Pa ge 1 Pa ge 64 American Journal of Multidisciplinary Research and Innovation (AJMRI) An Analysis of Demographic Factors that determine Employee Engagement in the Workplace: A Case Study of the RMG Industry of Bangladesh Mohammad Jahangir Alam1* Volume 2 Issue 2, Year 2023 ISSN: 2158-8155 (Online), 2832-4854 (Print) DOI: https://doi.org/10.54536/ajmri.v2i2.1356 https://journals.e-palli.com/home/index.php/ajmri Article Information ABSTRACT Received: March 04, 2023 Accepted: March 21, 2023 Published: March 26, 2023 As a labor-intensive and man-machine integrated manufacturing industry, the level of employee engagement in the industry is a big concern that has created a long-term adverse effect on both employers and employees to a large extent. Hence, this study has examined how the demographic factors of employees in this industry affect the engagement level of employees in the context of Bangladesh. Following the multistage sampling method, data was collected from 280 employees working in this industry and analyzed accordingly with the application statistical tool ANOVA and independent t-test. The results of the analysis indicate that the demographic factors of employees have an influence on employee engagement in the workplace at different levels. The managerial implication of this study is that the employers of the RMG industry will now know that the work engagement of employees is predicted by demographic factors of employees. Thus, this study will help this industry to set the right policies and procedures to adhere to a sustainable level of employee engagement in line with the demographic factors of employees. Keywords RMG, Employee Engagement, Demographic Factors, Hierarchical Regression, EE INTRODUCTION From the organizational perspective, both demographic factors (DF) are important aspects of people management phenomena that influence employee performance (Adewale, 2017; Hadoud et al., 2020). From the organizational perspective, DF mainly includes gender, marital status, age, length of experience, and educational qualification (Adewale, 2017). A recent study shows that the demographic attributes of employees were the primary concern while terminating the job of millions of employees in Seria due to the Covid-19 pandemic, (Jones & Comfort, 2020). Hence, this study has been initiated to find out the impact of both DF on employee engagement (EE). In the literature, the scholars also provided different opinions about the level of EE with DE (Sanyal et al., 2018; De Witte, 2003). Some scholars found a relationship between the DF of employees with their engagement level (De Witte, 2003), whereas others ignored the significance of such a relationship (Green & Leeves, 2013). On the contrary, the RMG industry of Bangladesh is now facing low labor productivity (Hassan, 2021), which is shaking its position in the world market (ACD Survey, 2020). As a labor-intensive manufacturing setup, where stable manpower is essential for its smooth survival, it is vital to the full engagement of its employees in all stages of integrated production processes. This country’s highest export-earning industry made 84.3% of total export earnings in the Fiscal Year 2019 (Bangladesh Bureau of Statistics, 2019). According to BGMEA (2019), this industry employs 4.2 million people directly and another 10 million people are indirectly dependent on this industry. In these circumstances, this study has examined the relationship of EE with DF in terms of gender, job category, marital status, education, age, income level, and length of job experience of employees in the RMG industry of Bangladesh. Because demographic factors of the employees are due to the fact that the personal obligations of employees and the conflict in their work lives are intensively correlated (Cemberci et al., 2022). On the other hand, some scholars, like Otoo and Mishra (2018). Otoo and Mishra (2018) stated that DFs like gender and marital status have no statistical significance on EE. Hence, this research gap has been examined in the context of this industry. LITERATURE REVIEW Employee Engagement Presently, business pioneers are getting a competitive edge over their rivals by enhancing EE in the workplace, as engaged employees perform better than others (Barrick et al., 2015). This priority issue helps organizations to enhance the overall performance of the business in a competitive environment (Costa et al., 2014). Because, engaged employees help to achieve their target and at the same time urge others to do the same as a part of the social process in the organization (Malik et al., 2020). As a result, all employees of the organization become engaged in the workplace and try to do their assigned work efficiently, and bear morale to enhance work role clarity among their associates (Malik et al., 2020). EE is the art of making people understand what they need to achieve in the organization (Whitehurst, 2016). It is the imperceptible spirit that motivates employees to higher levels of performance and a positive, fulfilling, and job- oriented situation categorized by vigor, dedication, and absorption (Schaufeli, 2017). Morgan (2017) signifies EE 1 Bangladesh University of Professionals (BUP), Bangladesh * Corresponding author’s e-mail: jahangir736@yahoo.com https://doi.org/10.54536/ajmri.v2i2.1356 https://journals.e-palli.com/home/index.php/ajmri Pa ge 65 https://journals.e-palli.com/home/index.php/ajmri Am. J. Multidis. Res. Innov. 