Abusive Supervision and Organizational Citizenship Behavior: The Mediating Role of Networking Behavior

Abstract

Abusive supervision has been recognized as a serious threat to the health of affected employees and to the sustainable development of organizations. Yet, the mechanism through which abusive supervision affects organizational performance is not well understood. We suggest that abusive supervision restricts important workplace behavior, especially networking behavior and organizational citizenship behavior, which is crucial for building social capital within organizations. We test our hypothesis using a new data set constructed from a questionnaire survey among Chinese employees in various firms. The results show that perceived abusive supervision affects both networking behavior and organizational citizenship behavior. Furthermore, networking behavior partially mediates the relationship between abusive supervision and organizational citizenship behavior. The results provide important insights into the role of abusive supervision in building social capital within organizations.

1. Introduction

As creativity and adaptability become increasingly important in a constantly changing business environment, firms are depending more upon employees who work voluntarily toward achieving organizational goals. Organizational citizenship behavior (OCB), defined as employees performing extra roles voluntarily, has special importance in the study of organizational sustainability. Many studies have examined the role of OCB in organizational success [1,2,3,4]. As OCB promotes proactive and creative problem-solving to meet multiple stakeholders’ needs and demands, it contributes to organizational performance and adaptability. Moreover, OCB itself is a sustainable workplace behavior for employees, because it contributes to both positive work-related outcomes, such as receiving help from others and better performance appraisal [5], along with employee wellbeing, because helping others provides gratification and directs attention away from one’s negative mood [6]. Therefore, understanding organizational antecedents of OCB is important in understanding organizational sustainability.

Researchers have recently become interested in abusive supervision as a dark side of leadership that affects OCB [7]. Conflict with supervisors has long been the primary reason for employee maladjustment in the workplace and a major cause of turnover. Over the past few decades, researchers have sought to understand destructive leadership behaviors, such as abusive supervision. Reviewing abusive supervision research between 2008–2013, Martinko et al. [8] conclude that abusive supervision has negative consequences on subordinates, ranging from psychological distress to workplace deviance, negative job attitudes, work–family conflict, reduced organizational commitment, and even problem drinking. As a result, employees may suffer from low morale, and not realize their potential to contribute to organizational success.

In an environment where competition is getting fierce, ineffective human resource management, stemming from abusive supervision, may pose a real threat for long-term organizational sustainability.

There has been considerable progress in understanding the mechanism through which abusive supervision affects organizational performance. Early studies focused on employees’ experiences with justice and its consequences [9,10]. For example, the negative effects of abusive supervision occur when an employee attempts to redress unfair treatment from a supervisor [11]. Since abusive supervision may break trust among employees, they may become reluctant to put their energy and effort into organizational performance. Recently, research on abusive supervision was extended to incorporate the resource drain that employees experience. For employees experiencing abusive supervision, the resulting stress drains psychological capital [12], hinders engagement at work [13,14,15], and may cause withdrawal from the organization under duress.

Despite this progress, we believe that research has not considered the impact of abusive supervision on important workplace behavior that could lead to low OCB. We argue that abusive supervision works as a job demand that hinders proactive workplace behaviors, such as networking behavior and OCB that can produce organizational adaptation and innovation. Moreover, we contend that networking behavior works as a job resource for contextual performance, such as OCB. We believe that understanding the process in which abusive supervision affects networking behavior and OCB will contribute to a greater understanding of organizational sustainability.

Thus, in this study, we look at the role of abusive supervision in hindering the formation of social capital and test the hypothesized relationship between abusive supervision, networking behavior and OCB.

2. Theoretical Background and Hypotheses

2.1. Organizational Citizenship Behavior

OCB refers to extra-role behavior by employees, including helping others within the organization beyond the call of duty [16]. OCB is often discretionary, and not recognized by the formal reward systems in an organization, but is important for the effective functioning of the organization. Podsakoff and colleagues [17] provide an organizational citizenship scale that includes civic virtue, altruism, conscientiousness, sportsmanship and courtesy as subdimensions. In the literature, either one type of OCB, or an aggregate of multiple types of OCB, was investigated. Recently, Klotz, Bolino, Song and Stornelli [18] suggested studying the profiles of OCB. They identified five profiles of OCB (prosocial citizens, contributors, the disengaged, specialists and moderates) and found that these profiles predicted job performance ratings, workplace status and citizenship fatigue.

OCB may enhance firm functioning in several ways [16]. Organ [1] suggests many benefits of OCB that could contribute to organizational performance: Facilitating the coordination of activities between team members and across workgroups, enabling organizations to attract and retain high-quality employees, enhancing worker or managerial productivity and enhancing the organization’s ability to adapt to environmental change. Bolino and colleagues [19] further suggest that OCB improves organizational performance as it contributes to social capital, which is part of the competitive advantage of the firm. They find that OCB helps people build structural, relational and cognitive social capital. That is, they suggest that OCBs bring people together by increasing the number of ties among employees and by shaping connections and contacts that could later be utilized in work.

As OCB proved to be significant toward organizational effectiveness, many studies were conducted to find the antecedents of OCB. According to Ocampo et al. [20], early research looked at attitudinal variables, personality traits, task characteristics and workplace-related elements as antecedents, while later research extended to incorporate other important concepts of organizational behavior, including job satisfaction, organizational commitment, work engagement, human resource (HR) practices, self-efficacy, transformational leadership, self-serving motives and culture. For example, HR practices may signal to employees that the organization values them, and this may give rise to a sense of obligation among employees to display OCB [21]. Sun et al. [4] found that adoption of high-performance HR practices increased OCB among employees. Moreover, leaders with transformational leadership and empowering leadership may provide followers with self-confidence and personal development that could lead them to perform a range of tasks beyond prescribed technical requirements [17,22,23].

With the spread of OCB in many different societal contexts, researchers found that the content of citizenship behavior may be different across cultures [21]. Instead of following the widely accepted OCB scale by Organ [16], Farh et al. [21] develop an OCB scale specific to Chinese workers. They asked Chinese students at one MBA program to provide citizenship behaviors that fit a broad definition of OCB and a few representative examples. The students were asked to draw on their work experiences to list 10–20 examples of citizenship behavior. A three-stage sorting procedure identified both etic and emic dimensions of OCB. The five dimensions of OCB obtained from the Chinese students were: (1) identification with company, (2) altruism toward colleagues, (3) conscientiousness, (4) interpersonal harmony and (5) protecting company resources. Three of five dimensions matched items from the original Western OCB scale: identification with company (civic virtue), altruism toward colleagues and conscientiousness. However, the dimensions of sportsmanship and courtesy were not present in the Chinese version of the OCB scale. Instead, interpersonal harmony and protecting company resources were elicited as uniquely Chinese components of OCB.

