Exploring Personal Resources and Its Relationship with Work Engagement: A Systematic Review
- Kulliyah of Economics and Management Sciences, International Islamic University Malaysia
- Institute of Islamic Banking and Finance, International Islamic University Malaysia
Journal of Business Management and Accounting 14(2) (2024) · https://doi.org/10.32890/jbma2024.14.2.3
Abstract
This systematic review of 55 empirical studies explores the relationship between personal resources and work engagement in various work environments. Its contribution is threefold: first, to identify the constructs that illustrate the ability of personal resources; second, to analyse current methods for studying personal resources and highlighting their limitations in theoretical generalisation; and third, to examine the role of personal resources to influence work engagement. The review identifies notable gaps in existing research and offers valuable perspectives to promote employee engagement in different professional settings. Findings highlight the need for cultural and sector-specific research to understand diverse responses to job demands and resources. It suggests the integration of emerging constructs like growth mindset and emotional intelligence into these models and emphasises the need for a more varied methodological approach, including longitudinal and qualitative studies. Additionally, it highlights the need to explore the impact of social, cultural, and technological factors in this relationship. An implication from this study is that organisations can improve job satisfaction, reduce turnover intentions, and enhance overall performance by creating a supportive environment that encourages personal resources. This can be achieved through offering training and development programmes, fostering a positive work culture, and ensuring a balance between job demands and resources.
Keywords: Systematic review, personal resources, work engagement, JD-R theory
INTRODUCTION
In today’s VUCA (Volatile, Uncertainty, Complex, Ambiguous)
business environment, work engagement stands out as a critical factor of employee well-being and performance. It is defined as a fulfilling cognitive and emotional condition characterised by vigour, dedication, and absorption in one’s role (Bakker et al., 2023; Bakker & de Vries, 2021; Macey & Schneider, 2008; Schaufeli et al., 2002). Work engagement has a significant impact on both individual and organisational outcomes, specifically positive aspects such as job satisfaction, lower turnover intentions, and higher employee performance, while disengagement has negative consequences such as absenteeism and burnout (Bakker & de Vries, 2021; Bakker & Demerouti, 2017; Kahn, 1990; Schaufeli & Taris, 2014).
Despite the extensive research on work engagement and its known importance for productivity and high performance, there is a high level of disengagement globally, as shown by reports that only 21% of employees worldwide are engaged at work (Gallup, 2022, 2023; Keating & Heslin, 2015). The fact that the concept of work engagement is very complex and influenced by many factors is the reason why there are many in-depth studies (Kooij et al., 2020; Okun
& Arun, 2020; Peláez Zuberbühler et al., 2021; Rashid & Harif, 2016; Saleem et al., 2022; Schaufeli, 2021). On the other hand, there is also a great need for a review to identify the weaknesses and gaps in this rapidly growing literature.
Work engagement is a multidimensional phenomenon that can be
influenced by a variety of factors. However, the JD-R theory, which is accepted by researchers and mostly used to explain their models of work engagement, provides a clear and useful explanation of the antecedents of work engagement, namely job demands, job resources, and personal resources (Bakker, 2011; Bakker & Demerouti, 2008, 2017; Schaufeli & Taris, 2014). Job demands refer to the various aspects of a job, whether they involve physical, psychological, social, or organisational elements that require continuous effort and come at a cost, such as extended working hours, dealing with a fussy customer, and the need to manage multiple tasks simultaneously (Bakker, 2011; Bakker et al., 2023; Bakker & Demerouti, 2007, 2008, 2014). On the other hand, various job resources such as performance feedback, rewards, teamwork, and support from superiors mitigate the impact of job demands. These resources not only make it easier to deal with work-related pressure but also enable individuals to achieve their work goals and promote their personal growth (Bakker & Demerouti, 2017; Brenninkmeijer et al., 2010; Demerouti et al., 2001; Xanthopoulou et al., 2012).
Personal resources refer to psychological or cognitive attributes associated with the capacity to effectively influence one’s environment (Bakker et al., 2023; Schaufeli & Taris, 2014). The emphasis of the Job Demands-Resources (JD-R) model on the role of personal resources alongside job resources and job demands in predicting work engagement shows how important they are in well-being research (Bakker et al., 2014; Bakker & Demerouti, 2017; Tummers & Bakker, 2021). Furthermore, meta-analyses suggest that personal resources have a stronger correlation with work engagement compared to other factors (Mazzetti et al., 2021, 2023). Therefore, there is a need for an integrated synthesis of existing research that explores the details of this relationship, focusing in particular on how changing work environments might impact this relationship. This study aims to systematically review the literature, particularly regarding personal resources and work engagement, to identify critical gaps, update recent developments, and provide actionable insights to promote employee engagement in a rapidly changing work landscape.
