Abstract
Purpose
This study explored moderating effects of employee generations on factors related to employee retention and motivation in the workplace.
Design/methodology/approach
The authors developed a survey instrument and collected the survey data via Amazon Mechanical Turk. After filtering out bad responses, the authors ended up with 489 sample cases for this study. The authors used structural equation modeling for data analysis.
Findings
Evidence showed that only transformational leadership was significantly related to retention of Generation X employees and only work–life balance had a significant relationship with intrinsic motivation. For Generation Y employees, transformational leadership was the only factor affecting their retention while both transformational leadership and autonomy showed significant impacts on their intrinsic motivation. Generation Z employees reported that only transformation leadership affected their retention while transformational leadership, corporate social responsibility and autonomy were significantly related to their intrinsic motivation in the workplace. All three generations showed statistical significance between intrinsic motivation and employee retention.
Practical implications
This study could help business practitioners increase employees' work motivation and retention.
Originality/value
First, our results revealed interesting similarities and differences between generations in terms of the factors that affected employees' retention and motivation. Second, this study proved that employees' generation affects the impacts of transformational leadership, CSR, autonomy, WLB and technology on their motivation and retention in the workplace. Third, the results of our study also showed that employees of different generations are intrinsically motivated by different factors, proving the importance of considering generational differences in motivation literature.
Keywords
Citation
Lee, C.C., Lim, H.S., Seo, D.(J). and Kwak, D.-H.A. (2022), "Examining employee retention and motivation: the moderating effect of employee generation", Evidence-based HRM, Vol. 10 No. 4, pp. 385-402. https://doi.org/10.1108/EBHRM-05-2021-0101
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited
1. Introduction
For the past several decades, employee retention has been an important topic to both scholars and practitioners because employees, the most valuable assets of an organization, are the ones who add to its value, quantitatively and qualitatively (Anitha, 2016). Therefore, employers have taken steps to ensure that employees stay with the organization for as long as possible (Alferaih et al., 2018). Doing so is challenging because the workforce is becoming more confident and demanding due to changes in markets and demographics (Anitha, 2016). A disengaged workforce leads to higher turnover rates that increase the costs of recruiting and selecting new employees (Malinen et al., 2013).
The objective of this study is to examine the moderating effects of employee generations on factors related to employee retention and motivation in the workplace. In doing so, this study makes a significant contribution to literature in several ways. First, although there have been numerous studies on factors that affect employees' retention such as a manger's leadership style (e.g. Khan and Wajidi, 2019), a firm's commitment to corporate social responsibility (e.g. Valentine and Godkin, 2017), autonomy (e.g. Kim and Stoner, 2008), work–life balance (e.g. Koubova and Buchko, 2013) and technology (e.g. Haar and White, 2013), there are no studies that have examined the effect of these five factors on employee retention and the underlying mechanism of these relationships. Second, few studies have examined effects of these five factors on different generations of employees – Gen X, Gen Y (also known as the Millennials) and Gen Z. Studies have focused on certain generations such as Gen Y (e.g. García et al., 2019) or Gen X (e.g. Westerman and Yamamura, 2007), but no studies have been conducted to understand the different effects of the five factors on employee retention spanning three different generations. According to the US Bureau of Labor Statistics (2021), while 40% of the 2020 American workforce comprises Gen X and 44% of Gen Y, Gen Z represented 15% of the American workforce. This indicates that Gen Z has also become an important generation to consider when examining generational differences of employee retention. Finally, no studies have reported the effects of these variables on retaining employees from these various generations during the pandemic. Retaining employees is a challenge at the best of times, but it has become even more challenging during the pandemic. A recent survey of working age people in various industries found that about 40% of respondents expressed strong intention to quit their current job in the next three to six months (De Smet et al., 2021).
2. Literature review and hypotheses
2.1 Employee generations
Based on the generational theory originated from the work of Mannheim (1970), generations refer to groups of individuals (i.e. cohorts) born in the same period, sharing similar historical events and social experiences. This means that a cohort of individuals who shared common historical and social experiences are more likely to share similar characteristics, attitudes and behaviors (Strauss and Howe, 1991). Given that the main objective of this study is to examine generational differences in effects of leadership styles, corporate social responsibility, autonomy, work–life balance and technology on intrinsic motivation and employee retention, we will use the generational theory as our theoretical framework to develop hypotheses in the next sections.