2.2. Abusive Supervision & OCB

Abusive supervision is one type of aggressive behavior that has many negative consequences within the workplace, including OCB. Tepper [24] (p. 263) defines abusive supervision as “subordinates’ perceptions of the extent to which their supervisors engage in the sustained display of hostile verbal and nonverbal behaviors, excluding physical contact”. The consequences of abusive supervision are far-reaching within organizations, and include negative work-related attitudes, reduced psychological well-being, intention to quit, as well as subordinates’ deviance, and lower performance [24,25]. Those who experience abusive supervision have lower levels of job satisfaction [11,25,26,27] and organizational commitment [26,27,28], while showing higher intentions to quit [26,27]. Moreover, employees experiencing abusive supervision tend to show dysfunctional resistance, such as refusal to perform supervisors’ requests [24]. In cases where the subordinate has a history of being more aggressive, abusive supervision can lead to supervisor-directed aggression [29]. Additionally, research shows that those experiencing abusive supervision engage in less OCB [10]. These studies demonstrate why it is imperative for organizations to solve problems of abusive supervision.

Indeed, the relationship between abusive supervision and OCB is well established and has been tested across multiple studies [13,30,31,32,33,34,35,36]. Aryee et al. [32] suggested that abusive supervision breeds a toxic relationship with the subordinates. Jiang et al. [37] also showed that abusive supervision lowers employee self-efficacy and creativity. Mackey et al. [38] meta-analyzed the relationship between abusive supervision and OCB based on 13 studies, and found a consistent negative impact.

Although the justice perspective has dominated abusive supervision literature, the resource perspective has made strides in explaining why abusive supervision may harm both employees and organizations [39,40]. The JD-R model [41] suggests that abusive supervision represents a chronic stressor, which could lead to the depletion of resources required to achieve work goals. For example, if employees are exposed to constant criticism and ridicule, they may exert too much effort to overcome the stressful situation, which may deplete their cognitive and emotional resources [42]. Hershcovis and Barling [40] also showed that abusive supervision lowered task and contextual performance through stress.

Recently, Tepper et al. [43] raised the possibility that abusive supervision might enhance team productivity through heightening subordinates’ attention and encouraging their proactive behavior to avoid further hostility or to prove that the supervisor is wrong. We have yet to find empirical results supporting the speculation. Their argument, however, suggests the need to think carefully of boundary conditions for the negative relationship between abusive supervision and OCB.

It is also worth mentioning that the prevalence of abusive supervision may vary across different national contexts [8,10]. For example, Tepper [11] suggests that abusive supervision may occur more frequently in countries with high power distance. Hofstede [44] attributes this to a greater acceptance of unequal power distribution among subordinates in these countries.

Mackey et al. [38] also suggests that the perception of abusive supervisions depend largely on the perceptions of supervisory injustice, which are affected by cultural difference. In a meta-analysis of abusive supervision, they found that mean perceptions of abusive supervision were generally lower in the United States than in collectivistic countries, including China, the Philippines and Taiwan. Furthermore, the relationship between abusive supervision and various subordinate attitudes is weaker in low power distance countries. Yet, as Mackey et al. [38] noted, studies of abusive supervision in different cultural settings are relatively few, which calls for more international studies.

Given our review of this literature, we believe that abusive supervision will affect employees’ OCB. The relationship between abusive supervision and OCB has been investigated in multiple studies, and yet, we present it as our first hypothesis to set the stage for our main hypothesis regarding networking behavior.

Hypothesis 1. 

Abusive supervision is negatively related to OCB.

2.3. Abusive Supervision and Networking Behavior

Although the negative consequences of abusive supervision in hindering OCB have been well established, studies on the mechanism that leads to such a relationship remain largely at the individual level. For example, the feelings of injustice or stress and low psychological capital have been identified as mediating mechanisms, which are based on the felt experience of the individual employee. We believe that we need to extend the scope of mechanism to include the social process that affects group and organizational outcomes. This is in line with the Thoroughgood et al. [45] call for a more holistic approach to destructive leadership. We propose networking behavior as an important job resource that affects contextual performance.

Networking behavior may be defined as individuals’ attempts to develop and maintain relationships with others who have the potential to assist them in their work or careers [46]. The literature on networking behavior is vast, but this subsection limits its attention to the studies that are of particular relevance to the relationship between abusive supervision and networking. From the literature, we recognize two opposite possibilities: abusive supervision may either negatively or positively affect networking [43].

Forret and Dougherty [46] identified five types of networking behaviors, namely, maintaining contacts, socializing, engaging in professional activities, participating in community and increasing internal visibility, and developed a networking behaviors scale using US data. Their study found that self-esteem is an important antecedent for networking behaviors, among other personal traits. Employees exposed to abusive supervision may suffer ego depletion and form negative self-images [12], and as a result, become less active in developing relationships. Building on the analysis by Kim [47] identified several enablers and constraints in different stages of networking. During the initial stage of building networks, the interview-based study found that access opportunities and positive self-perception enabled socializing with the alter, while absence of interest by the alters were pointed out as a constraint of network building. During the maintenance stage, the existence of compatible interests and affect toward the alter worked as an enabler, while cessation of common interests worked as a constraint. Exposition of an employee to public displays of criticism and ridicule may limit access opportunities open to the employee, and reduce her value as a contact in a network in the initial stage of network building and the subsequent maintenance stage. In another channel, abusive supervision may lower organizational identification, which could result in general indifference toward building networks within the organization. Shoss et al. [14] showed that employees tended to blame organizations for abusive supervision, as they consider the supervisor as the embodiment of their organization. The study suggests that the impact of abusive supervision is not confined to the dyadic relationship between the employee and the supervisor, but rather extends to the general relationship building efforts of the focal employee.

