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Organizational Psychology, 2023, Vol. 13, No. 4, P. 183-198. DOI: 10.17323/2312-5942-2023-13-4-183-198
ORGANIZATIONAL PSYCHOLOGY
www.orgpsyjournal.hse.ru
The role of organizational citizenship behavior as an intervening variable in the relationship between employee engagement and gig workers' productivity in India
Hemanth KUMAR T
ORCID: 0000-0003-4252-1157
G KAMAL M VINOD T S LEELAVATHI Madhavi SRIPATHI Naga Y V KUMARI
SR Gudlavalleru Engineering College, Gudlavalleru, India
Abstract. The rapidly growing gig economy is bringing a new economic revolution throughout the world. India is the next frontier of this revolution, with its demographic dividend of a half-billion labour force and the world's youngest population, growing urbanization, widespread use of smart phones and related technologies. In this context, this brand — new analysis offers detailed viewpoints and suggestions on India's gig-platform economy, which employs millions of people. As a result, many corporations increasingly rely on gig workers to do their work done. Employee engagement and organizational citizenship behavior may have an impact on employees' productivity. Purpose. The purpose of this study is to investigate the impact of employee engagement on gig workers' productivity through organizational citizenship behavior as an intervening variable. Method. This study was done with 197 respondents who are working in IT industry. The data is gathered through a questionnaire. The data analysis employs descriptive, exploratory, and inferential techniques. Findings. The study's findings showed that employee engagement has an impact on organizational citizenship behavior and organizational citizenship behavior has an impact on gig workers' productivity. Implications for practice. The findings suggest that organizations should focus on creating an engaged and committed workforce while promoting positive behaviors that contribute to organizational goals. By doing so, they can enhance gig workers' productivity and improve their overall performance.
Keywords: employee engagement, gig economy, gig workers, organizational citizenship behavior (OCB), structural equation modeling (SEM), path analysis.
Address: Gudlavalleru, Vijayawada, Andhra Pradesh 521356, India. E-mail: 404.hemanth@gmail.com
SR Gudlavalleru Engineering College, Gudlavalleru, India
Narasimha A RAO
Andhra University, Visakhapatnam, India
Introduction
The gig economy has caused a significant shift in corporate work culture. Because of the shifting landscape, many corporations increasingly rely on gig workers to do their tasks. The gig economy is also known as the contingent economy, the on-demand economy, the peer economy, and the platform economy. Even in the gig economy, it is a critical aspect for organizational success. Employee engagement is defined as an employee's enthusiasm and commitment to his or her job, which is built on trust, honesty, two-way commitment, and communication between the organization and its members (Abror et al., 2020). According to a survey published by ASSOCHAM (The Associated Chamber of Commerce and Industry of India), the size of the gig economy is expected to increase at a CAGR (Compound Annual Growth rate) of 17%. According to reports, 70 percent of corporates use gig workers to save costs and cover temporary gaps, and India has risen to fifth place in the world for flexi-staffing. We can see how crucial it is for corporations to have specific measures in place to address employee engagement concerns among gig workers.
The gig economy has a stronger influence on the country's labour market, with a huge working population and an overall workforce that expands by over four million each year. The number of gig workers in the country has increased dramatically over time, as have hiring figures (Bakens, Schepers, 2021; Mohsin, Isa, Awee, Purhanudin, 2022). According to reports, over 70% of corporations used gig workers at least once or twice in the previous year to meet organizational demands. It also claims that 45 percent of human resource executives employ gig workers to augment and enhance the capabilities of the existing staff. Most of them do this since it saves money and fills temporary openings.
Gig workers, or individuals who engaged a living outside of the typical employer-employee relationship, are roughly divided into platform and non-platform-based employees. Platform employees do their jobs via online software programs or digital platforms (Alfes., Shantz, Truss, Soane, 2013). Non-platform gig workers are often casual pay and own account employees in traditional industries, working part-time or full-time.
Clearly, workplace engagement in the gig economy is unique notions that can help individuals enhance their organizational citizenship behavior (OCB) (Casu, Mariani, Chiesa, Guglielmi, Gremigni, 2021). Many gig workers find themselves in a comfortable financial situation with many opportunities for stability and advancement. As a result of workplace engagement, the gig economy is expected to thrive; gig workers are obtaining and updating their skills to ensure that this source of labour stays sustainable (Gandhi, Sensuse, Sucahyo, 2019). Workplace engagement in the gig economy, as a primary action, assists in the development of employees' different talents, both technical and non-technical (Kendrick, 2013).
