The Impact of Person-Environment Fit on Organizational Commitment

Words: 30033

Business

14th Apr, 2024

Abstract

Background. The ICT sector in the UAE has been developing rapidly with support from the government that provides aid in the form of licensing and policies that promote business activity. By 2025, this industry will experience a compound growth of 3.5%, which will affect employment and organizational management strategies. Since employees are the central resources that allow businesses to grow and reach their strategic targets, there is a need to define factors affecting workplace satisfaction and intention to stay.

Literature Review. Previous studies focused on relationships between different variables, including work satisfaction, organizational commitment, intention to leave, engagement, psychological capital, and the person-environment fit. However, none of the previous studies determined the correlation between the six factors since the majority of the researchers focused on examining the connection between two variables. This research attempted to address this gap using the example of the ICT industry in the UAE.

Research Question. The primary research question was, “How can intention to stay and workplace satisfaction be improved?” The questions were subdivided into five secondary research questions that concerned specific inter-relationships between the six variables identified during the literature review.

Methods. This study utilized a quantitative approach to answer the research question. An online survey was conducted that included a total of 95 questions. The link to the survey was distributed among the telecommunication workers with the help of HR managers. The original sample included 379 participants; however, after data cleaning and filtering, the sample was narrowed to 176 employees. Pearson’s correlation analysis, simple moderations modeling, and simple mediation modeling were used to test twelve hypotheses. SPSS Version 26 and Hayes’s PROCESS macro were used to conduct statistical tests.

Results. The results provided evidence for accepting nine hypotheses out of twelve hypotheses. Pearson’s correlation analysis revealed significant inter-relationships between person-environment (P-E) fit, psychological capital, and organizational commitment on the one hand and job satisfaction on the other hand. Additionally, a strong correlation was found between intention to stay and job satisfaction. Moderation analysis demonstrated that work engagement moderated the relationship between psychological capital and workplace satisfaction. Mediation modeling revealed that job satisfaction mediated the relationship between P-E fit and organizational commitment, P-E fit and intention to stay, psychological capital and organizational commitment, as well as psychological capital and intention to stay.

Discussion. The results of this research helped increase the generalizability of previous findings and discover new inter-relationships between the six variables. The research results also helped to formulate recommendations for managers in the ICT sector in the UAE concerning retention rates. Additionally, suggestions for future research were discussed.

Introduction

An organization can be defined as a group of people working together towards a common purpose or set of goals (Eknath & Gadekar, 2020). The people or the ‘human resources’ are therefore the greatest assets for most companies. The people drive the company towards its vision. Thus, it is only logical that every organization strives hard to keep their most valuable asset happy and satisfied at work. Life in contemporary organizations is interconnected, intertwined, and sometimes complicated, so we find in the vast majority of matters that most aspects of work are intertwined together and are affected by each other, directly or indirectly, positively or negatively, and to a large, medium or low degree. Hence, by studying the factors that mediate and moderate the employees’ satisfaction with their job and their desire to continue working for an organization the present study will contribute to the enhancement of the organizational environment and workplace productivity of the telecommunications businesses.

The factors that impact a person’s commitment and desire to work in an organization may be related to the industry and its specifics. For the UAE, telecommunications has been a government’s priority in terms of business development and support, and this sector is expected to grow substantially by 2025 (Mordor Intelligence, 2021). Hence, by studying the factors that mediate and moderate the employees’ satisfaction with their job and their desire to continue working for an organization the present study will contribute to the enhancement of the organizational environment and workplace productivity of the telecommunications businesses.

Likewise, we find that the scientific research conducted on today’s organizations deal with the study of some variables, whether they are independent, intermediate, or dependent, in order to know the type and degree of interrelationships among these variables, and you find that there are interrelated, and overlapping relationships between these variables (Smith, 2018). The current research will study the relationships between six variables as follows:

Person-Environment Fit
Psychological Capital
Job Satisfaction
Job Engagement
Organizational Commitment
Intention to Stay.

By looking at some of the related previous studies, the researcher found that they dealt with two or more of these variables, and that they found significant relationships between them (Abdullah et al., 2011; Smith, 2018). But the researcher did not find a single study interested in studying the relationships between all these variables at the same.

In a business context, the issues on improving job satisfaction and organizational commitment tend to be discussed most of the time, for example, by Aizzat et al. (2003) and others. This is because these elements have become a strategic driver for a successful business. In most organizations, they prefer to derive benefits in their way from their ethical efforts in the form of increased employee satisfaction and commitment; however, they yet have figured out how to do it successfully. However, some previous research studies showed that employee’s resignation from one organization only after a few months of work to seek another job did show an increase in number throughout recent years (Abdullah et al., 2019; Smith, 2018). The current study is concerned with determining the relationship between (P-E fit & Psychological Capital) and (Job Satisfaction & Job Engagement) and its impact on (Organizational Commitment & Intention to Stay) by conducting an applied research in the UAE ICT Sector.

Telecommunications as the Study Context

Firstly, to brief the readers on the specifics of the information and communications technology (ICT) sector in the UAE, it is necessary to look at its history, present, and future perspectives. According to Mordor Intelligence’s (2021) report, the compound annual growth of this industry will be at 3.5% by 2025. This rapid growth is attributed to the government’s focus on ICT as they have established policies that contribute to the development of these businesses, such as the 2003 Telecom Law. Additionally, Mordor Intelligence (2021) ITU News (2011), and TDRA (n.d.) report that the growth of ICT is associated with the end-user interest in telecommunications, mainly the internet and applications such as IoT, cloud computing, and others.

The ICT sector in the UAE has been growing exponentially in the past. As for the future, there are several initiatives, such as the Dubai Smart City or the introduction of the 5G connection across the state, which will contribute to the future growth of this industry (Mordor Intelligence, 2021). Notably, the COVID-19 pandemic has affected the ICT and contributed to the 1.5% decrease in the revenue of the ICT companies (Mordor Intelligence, 2021). However, the prospects for the future suggest that ICT will continue to grow and develop, as this is one of the centers of the government’s attention, which means that more people will be employed in the ICT-related businesses, and organizations’ leaders will have to look for strategies for effectively managing their human resources.

When looking at the history of the ICT sector in UAE, its establishment and further developments are linked to the introduction of Radio and other telecommunications technologies (TRDA, n.d.). Naturally, as the telegraph, telephone, and radio technologies became available in the UAE, both individual consumers and businesses began to use these technologies. However, until 2007 the industry’s development has been constrained as not much competition was present. In 2007 the government introduced its liberalization policies and created a licensing system that would allow more businesses to begin working in telecommunications (ITU News, 2011). Moreover, in 2010 based on the ICT Development Index, the UAE has been ranked as the state with the most developed infrastructure in this sector (ITU News, 2011).

The UAE ICT sector can be characterized by significant growth within the last decades, where the Telecommunications and Digital Government Regulatory Authority (TDRA, n.d.) is the main responsible party. The government of the UAE sets a high priority on the development and implementation of ICT in various spheres of life.

the UAE’s businssesbusinesses pay great attention to measuring the satisfaction of employees at the workplaces, the evidence is quite limited regarding the ICT sector. In their study, Murali and Aggarwal (2020) examine the impact of transformational leadership style on employee engagement and job satisfaction. The authors revealed that there is a strong positive correlation between the mentioned leadership style and employee engagement. Accordingly, it is assumed that higher employee engagement serves as a moderator of organizational commitment and person-environment fitP-E fit (Murali & Aggarwal, 2020). The study also demonstrates that employee engagement enhances the confidence of employees regarding their performance, which can be considered as a positive impact on psychological capital accumulation.

As for job satisfaction of employees as a mediating factor in the UAE ICT sector, the companies strive to use this concept to manage associated variables, such as person-environment fitP-E fit, organizational commitment, and intention to stay. However, the relationships between these variables and the mediating factor are not yet properly studied in this field. Abdulla et al. (2011) state that the collectivist culture of the UAE makes external and internal factors of job satisfaction important. Therefore, further studies are critical to establishing specific relationships between the above-mentioned variables so that the findings can benefit in adjusting the ICT sector workplaces through employee engagement and job satisfaction.

Statement of the Problem

Since the ICT sector is an important industry for the economic development of the UAE, research that contributes to the enhancement of workplace productivity and work effectiveness can help organizations’ leaders manage their workplaces more effectively. Mainly, work satisfaction, which is one of the factors that is studied in the present research, is associated with productivity and employees’ intention to leave an organization, as supported by evidence from the study by Wu and Norman (2004). Employees choosing to leave a company has two primary effects on the business (Mashuri & Maharani, 2019; Jiang et al., 2019; Sasso et al., 2019). The first one is the need to find a replacement for this position, which requires time and efforts of the H.R. specialist, meaning that the business loses money when an employee leaves due to the need of investing in the recruitment and training of a person who will replace them. Secondly, whilst a company is looking for a replacement for the position, it also loses money and productivity since other employees have to adjust their work to account for the tasks that should have been completed by an individual who left (Abo El Nasr, 2015; Saks & Gruman, 2014). As a result, an intention to leave and employees who choose to transfer to a different organization is an issue for the businesses is an issue. Companies can address it by implementing practices that will affect factors promoting employee retention. Hence, the problem that this study investigates is linked to organizational performance, costs, and companies in the ICT sector creative, effective workplace environments where employees’ intention to leave is mitigated.

The thesis will addresses the problems since it will answer the ultimate question of how an ICT company’s work environment can be adjusted to suit the needs of the employees and ensure that they are committed, satisfiedd, and do not have any turnover intentions.

Significance of the Study

This study is significant due to its contribution to the development and enhancement of work productivity of the companies in the ICT industry. As was mentioned previously, the Mordor Intelligence (2021) report suggests that the ICT sector is among the most important ones and fastest developing sectors in the economy of the UAE. Moreover, the government emphasizes the need to support the development of this economic sector, which is why studies that investigate workplace efficiency are important for this sector and the overall economic development of the UAE (Mordor Intelligence, 2021).

This study is also significant not only because of the importance of the ICT sector for the economic development of the UAE but also since businesses operate more effectively when their employees are committed, engaged, and satisfied with their work. For example, Abo El Nasr (2015) and Saks and Gruman (2014) examine the meaning and impact of human resources on the organization and argue that this is the most significant asset and that companies should invest in developing the tacit skills and knowledge, as well as on strengthening the bond between the professionals and their employer. This necessity is linked to the fact that professional skills do not mean that an individual will be working relentlessly or will engage in creative and innovative work for the benefit of the organization since they will not be motivated to do this.

Moreover, rResearch by Van Vianen (2018) suggests that there is a need to invest in hiring people whose values and views align with those of the organization because this means that the employee will understand the goals of the business and will work to ensure that the company achieves these. However, the author also notes that in most cases, the hiring decisions are the suboptimal choice between the values of the company and the individual and the latter’s skills and knowledge. This is where the importance of training and development, as well as strategies, to ensure commitment and engagement. There is evidently a link between the different organizational factors and employees’ behavior; however, the link between these elements is not well researched. The thesis will fix the issue by examining the moderation and mediation effects of the different variables.

Research ObjectivesPurpose Statement and Research Questions

The purposeobjective of this research is to understand the relationship between the following variables: (Person-Environment FitP-E fit & Psychological Capital) and (Job Satisfaction & Job Engagement) and its impact on (Organizational Commitment & Intention to Stay) in the context of the ICT sector in the UAE.. Moreover, this study will determine if these variables have a moderating effect on a person’s intention to stay in an organization. The goal is to provide recommendations for companies in the ICT sector understand how to manage their human resources in a way that would mitigate the employees’ intention to stay and therefore contribute to the productivity of work for the organization.

This research is guided by the following research questions:

RQ1: What is the relationship between person-environment fitP-E fit, psychological capital, job satisfaction, work engagement, organizational commitment, and intention to stay of employees in the UAE ICT Sector?
RQ2: How does job satisfaction play a mediating role in affecting the relationship of other variables?
RQ3: How does work engagement play a moderating role in affecting the relationship of other variables?
RQ4: How does work satisfaction correlate with the individual’s intentions to stay in an organization?
RQ5: How employees’ intention to stay is linked to their commitment and satisfaction with work, considering their psychological capital?

Research Gap

Table 1 below demonstrates the research gaps that characterize the existing studies on job satisfaction its moderating and mediating effects and how the present study will address these inconsistencies. Previous researchers have provided evidence of the relationships between:

Person-Environment FitP-E fit and Psychological Capital (Choi et al., 2019; Wang et al., 2021)
Person-Environment FitP-E fit and Job Satisfaction (Redelinghuys et al., 2020; Redelinghuys et al., 2019; Rocconi et al., 2020);
Psychological Capital and Job Satisfaction (Kun & Gadanecz, 2019; Aydin Sünbül & Aslan Gördesli, 2021; Diržytė & Perminas, 2021);
Job Satisfaction and Employee Engagement (Tepayakul, & Rinthaisong; Vorina et al., 2017)
Job Satisfaction and Organizational Commitment (Romi et al., 2021; Jigjiddorj et al., 2021)
Job Satisfaction and Intention to Stay (Jiang et al., 2019, Sasso et al., 2019, Mashuri & Maharani, 2019).

The analysis of literature provided above four central research gaps concerning the relationship of the six variables under analysis. These gaps are described in Table 1 below.

Table 1. Research gaps

Research gap	How this study will address this gap
Most articles describe a relationship between two or three variables (Luthans, 2004;, Luthans & Youssef, 2004; Darvishmotevali & Ali, 2020).	This research focuses on six variables that are all potentially linked to job satisfaction and intention to stay
There is no study that would investigate the relationship between different organizational factors and the intention to stay.	This study will examine the six factors in combination to have an in-depth investigation of the employees’ decision to stay
There are no studies that focus on the investigation of the moderating and mediating effects of the different workplace-related factors	The focus of this research is on the moderating and mediating effects
There are no studies that would examine the research variables in the context of the ICU industry of the UAE.	This research will address the problem by focusing on the ICU sector.

Definition of Terms

This paper focuses on the discussion of six central concepts, including P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay. This section aims at providing definitions of these terms based on previous research. The definitions are provided below:

Person-Environment Fit. The extent of compatibility between an individual and the environment (Tepper et al., 2018; Xiao et al., 2021).
Psychological Capital. An individual’s ability to apply the skills related to emotional intelligence and emotional competence in order to stay motivated (Tang, 2020).
Job satisfaction. Employees’ subjective level of content with his work and sense of accomplishment with performing their duties (Sironi, 2019).
Work Engagement. Positive behavior and attitudes of employees towards their work that lead to improved work-related outcomes (Diniyati and Sudarma, 2018).
Organizational commitment. The ability of the employee or staff members of the organization to stay and contribute well to their jobs for such a long term (Elsaearvy, 2005).
Intention to stay. Individual’s subjective estimated probability that they do not plan to leave leaving the organization at some point in the nearest future (Vandenberg & Nelson, 1999).

Chapter Summary

Today, companies around the globe view their employees as the key resource that ensures their competitive advantage. Thus, large corporations, as well as small companies, try to keep their employees satisfied and prevent turnover intentions. Recent research demonstrates that there are several factors that affect intention to stay and job satisfaction, including P-E fit, psychological capital, work engagement, and organizational commitment. While the research on the interrelations among these variables is abundant, no research examines the relationships among these six variables simultaneously. This research aims at evaluating the relationships between these variables using rigorous quantitative methods.

