The Impact of HRM Practices on Job Satisfaction in the Unicorn Startups of India: Exploring the Mediating Effect of Employee Engagement
Chanchal Dey
Research Scholar,
Department of Business Administration,
Vidyasagar University,
Midnapore, WB, India
Dr. Debasish Biswas
Associate Professor
Department of Business Administration,
Vidyasagar University,
Midnapore, WB, India,
Abstract
This study explores the impact of Human Resource Management (HRM) practices on job satisfaction among employees in Indian unicorn startups. It also examines the role of employee engagement as a mediator between HRM practices and job satisfaction. Additionally, the study investigates the moderating effects of age and gender on the relationship between HRM practices and job satisfaction. The data is collected through structured questionnaires from 390 employees working in unicorn startups in Bengaluru, Delhi-NCR, and Mumbai and is analyzed using the Structural Equation Modeling technique. The findings indicate that HRM practices positively influence job satisfaction, and employee engagement acts as a significant mediator between the two. However, the moderating effects of age and gender are insignificant. The study emphasizes the importance of effective HRM practices and employee engagement in promoting job satisfaction in Indian unicorn startups. It concludes that startups should prioritize implementing effective HRM practices to ensure employee satisfaction and engagement. This research contributes to the understanding of the relationship between HRM practices, employee engagement, and job satisfaction, particularly in the context of India's unicorn startups.
Keywords: HRM practices, Employee engagement, Job satisfaction, India, Unicorns, Startups
Introduction
Under Prime Minister Narendra Modi, India started the 'Startup India' program on January 16, 2016, to promote a startup culture nationwide (Garg & Gupta, 2021). India's startups, with government support, are driving economic growth. Startups are crucial to India's $5 trillion economy goal by 2024-2025. The country's startup ecosystem is third after the United States and China (Ravishankar, 2022). Lee (2013) defines a "unicorn startup" as a company valued at over $1 billion. Unicorn startups in India are worth $340.79 billion and operate in many sectors. Indian unicorns are developing new technologies and creating jobs. According to YourStory Research, India's "unicorn" firms created 2.84 million jobs directly and indirectly (Bhuva, 2022). India has experienced a remarkable surge in the creation of unicorn startups. In 2021, India achieved a record-breaking milestone by adding 44 new unicorns, the highest number ever recorded. As of May 2023, India already had 108 unicorns. Bengaluru is the primary headquarters for most Indian unicorns, while the Delhi NCR region and Mumbai also have a significant presence. However, startups in India are known to have human resource management (HRM) issues, particularly in attracting and retaining employees. There is a significant reluctance among professionals to join startups, leading to critical staff retention issues. Furthermore, poor job satisfaction among employees has resulted in substantial attrition rates (Mukul & Saini, 2021). A significant number of research studies have thrown light on the impact of HRM practices on the attitudes and levels of performance of employees at organizations (Katou & Budhwar, 2007; Ileana Petrescu & Simmons, 2008). However, in the case of Indian unicorn companies, not many studies have been done in this area. This study fills in the gaps in current research about the role of HRM practices and job satisfaction. The study also examined how employee engagement, age, and gender change the relationship between HRM practices and job satisfaction.
Review of literature and hypothesis development
The Social Exchange Theory
The social exchange theory says that relationships at work are built on trust and commitment. Schaufeli et al. (2006) found that this happens between the people involved whenever there is a case of reciprocity. The pay, recognition, and other perks that employees get from their company, among other things, directly affect how engaged those employees are in their work (Saks, 2006). On the other hand, if there are not enough resources, workers will feel more stressed and less interested in their jobs (Schaufeli et al., 2006). Alfes et al. (2013 also found that employees will be better citizens and less likely to quit their jobs if the company gives them enough support and their supervisor cares about their well-being.
