prior research shows that the extreme novelty and difficulty of stretch goals could directly impair coordination among employees (Lawrence and Lorsch, 1967; Martin, 1992; Sitkin et al., 2011), but there is little evidence of a direct relationship between stretch goals and relationship conflict. Therefore, in this article we use social-exchange theory and uncertainty-management theory to explain the disruptive effects of stretch goals both on unethical behavior and relationship conflict.

Sitkin et al. (2011) suggest that employees using ordinary means to achieve stretch goals could easily succumb to the seduction of using extraordinary means, such as falsifying records. However, few empirical studies address the following question. If stretch goals create unethical behavior and relationship conflict among employees, how do companies decrease such disruptive effects, aside from just lowering the bar and creating easier goals? To answer such an important question, and given that justice climate − the degree of organizational fairness that a team perceives as a whole (Li and Cropanzano, 2009; Rupp and Paddock, 2010) − is an important predictor of organizationally relevant criteria (Ambrose and Schminke, 2007; Rupp et al., 2007a, 2007b), we test whether two types of justice climates (informational justice and interpersonal justice) mitigate the disruptive effects of stretch goals on unethical behavior and relationship conflicts.

Our work takes the literature on stretch goals and justice theory in several new directions. First, it improves the understanding of whether and why stretch goals encourage unethical behavior and relationship conflicts. From the perspective of social-exchange theory and uncertainty-management theory, we develop a theoretical argument that extremely novel and very difficult goals − stretch goals − precede cognition-driven behavior (unethical behavior) and affect-driven behavior (relationship conflict) in one research framework.

Second, this study improves the understanding of how to mitigate the disruptive effects of stretch goals on both unethical behavior and relationship conflicts. From the perspective of justice theory, we suggest that managers cannot take the disruptive effects of stretch goals for granted. That is, disruptive effects on unethical behavior are contingent on perceived informational-justice climate, and disruptive effects on relationship conflict are contingent on perceived interpersonal-justice climate.

Third, this study fills a research gap. There is no one empirical research paper that focuses on the disruptive effects of stretch goals or on ways to mitigate such effects. Our study examines employees in the Chinese banking industry, a unique population objective that is engaged in ethically complicated behaviors. Due to a high rate of organizational malfeasance in the banking industry in China (Xin, 2006; Zhang et al., 2009), we believe this sample provides an excellent starting point for examining the disruptive effects of stretch goals. We focus on unit-level outcomes because group members exposed to similar environmental cues regarding norms for appropriate behavior tend to behave in a fairly homogenous manner (Salancik and Pfeffer, 1978). In all, we present a comprehensive approach to understanding the disruptive effects of stretch goals by exploring how stretch goals matter and the conditions under which they matter more or matter less.

Concept definition and hypothesis development

Stretch goals

Prior research (Collins and Porras, 1994; Hamel and Prahalad, 1993; Rousseau, 1997; Sherman, 1995; Sitkin, et al., 2011) defines a stretch goal as an organizational goal with an objective probability of attainment that may be unknown but is seemingly impossible given the organization’s current practices, skills, resources, and knowledge. Sitkin et al. (2011) highlight two ways that stretch goals differ from ordinarily difficult goals: (1) extreme difficulty, which renders the goal seemingly impossible given current situational characteristics and resources; and (2) extreme novelty, or no known paths for achieving the goal given current capabilities (i.e. current practices, skills, and knowledge). Although these dimensions imply each other, extreme difficulty and novelty stress different aspects of a stretch goal’s construct (the specified outcome and knowledge of the means to reach it, respectively), and they directly relate to the two core outcomes of interest (unethical behavior and relationship conflict).

Disruptive effects of stretch goals on unethical behavior

Once a goal becomes too difficult to reach, the employees responsible for meeting the goal may perceive that the organization is exploiting them. Accordingly, their propensity to work in the organization’s best interest diminishes. Their activities may even harm the organization (Glomb and Liao, 2003). From the perspective of social-exchange theory, team members feel that the organization does not care about their suffering and does not stand in their shoes. Team members in these situations tend to form a kind of negotiated exchange (Bazerman et al., 2000) rather than reciprocal exchange (Blau, 1964; Emerson, 1976; Flynn, 2003) or generalized exchange (Van Dyne et al., 1995; Yamagishi and Cook, 1993) with others.

In a negotiated exchange, actors focus on the tangible benefits they may gain from participating in the exchange (Flynn, 2005). In the context of stretch goals, team members will spare no effort to achieve the goal; therefore, they simply focus on finishing the work-related task. They value the ends rather than the means and thus try their best to find shortcuts, even if those shortcuts jeopardize the firm’s long-term development and sustainability. Team members have no time to consider issues unrelated to the task that achieves the goal; they are not willing to think more comprehensively or pay more attention to the potential long-term consequences of their actions. Such narrow focus diminishes an important element of ethical behavior: ethical recognition in Jones’ (1991) model, in which the individual categorizes the morality of incoming information. This results in an increase in unethical behavior.

Another dimension of stretch goals is extreme novelty. If there is no known path for achieving a goal, it usually implies an increase in uncertainty. In other words, because nobody has reached the goal before, team members don’t know ‘how deep the water is’. If they cannot finish the task and achieve the goal, they have no idea of what the consequences will be. Will they be fired? Reprimanded? Demoted? According to uncertainty-management theory, employees tend to exhibit risk-taking behaviors when they face this kind of uncertainty (Takeuchi et al., 2012). Although they know risk-taking behavior may create future problems for the organization, many will find ways to justify the behavior.

Thus, from the perspective of social-exchange theory and uncertainty-management theory, we suggest that stretch goals boost unethical behavior in work units:

Hypothesis 1: Stretch goals are positively related to unethical behavior in work units.

