Mediating Role of Job Satisfaction on Turnover Intentions and Job Mismatch Among Millennial Employees in Bengaluru

Abstract

The millennials have become the largest cohort in the workforce, and their retention has become challenging for policymakers and organizations. Millennials are career-oriented and are ready to switch jobs if there is a mismatch in skills and job requirement. The purpose of this study is to investigate the mediating role of job satisfaction on turnover intention and job mismatch among millennial employees in Bengaluru. The study consists of 247 millennial employees from different industries of Bengaluru. Statistical tools such as SPSS 20, AMOS 20, and Sobel-Z test have been used for analysis. It is found from our research study that job mismatch is having a positive relationship with turnover intention, while job satisfaction is having a negative relationship with turnover intention. The relation between job mismatch and job satisfaction is negative. The findings demonstrated that job satisfaction partially mediated the relationships between job mismatch and turnover intentions. It was concluded from the study that millennials consider personal growth as the major factor, which influences their job satisfaction. This study is of practical importance as it impacts organizational practices (specifically human resource management practices).

Keywords

Job satisfaction turnover intention millennial job mismatch mediation overeducation skill mismatch

Introduction

India is competing with its shifting demographic structure. It is both the second most populated and the most youthful nation in the world. Over half of the Indian population is less than 25 years of age, and over 65% is less than 35 years (Ministry of Statistics and Programme Implementation, 2017). The expanse of the young people makes it essential for India to understand the needs, desires, and aspirations of its youth. If efficiently employed, India’s young people have an immense potential to add to the wealth of the country. Millennials (Generations Y) are born between 1981 and the late 1990s. National statistics claim that Gen Y is around 34% (at 440 million) of the population (Ahluwalia, 2018). India’s millennial generation is smarter than their predecessors as they prefer elaborate designations and want constant challenges and recognition. The millennials believe that changing jobs would improve their careers and, hence, embrace job-hopping (Martins, 2019).

Academic experts and human resource (HR) professionals consider that if millennials are satisfied with the work, then they will be more loyal, more averse to relinquish their positions and can undoubtedly affect organizational performance (Putri et al., 2020). As per the World Economic Forum survey (Mishra et al., 2018), Indian youth is dissatisfied with the job market. As many as 49% of the youth perceive jobs available in the market are not to their expectations. The correlation between economic growth and jobs is debilitating, and the main reason for worsening this condition is a mismatch between qualifications, skills, and jobs (Basole et al., 2018). In other words, there exist gap between the skills and qualifications acquired by youth and those that are required by employers. Organizations need to comprehend the characteristics of millennials and improve their job satisfaction levels by institutionalizing innovations in the working environment.

Numerous researchers have indicated that job satisfaction is of paramount significance as it is one’s general attitude towards the job, and therefore considered as a vital priority policy in most of the organizations (Chen et al., 2012; Tansel & Gazîoğlu, 2014).

Several factors influence job satisfaction such as work preparation (education), work hours, salary, work environment, nature of work, leadership behavior, promotion criteria, interpersonal relationship, job competency, welfare measures, personal recognition, and growth (Koorella & Perumal, 2019; Kumari et al., 2014).

Job satisfaction affects turnover intentions. As per Currall et al. (2005), job satisfaction has a direct link with absenteeism and intentions to resign. Turnover intention is an act of withdrawal behavior where employees move out of the organization to join another organization. It is either voluntary or involuntary and is a result of work dissatisfaction (Bluedorn, 1978). According to Wang and Zhang’s (2010) study, higher job satisfaction leads to lower staff turnover.

In developed countries, education–job mismatches (specifically over education) found to deter job satisfaction levels among employees. It may generate counterproductive work behavior, such as absenteeism and job turnover intentions (Sam, 2018). According to Kim and Sang’s (2018) study, higher job mismatch adversely affects job satisfaction levels.

From the above discussion, we can reason that job mismatch and turnover intentions matter the most for job satisfaction. These three are significant as they impact organizational performance and track employee satisfaction.

Previous research studies have focused on relationships between job satisfaction and employee turnover (Lee et al., 2017; Rahman, 2020), job–skill mismatches, and job satisfaction (Kim & Sang, 2018; Vieira, 2005). Only a few studies have delved into the mediating role of job satisfaction (Chen

et al., 2019; Khalida, 2018). The motivation behind this examination is to research the mediating role of job satisfaction on turnover intention and job mismatch among millennial employees. Such research studies are still in their infancy in India. The current research is of practical importance as it impacts organizational practices (specifically human resource management practices).

Based on the above discussion, we set the following hypothesis:

To examine the effects of millennials’ job mismatch on job satisfaction and turnover intention.

To evaluate the influence of millennials’ job satisfaction on turnover intention.