This paper systematically reviews 55 empirical studies that focus on personal resources and their impact on work engagement. This study aims to make three contributions. First, it aims to identify the constructs that demonstrate the capacity for personal resources. Second, to examine the current methodological approach to personal resources and its shortcomings in generalising into theories. Third, the role of personal resources in relation to work engagement will be explored, e.g., whether they are independent, mediating, or moderating.
The introductory section details the components of the article and the aim of the study. The next section addresses the literature review by examining personal resources and discussing their definition, relevance, and impact on work engagement in different theoretical contexts. Following this, the techniques of the systematic review are explained in detail, including search strategies and selection criteria. The review critically analyses the impact of personal resources on work engagement, considering various moderating and mediating factors. The discussion offers practical strategies for organisations to improve work engagement through personal resources while highlighting avenues for future research. The conclusion summarises the key findings of the study and highlights the critical role of personal resources in increasing work engagement.
LITERATURE REVIEW
Work Engagement and Theories Used in Work Engagement Studies
Work Engagement is defined as a positive state of mind about the work, and characterised by vigour, dedication, and absorption (Bakker, 2011, 2017; Schaufeli, 2017; Schaufeli & Salanova, 2007). Vigour is about the energy you feel when you think about your work, such as when you wake up, you feel energised about your work (Schaufeli & Bakker, 2004). Dedication is simply something about finding value in your work. Within the context of work engagement, dedication is described as a feeling of importance, excitement, pride, and a sense of challenge (Schaufeli et al., 2002), such as deriving a profound sense of fulfillment from contributing to meaningful projects or experiencing genuine enthusiasm for overcoming professional challenges. Absorption, the final dimension of work engagement, is distinct by complete concentration, a sense of enjoyment in tasks, a perception that time passes rapidly, and challenges in separating yourself from work (Schaufeli & Bakker, 2010). This characteristic of work engagement is the most accepted one in the literature and is used by many researchers.
Although many theories in the literature explain work engagement, some theories such as Job Demands-Resources (JD-R) theory, Conservation of Resources (COR) theory, Self-Determination theory (SDT), Self-Cognitive theory (SCT) are mostly used by researchers, and this reveals a complex understanding of the factors influencing employee well-being and performance. The JD-R model posits that work engagement is a result of the interplay between job demands and resources, and personal resources, emphasizing the role of personal and environmental factors (Bakker & Demerouti, 2017; Tummers & Bakker, 2021; Xanthopoulou et al., 2007, 2012). Similarly, COR theory underscores the significance of resource dynamics, positing work engagement as a process of resource gain and preservation (Halbesleben et al., 2014; Hobfoll et al., 2018). Both theories converge in recognising the crucial role of job resources in fostering work engagement, aligning with the shared idea that a resource-rich environment contributes to employee well-being.
On the other hand, Self-Determination Theory (SDT) and Social Cognitive Theory (SCT) bring unique perspectives to the concept of work engagement. SDT highlights the importance of intrinsic motivation and psychological needs, asserting that employees are more engaged when they experience autonomy, competence, and relatedness (Bakker & van Woerkom, 2017; Deci & Ryan, 2002; Ryan & Deci, 2000). SCT, rooted in observational learning and social influences, underscores the impact of role models and social support on work engagement (Bandura, 1989, 1999; Lyons & Bandura, 2021). While both SDT and SCT share the common ground of emphasizing the individual and social aspects of engagement, they diverge from JD-R and COR in their theoretical roots and focus, offering complementary insights into the psychological and social dimensions of work engagement.