Disruptive effects of stretch goals on relationship conflict

Numerous scholars (Locke and Latham, 1990, 1994; Mento et al., 1987; Wood and Locke, 1987) recognize that goal-setting directs effort and attention toward relevant activities and away from irrelevant activities. However, stretch goals, by definition, set aggressive targets that may not be attainable with a company’s current capabilities. Accordingly, the actions associated with stretch-goal implementation could create too large a break from past norms (March, 1976). Stretch goals require more effort from everyone, sometimes to the point that employees focus only on goal-relevant activities and have no time and energy to care for peers, help others, or show empathy toward one another. Once the goals are too difficult to reach, team members tend to form negotiated exchanges with other actors (Bazerman et al., 2000), during which actors neglect the social rewards of participating in more exchanges (Flynn, 2005).Thus, employees can become less willing to express their opinions, demonstrate respect, or stand in other employees’ shoes when making decisions; in extreme circumstances, they may verbally attack other employees.

Furthermore, the extreme novelty and difficulty of attaining stretch goals can directly impair coordination. According to Lawrence and Lorsch (1967) and Martin (1992), the plurality of ‘stories’ ascribed to the actions and outcomes associated with attempting to reach a stretch goal is likely to impair coordination among subunits that have separate purposes, specialties, and interests. Based on these ideas, Wright et al. (1993) finds that when a goal exceeds a certain degree of difficulty, employees help one another less. Furthermore, the extremity of stretch goals can dampen employee satisfaction and morale because the attempts to reach the goals are likely to involve one or more failures (Sitkin et al., 2011). Therefore, from the perspective of social-exchange theory, we hypothesize that when subject to a stretch goal, employees are more likely to behave destructively rather than constructively when managing the tensions that inevitably arise. In turn, tension and friction increases when managers implement stretch goals, which can weaken employee relationships (Bateman and Porath, 2003).

Additionally, Barnett and Pratt (2000) point out that stretch goals can elicit negative affective responses that often accompany change. Furthermore, Lind and Van den Bos (2002), Sitkin (1992), Sitkin et al. (2011), and Van den Bos and Lind (2002) suggest that seemingly impossible goals make these negative-affective responses contagious, whereby a sense of collective fear, helplessness, and demotivation impedes a willingness to try new approaches. Under such conditions, stretch goals create salient effects that dwarf incentives to succeed. When team members are embedded in such negative emotion, relationship conflicts are in turn likely to increase (Barnett and Pratt, 2000). Furthermore, when there is a chance that the organization will not meet a stretch goal in the near future, tension and friction among employees increases (Batman and Porath, 2003).

Thus, from the perspective of social-exchange theory and uncertainty-management theory, we suggest that stretch goals boost relationship conflicts in the work unit:

Hypothesis 2: Stretch goals are positively related to relationship conflict in work units:

If stretch goals drive unethical, cognition-driven behavior (behavior ‘from the head’) and contentious, affect-driven behavior (behavior ‘from the heart’), then how can companies decrease such disruptive effects? We argue that the justice climate, defined as the degree of fairness perceived by the team as a whole (Li and Cropanzano, 2009), is an effective weapon.

The mitigating effect of justice climate on unethical behaviors and relationship conflicts

Uncertainty-management theory posits that individuals use information about the various facets of organizational justice as heuristic devices for use in socially uncertain situations (Lind and Van den Bos, 2002). Thus, by integrating justice theory (Cropanzano et al., 2007; Li and Cropanzano, 2009) and uncertainty-management theory (Lind and Van den Bos, 2002; Van den Bos and Lind, 2002), the uncertainty associated with stretch goals should fall greatly. Team members in an environment with a high justice climate should be less likely to exhibit ethically risky behavior, because they are less worried about the consequences of the organization failing to meet a stretch goal. In fact, the lower level of worry may actually enhance team members’ identification with organizational goals (Olkkonen and Lipponen, 2006), even goals that seem impossible, as well as their motivation to display a cooperative attitude at work (Lind and Tyler, 1988; Lind and Van den Bos, 2002; Tyler and Lind, 1992).

Furthermore, by integrating justice theory (Cropanzano et al., 2007; Lavelle et al., 2007; Li and Cropanzano, 2009; Rupp and Paddock, 2010) and social-exchange theory (Blau, 1964; Flynn, 2005), it is easy to see that when team members perceive that organizations treat them fairly in daily encounters, they are more loyal to the organization and less likely to do bad things (Colquitt, 2001; Crawshaw, 2006; Lavelle et al., 2007). Such perception may diminish employees’ fears of being exploited (Brockner et al., 1997), thereby pushing them to consider the long-term effects of their choices, rather than taking shortcuts − that is, they understand that the means are as important as the ends.

By establishing such reciprocal-exchange relationships rather than the aforementioned negotiated-exchange relationships, actors stop neglecting social rewards (positive affects) and start communicating and helping each other, thereby significantly reducing relationship conflict.

Informational-justice and interpersonal-justice climate

Organizational-justice research demonstrates that people’s judgments of fairness are a function of three types of justice: distributive justice, or the perceived fairness of outcomes (Adams, 1965); procedural justice, or the procedures used to derive outcomes (Leventhal, 1980; Thibaut and Walker, 1975); and interactional justice, or the degree to which individuals treat one another with interpersonal sensitivity (Bies and Moag, 1986).

According to Greenberg (1993), interactional justice has two dimensions: interpersonal justice (based on dignity, respect, and propriety) and informational justice (based on justification, truthfulness, and providing adequate explanations for decisions). Numerous researchers also support separating interactional justice into two dimensions (Brockner and Wiesenfeld, 1996; Cropanzano and Greenberg, 1997; Folger and Cropanzano, 1998).