HRM practices, employee engagement and job satisfaction
HRM practices are the plans, procedures, and methods used to find, train, hire, evaluate, monitor, and keep the right mix of employees to help the organization reach its goals (Appelbaum & Gandell, 2003). HRM practices ensure that quality human resources are used to meet organizational goals. HRM practices and job satisfaction are closely related. Recruitment, placement, empowerment, training, compensation, promotion systems, performance evaluation, and flexibility are the HR practices most strongly associated with job satisfaction (Tessema & Soeters, 2006). HRM practices enhance job satisfaction, which promotes firm efficiency (Appelbaum & Gandell, 2003). Employee engagement is greatly impacted by HRM practices like compensation, recruitment, rewards, and job design (Saad et al., 2021). Engaged workers tend to be more invested in their accomplishments and job satisfaction. This is why organizations always prefer their employees to be engaged and satisfied (Orgambídez-Ramos et al., 2014). There is evidence that employee engagement improves health through improved job satisfaction (Sonnentag, 2003). Job satisfaction improves with employee participation programs. Supervisors who hold frequent staff meetings to gather employee feedback encourage employee satisfaction. (Ileana Petrescu & Simmons, 2008). The authors propose the following hypotheses:
H1: HRM practices are positively associated with job satisfaction.
H2: HRM practices are positively associated with employee engagement.
H3: Employee engagement is positively associated with job satisfaction.
Mediating effect of employee engagement
According to social exchange theory, HRM practices lead to employee engagement and loyalty. Employees build, maintain, and end relationships based on their perception of the costs and benefits (Ensher et al., 2001). The gap between ideal and actual HR practices should be minimum to improve employee engagement. The leadership should carefully implement HRM practices to meet the needs of different employees to encourage employee engagement (Jose, 2012). Several studies have examined job satisfaction using employee engagement as a mediator. HRM practices increase employee engagement because employees perceive fair treatment, support, and concern from their employers (Pradhan et al., 2019; Rai & Maheshwari, 2021). The authors puts forward the following hypothesis:
H4: Employee engagement has a mediating effect on the association between HRM practices and job satisfaction.
Moderating effect of employee age and gender
Age is found to be an important attribute in job satisfaction of employees (Saner & Eyüpoğlu, 2012). The older employees are often more satisfied than their younger counterparts in identical roles (Azeem, 2010). However, Scott et al. (2005) opined that there is no correlation between age and job satisfaction. Yousaf et al. (2022) found that females are more concerned about HRM practices compared to their male counterparts. Female employees are more satisfied in the workplace than male employees (Long, 2005). However, Akbari et al. (2020) found that female employees have poorer job satisfaction than their male counterparts. Researchers have used both age and gender as a moderator to analyze job satisfaction in their respective studies (Drabe et al., 2015; Tanwar & Prasad, 2016). In this connection, the authors propose the following hypotheses.
H5: Age moderates the relation between HRM practices and job satisfaction.
H6: Gender moderates the relation between HRM practices and job satisfaction.
Figure 1. Hypothesized research framework
Source: Compiled by authors.
Research methods
Sample and data collection
Since more than 70% of unicorn startups are in Bengaluru, Delhi-NCR, and Mumbai, some of these startups' employees were considered. We used Cochran's formula, as shown in Equation 1, to figure out how many samples we needed for our study, considering a 95% confidence level (z) which is 1.96, maximum probability of the variation taken to be 50% (p) and a 5% margin of error (e) (Cochran, 1977).
n0 = z2 p(1-p)/e2 (1)
Hence, the sample size calculated is n0 = 385. The structured questionnaires were given to 450 employees through the snowball sampling method. Only 390 of the 410 responses received were complete in every way. Most employees who answered the sample questions were men (74.9%), and more than half (60%) were under 30.
Measures
We have used the established scales to determine how to measure the different parts of the study, which will be put into the following categories. The nine items from Conway's (2004) measuring scale were used to evaluate HRM practices. Employee Engagement was assessed with the help of the 7-item measurement scale developed by Byrne et al. (2016). Job Satisfaction was measured by the 5-items from the measuring scale created by Baloyi et al. (2014). A seven-point Likert scale was used to evaluate all of the measures. The scale went from "very strongly disagree" (1) to "very strongly agree" (7). Age and Gender were measured with the help of a binary scale of "0" and "1".