To investigate the mediating role of millennials’ job satisfaction on turnover intention and job mismatch.

Literature Review

Job Mismatch

Job mismatch highlights the discrepancy between job characteristics and personal characteristics, which refers to the degree to which an individual/worker’s educational attainment, proficiency, subject major, and interested fields match the know-how of a specific job. According to Farooq (2011), job mismatch is a matter of grave concern as socio-economic costs are pertinent at the individual level, firm level, and national level. Job mismatch assembled into three distinct classes, namely education–job mismatch, skill–job mismatch, and major–job mismatch (Noh & Lim, 2009). As indicated by an ILO report (2013), education–job mismatch alludes to the circumstance where laborers have more (less) long stretches of education than their occupation requires. Skill–job mismatch measures the degree to which laborers do not have the right skills to execute the current job (Allen & Van der Velden, 2001). Finally, a major–job mismatch occurs when job expectation and the subject major of graduating college is not coherent.

Job Satisfaction

Job satisfaction is defined as the blend of mental, physiological, and environmental factors that cause a person to genuinely admit that he/she is happy with the job. In other words, it is the response from the workplace (Hoppock, 1935). In later studies, this definition was advanced, and it was characterized as the acknowledgement of an individual’s work values in the workplace and marked by gratifying enthusiasm (Bussing et al., 1999). As per Locke (1969), job satisfaction is an emotionally positive state, attained from an individual’s encounter with his or her job. It is not always the money factor; specific individuals are inclined towards the job as it gives genuine satisfaction.

Factors Influencing Job Satisfaction

Researchers hold different perspectives on the structure of job satisfaction. Moyes et al. (2006) studied factors prompting job satisfaction levels of accounting graduates. They found that safeguarding equal opportunities, supervision, recognition of employees, peer relations, and intrinsic values of a job influence job satisfaction. Smith et al. (1969) proposed five dimensions of job satisfaction such as pay, work, promotion, supervision, and relationships with colleagues. Later, their work was revised by Lee et al. (2017) and included job competency as another dimension. Padala’s (2011) study found that promotion, allowances, and salary are the core factors affecting job satisfaction. The Society for Human Resource Management report (2016) discussed that millennials enjoy their job if provided with work-specific training, professional, and career development aspects. According to Salma and Sajid (2012), interpersonal relationship, that is, employee’s relationship with peers, subordinates, and their managers, is the primary determinant of their job satisfaction. Khademi’s (2014) study revealed that welfare has a positive influence on motivation, performance and employee job satisfaction. By investing in welfare measures, the company gets the highest return in the form of increased efficiency from employees (Prabakar, 2013). According to Lee et al. (2017), the personal growth of an individual, salary, welfare measures, work itself, interpersonal relationships, leader behavior with subordinates and job competency affect job satisfaction. As per Shermon (2004), competence is a significant trait of a human being and, virtually, the product of knowledge, skills, and attitudes, which makes them perform their duties to the best of their knowledge and shapes them as better performers under critical situations.

Considering the above literature and discussion we had with 15 industry experts, this study characterized the factors affecting job satisfaction of millennial employees as “leader behavior, salary, and welfare, interpersonal relationships, work itself, personal growth, and job competency.”

Turnover Intention

When an employee decides to quit the organization, it shows an intention to leave. As per Carmeli and Weisberg (2006), the turnover intention has three essential elements: thoughts to leave the job, searching for another job, and the intention to quit the organization. As the turnover intention is the antecedent of actual turnover, it is essential to understand the reasons why employees exhibit such behavior and take up corrective actions (Dubey, 2017).

Foreman (2009) grouped the reasons into three general categories: work-related factors, individual factors, and external factors. Work-related factors include job satisfaction, organizational commitment, and wages, individual factors include age, education and gender, and external factors include joblessness, perception of employment, and others. One of the most prominent factors of employee turnover is that the workplace or job is not to his/her expectation (Yazinski, 2009).

Theories and Hypotheses Development

Person–job fit as per O’Reilly et al. (1991) is characterized as the fit between the person’s qualities (knowledge/information, skills/aptitudes, and abilities) and the demands of the job. The job fit is likewise used for job mismatch, from the point of view of featuring the inconsistency between job characteristics and individual characteristics, which refers to education mismatch (over- and undereducational attainment), skill mismatch, and major subject mismatch. Higher the conformity of educational match (education, skills, and subject major) with job requirements, higher is the job satisfaction (Edwards, 1991) and lesser is the turnover intentions. Job mismatch is related to work dissatisfaction and more turnover intentions (Chhabra, 2015).

The Herzberg two-factor theory (Herzberg et al., 1959) explains how motivating factors and hygiene factors are crucial for employee satisfaction in the job. If hygiene factors are not acknowledged, then it leads to dissatisfaction (Herzberg et al., 1959). It implies that satisfaction is a result of motivating factors, and discontent is the consequence of hygiene factors (Rynes, 1991).