As these theories are essential in explaining work engagement, researchers have conducted various studies on work engagement, highlighting its significance for employee well-being, performance, satisfaction, and turnover intention, among other factors (Firzly et al., 2022; Karatepe & Karadas, 2015; Rich et al., 2010; Şahin & Çankır, 2018; Singh, 2018). In these studies, the countries and sectors examined are remarkably diverse, ranging from Pakistan to Chile and encompassing sectors such as telecommunications and healthcare. For instance, research conducted on a sample of healthcare employees in the Netherlands revealed that work engagement is mediated by self-leadership, performance, and commitment with the explanation grounded in the self-leadership concept within self- determination theory (van Dorssen-Boog et al., 2021). Furthermore, a study by Lupsa et al. (2020) found that in Romanian public and private sector employees, work engagement serves as a mediator between psychological capital, organizational justice, and health, and the motivational process outlined in the JD-R theory explained the relationships in this study.
Personal Resources and Their Relationship with Work Engagement
Personal resource is a concept related to aspects of individuals’ capacity to actively shape their environment rather than passively existing in the workplace. These elements, linked to resilience, are essential components of one’s identity, reflecting the individual’s perception of their ability to influence and effectively manage their surroundings (Hobfoll et al., 2003). Similar to job resources, personal resources are essential in promoting personal growth and development, contributing significantly to the accomplishment of business objectives. These resources are integrated into the JD-R model through five ways (Schaufeli & Taris, 2014). Initially, as Bakker et al. (2010) demonstrated, personal resources directly impact well- being. Secondly, they act as moderators in the relationship between job characteristics and well-being, (Brenninkmeijer et al., 2010; van den Broeck et al., 2011). Thirdly, they mediate the relationship (Xanthopoulou et al., 2007), and fourthly, they are used to shape perceptions of job characteristics (Judge et al., 2000). And, finally, the JD-R model posits that personal resources serve as a third variable (Bakker et al., 2010).
Similar to the JD-R theory, the COR theory also uses personal resources and explains several research models related to work engagement. This theory is grounded in the idea that individuals possess a fixed amount of personal resources, and their decisions to preserve or enhance these resources are influenced by motivational factors (Hobfoll, 1989). The quantity of personal resources an individual keeps at any given moment is believed to positively impact their ability to invest in a given situation (Alessandri et al., 2018). The literature gives examples of personal resources, such as psychological capital (PsyCap), and their relation to work engagement. Thus, the absolute level of PsyCap (referring to the individual’s reported score at a specific moment) is an indicator of the personal resources available for investment in one’s professional endeavours (Alessandri et al., 2018). Individuals with high PsyCap levels are more likely to be committed, channeling more energy into their work, and enhancing their dedication to achieving goals. This leads to deeper involvement in their work (Alessandri et al., 2018; George et al., 2022; Rozkwitalska et al., 2022).
In recent literature, personal resources and work engagement have been extensively studied, with certain constructs acknowledged as personal resources. These include PsyCap, self-efficacy, strength use, self-leadership, resiliency, self-esteem, psychological ownership, optimism, mindfulness, emotional intelligence, religiosity, intrinsic motivation, growth mindset, psychological detachment, and numerous others (Abualigah et al., 2023; Amponsah-Tawiah et al., 2023; Brennan et al., 2023; Ghosh et al., 2020; Hamel et al., 2023; Inam et al., 2021; Matsuo, 2022; Naeem et al., 2020; Nandini et al., 2022; Nehra, 2023; Saleem et al., 2022; Schilbach et al., 2023; Su et al., 2022). Notably, research in 2024 suggests personal resources predict work engagement and positive outcomes such as adaptation (Vincent et al., 2024). These personal resources have demonstrated their significance in influencing work engagement and other potential positive workplace outcomes across various sectors and countries, as evidenced by studies. Studies show that personal resources play roles in reducing the effects of job demands and enhancing the impact of job resources. For instance, in some studies, PsyCap and intrinsic motivation were found to mitigate the effects of job demands, resulting in increased work engagement (Ghosh et al., 2020; Lupsa et al., 2020; Peláez Zuberbühler et al., 2021). Additionally, other studies indicated that personal resources act as enhancers of job resources; employees with personal resources tend to make better use of job resources, leading to a heightened sense of engagement at work (Matsuo, 2022; Mubashar & Harzer, 2023).
METHODOLOGY
A systematic review was carried out to examine and detail the existing empirical studies on the relationship between personal resources and work engagement in work settings. This review followed the methodology outlined by Denyer & Tranfield (2009). The process involved searching through a scientific database using specific keywords Research papers were selected based on established criteria, and their content was thoroughly evaluated and analysed. The insights were then categorized and presented in a coherent and structured manner.