Analysis
With the help of SmartPLS 4, the PLS-SEM method (partial least squares structural equation modeling) is used to analyze and judge the data. The method has been used in a number of recent studies because it has been shown to give accurate and thorough outcomes (Ringle et al., 2020; Memon et al., 2021).The measurement model was analyzed through the determination of internal consistency reliability, convergent validity (CV), and discriminant validity (DV), followed by the structural model with the determination of explanatory power (R2) and predictive relevance (Q2) (Hair et al., 2014). After that, path coefficients were evaluated for hypothesis testing.
Findings and Discussion
Assessment of measurement model
The validity and reliability of the model's constructs are considered in the evaluation of a measurement model. Figure 2 displays a graphical representation of the research model.
Figure 2. Graphical representation of research model
Source: Compiled by authors.
With the help of the SRMR (Standardized root mean residual) value, the Goodness of the model fit was estimated. This value helps determine if the model fits the observations in the study. The saturated and estimated models came up with the same SRMR value of 0.07. The model fits well if the SRMR < 0.08 (Hu & Bentler, 1999). Cronbach's alpha (α) was used to look at the reliability of the construct and the consistency between the variables (see Table I). All of the reliability scores are higher than 0.9 for all constructs, including HRM Practices, Employee Engagement, and Job Satisfaction. The reliability scores in between 0.70 to 0.95 are considered satisfactory (Hair et al., 2014). In Table I, the Average variance extracted (AVE) values show the convergent validity of the constructs. The AVE scores for HRM Practices, Employee Engagement, and Job Satisfaction are higher than 0.5. This shows that the constructs used are sufficiently one-dimensional (Fornell & Larcker, 1981).
Table I. Construct reliability and convergent validity
|
Construct |
α |
AVE |
|
HRM Practices |
0.94 |
0.67 |
|
Employee Engagement |
0.91 |
0.65 |
|
Job Satisfaction |
0.90 |
0.72 |
Note (s): α: Cronbach's alpha, AVE: Average variance extracted; Source: Compiled by authors.
The degree to which a component differs from other parts of the model is called its discriminant validity. Henseler et al. (2015) assert that the Heterotrait-Monotrait (HTMT) Ratio of Correlations is better than other ways to measure the discriminant validity. In Table II, the HTMT values of the constructs are shown. All HTMT values are below 0.8, indicating strong construct-indicator relationships. Constructs with distinct properties must have HTMT values below 0.85, while those with similar properties must exceed 0.90 (Henseler et al., 2015).
Table II. Discriminant validity using Heterotrait-Monotrait Ratio of correlations (HTMT)
|
Construct |
HRM Practices |
Employee Engagement |
|
Employee Engagement |
0.72 |
|
|
Job Satisfaction |
0.65 |
0.65 |
Source: Compiled by authors.
Assessment of structural model
According to Hair et al. (2014), to assess structural models, the bootstrapping approach is applied to ascertain the importance of the structural path coefficients. R2 statistics indicate the variance of the endogenous constructs explained by the model. The R2 values obtained are 0.45 and 0.44 for employee engagement and job satisfaction, respectively. The R2 values must be either equal to or higher than 0.10 to explain the variance of the endogenous constructs (Hair et al., 2021). While determining the predictive relevance, the Q2 values for employee engagement and job satisfaction are found to be 0.42 and 0.33, respectively. As the Q2 values are greater than 0, values are reconstructed well, and predictive relevance exists among these constructs. According to Castro and Roldán (2013), a value of Q2 > 0 indicates the presence of predictive relevance in the model. In contrast, a value of Q2 < 0 indicates the absence of predictive relevance in the model. In order to test the coefficients of hypotheses, bootstrapping with 1,000 simulations was applied (Hair et al., 2014). The path coefficients are shown in Table III. Path coefficients (β) show the direct effect of an independent variable on a dependent variable.