The Theory of Organizational Equilibrium (TOE) developed by March and Simon (1958) is the first recognized theory on turnover intentions. This theory suggests that perceived ease of movement and perceived desirability of movement are the two factors that determine an employee’s equilibrium and job satisfaction. These factors directly affect turnover intentions.

Fishbein and Ajzen’s (1975) theory of reasoned action helps clarify the connection between attitude, intention, and behavior. Furthermore, based on this theory, Mobley et al. (1978) proposed an intermediate linkage model between job satisfaction and employee turnover. This model expresses that when an employee is disappointed with a work, he/she at that point starts to assess choices and quits the organization if the option foreseen to be all the more satisfying.

The above theories used to build a theoretical framework for our research study and explain the relationship between job mismatch, job satisfaction, and turnover intentions.

Job Mismatch Effects on Job Satisfaction

The early studies have highlighted that mismatch workers exhibit lower job satisfaction (Cha & Chu, 2010; Park, 2004; Tsang & Levin, 1985). A study by Kim and Choi (2018) proved that job mismatch of the PhD workforce showed adverse effects on compensation and job satisfaction. According to Peiró et al.’s (2010) research, there exists a negative relationship between overall job satisfaction and overeducation. Sam (2018) studied about education–job mismatches on University graduates of Cambodia and found that education–job mismatches adversely affect job satisfaction. Shevchuk et al. (2019) learned over education and skill mismatch on many dimensions of job satisfaction. They deduced that both over- and underskilled employees expressed lower satisfaction levels concerning pay, security, achievement, and opportunity for development. Hence, we propose the following hypothesis.

H₁: Job mismatch has a negative influence on job satisfaction of millennials.

Job Mismatch Effects on Turnover Intention

As per Park (2004), 90% of workers who answer that their educational level is higher than required level do not, in general, think about their present place of employment as their permanent workplace, and they endeavor to search for different positions that match their educational level. Research study suggests that the individuals who are overeducated work underneath their latent capacity and demonstrate high turnover rate in contrast with people who work in employments that match their educational qualifications (Erdogan et al., 2011). Overqualified employees exhibit a greater degree of job mobility and turnover, presumably because of agitation or the desire to find positions that best suit their qualification and skills (Sicherman, 1991). Significant findings from the master thesis by Choi (2017) on the consequence of job mismatch proved that overeducation and skill surplus have positive effects on turnover intentions. For postgraduates, the turnover intention is affected by skill-mismatch, while the education–job mismatch more influences university graduates. Considering the above discussions, we propose the following hypothesis.

H₂: Job mismatch has a positive influence on turnover intention among the millennial generation.

Job Satisfaction and Turnover Intention

Pepe (2010) says job satisfaction is the most significant factor that influences employee’s intentions to leave or remain in an organization. Millennials are less committed to staying in organizations where they witness job dissatisfaction (Wen et al., 2018). Understanding the determinants of job satisfaction can effectively reduce the problem of attrition (Ravari et al., 2012). The research study by Khalida (2018) has demonstrated that job satisfaction and turnover intention variables exhibit a negative relationship. Low turnover intentions in the job improve productivity in an organization. Lee et al.’s (2017) study show that job satisfaction levels of early-career workers negatively influence turnover intentions. Given the above literature, we propose the following hypothesis:

H₃: Job satisfaction of millennials has a negative influence on turnover intention.

Research Method

Participants

We used a cross-sectional survey design as a part of quantitative analysis. To improve the representativeness of a broader population, we used a purposive sampling method. We selected 35 enterprises (in Bengaluru) belonging to different industries. Before approaching the respondents, we contacted the HR personnel of the enterprise (personally). Based on HR permission, we distributed a structured questionnaire to millennial employees. The industries that we approached included biotechnology, information technology, machine tool manufacturing, service industry, aeronautics, garment, aluminum and steel industry, electrical engineering, and computer and electronics industry. These are the prime industries prevailing in Bengaluru, Karnataka (Government of India, Ministry of Micro, Small and Medium Enterprises, 2016 report). The target population for the study is millennials/young employees of the organization. We conducted this study from October 2019 to January 2020. To collect the data, we adopted the stratified sampling method. The strata that we used was “age stratification” and belonged to the age group of 20–30 years, which represent samples of the millennial population. In each enterprise, we approached six to eight participants of each enterprise. To improve the accuracy of the research, we informed the target respondents (millennial employees) in advance that their “privacy is maintained,” and the results of the survey used for academic purpose. We considered a total sample size of 247 for the final study (refer Table 9 in the Appendix). Out of 247 participants, 135 were male and 112 were female (refer Table 10 in the Appendix).