We have to keep in mind, however, the possibility that abusive supervision may increase networking behavior. As noted above, Tepper et al. [43] suggest that abusive supervision may have a performance enhancing effect, if employees choose to increase their effort levels to prove that the supervisor is wrong, or to avoid further hostility. Increased investment in networking may be a part of the overall enhancement of efforts by the employee.

Given our review of this literature, we present our second hypothesis in a pair of competing alternatives:

Hypothesis 2a. 

Abusive supervision is negatively related to networking behavior.

Hypothesis 2b. 

Abusive supervision is positively related to networking behavior.

For the empirical analysis that follows, we adopt the networking behavior scale developed by Yu and Sun [34], which is an adaptation for the Chinese context of the scale first developed and utilized by Forret and Dougherty [46]. Based on the interviews of Chinese MBA students with work experience in various types of firms in China, they found that while three sub-dimensions, i.e., socializing, engaging in professional activities and increasing internal visibility, also feature significantly in the Chinese context, two sub-dimensions of maintaining contact and engaging in church and community were lacking in China, and should be replaced by giving social support and avoiding conflict. The differences are related to the significance of the guanxi relationships in China, and may reflect the influence of the collectivistic culture of the country on the contents of networking behavior [6].

2.4. Networking Behavior and OCB

Although networking behavior has been studied mainly in the context of career success, it serves as a valuable resource for achieving organizational effectiveness [48]. Since most work requires coordination within and across different teams and work units, networking behavior could help achieve organizational effectiveness. Networking behaviors, such as maintaining contacts and socializing, are the first step in transforming formal organizational structures and hierarchies into working relationships where valuable information is shared and exchanged. For example, participating in professional meetings and community activities allows employees to learn about the broader context in which their firms operate. Through these interactions, organizational members can engage in collective problem-solving and prepare for future changes to the environment. The importance of boundary spanning activities has also been emphasized in team effectiveness research. Studying the team effectiveness of sales groups, Ancona [49] finds that external activities are more important than internal cohesiveness for a team’s success. One can imagine that teams where employees actively engage in networking behavior and fulfill external roles will be more successful.

Some may note that there is a fairly large overlap between OCB and networking behavior. This observation is true, of course, and the overlap may be more significant in the Chinese context, where social support for fellow workers in distress are a particularly important category of networking behavior to build up the famous guanxi relationship. We emphasize however that there are important differences between the two concepts in actual analysis. According to the Chinese OCB scale which we are adopting [21], OCB in the Chinese context may include identification with company, altruism toward colleagues, conscientiousness, interpersonal harmony and the protection of company resources. Apart from the trait of altruism toward colleagues, there are ample dimensions in OCB that are independent of networking behavior. In addition, OCB is measured focused on intentions or motivations, while networking behavior is measured through actualized behavior.

Networking behaviors as a job resource are related to the formation of social capital within the organization. When engaging in networking behaviors, employees actively learn about other employees’ concerns, and they exchange information that may lead to problem-solving [13]. Nahapiet and Ghoshal [48] divide social capital into structural, relational, and cognitive dimensions. The structural dimension refers to the extent to which people in an organization are connected, while the relational dimension refers to the quality and nature of the connections, such as trust, intimacy and so forth. The cognitive dimension refers to a shared understanding that may help collaboration. Networking behavior helps people connect with each other and helps deepen their relationships with one another.

Sustained networking behavior, such as maintaining contacts, socializing and increased internal visibility, could spread knowledge about the challenges that people in the organization are facing, which could encourage collaboration in the future.

As such, networking behavior could play an important role in employee OCB. In order to help each other beyond the call of duty, employees must know what others are working on and the challenges they are facing. Reciprocity does not happen in a void. Rather, reciprocity requires connection between individuals. Thus, when employees reduce their networking behavior as a result of abusive supervision, they may also lose the chance to engage in OCB, even if they are more than willing to help fellow employees, if not their abusive supervisors. Thus, we posit below that networking behavior will mediate the relationship between abusive supervision and OCB.

Hypothesis 3. 

Networking behavior mediates the relationship between abusive supervision and subordinates’ OCB.

3. Methods

3.1. Sample and Procedures

We conducted our study with a sample of Chinese employees. Transformation of China from a centrally-planned economy into a market-driven economy has brought in fundamental changes in individual values [4]. Yet, traditional values are still deeply rooted in Chinese societies [50]. The values of traditional patriarchy, male domination, and a general sense of powerlessness [3], combined with the high level of power distance in China, result in widespread abusive supervision in Chinese workplaces [7]. Although our study does not measure the cultural component or compare across cultures, we believe the topic of abusive supervision in a Chinese context is meaningful, and deserves in depth exploration.

We used convenience sampling in our study. A questionnaire survey was conducted by collecting online and offline responses. The survey was conducted on employees working in China. Online data were collected from a Chinese survey website called “Sojump”, which is now known as WJX. In order to gather data with sufficient variation, we requested employees from different industries, firm sizes, ranks and demographic characteristics. Offline data were collected by visiting respondents directly. The survey was carried out from 31 March to 11 April 2019, and resulted in 36 offline and 225 online responses; the 261 valid samples were used to test the hypotheses.

Table 1. Characteristics of the sample (N = 261).

Variables	Items	Total	Variables	Items	Total
Gender	Male	127 (48.7%)	Work experience	Less than 1 year	62 (23.8%)
	Female	134 (51.3%)		1–5 years	77 (29.5%)
Age	Less than 20	2 (.8%)		6–10 years	35 (13.4%)
	20–29	92 (35.2%)		11–20 years	42 (16.1%)
	30–39	67 (25.7%)		21–30 years	37 (14.2%)
	40–49	60 (23.0%)		More than 30 years	8 (3.1%)
	50–59	40 (15.3%)	Position	Basic-level	179 (68.6%)
Educational background	High school	26 (1.0%)		Middle-level	73 (28.0%)
	Junior college	94 (36%)		High-level	9 (3.4%)
	Undergraduate	123 (47.1%)	Firm Size (number of employees)	Less than 50	45 (17.2%)
	Graduate	18 (6.9%)		50–100	42 (16.1%)
Marital Status	Unmarried	91 (34.9%)		100–300	77 (29.5%)
	Married	170 (65.1%)		300–500	27 (1.3%)
Family Status	No children	94 (36.0%)		500–1000	17 (6.5%)
	1 child	109 (41.8%)		More than 1000	53(2.3%)
	2 or more children	58 (22.2%)
Industry	Education	11 (4.2%)	Banking	11 (4.2%)
	Construction	21 (8.0%)	Health care	14 (5.4%)
	Food service	9 (3.4%)	Civil servants	70 (26.8%)
	Insurance	11 (4.2%)	Others	113 (43.3%)

presents the demographic characteristics of the participants in the study. As shown in Table 1, the respondents were from more than eight industries, including civil servants. Approximately 60% of the sample was from firms with less than 300 employees.

