Examining Job Performance through the lens of High-Performance Work Systems: Insights from e-tailing industry
Lokesh Vijayvargy
Professor
Jaipuria Institute of Management,
Jaipur, Rajasthan, India.
Corresponding author: lokeshvijay79@gmail.com
Renu Girotra,
Associate Professor
School of Business, Woxsen
University, Hyderabad, India
Email: renu27j@yahoo.in
Rashi Baliyan,
Associate Faculty
Exceed College, Westfield Education
Group, Sharjah, UAE
Email id: rashi15baliyan@gmail.com
Utkarsh Kumar Verma
Assistant Professor
School of Business,
Galgotias University, Greater Noida,
Uttar Pradesh, India
E-Mail: utkarsh.verma@galgotiasunversity.edu.in
Ananta Narayana
Assistant Professor
School of Business Management,
Noida International University,
Greater Noida, Uttar Pradesh, India
E-Mail: ananta.narayana20@gmail.com
Abstract
Purpose: This study investigates the effects of high-performance work systems on job performance in the context of the e-tailing industry in India. While HPWS's positive impact on job performance has been widely discussed and established, the study investigates the impact in current times marked by technological interventions impacting work structures. These have brought in challenges for HR personnel to keep employees motivated and satisfied to achieve enhanced organizational productivity. With ecommerce expanding exponentially and offering employment to many, it becomes vital for the organizations within the vertical to analyze employee motivation, job satisfaction through HPWS. This research explores this black-box investigating transformation in job performance, quality of life, motivation, job satisfaction, and organizational commitment in current times with the employee-centric approach.
Design/Methodology: This report, exploratory in character, has been conducted using primary and secondary sources, including journal articles, internet posts, and blogs. The questionnaire is the primary method of collecting data for this quantitative research. Data from 243 working executives of e-tailing (e-commerce retail) in India has been collected to test the research model with the following variables- HPWS, organizational commitment, motivation, job satisfaction, quality of life (QOL), and individual job performance. Partial least squares-structure equation modelling has been applied for statistical analysis and testing of the proposed research model,
Findings- HPWS's direct effect on job satisfaction, employee motivation, organisational commitment, QOL and employee performance has been presented. Also, the effect of mediation of these variables in the HPWS on employee performance has been discussed.
Originality/Value: This research saves the researcher's most precious element, time, by selecting the best and pertinent information and presenting it in a crisp form so that it can be easily grasped. This paper is a sincere effort of the authors to explore the post-pandemic effects of HPWS in the e-tailing industry.
Keywords- High-performance work system (HPWS), quality of life, employee motivation, job satisfaction
It has been well established by many researchers that HPWS does positively impact organisational performance in varied contexts. The mechanisms through which HPWS impacts on job performance in varied sectors and varied contexts still come across as a black box which is worth exploring (Murphy et.al., 2018), especially in times of uncertainty, and challenging situations in the external environment, such as post pandemic, Great resignation and likewise, which led to lower levels of job satisfaction, employees feeling undervalued, lower level of connect to the organizational values (Zenger & Folkman, 2022). Some recent studies done in the current times have indicated that developing HPWS has been observed to impact organizations positively, e.g., through employee satisfaction and reducing employee turnovers (Claudia et al., 2024). Lockdown and curfew restrictions significantly influenced the country's economy. Lockdowns were imposed in India to control the spread of the disease while strengthening the limited supply and production of critical necessities and their delivery to retail outlets. A Few of the sectors worst affected by the pandemic were the manufacturing and service sectors (Daniel, 2021). E-tailing, a mix of retailing through e-commerce, is one of the services sectors, albeit in a different segment, called ‘online service providers’ (Inti, 2023). Supply chains, one of the core pillars of e-tailing were also disrupted due to the lockdown's atrociousness (PWC, 2020). Etailing is one of the important verticals in current times. In the 2021 financial year, the e-retail industry's market value has been reported as 38 billion U.S. dollars, with the projection to rise to 130 billion U.S. dollars by 2026 fiscal year (statista.com)
Many new players have made retailing in India a dynamic and fast-paced business, accounting for more than 10% of the country's GDP and 8% of employment (Dayarathna, 2018). The retail sector experienced a lack of consumer traffic in the post-pandemic period, resulting in the need to tailor the business more closely to customer needs regarding customer happiness and organizational success. Post-pandemic retail sector expansion and drastic changes to high-performance work systems (HPWS) have prompted a buzz of interest (UNWTO). During this time etailing, primarily based on services of offering products through ecommerce saw significant growth, though supply chain was disrupted in comparison to pre-pandemic times. HPWS is believed to be implemented in the service industry to deliver quality customer performance by creating a satisfied and committed workforce (Dayarathna, 2018).