Gig workers are so online labor-based platform employees who may work from anywhere in the world. They do online employment as a side job or as their major source of income through various platform enterprises. The demographic profile of gig workers often varies from young to elderly employees, with both men and women participating—with young workers having a particularly high participation percentage (Hui, Law, Chen, 1999). Gig workers get extra money in addition to fulfilling assignments. Gig workers do tasks in a flexible, accessible work environment that not only allows them to apply creative ideas but also offer major economic, social, and personal prospects (Shaker Ardakani, Abzari, Shaemi, Fathi, 2016). They appreciate the position of being autonomous and enterprising while performing a job. Furthermore, the creative performance of gig workers has become a significant study issue, emphasizing the need of examining factors that impact gig workers' creative performance for effective engagement.
Literature review and hypotheses development
Employee engagement is one of the explanatory variables of affect and attitudes of individuals that captures the cognitive, emotional and behavioral components (Biswas, Bhatnagar, 2013). Employee engagement plays mediating role between perceived organizational support (POS) and person-organization fit (P-O fit) as the antecedents and organizational commitment and job satisfaction as the consequences (Barsulai, Makopondo, Fwaya 2019; Sharifi, 2018). When employees collaborate with organizational objectives, they encouraged towards higher levels of effort and leads to P-O fit (Eom, Yang, 2014; Kamal, 2016). As a result, higher levels of job involvement and employee engagement and building high degree of commitment by employee towards organization to improve trust and loyalty for high level of engagement.
There is a causal relation between determinants of employee engagement and their impact on individual performance (Perrin, 2003). All determinants were predictors of employee engagement that had major influence on working environment and coworker relationship (Bedarkar, Pandita, 2014). This reflects on social impact that could be created by organization (Anitha, 2014; Chaudhry, 2020). Motivated and committed employees become more engaged and contribute to growth of organization. It also explores the relation between employee motivation, commitment, engagement, and job involvement. It is the responsibility of employer to provide motivation to employees for positive relation between employee commitment, job performance and engagement (Shaheen, Farooqi, 2014). Successful organizations can identify the relation between employee job satisfaction, job performance and employee engagement (Bin, 2015; Chiu, Palupi, Zhu, 2022). Employee engagement blends with job satisfaction, commitment, psychological climate, discretionary effort (Harter et al., 2002b; Perrin, 2003; Vance, 2006b). Companies having engaged employees result in higher employee retention, productivity, profitability, customer satisfaction and growth (Gruman, Saks, 2011b; Markos, Sridevi, 2010). Physical expression refers to the amount of physical energy that employees must exert to carry out their duties. Another notable definition offered by W. Schaufeli with colleagues that engagement is "a good, rewarding, work-related state of mind characterized by vigour, devotion, and absorption" (Schaufeli et al., 2002, p. 74). A. M. Saks expanded W. A. Kahn's definition of engagement to include the entire company, saying that engagement "reflects the amount to which a person is psychologically present in a particular organizational function" (Kahn, 1990; Saks, 2006).
Organizational citizenship behaviors are discretionary behaviors that are beyond formal responsibilities. These enviable behaviors have been shown to be related to job satisfaction and organizational commitment which emerged as a result of positive emotions (Robinson, Hayday, 2007; Zeinabadi, 2010). Employees' involvement in their job is concerned with how they are engaging and it has been related to OCBs and employees performance. It was investigated theoretically the functional relation between employee engagement, organizational citizenship behavior and organizational effectiveness (Kataria, Garg, Rastogi, 2012; Azmi, Desai, Jayakrishnan, 2016). One of the studies contributed that OCB can be utilized as a mediator between employee engagement and organizational effectiveness. The study also focused on employees who are highly engaged they can achieve organizational performance (Kuncoro, Wuryanti, Wibowo, Gunadi, 2019).