Traditionally, the concept of organizational justice is an individual-level phenomenon. Existing research finds that organizational justice is likely to exert considerable influence on employee behavior (Brown et al., 2010; EI Akermi et al., 2010), undoubtedly including ethical/unethical behavior. In recent years, this has changed, as a number of research studies explore justice as a collective or group-level concept that is an important predictor of organizationally relevant criteria (Ambrose and Schminke, 2007; Rupp et al., 2007a, 2007b), such as unit-level turnover, customer satisfaction, unit-level burnout, group-level helpfulness, and group performance (Chen et al., 2005; Liao and Rupp; 2005; Lin et al., 2007; Moliner et al., 2005; Simons and Roberson, 2003). For example, Mayer et al. (2007) examine leader personality as a potential antecedent of work-group justice climate and find that leader agreeableness is positively related to interpersonal- and informational-justice climates. Liao and Rupp (2005) find that the climate for both procedural justice and informational justice predicts group performance and organizational-citizenship behavior (OCB). Likewise, Spell and Arnold (2007) find that the interaction of procedural-justice climate with distributive-justice climate is a predictor of employee mental health. This evidence suggests that research would benefit from examining multiple types of justice climates (see also Mayer et al., 2007; Moliner et al., 2005).

Given the mitigating role that justice climate plays in the relationship between stretch goals and unethical behavior, we predict that informational- and interpersonal-justice climates have mitigating effects on this relationship as well.

The mitigating function of the informational-justice climate

Informational justice refers to employee perceptions of the explanations for certain procedures or outcomes (Colquitt, 2001; Greenberg, 1993). Informational justice should mitigate the unethical behavior associated with stretch goals because employees understand the rationale for the organization’s seemingly unreasonable decision to set extremely aggressive, novel goals.

Thus, to create informational justice, managers should provide detailed explanations for stretch goals. The explanations should include specific reasons and interpretations that acknowledge both the threat and the potential opportunity. This, in turn, should greatly decrease unethical behavior.

Additionally, informational justice sends a strong signal to employees that the organization respects employees enough to provide adequate explanations for specific decisions (Greenberg, 1993). This, in turn, should reduce (via the employees’ sense of empathy) the temptation to cross the ethical line when facing a stretch goal.

Furthermore, informational justice should reduce negative affective responses and negative-affect contagion caused by the uncertainty that stretch goals produce. Relationship conflicts should correspondingly decrease, suggesting that informational-justice climates represent an equitable environment that should mitigate much of the tension employees feel when facing a stretch goal.

Thus, although stretch goals play a very important role in causing unethical behavior and intensifying relationship conflicts in work units, we suggest that the perceived presence of an informational-justice climate mitigates these disruptive effects of stretch goals. This leads us to the third hypothesis:

Hypothesis 3a: The relationship between stretch goals and unethical behavior is weaker in work units with strong informational-justice climates.

Hypothesis 3b: The relationship between stretch goals and relationship conflict is weaker in work units with strong informational-justice climates.

The mitigating function of the interpersonal-justice climate

A stretch goal can contaminate a whole organization with anger, anxiety, dismay, and so on (Sitkin, 1992; Sitkin et al., 2011), all of which are the bases of relationship conflict (Barnett and Pratt, 2000; Sitkin, 1992; Sitkin et al., 2011). Interpersonal justice refers to the extent to which authorities or parties involved in executing procedures or determining outcomes treat employees with dignity and respect (Bies and Moag, 1986; Colquitt, 2001). Interpersonal justice should mitigate the relationship conflict associated with stretch goals because it indicates support for employees who are facing stretch goals (Lawrence and Lorsch, 1967; Martin, 1992; Sitkin et al., 2011; Wright et al., 1993), thereby relieving negative-affective responses (Cropanzano et al., 2000; Rupp et al., 2008). Therefore, we suggest that, as is the case with informational-justice climates, interpersonal-justice climates hinder the negative contagion that stretch goals and the ensuing relationship conflicts cause.

Furthermore, we suggest that interpersonal justice mitigates ‘the ends justify the means’ forms of unethical behavior in the face of stretch goals (Brown et al., 2010; EI Akermi et al., 2010). For example, perceived interpersonal justice is associated with increased OCB (Fassina et al., 2008; Karriker and Williams, 2009; Lavelle et al., 2007; Rupp and Cropanzano, 2002), decreased intentions to leave the organization, and so on (Colquitt, 2001). Therefore, interpersonal justice can help form a constructive link between organizations and employees, consequently decreasing the possibility of unethical behavior, such as sabotage (Ambrose et al., 2002), theft (Colquitt et al., 2006; Greenberg, 1990, 1993), or falsifying reports (Jensen, 2001).

Accordingly, although stretch goals play a very important role in causing unethical behavior and intensifying relationship conflicts in work units, we suggest that perceived interpersonal justice helps relieve these disruptive effects. This leads us to the fourth hypothesis:

Hypothesis 4a: The relationship between stretch goals and unethical behavior is weaker in work units with strong interpersonal-justice climates.

Hypothesis 4b: The relationship between stretch goals and relationship conflict is weaker in work units with strong interpersonal-justice climates.