Yet, understanding the conceptual framework of when and how to implement HPWS is important, which can support in yielding comparatively better employee performance (Alothmany et al., 2022) as HPWS may have positive as well as negative impacts on employee outcomes (Kaushik and Mukherjee, 2022). Additionally, different verticals may bring in employee variability in terms of perception, which can also differ in the impact of HPWS on job performance. e.g. one perspective suggests that a consensus on perceptions should be established and variability reduced, whereas the second perspective advocates for differentiated HR investments and allowing variability in employee perceptions to achieve the best possible firm outcomes (Tuteleers&Wessa, 2024)
Review of Literature and Hypothesis Formation
The literature on HRM emphasises the importance of people in achieving organizational success as a precious asset. According to research in the industrial and service industries, executives' frameworks that encourage individual responsibility and expertise achieve improved utility, quality, and cost effectiveness (Pfeffer, 1998). Momentum study also points towards HPWS as one of the crucial components that can assist an organization in achieving enhanced performance, (Guthrie et al., 2009; Dayarathna, 2012; Iddhagoda and Opatha, 2018). Till date, though the positive effect of HPWS on outcomes is well-documented and agreed upon, the process of how it effects still remains underexplored (Wong et al., 2019). There also has been a scarcity of empirical study on the usage of HPWS in the retail and service industries, both mainstream and critical.
HPWS- Background
Concept of HPWS is considered to have its origin in USA as a response to compete while facing tough competition from Japanese companies in 1970’s and 1980’s (Cappelli and Neumark , 2001; Boxall and Macky, 2007). Whilst Japanese companies performed high on quality and productivity by implementing ‘lean production’ based models like quality circles, JIT (Just in time technique), and group-based production (Womack, Jones and Roos 1990), US companies initiated HPWS that had its focus on employees. The need of HPWS was also felt by US companies because of advent of offshoring, and AMT (Advanced manufacturing Technology) (Dayarathna, 2018).
Components
Becker et al (1997) HPWS recommended that HPWS followed is unique for every organization, and ‘focus on providing individualised treatment to each firm's individual environment in order to obtain best outcomes’. Structural transformation can also bring in the variation expecially in developing countries (Fan et.al., 2023). Likewise, as the authors here discuss e-tailing, which is a part of services sectors, HPWS can be unique for different verticals under the sector .e.g. highlighting about manufacturing, Appelbaum and Batt (1994) identified six distinct types of manufacturing, and observed that there was variation amongst those in the quantum of worker freedom, concept of supporting human assets, and the amount by which the benefits of the framework are shared. HPWS is shaped by a variety of factors, including the social and internal cultures of the firm, the attitudes of employees and managers, and the practices of human resources. (Gittell et al. 2010). Some of the important practices of HPWS are considered as‘High commitment work system; high involvement work system; and high-performance human resource management’(Tiwari n.d.). These practices are presented in Figure 1.
Figure 1. shows some of the key elements of HPWS
Figure 1: Elements of HPWS
(Source: ISME https://www.isme.in/high-performance-work-system-a-new-system-for-efficient-organizations/)
Approach for the study
The following is the structure of this document. The theoretical framework that supports our study hypotheses follows this introduction. After that, we have presented our research strategy and the findings of our tests. After some thorough analysis of previous studies which was done in introduction part, we have investigated HPWS potential to improve work satisfaction, employee motivation, employee quality of life, and organizational commitment. We have focused on etailing industry for our research as during, post-pandemic and current times also in retail industry the manufacturing and supply of essential items had not been stopped completely. Rather integrated with ecommerce or electronic mode of business has expanded the reach.
Hypothesis formation
HPWS and Job Satisfaction
An emotional component to job contentment influences one's perception of different aspects of employment. One's job satisfaction is directly related to how much they care about their work and the many aspects of it. According to a review of call focus workers, HPWS is linked to work contentment. Suppose HPWS allows them to have a strong relationship with their leader and helps them balance fun and important activities. In that case, employees are more satisfied with their roles, says Vanden Berghe (2011). This aspect seems to be well identified by varied verticals. Even the ecommerce startups are believed to be adapting fun-filled culture to attract and retain young talent while believing that such culture may positively impact performance of the incumbents (Girotra and Kaushik, 2018). HPWS has been observed to show positive impact on job satisfaction in other service verticals e.g. healthcare vertical (Padamata and Vangapandu, 2024)
H 1. HPWS positively influences job satisfaction
HPWS and Employees Motivation
When it comes to accomplishing anything with a certain goal in mind, inspiration is referred to (Mitchel, 1982). Effort inspiration is the allocation of individual work to do task-related chores in a timely manner (Lundberg et al., 2009). A study indicated that an increasing number of hotels are concerned about employee motivation since attracting and retaining the finest employees is challenging (Putra et al., 2017).
H 2: HPWS positively influences employee motivation
HPWS and Quality of life (QOL)
QoL relates to a person's overall enjoyment of their life, and it includes issues about family satisfaction, career pleasure, and relaxation pleasure, among other things (Lin, 2013). A person's happiness in other aspects of life, such as their family, work, health, and free time, influences their general happiness (Peters, 2019).