Another crucial contribution of this study is the assessment of inter-relationships among six variables, including P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay, in the context of the ICT industry in the United Arab Emirates. The telecommunication sector in the UAE es expected to grow rapidly in the nearest future due to the rapid development of technology and increased telecom use around the globe and in the UAE in particular. Thus, it is crucial for managers in the ICT sector in the UAE to have the latest knowledge concerning how to keep their employees satisfied and their turnover minimal. By analyzing the relationships among the six variables stated above, the research is expected to provide the managers in the ICT sector of the UAE with valuable insights concerning how to retain the employees and improve their intention by altering the workplace culture.

Before conducting this research, a thorough literature review concerning the relationships between the six variables was conducted. The literature review revealed four gaps in knowledge. The purpose of this study was to attempt to close these gaps using a sample of employees from the ICT sector quantitative methods of analysis. In order to achieve the purpose, five research questions were formulated. Additionally, we provided definitions of six variables to help the reader understand the essence of the concepts.

Another crucial contribution of this study is thea assessment of inter-relationships among six variables, including P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay, in the context of the ICT industry in the United Arab Emirates. The telecommunication sector in the UAE es expected to grow rapidly in the nearest future due to developed of technology and increased telecom use around the globe and the UAE in particular. Thus, it is crucial for managers in the ICT sector in the UAE to have the latest knowledge concerning how to keep their employees satisfied and their turnover minimal. By analyzing the relatioships among the six variables stated above, the research is expected to provide the managers in the ICT sector of the UAE with valuable insights concerning how to retain the employees and improve their intention by altering the workplace culture.

Before conducting this research, a through literature review concerning the relatioships between the six variables was conducted. The literature review revealed four gaps in knowledge. The purpose of this study was to attept to close these gaps using a sample of employees from the ICT sector quantitative methods of analysis. In order to achieve the prupose, five research questions were formulated. Additionally, we provided definitions of six varaibles to help the reader understand the essense of the concepts.

Literature Review

Introduction

The literature review below will investigateinvestigates the relationship between different organizational factors and their moderating effect on the job satisfaction and person’s intention to stay. As evident from the studies that will be presented, the majority of the research relevant to the topic is not recent and published more than five years ago, and none of the studies investigate the relationship between the six variables that are the focus of this research. Moreover, not many studies are dedicated specifically to the investigation of the human resource management practices pertaining to the ICT industry in the UAE, which is another research gap that this research aims to address.

The purpose of this literature review was to describe the current body of knowledge concerning the relationship between P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay. First, the section describes the strategy used for the literature search. Second, the literature review provides a discussion of theoretical frameworks utilized as the basis of the paper. Third, a review of variables organized by variables is provided. Finally, the literature review provided information concerning the available knowledge about relationships among the variables. The final section also includes hypotheses that will be tested in the results section. The purpose of this literature review was to describe the current body of knowledge concerning the relationship among P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay. First, the section describes the strategy used for literature search. Second, the literature review provides a discussion of theoretical frameworks utilized as the basis of the paper. Third, review of variables organized by variables are provided. Finally,

The information about the inter-relationship between the variables were used to formulate hypotheses, create a concept map, and describe the indicators.

Literature Search Strategy

The literature review was conducted on six different topics, which is consistent with the number of variables in the study. Literature search was conducted using the following keywords: ‘person-environment fit’, ‘psychological capital’, ‘job satisfaction’, ‘job engagement’, ‘organizational commitment’, and ‘intention to stay’. Additional words were used to supplement the six keywords, including ‘retention’, ‘workplace satisfaction’, and ‘intention to leave’. These keywords were searched in different combinations to find articles that assessed inter-relationships between variables of interest. These keywords were used for searching in different databases, including Research Gate, Google Scholar, JSTOR, and EBSCO. We included articles that released in 2017 and later to ensure that the knowledge was the most recent. We put increased emphasis on the articles that were published after 2018; however, some of the crucial sources were published before that year.

Before being including an article in the literature review, we read all the abstracts for papers to understand if they fit the topic of this thesis. After that, all the abstracts were printed out and labeled based on the most appropriate category, which were in accord with the variables explored in this paper. Some of the articles were included into several categories, as they described inter-relationships between two or more variables of interest. Such an organization of literature allowed us to manage the information in the most effective manner and to present the knowledge systematically.

Theoretical Background

Each of the variables that are discussed in this study has a theoretical background, linking it to the organizational performance and employee’s attitudes towards their employers. For example, the basic theory of the fit between the person and the environment studied by Anglin et al. (2018) and Guan et al. (2021) suggest that there is a set of inherent characteristics or values that an individual has, which either align with those of the company or do not. These values predetermine the attitudes and the ability of the person to work in a specific environment, which is linked to their performance, intention to leave, and commitment, studied by Kim and Yoon (2018), Kahn (1990) and others. Ultimately, each of these factors, as shown by the research in this literature review, has an effect on how the individual performs their duties and how they perceive their organization, which are crucial for the businesses’ success in the contemporary competitive environment, where the human resources are the vital sources of advancement.

Person-Environment Fit Theory

According to a P-E fit theory, there are reciprocal relationships between an individual and his or her environment, which means that both people and their contexts can impact each other. This theory postulates that a combination of individual resources and environmental factors identify the ability to adapt to changes (Morin, 2018). In terms of this theory, the fit between a person and environment predetermines a person’s behaviors and motivations (Anglin et al., 2018; Guan et al., 2021). This theory can be used as a theoretical framework to better understand the relationships between engagement moderating P-E fit and job satisfaction, intention to stay, and organizational commitment, as well as job satisfaction mediating the mentioned variables (Greguras & Diefendorff, 2009).

The personality dimension can be researched in terms of the amount of employee knowledge, skills, and competencies, while the environment can be considered as corresponding skills and abilities required for the work process (Yu, 2009). For instance, the discrepancy between the value of a person as an employee and his or her firm can serve to predict the intention to stay (Greguras et al., 2014). The characteristics of the environment can include income and opportunities from its side designed to meet the needs of employees, as well as requirements for their abilities (Chuang et al., 2015). For example, the workload may not meet the employer’s requirements, also posing a threat that the employees will not meet other requirements. Another potential implication of the identified theory is assessing to what extent an employee seeks to control the pace of work and to what extent this or her control is provided by technological capabilities (Schmidt et al., 2015). The organization, in turn, can take measures to address negative aspects and increase organizational commitment through greater job satisfaction (Lee et al., 2021). For example, an organization may change its approach to recruiting, promotion, and training.

AddiionallyAdditionally, the P-E fit theory introduces opportunities for creating a unique adaptive mechanism for individuals based on the developmental stage at which they are facing the necessity to change and acquire resilience toward the challenges within the target environment. For instance, Shen et al. (2018) and Wang and Wang (2018) suggest modifying the P-E fit framework toward the stage-environment fit so that respective changes could be made and so that individuals could gain the confidence and prowess needed to navigate the new setting. The described approach toward the P-E fit framework invites further possibilities for promoting motivation and the subsequent increase in retention rates in staff members by creating the environment that will suit their specific needs based on the unique stage of their personal and professional development (Calzo et al., 2020). Therefore, incorporating the theoretical perspectives that will enable managers to shape the context of the workplace setting to promote positive change in the staff is vital. Moreover, the P-E fit theory introduces the chance to connect P-E fit to the concepts of employee engagement and employees’ decision to leave (Xiao et al., 2021). Namely, the theory confirms that the change in the workplace setting toward a more comfortable one, particularly, the one that meets employees’ unique needs, is conducive to an improvement in retention rates and employee motivation along with employee engagement.

Affect Theory

An affect theory by Locke (1976) is another theoretical foundation that can be used to explain the chosen framework. This theory claims that job satisfaction is largely determined by the value people to assign to the various aspects of their work, as well as the extent to which their job-related expectations are met. Morin (2018) emphasizes that the underlying argument is that an individual’s values inform his or her expectations, while the discrepancy between the anticipated benefits and reality identifies either satisfaction or dissatisfaction. Regarding the target framework, the affect theory is beneficial to explore the intention to stay, psychological capital, and P-E fit, and organizational commitment.

The affect theory is valuable to utilize to better understand how employees identify and view their job satisfaction and associated workplace settings and changes. The key idea to be considered in future research is that the discrepancy between job requirements and an individual’s needs and abilities determines job satisfaction (Ahern, 2018). In addition, this theory states that the extent to which a person values one or another aspect of the job impacts his or her job satisfaction, while this impact can be either positive or negative. By using the affect theory as a framework, it would be possible to analyze the relationships between the identified variables in a more detailed and comprehensive manner.

Moreover, with the adoption of the affect theory, opportunities for examining the connection between motivation and the levels of employee engagement, as well as the extent of job satisfaction, emerge. Specifically, the affect theory allows connecting employees’ willingness to perform and improve to their emotional state (Ariani, 2015). As a result, a better management of employees’ engagement becomes possible (Singh, 2016). Furthermore, the affect theory suggests that, with the rise in emotional satisfaction and gratification obtained from performing workplace duties, staff members are likely to be less willing to resign (Osborne & Hammoud, 2017).

Person-Environment Fit

The concept of a person-environment fit (P–E fit)P-E fit is a crucial to proper business administration, particularly, the allocation of human resources. P-E fit can be identified as the extent of compatibility between an individual and the environment (Tepper et al., 2018; Xiao et al., 2021). Specifically, Andela and Van Der Doef (2018, p. 2) determine P-E fit as “the compatibility between an individual and a work environment that occurs when the characteristics are well matched.” Van Vianen (2018, p. 76) goes even further, suggesting that the specified definition should be simplified to the “compatibility between individuals and their environment.” The approach toward defining P-E fit offered by Van Vianen (2018) is quite strong, yet it could benefit from a greater nuance (Chang et al., 2020; Arias et al., 2020). In turn, Liu et al. (2019) complete the specified definition by adding the context of the work-life balance as the context in which the person-environment fitP-E fit framework should be placed, thus, providing the missing perspective. Specifically, the notion of the person-environment fitP-E fit implies the compatibility between a specific setting, which in the context under analysis is represented by the workplace environment, and individual characteristics such as culture, needs, social background, etc. (Mufti et al., 2019; Stich et al., 2019). The extent of compatibility between a persona and the environment determines the probability of a positive outcome (Sharf et al., 2017).

Psychological Capital

Another essential concept to be considered in relation to the subject matter, particularly, the P-E fit and the promotion of positive relationships in the workplace as the tool for enhancing the staff’s performance, psychological capital should be discussed. Darvishmotevali and Ali (2020) define psychological capital as the individual’s concern about the possible prospects that may occur in the future in regard to one’s career and the promotion opportunities (Maher et al., 2017). The specified point of view can be considered rather narrow since it involves mainly the perspective of an employee and does not allow for a comprehensive interpretation of the psychological capital, particularly, in the context of a specific organization.

In turn, Tang (2020) introduces the concept of the psychological capital from a slightly broader point of view, interpreting it as an individual’s ability to apply the skills relayteetd to emotional intelligence and emotional competence in order to stay motivated. Sameer (2018) contributes to the specified interpretation, confirming the importance of positivity in the workplace as a vital IE skill, similarly to Tsaur et al. (2019) and Çelik (2018). The described perspective appears to be more sensible given its potential for encompassing both the individual and the organizational standpoints on the issue of psychological capital (Gong et al., 2019; Mahfud et al., 2020). Therefore, the proposed interpretation of the psychological capital;, including the explicit knowledge and skills pertaining to the management of workplace situations derived from personal and professional experiences, needs to be deployed when addressing the issue of P-E fit. Therefore, it is vital for companies to invest in creating the environment in which staff members will be encourage and inclined to perform better (Aybas & Acar, 2017; Howard, 2017).

A recent study by Darvishmotevali and Ali (2020) investigated the effect of job insecurity, individual’s wellbeing, and their performance at work and the impact and mediating role that the psychological capital has on these factors. Mainly, job insecurity was found to have a negative effect on the person’s wellbeing and on their workplace productivity. Next, psychological capital can adversely affect job insecurity, psychological wellbeing, and work productivity (Darvishmotevali & Ali, 2020). Mainly. The idea behind this study was that an employee’s psychological capital could aid in them dealing with job insecurity, therefore resulting in their adequate wellbeing even in conditions where they do not have security. However, the findings suggest the opposite, although the limitations of this research, such as it being conducted with the hospitality industry employees, should be considered as well.

Job Satisfaction

Another critical concept that contributes to the development of a proper strategy for motivating staff members and allows building an environment in which they can succeed, job satisfaction needs further considerations. Being a rather subjective concept that depends not only on the presence of objective factors such as financial benefits, but also on a plethora of personal perceptions, the concept of job satisfaction is quite difficult to characterize (Qureshi & Hamid, 2017; Lim et al., 2017). However, multiple attempts have been made, some of the most successful being the representation of job satisfaction as “the level of contentment a person feels regarding his/her job and the sense of accomplishment he/she gets from doing it” (Sironi, 2019, p. 1724). Therefore, the notion of job satisfaction is tethered to the presence of emotional gratification that an employee receives from workplace performance. For this reason, considering job satisfaction as a critical variable in assessing the effects of P-E fit on the rates of organizational commitment and the intention to stay is necessary.

Remarkably, a range of scholars connect the concept of job satisfaction to the presence of a proper work-life balance. For example, Appelbaum et al. (2019), Prasetio et al. (2017), Kim and Yoon (2018), and Haski-Leventhal et al. (2019) insist that the described parameter is the fundamental notion in creating a positive workplace environment and ensuring that an employee feels comfortable in the organizational context. Ćulibrk et al. (2018), Demir (2020) and Abouraia and Othman (2017)also explain that job satisfaction is closely linked to the concept of organizational commitment and influences it directly, causing an increase in employee engagement and commitment with the rise in job satisfaction rates.

Work Engagement

Another essential notion that needs to be introduced in order to measure the correlation between P-E fit and the extent of organizational commitment, as well as the intention to stay, work engagement represents a major criterion.

There are several ways of approaching the notion of work engagement. Xiang et al. (2017) define work engagement as “a combination of work ability and willingness to work” (p. 240). Diniyati and Sudarma (2018) characterize work engagement by attributing the properties such as “vigor, dedication, and absorption” to it (p. 173). Although the described concepts as they pertain to the assessment of work engagement rates might seem synonymous, the researchers explain that the specified notions reflect different attitudes, specifically, the ability to focus on the job (absorption), loyalty to the company and the job (dedication), and excitement about the prospects of attaining key objectives (vigor) (Diniyati & Sudarma, 2018). Work engagement should not be confused with job satisfaction (di Stefano & Gaudiino, 2018). Representing the enthusiasm and motivation to perform (work engagement) as opposed to obtaining gratification from the obtained results (job satisfaction), work engagement requires the support of job motivation (Evitha et al., 2021). Since motivation defines the employees’ willingness to stay with the company, work engagement is vital in cementing their loyalty to the company and reducing turnover rates.

There are different definitions of employee engagement among different scholars, organizations, and different countries. The concept of employee engagement was first proposed by Kahn (1990) as the harnessing of organization members’ selves to their work roles; self-employment and self-expression of people physically, cognitively, and emotionally in their work lives (Nasurdin et al., 2018; El Junusi et al., 2021). Since Kahn proposed this concept, researchers have proposed different definitions which reflect a different understanding of employee engagement in each study, but this caused confusion for business management whether the efforts which improve employee engagement are working in all organizations (Çankır & Şahin, 2018; De Crom & Rothmann, 2018).

Kahn, William A.(1990) defined employee engagement as one who is fully absorbed by and enthusiastic about their work and so takes positive action to further the organization’s reputation and interests. Engaging employees is critical for retaining valuable talent and is an important piece of the employee satisfaction puzzle, as disengaged employees are more likely to leave their jobs (Geue, 2018). According to Forbes, employees who are engaged in their work are more likely to be motivated and remain committed to their employer (Paulise, 2020).