Table III. Direct effect of path coefficients
|
Hypotheses |
Effect |
β |
Decision |
|
H1 |
HRM Practices → Job Satisfaction |
0.37* |
Accepted |
|
H2 |
HRM Practices → Employee Engagement |
0.67* |
Accepted |
|
H3 |
Employee Engagement → Job Satisfaction |
0.35* |
Accepted |
Note (s): β: Path coefficient, p: Probability value, *p < 0.05; Source: Compiled by authors.
From Table III, all the Path coefficients (β) values were found to be positive, and the p-value of all the effects was less than 0.05, which meant all the effects were positive and statistically significant. Hence, all the hypotheses, i.e., H1, H2, and H3, are accepted.
Assessment of the mediation effect
The path coefficients regarding the mediation effect results are shown in Table IV. The path coefficients (ꞵ) value is found to be positive, and the p-value of this effect is less than 0.05, making the effect statistically significant. Thus, it is found that employee engagement mediates the relation between HRM practices and job satisfaction. Therefore, hypothesis H4 is also accepted.
Table IV. Mediation effect path coefficient
|
Hypothesis |
Effect |
β |
Decision |
|
H4 |
HRM Practices → Employee Engagement → Job Satisfaction |
0.23* |
Accepted |
Note (s): β: Path coefficient, p: Probability value, *p < 0.05; Source: Compiled by authors.
Assessment of the moderation effect
The graphical representation of the moderation model is shown in Figure 3. The path coefficients regarding the moderating effect are shown in Table V.
Figure 3: Graphical representation of moderation model
Source: Compiled by authors.
From Table V, although both age and gender strengthens the positive relation between HRM practices and job satisfaction due to the positive path coefficient (ꞵ) value, but their association is not statistically significant because the p-value exceeds 0.05. Therefore, hypothesis H5 and H6 will not be accepted.
Table V: Moderation effect path coefficients
|
Hypothesis |
Effect |
β |
Decision |
|
H5 |
Age x HRM Practices → Job Satisfaction |
0.08 |
Not accepted |
|
H6 |
Gender x HRM Practices → Job Satisfaction |
0.03 |
Not accepted |
Note (s): β: Path coefficient; Source: Compiled by authors.
Conclusions and Implications
The study outcomes indicate that HRM strategies are crucial for fostering job happiness in unicorn firms. Previous research has also demonstrated that HRM practices significantly affect job satisfaction (Tessema & Soeters, 2006; Ijigu, 2015). The research demonstrated that HRM strategies favorably impact employee engagement. Adopting effective HRM practices will ensure employee engagement (Saad et al., 2021; Memon et al., 2021). The study's results also indicate that employee engagement contributes to job satisfaction. When employees are involved in their work, they are more likely to be satisfied. Also, prior research has revealed that employee involvement strongly mediates the relationship between HRM practices and work satisfaction (Pradhan et al., 2019; Memon et al., 2021). Also, the study examined the moderating effect of age and gender on HRM practices and work satisfaction. In agreement with past research, the study shows that neither age nor gender moderates the relationship between HRM practices and job satisfaction (Mohammad et al., 2017). Unicorn startups have the potential of unicorn startups to drive innovation and create job opportunities. However, these companies face challenges in retaining employees and fostering a sense of camaraderie. The main reason for high employee turnover is the lack of job satisfaction. This is one of the first studies to examine HRM practices' effects on job satisfaction in India's unicorn startups. Understanding the relationship between HRM practices, employee engagement, and work satisfaction in India's unicorn businesses can close the research gap. The findings of this research can provide valuable insights to researchers and practitioners, enabling them to understand the relationship between HRM practices, employee engagement, and work satisfaction. Consequently, HR managers can prioritize developing programs that promote employee engagement and work satisfaction, while decision-makers can implement measures to enhance job satisfaction among startup employees. These efforts are expected to contribute significantly to the growth of a thriving startup ecosystem in India.
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