Survey Implementation, Measures, and Tools

Pre-survey

Before the formal survey, we conducted a pre-survey to assure the validity and reliability of the scale. The items of the job satisfaction scale, job mismatch, and turnover intention were pretested with 15 enterprises (refer Table 9 in the Appendix). After taking prior approval from the HR department, pretesting of the questionnaire was conducted on 117 employees who were under the age group of 20–30 years. Out of 117 employees, 72 were male and 45 were female, who had a minimum qualification of pre-degree or above. We assured participants to uphold their confidentiality with the utmost privacy. We tested the scale items for reliability measures. It resulted with a Cronbach’s Alpha of 0.747, which is quite satisfactory to use the suggested scales as per George and Mallery (2003). We piloted confirmatory factor analysis (CFA) to determine whether the observed variables served as useful indicators of the latent variables. CFA used to validate the constructs (Anderson & Gerbing, 1988). CFA analysis demonstrated an acceptable overall model fit, and thus, we can conclude that theorized model fits well with the observed data. Our study found that convergent validity, reliability, and discriminant validity of the survey instrument met the recommended threshold values (see Table 2). It means that the survey instrument developed is fit enough to measure the expected outcome.

Job Satisfaction Scale

We took the job satisfaction scale from Lee et al.’s (2017) study and adapted scale items to suit our research. We subjected these items to factor loading and Cronbach alpha analysis. We eliminated the items, which had weaker loadings (refer Table 1). For the final study, we have used 19 items for job satisfaction scale with six constructs. We named the constructs as interpersonal relationships, salary and welfare, leader behavior, personal growth, work itself, and job competency. This study suggests a second-order model, where job satisfaction comprised of six constructs.

Table 1.

Measurement Scale Items.

Construct	Items	Factor Loadings	Cronbach’s Alpha
Work itself	I feel fulfilled and proud of the work I am engaged in	0.762	0.781
	I can derive pleasure from my job	0.797
	My work supplies me with a stable job	0.844
Salary and welfare	I feel my work has been duly rewarded	0.822	0.861
	Welfare and benefits in our unit are fair	0.839
	The salary system of the company stimulates me to work hard.	0.846
Personal growth	Company training process helps me to improve my ability	0.864	0.901
	I can constantly get new knowledge and experience from my work	0.820
	As long as I do a good job, I will have promotion prospects	0.779
	I am willing to accept difficult work and challenges	0.855
InterpersonalRelationships	I am satisfied with how colleagues deal with each other in the company	0.844	0.811
	When pressures and difficulties arise in my work, my colleagues can offer me help and support	0.830
	My role in the team can be recognized and have a positive influence	0.790
Leader behavior	I am satisfied with the leaders in my workplace as a positive role model	0.803	0.851
	My superior is fair to subordinates	0.859
	My superior is very capable	0.866
Job competence	Despite doing my job well, I still have a lot of time to communicate with my relatives and friends.	0.887	0.889
	My work pressure makes me have no time to do what I want.	0.878
	The operation procedure of the company has made me very exhausted	0.851
Turnover Intention	I consider leaving my current enterprise one day	0.810	0.899
	I try looking for a suitable new job next year	0.861
	I think my prospects might not be good if I continue to stay in this company	0.821
Job mismatch	I have genuine education and knowledge for the current job	0.797	0.872
	My current job is relevant to my areas/discipline of education	0.764
	I have job-specific skills, which are relevant to the current job	0.789
	I have the necessary skills, which are relevant to the current job	0.804
	I have portable skills, which are relevant to the current job	0.812

Source: Primary survey.

Table 2.

Composite Reliability, Convergent Validity, and Discriminant Validity.

	CR	AVE	MSV	IR	SW	J	L	JM	TI	P	W
IR	0.813	0.592	0.139	0.769	–	–	–	–	–	–	–
SW	0.859	0.670	0.216	0.288***	0.819	–	–	–	–	–	–
J	0.890	0.729	0.152	0.246**	0.363***	0.854	–	–	–	–	–
L	0.851	0.656	0.153	0.195*	0.224**	0.238**	0.810	–	–	–	–
JM	0.872	0.577	0.313	–0.163*	–0.158*	–0.014	–0.168*	0.760	–	–	–
TI	0.900	0.751	0.313	–0.326***	–0.358***	–0.114	–0.270***	0.560***	0.866	–	–
P	0.902	0.697	0.216	0.373***	0.465***	0.389***	0.375***	–0.070	–0.261***	0.835	–
W	0.782	0.545	0.153	0.301***	0.247**	0.160*	0.391***	–0.227**	–0.384***	0.299***	0.738

Source: Gaskin and Lim (2016), “Master Validity Tool,” AMOS Plugin. Retrieved from Gaskination’s StatWiki

Note: CR > 0.7 (composite reliability is met), AVE > 0.5 (convergent validity is met), and MSV < AVE (discriminant validity is met). Significance of correlation (*p < .05, **p < .01, ***p < .001).

