How Social Capital Mediates the Impact of Job Crafting on Job Performance: Evidence from Vietnamese Industrial Enterprises

Abstract

Job crafting refers to changes that individuals make in their work to achieve their preferences and needs. Contingent on the social exchange theory, the aim of this study is to explore the relationship between job crafting and job performance. In addition, the study examines the mediating effect of social capital in the relationship between job crafting and job performance. The data was collected from 387 employees in Vietnamese industrial enterprises through a questionnaire survey using both qualitative and quantitative methods. The information was then analyzed by explanatory factor analysis (EFA) confirmatory factor analysis (CFA) as well as structural equation modeling (SEM). The results show that all three dimensions of job crating positively affect job performance and that social capital plays a mediating role in that relationship. This study contributes to the field of human resources management, particularly job crafting, by examining different dimensions of job crafting that impacts job performance. Moreover, this is the first study to test the mediating role of social capital on the relationship between job crafting and job performance. These insights may help the organizational managers to encourage beneficial job crafting.

1. Introduction

Organizations are nowadays operating in a competitive environment. Pressure from global, economic, and tech­ nological development forces organizations to continually adapt to their environment. These developments offer suggestions for employees’ job design. Traditionally, job design represents a top­down process in which managers are responsible for job structuring and modifying (Grant & Parker, 2009). This approach is being criticized being inflexible in the context of changes in job responsibilities. Employees should be able to change and develop tasks and roles proactively, allowing them to actively respond to the demands of the job.

Job crafting is one of the specific forms of proactive behavior. Job crafting is defined as the changes in work made by employees to meet their preferences and needs (Tims et al., 2013), and can lead to the accumulation of social capital (Bolino et al., 2002). The notion of a social network is taken from job design, and the link between job crafting and social capital is worth exploring (Muhammad et al., 2016; Qi et al., 2014). Applying social exchange theory (Blau, 1960), this means that by job crafting, employees have the advantages of exchanging resources with their colleagues and they are good at building and maintaining a network of relationships with others. Job crafters actively help their colleagues, and as such they get these benefits from their colleagues, resulting in increased social capital.

To our knowledge no study has been found, that engages social exchange theory, which is the most often used theory in behavior literature, to explain the impact of job crafting on job performance from the data collected from Vietnamese industrial company employees. There are two main contributions of this study to the literature of human resource management. First, this study examines the relationship of all three dimensions of job crafting and social capital. Second, most of the previous studies were explored in western countries; however, little has been analyzed in the eastern context.

This paper is structured as follows: Section 2 presents a literature review and hypothesis development, resulting in the development of a research model and the proposal of hypotheses. Next, Section 3 highlights the research methodology. Section 4 reports the empirical results while Section 5 identifies discussion as well as the limitations and future research.

2. Literature Review and Hypothesis Development

2.1. Job Crafting

Job crafting is considered as small changes that emplo­ yees make in their boundaries, conditions, relationships, and tasks of work that allow them to reframe the purpose of the job and that will enable them to experience the job differently (Wrzesniewski & Dutton, 2001). It is active behavior that employees conduct when they think that customizing their job can result in a good person­job fit in their work environment (Petrou et al., 2012; Tims et al., 2012). According to job crafting theory, there are several reasons why people engage in job crafting activities (i) to meet their control needs, (ii) to manage a good self­ image, (iii) to connect with others (Wrzesniewski & Dutton, 2001), and (iv) create a healthy and motivating job environment (Petrou et al., 2012). To this end, job crafting brings changes in employees’ identities and appreciates the meaning of their work, because their job characteristics are more aligned with their individual needs and abilities (Wrzesniewski & Dutton, 2001). This would be considered an essential mechanism for career advancement (Tims et al., 2012; Yoon et al., 2019). Job crafters change certain aspects of the way they perform their job, communicate with other colleagues, and how they think about their role. Wrzesniewski and Dutton (2001) suggest that job crafting consists of three essential elements, including task crafting, cognitive crafting, and relational crafting.

2.2. Task Crafting

Task crafting is about the changes in the type or amount of work that an employee performed (Slemp & Vella­ Brodrick, 2014). This means that employees are eager to change the daily tasks, change how they work, and/or change the time of their tasks. Employees try to redesign their job by changing their work experiences. It is important for an employee to be able to wield control over one’s work because it will minimizes negative feelings, such as job boredom (Harju et al., 2016) and burnout (Singh & Singh, 2018). Previous studies prove that task crafting positively impact job performance (Nguyen et al., 2019; Silman, 2014; Wrzesniewski & Dutton, 2001). Bakker and Demerouti (2017) demonstrated the fact that if employees optimize the resources in their jobs, they will improve their overall well­ being and perform better. Thus, the following hypothesis is proposed:

H1: Task crafting positively affects job performance.