S. Kular with colleagues found that most of the employees were under not engaged category and many people are not enjoying the work (Kular, Gatenby, Rees, Soane, Truss, 2008). People search for more satisfaction in their day-to-day work and employers should search for by which the employees will satisfied, how to make work meaningful and how it impacts on individual and organization (Jaman, James, Luamba, 2022). The study indicated that same engagement practices are not fit for all organizational employees' motivation (Shields, Rooney, Brown, Kaine, 2020). It was suggested that
individual differences shape employee's behavior which affects their ability to engage or disengage in all or some types of role performances (Kahn, 1990). Some of the researchers confirm that emotional factors influence on employees' personal satisfaction and motivate towards their work and organization (May, Gilson, Harter, 2004; Perrin, 2003a). The evidence of the study also showed that new employees scored highest level of engagement due to optimism and enthusiasm. There is a link between level of engagement and organizational performance (Lee, 2012). HR practices focused on improvements in productivity, satisfaction and financial performance through proper engagement (Burbano, 2021).
These reviews suggests that employee engagement can lead to higher levels of OCB, which refers to voluntary actions by employees that go beyond their formal job requirements to benefit the organization. In the context of gig workers, who are often remote and have fewer formal ties to the organization, understanding the impact of employee engagement on OCB is important to promote positive work behaviors that benefit both the gig worker and the organization.
H1: Employee engagement is positively associated with gig workers' organizational citizenship behavior.
Earlier studies indicate that employee commitment is a key factor that drives OCB. However, gig workers may not have the same level of commitment to the organization as traditional employees, understanding the role of commitment in promoting positive work behaviors is important to ensure that gig workers are engaged and productive contributors to the organization.
H2: Gig workers' commitment leads to organizational citizenship behavior.
Employee performance is concerned with an employee's efforts in terms of quality and quantity in carrying out his duties in accordance with the responsibilities assigned to him (Ricardianto et al., 2020). Employee performance is connected to each employee's achievement in compliance with the numerous rules, policies, or expectations of the business or employer (Fuertes et al., 2020). Similarly, employee performance is frequently measured by an employee's attitude while accomplishing a job set by the company (Kalogiannidis, 2020). It also refers to the effects that a certain employer produces within a company (Paais, Pattiruhu, 2020). Employee performance is simply how effectively a member of staff performs their job obligations, completes tasks, and behaves in the workplace (Tagliabue, Sigurjonsdottir, Sandaker, 2020).
Furthermore, the nature of employee performance reveals everyone's skills and talents in an organization (Jiang, Du, Zhou, Cui, 2020). When compared to those with fewer experience and talents, the most competent and skilled individuals tend to demonstrate a high level of competence and devotion on the job (Ward, 2019). Consequently, employee performance outperforms others with fewer experience and ability. Poorer levels of employee performance are more likely to trigger an attributional process in which managers attribute lower levels of employee performance to dispositional characteristics, therefore holding employees accountable for their job (Lyubykh et al., 2022). Fuertes et al. (2020) underline the importance of exceptional employee performance in offering high-quality services to clients and enhancing business profitability. These advantages of improved employee performance are projected to result in a long-term competitive advantage (Jung, H. S., Seo, K. H., Yoon, H. H., 2020).
A number of systematic literature reviews on employee performance and explanatory factors have been conducted in the management literature. For example, it was shown that inadequate technology, insufficient equipment, a lack of training, or insufficient effort may all contribute to lower performance (Lyubykh, Bozeman, Hershcovis, Turner, Shan, 2022). Furthermore, the organizational environment has been proven to have an impact on employee performance since businesses are increasingly having to deal with volatile, unpredictable, difficult, and ambiguous environments (Mutonyi, Sltten, Lien, 2021). A negative organizational environment in the organization can lead to
a drop in performance rates where it is to be regarded an effective tool that helps the firm achieve its goals (Pandey, 2020). The similar conclusion reported by some researchers who showed that if the environment is favorable, employee performance would improve, which also takes job stress into account in their study (Pradoto, Haryono, Wahyuningsih, 2022). According to another study, improving employee performance may be done by increasing indicators of information sharing characteristics (Sa'adah, Rijanti, 2022). These indicators focus on leaders and subordinates producing, accumulating, and exchanging new knowledge and ideas relating to their jobs, as well as job competence and experience. As a result, corporate knowledge sharing has been found to improve employee performance. This is consistent with the findings of some research, which discovered that knowledge sharing had a significant positive influence on employee performance (Achmar, Apriliyanti, 2021; Ahmed et al., 2020; Rabuana, Yanuar, 2023).
