Behavioral perspectives: Examining the nexus between high-commitment work systems and sustainable performance
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Cite this article:
Hussain, A.,
Xue, Y.,
Hassaan, M.,
Akhtar, R.,
Akhtar, A.,
Yaseen, A., &
Ibrahim, A.
(2025). Behavioral perspectives: Examining the nexus between high-commitment work systems and sustainable performance.
Social Behavior and Personality: An international journal,
53(5),
e14111.
Abstract
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Rapidly changing business environments necessitate sustainable performance. While research on environmentally responsible behavior continues to expand, the complexities and boundaries of this phenomenon are not yet fully comprehended. To address this knowledge gap, this study investigated the relationship between high-commitment work systems (HCWS) and sustainable performance, leveraging the resource-based view and sustainable human resources literature. Results from a survey of 555 telecommunications employees showed a positive correlation between HCWS and sustainable performance. Notably, innovative work behavior and employee well-being partially mediated this relationship. This study contributes to the HCWS and sustainable performance literature and offers practical recommendations for promoting sustainability and achieving sustainable development goals in the telecommunications industry.
The growing economy of Pakistan and the expanding field of human resource management (HRM) has driven firms to adopt strategic HRM practices to enhance business performance. Various labels, such as high-performance work systems (Sun et al., 2007) and high-involvement work systems (Gollan, 2005) have been used to describe strategic HRM approaches. Wei and Lau (2010) suggested that these labels share the principle of viewing employees as valuable resources that contribute to a firm’s competitive advantage. Many scholars have used these terms interchangeably (e.g., Chen et al., 2018), but in this study, we used the term high-commitment work system to describe the set of human resource practices designed to improve employee output by increasing the organization’s investment therein (Holbeche, 2022).
Scholars including Chen et al. (2018) and Oppenauer and Van De Voorde (2018) have posited that HCWS necessitate a mutual commitment between employees and organizations to enhance their efficacy in forecasting performance results. However, studies on the impact of human resources practices on performance have produced inconsistent results (Tzabbar et al., 2017; van Esch et al., 2018; Veth et al., 2019). Furthermore, strategic HRM research in Asia has been centered primarily on China (Chen et al., 2018; Chow et al., 2008; van Esch et al., 2018), so there is a need to investigate other Asian settings such as Pakistan (Fan et al., 2014; Farndale & Sanders, 2017). This study addressed that gap by investigating how HCWS influence sustainable performance in telecommunication companies in Pakistan while considering employee well-being and innovative work behavior as mediating factors.
Sustainable performance is a company’s ability to achieve long-lasting success by balancing economic feasibility, social responsibility, and environmental protection (Augustie & Saad, 2019; Ma et al., 2022). It is evaluated by metrics such as carbon emissions, waste reduction, water usage, and profitability (Augustie & Saad, 2019; Ma et al., 2022). HCWS promote sustainable performance by enhancing employee engagement, skill development, and motivation, leading to long-term competitive advantages (Jiang et al., 2017). HCWS can affect employees’ propensity for innovative behaviors, which involve generating, endorsing, and implementing novel ideas (Llego, 2013; Tzafrir, 2005; P. M. Wright et al., 2005). Innovative work behavior refers to behaviors directed toward implementing change; exploration of opportunities; and the introduction and application of new ideas, processes, or products within a work role, team, or organization to improve performance or results (De Jong & Den Hartog, 2010). Innovative work behavior is essential for driving organizational innovation and improving overall performance. (Muhamad et al., 2023). However, the impact of HRM systems on employees’ innovative work behavior in shaping sustainable performance has not been adequately explored, and empirical evidence is scarce (Jiménez-Jiménez & Sanz-Valle, 2008; Muhamad et al., 2023). Addressing this gap will enhance understanding of how HCWS can support and shape employees’ innovative work behavior, ultimately leading to sustainable performance.