Job Mismatch Scale

We used self-reports from individuals to measure job mismatches (Duncan & Hoffman, 1981). In our research, we used information about job mismatch, viz., how knowledge and skills gained through formal college education and the major subject match to assess their job tasks. Self-report measures have the benefit of being effectively implementable in a study and, along these lines, exceptional data acquired by their feedback. We adapted the questions for job mismatch from the study of Farooq (2011) and International labor survey by Stoevska (2017). We have measured job mismatch with five items on a five-point Likert scale (refer to Table 1).

Turnover Intention Scale

We adopted the turnover intention scale developed by Griffeth and Hom (1988) and Mobley et al. (1978). Researchers have extensively accepted this scale in academic circles. We have adapted and used this scale for our research study. We have measured turnover intention using three items on a five-point Likert scale (refer Table 1). All the above scale items are subjected to the CFA test to measure psychometric properties.

The questionnaire had four sections—section 1 related to job satisfaction; section 2 was on job mismatch; section 3 was on turnover intentions; and section 4 was on demographic profile. We got the response on a five-point Likert scale: strongly disagree to strongly agree.

After CFA, we conducted a scanning electron microscopy (SEM) analysis for the proposed model. We used latent variables such as job mismatch, job satisfaction, and turnover intention in developing the structural equation model. We tested these variables according to the hypothesis set in this article. The proposed structural equation model is shown in Figure 1. For analyzing job satisfaction as a mediating variable, we used the bias-corrected (BC) method of bootstrapping with 1000 sample size, and significance of the mediation effect was assessed by using the Sobel-Z test. This study has used SPSS 24 software & AMOS 20 to elicit inferences. Based on exhaustive literature reviews, we propose the following model.

Figure 1.

Note: JM—Job Mismatch, JS—Job Satisfaction, P—Personal Growth, W—Work Itself, L—Leader Behavior, IR—Interpersonal Relationship, SW—Salary and Welfare, J—Job Competency, TI—Turnover Intention, JM—Job Mismatch, JS—Job Satisfaction, and TI—Turnover Intention.

Figure 2.

Source: Primary survey.

Results

Scale Assessment

This study implements CFA to judge the unidimensionality of each item and for validity measurement. The measurement model (see Figure 2) consists of eight latent constructs, namely, work itself, personal growth, salary and welfare, interpersonal relationships, leader behavior, job competency, job mismatch, and turnover intention. Each construct had at least three to five items.

The fit indices of the measurement model are χ2 = 415.269, CMIN/df =1.403; p = .000, RMSEA = 0.040, CFI = 0.966, NFI = 0.894, and AGFI = 0.869. This indicates that the proposed scale fits for measurement.

Validity Test

We used the validity measures such as composite reliability, discriminant validity, and average variance extracted (AVE) to assess the validity concerns. As proposed by Campbell and Fiske (1959), construct validity of the scale is measured by convergent and discriminant validity. The convergent validity measures the correlation between scale items and measured by AVE and composite reliability (R). The AVE value of all the items ranged from 0.545 to 0.751. Since AVE values > 0.5, the convergent validity condition is met. The composite reliability measures (internal consistency of scale items) are above the threshold level of 0.7; scale items exhibit internal consistency. Discriminant validity tests whether measurement of constructs is unrelated. To check this condition, maximum shared variance (MSV) < AVE. Since all the values of MSV are less than AVE, the discriminant validity condition is met (refer Table 2). We found all standardized factor loading of each construct to be greater than 0.7 (Hair et al., 2010).

Table 3.

Path Coefficients and Determination Coefficients of the Structural Model.

Pathname	OutcomeVariables		CausalVariables	S.E.	CR	p	Path Coefficient	DeterminationCoefficient (R²)	Hypotheses
Path A	Job satisfaction	←	Job mismatch	0.042 (S_a)	–2.484	0.013*	–0.216 (a)	–	H₁ supported
Path B	Turnover intention	←	Job mismatch	0.080	7.162	***	0.476	0.46	H₂ supported
Path C	Turnover intention	←	Job satisfaction	0.023 (S_b)	–4.289	***	–0.391 (b)	0.46	H₃ supported

Source: Primary survey.

Note: *p < .05, **p < .01, ***p < .001. Here, a and b are path coefficients for paths A and B, respectively; S_a and S_b are their respective standard error.

Figure 3.

Note: JM—Job Mismatch, JS—Job Satisfaction, P—Personal Growth, W—Work Itself, L—Leader behavior, IR—Interpersonal Relationship, SW—Salary and Welfare, J—Job Competency, and TI—Turnover Intention.