Organizational Commitment

When addressing the connection between the propensity among staff members to leave and the extent of P-E fit, one must also consider the issue of organizational commitment. The subject matter has been studied quite profusely lately, yet the phenomenon of organizational commitment has been defined comparatively recently. Started with the introduction of Meyer and Allen’s model of organizational commitment, the concept in question has been developed extensively in the 2000s.

Currently, the concept of organizational commitment is determined as the willingness of an individual to contribute to the development of a company and the accomplishment of its objectives, as well as the overall extent of engagement in the firm’s performance in the target market (Elsaearvy, 2005). The current study defines organizational commitment or employee commitment as the ability of the employee or staff members of the organization to stay and contribute well to their jobs for such a long term. Overall, organizational commitment can be defined as a positive feeling or commitment from employees towards their organization (Elsaearvy, 2005). Organizational commitment has three kinds, as following: emotional or affective commitment, normative commitment, continuance commitment.

Normative or ethical commitment refers to an individual’s feeling of an obligation to remain in the organization due to pressure from others, and because of moral or ethical and personal commitment to the organization and towards colleagues (Elsaearvy, 2005, 219 ).

Emotional or affective commitment indicates the strength of the individual’s desire to continue working because he or she agrees with all its goals and values, and he or she wants to participate in achieving those goals (Greenberg & Baron, 2007). Also, organizational commitment refers to the sincerity, love, and inclusion that an individual shows towards his or her work and the organization in which he or she works (Abo El Nasr, 2005, 45).

Furthermore, Continuance Commitment refers to an individual’s desire or his / her willingness to remain with the organization and to continue working in it because he or her expects that if he or her leaves work in it, it will cost him or her a great loss, meaning that continued commitment is based on the individual’s commitment to continue working in the organization as long as he or she achieves the benefits he or she needs (Greenberg & Baron, 2007, 216; Al-Madi et al., 2017).

Remarkably, the concept of organizational commitment is inherently connected to the levels of organizational performance in staff members (Lim et al., 2017). Indeed, multiple studies confirm that the rates of meeting workplace responsibilities and objectives in individuals hinge largely on the extent of organizational commitment (Nikpour, 2017). In fact, a range of researches indicate that organizational commitment represents the staff members’ extent of engagement and motivation (Al Zefeiti & Mohamad, 2017). Therefore, it will be reasonable to define the subject matter as the “degree to which an employee identifies with a particular organization and its goals and wishes to maintain membership in the organization,” as Ahad et al. (2021, p. 16) suggest. Overall, the evidence of connections between the extent of employees’ willingness to turnover and the rates of organizational commitment appears to be quite large, though further insights into the issue must be developed (Ahad et al., 2021). Specifically, both issues appear to be tied to the degree of comfort that an employee experiences when participating in workplace routine (Lambert et al., 2021). Therefore, the concept of organizational commitment needs to be seen as a vital part of the assessment of the possibility of an increase in employee turnover rates (Lambert et al., 2021). Thus, a strategy for managing the latter issue can be developed.

Intention to Stay

Intention to stay is a well-studied concept and scholars have explained it in various ways. The present study assumes that intention to stay and intention to leave are direct anthonymsantonyms, which implies that there is a direct negative correlation between intention to leave and intention to stay. As a result, all the research written about intention to leave can be applied to intetionintention to stay in a reversed manner.

Intention to leave is defined as an “individual’s own estimated probability (subjective) that they are permanently leaving the organization at some point in the near future” (Vandenberg & Nelson,: 1999, 1315).

Intention to stay is defined as the level of an employees’ emotional attachment and commitment to an organization that prevents them from turnover (Choi et al., 2021). Dadgar et al. (2013) defined intention to stay as “the probability of the from the second half of 2007 to the end of first half of staying of the staffs in the organization with the current situation of employment” (p. 1222). Aslam and Safdar (2012) made a valuable addition to the definition of the intention to stay by stating that inentionintention to stay is the employee’s willingness to stay with an employeeremployer on a long-term basis. The juxtaposition of the definitions confermsconfirms the assumption that intention to leave and intention to stay are direct opposites.

While inetionintention to stay is a significant predictor of leaving or staying with an organization, the actual decision to leave are not exactly the same concepts, as sometimes people are forced to leave their job or stay with the current employer due to enviroenmtnalenvironmental and personal factors (Dadgar et al., 2013). Therefore, there is a notable research gap in the specified area. In particular, links to P-E fit should be examined closer since they represent another gap in the current body of research.

Theoretical Framework

Hypotheses Formulation

Hypotheses

Person Environment Fit and Job Satisfaction

Previously conducted research on the relationship between these variables provides valuable insights as per the validation of the hypothesis. A meta-analysis conducted by Ahn and Lee (2019) was based on 15,589 employees whose person-environment fitP-E fit was analyzed against job-related variables. The scholars integrated person-organization, and person-job fit into the first variable, and job satisfaction, organizational commitment, and intention to stay into the second variable. The findings of the study indicated that there wasis a strong positive relationship between person-environment fitP-E fit and job satisfaction. Moreover, Redelinghuys et al. (2020), Redelinghuys et al. (2019), and Rocconi et al. (2020) validated the positive relationship between person-environment fitP-E fit and job satisfaction when it is reinforced by leadership or organizational culture. Similar findings were delivered by Deschênes (2020), who identified that among the components of person-environment fitP-E fit, the person-job fit was most vividly correlated with job satisfaction.

Moreover, the aspect of age influence on the relationship between the variables was addressed by Rauvola et al. (2019). This study identified that job satisfaction of older adults was more dependent on person-organization fit, while younger employees’ job satisfaction was more significantly influenced by person-job and person-group fit. A study by Gander et al. (2020) used a nationally representative sample of the employed adult population to measure the person-environment, and character strengths influence on job and life satisfaction. It was found that the stronger the character and the better the person-environment fitP-E fit, the higher the level of job and life satisfaction. Furthermore, other authors concentrated on the impact of person-environment fitP-E fit on job satisfaction in different fields of occupation and types of organization; the findings unanimously indicated a positive relationship between variable as found in federal employees, police officers, and project management professionals (Wang & Brower, 2018; Wang et al., 2020; White et al., 2021). Thus, the reviewed scholarly literature allows for supporting the hypothesis.

H1: There is a positive relationship between person-environment fitP-E fit and job satisfaction.

Psychological Capital and Job Satisfaction

Several studies have been found to provide information on the moderating influence of psychological capital, including optimistic worldview, self-efficacy, resilience, and family support, on job satisfaction. According to Kun and Gadanecz (2019) and Aydin Sünbül and Aslan Gördesli (2021), whose primary area of concern was the educational field and teachers’ job experience, psychological capital predetermines better job satisfaction. Valuable insight on the correlation between health outcomes and psychological money was contributed by Diržytė and Perminas (2021), who found that people with fewer health issues demonstrate a higher level of psychological wellbeing, implying better opportunities for life and job satisfaction. A similar field-focused safety-management-related research on the correlation between the two variables found a positive relationship between psychological capital and safety compliance (Ye et al., 2020). Similarly, using data collected from a female sample with the help of a self-reported questionnaire, Ganji and Johnson (2020) identified the positive effect of family support on women’s job retention and satisfaction. Furthermore, Huynh and Hua’s (2020) research on the factors influencing job satisfaction and organizational commitment using data from employees at small- and medium-sized enterprises in Vietnam found that job satisfaction and psychological wellbeing were essential determinants for job commitment.

H2: There is a positive relationship between psychological capital and job satisfaction.

Job Satisfaction and Organizational Commitment

Previous studies investigating the effect of job satisfaction on organizational commitment in various fields provide the basis for supporting the hypothesis. Indeed, according to Romi et al. (2021) and Jigjiddorj et al. (2021), higher levels of job satisfaction led to better organizational performance, compliance with corporate policies and culture, as well as a commitment to the job. Moreover, as found by Zhu et al. (2014), job satisfaction and commitment are the driving forces of sustainable organizational development; identified positive relationships between job satisfaction and loyalty were proposed for practical use. However, as found by Goujani et al. (2019), not all categories of employees as derived from the loyalty matrix have a higher commitment as a result of job satisfaction; namely, the category of hostage employees showed a low level of loyalty. Nonetheless, the positive effect has been persistent in a general population of the reviewed studies.

H3: There is a positive relationship between job satisfaction and organizational commitment.

Job Satisfaction and Intention to Stay

As the review of previous studies suggests, lower job satisfaction triggers a higher level of likelihood os staying with an employeer. According to Jiang et al. (2019), such factors as job satisfaction, payment, workload, and others, had a negative relationship with the intentions to resign, which implies that they were positively correlated with intention to stay. Similar findings were presented by Sasso et al. (2019) and Al-Muallem and Al-Surimi (2019), who identified that an increased level of nurses’ turnover and pharmacists’ intention to leave was highly dependent on diminished job satisfaction. Moreover, study results obtained by Mashuri and Maharani (2019) support the hypothesis and indicate a positive relationships between intention to stay and job satisfaction level. Since previous research findings provide relevant, verifiable, and credible data on the correlation between job satisfaction and the likelihood to to stay with an employeer, the following hypothesis was formed.

H4: There is a positive correlation between job satisfaction and intention to stay.

Engagement Moderating Person-Environment Fit and Job Satisfaction

One might assert that engagement moderates the relationship of dependence between the independent variable of person-environment fitP-E fit and the dependent variable of job satisfaction based on the anticipated increased value of person-environment fitP-E fit under the influence of engagement, which will ultimately affect job satisfaction, increasing it. Accordingly, managers can promote fit between jobs and employees to achieve organizational fit and improve job satisfaction. The awareness of managers of the moderating effect of engagement can serve as the foundation for implementing practical actions in terms of organizational design, as well as employee socialization and retention. However, person environment fit is not to be considered as a general agenda, but regarding fit perceptions, thus supporting employees on their developmental trajectories (Wang et al., 2020). By remaining aware of person-environment fitP-E fit and job satisfaction dependence, managers can successfully regulate the organizational mechanisms.

The evidence regards personal resources as predictors of job satisfaction, but scholars do not consider job engagement as a mediator of productivity and job satisfaction (Redelinghuys et al., 2019); Rocconi et al., 2020). Moreover, the range of psychological phenomena that correlate with work engagement or pretend to be prerequisites is wide enough, and their role is not clearly defined. For example, self-efficacy is associated with enthusiasm, and it can be both a prerequisite and an effect. Perhaps employees with more resilience are more capable of remaining interested in work and ready to overcome various difficulties in work, which correlates with resilience as a personal resource. Therefore, an in-depth understanding of engagement as a moderator requires additional theoretical and empirical testing that can be conducted in the future studies.

H5: There is a positive correlation between person-environment fitP-E fit and job satisfaction as moderated by engagement, which increases the value of person-environment fitP-E fit and job satisfaction.

Engagement Moderating Psychological Capital and Job Satisfaction

A positive change in the value of psychological capital, as an independent variable, will result in the consecutive positive change in the dependent variable, job satisfaction. Engagement, as a moderator in the causal relationship between the independent variable and dependent variable, might either increase or decrease their relationship. In this case, engagement can be regarded as a stable and deep emotional and motivational state affecting various mental processes, which does not focus on any specific object or form of behavior, but describe an employee’s attitude to work in general. It provides resources, such as physical, social, and organizational aspects, which help to facilitate work requirements associated with high psychophysiological and psychological costs (Kun & Gadanecz, 2019). For example, conflict resolution, overtime work, and stress are moderated through a high degree of engagement, which is essential to achieve the set work goals and stimulate the personal and professional growth of employees.

There is a need to investigate engagement as a moderator between psychological capital and job satisfaction. In particular, since the psychological capital is a resource of socio-psychological relations, due to which an employee is able to successfully achieve the intended goals, one should discover the connection between both dimensions. Despite the fact that both variables function in different ways in terms of a person’s job-related attitudes and behaviors, they should have the same result, such as an increase in the quality of a person’s work, therefore, a rise in job satisfaction (Aydin Sünbül & Aslan Gördesli, 2021). Moreover, the ability of engagement to either improve or deteriorate job satisfaction caused by psychological capital specifics is critical to study to gain the awareness of the issues to integrate or avoid in a workplace.

H6: There is a moderating effect of engagement on psychological capital, which, in turn, improves job satisfaction.

Engagement Moderating Job Satisfaction and Organizational Commitment

Since engagement is not a causal result of job satisfaction, it moderates the relationship between independent (job satisfaction) and dependent (organizational commitment) variables. There is a need to explore the relationships between organizational commitment and job satisfaction in the context of employee performance and engagement. Moral considerations compose one of the components of employee engagement. On the one hand, a satisfied employee is more likely to feel a moral obligation to act loyally to the company. On the other hand, the continuity obligation expresses the concept that the commitment to work is dependent on the balance of costs and benefits for a certain employee. Future research is necessary to identify various methods and strategies to increase organizational commitment through improving the job satisfaction of employees. These include strategies in which employees can work together in a way that creates a strong bond. Those who feel a strong attachment and connection to the workplace demonstrate a higher level of commitment to the organization (Jigjiddorj et al., 2021; Romi et al., 2021). Based on the results obtained, a number of recommendations for the development of employee commitment can be made.

H7: Engagement moderates causal relationships between job satisfaction and organizational commitment, where the latter depends on the former.

Engagement Moderating Job Satisfaction and Intention to Stay

Past studies indicate that there is a correlation between the levels of engagement and, therefore, the willingness of an employee to stay. Specifically, the hypothesis concerning high engagement rates being correlated postivelypositively with job satisfaction and intention to stay is supported by the studies by Warr and Inceoglu (2012) and Skaalvik and Skaalvik (2014). However, the current body of knowledge indicates that there is a gap in the analysis of the subject matter. Furthermore, Kassing et al. (2012) also insists on the connection between employee engagement and the intention to stay by pointing out that low levels of motivation negatively affect intention to stay.

Since there is a positive relationship between job satisfaction and intention to stay, the value of engagement as a moderator between independent (job satisfaction) and dependent (intention to stay) variables will predetermine the relationship between the variables. It is important to identify the role of engagement in the impact of low job satisfaction on an employee’s search behavior, which the degree of his or her activity in looking for alternatives and considering proposals for other jobs. An unsuccessful search for alternatives positively affects the employee’s intention to stay in the organization, and a successful one strengthens the intention to leave (Mashuri & Maharani, 2019). Future research should be devoted to comprehensively considering organizational and personal factors that determine the departure or continuation of work in the organization. In particular, a hypothesis is that low job satisfaction negatively correlates with the intention to stay because of an unfavorable psychological atmosphere in the workplace, the tension in professional responsibilities, and dissatisfaction with the leadership, which determine the extent of engagement (Choi et al., 2021).

In turn, increased attention to workplace relationships, stress at work, and comfort for the employee is a characteristic feature of this issue, which allows assuming that an organization can influence the decision of employees to stay, creating a favorable atmosphere aimed at retention of employees in the company and developing a sense of organizational citizenship in employees (Jiang et al., 2019). The stimulation of their engagement in the life of the company can be explored based on care demonstration, provision with access to timely and relevant information, and training in the workplace.

H8: Engagement as a moderator predetermines the relationships between job satisfaction and the intention to stay an organization.