Employee well-being includes the physical, mental, and emotional well-being of employees, which has a direct impact on their job satisfaction and the organization’s sustainable performance (Moç, 2023). Studies have shown that sustainable performance and employee well-being are linked (see, e.g., T. A. Wright & Cropanzano, 1998). Employee well-being includes an individual’s ability to cope with stress, engage in meaningful work, and participate in their community (Litmanen, 2021). Research has also indicated there is a positive relationship between employee well-being and organizational performance (Peccei et al., 2013). However, previous studies have not examined the mediating role of employee well-being in the relationship between HCWS and sustainable performance. Understanding the impact of HCWS on employee well-being is vital to promote organizational development (X. Li & Lin, 2021). Our study aimed to provide practical insights for managers in leveraging human resources systems to promote innovation, enhance employee well-being, and achieve sustainable development goals.
The Current Study
The resource-based view emphasizes that firms require valuable resources, comprising human, physical, and organizational capital, to gain a competitive edge (Barney, 1991). Within HCWS, a skilled and committed workforce is vital, contributing significantly to organizational sustainability performance (Marchiori et al., 2023). Our study investigated the effect of HCWS practices on sustainability outcomes, mediated by employees’ innovative work behavior and employee well-being, through the lens of the resource-based view (Davis & DeWitt, 2021; Marchiori et al., 2023; Miao et al., 2020). By understanding these relationships, organizations can strategically leverage HCWS to promote sustainability (Azeem et al., 2021).
High-Commitment Work Systems and Sustainable Performance
HCWS are an HRM strategy that emphasizes employee involvement, empowerment, and development in improving sustainable performance. By prioritizing employee well-being, as well as employee empowerment and development, HCWS cultivate a more engaged and innovative workforce (Imran & Al-Ansi, 2019), which promotes improved customer service and loyalty (P. M. Wright et al., 2005). Furthermore, HCWS can optimize processes, reduce costs, attract top talent, and create a sustainable cycle of innovation and efficiency (Backhaus & Tikoo, 2004; Maylett & Wride, 2017). This aligns with the resource-based view, where HCWS balance economic, social, and environmental goals (Augustie & Saad, 2019; Ma et al., 2022). Investment in recruitment, training, compensation, recognition, and motivation results in increased employee commitment and promotes long-term sustainable performance (Ling & Amponstira, 2021). Therefore, we proposed the following hypothesis:
Hypothesis 1: There will be a positive relationship between high-commitment work systems and an organization’s sustainable performance.
High-Commitment Work Systems, Innovative Work Behavior, and Organizational Sustainable Performance
Innovative work behavior refers to the implementation of novel ideas and solutions driving innovation and enhancing organizational performance (Muhamad et al., 2023). HCWS can impact organizational sustainable performance by creating a work environment that encourages employee innovation (Nugroho, 2023). Employees’ innovative efforts contribute to sustainable practices, such as resource efficiency (Thneibat, 2024). Innovation also aligns organizations with social and environmental goals, enhancing sustainable performance (Borsatto & Bazani, 2023). As the resource-based view suggests that innovation is important for sustainable success (Uyanik, 2023) organizations should adopt and support creative ideas (Imran & Al-Ansi, 2019). Hence, we proposed the following hypotheses:
Hypothesis 2: There will be a positive relationship between high-commitment work systems and the innovative work behavior of employees.
Hypothesis 3: There will be a positive relationship between the innovative work behavior of employees and the sustainable performance of organizations.
Hypothesis 4: Innovative work behavior will mediate the relationship between high-commitment work systems and the sustainable performance of organizations.
High-Commitment Work Systems, Employee Well-Being, and Organizational Sustainable Performance
HCWS promote employee well-being by fostering a supportive environment through employee involvement, skill development, and job security (Peccei et al., 2013). By enhancing job satisfaction, work–life balance, and psychological well-being among employees, HCWS promote engagement and motivation, which have a positive impact on organizational performance and sustainability (T. A. Wright & Cropanzano, 1998). A healthy workforce attracts talent, fosters innovation, and enhances an organization’s reputation (S.-L. Li et al., 2019). Employee well-being directly affects job satisfaction and organizational sustainable performance (Moç, 2023) and serves as a mediator between HCWS practices and sustainable performance (Nielsen et al., 2017); thus, we proposed the following hypotheses:
Hypothesis 5: There will be a positive relationship between high-commitment work systems and employee well-being.