Search Strategy
In order to find relevant research for the analysis, an electronic search was conducted based on an abstract screening. This search was carried out using two prominent databases: Scopus and Web of Science. The term ‘work engagement’ (WE) was expanded to include its other commonly used names, such as ‘employee engagement’ (Amponsah- Tawiah et al., 2023; Ghosh et al., 2020; Nehra, 2023; Rashid & Harif, 2016), and ‘job engagement’ (Ojo et al., 2021), these terms were also included in the search. The search was conducted using a combination of keywords: “personal resource” AND “work engagement” OR “employee engagement” OR “ job engagement”.
Selection Criteria
To be included in the review, studies had to meet the following six requirements:
1) It had to be published in English 2) In a peer-reviewed academic journal 3) Within the last five years, from 2018 to 2023, which has seen an increase in empirical research on the topic 4) The research had to involve participants from the workforce, thus excluding reports on sports, clinical or academic groups 5) The relationship between personal resources and work engagement (WE) had to be explored 6) The study had to analyse current empirical evidence.
There was no exclusion based on the type of research method, so studies could be either quantitative or qualitative. They could include different designs such as case studies, cross-sectional analyses, and quasi-experimental approaches. However, literature reviews, editorials, and studies of a purely theoretical nature were excluded as they did not meet the following criteria.
Data Abstraction and Synthesis
The researcher narrowed the search within the selected online databases by applying specific selection criteria:
1) Language 2) Year of publication 3) Peer-reviewed scientific journals
The initial search returned 239 records from Scopus and 59 from Web of Science. The researcher then reviewed the abstracts to remove duplicates, which refined the set of articles for a more thorough examination of their full texts. The researcher used the Mendeley desktop application to manage, organise, and categorise these articles. After applying the remaining criteria—4 (sample), 5 (subject area), and 6 (empirical study)—the researcher included a total of 55 studies published between 2018 and 2023 in the review. Figure 1 illustrates the search and selection process as a flowchart.
RESULTS AND DISCUSSIONS
Results
After conducting extensive and detailed examinations, 55 papers were included in the analysis. After a thorough reading, analysis, and integration of these articles, four primary themes relevant to the objectives of the review emerged. The text outlines the following aspects:
1) Study characteristics
2) Theoretical underpinnings
3) Methods used
4) The relationship between personal resources and Work Engagement
(WE).
Theoretical underpinnings Methods used The relationshipJournal of Business between Management personal and Accounting, resources and Work Vol. 14,Engagement Number 2 (July) 2024, (WE). 237-275 ure 1 Figure 1 y Selection Flowchart Study Selection Flowchart me 1: Study Characteristics Theme 1: Study Characteristics review of the The55review research of articles the 55 shows researchthat studiesshows articles were that conducted studies across were a diverse rang inents and countries: conducted across a diverse range of continents and countries: Asia South and N Asia (25 studies), Europe (18 studies), Africa (7 studies), erica (3 studies), (25 Australia (1 study), studies), Europe (18and Multiple studies), countries Africa (1 study). (7 studies), SouthChina and India had the hig and North ber of contributions, Americaeach accounting (3 studies), for five Australia (1 studies. study), The distribution and Multiple of studies countries (1 over the years study). China and India had the highest number of contributions, each accounting for five studies. The distribution 6 of studies over the years is as follows: 2018 (2 studies), 2019 (3 studies), 2020 (4 studies), 2021 (12 studies), 2022 (18 studies), and 2023 (16 studies). The studies covered various sectors, with 11 of them focusing on multiple sectors. follows: 2018 (2 studies), 2019 (3 studies), 2020 (4 studies), 2021 (12 studies), 2022 (18 studies), and 2023 Other noteworthy sectors were public, education, and healthcare. (16 studies). The studies covered various sectors, with 11 of them focusing on multiple sectors. Other noteworthy sectors were public, education, and healthcare.
The figure itself is in the PDF version.