H 3: HPWS positively influences employee QoL.
HPWS and Organizational commitment
Employees' desire and capacity to assist the organization achieve its goals and destinations while maintaining a stable work environment is what is meant by ‘‘representative duty.’‘(Kahn, 1990) According to Teh and Sun (2012), HPWS considerably impacts workers' perceptions and degrees of responsibility. Positive employee evaluations of authoritative legislation issues, remuneration plans, advancement, execution targets, and culture shape these mentalities. Besides, managers also emphasized organizational commitment of employees as an important criterion to evaluate their perception of impact of HPWS on organizational peformance (Agirre-Aramburu et al., 2023).
H 4. HPWS positively influences employee organizational commitment
HPWS and employee performance
Assembling and selecting the right team members, preparing and training them, executing the executives and providing them with remuneration and benefits are all critical for HPWS (Evans and Davis, 2005). The HPWS has been used in comparison studies to measure efficiency, worker execution, hierarchical citizenship behavior, authoritative accountability, and other features (Wright, 2007). Incorporating HR systems directly influences desired business outcomes, such as increased development, improved hierarchical execution, and a more cost-effective advantage (Donate, 2015). However, different times and ways of executing practices may have different employee outcomes (Alothmany et.al., 2023).Though most of the literature recommends the use of HPWS for enhanced performance, some studies found an adverse relationship between ‘High involvement practices’ and organizational performance.
H 5. HPWS positively influences employee performance
Job satisfaction and employee performance
Having a progressive outlook on one's work may lead to greater levels of innovation, dedication, as well as better results on the job (Vanden Berghe, 2011). But there are a number of conflicting views on the link between employee happiness and productivity at work. As stated by Vanden Berghe (2011), the relationship between job satisfaction and job performance is only marginally linked. Another study discovered a weak link between work satisfaction and job performance (Ghoreishi et. al, 2014).
H 6. Job satisfaction positively influences employee performance
Employee motivation and employee performance
The term ‘worker inspiration’ refers to a cycle in which organizations use motivational factors, such as awards, prizes, and augmentations, to motivate their employees to accomplish their goals. Motivation is important for workplace worker execution and organizations may use persuasive methods to urge employees to accomplish their best achievements (Klassen et al., 2012).
H 7: Employee motivation positively influences employee performance
Quality of Life and employee performance
Workplace security, good relationships with managers and colleagues, work that is tailored to the needs and abilities of the employees, and potential for development and self-improvement if necessary are all more essential, according to Jewell and Siegel (1998). It is used to describe the connections between individuals, jobs, global, and multidimensional linkages. Highlighting the impact of HPWS on employees mental well-being through Job Demands- Resources (JD-R)Theory, Kim et.al.(2023) established that depending on the practices followed, HPWS can impact employees' mental health either in a positive or a negative manner. Psychological empowerment linked practices show positive impact while work-role overload reflect negative impact.
H 8: Quality of Life positively influences employee performance
Organizational commitment and employee performance.
Having an effective performance management system has a direct impact on the success of a business. Improved performance is a direct result of increased staff engagement (Stanton, 2014). It is impossible for a representative to fail to meet his or her duties if they have been locked in. Locked-in representatives work together, feel compelled to perform, and are fuelled by a desire to fulfil goals (Stanton P, 2011).
H9. Employee organizational commitment positively influences employee performance.
Mediating Hypothesis
When it comes to HPWS related systems such as high-precision positioning systems (HPPS), everything from enlistment to selection to preparations to advancement is critical (Huselid, 1995). Till date, though positive effect of HPWS on outcomes is well-documented and agreed upon, the process of how it effects still remains underexplored (Wong et al., 2019; Kloutsiniotis and Mihail, 2020).
H 10: Employee Job satisfaction mediates positive relationship between HPWS and employee performance
In light of the work requests assets (Job Demands-Resources) worldview (Ahola et al., 2008) an elite exhibition work framework will encourage workers to perform magnificently by focusing on the accessibility of mental and social assets. The JD-R model divides work requests and occupation assets into two distinct zones (Schaufeli and Taris, 2013). There are two types of work: requests and assets. Requests are things that need to be done physically or mentally, while assets are things that help you achieve your goals while limiting the damage they cause you physically or mentally.
H 11: Employee motivation mediates positive relationship between HPWS and employee performance
Job satisfaction and quality of life are two of the key indicators of employee well-being that are helpful to organizational outcomes. But some of the researches have also found HPWS to be negatively effecting employees well-being, and healthy life (Guerci et al., 2019). While HPWS have often been linked to positive results, they also have been found to yield negative effects on employees e.g. job dissatisfaction, and increased levels of anxiety (Wood et al., 2012; Topcic et al., 2016).