2(2) 64-71, 2023 as a tool for gaining the target rapidly. So, it could be noted that employees invest their effort when they are confident about their ability to perform and to see the rewards in return (Chacko & Conway, 2019). They want to maintain an energetic and compelling relationship in work through their engagement (Schaufeli, 2017). The core difference between an engaged and a disengaged employee is that an engaged employee is always passionate about his /her work and feels a strong tie to the organization (Osborne & Hammoud, 2017). According to Kahn (1992) and Saks and Gruman (2014), EE is a psychological presence of employees in terms of attentiveness, connectivity, integrity, and a deep focus on role performance. It is a multidimensional motivational construct involving the simultaneous investment of employees at work (Kahn, 1990). EE is a critical topic for business management (Osborne & Hammoud, 2017) and an emotional commitment to the organization and its goals (Kruse, 2012). It is derived from the job satisfaction of employees as a holy grail of organizational psychology (Mitchell, 2017). According to Mira et al. (2019) and Rothenberg et al. (2017), EE is employees’ feelings toward their work situation in terms of commitment, performance, and loyalty. The management of an organization considers two themes of EE: it is the key to organizational success as it drives the organization toward higher profitability, productivity, and customer satisfaction (Crawford et al., 2010), and the impact of disengagement of employees. About half of the American workforce is fully or slightly disengaged, which is termed the “engagement gap” (Saks & Gruman, 2014). There are several theories of EE, which were mainly based on two research areas: the ethnographic study on personal engagement and disengagement (Khan, 0), and job burnout and employees’ well-being (Saks & Gruman, 2014; Maslach & Leiter, 1997). However, according to Gallup (2015), EE has three basic categories; actively disengaged, engaged, and not engaged (Radda et al., 2015). Around 17.2% of employees in the organization are actively disengaged, 32% of employees are engaged and 50.2% of the employees are not engaged (Choudhury & Mohanty, 2018). The inner sight of EE goes through vigor, dedication, and absorption (Stolarski et al., 2020; Gera et al., 2019; Lu et al., 2016). Vigor is the willingness and intention to utilize the emotion and energy of an employee in the organization (Stolarski et al., 2020), dedication is the extreme involvement in work with courage, motivation, and the organization’s specific goal and absorption shows the deep concentration on work (Stolarski et al., 2020). In brief, the framework of EE includes three unique aspects of engagement that work together to generate the experience of EE in the workplace (Shuck et al., 2014). Demographic Factors The age of employees in the organization is one of the DFs that extensively helps to know the impact on employees’ behavior decade after decade (Madan & Srivastava, 2015). So, it is equally important to understand the impact of the age of employees on their engagement pattern. Aged employees have more job satisfaction than others (Madan & Srivastava (2015). According to them, there is a positive linear relationship between job satisfaction and age. Employees at the age of 28 years and more have higher work engagement than others, indicating that work engagement has a significant relationship with age. However, Otoo and Mishra (2018). They did not find any impact of the age of employees on their engagement behavior. Therefore, the relationship between EE and the age level of employees has been checked with the following hypothesis. H1: The age of employees has an impact on EE in the RMG industry of Bangladesh. While discussing the DFs of employees, gender appears as a critical one that shapes EE (Bernardi, 2008). Their studies on gender inequalities concluded that gender influences work dynamics impacting EE. A survey conducted by CIPD (2006) on 2000 employees revealed that females were more engaged than their male counterparts. However, this finding is a complete contrast to the NHS survey conducted by IES