2.3. Cognitive Crafting

Cognitive crafting is viewed as a situation, how employees changes their perception about their job to associate greater meaning to their work (Slemp & Vella­Brodrick, 2013). It allows employees to continuously re­evaluate how work affects them personally by changing the way they think about it (Slemp & Vella­Brodrick, 2013; Wrzesniewski & Dutton, 2001), while also continuously exploring how engaged they are to their work. Cognitive crafting is also thought of as a psychological dimension in which employees change their attitude to the way they think about their work to make work more satisfying. The feeling of doing a meaningful job can urge employees to have higher work engagement (Soane et al., 2013; Tim et al., 2012; Vogt et al., 2016). Sterger et al. (2012) found a positive relationship between cognitive crafting and internal work motivation which results in better performance. Thus, the second hypothesis is proposed:

H2: Cognitive crafting positively affects job performance.

2.4. Relational Crafting

Relational crafting refers to the control employees have over the people they interact with when performing their jobs (Berg et al., 2013; Slemp & Vella­Brodrick, 2013, 2014). Employees participate in crafting to satisfy their need to interact and build a social relationship with others (Wrzesniewski & Dutton, 2001). According to Deci and Ryan (2000), by increasing the time they spend with supportive and valued colleagues, employees satisfy their basic need for engaging with each other, which in turn builds good working relationships and makes the job more meaningful. Further, Daniels et al. (2014), Muhammad et al. (2016) also prove that close relationships with colleagues can result in better work performance. Thus, the following hypothesis is proposed:

H3: Relational crafting positively affects job performance.

2.5. The Mediating Role of Social Capital

Social capital is defined as the various recourses that individuals possess and have acquired from their networks (Donate et al., 2019). It depicts the norms and the network that shape collective action. Strength­based job crafting is pro­social behavior (Tian & Liu, 2017), and can lead to social capital accumulation (Bolino et al., 2002). Job crafters have the benefit of exchanging high­value resources with colleagues, and they are skillful enough to build mutually beneficial networks with other members of the team (Zhang et al., 2016). According to social exchange theory (Blau, 1960), job crafters help their colleagues, and their colleagues will often generate returns. As the degree of perception of social exchange increases, employees’ social capital accumulates.

The positive impact of social capital on employee knowledge sharing has been confirmed (Yu et al., 2013; Zimmermann et al., 2018). Relational and cognitive social capital has a positive and significant effect on routine work performance (Lefebvre et al., 2016). Moreover, the intensity of social capital shared mediates the impact of exclusive procurement arrangements on the degree of knowledge sharing (Huang et al., 2011; Yang & Farn, 2009). Similarly, the quality of the relationship between knowledge sharers and knowledge receivers is the salient factor affecting knowledge sharing among employees (Holste & Fields, 2010; Supriyanto et al., 2020).

H4: Task crafting positively affects social capital.

H5: Cognitive crafting positively affects social capital.

H6: Relational crafting positively affects social capital.

H7: Social capital positively affects job performance.

H8: Social capital significantly mediates the relationship between tasks crafting and job performance.

H9: Social capital significantly mediates the relationship between cognitive crafting and job performance.

H10: Social capital significantly mediates the relationship between relational crafting and job performance.

2.6. Research Framework

Based on the social exchange theory, the relationship between job crafting, social capital, and job performance is created. The research framework is illustrated in Figure 1.

Figure 1: Research Model

3. Research Method

3.1. Data

In this study, a survey of 400 employees in industrial companies in Ho Chi Minh City, Vietnam was conducted. Because of unavailable data on the population of industrial employees in Ho Chi Minh City, it is impractical to certify the representativeness of the sample applied. Hence, the samples were chosen through convenience sampling. All these participants were invited to fill out survey forms and were assured that data would be treated confidentially and anonymously. The number of samples was accepted because it fulfills the requirement of the research’s method­ which demands samples of at least five times as many as the indicators (Hair et al., 2010). This study uses 28 indicators, hence the required sample is 140.

Data collection was performed in the first two weeks of May 2021. We received 394 questionnaires, and the return rate was 98.5%. In order to ensure the validity of the data, we conducted the cleanness and screening of data. Finally, 387 useful answers were applied for the final test.

3.2. Variables and Measures

This study has six variables including task crafting, cognitive crafting, relational crafting, social capital, and job performance. The indicators to measure those variables were adapted from previous studies. Each item was measured by five­point Likert ­ type (1 = strongly disagree to 5 = strongly agree).

The job crafting scale was adapted from Slemp and Vella­ Brodrick (2013), which is divided into three dimensions, namely, tasks crafting, cognitive crafting, relational crafting, with a total of 15 items. The social capital scales were measured on nine items, adapted from the study of Chumg et al. (2015); and job performance was also evaluated on five items that were adapted from Williams and Anderson (1991). Because all the scales are in English, we had to translate the scales into Vietnamese. Some of the terms in the scales were edited to make the meaning clearer.

4. Results

4.1. Sample Characteristics

Table 1 shows the demographic profile of the respon dents. As illustrated, the number of females and males was almost equal, with 207 males (53.49%) and 180 females (46.51%). In terms of age, most of the respondents were between 30 and 40 years of age, at 43.41%, followed by those who were under 30 years, at 26.36%. There were 203 bachelors amongst the respondents, accounting for 52.45%. Employees who have work experience of over 5 years are more than 50%.