Data collection for hypothesis testing

The sample

We chose the banks in China as the sampling target to testing stretch goals, informational justice, interpersonal justice and its influence on unethical behavior and relationship conflict for the following reason. There is a high rate of organizational malfeasance in the banking industry in China. For instance, according to Xin’s (2006) research, in 2005, 1272 crimes and irregularities were detected in banking industry in China, causing a total monetary loss of 1.47 billion RMB. Furthermore, most of the crimes in the banking industry in China were difficult to detect because of low visibility and high complexity. As such, it is an urgent and prerequisite task for the scholars to find out effective ways to decrease the employees’ unethical behavior, so that it can prevent these unethical behaviors from exaggerating into irregularities, or even subsequently severe crimes. Furthermore, with regard to the previous studies on stretch goals (Golovin, 1997; Hughes, 2001; Kerr and Landauer, 2004; Sherman, 1995; Sitkin et al., 2011), no one has empirically examined the effect of stretch goals and interactional justice on employees’ behavior in the banking industry, especially in China, which provides scholars with an excellent experimental context to dig into such relevant research.

Although merit of single industry research is undesirable (Delery, 1998) because industry context has an effect on the relationship between variables of interests, and thus constrains the external validity of the findings, by focusing on one industry, researchers have access to an in-depth understanding of stretch goals and unethical behavior and relationship conflict in the banks of China. This method was adopted previously in numerous studies (King, 1997; Near et al., 2004), which highlighted the advantage that ‘the unknown sources of variance due to organization type could be controlled’ (Near et al., 2004: 224).

The procedures

From March to May 2011, we recruited participants from 189 units in banks of northwestern China. Business administration students of a large northwestern university contacted each bank. Students hand-delivered one survey packet to participating departments within the banks. The packets included three employee surveys and one supervisor survey. Each packet included clear instructions regarding who should fill out the surveys and included self-addressed stamped envelopes for the participants to send their completed surveys back to the researchers. Further, the instructions indicated that the three employees agreeing to participate must be the subordinates of the supervisor who also agreed to participate in the study. The respondents were told that their responses would be confidential. We collected data in this manner from multiple sources within each bank. This approach was designed to tap the sources of information within each organization that were most relevant to our research questions and to overcome common method variance in the survey responses. The questionnaires were prepared in English, translated into Chinese by a professional translator, and then back-translated into English by another professional translator. The back-translated versions were compared with the originals to ensure accuracy.

The survey began with an introductory letter from the researchers, followed by instructions on how to complete the surveys. Subordinate participants responded to a series of questions regarding stretch goals in their department, informational justice, and interpersonal justice. Manager participants responded to questions regarding the unethical behavior and relationship conflict in his/her work unit. The questionnaires administered to subordinates and the managers ended with demographic questions, such as gender, department tenure, and so on.

We received data from a total of 128 departments out of 189 for a total response rate of 67.72 percent. Eleven departments returned two employee surveys. Previous research suggests three responses is a sufficient number to aggregate to the department level (Colquitt et al., 2002; Mayer et al., 2009; Richardson and Vandenberg, 2005). According to this, we only included departments with three employee respondents, leaving a total of 117 departments with usable employee data. We also collected data from 132 department managers. The employee and manager responses were matched, leaving a total of 117 departments with matched data. Thus, these 117 departments (including a total of 351 employees and 117 managers) in six banks were used to test the hypotheses in this study.

Regarding demographics, 52 percent of the employee respondents were male, and the average age of the participants was 38 years (SD = 10.25). The employee participants had an average organizational tenure of 5.8 years (SD = 6.2). Sixty-five percent of the manager respondents were male, and the average age of the participants was 40.5 years (SD = 9.6). The manager participants had an average department tenure of 10.96 years (SD = 7.38).

The measures

All items are provided in Appendix I. All ratings were made on a 7-point scale (1 = strongly disagree; 7 = strongly agree).

Stretch goals

According to the prior research (Collins and Porras, 1994; Hamel and Prahalad, 1993; Rousseau, 1997; Sherman, 1995; Sitkin et al., 2011), and the two characteristics of stretch goals − extremely difficult and extremely novel (Sitkin et al., 2011) − we used six items to measure this scale (α = 0.90), and the specific procedures are in Appendix II.

Interpersonal justice

We measured interpersonal justice using Colquitt’s (2001) 4-item scale (α = 0.89).

Informational justice

We measured informational justice using Colquitt’s (2001) 5-item scale (α = 0.87).

Unethical behavior

Department managers rated their department’s unethical behavior using Akaah’s (1996) 17-item unethical behavior scale (α = 0.89).

Relationship conflict

Department managers rated the amount of relationship conflict within their departments using Jehn’s (1995) 4-item relationship conflict items (α = 0.91).

Control variables

We included control variables at three levels to rule out explanations representing alternatives to our model. At the individual level (level 1), we controlled for employees’ age, gender, and education level. At the department level (level 2), we controlled for department size (i.e. number of members). Numbers of departments and numbers of employees within a bank were controlled for at the bank level (level 3).

Aggregation analysis

Before aggregating individual responses into department-level variables, we assessed whether sufficient agreement exists among department members to justify aggregation of the measures of stretch goal, interpersonal justice, and informational justice to the unit level (James, 1982; Klein and Kozlowski, 2000). We did so by calculating average deviation (AD_M) scores (Burke and Dunlap, 2002) for each work unit. AD_M scores have at least two advantages over alternative means of assessing agreement such as r_wg scores. First, unlike r_wg assessments, they do not require that the researcher generate, a priori, the form of the null response distribution and accurately allocate percentages to each response. Second, because they yield estimates of agreement in the same units as the original scale, they provide a more direct conceptualization and assessment of agreement (Burke and Dunlap, 2002).

The AD_M index reflects the degree of interrater agreement by measuring the dispersion of responses around the mean member response. Lower scores indicate greater agreement, and Burke and Dunlap (2002) identified 0.80 as the cutoff value for five-item scales. That is, values below 0.80 indicate that sufficient agreement exists to render aggregation appropriate.