3.2. Measurement

3.2.1. Abusive Supervision

Abusive supervision was measured by a fifteen-item scale proposed by Tepper [27], which has been used in Wu and colleagues [51]. Sample items for perceived abusive supervision include the following: “My leader gives me the silent treatment”; “My leader puts me down in front of others”; and “My leader invades my privacy”. All items were rated on a 7-point Likert scale (1 = “strongly disagree”, 7 = “strongly agree”).

3.2.2. Organizational Citizenship Behavior

To measure OCB, we used a twenty-item of OCB scale developed by Farh and colleagues [21], which has been utilized extensively in the Chinese context. The sample items for this scale are “Willing to stand up to protect the reputation of the company”; “Willing to assist new colleagues to adjust to the work environment”; “Uses illicit tactics to seek personal influence and gain with harmful effect on interpersonal harmony in the organization”; and “Conducts personal business on company time (e.g., trading stocks, shopping, going to barber shops)”. All items were rated on a 7-point Likert scale (1 = “strongly disagree,” 7 = “strongly agree”).

3.2.3. Networking Behavior

We used a nineteen-item scale proposed by the Chinese researchers Yu and Sun [52] in this research, which takes into account the characteristics of Chinese culture. Networking behavior consists of five dimensions, such as “increasing internal visibility”, “socializing”, “engaging in professional activities”, “giving social support” and “avoiding conflict”. Sample items for networking behavior include the following: “invited someone to drink or dine together at their convenience” for socializing, “attended conferences or trade shows” for engaging in professional activities, “gave comments and viewpoint in different occasions” for increasing internal visibility, “avoid clashing with someone directly” for avoiding conflicts, and “provided important information when someone needed it” for providing social support. All items were rated on a 7-point Likert scale (1 = “strongly disagree,” 7 = “strongly agree”).

3.2.4. Control Variables

As control variables, we included the following demographic and employment characteristics of the respondents: gender, age, educational background, marital status, family status, industry, tenure, position and firm size. All categorical variables were coded as dummy variables. The first gender is coded as “1” = female and “0” = male, and age is coded as “1” = under 20, “2” = 21–29, “3”= 30–39, “4”= 40–49, “5” = 50–59, and “6”= 60. In addition, education is coded as “1” = high school diploma or under, “2” = associate degree, “3” = bachelor’s degree, and “4” = master’s degree or above. Work experience is coded as “1” = less than 1 year, “2” = 1–5 years, “3” = 6–10 years, “4” = 11–20 years, “5” = 21–30 years, and “6” = more than 30 years. Finally, their position level is coded as “1” = employee, “2” = manager, and “3” = top management.

3.3. Data Analysis

Collected data were analyzed using the Amos 21.0, SPSS 25.0 program, and Hayes’ PROCESS macro version 3.1 [53]. First, frequency analysis and descriptive statistics analysis were conducted to identify the general sample characteristics and main variables of this study. The reliability of the items for all major variables was found to be at least 70, which ensured internal consistency [54,55]. Additionally, correlation analysis was conducted to identify the relationship and direction among major variables using SPSS 25.0.

Second, to assess the validity, we conducted exploratory factor analysis (EFA) using SPSS 25.0 and confirmatory factor analysis (CFA) using Amos 21.0. Finally, we used the Hayes’ PROCESS macro to test the hypothesis.

The macro calculates the confidence interval (CI) using the ordinary least squares (OLS) analysis to calculate the mediating effect. If the confidence interval does not include “0”, the indirect effect is interpreted as significant. Therefore, we calculate a 95% confidence interval from 10,000 bootstrap samples [54,55,56].

4. Results

4.1. Results of the Validity Test

We conducted EFA to confirm the construct validity of the items measuring each variable. Principal components analysis (PCA) was used as a factor analysis extraction method, and the rotation method was based on varimax. Factors with an eigenvalue of 1 or more were selected, and each had a factor loading higher than 0.5. As for abusive supervision, three of 15 items from the survey were removed through the process. The removed items are “tells me my thoughts or feelings are stupid”, “ridicules me”, “puts me down in front of others”, and twelve items were used for the analysis. As for networking behavior, three of 19 items were removed, including “never gossiped about someone”, “avoided to make someone feel slighted”, “took the initiative to greet to someone”. Yu and Sun [34] have shown that networking behavior has five dimensions: “increasing internal visibility”, “engaging in professional activities”, “socializing”, “giving social support” and “avoiding conflicts”. However, in this study, “giving social support” and “avoiding conflicts” were classified as one factor. Therefore, networking behavior consisted of four subfactors in our study. As for OCB, two of the original items, such as “takes one’s job seriously and rarely makes mistakes”, “often arrives early and starts to work immediately”, were deleted, and were grouped into two subdimensions, which were grouped along the etic and emic dimensions suggested by Farh et al. [21]. The final factor analysis results are presented in

Table 2. Results of exploratory factor analysis.