The figure itself is in the PDF version.
| Authors (Citation) | Country of the Study/Sector | Variable as Personal Resource and Its Role | Unit of Analysis | Hypothesis between PR and WE | Theory Used | Method and Analysis | Sample/ Study Design | |
|---|---|---|---|---|---|---|---|---|
| 1 | Inam et al. (2021) | Pakistan/Telecom | Self-Leadership- Independent | Individual | Accepted | 1. Social Cognitive Theory 2. Intrinsic Motivation Theory | Quantitative- SEM | 318 middle-level manager- 2 wave data collection/ Non-experimental |
| 2 | Chan et al. (2020) | Hong Kong/Education | Self-Efficacy- Independent | Individual | Accepted | 1. Social Cognitive Theory 2. Self-Determination Theory | Quantitative -PLS- SEM | 292 Teaching assistant/ Cross-sectional |
| 3 | Pakistan/Manufacturing | Self-Efficacy- Independent | Individual | Accepted | 1. Social Cognitive Theory | Quantitative- SPSS PROCESS MACRO model | 373 employees working in different manufacturing organizations - 2 wave data collection/ Non-experimental | |
| 4 | Saleem et al. (2022) | Malaysia/Construction | PsyCap-Independent | Individual | Accepted | 1. Social Cognitive Theory | Quantitative- SEM | 345 construction workers/ Cross-sectional |
| 5 | Zhu et al. (2022) | China | Self-Efficacy-Independent | Individual | Accepted | 1. Social Cognitive Theory 2. Cognitive Appraisal Theory | Quantitative- SEM LISREL | Cross-sectional - Quasi experimental |
| Italy/ | 1219 employees/ | |||||||
| 6 | Giancaspro et al. (2022) | Mix Sectors (private and public) | PsyCap- Independent | Individual | Accepted | 1. JD-R Theory 2. COR Theory 3. Social Cognitive Theory | Quantitative- SEM | Cross-sectional |
| Japan/ | Study 1- 459 nurses Study 2- 248 nurses 3 wave data collection | |||||||
| 7 | Healthcare | Strength Use, and Mindfulness- Independent | Individual | Accepted | 1. Self-Determination Theory | Quantitative- SEM | Non-experimental | |
| India/ | 324 employees in automobile sector/ | |||||||
| 8 | Automotive | Self-Leadership- Independent | Individual | Accepted | 1. Self-Determination Theory 2. Broaden and Build Theory | Quantitative- SPSS PROCESS MACRO model | Cross-sectional | |
| 9 | Nehra (2023) | India/ IT | Psychological Detachment- Independent Spirituality, Intrinsic Motivation - Mediating | Individual | Accepted | 1. Self-Determination Theory 2. Broaden and Build Theory | Quantitative- SEM | 408 employees - 3 wave data collection. Non-experimental |
| France/ | 120 employees - 3 wave data collection/ | |||||||
| 10 | Roussillon Soyer et al. (2022) | Beverage | Autonomous Motivation- Independent | Individual | Accepted | 1. Self-Determination Theory | Quantitative- SPSS PROCESS MACRO model | Longitudinal study design |
| Netherlands/ | 195 health care professionals - 3 wave/ | |||||||
| 11 | van Dorssen-Boog et al. (2021) | Healthcare | Self-Leadership- Independent | Individual | Accepted | 1. Self-Determination Theory 2. Self-Leadership Theory | Quantitative- Logistic Regression | Longitudinal study design |
| Japan/ | 288 employees/ | |||||||
| 12 | Ghosh et al. (2020) | Multiple Sectors | Intrinsic Motivation | Individual | Accepted | 1. Self-Determination Theory 2. Unconscious thought theory 3. JD-R Theory | Quantitative- first stage moderated mediation model | Cross-sectional |
| Poland/ | 495 Polish office employees/ | |||||||
| 13 | Rozkwitalska et al. (2022) | Manufacturing and Service Industry | PsyCap - Independent | Individual | Accepted | 1. JD-R Theory 2. COR Theory | Quantitative- SEM | Cross-sectional |
| Nigeria/ | 528 Public sector employees/ | |||||||
| 14 | George et al. (2022) | Public | Emotional Intelligence- PsyCap - Independent | Individual | Accepted | 1. COR Theory 2. The cognitive–motivational– reactional theory | Quantitative - a serial mediation model | Cross-sectional |
| Romania/ | 193 social workers/ | |||||||