H 12: Quality of life mediates positive relationship between HPWS and employee performance
Commitment serves as an interface between HPWS and workers’ outcomes (Cooke et al., 2016). HR exercises are aimed at creating, propelling, preserving, enhancing the usefulness and creativity of the workforce, and corporate citizenship conduct, which in return advance performance and improvement (Jenkins and Delbridge, 2013).
H 13: Employee organizational commitment mediates positive relationship between HPWS and employee performance
RESEARCH METHODOLOGY
Based on primary and secondary research methods such as journal articles, blogs and the Internet, this report is exploratory in character. The questionnaire is the primary method of collecting data in this quantitative research. Primary data from respondents is collected to test the research model with the following variables- HPWS, organizational commitment, motivation, job satisfaction, QOL, and individual job performance. For statistical analysis and to test the proposed research model, partial least squares-structure equation modelling is applied. The study explores the cause and effect relationship between the identified variables directly as well as through the mediating variables.
Retail services sector has been chosen for this study because of its important contributions to GDP, employment as well as the economy. Besides, the study takes the employee-centric approach that has been used by many researchers to study the impact from employees perspective (Padamata and Vangapandu, 2024). Literature on strategic HR lays emphasis on studying employees response to HR practices (Yim et.al., 2024).
Data Collection and Sampling Procedure
Data was gathered from ten retail organizations (convenient sampling), located in North India. Data was collected during post-pandemic period. Time period for data collection was from February 2021 to May 2021. Before the questionnaire design was finalised, the research team contacted the HR managers of the participating retail organizations primarily to understand issues. Once these questions have been answered, it was time to move on to defining the study objectives as well as determining which organizations will participate. Pilot test was done with the mix of employees’ hierarchal levels in Delhi region for the quicker response and follow up. For the main study, the questionnaire was then randomly shared with retail sector employees without asking their designation through referrals, HR Managers, contacts through social media, and also by contacting some retail stores directly. The instrument was shared through WhatsApp with the individuals or emailed based on the target, reachability as well as respondents’ ease of response submission. The region targeted was North India that primarily targeted Delhi region, some parts of Punjab, Haryana, Uttarakhand, and Uttar Pradesh. Overall, 243 of the 300 questionnaires were delivered, with a response rate of 81%.
Demographics
There were 146 men, accounting for 60.0 percent of the target population, while females accounted for 40.0 percent. Only 4.7 percent were beyond the age of 50, 31.5 percent between the ages of 21 and 30, 32.7 percent between the ages of 31 and 40, 25.9% between 40-50, and 5.2 percent under the age of 20. Postgraduates accounted for 28%, while those with a Bachelor's degree were 39%, a certificate or diploma from a community college accounted for 19%, and those with additional credentials accounted for 14%. Associates, operational managers, senior executives and heads of departments comprised 38.7%, 36.5%, 15.5%, and 9.3% respectively. 39 (16%) had less than two years of experience, 85 (35%) had two to five years of experience, 64 (26.3%) had six to ten years of experience, and 40 (16.5%) had eleven to fifteen years of experience, while 15 (6.2%) had more than 15 years’ experience.
Measures
Responses for all measures were collected on a five-point Likert scale (scale from ‘1 = entirely disagree’ to ‘5 = totally agree’). The HPWS is the independent variable, work satisfaction, employee motivation, organization commitment, and quality of life are the mediating factors, and employee performance is the dependent. Also performed was ‘Exploratory Factor Analysis (EFA)’ (maximum likelihood extraction approach; Promax rotation; ‘cut-off value = 0.50’).
‘High performance work systems (HPWS)’
HR practices and work structures followed in retail organizations of North India based on senior HR personnel interviews were considered. Since the study intended to measure employees’ perceptions in retail organizations surveyed (Pass, 2017), these form the basis of HPWS, according to a previous research. HPWS was measured on two level concept. There were a total of 22 items utilised, each of which had two sub-scales (i.e., HRM practices and work structures). We utilised the Panagiotis et al. scales for ‘HRM practices’ (nine out of eleven items, α = 0.920) and ‘work structures’ (nine out of eleven items, α = 0.939). (2020). The HPWS has a Cronbach's alpha of 0.937.
‘Job Satisfaction’
To measure ‘Job Satisfaction’, Zopiatis et al. employed a four-item scale that included items that had been used in previous studies (2014). As a few examples, I'm happy with my job, and enjoy working at this company. JS had a Cronbach's alpha of 0.852..
‘Employee Motivation’
Chiang and Jang's ‘Employee Motivation’ was evaluated by using six commonly used items to test the construct of motivation (2008). ‘I am motivated in my work’ and ‘my work is intriguing’ are two examples. Its Cronbach's alpha was 0.894, according to the information.