and investigated by Robinson et al. (2004) as it did not find any difference in engagement of work between males and females. Furthermore, Otoo and Mishra (2018) concluded in their studies that the gender identity of employees has no statistically significant impact on EE. Therefore, the relationship between EE and the gender identity of employees has been examined in this study with the following hypothesis. H2:The gender identity of employees has an impact on EE in the RMG industry of Bangladesh. The marital status of an employee provides useful insights into the dynamics of his /her work behaviors (Schaufeli et al., 2002). It could be assumed that the individuals who have children are engaged since this is important to their families. However, scholars state that the engagement of employees with dependent families may be hindered by outside obligations (Schaufeli et al., 2002). On the other hand, a recent study shows that work engagement– namely absorption- changes according to marital status (Cemberci et al., 2022). In contrast, some scholars did not find any significant relationship between marital status and the work engagement of employees (Otoo & Mishra (2018). Therefore, the relationship between EE and the marital status of employees has been tested in this study under the following hypothesis. H3:The marital status of employees has an impact on EE in the RMG industry of Bangladesh. The income level of any employee is related to the compensation package offered by his or her organization which has a strong link with employee turnover intention and such an intention also influences his /her engagement level at work (Vatankhah et al., 2017). Crawford et al. https://journals.e-palli.com/home/index.php/ajmri Pa ge 66 https://journals.e-palli.com/home/index.php/ajmri Am. J. Multidis. Res. Innov. 2(2) 64-71, 2023 (2014) define compensation as a key motivating factor for EE, while Cyr & Choo (2010) stated compensation is one of the best predictors of EE. According to a recent study, the pay level of employees is important for any industry that deals with mob workers, like the RMG industry of Bangladesh (Ugarte & Rubery, 2021). The scope of a higher level of income is crucial for any employee, while he /she is on the hiring panel (Niebuhr & Peters, 2020). From this perspective, the relationship between EE and the income level of employees has been tested in this study under the following hypothesis. H4: The income level of employees has an impact on EE in the RMG industry of Bangladesh. According to Sharma et al. (2017), the education level of employees, the strongest component of demographic attributes, has an influence on EE. A significant difference prevails between work engagement (in terms of vigor, dedication, and absorption) and education level (Sharma et al., 2017). Undoubtedly, there is a positive relationship with the education level of employees; highly educated employees exhibit high levels of work engagement. However, Adewale (2017) stated that educated employees believe that they are irreplaceable because of their earned skills and thus they remain reluctant to be engaged at work. From this perspective, the relationship between EE and the education level of employees has been tested in this study under the following hypothesis. H5: The education level of employees has an impact on EE in the RMG industry of Bangladesh. The job category of employees is somehow related to their engagement; however, this can vary substantially from company to company too (Saks & Garman, 2014). It is also noted that professional workers have the highest engagement; manufacturing or production employees are the least engaged (Saks & Garman, 2014). A Gallup poll found that only about 30% of workers feel engaged, while only 35% of managers feel engaged. In fact, 51% of managers are not engaged and 14% are actively disengaged, while 52% of workers are not engaged and 18% are actively disengaged (Diener & Tay, 2015). From this perspective, the relationship between EE and the job category of employees has been tested in this study under the following hypothesis. H6: The job category of employees has an impact on EE in the RMG industry of Bangladesh. The results of a recent study conducted on EE and job experience indicate that there is a significant relationship between job experience and work engagement (Cemberci et al., 2022). Job experience is the extent of continuous involvement in a given occupation (Cemberci et al., 2022). It has revealed a positive correlation between job experience and EE (Cemberci et al., 2022), which was also supported by other scholars [Yildirim, 2008]. Higher engagement levels were found in more experienced employees (Douglas & Roberts, 2020). Scholars found that 16 years of or longer job experience of employees is positively related to