Job Satisfaction Mediating Person Environment Fit and Organization Commitment

Since there is a positive relationship between person-environment fitP-E fit and organizational commitment, job satisfaction might be regarded a mediator between the variables. This is because as was discussed in the literature review, the person-environment fitP-E fit theory and commitment are pertaining to the individual’s choice of a suboptimal workplace that would align with their values and expectations. However, the extent of one’s job satisfaction may affect the person’s overall perception of their work and therefore mediate their view. The connection between the levels of P-E fit, organizational commitment, and the presence of job satisfaction in staff members has also been addressed in the studies by Ahmad (2012) and Gul et al. (2018) correspondingly. Mentioning the specified variables in tandem, the authors indicate that there is a link between them, yet further correlation is to be examined more closely. Thus, a notable research gap can be observed.

H9: There is a positive impact of job satisfaction as a mediator on person-environment fitP-E fit (an independent variable), resulting in organizational commitment (a dependent variable) since a satisfied workforce is more likely to perform optimally and remain loyal to an organization.

Job Satisfaction Mediating Person-Environment Fit and Intention to Stay

Job satisfaction is a mediator in the P-E fit and intention to stay relationship since P-E fit predetermines job satisfaction, which ultimately affects intention to leave (Anglin et al., 2018; Guan et al., 2021). The relationship between these variables is linked to an individual selecting an environment for work where they will be satisfied with the work conditions and the perspectives and therefore, their intention to look for a different position should be low (Anglin et al., 2018; Guan et al., 2021). Specifically, papers by Ahmad (2012) and Shah et al. (2015) confirm that job satisfaction has an influence on the P-E fit levels, as well as the willingness to retire.

H10: There is a positive relationship between a high P-E fit (an independent variable) and intention to stay (a dependent variable) as job satisfaction mediates a P-E fit as a dominant force in one’s career.

Job Satisfaction Mediating Psychological Capital and Organization Commitment

Job satisfaction is a mediator between psychological capital and organizational commitment due to the dependence of job satisfaction on psychological capital, which generates organizational commitment (Romi et al., 2021; Jigjiddorj et al., 2021). The exploration of this variable is especially interesting since the literature review suggests that in some industries, psychological capital does not affect satisfaction and with one’s work and organizational commitment.

H11: There is a mediating role of job satisfaction regarding psychological capital (an independent variable), the amount of which impacts the level of organizational commitment (a dependent variable).

Job Satisfaction Mediating Psychological Capital and Intention to Leave

The mediating effect of job satisfaction on psychological capital and intention to leave is validated by the dependence of job satisfaction on psychological capital; job satisfaction level predetermines intention to leave (Jiang et al., 2019, Sasso et al., 2019, Mashuri & Maharani, 2019). This mediating effect will help understand whether one’s psychological capital strengthens a person’s intention to leave an organization or vice versa, where it supports there decision to work in an environment where their satisfaction with work is low.

H12: Job satisfaction as a mediator enriches psychological capital (an independent variable), which reduces the intention to leave (a dependent variable) since having meaningful job experiences is attractive to employees.

Concept Mapual Framework

In the light of the previous research studies , the research statement and the research concepts it can be introduced the following conceptual framework which determines the research variable as shown in Figure 1.

Specifically, Fig.ure 1 points to the correlation between the extent of moderation and the rates of mediation. Namely, the extent of engagement rates in employees, among other factors, appears to be affected heavily by the presence of motivation. More importantly, the connection between P-E fit and the extent of psychological capital in the organizational setting appear to be in direct correlation to each other, as Fig. 1 shows. Furthermore, the correlation and causation between P-E fit and the increase in psychological capital appears to be mostly confirmed, as the table below illustrates. Specifically, due to the development of the approach to managing the human resources in the way that allows them to be placed in the setting where they feel most comfortable, the opportunities for avoiding conflicts, misunderstandings, mismanagement of information, and the related issues can be created ().

Conceptual Framework - Variables and Their Connection — Figure 1. Conceptual Framework – Variables and Their Connection

Indicators

Indicators of Person Environment Fit in the Current Study:

Person–Organization Fit
Person–Job Fit
Person–Group Fit
Person–Person Fit

Indicators of Psychological Capital in the Current Study:

Self-Efficacy
Optimism
Hope
Resilience

Indicators of Job Satisfaction in the Current Study:

Salary and incentives
Work Relations
Employment empowerment
Physical work environment

Indicators of work relations in the current study, for example:

Work relations with colleagues
Work relations with superiors
Work relations with subordinates
Work relationships with clients or with public.

Indicators of Employee Engagement in the Current Study:

Vigor
Dedication
Absorption

Indicators of Organizational Commitment in the Current Study:

Emotional or Affective Commitment
Normative or Ethical Commitment
Continued Commitment

Emotional or Affective Commitment:

Phrases of emotional or affective commitment in the current study, for example:
- I have a strong feeling of belonging to that organization for which I work.
- I feel emotionally attached to this organization.
- I feel like a family member of that organization.
- I would be very happy if I spend the rest of my life working in this organization.

Normative or Ethical Commitment:

Phrases of normative or ethical loyalty job in the current study, for example:
- I feel obligated to stay in the organization due to pressure from others.
- I feel compelled to stay in the organization in order not to leave a bad impression on my colleagues because I left my work.
- I have a moral and personal obligation to remain in this organization.
- This organization has a merit over me, and it is not ethical in general and work ethics to leave work in this organization.

Continued Commitment:

Phrases of job satisfaction in the current study, for example:
- I see the need to continue working in this organization.
- Working in this organization brings many benefits to me.
- Leaving this organization is costing me a lot.
- I need to continue with this organization because I cannot bear the burden of living otherwise.

Indicators of Intention to Stay in the Current Study:

Employee’s perception of organization support
Employee’s perception of organization commitment
Employee’s perception of job satisfaction
Employee’s perception of job engagement

Chapter Summary

The literature review demonstrated that the concepts discussed in the present paper are a matter of increased interest among scholars. Numerous papers were found on the topics of P-E fit, psychological capital, job satisfaction, job engagement, organizational commitment, and intention to stay. However, despite the abundance of evidence, four gaps in literature were identified. First, most of the articles found for this review described a relationship between two or three variables. Second, no empirical studies were found that would investigate the relationship between different organizational factors and the intention to stay. Third, no research was found that focused on the investigation of the moderating and mediating effects of the different workplace-related factors. Finally, no recent studies on the topic of interest examined the research variables in the context of the ICU industry of the UAE.

In order to close the literature gap, this study discusses the inter-relationships of multiple six variables using test for both direct and indirect influence. A total of twelve hypotheses were formulated using results of previous research provided in this literature review. The hypotheses presupposed investigation of direct relationships as well as moderation and mediation models. The chapter also introduced a concept map and indicators for differentall the variables.

Methodology

Introduction

This section focuses on the description of methods utilized to acquire the research results and draw conclusions. The methodology section is of extreme importance for research, as it provides information to the reader what steps should be done to repeat the results of the research (Gill & Johnson, 2010). Researchers often write this section first, as it is the most objective part of the paper that serves a as backbone for all the other sections of the paper (Kallet, 2004). The methodology section allows the experts understand if the utilized methods were adequate for answering the research questions (Dagnino & Chinici, 2015). Additionally, the methodology section helps the reader to understand if the utilized methods could lead to the biased results (Dagnino & Chinici, 2015). Thus, it is crucial to describe the methodology of a study with maximum detail to avoid any uncertainties or misinterpretations.

The section is subdivided into several subsections, including research design, research paradigm, sampling, instrumentation, data collection methods, and data analysis. In the first subsection, we provide justification of utilizing a quantitative approach to the research and utilization of primary data rather than secondary data. The second subsection describes different research paradigm and justifies the use of positivistic paradigm for this paper. The third subsection describes the population under analysis and the sampling methods used to recruit the participants. This subsection lase includes inclusion and exclusion criteria. The fourth subsection describes the instruments used for data collection and justifies their use. The fifth subsection describes the data collection procedure used for acquiring the primary data. The sixth subsection describe the data analysis techniques used to arrive at conclusion. The section is concluded with a chapter summary that describe the crucial point of the methodology section.

Research Design

Method Selection

A quantitative approach is the most appropriate method for the present study. According to Abo El Nasr and Medhat (2017), the use of quantitative research is appropriate when a researcher needs to test a hypothesis. In contrast, qualitative research aims to gain a better understanding of a problem or a phenomenon that has not been clearly defined (Saunders et al., 2019). Qualitative studies to identify problems in the general area of interest for future research to focus on specific issues (Copper & Schindler, 2014). Quantitative research is usually based on the results of qualitative research and provides specific answers to narrow questions (Saunders et al., 2019). Quantitative research methods allow high breadth of the research, as numerous participants can be involved in a study (Copper & Schindler, 2014). However, questions that are answered by quantitative research are to be very specific. At the same time, quantitative research does not allow acquiring in-dept insights from the analysis, as the research design does not aim at explaining facts acquired from the analysis.

Qualitative approach is the opposite to the quantitative research methods. In contrast to the quantitative approach, qualitative research aims to gain a better understanding of a problem or a phenomenon that has not been clearly defined (Saunders et al., 2019). Qualitative studies identify problems in the general area of interest for future research to focus on specific issues (Copper & Schindler, 2014). Qualitative design allows the research to collect unstructured information concerning the feeling, emotions, and attitudes towards the phenomena of interest (Creswell, 2007). However, qualitative design does not allow to collect data from a wide variety of participants to acquire knowledge from a broad sample (Creswell, 2012). Usually, the number of participants in the qualitative studies is limited to 10-30 participants (Creswell, 2007).

Another approach to research design is the mixed-method approach, which combines both qualitative and quantitative research methods. A mixed-method approach allows enjoying the benefits of both research methods (Saunders et al., 2019). When using such an approach, researchers can explain the results of quantitative analysis with the results of the qualitative analysis (Saunders et al., 2019). In this case, qualitative research design supplements the quantitative research design. However, there is significant danger that the mixed method may lead to confusion, as the researchers need to control for the drawbacks of both research methods.

A quantitative approach is associated with the analysis of numeric data, while a qualitative approach relies on non-structured data (Copper & Schindler, 2014). Thus, quantitative research relies on surveys as the primary source of data, while qualitative studies collect data through interviews, focus groups, and observations (Saunders et al., 2019).

A quantitative approach iswas identified as a more appropriate approach, as it requires a clearly formulated research and rigorous methodology aimed at testing the identified hypotheses Copper & Schindler, 2014). The literature review revealed that information on the topic is abundant; however, it is not specific enough to apply to the ICT sector in the UAE. In other words, this research does not aim at gaining information about the feeling and attitudes of participants, which implies that the qualitative approach is inapplicable. A mixed-method approach was considered as an alternative to using qualitative data only. However, it was decided against using a mixed-method approach due to the redundancy of information. A mixed-method approach is usually used when a researcher needs to explain the qualitative results (Copper & Schindler, 2014). In this research, we did not aim at explaining the results of the quantitative research. Instead, Tthe purpose of this research is to increase the generalizability of previous findings. The explanations have already been given by previous studies, as demonstrated in the literature review.

When describing the methodology, it is crucial to distinguish between primary and secondary research methods. Primary research methods include surveys, interviews, focus groups, and observations, while secondary research methods include online research using publicly available data, literature reviews, and case studies (Saunders et al., 2019). Since data in open access on the topic of interest was scarce, secondary research methods were not considered for the present research.

Surveys are used to gather information from a defined population group (Creswell, 2007). The survey results are relatively simple to quantify; therefore, surveys are used primarily in quantitative research (Cooper & Schindler, 2014).

Interviews are helpful for receiving meaningful insights from experts in the sphere of interest (Creswell, 2007). Even though interviews may be difficult to analyze, they are a vital source of information for qualitative research (Hair, 2015). Focus groups are another source of data for researchers using the qualitative approach, as participants in the focus groups have a common background and can express their feelings and share their experiences freely (Saunders et al., 2019). Observations can be used for both qualitative and quantitative research, as they can provide crucial information from the natural environment without interacting with the participant directly (Creswell, 2012).

Since the research design of this paper is quantitative, surveys and observations were considered as primary data sources. Observations are usually used to learn behavior and values through reading, listening, watching, and touching objects, beings, or phenomena (Creswell, 1994). Observations are crucial when the researcher needs to collect information without disrupting the natural environment (Hair, 2015). Additionally, the method may be crucial for understanding non-verbal behavior, which is a significant part of organizational culture. However, the drawbacks, such as the inability to learn about the past and lack of control, made the data collection method difficult to use for achieving the purpose of the present research. Thus, surveys were used as the central data collection method for the study. Surveys allowed the researcher to collect viable information on the variables of interest in a cost-efficient manner.

Research Paradigm

Aligning the research paradigm with the purpose and methods is crucial for answering the research questions in the most suitable and accurate manner. According to Kuhn (1970), a research paradigm is “the set of common beliefs and agreements shared between scientist about how problems should be understood and addressed” (p. 47). Research paradigms are differentiated based on researchers’ responses to three basic questions, including ontological, epistemological, and methodological questions. The ontological question is the researcher’s view on reality and the nature of the knowable. The epistemological question explains the relationships between the knowable and the inquirer. The methodological question explains how the inquirer needs to manipulate the reality to acquire knowledge about the desired subject. In other words, research paradigms provide the community of researchers with a specter of research questions that should be asked and instruments that can be used to answer these questions (Kuhn, 1970). Babbie (1998) states that these responses cannot be right or wrong; instead, they are either suitable or not suitable depending on the study’s design, purpose, and research questions.

Three possible paradigms were considered for answering the research question, including positivism, constructivism, and pragmatism. Uyangoda (2015) states that positivism presupposes that there is one single reality that can be measured and known due to objectivity of the world. When utilizing positivism as the primary paradigm for a study, researchers are expected to act in an unbiased manner and deduct the cause-and-effect relationships using context-free methods (Babbie, 1998). Positivists usually utilize quantitative research methods as they allow to measure the reality with high precision, minimize data collection and analysis biases, and help to test cause-and-effect relationships.

Constructivism is the opposite worldview when compared positivism (Kuhn, 1970). In particular, constructivism assumes that there are multiple realities that coexist and require interpretation. Researchers that adopt this paradigm utilize qualitative methods, as they interact with the phenomenon of interest and gather data using biased methods, such as interviews and focus groups. The researchers that adopt constructivism as the primary approach to conducting a study utilize data analysis methods that allow much variation in interpretations.

Pragmatism presupposes that reality may be renegotiated and interpreted, which implies that the methods that should be used depend on the purpose of the study. According to Babbie (1998), pragmatists believe that both qualitative and quantitative methods can be used if they solve the problem. Pragmatism is usually used for mixed-method research, as the methods utilized in one study are conflicting.

This researched utilized the positivists’ viewpoint as the paradigm for the present paper. This research aimed at assessing cause-and-effect relationships using rigorous quantitative methods. These methods can be applied only if the researcher believes that there is only one reality that can be understood using empirical methods. Positivism assumes that the reality can be measured using mathematical methods, and this research intends to collect and analyze numeric data, which is in accord with the positivists’ paradigm.

Instruments

A total of eight instruments will be used to measure the variables. The first instrument will include four questions about general demographical characteristics, including age, gender, marital status, and education level. The second instrument will provide information concerning job data. A self-crated questionnaire will be used. Third, the Perceived Person-Environment FitP-E fit Scale (PPEFS) will be used to measure P-E fit. It is a 19-item questionnaire based on a seven-point Likert scale (Chuang et al., 2015). Fourth, a modified Psychological Capital Questionnaire (PCQ) will be used for measuring Psychological capital. Instead of 24 questions in the original PCQ, the modified version will have only 23 questions (Luthans, 2007).