We calculated AD_M scores for each department across the three variables that were assessed by employees (stretch, interpersonal justice, and informational justice). The overall mean AD_M for the four variables, across all departments, was 0.50. The mean AD_M values for the four aggregated variables (stretch goal, interpersonal justice, and informational justice) was 0.57, 0.45, 0.47 respectively. All of these values are below the cut-off suggested by Burke and Dunlap (2002). We therefore retained all departments in the analyses (Varela et al., 2008).

Results

Descriptive statistics

Table 1 represents the descriptive statistics and zero-order correlations among variables in the study.

Table 1.

Descriptive statistics^a.

Variable	Mean	SD	1	2	3	4	5	6	7	8	9	10	11
1. Employee age	36.59	3.12
2. Employee gender	1.34	0.08	0.06
3. Employee education	3.27	0.08	−0.09	0.13
4. Department size	6.43	0.07	−0.04	−0.19	0.12
5. Number of departments in a bank	17.26	0.35	0.02	−0.15	−0.28*	−0.18
6. Number of employees in a bank	110.87	1.97	−0.01	−0.22	−0.21	0.23	0.88**
7. Stretch goal	3.65	1.47	0.03	−0.08	−0.09	0.15	−0.01	0.09	(0.90)
8. Informational justice	3.09	0.28	−0.01	−0.01	−0.12	−0.11	0.22	0.18	−0.12	(0.87)
9. Interpersonal justice	3.11	0.35	0.03	0.11	0.01	−0.09	0.06	0.06	0.11	0.57***	(0.89)
10. Unethical behavior	2.63	0.87	0.04	0.13	0.21	0.17	−0.03	0.02	0.29**	−0.27**	−0.21**	(0.89)
11. Relationship conflict	3.06	0.52	0.04	0.10	−0.13	0.15	0.21	0.28	0.34**	−0.18*	−0.23**	0.45***	(0.91)

n = 351 at the individual level, n = 117 at the department level, and n = 6 at the organizational level; reliabilities of the scales are noted in the diagonals. Data on variables 1−3 and 7−9 were reported by individual employees; data on variables 4−6 were collected from the bank’s human resource management; variables 10−11 were evaluated by department managers.

*,**, and *** are significant degrees of 0.05, 0.01, and 0.001 respectively.

Measurement model

We conducted a series of confirmatory factor analyses (CFAs) on those items comprising the collective perception measures (stretch goal, informational justice, and interpersonal justice). We first tested a three-factor model that corresponds with our conceptualization of the three collective variables as distinct from one another. This three-factor model provides a good fit to the data (χ²/df=2.19, RMSEA=0.072, CFI=0.94, NNFI=0.96). Additional CFAs indicate the three-factor model is a better fit than a two-factor model that combines the two dimensions of organizational justice into a single dimension, or a one-factor model that combines all items into a single contextual dimension.

Hypothesized model

To partition the variance at the individual (employees), department, and bank level in hypothesis testing, we calculated hierarchical linear models with HLM 6.08 (Raudenbush et al., 2004) to test our hypotheses. These HLM3 models could estimate the individual-level effects (level 1), as well as the separate effects of department-level and bank-level predictors (level 2 and level 3) on the intercepts and slopes at the individual level. In addition, following the recommendation of Hofmann and Gavin (1998), we grand-mean-centered all level 1 predictors, except for the dummy-coded gender and education variables. The results of the regression analyses for unethical behavior are presented in Table 2.

Table 2.

HLM results: The main and interactive effects of stretch goal and justice on unethical behavior^a.

Variables	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
1 Intercept	−0.76*	−9.25*	−9.47*	−9.75*	−6.83	−0.63
2 Level 1 control
Employee age	0.30	0.03	0.03	0.03	0.02	0.02
Employee gender	0.26	0.35	0.30	0.30	0.24	0.16
Employee education	0.36	0.48	0.46	0.46	0.41	0.41
3 Level 2 control and independent
Department size	0.75	0.98	1.03	1.08	0.62	0.61
Stretch goal		0.46**	0.51***	0.52***	0.47**	0.59***
Informational justice			−0.36*	−0.36*	−0.38*	−0.39*
Interpersonal justice			−0.29*	−0.27*	−0.25*	−0.24*
Informational justice*stretch goal				−0.20*		−0.17*
Interpersonal justice*stretch goal					0.15	0.13
4 Level 3 control
Number of departments in a bank	0.19	0.34	0.38	0.41	0.20	0.27
Number of employees in a bank	−0.03	−0.06	−0.06	−0.07	−0.03	−0.04
R^2c	0.14	0.23*	0.25*	0.30*	0.27*	0.35*

n = 351 at the individual level, n = 117 at the department level, and n = 6 at the organizational level. To facilitate comparisons of the magnitudes of effects at each level stemming from differently scaled variables, we entered standardized predictors to the estimated models.

R² is calculated based on proportional reduction of error variance, due to predictors in the models of Table 2 (Snijders and Bosker, 1999).

,**, and *** are significant degrees of 0.05, 0.01, and 0.001 respectively.

Similar to the significance of the Pearson correlation between stretch goal and unethical behavior (r = 0.29, p < 0.01, from Table 1), the regression coefficient of stretch goal in Model 2 of Table 2 was significant (γ = 0.46, p < 0.01). Furthermore, when two kinds of interactional justice (informational justice and interpersonal justice) were considered, as in Model 3, the regression coefficient of stretch goal in Model 3 of Table 2 was also significant (γ = 0.51, p < 0.01).