work engagement (Douglas & Roberts, 2020). Shukla et al., (2015) also stated that there is a significant difference in the levels of work engagement based on the level of job experience. From this perspective, the relationship between EE and the job experience of employees has been tested in this study under the following hypothesis. H7: The job experience of employees has an impact on EE in the RMG industry of Bangladesh. Conceptual model of the Study The conceptual model of a study explains the way of conducting research work and thus makes the findings generally acceptable as Adom et al. (2018) recommended. This model configures the way of the relationship between EE and DF in the context of the RMG industry of Bangladesh which includes two variables; independent and dependent variables (Figure 1). Independent viable DF has seven constructs, whereas the dependent variable is EE. Accordingly, seven hypotheses were developed and examined to reveal the relationship between those variables. Figure 1: Conceptual Model https://journals.e-palli.com/home/index.php/ajmri Pa ge 67 https://journals.e-palli.com/home/index.php/ajmri Am. J. Multidis. Res. Innov. 2(2) 64-71, 2023 METHODOLOGY Data and Sample The research methodology is a systematic way of solving problems (Patel & Patel, 2019) that deals with numerical characters and hypnotizes the connection of variables to detain the target output (Apuke, 2017; Martinez et al., 2018). The methodology of this study includes 4.2 million employees working in the RMG industry of Bangladesh (BGMEA, 2019) as the study population. Considering the criteria of representative sampling, the sampling of this study includes two frames; sampling of respondents- the ultimate unit of analysis and sampling of factories (Landy et al., 2020; Thompson, 2013). In this viewpoint, the sample size of respondents and the factories have been affixed 280 and 40 respectively by the application of n=Z2PQ/d2 (n: Sample size, Z: Standard normal variate at 90% confidence level, p: Dichotomous probability, q: 1-p, and d: the precision level at 5%) and n=Z2CV2/e2 (n: Sample size, CV: Coefficient of variation at 5%, e: the precision level at 1.5%, Z: Standard normal variate value at 95% confidence level) Caltech (n.d.) recommended. On the contrary, a multi-stage sampling (MSS) method was applied to select the ultimate respondents as it allows both the probability and non-probability sampling techniques depending on the purpose of sampling (Latpate et al., 2021; Zee, 2014; Khedive, 2013). Accordingly, simple random sampling (SRS) was applied in the case of selecting sample factories, and the convenience sampling technique in the case of selecting individual respondents from the sample factories (Scholtz et al., 2021). The employees having less than 1.5 years of service and ages less than 20 years, factories <2 years in operation, and without membership of BGMEA were not counted while calculating the sample size. Research Instrument A structured closed-ended questionnaire having a 5-point Likert rating scale was developed with the involvement of different parties to capture data from the respondents. At first, this questionnaire was in English developed, which was later translated into Bengali language. Pre- testing of the questionnaire was conducted by taking personal interviews as Reynolds and Diamantopoulos (1998) recommended. Finally, the reliability testing was also conducted following the scale of Cronbach’s Alpha (Taber, 2017). The first section of this questionnaire includes 7 items: gender, age, job category, education level, marital status, experience level, and income level of the respondents. Accordingly, the second section includes 9 questions about the work engagement of the respondents. The independent t-test and one-way ANOVA were applied to identify the relationship between the independent variable demographic factors and the dependent variable employee engagement. An Independent t-test was applied in the case of gender, job type, and marital status as this test shows the relationship between the two groups (Gerald, 2018 & Kim, 2017). On the contrary, one-way ANOVA was applied to the age, education, income, and experience of employees as this test identifies the relationship between more than two groups (Gerald, 2018 & Kim, 2017). In statistical terms, an independent sample is a sample where the participants of each group are independent (Gerald, 2018). On the contrary, many statistical applications require comparing more than two groups, and thus the scientists developed the one-way ANOVA method to do hypothesis testing for more than two population means (Ostertagová1 & Ostertag, 2013). This analysis is one of the most frequently used statistical tools that arise from the error of alpha level inflation and generates a ratio of between