2.2 Effects of leadership across generations
Transformational leadership is defined as transforming the values and priorities of followers and motivating them to perform beyond their expectations (Kark et al., 2003). Concurrently, Wilkesmann and Schmid (2014) reported that one characteristic of strong leaders is the ability to motivate and influence people. Motivation was also found to be a complex act that had several factors involved. Employees, who were proactive both at work and in their personal lives, were positively affected by both their employer's leadership style and ability to foster a team and showed stronger motivation (Felfe and Schyns, 2014; Khan and Wajidi, 2019). Gerhold and Whiting (2020) explored the motivations of employees over several generations, from Boomers to Gen Z, and the leadership skills that inspired them. They found no significant differences among generations. Rather the differences were driven more by an employee's stage of life and career than age. They reported that leadership fundamentals were a constant. These fundamentals, building strong teams, providing feedback and understanding employees' motivations, were multi-generationally relevant skills. In addition, Diskiene et al. (2019) found that the relationship between a leader's emotional and social intelligence and an employee's motivation to work was undeniable, although there was some variance depending on the latter's age. Interestingly, younger workers relied less on their leader's emotional stability to motivate them than older, more experienced workers.
Fiaz et al. (2017) stated that an autocratic leadership style resulted in a lack of employee motivation, whereas democratic and laissez-faire leadership boosted employee morale, resulting in improved efficiency and effectiveness. Building on this, Bornman (2019) reported that Gen Z employees preferred a transformational leadership style, servant leadership and leaders who exhibited feminine traits. Gen Z employees were less satisfied with leaders with dark triad traits, rated these leaders as ineffective and had little motivation to perform for them (Vadvilavičius and Stelmokienė, 2019). In summary, a positive and transformational leadership style that gives more autonomy to the employee tends to motivate employees. Therefore, we posit that:
The generation of employees will moderate the effect of leadership on their intrinsic motivation in the workplace, such that transformational leadership is more positively related to the workplace motivation of younger generation employees.
Transitioning to employee retention, Aboramadan (2021) reported that transformational leadership had a positive effect on employee engagement by reducing their turnover intentions. Similarly, transformational leadership had a direct negative effect on voluntary turnover intentions (Alatawi, 2017; Alferaih et al., 2018). Transformational leadership programs could infuse a company with competent leadership (Alatawi, 2017). Good leaders' relationships with their employees, ability to lead and their leadership style were directly associated with employees' satisfaction and future career decisions, productivity level, and most importantly, employee retention (Clausen, 2009). Al-Asfour and Lettau (2014) demonstrated that Gen Y employees preferred regular feedback, a positive communication style and regular communication of information from their leaders. Thus, we hypothesize that:
The generation of employees will moderate the effect of leadership on employees' retention in the workplace, such that transformational leadership is more positively related to the workplace retention of younger generation employees.
2.3 Effects of corporate social responsibility across generations
A firm's commitment to corporate social responsibility (CSR) has become a major issue for many employees. Chaudhary (2018) reported that an organization's CSR programs could enhance the motivation of three types of employees – idealists, enthusiasts and indifferentists. CSR was also noted to attract and motivate Gen Z workers in the accounting profession (Sobotka, 2019). Therefore, we argue that:
The generation of employees will moderate the effect of CSR on employees' intrinsic motivation in the workplace, such that greater CSR is more positively related to the workplace motivation of younger generation employees.
Employees' perceptions about CSR promoted their organizational citizenship behavior (OCB), reduced their intentions to quit and increased their intentions to stay (Mohammed Sayed Mostafa and Shen, 2020). Chaudhary (2018) reported that when it came to retention, employees did not stay with a firm because of its CSR program, but they might leave if the firm engaged in actions that violated their values and the CSR program. Pierce and Snyder (2015) confirmed a positive relationship between a firm's business ethics policy and employee turnover. The introduction of ethical guidelines promoted fairness and equality, which helped create a positive work environment, subsequently leading to deeper organizational commitment and reduced employee turnover. This increased perception of CSR also promoted the fit between employees and their employer (Valentine and Godkin, 2017), made employees proud of their company (Coldwell et al., 2008) and increased engagement across the workforce (Sobotka, 2019), especially that of the younger demographic (Cohen et al., 2017). CSR thereby possibly reduced employees' intentions of leaving. Thus, we maintain that:
The generation of employees will moderate the effect of CSR on employees' retention in the workplace, such that a CSR policy is more positively related to the retention of younger generation employees.