Items	Etic OCB	AS	Emic OCB	NB 4	NB 2	NB 3	NB 1
Willing to assist new colleagues adjust to the work environment	0.824	−0.091	0.119	0.205	0.044	0.025	0.051
Willing to help colleagues solve work-related problems	0.814	−0.044	0.152	0.229	0.072	0.082	−0.004
Willing to cover work assignments for colleagues when needed	0.779	−0.060	0.181	0.106	0.076	0.092	0.028
Willing to coordinate and communicate with colleagues	0.766	−0.076	0.248	0.092	0.068	0.102	0.064
Willing to stand up to protect the reputation of the company	0.700	−0.016	0.311	0.066	0.265	−0.080	0.098
Actively attends company meetings	0.694	−0.082	0.227	0.154	0.131	0.059	0.151
Complies with company rules and procedures, even when nobody watches, and no evidence can be traced	0.638	−0.027	0.363	0.014	0.126	0.010	0.065
Eager to tell outsiders good news about the company and clarify their misunderstandings	0.637	−0.049	0.278	0.109	0.283	−0.071	0.108
Makes constructive suggestions that can improve the operation of the company	0.632	−0.049	0.223	0.099	0.176	0.164	−0.003
Does not mind taking new or challenging assignments	0.576	−0.098	0.307	0.099	0.077	0.326	0.074
Tries hard to self-study to increase the quality of their work output	0.561	−0.089	0.409	0.078	0.216	0.058	−0.026
Expresses anger at me when he/she is mad for another reason	−0.046	0.835	−0.034	0.061	−0.106	−0.013	0.072
Blames me to save himself/herself embarrassment	−0.030	0.823	0.031	−0.080	0.014	−0.051	−0.051
Makes negative comments about me to others	−0.009	0.759	−0.095	−0.041	−0.179	0.091	0.159
Breaks promises he/she makes	−0.067	0.749	−0.079	0.059	0.130	0.023	−0.208
Gives me the silent treatment	−0.099	0.735	−0.190	−0.040	−0.071	−0.090	−0.142
Does not give me credit for jobs requiring a lot of effort	−0.052	0.731	0.068	0.117	0.137	−0.201	−0.064
Lies to me	−0.089	0.702	−0.257	0.047	−0.050	−0.135	−0.085
Is rude to me	0.029	0.652	−0.209	−0.299	−0.188	0.213	0.096
Invades my privacy	−0.028	0.629	−0.263	−0.151	−0.030	0.111	−0.197
Reminds me of my past mistakes and failures	−0.148	0.605	−0.015	0.044	−0.104	−0.017	0.085
Tells me I am incompetent	−0.037	0.563	−0.038	−0.129	−0.070	−0.137	0.232
Does not allow me to interact with my coworkers	−0.079	0.537	−0.056	−0.374	−0.079	0.154	0.121
Conducts personal business on company time (e.g., trading stocks, shopping and going to barber shops) (R)	0.233	−0.115	0.803	−0.069	0.185	0.025	0.075
Uses company resources to do personal business (e.g., company phones, copy machines, computers and cars) (R)	0.198	−0.127	0.802	0.025	0.205	0.052	0.005
Takes credit, avoids blame and fights fiercely for personal gain (R)	0.350	−0.005	0.754	0.139	−0.076	0.062	0.081
Uses position power to pursue selfish personal gain (R)	0.361	−0.094	0.747	0.086	0.026	0.007	0.038
Views sick leave as a benefit, and makes excuses for taking sick leave (R)	0.274	−0.154	0.732	0.089	−0.012	−0.005	0.082
Often speaks ill of the supervisor or colleagues behind their backs (R)	0.228	−0.162	0.725	−0.049	0.209	0.072	0.070
Uses illicit tactics to seek personal influence and gain, with harmful effects on interpersonal harmony in the organization (R)	0.280	−0.179	0.707	0.097	0.011	−0.016	−0.047
Avoided clashing with someone directly	0.140	−0.036	0.066	0.791	0.083	0.054	0.166
Did not burden someone with his/her work	0.271	−0.057	0.070	0.714	0.079	0.086	0.053
Shared ideas and gave advice to each other	0.207	−0.078	0.029	0.613	0.186	0.393	0.090
Concerned about someone’s work, life, or health	0.297	−0.054	0.029	0.600	0.298	0.144	0.070
Shared someone’s work load actively when he/she was very busy	0.354	−0.122	0.044	0.549	0.288	−0.160	0.313
Provided important information when someone needed it	0.069	0.042	0.028	0.540	−0.132	0.481	0.287
Attended tournaments/competitions/contests	0.249	−0.126	0.129	0.056	0.759	0.162	0.303
Attended meetings of civic and social groups, clubs, etc.	0.206	−0.051	0.191	0.137	0.698	0.233	0.028
Attended training activities	0.356	−0.064	0.147	0.244	0.677	0.164	0.149
Attended conferences or trade shows	0.304	−0.113	0.136	0.173	0.622	0.246	0.334
Gave comments and viewpoints on different occasions	0.068	−0.007	0.039	0.100	0.182	0.759	0.041
Been on highly visible task forces or committees at work	0.072	−0.102	0.025	0.117	0.431	0.628	0.147
Took responsibility for intracompany tasks to get recognized by someone	0.204	−0.065	0.045	0.071	0.180	0.615	0.352
Attended someone’s wedding/funeral willingly	0.049	−0.024	0.132	0.257	0.121	0.240	0.731
Invited someone to drink or dine together at their convenience	0.088	0.048	0.102	0.135	0.299	0.285	0.717
Chatted with someone willingly at leisure	0.233	−0.083	−0.004	0.213	0.375	0.022	0.576
Reliability (Cronbach’s alpha)	0.931	0.910	0.916	0.826	0.881	0.745	0.779
Eigenvalue	13.318	5.438	3.949	2.238	1.747	1.470	1.173
Variance (%)	28.952	11.822	8.585	4.865	3.797	3.196	2.549

NB 1: socializing, NB 2: engaging in professional activities, NB 3: increasing internal visibility, NB 4: avoiding conflict and giving social support.

. The original data together with survey questions will be made available upon the reader’s request.

We conducted CFA to examine the discriminant validity of three key variables. We compared the fit of a seven-factor model suggested in the hypothesis of this study with a three-factor model (combining Etic OCB and Emic OCB and four subdimensions of networking behavior), a four-factor model (combining four subdimensions of networking behavior), and a six-factor model (combining Etic OCB and Emic OCB). As presented in

Table 3. Results of the Confirmatory Factor Analysis of discrimination validity.