| 15 | Lupsa et al. (2020) | Public and Private | PsyCap - Independent | Individual | Accepted | 1. JD-R Theory 2. COR Theory | Quantitative- SEM | Cross-sectional |
| Italy/ | 420 white-collar employees/ | |||||||
| 16 | Alessandri et al. (2018) | Multiple Sectors | PsyCap - Independent | Individual | Accepted | 1. COR Theory | Quantitative- SEM | Cross-sectional |
| Ghana/ | 274 full‒time frontline employees - 2 wave data collection/ | |||||||
| 17 | Ampofo (2021) | Hotel | Psychological Contract - Independent | Individual | Accepted | 1. COR Theory | Quantitative- SEM | Non-experimental |
| United Kingdom/ | 348 entrepreneurs- 1002 employees- 4-wave data collection/ | |||||||
| 18 | Multiple Sectors | PsyCap - Mediating | Individual | Accepted | 1. JD-R Theory 2. Work Recovery Approach | Quantitative- SEM | Non-experimental | |
| Spain and Latin American Countries/ | 252 employees/ | |||||||
| 19 | Service Sector | PsyCap - Mediating | Individual | Accepted | 1. JD-R Theory 2. COR Theory | Quantitative- SEM | Cross-sectional | |
| India/ | 530 salespeople/ | |||||||
| 20 | Gupta et al. (2022) | B2B Sales | PsyCap - Independent | Individual | Accepted | 1. Social Cognitive Theory 2. JD-R Theory | Quantitative- SEM | Cross-sectional |
| Greece/ | 1011 employees/ | |||||||
| 21 | Katou et al. (2022) | Multiple Sectors | Personal Resource- Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- Multilevel SEM | Cross-sectional |
| Germany/ | 1145 manufacturing employees/ | |||||||
| 22 | Döbler et al. (2022) | Manufacturing | Personal Resource- Moderating | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| Türkiye/ | 416 employees/ | |||||||
| 23 | Koroglu & Ozmen (2022) | Multiple Sectors | Psychological Well-Being- Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| China/ | 276 employees/ | |||||||
| 24 | Su et al. (2022) | Social Services Sector | Psychological Ownership - Mediating | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| Netherlands/ | 9,465 employees/ | |||||||
| 25 | Borst et al. (2019) | Public | Personal Resource- Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- Mplus SEM | Cross-sectional |
| Indonesia/ | Study 1 - 185 employees/survey Study 2 - 17 managers/semi-structured interview | |||||||
| 26 | Nandini et al. (2022) | Digital Start-up | Self-Efficacy, and growth mindset - Independent | Individual | Accepted | 1. JD-R Theory | Mixed Method- Semi Structured Interview, content analysis and SEM | Cross-Sectional |
| India/ | 630 Indian school teachers/ | |||||||
| 27 | Pathardikar et al. (2023) | Education | Self-Esteem - Independent | Individual | Accepted | 1. JD-R Theory 2. Social cognitive career theory | Quantitative- SEM | Cross-Sectional |
| Pakistan/ | 202 top managers/ | |||||||
| 28 | Mubashar & Harzer (2023) | Banking | Signature Strength Use - Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-Sectional |
| Ghana/ | 482 bank employees/ | |||||||
| 29 | Amponsah-Tawiah et al. (2023) | Banking | Emotional Intelligence - Independent | Individual | Accepted | 1. Appraisal Theory | Quantitative- SEM | Cross-Sectional |
| Jordan/ | 338 telecom employees/ | |||||||
| 30 | Abuaigah & Koburtay, (2023) | Telecom | Religiosity - Independent | Individual | Accepted | 1. JD-R Theory | Quantitative -PLS- SEM | Cross-Sectional |
| Tanzania/ | 202 public schools’ employees- 3-wave data collection/ | |||||||
| 31 | Jiang et al. (2023) | Private and Public Sector | Career Adaptability - Mediating Variable | Individual | Accepted | 1. JD-R Theory | Quantitative- CFA | Non-experimental |
| Saudi Arabia/ | 306 employees in Government organisations/ | |||||||
| 32 | Alamri (2023) | Public | Public Service motivation - Moderating | Individual | Accepted | 1. Self-regulatory theory 2. Public Service Motivation Theory | Quantitative- SPSS PROCESS MACRO model | Cross-Sectional |
| India/ | 284 HR managers/ | |||||||