Finally, Models 4−6 examined the moderating influence of both the informational justice and the interpersonal justice on the relationship between stretch goal and unethical behavior. As shown in Table 2, the effect of the interaction between the informational justice and stretch goal on unethical behavior was weaker for higher degrees of informational justice than for lower degrees of informational justice, thus confirming Hypothesis 3a. However, the effect of the interaction between the interpersonal justice and stretch goal on unethical behavior was not significant, thus not supporting Hypothesis 3b. Furthermore, the regression coefficient of the stretch goal in Model 6 of Table 2 was also significant (γ = 0.59, p < 0.01), and the informational justice was significantly correlated with unethical behavior (γ = -0.39, p < 0.05, Model 6 in Table 2).

Similarly, the results of the regression analyses for relationship conflict are in Table 3.

Table 3.

HLM results: The main and interactive effects of stretch goal and justice on relationship conflicts^a.

Variables	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
1 Intercept	−4.11	0.66	0.74	−1.65	0.34	1.18
2 Level 1 control
Employee age	0.01	−0.01	−0.01	0.01	0.01	−0.01
Employee gender	0.36	0.06	0.01	−0.00	0.02	−0.12
Employee education	−0.19	−0.39	−0.42	−0.36	−0.41	−0.41
3 Level 2 control and independent
Department size	0.35	−0.20	−0.22	0.22	−0.16	−0.16
Stretch goal		0.38**	0.42**	0.43**	0.52***	0.56***
Informational justice			−0.22*	−0.28*	−0.19*	−0.23*
Interpersonal justice			−0.28*	−0.30*	−0.32*	−0.33*
Informational justice*stretch goal				−0.19		−0.15
Interpersonal justice*stretch goal					−0.23*	−0.16*
4 level 3 control
Number of departments in a bank	0.03	−0.10	−0.08	0.16	−0.05	0.05
Number of employees in a bank	0.01	0.03	0.03	−0.02	0.03	0.01
R^2c	0.13	0.33**	0.35**	0.38**	0.44**	0.51***

R² is calculated based on proportional reduction of error variance, due to predictors in the models of Table 3 (Snijders and Bosker, 1999).

,**, and *** are significant degrees of 0.05, 0.01, and 0.001 respectively.

Similar to the significance of the Pearson correlation between stretch goal and relationship conflict (r = 0.34, p < 0.01, from Table 1), the regression coefficient of the stretch goal in Model 2 of Table 3 was significant (γ = 0.38, p < 0.01). Furthermore, when two kinds of interactional justice (informational justice and interpersonal justice) were considered, as in Model 3, the regression coefficient of the stretch goal in Model 3 of Table 3 was also significant (γ = 0.42, p < 0.01).

Finally, Models 4−6 examined the moderating influence of both the informational justice and the interpersonal justice on the relationship between stretch goal and relationship conflict. As shown in Table 3, the effect of the interaction between the interpersonal justice and stretch goal on relationship conflict was weaker for higher degrees of interpersonal justice than for lower degrees of interpersonal justice, thus confirming Hypothesis 4b. However, the effect of the interaction between the informational justice and stretch goal on relationship conflict was not significant, thus not supporting Hypothesis 4a. Furthermore, the regression coefficient of the stretch goal in Model 6 of Table 3 was also significant (γ = 0.56, p < 0.001), and the interpersonal justice was significantly correlated with relationship conflict (γ = -0.33, p < 0.05, Model 6 in Table 3).

The interactive effects are plotted in Figure 1. In support of Hypothesis 3a and Hypothesis 4b, simple slope analyses show that the stretch goal is less positively and significantly related to unethical behavior for strong informational justice compared to those with a weak informational justice. This result supports Hypothesis 3a. In addition, we found that the stretch goal is less positively and significantly related to relationship conflict for strong interpersonal justice compared to those with a low interpersonal justice. The results support Hypothesis 4b.

Figure 1.

Moderating effects of informational justice/interpersonal justice on the relationship between stretch goal and unethical behavior/relationship conflict.

Discussion

We find that when employees perceive that there is a strong informational-justice climate in their work units, unethical behavior associated with stretch goals is reduced. We also find that when employees perceive that there is strong interpersonal-justice climate in their work units, relationship conflicts associated with stretch goals are reduced. These findings suggest that stretch goals do not necessarily result in unethical behavior and relationship conflicts. Rather, it appears that interactional justice plays a pivotal role in establishing the reactions to stretch goals. Thus, these results extend the literature on stretch goals by demonstrating the importance of organizational justice.

Theoretical implications

This study contributes to various types of literature by partially illuminating the influence of stretch goals on unethical behavior and relationship conflicts. Furthermore, this study examines an integrated model of the conditions under which stretch goals relate to unethical behavior and relationship conflicts. More specifically, we provide a new frame for several topics of interest regarding goal-setting, behavioral ethics, and organizational-justice researchers.

First, our study contributes to the literature focused on the incentive function of the goal-setting and positive outcomes of stretch goals. This literature, however, neglects the negative influences of goal-setting (Barsky, 2008; Locke and Latham, 1990; Stikin et al., 2011). Although several studies suggest correlations between goal-setting and unethical employee behavior (Barsky, 2008; Bazerman and Tenbrunsel, 2011; Latham and Locke, 2006; Schweitzer et al., 2004; Sitkin et al., 2011), few attempts have been made to explain those correlations. For example, consistent with Bandura’s (1991) social cognitive theory, Schweitzer et al. (2004) suggest that psychological factors encourage unethical behavior when people fall short of goals; therefore, they expect that people with unmet goals are more likely to misrepresent their performance than people without specific goals, or people attempting to ‘do their best.’

Still, these perspectives provide limited insights into the effects of employee cognition-driven behavior, such as unethical behavior. Moreover, they fail to explain why employees in the work unit experience increased negative affect-driven behavior, or relationship conflict, when they face impossible goals in the workplace. In order to fill these gaps, we develop an integrated theoretical argument for how stretch goals affect cognition-driven behavior (unethical behavior) and affect-driven behavior (relationship conflict), and we give reasonable explanations from the perspective of social-exchange theory and uncertainty-management theory.