2.4 Effects of autonomy across generations
Several decades ago, Hackman and Oldham (1976) demonstrated the importance of autonomy for workplace motivation. More recently, Shin et al. (2019) showed that autonomy enabled employees to establish their own processes, schedules and goals, all of which drove motivation. Specifically, when Gen Z employees were responsive to leaders, this encouraged autonomy, innovation and work product ownership (Lanier, 2017). Thus, we posit that:
The generation of employees will moderate the effect of autonomy on employees' motivation in the workplace, such that greater autonomy in one's job role is more positively related to the workplace motivation of younger generation employees.
Rothmann et al. (2013) reported that employees' satisfaction with their degree of autonomy played a significant role in retaining staff. Providing employees with more autonomy made them less likely to leave (George, 2014) and had a negative effect on turnover rates (Kim and Stoner, 2008). For example, Farr-Wharton et al. (2011) observed that there was a positive relationship between perceptions regarding their autonomy and their commitment to an organization. To maintain this sense of autonomy, Ghosh et al. (2012) emphasized the importance of empowering employees. They noted that a better sense of autonomy, stemming from their empowerment, improved employees' sense of belonging and thus their commitment to the organization and decision to stay in it. Thus, we posit that:
The generation of employees will moderate the effect of autonomy on employees' retention in the workplace, such that greater autonomy is more positively related to the retention of younger generation employees.
2.5 Effects of work–life balance across generations
Work–life balance (WLB) was found to have a positive impact on employees' motivation. This impact on employees is defined as the pleasure gained from their work and the likelihood that they would willingly engage in a work-related task (Bui et al., 2016). Dizaho et al. (2017) observed that one way to improve WLB was to have flexible work arrangements. This balance, a healthy relationship between work and life, increased employees' motivation, both at work and at home (Koubova and Buchko, 2013), engagement and satisfaction (Kaur and Randhawa, 2021). According to Woler et al (2020), younger generations tended to be less satisfied and more stressed with their WLB. To combat this, emphasizing an improvement in WLB for millennials would positively impact their work motivation (Woler et al., 2020). There were multiple studies that reported the younger generations were more related with WLB (Dex and Bond, 2005). Therefore, we posit that:
The generation of employees will moderate the effect of WLB on employees' motivation in the workplace, such that greater WLB is more positively related to the workplace motivation of a younger generation of employees.
Deery (2008) reported that support from managers, personal attributes and industry norms affected the degree of conflict between work and family, which then affected employees' turnover decisions. Organizational support for these WLB factors can increase the retention rate (Parkes and Langford, 2008). In particular, Pulevska-Ivanovska et al. (2017) found that WLB was particularly important for Gen Z. If the organization could not provide a WLB, Gen Z employees were more likely to leave. We assumed that WLB was one of the critical factors that affect employee retention. Investment in supportive work environment practices also had a positive influence on employee retention (Kundu and Lata, 2017). One explanation for this relationship is that deeply rooted employee loyalty and commitment to the organization is created gradually over time (Ahsan et al., 2016). Therefore, we argue that:
The generation of employees will moderate the effect of WLB on employees' retention in the workplace, such that greater WLB is positively related to the retention of a younger generation of employees.
2.6 Effects of technology across generations
Elias et al. (2012) reported a positive correlation between technology and work motivation when dealing with the dissemination of internal information and the interpretation of large data files. Innovative practices at work, such as the use of Internet and email, appeared to increase employees' motivation. Coupled with the creation of good working atmospheres, the opportunity to work with new technology were positive motivators at work and valued by Gen Z employees (Gracyzk-Kucharska, 2019). Thus, we argue that:
The generation of employees will moderate the effect of technology on employees' motivation in the workplace, such that more technology is more positively related to the workplace motivation of younger generation employees.