Fifth, the Organizational Commitment Questionnaire will be used to measure organizational commitment (Mowday, 1979). It is a high-validity instrument based on a seven-point Likert scale. Sixth, a short for of Minnesota Satisfaction Questionnaire (MSQ) will be used to measure job satisfaction (Minnesota Satisfaction Questionnaire, n.d.). The questionnaire contains 20 questions based on a five-point Likert scale. Seventh, work Engagement will be measured Work and Well-Being Survey (UWES). It is a 17-question questionnaire also based on a five-point Likert scale (Schaufeli & Bakker, 2004). Finally, intention to stay will be measured using the Michigan Organizational Assessment Package, consisting of three questions (Survey Research Center, 1975). A reversed scale will be used to measure the variable, as the questionnaire is intended to measure the intention to leave.

In summary, the total number of questions in all instruments is 95, which implies that a participant will need approximately 20 minutes to finish the survey. All the instruments have high validity, confirmed by numerous research. Thus, the instruments used for the present study are a significant strength.

Population and Sampling

Sampling

The population under the analysis of the present research includes all employees of the ICT sector in the UAE. In other words, the population includes the employees of the Telecommunications Regulatory Authority and Digital Government (TRADG), Etisalat, and du. The information about the number of employees of the TRADG is not provided in the open-source; however, it was estimated that the current number of employees in the governing body is 1,000. The current number of employees of Etisalat is 43,000 (Owler, 2021). In 2018, the approximate number of du’s employees was 4,000 (du, 2019). Thus, the total size of the population under analysis is estimated at 48,000.

The sample size was estimated to be 119 using the formula provided by Cochran (1977). The formula, assumptions, and calculations are provided below.

Where:

t = t-value corresponding to the alpha level;
s = standard deviation in the population;
d = acceptable margin of error for mean being estimated.

The selected margin of error was 3%, as it appears appropriate for the studies of such purpose (Cochran, 1977). Thus, the acceptable margin of error of the mean being estimated can be calculated by multiplying the seven-point scale by the margin of error. Standard deviation was estimated by dividing the full point scale by the range. Since a 7-point scale is used for the majority of measurements, the range is 6, and the estimated standard deviation is 1.167. Thus, the sample size can be calculated the following way:

Stratified sampling was used to recruit participants. Stratified sampling is a random sampling method that aims at recruiting an unbiased sample of participants from all the groups present in a population (Saunders et al., 2019). In order to use the stratified sampling method, a researcher needs to divide the total population into strata by using simple probability sampling in each of the strata (Abo El Nasr & Medhat, 2017). The benefit of stratified sampling is that it guarantees that all the subgroups of the population will be represented in the sample appropriately.

At first, it was considered to use simple random sampling; however, it was decided that the method would lead to increased bias. The problem with simple random sampling is that it can overrepresent some subgroups in the population (Cohran, 1977). Stratified sampling provides better precision than simple random sampling, it is more cost-effective and can allow the analysis of separate subgroups (Cohran, 1977). The population under analysis consists of employees from three organizations. Thus, it would be appropriate to make a stratum out of every organization.

There were several inclusion criteria that should be mentioned. First, all the unfinished questionnaires were excluded form the analysis, which implies that only fully finished questionnaires were included in the analysis. Additionally, the participants had to be employed in the ICT sector and have at least six months of experience working in the industry. No other inclusion criteria were established for this study.

Instrumentation and Operationalization of Variables

A total of eight instruments will be used to measure the variables. The first instrument had four questions about general demographical characteristics, including age, gender, marital status, and education level. The second instrument provided information concerning job data. A self-created questionnaire will be used. The first two instruments were based on the standard questions used by researchers when measuring the demographics of the sample. The data acquired from the first two instruments was used to understand if any bias was present associated with the composition of the sample.

Third, the Perceived P-E fit Scale (PPEFS) was used to measure P-E fit. It is a 19-item questionnaire based on a seven-point Likert scale (Chuang et al., 2015). PPEFS is based upon the assumption that P-E fit is based upon three dimensions, including person-job fit, person-organization fit, and person-supervisor fit (Chuang et al., 2015). The scale includes a total of 19 questions that ask the responder to identify how the feeling described in the statements matched to the participant’s attitudes. The questionnaire is associated with high validity that was confirmed by numerous empirical studies in different spheres and industries (Etzel & Nagy, 2016).

Fourth, a modified Psychological Capital Questionnaire (PCQ) will bewas used for measuring Psychological capital. Instead of 24 questions in the original PCQ, the modified version will have only 22 questions (Luthans, 2007). The reason behind decreasing the number of questions was the researcher’s inability to access the full version of PCQ, as it was not in the open access. There are two version of PCQ, including the full version that includes 24 questions (PCQ-24) and the shortened version of the questionnaire that included 12 questions (PCQ-12). Both questionnaires were confirmed to have high validity for measuring the psychological capital (Cid et al., 2020; Kamei et al., 2019). The questionnaire utilized for measuring the psychological capital asked the participants to measure the level of their agreement to the provided statements using a six-point Likert scale.

Fifth, the Organizational Commitment Questionnaire was used to measure organizational commitment (Mowday, 1979). It is a high-validity instrument based on a seven-point Likert scale. The questionnaire asked the responders to indicate their level of agreement and disagreement with 15 statements. Even though no recent research was found that used the questionnaire to measure organizational commitment, the instrument had successfully been used in earlier research for the same purpose (Kanning & Hill, 2013).

Sixth, a short for of Minnesota Satisfaction Questionnaire (MSQ) was used to measure job satisfaction (Minnesota Satisfaction Questionnaire, n.d.). The questionnaire contains 20 questions based on a five-point Likert scale. The questionnaire is used successfully in modern research, and its validity is well-established (Bello et al., 2020).

Seventh, work engagement was measured Utrecht Work Engagement Scale (UWES). It is a 17-question questionnaire also based on a five-point Likert scale (Schaufeli & Bakker, 2004). The validity of this instrument is also well-established, as it is used in the recent research for measuring the engagement of employees in the work process. The instrument was used successfully by researchers in the education sphere; it may was also used successfully in other industries (Serrano et al., 2019).

Finally, intention to stay will bewas measured using the Michigan Organizational Assessment Package, consisting of three questions (Survey Research Center, 1975). A reversed scale was used to measure the variable, as the questionnaire is intended to measure the intention to leave. This paper presupposes that intention to stay is the directly negatively correlated with the intention to stay, which implies that the reversed scale could measure intention to stay accurately.

In summary, All the instruments have high validity, confirmed by numerous studies. Thus, the instruments used for the present study were assumed to be a significant strength. The total number of questions in all instruments totaled at 95. The participants needed between 20 and 30 minutes to finish all the questions, which affected the percentage of the finished surveys. Only 62.5% of all respondents finished the survey, while 37.5% failed to answer all the questions. Thus, the number of questions decreased the number usable responses significantly.

Each variable was measured using a sum of scores for all the questions in the instrument. For instance, P-E fit was measured by adding the scores of all 19 question of the PPEFS together. Similarly work engagement, was measured by adding the scores of UWES together. The only variable that was measured differently was intention to stay, as we intended to use the reverse scale. Before adding the scores together, the researcher converted all the answers to the reversed scale by switching ‘1’ with ‘5’, ‘2’ with ‘4’, ‘4’ with ‘2’, and ‘5’ with ‘1’ by hand. After that, the answers were added together to measure intention to stay.

Data Collection Procedure

Data utilize for present research will bewas collected automatically using online questionnaires. The utilization of online questionnaires instead of phone or in-person surveys increased the effectiveness and accuracy of the data collection procedure. According to Ball (2019) there are both advantages and disadvantages of online surveys. On the one hand, online surveys are associated with low cost, high speed of reach, flexibility, and automation (Ball, 2019). Additionally, online surveys are preferred by the participants and the entry error possibility are reduced to minimum (Ball, 2019). However, there are also disadvantages that include the inability of a participant to ask questions if they are unclear. Additionally, the online surveys are vulnerable to survey fraud, as participants can complete the survey several times and enter erroneous data deliberately (Ball, 2019). Careful assessment of possible drawbacks revealed that the possibility of their influence was minimal. Thus, it was decided in favor of online survey use as the primary data collection method.

The employees willparticipants be were recruited using businessinternal emails of employees. The researcher will contacted the HR departments of three organizations using email and phone calls. We explained the representatives of the HR department the purpose of the study and asked them to distribute the questionnaire among the employees. The HR managers were also sent invitation letters and detailed description of how the employees could withdraw from the study and what benefits they will receive. The HR managers were also informed about the possible dangers associated with conducting the research.The HR department will be explained the purpose of the study and ask to provide a list of personal emails of the employees. After that, recruitment letters will be sent to the employees with explanations of the research and an informed consent form. The emails to HR managers also contained links to will contain a link to Survey Monkey, an online surveying platform that allows easy and secure primary data collection tool.

All the collected information will bewas stored on Survey Monkey’s server until the completion of the survey. As soon as the required number of responses iswas acquired, the data collection procedure will bewas stopped. All the informationthe data will be was downloaded to a laptop protected by a password. The collected information will notdid not contain any personal data as an additional measure of protection. After the data wasis downloaded, it will bewas cleaned and analyzed using the methods described below in this paper.

Data Analysis Methods

Data AnlaysisAnalysis Methods

The data will bewas analyzed using Statistical Package for Social Sciences (SPSS) version 25. The research utilized a wide variety of statistical methods, including descriptive statistics, Pearson’s correlation analysis, simple mediation model, and simple moderation model. Descriptive statistics was used to understand the characteristics of participants included in the sample. Frequency tables were created and to analyze if there were any bases associated with the sample characteristics. Additionally, descriptive statistics was used to assess if the data was normally distributed, which is crucial for the correlation analysis (McClaive et al., 2018).

Pearson’s correlation analysis was used to test Hypotheses 1-4, which focused on the correlation between person-environment fit and job satisfaction, capital and job satisfaction, job satisfaction and organizational commitment, and between job satisfaction and intention to stay. There are two primary methods used for correlation analysis of numeric data, which are Pearson’s correlation analysis and linear regression analysis (McClaive et al., 2018). The primary benefit of Pearson’s correlation analysis is its ease of interpretation. However, Pearson’s correlation analysis is rarely used, as it does not allow to quantify the effect of several independent variables on one dependent variable (Gogtay & Thatte, 2017). This research did not intend to create complicated models assess the magnitude of the effect of several independent variables on one dependent variable. Thus, Pearson’s correlation analysis appeared the most appropriate approach to testing the hypotheses.

Hypotheses 5-8 were tested using simple moderation model conducted with the help of Hayes’s (2013) PROCESS macro for SPSS. Moderation models are created when there is a strong possibility that the relationship between two variables is affected by the presence of a third variable. Simple moderation analysis does not take into consideration any control variables are additional moderation variables that may have an effect on the dependent variable (Igartua & Hayes, 2021). Instead, the model presupposes that there is only moderation variable that affects the relationship between independent variable and one dependent variable.

Hypotheses 9-12 were tested using simple mediation analysis that in the PROCESS macro for SPSS. According to Igartua and Hayes (2021), this model is used one there is a strong suspicion that an independent variable influences the dependent variable through a third, mediating variable. Simple mediation model used for this research assumed that there was only one mediating variable that affected the relationship between one independent variable and one dependent variable.

The primary statistical methods will include descriptive statistics to understand the basic characteristics of the sample, Pearson’s correlation analysis, and regression analysis. Additionally, a total of 4 mediation and moderation models will be created using Hayes’s (2013) PROCESS macro for SPSSThis study utilized. A a significance level of 0.05 will be used for all statistical tests. The results will bewere interpreted and compared to the current body of knowledge.

Chapter Summary

This chapter focused on the description of the methods utilized to answer the research questions and test the hypotheses. The aim of the section was to demonstrate the validity of utilized methods for achieving the purpose of the study. This research selected a quantitative design, as we aimed at increasing the generalizability of previous findings by testing the hypotheses based on a sample from the ICT sector in the UAE. It was decided to use primary data acquired from the online survey. In order to collect the needed data, a questionnaire that included a total of 95 questions was compiled from eight different instruments. Two of the instruments, which collected demographic data, were self-created, while six other surveys were borrowed from open sources. The borrowed questionnaires had high validity confirmed by numerous studies

The population under analysis were employees working in the ICT industry in UAE. The total population under analysis was estimated to be around 48,000 people. The minimal sample for this research was 119 participants; however, more participants were required to ensure at least 119 valid responses. All the surveys that were unfinished by the participants were excluded from the analysis. Additionally, employees that had less than six months of experience working in the ICT sector were also excluded from data analysis.

The links to the survey were distributed with the help of HR managers of the ICT companies. The HR managers were emailed with a request to distribute the questionnaire among the employees. After the data was collected, it was analyzed using descriptive statistics, Pearson’s correlation analysis, simple mediation analysis, and simple moderation analysis. Alpha of 0.05 was used as a threshold for statistical significance.

Results

Introduction

This section aims at describing the results of the analysis in the most unbiased matter to allow the readers draw their own conclusions. In general, the function of the results section is to present the key results in the most objective manner (Saunders et al., 2019). This section is usually built around a series of tables and figures that help to describe the results without interpretation. fsd

First, this section focuses on the description of the sample by briefly mentioning the key characteristics of the initial sample and detailed analysis of the characteristics of the final sample. Second, the section provides descriptive statistics of six variables along with histograms that present the distribution of values. Third, the section describes the results of hypotheses testing subdivided into three groups according to the statistical methods. Finally, the section provides a discussion of assumptions to assess if the results were biased. The section is concluded with a summary of the chapter.

Description of the Sample

The questionnaire was distributed among 374 respondents, among which 59.64% were males, and 40.36% were females. The majority of the respondents had a Bachelor’s degree (47.76%) or a Master’s degree (36.41%). As for marital status, 36.94% of the respondents were single, and 58.05% were married. Most of the respondents (48.9%) worked for the telecom operator, 13.46% worked for a telecom operator (du or Etisalat), 4.12% worked for an ICT sector company, and 33.52% of the respondents identified their employer as “other.” The age distribution of the respondents is provided in Figure 1 below.

Only 233 out of 374 replied to all the questions in the questionnaire, which implies that 37.7% of the responses were excluded from the analysis on the basis of incomplete replies. Additionally, it was decided to analyze data received from respondents working for a telecom regulator or a telecom operator. As a result, additional 14.97% of responses were excluded from the dataset, as the responses were received from respondents that worked for other types of employers. In summary, only 177 (47.33%) of responses were used for the analysis provided in this section.

The final sample included 176 respondents, which was 47% of the initial sample. Even though the sample was less than 50% of the initial number of respondents, it was above the threshold of 119 respondents that were identified as the minimal number of respondents, according to the formula provided by Cochran (1977). The characteristics of the final sample were somewhat different from the original sample. The analysis of demographic characteristics of the final sample revealed no bias in the age, gender, education level, and marital status distribution. The description of the demographic characteristics of the final sample is provided below.

Age Distribution

The age distribution of the final sample is provided in Table 1 below. The results demonstrate that more than three quarters of the sample were younger than 40 years old, which implies that the ICT sector attracts relatively young employees. This may be associated with the fact that the ICT sector in the UAE is deeply rooted to high-end technology, which may be more challenging to grasp for the older generation than for the younger generation. At the same time, such age distribution of the sample may be explained by the composition of the UAE population. According to Global Media Insight (GMI, 2022), more than 87% of the UAE population is younger than 54. Such an age composition if the UAE can be explained by the fact, that it consists of 88.52% of expatriate that came to the country to work (GMI, 2022). Thus, the age distribution of the sample appears representative of the age distribution of the population under analysis.