‘Quality of Life’
A five-item ‘Quality of Life’ scale was devised by modifying questions from research by Kim et al. (2014) to assess the quality of life. ‘I am pleased with my life’ and ‘I am typically content with my life’ were two examples of the things. Cronbach's alpha for EM is 0.812.
‘Organization Commitment’
Meyer et al. devised a six-item scale to measure ‘Organization Commitment’ (2002). There were a few examples: ‘I feel a strong feeling of belonging’ and ‘This institution deserves my commitment’. Cronbach's alpha for EM is 0.849.
‘Employee Performance’
Janssen and Van Yperen used a six-item performance scale to measure ‘Employee Performance’ (2004). As a consequence, I'm capable of doing a wide range of duties. Cronbach's alpha was 0.870 in terms of employee performance.
Direction of dependent, independent and mediating variables has been presented in the conceptual model in Figure 2. The conceptual model has been bifurcated into two as Figure 2a, and Figure 2b, which present direction between independent, and dependent variables; andmediation between independent, and dependent variable respectively.
Figure2a, and Figure 2b present the conceptual model.
Conceptual Model:
Figure 2a: Conceptual Model of the study presenting the direction between independent, and dependent variables
Figure 2b: Conceptual Model of the study presenting the mediation between independent, and dependent variable
Control variables
Both ‘gender’ (male or female) as well as the level of education (post-secondary or bachelor) were taken into account. There was no control for the employees' job status because the vast majority (89 percent) worked full-time. It was also not included as a control variable because ten retailers participated in the study. All retail organizations are of the similar size and utilize similar HR policies.
Analysis approach, “common method bias” and evaluation of “Model Fit”:
“Confirmatory Factor Analysis (CFA)” was carried out in Smart PLS 3 following the EFA. There were good “model fit indices” in the 7-factor model (“x2 /df = 2.991”; “RMSEA = 0.060”; “CFI = 0.926”; “TLI = 0.911”; “SRMR = 0.048”). This study’s framework minimised the risk of “Common Method Variance (CMV)” because of “cross-sectional nature” of the methodology. To begin, the “procedural remedies” of Podsakoff et al. (2003) were followed during the questionnaire construction. The complete collinearity test (VIF < 3.3), and a series of “confirmatory factor analyses (CFAs)” were also done by following earlier research (e.g., Kock, N., 2015). Harman’s single factor was used to further manage CMV as well. “Method bias” was shown to be non-existent in each of the statistical test. It seems unlikely that CMV had an effect on our findings.
Method of analysis
Partial Least Squares Structural Equation Modelling (PLS-SEM or “Smart PLS 3”) was employed for the purpose of this study via “Smart PLS 3” (Ringle et. al., 2014), which has been more prominent in behavioral research over the past few years (Aggarwal et al., 2007). Using PLS-capacity SEMs, hierarchical component models, containing both formative and reflecting features, are required for the current investigation. HPWS were classified as “reflective-formative” higher-order components using the repetitive indicators technique with (formative) measurement mode B (Becker et al., 2012) and the “two-step approach” (Hair et al., 2014, pp. 230–233).
Assessment of the measurement model
As previously stated, the conceptual paradigm includes both reflective and formative signs. According to Hair et al. (2014, pp. 95-96) lower-order constructs, validity, and reliability were assessed using “Average Variance Extracted”, “individual indicator reliability”, and “composite reliability” (CR and AVE). AVE and CR scores exceeded the 0.50 and 0.70 thresholds, respectively, for all factor loadings. It was found that consistency had been established as a result. Values, and factor loadings have been presented in Table 1.
Table 1 presents the factor loadings and results.