Employee performance has been studied for decades in a variety of situations and across a wide range of disciplines and cultures, all with the goal of better understanding the behaviors, concepts, and resources that contribute to increased performance (Ioannidou, Karagiorgos, Alexandris, 2016). Prioritizing employee performance benefits both the organization and its personnel (Xiong, Wen, 2020). It allows people to reach their full potential while also improving overall performance, which has the potential to promote morale and improve job quality (Iqbal, Abdullah, 2021; Jaman, 2020). Employee performance data will now be utilized not only to show what the company can do now to better its business, but also to feed into future growth plans. Finally, and probably most critically, employee performance in achieving goals may benefit or harm the broader firm. As a result, if a firm does not adequately review its employees' performance, the organization will become chaotic and out of control (Singh, Chand, Mittal, Aggarwal, 2020). There are two options: either the leaders respond favorably to improve performance, such as by delivering constructive remarks or training, or they respond negatively through harsh supervision.
Previous studies indicates that higher levels of OCB can result in increased productivity among employees. However, in the case of gig workers who often have less direct supervision and formal connections with the organization, it is crucial to comprehend the impact of OCB on their productivity. This understanding is necessary to ensure that gig workers are making positive contributions to the organization's objectives.
H3: there is a positive relation between OCB and productivity among gig workers.
Figure 1. Mediating model of OCB between employee engagement and productivity
The above reviews suggested that OCB can act as a mediator in the association between employee engagement and productivity. However, given that gig workers may have unique work arrangements and motivations compared to traditional employees, it is crucial to comprehend the role of OCB as a mediator in the relationship between employee engagement and gig workers' productivity. Specifically, if gig workers are highly engaged, they may be more inclined to exhibit OCB, resulting in enhanced
productivity levels. Therefore, investigating the mediating role of OCB in this relationship can provide valuable insights into strategies for promoting engagement and productivity among gig workers.
H4: OCB mediates the relationship between employee engagement and gig workers' productivity.
Based on the above literature and discussion, the following research model is presented in Figure 1.
Methodology
The survey-based study gathered primary data from gig workers who work from various organizations. To collect data from respondents through questionnaire, a snowball sampling approach is utilized. The variables employed in this study were the dependent variable, mediating variable, and independent variables. Employee productivity is the dependent variable, OCB is the mediating variable (Sani, Ekowati, 2021), and employee engagement is the independent variable. Each variable consists with various factors and each factor having various items. The responses to each instrument item from the questions are graded on a Likert scale from 1 to 5.
The study assessed employee engagement through instrument developed by Gallup. The tool developed by Gallup is called the "Gallup Q12 Employee Engagement Survey," which measures organizational engagement. It used 12 items to assess four dimensions of employee engagement (i.e., basic needs, individual achievement, teamwork and growth) put forth to the respondents.It is designed to measure the level of engagement that employees have with their organization, such as their level of commitment, motivation, and satisfaction with their work. It does not specifically measure professional engagement, which refers to an employee's engagement with their specific job or role within the organization.
Organizational citizenship behavior was assessed in this study through three dimensions and 18 items adapted from "The Organizational Commitment Scale" developed by N. Alan and J. Meyer. The three dimensions measured were affective, continuance, and normative commitment (Alan, Meyer, 1990).
Employee productivity was measured through three dimensions: task performance, contextual performance, and counterproductive work behavior, using 18 items adapted from the "Individual Work Performance Questionnaire, IWPQ" developed by L. Koopmans with colleagues (Koopmans et al., 2015). Task performance referred to fulfilling the job requirements, while contextual performance referred to behaviors that support the organization but are not explicitly required, such as helping colleagues. Counterproductive work behavior referred to behaviors that harm the organization or its employees, such as theft or absenteeism. By using these scales, the study was able to measure OCB and employee productivity among gig workers.