Table 1. Age distribution of the final sample.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	18-25	20	11.4	11.4	11.4
	26-30	32	18.2	18.2	29.5
	31-35	39	22.2	22.2	51.7
	36-40	42	23.9	23.9	75.6
	41-45	23	13.1	13.1	88.6
	46-50	11	6.3	6.3	94.9
	51-55	4	2.3	2.3	97.2
	56-60	5	2.8	2.8	100.0
	Total	176	100.0	100.0

Gender Distribution

The sample consisted of 63.1% males and 36.9% females, which demonstrates an unequal distribution. Without a point of comparison, the reader may assume that ICT sector is not inclusive enough, as it attracts less females than males. However, when compared to the gender distribution of the UAE population, the gender distribution of the sample seems to favor females more than males. According to GMI (2022), 68.8% of the population in the UAE are males and only 31.2% are females. The percentage of females in the sample is higher by 5.7% than the percentage of females in the sample, which can be explained in two ways. On the one hand, the difference in the gender distribution is attributed to the fact that the ICT sector is more open to females than other sectors. On the other hand, the difference in gender distribution is attributed to chance. The prevalence of males in the sample is also explained by the large percentage of expatriates in the UAE population. ales come to UAE to work and develop financially, which makes female population a minority in the UAE (GMI, 2022).

Education Level

The distribution of the final sample by education level is provided in Table 2 below. The analysis demonstrates that the majority (84.7%) of the sample had a Bachelor’s degree or higher, which demonstrates high level of education among the sample. Such a level of education can be explained by the level of education in the UAE in general (World Education News and Reviews, 2018). Additionally, since the ICT sector is associated with high-tech, it may require higher education to work effectively. However, it is difficult to say if the education level distribution is different or similar with education level distribution in the UAE, as no such data is available in the open access.

Table 2. Distribution of the education level

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Less than High School	1	.6	.6	.6
	High School	10	5.7	5.7	6.3
	Diploma	11	6.3	6.3	12.5
	Higher Diploma	5	2.8	2.8	15.3
	Bachelor	80	45.5	45.5	60.8
	Master’s Degree	64	36.4	36.4	97.2
	PhD	5	2.8	2.8	100.0
	Total	176	100.0	100.0

Marital Status Distribution

The distribution of the marital status of the sample is provided in Table 3 below. The analysis demonstrated that the majority of the respondents (61%) were married. The distribution of the UAE population by marital status was unavailable in the open access, which made it impossible to correlate the sample distribution to the UAE population.

Table 3. Marital status distribution of the sample

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Single	56	31.8	31.8	31.8
	Married	109	61.9	61.9	93.8
	Divorced	10	5.7	5.7	99.4
	Widowed	1	.6	.6	100.0
	Total	176	100,0	100,0

Descriptive Statistics of Variables

Descriptive statistics of the variables was provided to help the reader understand the data distribution by variable. According to McClaive et al. (2018), descriptive statistics can be helpful for two reasons. On the one hand, it provides essential information about the variables in a dataset using a clear format (McClaive et al., 2018). On the other hand, descriptive statistics can help to highlight possible relationships among variables (McClaive et al., 2018). This section describes the variables in terms of central tendency using mean, median, and mode, and in terms of dispersion, using standard deviation, minimum, maximum, skewness, and kurtosis. Additionally, this section provides histograms of the distribution to assess if the variables followed the normal distribution curve. According to McClaive et al. (2018), normality of distribution for both Pearson’s correlation and regression analysis. Since regression analysis is the essential part of the simple moderation and mediation model, normality of distribution of the variables was essential for confirming the reliability of findings. The descriptive statistics of the variables is provided in Table 4 below.

Table 4. Descriptive statistics of variables

	Person- Environment Fit	Psychological Capital	Organizational Commitment	Job Satisfaction	Work Engagement	Intention to Stay
N Valid	176	176	176	176	176	176
N Missing	0	0	0	0	0	0
Mean	45,25	48.77	48.69	38.73	34.20	7.14
Median	43,00	49.00	49.00	37.00	31.00	6.00
Mode	38	37^a	49	38	25^a	6
Std. Deviation	15,711	12.638	7.623	11.234	13.655	3.483
Skewness	1,203	.515	-1.043	.957	2.167	.848
Std. Error of Skewness	.183	.183	.183	.183	.183	.183
Kurtosis	1,668	.691	3.972	1.343	6.188	-.262
Std. Error of Kurtosis	,364	.364	.364	.364	.364	.364
Minimum	19	23	15	20	17	3
Maximum	104	89	71	78	102	15

a. Multiple modes exist. The smallest value is shown

Person-Environment Fit

The mean score of P-E fit was 45.25 with a standard deviation of 15.7. This implies that the scores between 13.85 and 76.65 95% of the population. The scores varied between 19 and 104, as the variable was measured using 19 questions. The distribution of the sample is positively-skewed (Skewness = 1.2), and leptokurtic (Kurtosis = 1.67). The analysis of the histogram provided in Figure 2 below demonstrates that the distribution follows the normal distribution curve with slight irregularities.

Psychological Capital

The mean value of psychological capital 48.8 with a standard deviation of 12.6. This implies that 95% of scores lied between 23.6 and 74, with the maximum value of 89 and the minimum value of 23. The distribution was positively skewed (Skewness = 0.5), and leptokurtic (Kurtosis = 0.7). The histogram for the variable demonstrated that the distribution was close to normal, which was crucial for further statistical analysis. The histogram for psychological capital is provided in Figure 3 below.

Organizational Commitment

The mean value for the organizational commitment was 48.7 with a standard deviation of 7.6. This implies that 95% of scores were included in the interval between 33.5 and 63.9, while the scores for the variable varied between 15 and 71. The distribution was negatively skewed (Skewness = -1), and extremely leptokurtic (Kurtosis = 4). The histogram for the variable demonstrated that the distribution was close to normal with insignificant deviations. The histogram for organizational commitment is provided in Figure 4 below.

Job Satisfaction

The mean score for job satisfaction was 38.7 with a standard deviation of 11.2. This implies that the interval between 16.3 and 61.1 included 95% of responses, while the values ranged between 20 and 78. The distribution was positively skewed (Skewness = 1), and leptokurtic (Kurtosis = 1.3). The histogram for the variable provided in Figure 5 below demonstrated that the distribution was close to normal, which implies that the variable fulfilled the assumption of notmalitynormality.

Work Engagement

The mean value for work engagement was 34.2 and the standard deviation was 13.7. This implied that 95% of scores of the population would be included in the interval between 6.8 and 61.6, while the values ranged between 17 and 102. The distribution was positively skewed (Skewness = 2.2), and extremely leptokurtic (Kurtosis = 6.2). The histogram visualizing the distribution of the variable (see Figure 6) demonstrated that the pattern was close to normal distribution, which is crucial for fulfilling the assumption of normality.

Intentions to Stay

The mean value of intention to stay was 7.14 with a standard deviation of 3.5. This implied that 95% of scores for the population were included in the interval between 0.14 and 14.14, while the values ranged between 3 and 15. The distribution was positively skewed (Skewness = 0.8), and slightly platykurtic (Kurtosis = -0.3). The distribution of values did not follow the normal distribution curve, which implies that intention to stay did not comply with the assumption of normality. This fact may have led to biased results of statistical analysis.

Figure 7. Histogram for intention to stay

Hypotheses 1-4

Hypotheses 1-4 were tested using Pearson’s R, which is one of the most straightforward methods of analyzing relationships between two variables. A correlation matrix was created (see Table 5) to assess correlations in four pairs of variables. The analysis revealed statistically significant correlations between person-environment fit and job satisfaction (r = 0.746, p < 0.001), between psychological capital and job satisfaction (r = 0.621, p < 0.001), between job satisfaction and organizational commitment (r = 0.344, p < 0.001), and between job satisfaction and intention to stay (r = 0.607, p < 0.001). Since all the examined correlations were positive, the analysis provided significant evidence to accept Hypotheses 1-4. The results were consistent with the preliminary analysis, even though slight deviations in the Pearson’s r coefficients were present.

Table 5. Pearson’s correlation analysis

		Person Environment Fit	Psychological Capital	Organizational Commitment	Job Satisfaction	Work Engagement	Intention to Stay
Person Environment Fit	Pearson Correlation	1	.582^**	.261^**	.746^**	.549^**	.658^**
	Sig. (2-tailed)		.000	.000	.000	.000	.000
	N	176	176	176	176	176	176
Psychological Capital	Pearson Correlation	.582^**	1	.309^**	.621^**	.568^**	.442^**
	Sig. (2-tailed)	.000		.000	.000	.000	.000
	N	176	176	176	176	176	176
Organizational Commitment	Pearson Correlation	.261^**	.309^**	1	.344^**	.419^**	.009
	Sig. (2-tailed)	.000	.000		.000	.000	.906
	N	176	176	176	176	176	176
Job Satisfaction	Pearson Correlation	.746^**	.621^**	.344^**	1	.683^**	.607^**
	Sig. (2-tailed)	.000	.000	.000		.000	.000
	N	176	176	176	176	176	176
Work Engagement	Pearson Correlation	.549^**	.568^**	.419^**	.683^**	1	.452^**
	Sig. (2-tailed)	.000	.000	.000	.000		.000
	N	176	176	176	176	176	176
Intention to Stay	Pearson Correlation	.658^**	.442^**	.009	.607^**	.452^**	1
	Sig. (2-tailed)	.000	.000	.906	.000	.000
	N	176	176	176	176	176	176
**. Correlation is significant at the 0.01 level (2-tailed).

Hypotheses 5-8

Hypotheses 5-8 were united into one subsection because all of them were analyzed using a simple moderation model of PROCESS macro in SPSS. The analysis of the moderation effect of work engagement on the relationship between person-environment fit and job satisfaction revealed that both person-environment fit and work engagement had a significant positive effect on job satisfaction. Overall, the regression model had a high predictive ability with R² = 0.6657. However, the moderation effect of work engagement was statistically insignificant with p = 0.3823. Thus, Hypothesis 5 was rejected, signifying that work engagement does not moderate the relationship between person-environment fit and job satisfaction.

The analysis of the moderation effect of work engagement on the relationship between psychological capital and job satisfaction revealed that both psychological capital and work engagement had a significant positive effect on job satisfaction. The created regression model had an even higher predictive ability with R² = 0.7467. The interaction effect between the independent variables was statistically significant with p = 0.044, which demonstrated that work engagement moderated the relationship between psychological capital and job satisfaction. This implies that there was significant evidence to accept Hypothesis 6.

The assessment of the moderation effect of work engagement on the relationship between organizational commitment and job satisfaction revealed that neither organizational commitment nor work engagement had a significant effect on job satisfaction. Moreover, even though the created regression model had a high predictive ability (R² = 0.6873), the interaction effect between work engagement and organizational commitment was statistically insignificant (p = 0.5262). Thus, Hypothesis 7 was rejected, demonstrating that work engagement had no moderation effect on the relationship between organizational commitment and job satisfaction.

The model created for testing the moderation effect of work engagement on the relationship between job satisfaction and intention to stay revealed that work engagement had a significant effect on the intention to stay, while job satisfaction was a significant predictor of intention to stay. The model was statistically significant with R² = 0.6197; however, the moderation effect of work engagement on the relationship between job satisfaction and intention to stay was statically insignificant, as the p-value of the interaction effect (p = 0.568) was slightly above the alpha level of 0.05. Thus, Hypothesis 8 was rejected. Detailed results of moderation analysis for Hypotheses 5-8 are provided in Table 6 below.

Table 6. Results of moderation analysis for Hypotheses 5-8

	Outcome variable: Job satisfaction			Outcome variable: Intention to stay
	H5	H6	H7	H8
Main Effect
P-E Fit	0.4453***
Psychological Capital		0.4822***
Organizational Commitment			-0.0066
Job Satisfaction				0.1103**
Moderator
Work Engagement	0.4429**	0.7241***	0.3565	-0.0836
Overall F	114.1802	72.254	51.3204	35.7474
R²	0.6657	0.5576	0.4723	0.384
Test for high order unconditional interaction
Value	-0.0019	-0.005	0.0033
R²change	0.0015	0.0106	0.0012	0.0132
Fchange	0.7671	4.102	0.4034	3.6782
p-value	0.3823	0.0444	0.5262	0.0568

Note. * p <.05, ** p <.01, *** p <.001, two-tailed.

Hypotheses 9-12

Hypotheses 9-12 were united into one subsection because all of them were tested using a simple mediation model in PROCESS macro in SPSS. The analysis of the mediation effect of job satisfaction on the relationship between person-environment fit and organizational commitment revealed that job satisfaction was a significant mediator. A 95% confidence interval (CI) of the indirect effect of job person-environment fit on organizational commitment was [0.0419, 0.2019]. Since both the upper and the lower limits of the 95% CI were positive, the mediation effect was statistically significant.

The analysis of the mediation effect of job satisfaction on the relationship between person-environment fit and intention to stay revealed that the indirect effect of person-environment fit on the intention to stay was statistically significant. A 95% CI of the indirect effect was [0.0146; 0.0742], meaning that both the upper and the lower limits of the CI were above zero. Therefore, Hypothesis 10 was accepted, signifying that job satisfaction mediates the relationship between person-environment fit and intention to stay.

The assessment of the mediation effect of job satisfaction on the relationship between psychological capital and organizational commitment provided significant evidence that job satisfaction mediated the relationship. A 95% CI of the indirect effect of psychological capital on organizational commitment was [0.0112, 0.1803]. Since both the upper and the lower limits of the CI were positive, Hypothesis 11 was accepted.

The assessment of job satisfaction as a mediator in the relationship between psychological capital as an independent variable and intention to stay as a dependent variable provided significant evidence to support Hypothesis 12. The indirect effect of psychological capital on the intention to stay was statistically significant, as both the lower limit (0.0609) and the upper limit (0.1253) of the 95% CI were both positive. Thus, Hypothesis 12 was accepted. Table 7 below provides a summary of results of tests for Hypotheses 9-12.

	Outcome variable: Organizational commitment		Outcome variable: Intention to stay
	H9	H11	H10	H12
Main Effect
P-E Fit	0.0045		0.1025***
Psychological Capital		0.0939		0.0291
Mediator
Job Satisfaction	0.2285**	0.1676**	0.0812**	0.1678***
Overall F	11.5905	13.2716	74.5594	51.9419
R²	0.1182	0.133	0.4629	0.3752
Bootstrap results for indirect effect
Value	0.122	0.0925	0.0433	0.0926
Boot SE	0.0416	0.0416	0.015	0.0164
95% CL	[0.0399, 0.2031]	[0.0142, 0.1758]	[0.0140, 0.0729]	[0.0598, 0.1247]

Note. * p <.05, ** p <.01, *** p <.001, two-tailed.

Discussion of Assumptions

There are several assumptions associated with Pearson’s correlation analysis and regression analysis. First assumption is associated with the level of measurement, which implies that all the values should be measured at the level of either ratio and interval (McClaive et al., 2018). This assumption was fulfilled by the design of the data collection procedure, as all the variables were measured using Likert scale questions. Second, Pearson’s correlation analysis as well as regression analysis require that the relationship between the variables was linear. This assumption was tested by creating scatterplots for different pairs of variables and visually assessing these scatterplots for patterns. Four of these scatterplots are provided in Figure 8 below. Visual analysis demonstrated the assumption of linearity was fulfilled in the majority of cases. However, in some cases, the relationship was challenging to spot, which may have led in biased results.

Third, both linear regression and Pearson’s correlation analysis require that the data is normally distributed (McClaive et al., 2018). This analysis was conducted by creating histograms for visualization of distribution and comparing the actual distribution to the normal distribution. The analysis is provided in Section 4.3 of this thesis. The analysis revealed that all variables except for intention to stay followed the normal distribution curve with insignificant inclinations. However, it should be acknowledged that statistical analysis that included intention to stay as one of the variables may be biased.