Table 1. First-order measurement model: reliability and convergent validity
|
HPWS (α = 0.944) |
||||||
|
Dimension |
Item |
Loading |
Mean |
SDs |
CR |
AVE |
|
HRM practices Panagiotis et al. (2020) |
Considerable importance is placed on the staffing process post pandemic |
0.804 |
3.8 |
1.116 |
0.934 |
0.61 |
|
Extensive training programs are provided for individuals in customer contact or front-line jobs post pandemic |
0.788 |
3.75 |
1.208 |
|||
|
Formal training programs are offered to employees in order to increase their promotability in this organization |
0.838 |
3.87 |
1.124 |
|||
|
Job security is assured to me in this job |
0.755 |
3.63 |
1.224 |
|||
|
|
Performance is more often measured with objective quantifiable results |
0.755 |
3.80 |
1.172 |
||
|
I, in this job are often asked by my supervisor to participate in decisions |
0.787 |
3.84 |
1.182 |
|||
|
The job description for this job contains all of the duties performed by me |
0.757 |
3.79 |
1.175 |
|||
|
I receive rewards post pandemic in this job |
0.745 |
3.70 |
1.261 |
|||
|
My Long-term potential is emphasized post pandemic |
0.797 |
3.80 |
1.210 |
|||
|
Cronbach’s Alpha |
0.92 |
|||||
|
Work Structures |
Healthy eating facilities are provided by the organization |
0.841 |
3.79 |
1.209 |
0.948 |
0.672 |
|
|
Concern is shown for my health and safety at work place |
0.844 |
3.74 |
1.233 |
||
|
|
The overall infrastructure provided by the organization is satisfying in terms of hygiene. |
0.808 |
3.71 |
1.253 |
||
|
|
I am allowed to make flexible choices about the working conditions. |
0.827 |
3.75 |
1.248 |
||
|
Organization shifts to a hybrid workspace model post-pandemic |
0.833 |
3.75 |
1.170 |
|||
|
I am communicated effectively and in a timely manner |
0.801 |
3.65 |
1.181 |
|||
|
My contribution is noted and respected by the organization |
0.853 |
3.73 |
1.262 |
|||
|
I am providing better access in terms of medical benefits, financial plans, wealth management, and insurance schemes |
0.809 |
3.58 |
1.184 |
|||
|
If I feel underpaid, I can discuss my feelings with my supervisor |
0.758 |
3.70 |
1.215 |
|||
|
Cronbach’s Alpha |
0.939 |
|||||
|
Job Satisfaction Zopiatis et al. (2014) |
The feeling of accomplishment I get from the job |
0.774 |
3.19 |
1.018 |
0.901 |
0.695 |
|
All in all, I’m satisfied with my job |
0.895 |
3.35 |
1.040 |
|||
|
|
In general, I like working here |
0.886 |
3.34 |
1.069 |
||
|
The freedom to use my own judgment |
0.771 |
3.31 |
1.147 |
|||
|
Cronbach’s Alpha |
0.852 |
|||||
|
Employee Motivation Chiang and Jang (2008) |
My work is interesting |
0.837 |
3.74 |
.994 |
0.919 |
0.654 |
|
|
My job inspires me |
0.847 |
3.85 |
.976 |
||
|
|
At my work, I feel bursting with energy |
0.823 |
3.64 |
.954 |
||
|
I am enthusiastic about my job |
0.8 |
3.49 |
1.062 |
|||
|
A pleasant work environment motivates me |
0.776 |
3.83 |
.942 |
|||
|
In my work, I am motivated |
0.767 |
3.63 |
.907 |
|||
|
Cronbach’s Alpha |
0.894 |
|||||
|
Quality of Life Swamy et al. (2015) |
My organization work environment is good and highly motivating. |
0.785 |
3.99 |
.798 |
0.869 |
0.571 |
|
|
Working conditions are good in my company |
0.771 |
3.95 |
.829 |
||
|
|
There is cooperation among all the departments for achieving the goals |
0.78 |
4.04 |
.754 |
||
|
|
I am proud to be working for my present Company |
0.752 |
4.00 |
.862 |
||
|
I am not discriminated on my job because of my Gender |
0.687 |
4.07 |
.892 |
|||
|
Cronbach’s Alpha |
0.812 |
|||||
|
Organization Commitment Mowday et al. (1979) |
I feel a strong sense of belonging to this organization |
0.709 |
3.37 |
1.200 |
0.888 |
0.57 |
|
|
This organization deserves my loyalty |
0.791 |
3.64 |
.867 |
||
|
|
I talk up this organization to my friends as a great organization to work for |
0.783 |
3.33 |
.957 |
||
|
|
I really care about the fate of this organization |
0.747 |
3.60 |
1.052 |
||
|
I find that my values and the organization’s values are very similar |
0.774 |
3.70 |
.939 |
|||
|
Deciding to work for this organization was a good decision |
0.724 |
3.40 |
.967 |
|||
|
Cronbach’s Alpha |
0.849 |
|||||
|
Employee Performance Pradhan & Jena (2017) |
I use to maintain high standard of work. |
0.824 |
3.35 |
1.082 |
0.902 |
0.608 |
|
|
I know I can handle multiple assignments for achieving organizational goals |
0.649 |
2.40 |
1.172 |
||
|
|
I can handle effectively my work team in the face of change |
0.809 |
2.94 |
1.076 |
||
|
|
I use to cope well with organizational changes from time to time. |
0.846 |
3.37 |
1.065 |
||
|
|
I derive lot of satisfaction nurturing others in organization |
0.806 |
3.28 |
1.184 |
||
|
|
I love to handle extra responsibilities |
0.726 |
3.60 |
.975 |
||
|
|
Cronbach’s Alpha |
0.87 |
*SD= Standard Deviation, CR= Composite Reliability, AVE= Average Variance Extracted
For discriminant validity, the “Fornell-Lacker” and the ‘Heterotrait-Monotrait ratio” (HTMT < 0.85) were used (Henseler et al., 2015). Discriminant validity was attained since all of the HTMT values were below 0.85.