Hypothesis 6: There will be a positive relationship between employee well-being and the sustainable performance of organizations.
Hypothesis 7: Employee well-being will mediate the relationship between high-commitment work systems and the sustainable performance of organizations.
Our research model is shown in Figure 1.
Figure 1. Research Model
Note. Dashed lines denote proposed mediating effects.
Method
Participants and Procedure
This quantitative study explored the relationships among HCWS, innovative work behavior, employee well-being, and sustainable performance within the telecommunication sector in Punjab Province, Pakistan. Data were collected from 700 employees across major telecommunications companies (i.e., Mobilink, Telenor, Ufone, and Zong) using an adapted questionnaire distributed via Google Forms. We obtained informed consent from all participants. Data collection took place from September 10 to December 20, 2023. After excluding 145 responses from employees in nontelecommunications sectors, we analyzed 555 responses using structural equation modeling. Demographic details are shown in Table 1.
Table 1. Respondents’ Demographic Details
Note. Results were generated using SPSS 25.0.
Measures
We used a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) to measure all the variables in this study. To ensure the cultural and linguistic equivalence of the measurement instruments, all questionnaires were translated into Urdu, the primary language of the participants, using the back-translation method (Brislin, 1970). Items were slightly modified, through literature review and discussions with professors and industry experts, to fit the context of our study.
We assessed HCWS using six items from Xiao and Björkman (2006), innovative work behavior with four items from Janssen (2000), employee well-being using four items from Nielsen et al. (2017), and sustainable performance with five items adapted from Mousa and Othman (2020). See Appendix for all items.
Data Analysis
We used SPSS 25.0 for demographic analysis, and SmartPLS 4.0 for hypothesis testing, regression analysis, and mediation analysis. Cronbach’s alpha values ranged from .70 to .95. Therefore, the measures had good reliability. We conducted a confirmatory factor analysis to validate the structural model.
Results
Validity and Reliability Tests
Figure 2 shows the associations among the variables (Hair et al., 2019).
Figure 2. Measurement Model
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
We used outer model analysis to assess the validity and reliability of the constructs and items following the application of quality criteria to our measurement instruments (Henseler et al., 2016). The results (see Table 2) showed acceptable outer loadings of > .60 and > .70.
Table 2. Quality Criteria for the Measurement Instruments
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance; CR = composite reliability; AVE = average variance extracted.
Discriminant Validity
We calculated heterotrait–monotrait ratios and Fornell–Larcker criterion values, and conducted a cross-loading analysis to evaluate discriminant validity (Henseler et al., 2015; Rasoolimanesh, 2022) and ensure the variables measured what they were intended to measure (Taherdoost, 2016; Vanalle et al., 2017). Table 3 shows the results of the cross-loading analysis.
Table 3. Cross-Loading Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; SP = sustainable performance; EWB = employee well-being.
Table 4 shows the results of the Fornell–Larcker criterion analysis.
Table 4. Fornell–Larcker Criterion Results
Note. Square roots of average variance extracted are shown on the diagonal.
Table 5 shows the heterotrait–monotrait ratios, indicating that adequate discriminant validity was achieved in our study. Some scholars advocate for a stricter threshold of .85 (Clark & Watson, 2016; Kline, 2018), while others consider values below .90 to be acceptable (Gold et al., 2001; Teo et al., 2008). In this study, we adopted a threshold of .90 to assess discriminant validity.
Table 5. Heterotrait–Monotrait Ratio Matrix
Multicollinearity Analysis
Before analyzing the study’s structural model, we checked for multicollinearity in the data using variance inflation factors (Hair et al., 2017). Our study had a multicollinearity value of 2.51, which falls within the standard range < 3.00, suggesting that multicollinearity did not pose a problem in this study (Henseler et al., 2016).