Finally, the correlation analysis assumes that there should be related pairs, which implies that every datapoint in the dataset should have a paired value. This was achieved during the data cleaning process. As was mentioned in Chapter 3, all the incomplete questionnaires were removed from the analysis, which ensured that the assumption of related pairs is fulfilled.

Chapter Summary

This sectionchapter aimed at providing unbiased description of the analysis of data. First, the chapter established that the sample characteristics were similar to the characteristics of the UAE population. Second, descriptive statistics of variables was analyzed to provide essential information about the variables and highlight possible relationships among variables. Additionally, the section visualized the distribution of variables using histograms. The histograms were essential for assessing if the assumption of normality for correlation and regression analysis were followed.

The primary purpose of the chapter was to provide the results of hypotheses testing. The analysis provided significant evidence to accept Hypotheses 1-4, Hypothesis 6, and Hypotheses 9-12. There was not enough evidence to accept Hypothesis 5, Hypothesis 7, and Hypothesis 8. However, it should be mentioned that the moderation effect of work engagement on the relationship between job satisfaction and intention to stay almost reached statistical significance with p = 0.057.

The discussion of assumptions revealed that the dataset complied with all the assumptions. The discussion demonstrated that the assumption of the level of measurement was followed by design of the questionnaires and the data cleaning procedure ensured that the assumption of related pairs was followed. The analysis of histograms demonstrated that five of six variables had distributions close to the normal distribution curve, while the distribution of intention to stay did not follow the normal curve. The assessment of scatterplots ensured that the assumption of linear relationship between variables was followed.

Work Plan and Timetable

It is important to develop a work plan that identifies specific activities that will be carried out in the study. The work plan helps in breaking down the entire project into specific tasks that should be completed within a specific time. The following Gantt chart identifies these activities and the timeline within which they should be completed. As shown in the table, all the activities should be completed by the end of May/June 2021.

Activity/Time	Sep Oct 2021	Nov Dec 2021	Jan Feb 2022	Mar Apr 2022	May Jun 2022	Jul Aug 2022	Sep Oct 2022	Nov Dec 2022	Jan Feb 2023
Proposal Defense
Proposal Approval
Literature Review
Primary Data Collection
Data Analysis
Write-up/Editing
Final Submission

Conclusion & Discussion

Introduction

This chapter aims at discussing the results of the study against the current body of knowledge that was overviewed in Chapter 2 of the paper. The primary purpose of this section was to interpret the results of statistical analysis and compare the conclusions with previous findings. It is the central part of the thesis, as it answers all the research questions and provides recommendations for managers of the ICT sector and researchers interested in the interrelationship between the six variables that were analyzed in this study.

Chapter 5 is subdivided into several subsection. The first subsection focuses on detailed examination of the results of statistical analysis organized by hypotheses. The second subsection discusses the limitations of this research associated with methods and scope of the study. The third subsection provides recommendations for improving retention in the ICT sector in the UAE, as well as suggestions for future research. The fourth subsection included the central implications of the study. The chapter is concluded with a brief summary of the main points.Since most aspects of work are intertwined and are affected by each other, directly or indirectly, positively or negatively, and to a high, medium, or low degree, we believe that most aspects of work are intertwined and are affected by each other in the vast majority of matters. Similarly, we notice that science analysis on today’s organizations focuses on the analysis of certain variables, in order to determine the form and degree of interrelationships within these variables, and we discover that these variables are interrelated and overlap.

Discussion of Results

Hypothesis 1

Hypothesis 1 stated that there was expected to be a positive correlation between P-E fit and job satisfaction. Pearson’s correlation analysis allowed the researcher to accept the hypothesis with a high degree of certainty, as a very strong positive correlation between the variables was found. The coefficient of r = 0.746 signified a fairly strong positive correlation between the variables (Gogtay & Thatte, 2017). This implies that the stronger the P-E fit of employees the higher their satisfaction with work in the ICT sector in the UAE. In summary, this paper is a research proposal that describes a mixed-method study focusing on the different organizational factors that affect the attitudes and work performance of the individuals employed in the ICT sector in the UAE. Hence, the goal of this study is to examine the interconnection of the different variables and their moderating and mediating effect on one another. The anticipated outcome is the ability to draw conclusions regarding how businesses can structure their organizational environments and HR practices to ensure that their employees work productively, receive effective training that makes these human resources a valuable asset and a competitive advantage, and stay with the company. These outcomes will be specific to the ICT industry in the UAE because it is a growing economic sector and the priority for the economic development set by the state’s government. Therefore, this study will contribute significantly to the business activity development in the UAE and will help businesses.

The possible future gaps include the difference in the importance of the different factors since this study will not examine the specific level of impact that the six variables have on the organizational outcomes and employee’s work. Moreover, future research can use the theoretical model and framework developed in this paper to study the six factors in question-based on different industries or even states. This is because the culture of the UAE differs from that in the West or Asia, and the employees’ attitudes and perceptions may vary greatly depending on the social context that they live and work in, which means that the conclusions of this study may be not applicable to these environments.

The results of the analysis are consistent with the P-E fit theory. According to the theory, P-E fit predetermines the behaviors of employees at work (Anglin et al., 2018; Guan et al., 2021). The theory states that a better P-E fit is associated with improved motivation to work, as the employees feel right for the job because they have the relevant skills, share the same values as the organization, and have similar underlying assumptions (Calzo et al., 2020). Since the employees have more motivation, they are more likely to be successful, which leads to increased satisfaction with their professional life. The results of this study confirmed that the assumptions of the P-E theory are applicable to the ICT industry in the UAE.

The results of this study are also in accord with findings of previous research. Ahn and Lee (2019) conducted a thorough research based on a large sample of industrial workers in Korea that arrived at the same results. Similar results were achieved in recent research in Europe and Americas (Redelinghuys et al., 2020; White et al., 2021). This research increased the generalizability of results of previous research by confirming a positive correlation between P-E fit and job satisfaction of the ICT sector in the UAE.

Hypothesis 2

Hypotheses 2 assumed that there was a positive correlation between psychological capital and job satisfaction in the employees of the ICT industry in the UAE. The results of Pearson’s correlation analysis revealed a moderate positive between the variables, as the correlation coefficient was 0.62. This implies that the higher the ability to apply the skills related to emotional intelligence and emotional competence of the employees in the ICT sector the more content they feel with their current duties, salaries, and position in the company.

The results of this study are consistent with previous research that assessed the effect of psychological capital on job satisfaction. Previously, the relationship between the variables was well established in the education industry in various countries (Aydin Sünbül and Aslan Gördesli, 2021; Kun and Gadanecz, 2019). Huynh and Hua’s (2020) arrived at similar conclusions by studying the relationship between the variables using a sample of employees from small- and medium-size companies in Vietnam. This research increased the generalizability of previous research by confirming that there was a positive relationship between psychological capital and job satisfaction in the ICT sector in the UAE.

Hypothesis 3

The third hypothesis concerned the relationship between job satisfaction and organizational commitment. The analysis provided in this study confirmed that there was a positive correlation between the two variables, as the correlation coefficient was positive and statistically significant with p < 0.001. However, the effect size of the relationship was small, as Pearson’s correlation coefficient of r = 0.344 indicated a relatively weak correlation between the variables. Thus, it may be concluded that in some cases increased job satisfaction may lead to increased organizational commitment in the ICT industry in the UAE. However, if managers in the sector need to increase organizational commitment, they may try other strategies than improving job satisfaction, as only a weak correlation was found between the variables.

The results are somewhat consistent with previous research findings. Romi et al. (2021) stated that increased workplace satisfaction had a moderate positive effect on organizational commitment. Similarly, Jigjiddorj et al. (2021) state that higher levels of job satisfaction in Mongolian employees led to better organizational performance, compliance with corporate policies and culture, as well as a commitment to the job. While the results of this study were consistent with previous research, they demonstrated that workplace satisfaction had a smaller effect on organizational commitment in ICT employees in the UAE in comparison with other industries from other countries. Thus, this research contributed to the current body of knowledge by increasing the generalizability of finding of the previous research and providing specific knowledge concerning management in the telecom sector in the UAE.

Hypothesis 4

The fourth hypothesis developed in this paper concerned the relationship between job satisfaction and intention to stay. Pearson’s correlation analysis revealed a moderate correlation between job satisfaction and intention to stay with Pearson correlation coefficient of r = 0.61. This implies that the higher the level of job satisfaction of employees in the ICT sector in the UAE, the more likely they intend to stay in their current workplace. In other words, the higher the workplace satisfaction the less likely the employees in the ICT sector in the UAE have turnover intentions. Therefore, if the managers in the sector under analysis want to decrease turnover, they can utilize strategies for increasing workplace satisfaction.

The results of this study are consistent with previous research results. Jiang et al. (2019) concluded that employees of small and medium enterprises are less likely to turnover if they are satisfied with their current job. Similarly, Al-Muallem and Al-Surimi (2019) confirmed the results for the healthcare sector. The results of this study concerning the relationship among job satisfaction and intention to stay are in line with current research findings and add their generalizability by providing evidence for the correlation from the telecom sector in the UAE.

Hypothesis 5

Hypotheses 5 concerned the relationship between three variables, including engagement, P-E fit, and job satisfaction. The results of the analysis using a simple moderation model revealed that work engagement did not moderate the relationship between P-E fit and job satisfaction. The relationship between P-E fit and job satisfaction was direct, which was confirmed by both regression and correlation analyses. This implies that there is a high probability that an increase in P-E fit will increase workplace satisfaction regardless of how engaged the employees are in the work. However, it should be acknowledged that this finding concerns only employees from the ICT industry in the UAE.

Previous research did not touch upon the moderating effect of work engagement on the relationship between workplace satisfaction and P-E fit. Even though a recent study by Wang et al. (2020) mentioned that the moderating effect may exist, there was no empirical confirmation to the idea. Thus, this study provided as significant contribution to the current body of knowledge by acknowledging that, in the telecom sector of the UAE, the relationship between P-E and job satisfaction was not moderated by work engagement.

Hypothesis 6

Hypothesis 6 focused on the relationship work engagement moderating the relationship between psychological capital and workplace satisfaction. The results of the analysis revealed that there was significant evidence that work engagement moderated the correlation between job satisfaction and psychological capital. This implies that if managers wanted to increase job satisfaction by altering psychological capital, they need to take into consideration work engagement as modifier of the effect. In other words, this research confirmed the assumption that since the psychological capital is a resource of socio-psychological relations, due to which an employee is able to successfully achieve the intended goals, connection between the variables could be discovered.

Previous research did not focus on analyzing the moderating effect of work engagement in the relationship between workplace satisfaction and psychological capital. Even though the analysis of definitions demonstrated work engagement could moderate the effect of psychological capital on job satisfaction, no previous research tested such a relationship. Thus, this research’s uniqueness lies in providing preliminary evidence of the moderating effect of work engagement in the relationship between job satisfaction and psychological capital.

Hypothesis 7

The seventh hypothesis focused on the moderating effect of work engagement on the relationship between organizational commitment and job satisfaction. Simple moderation analysis revealed that the effect of organizational commitment on job satisfaction was not moderated by work engagement in the employees of the telecom industry in the UAE. This implies if managers in the sector want to boost workplace satisfaction by increasing organizational commitment, they do not need to be concerned with the moderating effect of engagement. However, it should be mentioned that both work engagement and organizational commitment have a significant direct effect on job satisfaction with r = 0.68 and r = 0.34 correspondingly. Thus, if managers modified both work engagement and organizational commitment, they would increase the effect on job satisfaction. Managers should also be aware that modifying organizational commitment to increase job satisfaction may be ineffective, as the correlation between the variables was found to be weak.

The results concerning the analysis of the moderating effect of work engagement on the relationship between organizational commitment and job satisfaction is unique. The literature review revealed no previous research that tested a similar model in recent years in any industries of any countries. Thus, this research provided empirical evidence that the moderating effect of work engagement in this correlation in highly improbable.

Hypothesis 8

Hypotheses 8 focused on the moderating effect of work engagement on the relationship between intention to stay and job satisfaction. The results of the analysis revealed that work engagement did not moderate the relationship between job satisfaction and intention to stay. However, both work engagement and job satisfaction were moderately positively correlated with intention to stay with r = 0.68 and r = 0.61.

Previous research did not focus on the analysis of the moderating effect of work engagement on the relationship between workplace satisfaction and intention to stay or turnover intentions. Even though Mashuri and Maharani (2019) hinted on the existence of such an effect, no empirical evidence was provided. Thus, this research confirmed that, when speaking of employees in the ICT sector in the UAE, work engagement did not moderate the effect of job satisfaction on intention to stay.

Hypothesis 9

The ninth hypothesis tested if there was a positive impact of job satisfaction as a mediator on P-E fit (an independent variable), resulting in organizational commitment (a dependent variable) since a satisfied workforce is more likely to perform optimally and remain loyal to an organization. The results of the analysis provided significant evidence of the mediating role of job satisfaction in the relationship between P-E fit and organizational commitment. Moreover, the mediation analysis demonstrated that the direct effect of P-E on organizational commitment was insignificant. Previously, Pearson’s correlation analysis demonstrated that there was a weak but significant correlation between P-E fit and organizational commitment (r = 0.261). However, the mediation analysis suggested that this correlation was indirect. Instead of P-E fit directly affecting organizational commitment, it affects job satisfaction, which, in turn, affects organizational commitment. The correlation analysis demonstrated that there was a strong correlation between P-E fit and job satisfaction (r = 0.746), and a weak correlation between job satisfactions and organizational commitment (p = 0.344). However, it should be acknowledged that these results are applicable only to the ICT sector in the UAE.

Previous research did not test for such a relationship between job satisfaction, P-E fit, and organizational commitment. Thus, this research is unique in identifying the relationship between these three variables using a simple mediation model. However, this research compliments the findings of previous scientific inquiries, which concluded that there was a positive correlation between P-E fit and organizational commitment (Jigjiddorj et al., 2021; Romi et al., 2021). The results of this study insist that even though the correlation between P-E fit and organizational commitment exists, it is indirect. Thus, if managers of the ICT sector wanted to increase organizational commitment, increasing P-E fit would be ineffective.

Hypothesis 10

Hypothesis 10 focused on testing the mediating role of job satisfaction on the relationship between P-E fit and intention to stay. The results of the analysis demonstrated that the effect of P-E fit on intention to stay was both direct and indirect. Previously, Pearson’s correlation analysis revealed that the there was a moderate-to-strong correlation between P-E fit and intention to stay with r = 0.658. The results of the analysis of the simple mediation model revealed that P-E fit affected intention to stay both directly and by affecting job satisfaction.

Previous research did not test for such a relationship between these three variables, which makes this study unique. However, previous research stated that there was a strong correlation between P-E fit and workplace satisfaction (Anglin et al., 2018; Guan et al., 2021). Similarly, previous research established the there was a strong connection between job satisfaction and intention to stay (Jiang et al., 2019). Since it would be logical to assume that P-E fit affects job satisfaction, which, in turn, affect s intention to stay, it may be stated that this study is in line with previous findings.

Hypothesis 11

The eleventh hypothesis focused on testing for the mediating tole of job satisfaction in the relationship between psychological capital and organizational commitment. The results of the analysis revealed job satisfaction was a significant mediator in the relationship between psychological capital and intention to stay. Additionally, the analysis of the simple mediation model revealed that the direct effect of psychological capital on intention to stay was insignificant. Pearson’s correlation analysis demonstrated that there was a weak correlation between psychological capital and organizational commitment with r = 0.309. The results of this research demonstrated that this correlation was due to psychological capital affecting job satisfaction, which, in turn, had an effect on organizational commitment.