Companies competent with IT knowledge, objects and entrepreneurship had better chances of attracting loyal prospects and retaining their employees, especially those of Gen Z (Haar and White, 2013). In addition to attracting employees, digital communication created two-way channels of dialogue and helped employees understand how their roles were helping the company. This increases possible retention rates (Kick et al., 2015).
As McGrindle (2015) noted, Gen Z cannot live without the internet and mobile phones. They preferred organizations that allowed them to use technology to communicate and work regardless of their geographic location. Gen Z generally were not found to plan to work long-term in one company, but wanted an employer that adapted to their needs, which included digital innovation and communication (Bucovetchi et al., 2019). Failure to do so would lead to reduced retention rates (Hicks, 2018). Therefore, it is reasonable to assume that the company's technological environment would affect Gen Z employees' choice to remain with the company. Thus, we contended that:
The generation of employees will moderate the effect of technology on employees' retention in the workplace, such that more technology is more positively related to the retention of younger generation employees.
2.7 Motivation and retention
Motivation has a significant relationship with employee retention; without the positive impact of motivation, employee turnover would increase (Shah and Asad, 2018). For instance, in a study of bank employees, Ramlall (2004) reported the positive impact of motivation on employee retention. It is important to note that Shah and Asad (2018) found intrinsic and extrinsic motivation to be essential as both had a significant positive effect on employee retention. Therefore, our final hypothesis stated that:
Employees' intrinsic motivation is positively related to their retention in all generations.
3. Method
3.1 Sample data and questionnaire
The definition of generations in terms of the birth year varies across studies. As a compromise, we used the middle value. Thus, for the purpose of this study, three generations (Gen X, Y and Z) are defined based on the age as of August 2020. Specifically, Gen X is between 40 and 55 years old; Gen Y is between 25 and 39 years old; and Gen Z is between 18 and 24 years old. We created a survey questionnaire with the items that measured our variables and posted it on Google Forms. To take the survey, we required members of Amazon's Mechanical Turk to be employed and ages 18–55 years old. The survey was first run for a week in the third week of April 2020 and received 570 responses. We deleted 9 responses due to repeat responses and 24 due to multiple missing values, which reduced the total number of valid responses to 537. Furthermore, 48 responses were deleted due to poor response quality. Poor responses were identified using items that were reverse coded. After removing the poor responses, we were left with 489 useable and valid sample cases for this research. Regarding the sample size per each generation group, Gen Z is 120 (24%), Gen Y is 278 (56%) and Gen X is 91 (18%).
3.2 Measures
Our participants indicated their responses to all items on a 7-point Likert-type scales, ranging from 1 (strongly disagree) to 7 (strongly agree). Note that Cronbach's alpha for all variables exceeded the 0.70 cutoff value (Greco et al., 2018), indicating that all of the variables were reliable and could be used in the analysis. Examples of each item for each category are in Table 1.
3.2.1 Retention
We used three items from Armstrong-Stassen and Schlosser (2008) to measure the employees' intention to remain with their company.
3.2.2 Transformational leadership
We used the Vera and Crossan (2004) 12-item scale to assess transformational leadership, consisting of four dimensions – charismatic leadership, inspirational motivation, intellectual stimulation and individual consideration.
3.2.3 Corporate social responsibility
We chose items from Woo (2013) to measure, which assessed five dimensions of CSR: environment, human rights and labor issues, product responsibility, society and economics. We excluded the product responsibility category because of low factor loading problems.
3.2.4 Autonomy
We used three items from Hackman and Oldham (1976) to assess autonomy.
3.2.5 Work–life balance
To measure this variable, we used five items from Brett and Stroh (2003).
3.2.6 Technology
To measure this variable, we picked three items from Nambisan et al. (1999).
3.2.7 Intrinsic motivation
We used items from Grant (2008) to measure intrinsic motivation.
3.3 Analytical models
In this study, we created three analytical models to test our hypotheses that examine the generational differences in the relationships between five independent variables and three dependent variables. The first model was the intrinsic motivation model in which intrinsic motivation was the dependent variable and transformational leadership, CSR, autonomy, WLB and technology were the independent variables.
The second model was the retention model in which retention was the dependent variable and the five independent variables were the same as the first model.