Table 4.

Fit Statistics in the Structural Model.

Sl. No.	Goodness of Fit Model Index	Recommended Value*	Observed Value	Results
1.	Chi-square/degree of freedom**	≤2.00	1.428	Acceptable	Hair et al., (2010) Byrne (2010)
2.	Goodness of fit index (GFI)	≥0.80	0.889	Fit
3.	Adjusted goodness of fit index (AGFI)	≥0.80	0.867	Fit
4.	Tucker–Lewis index (TLI)	≥0.90	0.958	Fit
5.	Comparative fit index (CFI)	≥0.90	0.962	Fit
6.	Normalized fit index (NFI)	≥0.80	0.885	Fit
7.	Root mean square of approximation (RMSEA)	≤0.08	0.042	Acceptable

Source: Primary survey.

Assessments of the Proposed Structural Model and Hypothesis Testing

The structure model (see Figure 1) consists of job satisfaction as a second-order factor and six first-order factors (leader behavior, personal growth, salary and welfare, work itself, interpersonal relationships, and job competence). Here, job mismatch is an exogenous variable and turnover intention as an endogenous variable.

The fit indices of the final SEM model are χ2 = 449.9, CMIN/df = 1.472; p = .000, RMSEA = 0.049, CFI = 0.968, NFI = 0.907, and AGFI = 0.831. The results indicate that the structure model is fit for prediction and interpretation (see Table 4). All the parameter estimate values of the SEM have a critical ratio (CR) values greater than ±1.96, validating the rejection of null hypothesis (see Table 4).

By referring to Table 3 and Figure 3, we can infer that job mismatch significantly influences job satisfaction and turnover intention. The standardized path coefficient of job mismatch to job satisfaction is −0.22 (p <.05), indicating negative relation and, thus, proving hypothesis 1. The standardized path coefficient of job satisfaction to turnover intention is −0.39, demonstrating job satisfaction adversely affects turnover intention (p <.01). Hence, hypothesis H3 is supported.

The standardized path coefficient of job mismatch on turnover intention is 0.48 and reveals that job mismatch is positively correlated with turnover intention (p < .01). Meanwhile, the coefficient of determination (R2) values for turnover intention is 46%. As per Falk and Miller (1992), the minimum threshold value of R2 is 10%. As we have met the criteria of R2, our proposed SEM is valid.

Total, Direct, and Indirect Effects

For analysis of total, direct, indirect, and mediating effects, we used the bootstrapping technique. For assessing the path significance, the BC method preferred as it helps in reducing the type 1 error (Williams & MacKinnon, 2008).

In our study, the dependent variable is the turnover intention, and Table 6 shows the direct, indirect, and total effects of the constructs on the dependent variable. The total effect of job mismatch to turnover intention is 0.672, consisting of a direct effect of 0.571 and an indirect effect of 0.101. The total effect of job mismatch on job satisfaction is –0.104, consisting of the direct effect of –0.104 and no indirect effect. The total effect of job satisfaction on turnover intention is –0.970, consisting of the direct effect of –0.970 and no indirect effect. The result analysis reveals that all the path coefficients were significant.

Sobel-Z Test for Mediation

We carried out the Sobel-Z test for analyzing the significance of the mediation effect. The Sobel test equation is as follows:

Z-value = a × b/SQRT (b2×Sa2 + a2×Sb2).

See Table 3 for the values of a, b, Sa, and Sb. Therefore, Z = 4.92, which is >1.96 with p-value <0.001. The results confirm that the mediation effect is significant.

To compute impact, we use equation a×b

Therefore, a×b = (−0.216 × –0.391) = 0.085. Job satisfaction as a mediator has an impact of 8.5%.

Note: Source for calculation: Preacher, J. K. & Geoffrey J. G. calculation tool for mediation test. Available from http://quantpsy.org/sobel/sobel.htm

Table 5.

Path Coefficients of Each Dimension of Job Satisfaction and Significance Test.

Path	Standard Load	C.R	p-Value
Interpersonal relationship ← job satisfaction	0.522	–	–
Job competence ← job satisfaction	0.48	4.479	.00***
Leader behavior ← job satisfaction	0.50	4.520	.00***
Work itself ← job satisfaction	0.51	4.402	.00***
Personal growth ← job satisfaction	0.70	5.204	.00***
Salary and welfare ← job satisfaction	0.62	4.970	.00***

Source: Primary survey.

Note: *p < .05, **p < .01, ***p < .001.

Table 6.

Direct, Indirect, and Total Effects of Turnover Intention by Bootstrap (1000 Samples).