and within group variances that focuses on the differences of group means (Kim, 2017). A statistical interface SPSS was applied to analyze the data following these techniques. RESULTS The data for this study were collected from 40 factories of the RMG industry of Bangladesh located in Dhaka, Narayangonj, Savar, Gazipur, Mymensingh, and Chottagram. And before going to the analysis, the error in the dataset is to avoid the overestimation or an underestimation of the parameter. Table 1 shows that 50.7% were female, 58.9% of respondents were workers, 41.1% were management, and the majority of them were married (79.3%). Among 280 respondents, only 5% were above 40 years, 36.79%, and 41.8% fell within the age group of 26-30 years 31-40 years. According to education level, they are segregated as upto SSC (58.57%), HSC (3.57%), Bachelor (11.4%), and above bachelor (26.4%). In terms of monthly income, 17.9% of the respondents were earning less than 12000.00, whereas 13.2% of them were earning more than 50000.00. Table 1: Summary of the respondents’ and organizations’ statistics Demographics Nos. % Gender Male 138 49.3 Female 142 50.7 Job Category Worker 165 58.9 Management staff 115 41.1 Age (Years) 20-25 47 16.79 26-30 103 36.79 31-40 116 41.43 Above 40 14 5.00 https://journals.e-palli.com/home/index.php/ajmri Pa ge 68 https://journals.e-palli.com/home/index.php/ajmri Am. J. Multidis. Res. Innov. 2(2) 64-71, 2023 Marital Status Single 58 20.7 Married 222 79.3 Education Up to SSC 49 58.57 HSC 10 3.57 Bachelor 32 11.43 Above bachelor 74 26.43 Monthly Income below 12000 50 17.9 12000-15000 68 24.3 16000-20000 64 22.9 21000-25000 10 3.6 26000-3000 25 8.9 31000-50000 26 9.3 51000-80000 12 4.3 81000-100000 7 2.5 Above 100000 18 6.4 Total Experience 1.5-3 years 63 22.50 4-8 years 114 40.71 9-12 years 66 23.57 13-15years 17 6.07 More than 15 years 20 7.14 Table 1 also shows that 22.50% of respondents were working for 1.5 years, whereas 7.4% were for more than 15 years. Table 2 illustrates the results of the t-test and one-way ANOVA. The results of the t-test indicate that the relationship of EE with the gender identity of employees is statistically significant as the t-value (.0015) is <0.05, while a positive t-value (3.001) indicates that male employees are more engaged than female employees. The results of the t-test indicate that there is no relationship between EE and job category as the significance of the t-value (0.209) is not <0.05. On the contrary, EE has a significant relationship with marital status, as the t-test value (0.00) is <0.05, while a negative t-value (-3.912) indicates that unmarried employees are more engaged than married employees. Table 2: Relationship Between Employee Engagement and Demographic Factors SL No. Variable t-value /f-value Sig. (Two-tail) Sig. (One-tail) Decision 1 Gender 3.001 0.003 0.0015 Statistically significant. 2 Job type 0.812 0.418 0.209 Statistically not significant. 3 Marital status -3.912 0.000 0.000 Statistically significant. 4 Age 8.644 0.000 Statistically significant. 5 Education level 4.637 0.001 Statistically significant. 6 Income level 4.840 0.000 Statistically significant. 7 Total experience 2.623 0.035 Statistically significant. The results of the one-way ANOVA test show that EE differs depending on the age of employees, as the f-value (0.000) is <0.05, while a negative t-value (-3.567) of EE with two age groups of employee shows that employees above 35 years are more engaged at work. The results of the one-way ANOVA test also indicate that there is a significant relationship between EE and the education level of employees (the significance of the f-value is 0.001, which is<0.05). At the same time, the t-test (3.475) between EE and two education groups shows that the employees below SSC are more engaged at work. It also shows that there is a significant relationship (significance of f-value 0.000 is <0.05) between EE and two different income groups, and the employees with higher earnings (BDT 12000 and more) are better engaged at work (the negative t-test is -4.954). The results of the one-way ANOVA test between EE and different experience groups of employees indicate a significant relationship (the f-value is 0.035, which is <0.05), while a negative t-test (-2.416) shows that employees with higher experience (above 8 years) are more engaged at work. In sum, the analysis shows that gender, age, marital status, education level, monthly income, and experience level of employees have an individual relationship with https://journals.e-palli.com/home/index.php/ajmri Pa ge 69 https://journals.e-palli.com/home/index.php/ajmri Am. J. Multidis. Res. Innov. 