The third model examined whether intrinsic motivation affects retention. Retention was the dependent variable and intrinsic motivation was an independent variable.
Figure 1 describes our analytical models with the results. When conducting three analytical models, we used a subsample analysis instead of a two-way interaction design to examine generational differences in the relationships as we hypothesized. This method allows us to compare the impact of each independent variable on dependent variables among different generations of employees. This approach is preferable because it reduces the possibility that noise will be introduced into the model (Stone-Romero and Anderson, 1994).
4. Results
4.1 Descriptive statistics and correlations
Table 2 summarizes descriptive statistics for the variables used in our study.
4.2 Measurement model
To evaluate the fit of our measurement model, we conducted a series of confirmatory factor analyses (CFA). We used several fit indices such as chi-square (χ2) values, the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA) and the Standardized Root Mean Square Residual (SRMR). As shown in Table 3, the results of CFA suggest an excellent fit (χ2 = 757.41, p < 0.01; CFI = 0.95, RMSEA = 0.06, SRMR = 0.07) for our hypothesized seven-factor model (Hooper et al., 2008). In addition to our focal seven-factor model, we further assessed the fit of alternative models. The results proved that the hypothesized seven-factor model fits the data significantly better than the other possibilities.
Several statistical indictors were used to assess the reliability and the convergent and discriminant validity of our constructs. As shown in Table 4, composite reliability (CR) estimated our constructs to be from 0.885 to 0.946, which were all above the threshold value of 0.7 (Fornell and Larcker, 1981). Therefore, internal consistency was validated. Convergent validity of the constructs was also acceptable. All estimated factor loadings were significant at p < 0.001, and all estimates are above 0.6 and most estimates are above 0.7. Furthermore, average variance extracted (AVE) for all constructs are above 0.5, the acceptable threshold level (Fornell and Larcker, 1981). Given that the AVE for each construct was greater than the squared correlations between two constructs (Fornell and Larcker, 1981), discriminant validity of the constructs was achieved. Hence, these results provided support for using the seven constructs as reliable and distinctive variables in our analysis.
4.3 Test for the potential common method bias
Given the nature of our data using a single source of information, we tried to control for common method bias with both procedural and statistical remedies. In terms of procedural remedies, we ensured respondent anonymity, provided a guidance with detailed instruction, added reversed items and minimized the length of the survey following guidelines provided by Podsakoff and Organ (1986). In terms of statistical remedies, we conducted Harman's single-factor test to examine potential common method bias (Harman, 1967; Podskoff and Organ, 1986). Our results of the Harman's single-factor test indicated that the single factor accounted for 43.37% of the total variance, not exceeding 50% (Podsakoff and Organ, 1986). Thus, common method bias does not appear to be an issue in this study.
4.4 Testing hypotheses using structural equation model
The results of the testing using structural equation modeling showed that the hypothesized model yielded an excellent fit (χ2 = 2,194.49). In order to further assess the validity of the hypothesized model, we tested a more parsimonious model that removed the direct paths from the independent variables to retention. This would be an alternative model. According to the principle of model parsimony, an alternative model would fit the data better if the χ2 value of the hypothesized model did not drop significantly. If the χ2 value of the hypothesized model dropped significantly, however, the hypothesized model would fit the data better. Although the alternative model also yielded an excellent fit (χ2 = 2,316.78), our hypothesized model provided a significantly better model fit compared to the alternative model (Δχ2 = 122.29). Table 5 presents a summary of the fit indices for the hypothesized and alternative models.
Consistent with H1a, the effects of transformational leadership on the employees' intrinsic motivation were different among the generations. They were significant for Gen Y (β = 0.50, p < 0.01) and Gen Z (β = 0.37, p < 0.01), but not for Gen X (β = 0.18, n.s.), supporting H1a. Although transformational leadership had a significant effect on all employees' retention (β = 0.30, p < 0.01 for Gen X; β = 0.33, p < 0.01 for Gen Y; β = 0.29, p < 0.01 for Gen Z), the effects were not different across generation groups. Therefore, H1b was not supported.