Results and discussion
From the Table1 it is found that the mean values of the variables "employee engagement", "organizational citizenship behavior" and "employee productivity" are varying from 3.23 to 3.71. The variables are grouped based on gender. The standard deviation of employee engagement is 0.5 and 0.42 for female and male respectively. Similarly, the standard deviation of OCB is 0.54 and 0.57 and for productivity is 0.33 and 0.38. Measures of skewness and kurtosis gender wise for the variable employee engagement ((0.73, 0.45) and (1.60, 1.88)), for OCB ((0.32, -1.6) and (1.55, 1.24)) and for productivity ((0.66, 0.47) and (0.83, -0.23)).
Table1. Descriptives
Parameters Gender EE OCB Productivity
N Female 27 27 27
Male 170 170 170
Missing Female 0 0 0
Male 0 0 0
Mean Female 3.71 3.7 3.23
Male 3.64 3.61 3.13
Standard deviation Female .507 .547 .334
Male .426 .508 .382
Skewness Female .736 .326 .662
Male .451 -.161 .474
Standard error skewness Female .448 .448 .448
Male .186 .186 .186
Kurtosis Female 1.6 1.55 .0832
Male 1.88 1.24 -.232
Standard error kurtosis Female .872 .872 .872
Male .37 .37 .37
Reliability analysis
The Table 2 shows the overall reliability of the items. The overall score of Cronbach's alpha is 0.925 (N = 3.48, SD = 0.389) which is more than the acceptable range i.e. 0.7 (Nunnally, 1978; George, Mallery, 2003). Hence it is clear indication that scale is reliable for further analysis.
Table 2. Scale reliability statistics
Mean SD Cronbach's a
Scale 3.48 .389 .925
Figure 2. Correlation heat map
Table 3. Correlation matrix
Variables Correlation EE OCB Productivity
Employee engagement (EE) Pearson's r p-value -
Organizational citizenship behavior (OCB) Pearson's r .744 -
p-value < .001 -
Employee productivity Pearson's r .557 .713 -
p-value < .001 < .001 -
The correlation map (Figure 2) and Table3 depict the relationship between various components studied in the research. It is observed that gig workers' productivity has a strong positive correlation with both OCB (0.71) and employee engagement (0.56). Additionally, most of the components studied exhibit a positive relationship with gig workers' productivity. Conversely, employee counter work behavior shows a negative correlation with other components of employee engagement, OCB, and gig workers' productivity.
Further analysis shows that employee engagement strongly correlates with individual work (0.88) and basic needs (0.79). Meanwhile, OCB is strongly correlated with affective commitment (0.90), continuance commitment (0.77), and normative commitment (0.92). Moreover, gig workers' productivity is highly correlated with task performance (0.84) and contextual performance (0.90). Based on these findings, the study accepts the hypotheses H1 and H3.
Structural equation modeling
The regression and SEM model specify different relationships between variables in the model. The models include the same predictor and predicted variables in different configurations. Although statistical tests of significance differ, the amount of variance explained in each model is equal.
Like the regression analysis (Table 4) significant parameter estimates were contextual performance (z = 13.048) is highly significant and counterproductive work behavior (z = 0.255) is not significant with gig workers' productivity. The variable estimates individual (z = 8.83) and teamwork (z = 8.14) are highly significant than growth (z = 6.64) of respondents. Similarly, continuance commitment (z = 10.03) and normative commitment (z = 16.67) are significant with organizational citizenship behavior.
Table 4. Measurement model
Latent Observed Estimate SE 95% Confidence Intervals ß z
Lower Upper P
Productivity ATP 1 0 1 1 .8547
ACP .7195 .0551 .611 .828 .8158 13.048 < .001
ACWB .0159 .0621 -.106 .138 .0193 .255 .799
Employee engagement ABN 1 0 1 1 .5983
AI 1.1798 .1336 .918 1.442 .8784 8.833 < .001
AT .8943 .1099 .679 1.11 .7533 8.134 < .001
AG .5432 .0818 .383 .704 .5686 6.64 < .001
Organizational citizenship behavior AAC 1 0 1 1 .8519
ACC .5457 .0544 .439 .652 .6451 1.032 < .001
ANC .9531 .0572 .841 1.065 .9043 16.67 < .001
The path diagram (Figure 3) estimated the relation between the variable employee productivity (0.71) with contextual performance and no significant relation with counterproductive work behavior (0.01) with significant value of 0.799 which is greater than 0.05. Employee engagement is estimated with the variables of individual (1.17), teamwork (0.89) and growth (0.54) of gig workers.