2(2) 64-71, 2023 EE, while job category does not exist such a relationship. It shows that male employees, employees above 35 years, unmarried employees, less educated or non-educated employees, and employees with higher earnings and higher experience are more engaged at work. DISCUSSION AND SIGNIFICANCE This study has significantly proved that the EE of employees in the RMG industry of Bangladesh has a relationship with their demographic attributes, with few exceptions. It has probed EE of employees has an individual relationship with their gender, age, marital status, education level, monthly income, and experience level of employees. But does not have any link with the job category of employees, which is the contrast to this study, as some scholars do not support this argument. The age of employees is a challenging factor for employees in the RMG industry, as it’s a labor-intensive industry, where the majority of the employees fall under the age of 20-30 years. So, the finding “employees above 35 years are more engaged at work” of this study is directive for the policymakers of this industry toward EE. Because, such finding is already supported by many scholars though others opposed this (Otoo & Mishra, 2018). Otoo and Mishra (2018). The finding about the gender identity of employees is also significant because EE differs between male and female employees to some extent (Otoo & Mishra, 2018). The finding of the study about the marital status of employees is crucial for the management of this industry as the number of married (79.3%) and unmarried (20.7%) employees differs significantly. According to Cemberci et al. (2022), EE changes with marital status, and Schaufeli et al. (2002) stated that the marital status of an employee provides useful insights into the dynamics of work behaviors. This study has revealed a useful insight into the employees, which is a big concern about turnover intention as such intention also influences EE level at work (Vatankhah et al., 2017). The policymakers of this industry need to work as the monthly income of 66.1% of employees ranges from BDT 12000 to 20000, and this is high time to think about this as the marginal level workers are still in the street to hike their wages. Similarly, the finding about the education of employees “the less educated employees are more engaged at work”, is a scope for further work to enhance EE in this industry. Because this finding is contradictory to the argument of the scholars who stated that the higher level of education of employees is the strongest component of demographic attributes that has an influence on EE (Sharma et al., 2017). Again, the finding of this study about job experience is significant as it revealed that employees with higher experience are more engaged at work, which is supported by literature (Cemberci et al., 2022; Douglas & Roberts, 2020). So, the retention plan of employees is important for sustainable EE in this industry. Finally, the finding of this study about job category is “there is no relationship between EE and job category”, which is a vital finding to work, which is in contrast to the literature. According to Sorenson & Garman (2013), the job category of employees is somehow related to their engagement, and a Gallup (2015) poll found that only about 30% of workers feel engaged, while only 35% of managers feel engaged (Diener & Tay, 2015). Limitations This study has gone through some impending limitations that need to be reckoned with for the interest of future exploration. Firstly, only the BGMEA enlisted organizations were considered, while a good number of organizations remained out of this list. Secondly, all the demographic attributes of employees were not considered in this study, which is the weakness of generalizing the findings. CONCLUSION This study has been initiated to understand the impact of demographic attributes on EE in the RMG industry of Bangladesh, and this has duly concluded that EE has a relationship in this industry. This study has revealed that six out of seven demographic attributes: gender, age, marital status, education level, monthly income, and experience level of employees influence EE to a large extent, whereas the job category does not have such influence. Hence, the management as well as the policymakers of this industry and their managers need to formulate the right strategies to deal with these factors well for better EE leading to prosperous business growth ahead. Researchers may take this study into an account as a strategy to explore the further scope of utilizing those factors for the persuasion of EE. Furthermore, this study might merit further exploration to reveal whether any other factor works in the organization, which influences EE. REFERENCE Asian Center Development. (2020). A Survey Report on the Garment Workers of Bangladesh (ACD survey report). Dhaka, Bangladesh. Adom, P.K., Kwakwa, P.A. and Amankwaa, A. (2018). 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