Consistent with H2a, CSR was positively and significantly related to employees' intrinsic motivation for Gen Z (β = 0.23, p < 0.05), but not for Gen X (β = 0.03, n.s.) or Gen Y (β = −0.02, n.s.). However, the effects of CSR on employees' retention were not significant in any of the generation groups (β = 0.03, n.s. for Gen X; β = 0.03, n.s. for Gen Y; β = 0.02, n.s. for Gen Z), failing to support H2b.
Supporting H3a, autonomy was positively and significantly related to employees' intrinsic motivation for Gen Y (β = 0.28, p < 0.01) and for Gen Z (β = 0.24, p < 0.05), but not for Gen X (β = 0.18, n.s.). H3b was not supported because autonomy did not have a significant impact on employees' retention in any of the generation groups (β = 0.01, n.s. for Gen X; β = 0.01, n.s. for Gen Y; β = 0.01, n.s. for Gen Z).
Hypotheses 4a proposed that the effect of WLB on employees' intrinsic motivation would be more significant to younger generations while Hypothesis 4b proposed that the effect of WLB on employees' retention would be more significant to younger generations. The results revealed that WLB was positively and significantly related to employees' intrinsic motivation for Gen X (β = 0.42, p < 0.01), but not for Gen Y (β = 0.04, n.s.) and Gen Z (β = 0.05, n.s.). However, WLB did not have a significant effect on employees' retention in any of the generation groups (β = 0.01, n.s. for Gen X; β = 0.04, n.s. for Gen Y; β = 0.02, n.s. for Gen Z). H4a was not supported because the effect of WLB on intrinsic motivation was not significant among younger generations, Gen Y and Gen Z. In addition, H4b was not supported because no significant difference was found among the three generations.
Hypotheses 5a and 5b proposed that the effect of technology on employees' intrinsic motivation (H5a) and their retention (H5b) would differ by generation. However, technology had no significant effect on employees' intrinsic motivation in any generation groups (β = 0.08, n.s. for Gen X; β = 0.07, n.s. for Gen Y; β = 0.05, n.s. for Gen Z). Furthermore, technology had no significant effect on employees' retention in any generation groups (β = 0.03, n.s. for Gen X; β = 0.05, n.s. for Gen Y; β = 0.04, n.s. for Gen Z). Based on these findings, neither H5a nor H5b was supported.
Hypothesis 6 proposed that employees' intrinsic motivation would be positively related to their retention in all generations. Our findings supported this contention (β = 0.54, p < 0.01 for Gen X; β = 0.48, p < 0.01 for Gen Y; β = 0.49, p < 0.01 for Gen Z).
5. Discussion
5.1 Theoretical contributions
The results of this study provided several theoretical contributions to management literature. First, our results revealed interesting similarities and differences between generations in terms of the factors that affected employees' retention and motivation. For Gen X employees, transformational leadership was significantly related to retention and only WLB had a significant relationship with their intrinsic motivation. For Gen Y employees, transformational leadership was also the only factor affecting their retention, while both transformational leadership and autonomy had a significant impact on their intrinsic motivation. Finally, for Gen Z employees, only transformation leadership also mattered for their retention while transformational leadership, corporate social responsibility and autonomy were significantly related to their intrinsic motivation. For all three generations, there was a statistically significant relationship between intrinsic motivation and employee retention.
Second, this study proved that employees' generation affects the impacts of transformational leadership, CSR, autonomy, WLB and technology on their motivation and retention in the workplace. As motivating and retaining employees becomes more challenging and workforces become more diverse in terms of generation, understanding generational differences in employee motivation and retention becomes a very important topic to explore. Only a few studies looked at generational differences in either employee motivation (Andrade and Westover, 2018) or employee's retention (Roman-Calderon et al., 2019) and no studies have examined the different effects of transformational leadership, CSR, autonomy, WLB and technology on employee motivation and retention spanning three different generations.
Third, the results of our study also showed that employees of different generations are intrinsically motivated by different factors, proving the importance of considering generational differences in motivation literature. However, our results did not provide empirical support for generational differences in retaining employees. Interestingly, only transformational leadership significantly affected employees of all generations. This finding would emphasize the critical role of leadership in retaining employees regardless of their generation.