Second, our study contributes to research investigating the link between the justice theory and behavioral ethics. However, until now, the justice and ethics literatures have largely run parallel to each other, and it is imperative for us to make a bridge between these two areas. According to Treviño et al. (2006), despite the obvious connection between notions of justice and ethical theory (Rawls, 1971), organizational justice work largely ignored the normative link until recently (e.g. Cropanzano and Stein, 2009). Therefore, we go beyond the traditional studies that look only at the superficial relationships between goal-setting and unethical behavior (Barsky, 2008; Schweitzer et al., 2004), and we pay more attention to how to mitigate the disruptive effects of stretch goals.

This contrasts with research that implicitly assumes that because employees are prone to behave unethically, the justice climate should keep these impulses in check (Li and Cropanzano, 2009; Trevino and Weaver, 2001). We do, in fact, find that informational justice moderates the relationship between stretch goals and unethical behavior, but it does not moderate the relationship between stretch goals and relationship conflicts. Likewise, we find that interpersonal justice moderates the relationship between stretch goals and relationship conflicts, but it does not moderate the relationship between stretch goals and unethical behavior. It seems that informational justice speaks to the fairness, accuracy, and timeliness of information (Karriker and Williams, 2009), and that when employees facing a stretch goal perceive a strong degree of informational-justice climate in their work units (Sitkin et al., 2011), the stretch goal seems less difficult and still attainable with enough effort and persistence. This consequently mitigates unethical behavior. Similarly, interpersonal justice addresses the fairness of employee treatment (Karriker and Williams, 2009). We find that when employees perceive a strong degree of interpersonal-justice climate in their work units, the tension that accompanies stretch goals does not lead to as much relationship conflict.

Why does informational justice not mitigate relationship conflicts? We suggest that although informational justice makes stretch goals seem more reasonable and understandable, it is really not easy to establish mutual trust among employees simply by giving relevant explanations for decisions.

Why does interpersonal justice not mitigate unethical behavior? We suggest that although interpersonal justice can mitigate the contagious negative morale that stretch goals create (Barnett and Pratt, 2000; Sitkin, 1992; Sitkin et al., 2011), it is really not easy to eliminate employee concerns about adopting a stretch goal, the specific procedures for reaching the stretch goal, and other relevant questions simply by having respect for and dignifying the employees. These practical concerns are the culprit of unethical behavior in work units.

According to consistent theory (Osgood and Tannenbaum, 1955), informational justice relates to cognition-based content; therefore, it is reasonable to assume that it will affect team members’ judgment of unethical behavior (ethical recognition, moral disengagement, etc.) caused by stretch goals and subsequently decrease certain cognition-driven behavior (such as unethical behavior). Contrary to this, interpersonal justice relates to affect-based content; therefore, it is reasonable to assume that it will affect team members’ cooperation and subsequently decrease affect-driven behavior (such as relationship conflict).

Therefore, it is not surprising to find that interpersonal justice has no significant moderating effects on the relationship between stretch goals and unethical behavior, and informational justice has no significant moderating effects on the relationship between stretch goals and relationship conflicts. As such, this article echoes numerous calls for more research into the consequences of different kinds of organizational justice (Karriker and Williams, 2009; Lavelle et al., 2007; Patient and Skarlicki, 2010; Roch and Shanock, 2006).

Third, our study contributes to the research on stretch goals. More scholars are exploring the pitfalls of goal-setting (Barsky, 2008; Bazerman, and Tenbrunsel, 2010; Latham and Locke, 2006; Schweitzer et al., 2004; Sitkin et al., 2011), and some of them (Barsky, 2008) propose a theoretical model linking attributes of goals and goal-setting practices to unethical behavior through two psychological mechanisms: ethical recognition and moral disengagement. The research also addresses the moderating role of individual differences (e.g. goal commitment and conscientiousness), as well as the broader organizational ethical context. Others focus on using laboratory experiments to explore the role of goal-setting in motivating unethical behavior. However, until now no research uses the survey method to unveil the disruptive effects of stretch goals or how to mitigate such negative outcomes.

Therefore, in order to fill this gap, we examine employees and managers in the Chinese banking industry − a unique population engaged in ethically complicated behaviors. China is one of the fastest growing emerging economies, and just as Luo (2006: 121) points out, ‘[i]n emerging markets, governmental regulations are much more variable, market information is more difficult to verify, and legal systems designed to protect and enforce contracts are much weaker than in developed economies.’ In other words, rampant corruption is an issue in China. However, due to comprehensive globalization, human resource management in China, for example, is shifting its focus from people-handling to strategic thinking, which makes it more competitive (Zhu et al., 2005). As a result, stretch goals are common in the Chinese banking industry.

The original intention of adopting stretch goals lies in their incentive function, which may motivate employees to do their best and bring maximum benefits to the banks. We believe that the high rate of organizational malfeasance in Chinese banks (Xin, 2006; Zhang et al., 2009) makes our sample an excellent starting point for examining the disruptive effects of stretch goals and improves our understanding of human resource management in practical management.

Managerial implications

Understanding whether a stretch goal will incite unethical behavior and relationship conflict − and knowing how to decrease such disruptive effects − will help managers manage employees more effectively. The wildly unethical behavior uncovered in recent corporate scandals makes it that much more important that scholars find effective ways to decrease unethical behavior and prevent it from leading to more significant irregularities or even more severe crimes in transitional economies such as China.