| 33 | Kataria et al. (2023) | IT | PsyCap- Moderating | Individual | Accepted | 1. Social Exchange Theory | Quantitative- SEM | Cross-Sectional |
| Nigeria/ | 233 nurses/ | |||||||
| 34 | Balogun (2023) | Healtcare and Public | Self-Efficacy, and resilience - Moderating | Individual | Accepted | 1. COR Theory | Quantitative- Moderated Regression | Cross-Sectional |
| U.S./ | 850 employees- 3-wave/ | |||||||
| 35 | Etzel et al. (2023) | IT | compassionate goal orientation - mediating | Individual | not accepted | 1. Egosystem-Ecosystem theory of social motivation | Quantitative-random intercepts cross-lagged panel model | Longitudinal study design |
| Ireland / | Study 1- 279 employees- 3-wave data collection Study 2- 46 supervisors/ | |||||||
| 36 | Public | optimism - Moderating | Individual | Accepted | 1. COR Theory | Quantitative- Hierarchical linear regression | Longitudinal and Cross sectional | |
| Jordan/ | 367 telecom employees/ | |||||||
| 37 | Abualigah et al. (2023) | Multiple Sectors | Religiosity - Moderating | Individual | Accepted | 1. JD-R Theory | Quantitative -PLS- SEM | Cross-sectional |
| Palestine/ | 423 employees/ | |||||||
| 38 | Abukhalifa et al. (2023) | Non-Profit Sector | PsyCap - Moderating | Individual | Accepted | 1. JD-R Theory 2. Broaden and Buiild theory | Quantitative- SEM | Cross-sectional |
| Nigeria/ | 139 lecturers/ | |||||||
| 39 | Edokpolor et al. (2022) | Public Education Sector | Self-Efficacy- Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- Simple linear regression | Cross-sectional |
| Romania/ | 87 employees- 5-daysdata collection/ | |||||||
| 40 | Multinational Company | Stength Use - Moderating | Individual | Accepted | 1. JD-R Theory 2. COR Theory | Quantitative -Hierarchical Linear Modeling | Daily diary studies | |
| Netherlands/ | 144 employees/ | |||||||
| 41 | van Gelder et al. (2022) | Multiple Sectors | 1. Work-life segmentation preference, and 2. digital leadership- Moderating | Individual | 1. Accepted 2. Not accepted | 1. JD-R Theory | Quantitative- CFA | Cross-sectional |
| Poland/ | 450 knowledge workers/ | |||||||
| 42 | Wojtczuk-Turek (2022) | Multiple Sectors | Personal Values- Moderating | Individual | Accepted | 1. JD-R Theory | Quantitative- CFA | Cross-sectional |
| Australia/ | 401 nurses / | |||||||
| 43 | Grover et al. (2018) | Healthcare | PsyCap - Independent Psychological Well-Being - Mediating | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| China/ | 97 employees- 2-days study | |||||||
| 44 | Service Sector | Personal resources at home and at work - Independent and mediating | Individual | Accepted | 1. COR Theory | Quantitative -Hierarchical Linear Modeling | Daily diary studies | |
| Russia/ | 141 bank employees- 3-wave data collection | |||||||
| 45 | Karatepe et al. (2019) | Banking | Self-Efficacy- Independent | Individual | Accepted | 1. JD-R Theory 2. COR Theory 3. Social Information Processes | Quantitative- SEM | Non-experimental |
| Brazil/ | 451 teachers/ | |||||||
| 46 | da Silva et al. (2021) | Education | Self-Efficacy- Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| South Africa/ | 353 teachers/ | |||||||
| 47 | Education | PsyCap, and emotional intelligence - Independent | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional | |
| Vietnam / | 602 employees / | |||||||
| 48 | Truong et al. (2021) | SME | Personal Resources - Independent | Individual | Accepted | 1. JD-R Theory 2. Social exchange theory | Quantitative -PLS- SEM | Cross-sectional |
| Netherlands/ | 1,048 employees- 2-wave data collection/ | |||||||
| 49 | Public Service Agency | Optimism, efficacy, resiliency, and flexibility - Mediating | Team and Multilevel | Accepted | 1. Self-determination theory | Quantitative- SEM | Longitudinal study design | |
| Finland/ | 396 academic engineers and architects/ | |||||||
| 50 | Multiple Sectors | PsyCap - Independent | Individual | Accepted | 1. COR Theory | Quantitative- SEM | Cross-sectional | |