5.2 Practical implications
The retention of an employee, especially younger generation employees, is pivotal in ensuring that organizations will be able to maintain sustained competitive advantages during the period of the pandemic since many companies have been experiencing serious younger generation employee retention issue. For instance, major retail companies, such as Target and Walmart, have been confronted with challenging managerial decisions because of the workforce shortage and have been forced to decrease their operation hours. To resolve this challenge, many companies have tried to increase the retention rate of their employees, especially those of the younger generation, by offering competitive financial and non-financial packages such as signing bonuses, healthcare benefits and/or opportunities for a college education. Despite all these endeavors, many companies have still been experiencing serious employee retention problems, which they have never experienced before. The findings of this study could be highly useful for organizations that are experiencing serious employee retention issues, many of whom are younger generation employees who are quitting their jobs during the pandemic.
First, these findings suggest reasons why so many organizations have had a challenging time managing low employee retention rates by showing that the impact of major factors (transformational leadership, CSR, autonomy, WLB and technology) on employee retention could vary depending on an employee's generation. For instance, our study's findings show that organizations actively implementing CSR policies may positively affect the retention of younger generation employees relative to older generations by intrinsically motivating younger generation employees more. Therefore, organizations should consider generational differences in employee motivation and retention when implementing employee retention strategies since an effective strategy for one employee generation may not be effective (or even harmful) for another employee generation.
Second, these results illustrate that employee retention is not a simple function, but rather a result of interactions between employee motivation and the specific generation. For instance, for Gen X, even though job autonomy does not directly affect employee retention, job autonomy still plays a crucial role in affecting employee retention by affecting employee motivation. Therefore, organizations should take care of factors affecting employee motivation as well because employee motivation works as a significant pathway to boost employee retention.
5.3 Limitations and future research directions
While the study advances our understanding in these areas, it has several limitations that future studies could explore. First, given that our study was a cross-sectional study with all responses collected from a single period, strong causality arguments cannot be made. Considering that our study collected the sample during the period of pandemic, it would have been a more interesting study if we deployed a longitudinal design because longitudinal data would have allowed us to examine how our independent variables affected employee motivation and retention as employee worked through the pandemic. Future studies should implement longitudinal design by collecting samples at different time points to provide greater insight into the causality argument as well as into the impact of the pandemic. Second, although this study examined the impact of employee motivation on employee retention as a significant pathway, we didn’t test the mediating effect of employee motivation on employee retention. Further studies could be done to investigate the mediating effect of employee motivation on employee retention in the context of different employee generations. Furthermore, regarding employee generation as a moderator, even though we used sub-sample design to examine the moderating impact of an employee's generation on employee motivation and retention, further studies could test the effect of the interaction between our independent variables and employee generation. Third, future studies could extend our study by examining whether our findings could change depending on the industry (e.g. retail, manufacturing) as well as firm characteristics (e.g. size). For instance, stronger impact of CSR on employee motivation in Gen Z may not exist in the financial industry wherein competitive environment and culture dominates.