Model	${\mathit{\chi }}^{\mathbf{2}}$	df	$\mathsf{\Delta }{\mathit{\chi }}^{\mathbf{2}}$	$\mathsf{\Delta }\mathbf{df}$	CFI	TLI	RMSEA
Hypothesized 7-factor model	1533.618	888	-	-	0.911	0.901	0.053
3-factor model (combining Etic OCB and Emic OCB and four subdimensions of networking behavior)	1573.081	899	39.463	11	0.907	0.898	0.054
4-factor (combining four subdimensions of networking behavior)	1561.028	898	27.41	10	0.909	0.899	0.053
6-factor (combining Etic OCB and Emic OCB)	1555.125	892	21.507	4

Note. Fit index criteria: IFI: incremental fit index (>0.90); TLI: Tucker–Lewis Index (>0.90), CFI: comparative fit index (>0.90), RMSEA: root-mean-square error of approximation (≤0.01) [14].

, the seven-factor model had the best fit.

4.2. Descriptive Statistics and Correlation Analysis

Table 4. Descriptive Statistics and Correlations Analysis.

		Mean	S.D.	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)
(1)	Gender(1 = female)	0.51	0.50
(2)	Age	3.17	1.10	−0.179 **
(3)	Education	2.51	0.77	−0.003	−0.313 **
(4)	Unmarried (1)	0.35	0.48	0.085	−0.708 **	0.290 **
(5)	No children (1)	0.36	0.48	0.108	−0.714 **	0.345 **	0.841 **
(6)	Work experience	0.04	0.20	0.090	0.072	0.109	−0.073	−0.038
(7)	In(education = 1)	0.08	0.27	−0.135 *	−0.007	0.061	0.020	−0.017	−0.062
(8)	In(construction = 1)	0.03	0.18	0.058	−0.183 **	−0.153 *	0.126 *	0.164 **	−0.040	−0.056
(9)	In(food service = 1)	0.08	0.28	0.047	−0.072	0.176 **	0.038	0.060	−0.064	−0.090	−0.057
(10)	In(finance = 1)	0.05	0.23	0.198 **	−0.161 **	0.041	0.111	0.140 *	−0.050	−0.070	−0.045	−0.072
(11)	In(health care = 1)	0.27	0.44	−0.189 **	0.341 **	−0.053	−0.280 **	−0.292 **	−0.127 *	−0.179 **	−0.114	−0.184 **	−0.144 *
(12)	In(civil servant = 1)	2.77	1.48	−0.148 *	0.800 **	−0.158 *	−0.585 **	−0.593 **	0.149 *	0.028	−0.140 *	−0.129 *	−0.238 **
(13)	Position(1 = staff)	0.69	0.47	0.084	−0.265 **	−0.024	0.218 **	0.215 **	−0.063	−0.073	−0.053	−0.003	0.015
(14)	Film size	3.34	1.71	−0.001	−0.167 **	0.234 **	0.133 *	0.160 **	0.014	−0.034	−0.074	0.150 *	0.142 *
(15)	AS	3.31	1.15	−0.081	0.006	0.075	−0.032	−0.047	−0.027	0.091	−0.076	−0.073	−0.017
(16)	NB_4	5.77	0.77	0.046	−0.050	−0.062	−0.009	0.016	−0.022	0.034	0.018	0.001	0.118
(17)	NB_2	5.24	1.20	0.039	0.091	−0.137 *	−0.200 **	−0.222 **	0.065	0.002	0.014	−0.007	0.002
(18)	NB_1	5.02	1.26	0.022	0.024	−0.014	−0.084	−0.065	0.016	0.032	0.052	−0.039	0.122 *
(19)	NB_3	4.44	1.25	0.023	−0.183 **	−0.038	0.056	0.056	0.003	−0.014	0.029	0.055	0.089
(20)	EticOCB	5.91	0.78	−0.018	0.151 *	−0.182 **	−0.200 **	−0.198 **	0.057	0.008	−0.014	−0.065	0.030
(21)	EmicOCB	6.20	0.90	0.053	0.018	−0.170 **	−0.053	−0.062	0.038	−0.069	0.008	−0.093	0.071
		(11)	(12)	(13)	(14)	(15)	(16)	(17)	(18)	(19)	(20)	(21)
(12)	In(civil servant = 1)	0.399 **
(13)	Position(1 = staff)	0.037	−0.268 **
(14)	Firm size	−0.215 **	−0.161 **	0.071
(15)	AS	−0.035	0.125 *	−0.065	0.000
(16)	NB4	−0.076	−0.084	0.034	0.062	−0.162 **
(17)	NB2	0.036	0.014	0.020	0.072	−0.220 **	0.493 **
(18)	NB1	−0.105	−0.036	−0.027	0.117	−0.090	0.507 **	0.557 **
(19)	NB3	−0.114	−0.205 **	−0.011	0.022	−0.128 *	0.443 **	0.534 **	0.499 **
(20)	Etic OCB	0.027	0.047	−0.012	−0.003	−0.219 **	0.509 **	0.555 **	0.339 **	0.316 **
(21)	Emic OCB	0.143 *	−0.133 *	0.172 **	0.026	−0.299 **	0.309 **	0.398 **	0.237 **	0.182 **	0.634 **

Notes: (1) N = 261, * p < 0.05, ** p < 0.01 (two-tailed); AS: abusive supervision. NB 1: socializing, NB 2: engaging in professional activities, NB 3: increasing internal visibility, NB 4: avoiding conflict and giving social support; OCB: organizational citizenship behavior.

shows the mean, standard deviation (SD) and correlations for each of the major variables. Internal consistency reliabilities for the latent variables are reported along the diagonal in parentheses.

4.3. Hypotheses Tests

In this study, we examine the effect of abusive supervision on OCB, the outcome variable, via networking behavior, which is tested by dividing it into direct and indirect effect. Although OCB was identified as two factors in CFA, our analysis showed that results on the two OCB subdimensions were almost identical. Therefore, in this study, we decided to report the results on combined OCB for simplicity. To test our hypotheses, we used Hayes’ PROCESS macro version 3.1 and confirmed the hypothesis through Hayes’ Process model 4 [57]. The results are presented in

Table 5. Results of mediating effect of networking behavior on the relationship between abusive supervision and organizational citizenship behavior.