Path Name	Path	Effect	Estimates	t-Values	p-Value
Path A	Job mismatch ← job satisfaction	Direct	–0.104	–2.484	0.018
		Indirect	0.000	–2.484
		Total	*0.104
Path C	Job mismatch ← turnover intention	Direct	0.571	7.162	0.001**
		Indirect	0.101	7.162	0.016*
		Total	0.672
Path B	Job satisfaction ← turnover intention	Direct	–0.970	–4.289	0.001**
		Indirect	0.000	–4.289
		Total	–0.970

Source: Primary survey.

Note: *p < .05, **p < .01, ***p < .001.

When “job satisfaction” enters as the mediator variable, the direct effect of job mismatch on turnover intention was reduced from 0.571 to 0.101, indicating the impact of mediation. The results of the indirect effect test again proved that job mismatch → turnover intention was statistically significant. We conclude that job satisfaction plays a partial mediating role (see Table 7).

Table 7.

Testing Mediation Hypothesis.

Hypothesis	Direct Effect	Indirect Effect	Result
JM→JSàTI	0.571**	0.101*	Partial Mediation

Source: Primary survey.

Note: *p < 0.05, **p < 0.01, ***p < 0.001.

Discussion

In our study, job satisfaction is a second-order factor and consists of six first-order factors. The order of influence observed was personal growth, salary and welfare, interpersonal relationships, work itself, leader behavior, and job competencies (see Table 5). The findings of our research are in line with the conclusion of Lee et al. (2017). However, a research study by Zhang and Liao (2009) shows that salary and welfare is the main factor that influences job satisfaction levels followed by other factors such as job, promotion, and relationship. The reason for the dissimilarity in findings could be that Indian millennial employees are keen on personal growth than salary and welfare. Indian Millennial employees are in the learning phase and would like to enhance their working capacity. Moreover, job satisfaction of Indian millennial on job competence is relatively low. It means that millennial employees are currently focusing on developing job skills to perform a job task with competence.

Furthermore, our research found that job mismatch is negatively correlated with job satisfaction. This result is in line with McKay et al.’s (2018) study. Their research showed a substantially lower level of job satisfaction among those who consider themselves under- or especially overqualified in their current job. Our findings suggest that the larger the gap between qualifications and competencies (required in the current position), the greater the negative effect on job satisfaction. According to the Society for Human Resource Management report (2016), circumstances to use skills and abilities at work are a significant contributor to achieve job satisfaction. Hence, underutilization of skills is a matter of concern as employees tend to look out for alternative employment or it leads to dissatisfaction in the current job. The result of this study is in line with previous studies of Lee et al. (2017), which shows that job satisfaction adversely affects turnover intention. When employees have dissatisfactions toward their current work, it is easier for them to consider quitting. For employees, who are below the age of 25, the turnover intention is driven more by job satisfaction than pay fulfillment (Choudhury & Gupta, 2011). The main reasons for dissatisfaction are the absence of career growth opportunities, recognition, biased work environment, and bad relations at the workplace (ET Bureau, 2018). From our research study, we found that job mismatch significantly affects turnover intentions. This finding is in line with the study of Choi (2017). When employees feel that their skill and education are not matching with their work, they are more averse to be happy with their jobs and have stronger turnover intention.

Theoretical Implications

The empirical findings of our study give us a clear understanding of how job satisfaction mediates the relationship between turnover intention and job mismatch. It also complements to the existing literature in the area of turnover intention and its predictors. Our research pinpoints that job mismatch positively influences turnover intentions, that is, the larger the gap between qualification and competencies required for the job, the higher the effect on turnover intentions. We also found that job mismatch adversely affects job satisfaction, that is, job mismatch lowers the millennials job satisfaction levels, which may then lead to absenteeism and turnover intentions. Hence, by striking a balance between the supply of educated workforce and its utilization in the workplace, we can improve job satisfaction.

Furthermore, we found that job satisfaction mediates the relationship between job mismatch and turnover intentions. Hence, job satisfaction is essential for employees and employers. Additionally, this study has identified job satisfaction factors that influence millennial employees placed in different industries in Bengaluru. These factors are instrumental in delivering job satisfaction and reduce turnover intentions.

Managerial Implications

One of the greatest expenses to an organization, from an HR perspective is employee attrition. This study identifies the antecedents of turnover intentions (job satisfaction and job mismatch). HR managers to pay careful attention to job fit when employing educated/skilled millennials. If the employees are overqualified for the job, then their job roles have to be redefined to suit qualifications. Companies can assign challenging roles to keep them engaged with their jobs. For underqualified employees, companies can conduct training and development to upgrade their knowledge and skills with the goal that they can sustain in the job. Since job satisfaction is partially mediating job mismatch and turnover intentions, organizations have to monitor job satisfaction levels as it affects turnover intentions frequently. When millennial employees are satisfied with their jobs, they are more productive and less likely to remain absent and leave jobs. Therefore, HR managers should devise practices that enable continued satisfaction in the workplace.