The mediator role of organizational citizenship behavior estimated with continuance commitment (0.54) and normative commitment (0.95) respectively.
Mediating effects of organizational citizenship behavior
To create mediation, three elements must be satisfied (Baron, Kenny, 1986). First, the mediator must be connected to the independent variable ("employee engagement"). The mediator organizational citizenship behavior must also be connected to the dependent variable. Third, after controlling for the mediator, a substantial link between the independent variable (employee engagement) and a dependent variable (productivity) is decreased (partial mediation) or no longer exists (full mediation). Conditions one and two, as previously indicated, have been met. Employee engagement must first be linked to productivity for requirement three.
Figure 3. Path diagram
From Table 5 and Table 6 additional mediation analysis was performed to test for a mediation model in which OCB mediates the association between employee engagement and productivity. Productivity was based on the OCB alone and then again with the engagement measures controlled. There is a direct relationship between employee engagement and OCB (SE = 0.055, Z = 15.63), and between OCB and productivity (SE = 0.054, Z = 8.96). However, there is indirect relationship between employee engagement and productivity (SE = 0.064, Z = 0.80). Consequently, we accept the hypothesis H4.
Table 5. Mediation estimates
Effect Estimate SE z P
Indirect Indirect .0552 7.773 < .001
Direct Direct .0643 .802 .423
Total Total .0510 9.422 < .001
Table 6. Path estimates
Estimate SE z p
Employee engagement Organizational citizenship behavior .8732 .0559 15.631 < .001
Organizational citizenship behavior Productivity .4910 .0548 8.960 < .001
Employee engagement — Productivity .0516 .0643 .802 .423
Gig workers' productivity
To test the hypothesis for gig workers' productivity, regression analysis was conducted in which R is 0.71 that shows the strong correlation between the variables (Table 7). As p-value is less than 0.05 with (df = 196; F = 101), the model is appropriate and gig workers' productivity is depending on employee engagement and OCB.
Table 7. Model fit measures
Model R R2 Adjusted R2 RMSE F Overall model test df1 df2 p
1 .714 .510 .505 .263 101 2 194 < .001
Linear regression
Linear regression model summary as well as the overall fit statistics is shown in the table above. It has found that R2 of our model in employees and gig workers' responses are 0.71 with R2 = 0.51 meaning that linear regression explains 26.3 percentage of the variance in the data.
Table 8. Model coefficients — AP
Predictor Estimate SE t P
Intercept 1.1830 .1608 7.358 < .001
Employee engagement .0516 .0648 .796 .427
Organizational citizenship behavior .4910 .0552 8.892 < .001
Model coefficients indicate as to how much the dependent variable varies with an independent variable when all other independent variables are held constant (Table 8). From the above table it shows that based on employee responses the OCB significant predictor as a sig. value in above mentioned variables is less than 0.05 and employee engagement is indirect predictor as a significant value is greater than 0.05. Hence, the data indicating that the hypothesis H2 is accepted.
Results and discussion
The results of the study suggest that gig workers' productivity is strongly correlated with both OCB and employee engagement. The correlation map and table show that most of the components are positively related to gig workers' productivity, with counterproductive work behavior being negatively correlated with other components of employee engagement, OCB, and gig workers' productivity. Specifically, employee engagement strongly correlates with individual work and basic needs, while OCB is strongly correlated with affective commitment, continuance commitment, and normative commitment. Gig workers' productivity is highly correlated with task performance and contextual performance.
The study also found significant parameter estimates, with contextual performance being highly significant and counterproductive work behavior being not significant with gig workers' productivity. Individual and teamwork were found to be highly significant than growth of respondents. Similarly, continuance commitment and normative commitment were significant with organizational citizenship behavior. The path diagram estimated the relationship between employee productivity and contextual performance, with no significant relationship found between counterproductive work behavior and gig workers' productivity. Employee engagement was estimated with the variables of individual, teamwork, and growth of gig workers. The mediator role of OCB was estimated with continuance commitment and normative commitment, respectively. Additional mediation analysis
was performed to test for a mediation model in which OCB mediates the association between employee engagement and productivity. There was a direct relationship between employee engagement and OCB, as well as between OCB and productivity. However, there was an indirect relationship between employee engagement and productivity.