	NB 4 (Avoiding Conflict and Giving Social Support)				NB 2 (Engaging in Professional Activities)				NB 1 (Socializing)				NB 3 (Increasing Internal Visibility)				OCB
	B	Se	T	p	B	Se	T	p	B	Se	T	p	B	Se	T	p	B	Se	T	p	B	Se	T	p
Constant	6.899	0.501	13.772	***	6.560	0.744	8.813	***	6.086	0.805	7.558	***	6.878	0.800	8.600	***	6.953	0.459	15.158	***	3.965	0.534	7.426	***
Gender(1 = female)	0.018	0.103	0.174		0.075	0.153	0.489		0.006	0.165	0.034		−0.121	0.164	−0.739		0.020	0.094	0.207		−0.005	0.082	−0.063
Age	−0.076	0.091	−0.830		−0.075	0.136	−0.551		0.026	0.147	0.177		−0.318	0.146	−2.181	*	0.098	0.084	1.175		0.125	0.073	1.711
Education	−0.072	0.074	−0.971		−0.118	0.111	−01.065		0.069	0.120	0.578		−0.152	0.119	−1.280		−0.130	0.068	−01.903		−0.089	0.059	−1.497
Unmarried (1)	−0.206	0.195	−1.057		−0.234	0.290	−0.807		−0.338	0.314	−1.077		−0.218	0.312	−0.700		−0.123	0.179	−0.688		−0.027	0.155	−0.174
No children (1)	0.045	0.199	0.225		−0.667	0.296	−2.255	*	−0.190	0.320	−0.594		−0.236	0.318	−0.744		−0.163	0.182	−0.895		−0.038	0.160	−0.237
In(education = 1)	−0.119	0.257	−0.463		0.495	0.382	1.298		−0.117	0.413	−0.284		0.198	0.410	0.482		0.375	0.235	1.592		0.303	0.205	1.479
In(construction = 1)	0.137	0.189	0.728		0.228	0.280	0.816		0.100	0.303	0.330		−0.035	0.301	−0.117		0.099	0.173	0.575		0.013	0.149	0.088
In(food service = 1)	−0.018	0.282	−0.062		0.208	0.419	0.497		0.525	0.453	1.158		−0.228	0.450	−0.506		−0.012	0.258	−0.048		−0.056	0.224	−0.248
In(finance = 1)	−0.002	0.186	−0.010		−0.049	0.276	−0.177		−0.289	0.299	−0.966		0.182	0.297	0.613		−0.207	0.170	−1.217		−0.193	0.148	−1.307
In(health care = 1)	0.349	0.228	1.528		−0.011	0.339	−0.031		0.573	0.367	1.561		0.310	0.365	0.850		0.136	0.209	0.648		0.060	0.182	0.330
In(civil servant = 1)	−0.065	0.135	−0.484		0.127	0.200	0.634		−0.260	0.217	−1.202		−0.102	0.215	−0.473		0.225	0.123	1.822		0.209	0.107	1.948
Work experience	−0.005	0.060	−0.077		−0.101	0.089	−1.140		−0.078	0.096	−0.809		−0.076	0.096	−0.792		−0.156	0.055	−2.840	**	−0.135	0.048	−2.849	**
Position(staff = 1)	0.375	0.285	−1.315		0.154	0.424	0.363		−0.828	0.459	−1.806		−0.216	0.456	−0.473		0.025	0.261	0.096		0.077	0.229	0.335
Firm size	0.019	0.030	0.628		0.089	0.045	1.996		0.070	0.049	1.454		−0.008	0.048	−0.171		0.032	0.028	1.173		0.008	0.024	0.341
AS	−0.102	0.044	−2.335	*	−0.219	0.065	−3.380	**	−0.088	0.070	−1.250		−0.133	0.070	−1.909		−0.160	0.040	−4.003	***	−0.090	0.035	−2.545	*
NB 4																					0.262	0.061	4.276	***
NB 2																					0.218	0.046	4.788	***
NB 1																					−0.008	0.041	−0.197
NB 3																					−0.030	0.040	−0.738
R	0.260				0.381				0.290				0.298				0.430				0.635
R-sq	0.067				0.145				0.084				0.089				0.185				0.403
MSE	0.595				1.314				1.538				1.518				0.499				0.371
F	1.1027 ***				2.5833 ***				1.4048 ***				1.4904 ***				3.4543 ***				8.1121 ***

Notes: (1) N = 261, * p < 0.05, ** p < 0.01, *** p < 0.001 (two-tailed); NB 4: avoiding conflict, NB 2: engaging in professional activities, NB 1: increasing internal visibility, NB 3: socializing; OCB: organizational citizenship behavior.

.

First, we tested Hypothesis 1, which predicts that abusive supervision is negatively related to OCB. As shown in Table 5, the results demonstrate that abusive supervision had a significant and negative effect on OCB (B = −0.160, p < 0.001). Thus, Hypothesis 1 was supported.

Hypothesis 2a predicts that abusive supervision is negatively related to networking behavior, while Hypothesis 2b predicts that abusive supervision is positively related to networking behavior. As shown in Table 5, the results demonstrate that abusive supervision had a significant and negative effect on NB 4 (avoiding conflict and giving social support) (B = −0.160, p < 0.001) and NB 2 (engaging in professional activities) (B = −0.160, p < 0.001). However, abusive supervision had no significant effect on NB 1 (socializing) and NB 3 (increasing internal visibility). Thus, Hypothesis 2a was partially supported, while Hypothesis 2b was rejected.

Hypothesis 3 suggests that networking behavior will mediate the relationship between abusive supervision and subordinates’ OCB. As we predicted, the mediating effect of networking behavior was significant (B = 0.406, p < 0.001) under the control of the perceived abusive supervision, indicating that networking behavior was partially mediated. Table 5 and

Table 6. Results of total, direct and indirect effect.

	Effect	Boot SE	95% Boot CI (LLCI, ULCI)
Total effect	−0.160	0.040	[−0.239, −0.081]
Direct effect	−0.090	0.035	[−0.160, −0.020]
Indirect effect (AB→NB 4→OCB)	−0.070	0.027	[−0.125, −0.018]
Indirect effect (AB→NB 2→OCB)	−0.027	0.015	[−0.058, −0.001]
Indirect effect (AB→NB 1→OCB)	−0.048	0.019	[−0.007, 0.012]
Indirect effect (AB→NB 3→OCB)	0.001	0.005	[−0.007, 0.020]

Note: Entries are unstandardized regression coefficients. Bootstrap resample = 10,000. Boot SE = bootstrap standard error; Boot CI = bootstrap confidence interval. LLCI: Lower Level Confidence interval, ULCI: Upper Level Confidence Interval. NB 4: avoiding conflict, NB 2: engaging in professional activities, NB 1: increasing internal visibility, NB 3: socializing; OCB: organizational citizenship behavior.

provide the results for the total, direct, and indirect effect. We tested the mediation effect with bootstrapped confidence intervals on the basis of 10,000 random samples. The indirect effect of abusive supervision on OCB through avoiding conflict and giving social support and engaging in professional activities networking behavior was significant, as the bootstrap confidence interval of the indirect effect (LLIC = −0.119, ULCI = −0.018) did not contain zero. Therefore, Hypothesis 3 was supported.