Structural Model
We used SmartPLS 4.0 to conduct a bootstrapping analysis with 5,000 resamples, following the recommendation of Henderson (2005). We investigated the link between the independent factor (i.e., HCWS), the mediating variables (i.e., innovative work behavior and employee well-being), and the dependent variable (i.e., sustainable performance), as shown in Figure 3. We also calculated t values, path coefficients, standard errors, and the significance of the relationships. Figure 3 demonstrates that all measures were statistically significant, with t values > 1.96 and p values < .05 (Winship & Zhuo, 2020).
Figure 3. Structural Model
Note. Path coefficient values of .000 indicate estimates below .0005. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
All indicators of sustainable performance exhibited strong correlations with the study variables, suggesting robust relationships between HCWS, innovative work behavior, employee well-being, and sustainable performance, as depicted in Table 6.
Table 6. Latent Variable Correlations
The R2 coefficient was utilized to gauge the model’s suitability (Winship & Zhuo, 2020). The results were as follows: sustainable performance, R2 = .573, innovative work behavior, R2 = .638, and employee well-being, R2 = .505, indicating considerable moderate relationships. The R2 values for innovative work behavior and employee well-being likely resulted from HCWS as the main predictor, while the R2 for sustainable performance resulted from a combination of HCWS, innovative work behavior, and employee well-being as predictors. This combination included both direct effects and indirect (mediating) effects through innovative work behavior and employee well-being.
Results of Hypothesis Testing
Table 7 presents the outcomes of the structural model assessment, displaying the t values that represent the relationships between the predictor variables and their corresponding influencing variables. Additionally, Table 7 shows the path coefficients and bootstrapping analysis output generated by SmartPLS 4.0.
Table 7. Hypothesis Testing Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
The results of the hypothesis testing using SmartPLS 4.0 are shown in Table 7 and Figure 3. All direct hypotheses (Hypotheses 1, 2, 3, 5, and 6) were supported, β > .20, t > 1.96, p < .05.
Mediation Hypothesis Testing
Hypothesis testing results for the mediating variables are shown in Table 8 and Figure 3. Hypotheses 4 and 7 were supported, β > .20, t > 1.96, p < .05.
Table 8. Mediation Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
Analysis of Partial or Full Mediation
The findings shown in Tables 7 and 9 support the mediating effect of innovative work behavior and employee well-being on the connection between HCWS and sustainable performance (Hypotheses 4 and 7). To determine whether this mediation was partial or full, we employed the variance-accounted-for approach, calculating the ratio of the indirect to total effect. A value below 20% signifies no mediation, 20–80% indicates a partial mediation effect, and over 80% suggests full mediation (Hair et al., 2019). Table 8 displays the indirect effects, while the direct effects can be found in Table 7, revealing partial mediation.
Table 9. Mediation Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance; VAF = variance accounted for.
Discussion
Our study significantly enhances understanding of the relationship between HCWS and sustainable performance, shedding light on the internal mechanisms driving organizational success. Consistent with prior research (Barrick et al., 2015), our findings revealed a robust link between HCWS and sustainable performance. This correlation underscores the critical role of HCWS in fostering an environment conducive to sustainable performance, thus promoting employee engagement, empowerment, and motivation through autonomy, skill development, and job security (Peccei et al., 2013). Notably, innovative work behavior and employee well-being partially mediated this relationship. Our results suggest that HCWS positively impacted innovative work behavior and employee well-being, driving sustainable performance. This aligns with research by Chaubey et al. (2019) and X. Li and Lin (2021), emphasizing the role of HCWS in fostering innovation, well-being, and sustainable performance. The practical implications are substantial, particularly for organizations striving to achieve long-term sustainable development goals. By investing in HCWS, organizations enhance social responsibility and economic viability (T. A. Wright & Cropanzano, 1998). Moreover, HCWS cultivate a supportive work environment where employees feel valued, motivated, and empowered to take calculated risks, experiment with innovative solutions, and drive organizational growth and sustainability (Imran & Al-Ansi, 2019). Our study’s contributions have far-reaching implications, establishing clear links between HCWS, innovative work behavior, employee well-being, and sustainable performance. This foundational linkage provides a basis for exploring strategies that foster sustainable performance, enhance employee well-being, and ensure long-term success (Augustie & Saad, 2019; Ma et al., 2022).