Finally, regression analysis was conducted to evaluate the hypothesis that gig workers' productivity depends on employee engagement and OCB. The R-value of 0.71 shows a strong correlation between the variables. The p-value being less than 0.05 with (df= 196; F = 101) indicates that the model is appropriate, and gig workers' productivity depends on employee engagement and OCB. The study highlights the importance of both employee engagement and OCB in enhancing gig workers' productivity. The findings suggest that organizations should focus on creating an engaged and committed workforce while promoting positive behaviors that contribute to organizational goals. By doing so, they can enhance gig workers' productivity and improve their overall performance.
Conclusion
The study found a strong correlation between gig workers' productivity, employee engagement, and organizational citizenship behavior. The study also found that task performance and contextual performance were highly correlated with gig workers' productivity, while counterproductive work behavior was not significant. The mediator role of OCB was also established between employee engagement and productivity. The study concludes that gig workers' productivity is dependent on both employee engagement and OCB. Based on the results of the study, it is suggested that organizations should focus on promoting employee engagement and OCB among gig workers to enhance their productivity. This can be achieved by providing opportunities for individual and teamwork, as well as growth and development. Additionally, fostering a sense of commitment among gig workers can also contribute to higher levels of OCB. It is also recommended that organizations carefully monitor and address any counterproductive work behavior, as this has a negative impact on gig workers' productivity. Finally, mediation analysis suggests that OCB may mediate the relationship between employee engagement and productivity, indicating the importance of encouraging OCB to improve productivity among gig workers. further research could explore the role of individual characteristics, such as personality traits and motivation, in shaping gig workers' engagement and productivity. Finally, it may be valuable to conduct longitudinal studies to better understand the dynamic relationships between engagement, OCB, and productivity over time.
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Received 01.09.2022
Роль организационного гражданского поведения как промежуточной переменной во взаимосвязи между вовлечённостью сотрудников и производительностью самозанятых работников в Индии
КУМАР Т Хемант
ОЯСЮ: 0000-0003-4252-1157
Инженерный колледж С.Р. Гудлаваллеру, Гудлаваллеру, Индия
РАО Нарасимха
Университет Андхра, Вишакхапатнам, Индия
КАМАЛЬ Г ВИНОД М ЛИЛАВАТИ Т. С. ШРИПАТИ Мадхави КУМАРИ Ю В Нага
Инженерный колледж С.Р. Гудлаваллеру, Гудлаваллеру, Индия
Аннотация. Быстро растущая гиг-экономика вызывает новую экономическую революцию во всём мире. Индия является очередным рубежом этой революции с её демографическим приростом в виде полумиллиарда рабочей силы и самым молодым населением в мире, растущей урбанизацией, широким распространением смартфонов и связанных с ними технологий. В этом контексте данный совершенно новый анализ освещает подробные точки зрения и выдвигает предложения для индийской экономики, основанной на платформе свободного заработка, в которой работают миллионы людей. В результате многие корпорации всё чаще полагаются на свободных работников для выполнения своих задач. Вовлечённость сотрудников и их гражданское поведение в организации могут влиять на производительность их труда. Цель. Целью данного исследования является изучение влияния вовлечённости сотрудников на производительность их труда посредством организационного гражданского поведения в качестве промежуточной переменной. Метод. В этом исследовании приняли участие 197 респондентов, работающих в ИТ-индустрии. Данные собирались путём анкетирования. В анализе данных использованы описательные, исследовательские и логические методы. Выводы. Результаты исследования показали, что вовлечённость сотрудников вносит вклад в организационное гражданское поведение, а организационное гражданское поведение, в свою очередь, вносит вклад в производительность труда. Практическая значимость. Результаты показывают, что организациям следует сосредоточиться на создании заинтересованного и преданного своему делу персонала, одновременно поощряя позитивное поведение, которое способствует достижению организационных целей. Поступая таким образом, они могут повысить производительность труда рабочих и повысить их общую производительность.
Ключевые слова: вовлечённость сотрудников, гиг-экономика, гиг-работники, организационное гражданское поведение, моделирование структурными уравнениями, путевой анализ.