5. Discussion

OCB has been recognized as an important contributor to contextual performance, critical for organizational sustainability. Abusive supervision has been studied extensively as an important antecedent that has negative impact on OCB. Yet, the mechanism through which abusive supervision affects OCB has not been explored sufficiently [43]. In this study we suggested networking behavior as a mechanism that connects and mediates abusive supervision and OCB. We explored the relationship between abusive supervision, networking behavior and OCB in the Chinese context. The results showed that abusive supervision lowered OCB, confirming prior studies. Our study also showed that abusive supervision had a negative effect upon networking behavior. The negative effect was found for two of the four dimensions of networking behavior (engaging in professional activities and avoiding conflict/giving social support). Finally, the two sub-dimensions of networking behavior mediated the relationship between abusive supervision and OCB.

Abusive supervision did not show significant effects on the two remaining aspects of networking behavior: socializing and increasing internal visibility. Our surmise is that socializing is such a prevalent part of social behavior among Chinese employees that there is little variation in the level of socializing in the first place. Finding no impact on increasing internal visibility is harder to explain. We may recall that Tepper et al. [43] suggested possible ambiguities in the direction of the impact of abusive supervision on worker response. Perhaps workers in different categories react to abusive supervision in opposite ways in the realm of increasing of internal visibility, resulting in apparent no impact. If this is the case, we will have to find individual and organizational characteristics that would result in differential effect in future studies.

This study contributes to the literature on abusive supervision and its organizational consequences, by showing that the negative effect of abusive supervision is not confined just to the dyadic relationship between subordinate and supervisor, but also extends to the social relationship across organizational members. Our result is consistent with recent studies that examine the role of abusive supervision in the formation of social capital that could affect knowledge sharing [7] and creativity [37].

We also contribute to the literature on networking behavior by showing its contribution to organizational effectiveness, in addition to individual career success. Although the original definition of networking behavior states that networking behavior may help work outcomes as well as career success [58], most studies focused on career outcome rather than work outcome. To our knowledge, this is the first study to link networking behavior to both abusive supervision and OCB. Our study shows that networking behavior contributes to organizational functioning by supporting greater organizational communication and access to resources. This study also shows the importance of communication in facilitating the goodwill of employees. Without knowing each other’s challenges, employees may not engage in citizenship behavior even if they want to do so. Thus, organizations may benefit from promoting various networking opportunities for their employees, such as providing formal or informal gathering opportunities.

This study has practical implications as well. Firms need to be more proactive in addressing abusive supervision. Often, abusive supervision is ignored by the top management, because supporting employees in complaints against their supervisors runs against the deeply-rooted value of following authority. In some cases, abusive bosses may be promoted because they can handle tough situations like restructuring, as they appear less liable to experience emotional trauma, or even improve short-term performance [43]. Promotion is even more likely if an abusive boss has the right political skills. This study shows that such events could inadvertently restrict the development of social capital and positive extra-role behavior by employees, which could harm organizational sustainability in a fast-changing business environment.

6. Limitations and Future Research

Despite these contributions, our study is not free of limitations. First, since our study measures abusive supervision, networking behaviors and OCB for the same set of employees, it is not devoid of common method variance [58]. It is also possible that reverse causality may be present in this relationship. That is, those who do not engage in networking behavior and OCB are likely to perceive their supervisors as abusive, or they may be more likely to be the target of abusive supervision. To rule out this possibility, we have estimated a reverse causality model and found that our proposed model had a superior fit. Yet, longitudinal and multi-method designs are necessary to address the reverse causality issue more fully in the future.

Second, we have not considered differences in the way individuals react to abusive supervisors. Individual characteristics may affect the perception of abusive supervision either as an antecedent or as a moderator. For example, Wu and Hu [59] found that employees’ susceptibility to emotional contagion moderated the abuse–emotional exhaustion relationship, with those having a low contagion score exhibiting a weaker relationship. Thus, future research should measure the traditional job resource variables, such as psychological stress and anxiety, as a mediator between abusive supervision and networking behavior.

Third, although we have suggested that abusive supervision has a negative effect on networking behavior, recent developments in abusive supervision suggest that abusive supervision may lead to positive work outcomes as well [43]. Tepper et al. [43] argued that both performances enhancing and undermining pathways of the abusive supervision affect employee’s performance behavior. For example, employees might have a desire to prove that the supervisor was wrong, and prepare themselves for new employment. The threat rigidity hypothesis also suggested that performance can increase or decrease after threats [60]. Thus, future studies should consider studying turnover intention and try to identify boundary conditions for the relationship between abusive supervision and networking behavior.

Finally, although we have expanded the literature by testing the relationship between abusive supervision and OCB in the Chinese context, we have not measured the culture directly, nor did we design the study to directly compare the results across different national contexts. Our study shows that the effect size of abusive supervision and OCB is slightly low (β = −0.16, p < 0.01), compared to the effect size suggested by Mackey et al. [38] in their meta-analysis (β = −0.21). Since we do not have a comparative sample in another national context, however, we cannot comment on the universality of our findings. One cultural aspect worth further examination is the belief in traditional values, which may affect the relationship between abusive supervision, networking behavior and OCB. Those holding traditional values may behave differently when faced with abusive supervision, as they view downward authority as less problematic [51]. Moreover, those accepting traditional values may expect patriarchal support and may become rebellious, reducing their organizational behavior. Furthermore, we could extend the study to include other Asian countries, which are known to have high mean levels of abusive supervision, as well as other Western countries, which have lower levels of abusive supervision. Future studies should include these aspects to shed light on the role of culture on abusive supervision, and whether these differences may affect organizational sustainability through OCB.