Table 1: Sample Characteristics

4.2. Descriptive Statistics

To explore the nature of the data and variables, descriptive statistics were analyzed. Table 2 displays the values of minimum, maximum, mean, and standard deviation of these variables.

Table 2: Descriptive Statistics

4.3. Common Method Variance

Common method bias can occur when all the variables in the research are gathered from the same source using the same method. Thus, Harman’s single factor test was adopted to find out the problem (Podsakoff et al., 2003). By analyzing the result, we found that the data is free from common method bias because the total variance for a single factor is 48%, which is under the 50% threshold (Podsakoff et al., 2003).

4.4. Reliability Analysis

The study used factor analysis and Cronbach’s Alpha to test construct validity and reliability, respectively (Table 3). The instrument was deemed valid if the factor loading of each indicator was above 0.5, the Kaiser­Meyer­Olkin (KMO) of the variables was higher than 0.5 and the value of Barlett’s test was lower than 5% (Hair et al., 2010). Moreover, the instrument was reliable only when the Cronbach’s alpha value stands on or above 0.6 (Hair et al., 2010).

Table 3: The Results of Construct Validity and Reliability Analysis

4.5. Convergent Validity

In this study, comprehensive reliability (CR) and average variance extraction (AVE) was used to test the convergent validity of the variables.

From Table 4, the CR value of each variable is higher than the criterion value of 0.6 (Fornell & Larcker, 1981). The AVE scores are all above 0.5 (Fornell & Larcker, 1981). To sum up, all the variables in this study have convergent validity.

Table 4: The Results of Construct Validity and Reliability Analysis

4.6. Testing of Hypotheses

To test whether hypotheses H1 to H10 are supported, the authors applied Smart PL3 and SPSS 25 to examine the relationship between job crafting, social capital, and job performance.

Hypotheses H1, H2, H3 propose that task crafting, cognitive crafting, and relational crafting have a positive impact on job performance. As illustrated in Table 5, the effects of these factors got values of 0.255 (p < 0.001), 0.231 (p < 0.001), and 0.339 (p < 0.001) repetitively. This means that relational crafting has the greatest effect on job performance while cognitive crafting has the smallest effect on job performance. Besides that, these factors also positively impact social capital. These results show that task crafting has the greatest impact on social capital, while cognitive crafting has the smallest impact on social capital. Last but not least, social capital has a positive relationship with job performance.

Table 5: Structural Model Results

To evaluate the mediating effect of social capital in the relationship between job crafting and job performance, further analyses were performed to confirm the indirect effects. The results are shown in Table 6. Specifically, the bootstrap confidence intervals method was used with 5000 iterations to test the significance of the indirect effects.

Table 6: Indirect and Total Effects Analysis

*TC: Tasks crafting; CC: Cognitive crafting; RC: Relational crafting; JP: Job performance.

The results indicate that the indirect effects of the three dimensions of job crafting on job performance are positive with the values 0.069 for task crafting, 0.051 for cognitive crafting, and 0.056 for relation crafting. Thus, all hypotheses H8, H9, H10 are supported (Figure 2).

Figure 2: Structural Model

5. Discussion and Conclusion

The research is conducted with cross­sectional data. The results of the empirical analysis show that all the proposed hypotheses in this study are valid. Firstly, job crafting has positive effect on job performance, which supports the results of Tims et al. (2015). Secondly, job crafting positively impacts social capital. Based on the theory of social exchange, this study explores three dimensions of job crafting (cognitive, relational, and task crafting). The perspective of job crafting is self­oriented while the perspective of social capital is oriented towards the individual’s colleagues. According to social exchange theory, one’s efforts are rewarded by their colleagues. Moreover, social capital has a positive relationship with job performance. This result is the same as found by Ali­Hassan et al. (2015) and Basu et al. (2017).

Using the framework of job crafting, social capital, and job performance, this study enriches social exchange theory and the existing literature concerning the consequences of job crafting. Taking industrial employees in Ho Chi Minh City, Vietnam, as the research object, this study provides human management suggestions. When employees with higher job crafting skills and greater social capital are recruited by human resources management departments of enterprises, this can reduce post­training costs. At the same time, for employees who have already been employed, an improvement in their job crafting skills and social capital will help improve their job performance. Lastly, the current study suggests that the social capital of employees may also enhance employees’ performances.

Although the present research provides some insights into the literature of job crafting, it still has limitations, which open up opportunities for future researches. First, convenience sampling and cross­sectional data were analyzed, due to limited resources including manpower, financial resources, and time. In follow­up studies, other sampling methods, such as quota sampling or random sampling, and longitudinal research could be adopted.

Secondly, this study relied on self­reported data, which could bias the results (Conway & lance, 2010). Future research could benefit from integrating more objective data. For instance, managers’ or colleagues’ opinions about individuals’ employability could be included.

Finally, the respondents in this study are from the same industrial sector in Ho Chi Minh city, Vietnam, so the validity of the model cannot be generalized. It is expected that future research could look at respondents who are from a different field of work.