Practical Implications
Integrating HCWS into a company’s operations can significantly improve both the innovative behavior of employees and organizational sustainable performance. Cultivating a supportive organizational climate that fosters innovation through efficient HCWS can lead to sustainable performance. Moreover, the insights we have obtained in this study align with the United Nations’ sustainable development goals, particularly regarding decent work and economic growth; industry, innovation and infrastructure; responsible consumption and production; and climate action through promoting suitability in organizational practices (United Nations, n.d.). Managers and human resource professionals should adopt HCWS as part of their strategic efforts to contribute to these global goals while also improving internal performance and innovation.
Limitations and Future Research Directions
This study has limitations that warrant future consideration. The sample of 555 respondents, drawn exclusively from Pakistan’s Punjab province and from the telecommunications sector, may constrain the generalizability of findings to other industries or geographical regions. To address this, future investigations would benefit from employing larger, more diverse samples to enhance external validity. Additionally, the cross-sectional research design provides only a temporal snapshot of the observed relationships, highlighting the need for longitudinal or experimental designs to establish stronger evidence for causality. Most significantly, the current study is limited in its capacity to comprehensively assess the impact of HCWS on sustainable performance. These limitations present a crucial opportunity for future research to examine how HCWS contribute to the achievement of specific sustainable development goals. Such investigations could establish clearer theoretical and empirical linkages between employee innovative behavior in the workplace and organizational sustainable performance outcomes.
Conclusion
This empirical study investigated the intricate relationships between HCWS, innovative work behavior, employee well-being, and sustainable performance within Pakistan’s telecommunications sector. Our findings indicate that HCWS played a pivotal role in driving sustainable performance, mediated by innovative work behavior and employee well-being. Notably, our research findings suggest that HCWS positively impacted innovative work behavior and employee well-being, which, in turn, enhanced organizational sustainable performance. Our research contributes to theory and practice by providing empirical evidence on the HCWS–sustainable performance relationship in a developing country context, emphasizing the mediating effects of employee well-being and innovative work behavior on organizational sustainable performance. Overall, this study provides valuable insights for strategic HRM, highlighting the critical role of HCWS and employee well-being in driving organizational success and sustainability. By embracing this knowledge, organizations can navigate the complex landscape of modern business, prioritizing both people and performance.
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United Nations. (n.d.). Sustainable development goals.
Uyanik, M. (2023). Resource-based view in marketing literature. Journal of Business and Management Studies, 5(4), 29–39. https://doi.org/10.32996/jbms.2023.5.4.4
van Esch, E., Wei, L. Q., & Chiang, F. F. T. (2018). High-performance human resource practices and firm performance: The mediating role of employees’ competencies and the moderating role of climate for creativity. The International Journal of Human Resource Management, 29(10), 1683–1708.
Vanalle, R. M., Ganga, G. M. D., Godinho Filho, M., & Lucato, W. C. (2017). Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. Journal of Cleaner Production, 151, 250–259. https://doi.org/10.1016/j.jclepro.2017.03.066
Veth, K. N., Korzilius, H. P. L. M., Van der Heijden, B. I. J. M., Emans, B. J. M., & De Lange, A. H. (2019). Which HRM practices enhance employee outcomes at work across the life-span? The International Journal of Human Resource Management, 30(19), 2777–2808. https://doi.org/10.1080/09585192.2017.1340322
Wei, L.-Q., & Lau, C.-M. (2010). High performance work systems and performance: The role of adaptive capability. Human Relations, 63(10), 1487–1511. https://doi.org/10.1177/0018726709359720
Winship, C., & Zhuo, X. (2020). Interpreting t-statistics under publication bias: Rough rules of thumb. Journal of Quantitative Criminology, 36(2), 329–346. https://doi.org/10.1007/s10940-018-9387-8
Wright, P. M., Gardner, T. M., Moynihan, L. M., & Allen, M. R. (2005). The relationship between HR practices and firm performance: Examining causal order. Personnel Psychology, 58(2), 409–446.
Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a predictor of job performance and voluntary turnover. Journal of Applied Psychology, 83(3), 486–493. https://doi.org/10.1037/0021-9010.83.3.486
Xiao, Z., & Björkman, I. (2006). High commitment work systems in Chinese organizations: A preliminary measure. Management and Organization Review, 2(3), 403–422. https://doi.org/10.1111/j.1740-8784.2006.00049.x
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Vanalle, R. M., Ganga, G. M. D., Godinho Filho, M., & Lucato, W. C. (2017). Green supply chain management: An investigation of pressures, practices, and performance within the Brazilian automotive supply chain. Journal of Cleaner Production, 151, 250–259. https://doi.org/10.1016/j.jclepro.2017.03.066
Veth, K. N., Korzilius, H. P. L. M., Van der Heijden, B. I. J. M., Emans, B. J. M., & De Lange, A. H. (2019). Which HRM practices enhance employee outcomes at work across the life-span? The International Journal of Human Resource Management, 30(19), 2777–2808. https://doi.org/10.1080/09585192.2017.1340322
Wei, L.-Q., & Lau, C.-M. (2010). High performance work systems and performance: The role of adaptive capability. Human Relations, 63(10), 1487–1511. https://doi.org/10.1177/0018726709359720
Winship, C., & Zhuo, X. (2020). Interpreting t-statistics under publication bias: Rough rules of thumb. Journal of Quantitative Criminology, 36(2), 329–346. https://doi.org/10.1007/s10940-018-9387-8
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Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a predictor of job performance and voluntary turnover. Journal of Applied Psychology, 83(3), 486–493. https://doi.org/10.1037/0021-9010.83.3.486
Xiao, Z., & Björkman, I. (2006). High commitment work systems in Chinese organizations: A preliminary measure. Management and Organization Review, 2(3), 403–422. https://doi.org/10.1111/j.1740-8784.2006.00049.x
Figure 1. Research Model
Note. Dashed lines denote proposed mediating effects.
Table 1. Respondents’ Demographic Details
Note. Results were generated using SPSS 25.0.
Figure 2. Measurement Model
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
Table 2. Quality Criteria for the Measurement Instruments
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance; CR = composite reliability; AVE = average variance extracted.
Table 3. Cross-Loading Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; SP = sustainable performance; EWB = employee well-being.
Table 4. Fornell–Larcker Criterion Results
Note. Square roots of average variance extracted are shown on the diagonal.
Table 5. Heterotrait–Monotrait Ratio Matrix
Figure 3. Structural Model
Note. Path coefficient values of .000 indicate estimates below .0005. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
Table 6. Latent Variable Correlations
Table 7. Hypothesis Testing Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
Table 8. Mediation Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance.
Table 9. Mediation Analysis Results
Note. HCWS = high-commitment work systems; IWB = innovative work behavior; EWB = employee well-being; SP = sustainable performance; VAF = variance accounted for.
All authors contributed to the conception, design, and execution of this research. Asif Hussain conducted the literature review, developed the theoretical framework, and wrote the original draft manuscript. Yang Xue was responsible for supervision; project administration; and reviewing, editing, and rewriting the draft manuscript. Muhammad Hassaan was responsible for data collection, statistical analysis, and rewriting the manuscript. Raheel Akhtar designed the questionnaire and undertook the data collection, data interpretation, editing, revising, and rewriting the manuscript. Adeel Akhtar was responsible for conceptualization, editing, revising, and rewriting the manuscript. Asif Yaseen wrote the methodology, conducted the data analysis, and edited and rewrote the manuscript. Asma Ibrahim wrote the interpretation of the results, discussion, implications, and contributed to rewriting the manuscript.
The authors have no conflicts of interest to declare.
The data that support the findings of this study are available on request from the corresponding author.
Raheel Akhtar, Department of Business and Public Administration, Emerson University Multan, Multan City, Punjab, 60700, Pakistan. Email [email protected]
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