The findings of this study concerning Hypothesis 11 are in line with previous research, which provided significant evidence that job satisfaction mediated the relationship between psychological capital and organizational commitment (Romi et al., 2021; Jigjiddorj et al., 2021). This study added to the generalizability of previous findings by confirming them for the ICT sector in the UAE. Additionally, the research contributed by providing evidence that psychological capital does not have a direct effect on organizational commitment.

Hypothesis 12

The final hypothesis focused on the mediating role of job satisfaction in the relationship between psychological capital and intention to stay. The results of the analysis confirmed that job satisfaction acts as a mediator in the relationship between psychological capital and intention to stay in the ICT sector in the UAE. Moreover, the analysis of the simple mediation model revealed that the effect of psychological capital on intention to stay was insignificant. Pearson’s correlation analysis demonstrated that there was a weak-to-medium correlation between psychological capital and intention to stay with r = 0.442. This research demonstrated that the correlation was indirect, since psychological capital affected job satisfaction, which, in turn, affected intention to stay.

The results of this research for Hypothesis 12 were in line with findings of previous studies. Several recent studies arrived at a similar result that job satisfaction mediated the relationship between psychological capital and intention to stay (Jiang et al., 2019, Sasso et al., 2019, Mashuri & Maharani, 2019). This research contributed to the current body of knowledge by increasing the generalizability of findings of previous studies on the correlation.

Summary of Findings

This research provided significant insights into mechanisms concerning the relationships between six variables, including P-E fit, psychological capital, organizational commitment, work engagement, job satisfaction, intention to stay, and job satisfaction. The primary purpose of the analysis was to understand how managers can improve workplace satisfaction of their employees and increase retention rates. First, the analysis established that P-E fit, psychological capital, and organizational commitment positively affect workplace satisfaction in the ICT sector in the UAE. After that, the analysis confirmed that there was a strong correlation between intention to stay and workplace satisfaction in the industry. Thus, it may be concluded that P-E fit, psychological capital, and organizational commitment affect intention to stay at least indirectly through job satisfaction. All of these findings were in accord with previous research.

After these basic relationships were established, the research focused on determining the role of work engagement in the relationships between these variables.

Literature review led to the understanding that work engagement could moderate the relationship between P-E fit, psychological capital, and organizational commitment on one side and job satisfaction on the other hand. Additionally, the analysis of literature revealed that work engagement could moderate the relationship between job satisfaction and intention to stay. After analyzing four simple moderation models, the analysis revealed that work engagement moderated the relationship between psychological capital and job satisfaction. However, it should also be noticed that Pearson’s correlation analysis revealed significant positive correlations with five other variables.

After the moderating role of work engagement was tested, the analysis focused on the mediating role of job satisfaction in the relationships between different variables. The analysis revealed that job satisfaction mediated the relationships between P-E fit and psychological capital on one side and organizational commitment on the other. Similarly, the analysis revealed that job satisfaction acted as a mediator in the relationship between P-E fit and psychological capital on one side and intention to stay on the other. Job satisfaction was found to be deeply interwoven in the relationship between different variables. The results of the analysis suggest that if managers want to increase retention rates in the ICT sector in the UAE, they should focus on increasing workplace satisfaction. The analysis demonstrates that job satisfaction can be increased using different strategies, such as increasing organizational commitment, P-E fit, or psychological capital.

In summary, this research analyzed the relationships between six variables to understand factors that can contribute to retention of employees. In particular, the study identified that all six variables are positively interconnected between each other, which was consistent with previous studies (Al-Muallem & Al-Surimi, 2019; Deschênes, 2020; Jiang et al., 2019; Jigjiddorj et al., 2021; Kun & Gadanecz, 2019; Redelinghuys et al., 2019; Redelinghuys et al., 2020; Romi et al., 2021; Sasso et al., 2019; Zhu et al., 2014). We also confirmed that work engagement moderated some of the relationships, which was consistent with the current body of knowledge (Ahmad, 2012; Anglin et al., 2018; Guan et al., 2021). Job satisfaction was also found to act as a mediator in some of the inter-relationships between variables, which was also in accord with previous research (Ahmad, 2012; Anglin et al., 2018; Jigjiddorj et al., 2021; Romi et al., 2021).

Thus, this research made two central contributions to the current body of knowledge. On the one hand, we increased the generalizability of previous findings by testing the relationships between the variables in the context of the ICT sector in the United Arab Emirates. On the other hand, we assessed interrelations among six variables simultaneously, which allowed us to understand the complexity and intricacy of the relationships between factors that affect job satisfaction and intention to stay. The results of this research can be used by managers to improve retention rates in the ICT sector of the country.

Limitations

In order to understand the applicability of the results of this research, it is crucial to determine the limitations of this study. Acknowledgement of limitations provided in this section aims at putting the research findings in context so that the reader could establish the validity of the scientific work and the credibility of findings. This section provides a list of limitations and a concise analysis of the possible impact on the reliability research findings.

First, it should be acknowledged that the results of this study apply only to the telecommunication sector in the UAE. The final sample included employees of telecom operators and regulators of the UAE, which implies that the applying the results of this study to another population may be associated with significant bias. However, since this study is based upon previous research and adds to the generalizability of the current body of knowledge, its results can be applied to other industries and countries with caution.

Second, this sample of size of the study was limited to 176 participants, which is approximately 0.36% of the population. Even though the sample size was larger than the minimal sample size calculated in Section 3.4 using a Cochran’s formula, it may limit the reliability of findings. Thus, when evaluating the reliability of findings of this study, the reader should consider that the sample size may be a source of bias.

Third, the research could not guarantee that sampling was truly random. The researcher contacted HR managers of different organizations, which distributed invitations among their employees. Therefore, the research could not control the sampling process which may have led to bias. The HR managers could have selected the participants based on their own opinion about which employees could participate in the survey. Therefore, the results of the analysis may be biased due to the lack of control over the sampling process.

Fourth, the data analysis violated the assumption of normality for intention to stay. While normality of five out of six variables was established with a high degree of certainty. However, the analysis of distribution of intention to stay demonstrated that the distribution of the variable did follow the normal distribution curve. According to Pek et al. (2018), non-normality may lead to significant errors in the statistical analysis. As a result, it can lead to incorrect results and conclusion. Thus, when evaluating the results of the study, it is crucial for the reader to understand that the assumption of normality was violated.

Fifth, the it could not be guaranteed that the relationship between different pairs of variables was linear. For instance, as it was seen in Figure 8, the relationship between intention to stay and job satisfaction was difficult to understand based on the scatterplot. Similarly, the relationships between other variables were non-linear, which may have affected the accuracy of the results (McClaive et al., 2018). This may be a significant issue when accompanied by the absence of normality for intention to stay. Therefore, the conclusions drawn from the analysis of intention to stay may be biased.

Sixth, this research did not inspect all the possible inter-relations among the six variables. Even though Pearson’s correlation analysis helped to establish direct inter-relations among all the variables, there numerous other possible relationships among the variables. For instance, it could be beneficial to inspect the role of job satisfaction as a mediator in the correlation between work engagement and intention to stay. Since the study did not account for all the possible inter-relationship between the six variables, there may still be hidden relationships that were not discovered by the analysis provided in this paper.

Seventh, the models tested in this research were very simple. This research aimed at testing numerous relationships, which did not allow to conduct in-depth analysis of any single relationship. All the models included either two or three variables without any control variables, which may have affected the accuracy of the results. Therefore, the results of this paper may require further confirmation using more complicated statistical models.

Finally, the study is limited by the qualifications of the researcher. Even though the researcher has large experience in management of organizations in the UAE and significant academic background, it is the first large-scale study conducted by the author. The researcher acknowledged this limitation and used every opportunity to consult with University authorities to minimize errors and biases implied by the lack of experience in academic research. However, it may still be a significant limitation to the study.

Recommendations

Recommendations for Managers

The list of recommendations provided below is based upon the findings of this research. The list is focuses on how to increase job satisfaction and retention levels in the ICT sector in the UAE. Human resources are the greatest asset for any company, as they possess the knowledge and the skill that can be used to grow the company’s profitability. Therefore, it is crucial for all company to keep the employees satisfied. Even though the literature on the topic of workplace satisfaction and turnover is abundant (Abdullah et al., 2011; Mashuri & Maharani, 2019; Jiang et al., 2019; Sasso et al., 2019; Abo El Nasr & Medhat, 2015; Saks & Gruman, 2014; Smith, 2018), there is a lack of relevant knowledge available for the ICT sector in the United Arab Emirates. The sector of telecommunication is expected a substantial growth by 2025 due to its significance and governmental support (Mordor Intelligence, 2021). Previous studies revealed numerous factors that affected workplace satisfaction, including person-environment fit, psychological capital, job satisfaction, job engagement, organizational commitment, intention to stay (Abdullah et al., 2019; Smith, 2018).

This study examined 12 different inter-relations among these variables, which allowed to formulate the following recommendations for manager to improve job satisfaction and retention levels.

Focus on job satisfaction and P-E fit to increase retention rates. While this suggestion may be obvious for some managers, the influence of job satisfaction on intention to stay in the ICT sector in the UAE has not been tested before this paper. The correlation analysis revealed that job satisfaction and P-E fit are strongly positively correlated with intention to stay. Therefore, if managers want to improve retention level of employees, they are recommended to implement strategies for improving P-E fit and job satisfaction.
Improve P-E fit to increase job satisfaction. The correlation between P-E fit and job satisfaction is very strong (r = 0.75), which implies that increasing P-E fit is likely to increase job satisfaction. While it may be assumed that the correlation works in both ways, the P-E fit theory states that P-E fit is a predictor of job satisfaction but not vice versa. According to Ajayi et al. (2021), common strategies to increase P-E fit include frequent communication between managers and employees, mentorship, and cross-cultural competence training to decrease discrimination and culture-based bias. However, managers are advised to search for strategies that fir best for their context considering the organizational culture of the company.
Avoid focusing on organizational commitment to increase job satisfaction or intention to stay. The relationship between organizational commitment and job satisfaction was found to be weak. It was even weaker for between organizational commitment and intention to stay, which appears counter-intuitive. Therefore, managers in the ICT industry in the UAE are recommended to look for other strategies to increase job satisfaction and intention to stay instead increasing organizational commitment.
Combine psychological capital and work engagement to increase job satisfaction. The analysis revealed that work engagement and psychological capital had a positive effect on job satisfaction separately. However, if combined together, the provide an even greater effect on job satisfaction, as work engagement moderates the relationship between psychological capital and job satisfaction.

Previous studies revealed numerous factors that affected workplace satisfaction, including person-environment fit, psychological capital, job satisfaction, job engagement, organizational commitment, intention to stay (Abdullah et al., 2019; Smith, 2018).

Recommendations for Future Research

The results of this research are affected by the limitations described in Section 5.3. Thus, it is recommended that future research addresses these limitations to increase reliability and generalizability of findings of this study. We provide a list of recommendations for future research below.

Apply similar design to other contexts. The generalizability of the results of this study is limited only to telecom sector of the UAE. Future research can increase the generalizability of this study by using the same design but applying to other industries and countries. An increase in generalizability of findings will allow to transfer the conclusions of this study to other business situations no limited to managing the employees of the ICT sector in the UAE.
Improve the sampling technique to improve reliability of findings. This research was limited by a relatively small sample size and researcher’s inability to ensure that all the requirements of stratified sampling were followed. Therefore, future research should test similar hypotheses using larger samples and better sampling techniques. Simple random sampling can be used to replace stratified sampling.
Address non-normality of data. This paper did not account for the absence of normality in the distribution of several variables, which may have affected the results of the study. Therefore, future research, should address the problem and ensure that the absence of normality in distribution did not affect the research results.
Test for other possible inter-relations. This research focused on testing twelve hypotheses based on results of previous studies. Future research should search for other possible inter-relations among these six variables. In particular, the mediating role of job satisfaction in the relationship between work engagement and intention to stay, or the moderating effect of psychological capital in the relationship between job satisfaction and P-E fit.
Create more complicated models. The statistical models tested in this paper were relatively simplistic, as they included only two or three variables. Future research is recommended to created more complicated statistical models, such as multiple regression analysis with several independent and control variables. However, such an endeavor appears challenging if the researchers focus on testing multiple models in one study. Thus, it is highly recommended to focus on a limited number of correlations to increase the reliability and accuracy of findings.
Consider different research design. This theory utilized quantitative research design, as it appeared the most appropriate for the purpose of the study. However, if future research focuses on a limited number of variables and inter-relations, it may consider attempting to explain the research results. In particular, it would be beneficial to use a mixed method approach so that qualitative research methods could compensate for the limitations of the qualitative analysis. According to Saunders et al. (2019), a mixed method approach is often used so that interviews and focus groups could help to explain the results of surveys.
Use other theoretical frameworks. This research utilized the affect theory and the P-E fit theory to explain the research results and the logical behind building the hypotheses. However, other theoretical frameworks can be used to address the same questions, which may increase the depth of the current body of knowledge.

Implications

Job satisfaction is an extremely complicated concept, as it is affected by numerous factors. At the same time, studying job satisfaction is crucial, as it helps to understand how employees can be retained. This study focused on studying interconnections between six variables, including work satisfaction, intention to stay, person-environment fit, engagement, psychological capital, and organizational commitment in the context of the ICT sector in the United Arab Emirates. A total of twelve hypotheses were formulated based on the review of recent literature on the topic. Pearson’s correlation, simple moderation analysis, and simple mediation analysis were used to test the hypotheses. The analysis found empirical evidence to accept nine out of 12 of them.

This research had significant implications for managers and researchers in the UAE and globally. The central implication of this study is that it provided recommendations for the managers of the ICT sector to improve employee satisfaction and retention rates. A total of four recommendations were provided based on the results of this research and previous studies. These recommendations were tailored specifically for the ICT sector in the UAE, which is of critical value for the managers in the country.

It should also be mentioned that this study provided an extensive literature review concerning inter-relations between job satisfaction, intention to stay, person-environment fit, engagement, psychological capital, and organizational commitment. The literature review included only recent article that were published no earlier than 2018. Therefore, the provided literature review is a reflection of the current body of knowledge concerning the inter-relationships between the six variables under analysis. Thus, if researchers decide to conduct similar studies, they can utilize the literature review provided in this study to acquire a general idea about the state of knowledge concerning the subject of interest.

Another crucial implication of this research is provision of extensive recommendations for future research. Careful analysis of previous studies and methodology of this research allowed to formulate seven recommendations, which will be helpful for scholars that decide to study the relationships between intention to stay and its possible predictors. This research provided recommendations concerning both methods that can be used in future research and themes that can explored in future studies.

Chapter Summary and Conclusion

This concluding chapter focused on the interpretation of the results of hypotheses testing. This chapter described numerous peculiarities of inter-relationships between the six variables. Most of the findings were consistent previous research, which increased the generalizability of previous studies. Additionally, some findings were unique, which provided significant contribution to the current body of knowledge.

The primary conclusions were that if managers in the ICT sector in the UAE want to increase retention rates, they should focus on improving job satisfaction of the employees. This study suggests that the most appropriate strategies for increasing job satisfaction is improving P-E fit, psychological capital, and work engagement. At the same time, improving organizational commitment to increase job satisfaction was proved to be not very effective. Additionally, the chapter acknowledge eight significant limitations and provided recommendations concerning how the reliability of the results can be improved in future research by addressing these limitations.

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