Similar to Schweitzer et al. (2004), our results demonstrate that stretch goals encourage constructive effort but unethical behavior. We therefore strongly suggest that managers who attempt to use stretch goals should adopt them with extreme caution. A stretch goal is a double-edged sword (Sitkin et al., 2011) − it might facilitate positive behavior in some specific circumstances, but we suggest that it is more likely to encourage unethical behavior and relationship conflict in the work unit. Therefore, similar to Locke and Latham’s (1994) suggestion, we recommend that managers design and implement less extreme stretch goals that are difficult but still attainable. This may decrease the possibility of unethical behavior and relationship conflict.

Additionally, even if it is impossible or very difficult for mangers to design and implement less extreme stretch goals that are difficult but still attainable, informational justice and interpersonal justice can still mitigate the disruptive effects. Specifically, if managers pay more attention to employees’ unethical behavior and explain their decisions, employees may perceive that a strong degree of informational and interpersonal justice exists, which can effectively weaken the disruptive effects of stretch goals. As such, this article provides managers with practical approaches to help them navigate the effects of stretch goals from the perspective of organizational justice.

Limitations and future research

As with any study, this research is not without limitations. First, although we attempt to link stretch goals to their subsequent negative outcomes (unethical behavior and relationship conflicts), we did not actually assess any mediating variables, as including such variables makes our theoretical model cumbersome. However, we do acknowledge the importance of examining the underlying mechanisms that are responsible for the disruptive effects of stretch goals, and we call for scholars to address this in the near future.

Second, in this article we focus on the mitigating function of two types of justice: informational justice and interpersonal justice. However, with the move toward more integrative models of organizational justice (Ambrose and Schminke, 2009), it is imperative to do more research on the overall justice construct and its relationship to stretch goals and their negative outcomes (unethical behavior and relationship conflict). Moreover, we call for more organizational-justice research and a research design that embraces global perceptions of justice.

Third, although the evidence supports most of the hypotheses in our article, two are unsupported. Clearly, our empirical results show that informational justice and interpersonal justice mitigate the disruptive effects of stretch goals on unethical behavior and relationship conflicts totally differently. However, why do they work so differently? And what are the potential explanations? Although we have some reasonable explanations, we expect more research.

Fourth, our research is the first to use Chinese samples to test the moderating variables, which largely enriches the empirical research on stretch goals and organizational justice; however, our samples are drawn solely from the banking industry in China. Although we expect our findings to apply to other industries and other countries, our exclusive focus on one industry and our moderate sample size remain limitations. The present research responds to the call in Detert et al. (2007: 1001) for ‘future research across organizational contexts’ by exploring the effects of stretch goals in a variety of organizations in different industries. Thus, future research should employ larger sample sizes and examine other industries to cross-validate our model in different settings. In particular, if data-collection conditions permit, in the future, we could collect more data from Taiwan, Hong Kong, and other countries in the Asia-Pacific area or from western countries. Undoubtedly, more comparison research among different countries, particularly between eastern and western countries, will be more valuable, whether from a theoretical or a practical perspective.

Fifth, we only focus on negative outcomes (unethical behavior and relationship conflict) in this article. However, according to previous research (Rousseau, 1997; Sitkin et al., 2011; Takeuchi et al., 2008), there is likely to be a positive relationship between stretch goals and positive outcomes, such as creativity and new ways of thinking and acting (Hamel and Prahalad, 1993; Rousseau, 1997). It is important that scholars, in future research, enrich the potential dependent variables by considering more positive outcomes from stretch goals.

Sixth, in this article we collect data from multiple sources in the organization. However, it would be interesting to explore unethical behavior and relationship conflicts at the individual level by collecting self-reported data from the perspective of managers and employees, thus making the model multilevel.

Conclusion

Despite their limitations, these findings provide new insights into the relationships among stretch goals, informational justice, interpersonal justice, unethical behavior, and relationship conflicts. The results show that the disruptive effects of stretch goals on unethical behavior are weaker when informational justice in the work unit is strong, and the disruptive effects of stretch goals on relationship conflicts are weaker when interpersonal justice in the work unit is strong. Furthermore, we expect future scholars in human resource management to open the ‘black box’ between organizational justice and employees’ moral perceptions and behavior.

Footnotes

Appendix I.

Appendix II.

Acknowledgements

The authors also express their appreciation to the Guest Editors of the Special Issue, Russell Cropanzano, Jonathan R Crawshaw, Chris M Bell, and Thierry Nadisic, and three anonymous reviewers for their suggestions and comments.

Funding

This study was funded by grants from the National Natural Science Foundation of China (grant no.71272002; no. 70902066; no. 71002049), the Program for New Century Excellent Talents in University (NCET-12-0439; NCET-11-0816), the Fundamental Research Funds for the Central Universities in Xi’an Jiaotong University (grant no. 08143053), and the Program for Star of Shaanxi Youth Science and Technology.

Zhe Zhang is an Associate Professor of Management at the School of Management, Xi’an Jiaotong University, China. She received her PhD in Business Management from the School of Management, Xi’an Jiaotong University, China. Her publications have appeared in Human Resource Management, International Journal of Human Resource Management, Asia Pacific Journal of Management, Management and Organization Review, and other outlets. Her current research focuses on Private-Public Partnership and human resource management. [Email: zhangzhe220@sina.com]

Ming Jia is an Associate Professor of Accounting at the School of Management, Northwestern Polytechnical University, China. He received his PhD in Business Management from the School of Management, Xi’an Jiaotong University, China. His publications have appeared in Human Resource Management, International Journal of Human Resource Management, Management, and Organization Review, and other outlets. His current research focuses on corporate governance and corporate social responsibility. [Email: mingazhe@sina.com]

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