We clustered indicators from each dimension to reflect the second-order construct using the two-step technique (i.e., HPWS). As a result, we used latent variables (dimensions) as second-order construct markers (Wright et al., 2012). The first stage was to follow Petter et al. (2007)'s advice. ‘‘Variance Inflation Factors (VIF)’ ‘were then used to assess all ‘‘formative factors” for ‘‘multicollinearity’‘ (see Cenfetelli and Bassellier, 2009). VIF loadings were all below the 3.33 threshold. In this way, it is clear that build dependability was attained. Fornell and Larcker and HTMT conditions were met for the second-order model's discriminant validity (HTMT < 0.85).
Table 2 shows the results for Second-order measurement model
Table 2. Second-order measurement model
|
HPWS Dimensions |
Loading |
Weight |
VIF |
|
HRM practices |
0.841 |
0.465*** |
1.482 |
|
Work Structures |
0.924 |
0.659*** |
1.482 |
Note: *** p-value < 0.001
RESULTS
Table 3 presents how the research variables are related to each other in terms of mean, standard deviation, reliability, and bivariate correlations. The bootstrapping approach was used in the evaluation of the structural model (Fig. 2). (5000 randomly drawn samples).
Table 3 presents Means, SDs and correlations
Table 3. Means, SDs and correlations (Cronbach’s α is in parentheses):
|
Mean |
SD |
1 |
2 |
3 |
4 |
5 |
6 |
|
|
1. HPWS |
3.74 |
0.86 |
(0.944) |
|||||
|
2. Job Satisfaction |
3.30 |
0.89 |
.344** |
(0.852) |
||||
|
3. Employee Motivation |
3.70 |
0.79 |
.290** |
.551** |
(0.894) |
|||
|
4. Quality of Life |
4.01 |
0.62 |
.355** |
.282** |
.350** |
(0.812) |
||
|
5. Organization Commitment |
3.51 |
0.75 |
.343** |
.555** |
.640** |
.311** |
(0.849) |
|
|
6. Employee Performance |
3.16 |
0.85 |
.287** |
.648** |
.636** |
.357** |
.678** |
(0.87) |
Note: N=243. SD, standard deviation. *Indicates significant paths: *p < 0.05, **p < 0.01, ***p < 0.001, ns = not significant.
Statistical significance values for path coefficients are shown in Table 4. The findings of Table 4 reveal a positive correlation between employees’ views of High-Performance Work Systems (HPWS) and other variables- job satisfaction (β=0.363, p<0.001), motivation (β=0.312, p<0.001), quality of life (β=0.363, p<0.001), organizational commitment (β=0.370, p<0.001) and employee performance (β=0.365, p<0.001). These positive correlations thereby support hypothesis 1,2,3,4 and 5 which intended to investigate influence of HPWS on job satisfaction, employee motivation, quality of life, organizational commitment, and employee performance respectively. Both job satisfaction (β=0.307, p<0.001) and Employee motivation (β=0.222, p<0.001) were shown to be significant predictors of Employee Performance, as was Quality of life (β=0.089, p<0.01), and Organization Commitment (β=0.365, p<0.001). That’s why these results support hypothesis 6, 7, 8 and 9 much more firmly. Hence, the results show supporting positive influence of job satisfaction, employee motivation, quality of life, and organizational commitment on employee performance. Finally, hypothesis 10, 11, 12 and 13 present that Job satisfaction, Employee Motivation, Quality of Life, and Organizational Commitment would moderate the association between HPWS and Employee Performance, respectively. Based on the mediation process, the “indirect effects” between the “independent” (i.e.,HPWS) and “dependent” (i.e., Employee Performance) variables should be statistically significant (Zhao et al.,2010,). Through the bootstrap analysis (5000 samples) option in Smart PLS, the “product-of-coefficient (αβ)” technique (MacKinnon et al., 2002) was utilized to calculate these indirect correlations. According to Table 4, the indirect effects of HPWS on employee performance via job satisfaction (αβ=0.112, p<0.001), employee motivation (αβ=0.069,p<0.001), quality of life(β=0.032, p<0.001), and organizational commitment(β=0.135,p<0.001) were statistically significant. There is strong evidence to back up hypothesis 10, 11, 12 and 13.