Figures
Figure1
Research framework
Summary of measure
| Measure | Cronbach's alpha | Dimension | Item |
|---|---|---|---|
| Retention | 0.94 | Retention |
|
| Transformational leadership | 0.96 | Charismatic leadership |
|
| Inspirational motivation |
| ||
| Intellectual stimulation |
| ||
| Individualized consideration |
| ||
| Corporate Social Responsibility (“I think the company in which I work tries to …”) | 0.90 | Environment |
|
| Human rights and labor |
| ||
| Society |
| ||
| Economic |
| ||
| Autonomy | 0.94 | Autonomy |
|
| Work–life balance | 0.90 | Work–life balance |
|
| Technology | 0.89 | Technology |
|
| Intrinsic motivation (“Why are you motivated to do your work?”) | 0.93 | Intrinsic motivation |
|
Means, standard deviations and correlations of the variables
| M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. | Retention | 4.73 | 1.84 | (0.96) | ||||||||
| 2. | CSR | 4.90 | 1.22 | 0.64** | (0.90) | |||||||
| 3. | Autonomy | 5.07 | 1.51 | 0.54** | 0.39** | (0.94) | ||||||
| 4. | WLB | 4.62 | 1.63 | 0.22** | 0.11* | 0.26** | (0.90) | |||||
| 5. | Technology | 5.40 | 1.40 | 0.49** | 0.45** | 0.46** | 0.18** | (0.89) | ||||
| 6. | Intrinsic motivation | 4.76 | 1.73 | 0.65** | 0.48** | 0.54** | 0.26** | 0.44** | (0.93) | |||
| 7. | TFL | 4.77 | 1.44 | 0.65** | 0.48** | 0.48** | 0.25** | 0.44** | 0.70** | (0.94) | ||
| 8. | Generation X (dummy) | 0.19 | 0.39 | 0.01 | −0.01 | 0.00 | 0.11* | 0.10* | 0.07 | 0.09* | ||
| 9. | Generation Y (dummy) | 0.57 | 0.50 | −0.01 | 0.07 | 0.03 | −0.06 | 0.00 | 0.01 | 0.05 | −0.55** | |
| 10. | Generation Z (dummy) | 0.25 | 0.43 | 0.00 | −0.08 | −0.04 | −0.03 | −0.09* | −0.08 | −0.14** | −0.27** | −0.66** |
Note(s): TFL = Transformational Leadership. CSR = Corporate Social Responsibility. WLB = Work–life Balance. N = 489. Cronbach's alphas appear across the diagonal in parentheses
*p < 0.05
**p < 0.01
Comparisons of confirmatory factor analysis models
| Model | χ2 | df | CFI | RMSEA | SRMR |
|---|---|---|---|---|---|
| Hypothesized measurement model | |||||
| Seven-factor model | 757.41 | 254 | 0.95 | 0.06 | 0.07 |
| Alternative measurement models | |||||
| Six-factor model | 840.28 | 255 | 0.95 | 0.07 | 0.10 |
| Five-factor model | 842.77 | 257 | 0.95 | 0.07 | 0.09 |
| Four-factor model | 904.35 | 260 | 0.94 | 0.07 | 0.09 |
| Three-factor model | 926.28 | 264 | 0.94 | 0.07 | 0.09 |
| Two-factor model | 947.56 | 269 | 0.94 | 0.07 | 0.09 |
| One-factor model | 1,033.82 | 275 | 0.93 | 0.08 | 0.13 |
Summary of the reliability and the convergent and discriminant validity of constructs
| Latent variables | Dimension/item | Standardized factor loadings | AVE | CR |
|---|---|---|---|---|
| Retention | RT1 | 0.901 | 0.845 | 0.942 |
| RT2 | 0.928 | |||
| RT3 | 0.928 | |||
| Transformational leadership | Charismatic leadership | 0.883 | 0.814 | 0.946 |
| Inspirational motivation | 0.813 | |||
| Intellectual stimulation | 0.945 | |||
| Individual consideration | 0.961 | |||
| Corporate social responsibility | Economic | 0.709 | 0.607 | 0.860 |
| Society | 0.869 | |||
| Human rights and labor | 0.807 | |||
| Environmental | 0.719 | |||
| Autonomy | AT3 | 0.936 | 0.834 | 0.938 |
| AT2 | 0.898 | |||
| AT1 | 0.905 | |||
| Work–life balance | WLB5 (reverse coded) | 0.653 | 0.652 | 0.903 |
| WLB4 (reverse coded) | 0.835 | |||
| WLB3 (reverse coded) | 0.802 | |||
| WLB2 (reverse coded) | 0.867 | |||
| WLB1 (reverse coded) | 0.860 | |||
| Technology | T3 | 0.808 | 0.721 | 0.885 |
| T2 | 0.884 | |||
| T1 | 0.853 | |||
| Intrinsic motivation | MI3 | 0.919 | 0.815 | 0.929 |
| MI2 | 0.853 | |||
| MI1 | 0.934 |
Note(s): N = 489. AVE = Average variance extracted; CR = Composite reliability
Summary of model fit indices
| Model | χ2 | Δχ2 | df | Δdf | CFI | RMSEA | SRMR |
|---|---|---|---|---|---|---|---|
| Hypothesized model | 2,194.49 | 122.29** | 1,031 | 5 | 0.95 | 0.03 | 0.07 |
| Alternative model: removing direct paths from independent variables to retention | 2,316.78 | – | 1,036 | – | 0.94 | 0.04 | 0.07 |
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