.Furthermore, this research listed out factors influencing job satisfaction. HR managers can make a note of these factors and implement it effectively in their organization. As employers assess students based on their education/skills during campus recruitments, universities and colleges can enrich their curriculum, vocational qualification, and enhance the millennials job fit.

Conclusions

HRs are one of the main assets of any nation, and holding these assets is indispensable for the development of any economy. Qualification and skill mismatches are complex phenomena that affect work productivity and companies’ competitiveness. When millennials enter the workforce and recognize that their skill potential and qualifications are not in sync with job requirements, it leads to job dissatisfaction and turnover intentions. Hence, mismatches are to be minimized as it affects job satisfaction and turnover intentions. It is for the higher education system to identify the required skills to thrive in the Industrial 4.0 environment and produce quality graduates by focusing more on skills and not degree. Understanding triangular relationship (job mismatch, job satisfaction, and turnover intentions) is crucial for enhancing the overall productivity of an organization. Suppose an organization listens to millennial ideas, rewards their performance, provides training, and assists them in their career development. In that case, there are chances that we can minimize turnover. Since job satisfaction partially mediates the relationship between job mismatch and turnover intention, all efforts are to be done so that millennial employees are happy with the present place of employment. This study is useful to HR managers, academician, and policymakers to develop practices that make millennials great employees.

Limitation and Future Research

We can undertake future research on processes of educational mismatch (e.g., overeducation/undereducation) and of skill mismatch (e.g., overskilling/underskilling). Furthermore, we can study their interaction effect. A researcher can conduct an exhaustive study to detect the specific type of skills (e.g., generic and occupation-specific) required for the job market. In our research study, the ability of independent variables (job mismatch and job satisfaction) to predict the dependent variable (turnover intention) variance is 46% (R2 = 0.46). The remaining 54% of the variance is still unexplained. We can conduct further research to identify other predictors of turnover intention. Our study focused only on organizational factors that lead to job satisfaction. In contrast, we have not explored the personal factor of millennial, which is equally important in inducing satisfaction with their job.

Appendix

Table 8.

Pre-test Survey.

Sl. No.	Industries	Number of Respondents
1	Manufacturing (tractors and tillers)	9
2	Manufacturing (food processing)	8
3	Electrical and electronics	15
4	Electrical and electronics	7
5	Services (telecom)	9
6	Manufacturing(consumer durables and home appliances)	7
7	Electrical and electronics	9
8	Electrical and electronics	7
9	Services	5
10	Services	6
11	Manufacturing (Solar equipment)	7
12	Services (healthcare)	10
13	Services (IT)	5
14	Services (finance)	5
15	Services (IT)	7
Total		117

Source: Primary survey.

Table 9.

Final Survey.

Sl. No.	Industries	Number of Respondents
1	Biotechnology	6
2	Biotechnology	5
3	Biotechnology	7
4	Biotechnology	4
5	Biotechnology	5
6	Information technology	7
7	Information technology	8
8	Information technology	9
9	Information technology	12
10	Information technology	5
11	Machine tool manufacturing	6
12	Machine tool manufacturing	9
13	Machine tool manufacturing	10
14	Machine tool manufacturing	7
15	Machine tool manufacturing	8
16	Service industry (telecom)	9
17	Services	7
18	Aeronautics	13
19	Aeronautics	7
20	Aeronautics	8
21	Garment	12
22	Garment	4
23	Garment	7
24	Garment	8
25	Garment	9
26	Aluminum and steel	8
27	Aluminum and steel	9
28	Aluminum and steel	5
29	Electrical engineering	6
30	Electrical engineering	8
31	Electrical engineering	7
32	Computer and electronics manufacturing	4
33	Computer and electronics manufacturing	3
34	Computer and electronics manufacturing	3
35	Computer and electronics manufacturing	2
	Total	247

Source: Primary survey.

Table 10.

The Sociodemographic Characteristics of the Respondents.

Variable	Group	N	%
Gender	Male	135	54.7
Gender	Female	112	45.3
Age (in years)	20–23	72	29.1
	24–26	91	36.8
	27–30	84	34
Education level	Higher secondary	24	9.7
	Graduation	147	59.5
	Postgraduation	76	30.8
Work experience	<2 years	74	30.0
	2–4 years	114	46.2
	>4 years	59	23.9
Working hours	<40 hours in week	95	38.46
Working hours	>40 hours	152	61.53
Salary (per month)	10,000–20,000	50	20.2
	20,000–30,000	86	34.8
	30,000–40,000	24	9.7
	40,000–50,000	34	13.8
	>50,000	51	20.6

Source: Primary survey

Footnotes

Declaration of Conflicting Interests

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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