Table 4 presents Summary of Path Coefficients and Significance levels
Table 4. Summary of Path Coefficients and Significance levels
|
Direct Hypotheses and corresponding paths |
Path Coefficient |
T-Statistics |
Hypothesis Support |
|
HPWS →Job Satisfaction |
0.364 |
6.32 *** |
H1 supported |
|
HPWS → Employee Motivation |
0.312 |
04.81*** |
H2 supported |
|
HPWS → Quality of Life |
0.363 |
4.539*** |
H3 supported |
|
HPWS →Organization Commitment |
0.370 |
5.939*** |
H4 supported |
|
HPWS → Employee Performance |
0.325 |
5.355*** |
H5 supported |
|
Job Satisfaction → Employee Performance |
0.307 |
5.02*** |
H6 supported |
|
Employee Motivation →Employee Performance |
0.222 |
3.791*** |
H7 supported |
|
Quality of Life → Employee Performance |
0.089 |
2.382** |
H8 supported |
|
Organization Commitment →Employee Performance |
0.365 |
6.647*** |
H9 supported |
|
|
|
|
|
|
Mediation hypotheses and corresponding paths |
|
|
|
|
HPWS →Job Satisfaction → Employee Performance |
0.112 |
3.96*** |
H10 supported Partial Mediation |
|
HPWS → Employee Motivation→ Employee Performance |
0.069
|
2.937***
|
H11 supported Partial Mediation |
|
HPWS → Quality of Life→ Employee Performance |
0.032
|
2.06**
|
H12 supported Partial Mediation |
|
HPWS →Organization Commitment→ Employee Performance |
0.135
|
4.199***
|
H13 supported Partial Mediation |
*Indicates significant paths: *p < 0.05, **p < 0.01, ***p < 0.001, ns = not significant.
While Table 4 presents the summary of Path Coefficients, Significance levels as well as the hypothesis results in terms of acceptance, Ta gives a pictorial presentation of the significant paths as PLS model.
Figure 3 presents the PLS model of the study indicating the significant paths
Figure 3:.The “Two-Step Approach” PLS Model. *Indicates significant paths: *p < 0.05. **p < 0.01. ***p < 0.001. ns = not significant.
CONCLUSION
Employee performance is one of the key factors in determining the success of the firms (Tracey, 2014), hence it is vital for the organizations to also focus on HPWS besides other factors that impact employee performance (Noe et al., 2009). It becomes equally important for the retail industry, which involves a high level of interpersonal communication (ILO), as such practices encourage trust and cooperation among employees, which enables the provision of a good customer experience (Godard, 2004). Retail vertical accounts for 10% of the country's GDP and 8% of employment (Dayarathna, 2018).
HPWS practices have been investigated under two categories in terms of HRM practices, and work structures. The results show that practices of considering staffing process as an important process, providing adequate training programs not only for good customer experience but also keeping employees’ growth in mind, while focussing on long term potential of employees are considerably followed by the retail organizations surveyed. Dayarathna (2018) presented that HPWS practices support in enhancing employees’ competencies. The study also indicates that these organizations encourage supervisors involve their subordinates in decision making process. Appelbaum et al (2000) suggest that high-performance workplace promotes subordinates in decision making process that affects their jobs as well as the company. The job description is carefully drafted to encase the duties to be performed by the employees, which probably supports in performance measurement with the help of objective quantifiable results, and in turn the employee performance, our target dependent variable. HPWS practices have been shown to be supporting work force productivity in the existing literature as well (Datta et al. 2005). In addition, organizations appear to be focussing on, and considerate about providing good work structure such as hygiene, healthy eating facilities, medical benefits, financial and insurance schemes (Goel, Garg, Baliyan and Girotra, 2022) to their employees.
Retail verticals are hit hardest during the lockdowns or adverse situations, but are also believed to bounce back rapidly (Daniel, 2021). Retail workers are often considered as one of their significant assets that support in organizational success (Chi and Gursoy, 2009), hence the retail organizations that follow considerable HPWS practices are more likely to witness good employee performance which may support in organization performance (Iddhagoda and Opatha, 2018; Bowen, 2004).
IMPLICATIONS
Managerial Implications
This research indicates supporting performance outcomes because of HPWS implementation even during challenging times such as pandemic. Insights from our study are relevant to etailing organizations, because it shows that HPWS implementation has a positive impact on employee performance and job satisfaction, employee motivation, organization commitment, quality of life by formulating and applying the hypothesis related to mediation effect on overall employee performance in an organization.
Economic Implications
Employees’ performance outcome positively impacts organization’s overall performance (Guthrie et al., 2009; Iddhagoda and Opatha, 2018), and is one of the key financial indicators of effectiveness of human resource activities practiced by organizations (Kim et al., 2021). Hence, these practices may benefit organizations on economic terms as well. Quantum of the practices investigated for this study may help organizations analyze their investments.
Societal Implications
Though HPWS is often implemented for business outcomes, it may prove beneficial for the society as well. HPWS has positive impact on job satisfaction, which has been shown to have positive effects at individual, familiar, and societal levels. For example, it has been shown to have spillover effects on marital satisfaction, among others (e.g. Ilies et al., 2009). Implementation of HPWS may enhance job satisfaction, which may make this vertical attractive and help encourage youngsters to enroll in relevant study programs, hence providing employment avenues.
Limitations and Directions for Future Research
Though research has been carried out in the best possible manner to fulfil the study's objectives, a few things could have been improved. The study was limited to ten retail organizations. Studies can be conducted on higher numbers and varied sizes of retail organizations to understand the quantum of HPWS practices followed as well as the impact.
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