| Indonesia/ | 782 employees / | |||||||
| 51 | Zulkarnain et al. (2023) | Palm Oil Sector | Personality Character | Individual | Accepted | 1. Work Engagement Theory | Quantitative- Hierarchical Regression | Cross-sectional |
| China/ | 358 employees/ | |||||||
| 52 | Yin (2023) | Multiple Sectors | Paradox Mindset | Individual | Accepted | 1. JD-R Theory | Quantitative- SEM | Cross-sectional |
| France/ | 472 employees/ | |||||||
| 53 | Hamel et al. (2023) | Multiple Sectors | Secure Workplace attachment | Individual | Accepted | 1. JD-R Theory | Quantitative- SPSS PROCESS MACRO model | Cross-sectional |
| Chile/ | 200 employees/ | |||||||
| 54 | Textile industry | psychological empowerment | Individual | Accepted | 1. JD-R Theory | Quantitative- SPSS PROCESS MACRO model | Cross-sectional | |
| Malaysia/ | 259 employees/ | |||||||
| 55 | Ojo et al. (2021) | Knowledge-based sector | Resilience - Independent | Individual | Accepted | 1. COR Theory | Quantitative -PLS- SEM | Cross-sectional |
1Social Cognitive Theory
Chan et al. Hong Kong/ Self-Efficacy- Quantitative -PLS- 292 Teaching assistant/
2 Individual Accepted 2. Self-Determination
(2020) Education Independent SEM Cross-sectional
Theory
373 employees working
Quantitative- SPSS in different manufacturing
Naeem et al. Pakistan/ Self-Efficacy-
3 Individual Accepted 1. Social Cognitive Theory PROCESS MACRO organizations - 2 wave data
(2020) Manufacturing Independent
model collection/
Non-experimental
Saleem et al. Malaysia/ PsyCap- 345 construction workers/
4 Individual Accepted 1. Social Cognitive Theory Quantitative- SEM
(2022) Construction Independent Cross-sectional
1. Social Cognitive Theory Quantitative- SEM Cross-sectional - Quasi
Zhu et al. China Self-Efficacy- LISREL experimental
5 Individual Accepted 2. Cognitive Appraisal
(2022) Independent
Theory
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Italy/
1. JD-R Theory
Giancaspro et Mix Sectors PsyCap- 1219 employees/
6 Individual Accepted 2. COR Theory Quantitative- SEM
al. (2022) (private and Independent Cross-sectional
3. Social Cognitive Theory
public)
Strength Study 1- 459 nurses
Japan/ Use, and 1. Self-Determination Study 2- 248 nurses
7 Matsuo (2022) Individual Accepted Quantitative- SEM
Healthcare Mindfulness- Theory 3 wave data collection
Independent Non-experimental
1Self-Determination
Self- Quantitative- SPSS 324 employees in
Jnaneswar & India/ Theory
8 Leadership- Individual Accepted PROCESS MACRO automobile sector/
Ranjit (2023) Automotive 2. Broaden and Build
Independent model Cross-sectional
Theory
Psychological
Detachment-
Independent 1. Self-Determination
408 employees - 3 wave
India/ Theory
9 Nehra (2023) Individual Accepted Quantitative- SEM data collection.
IT Spirituality, 2. Broaden and Build
Non-experimental
Intrinsic Theory
Motivation -
Mediating
Roussillon Autonomous Quantitative- SPSS 120 employees - 3 wave
France/ 1. Self-Determination
10 Soyer et al. Motivation- Individual Accepted PROCESS MACRO data collection/
Beverage Theory
(2022) Independent model Longitudinal study design
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
van Dorssen- Self- 1. Self-Determination 195 health care
Netherlands/ Quantitative-
11 Boog et al. Leadership- Individual Accepted Theory professionals - 3 wave/
Healthcare Logistic Regression
(2021) Independent 2. Self-Leadership Theory Longitudinal study design
1. Self-Determination
Quantitative- first
Japan/ Theory
Ghosh et al. Intrinsic stage moderated 288 employees/
12 Multiple Individual Accepted 2. Unconscious thought
(2020) Motivation mediation Cross-sectional
Sectors theory
model
3. JD-R Theory
Poland/
495 Polish office
Rozkwitalska Manufacturing PsyCap - 1. JD-R Theory
13 Individual Accepted Quantitative- SEM employees/
et al. (2022) and Service Independent 2. COR Theory
Cross-sectional
Industry
Emotional 1. COR Theory
528 Public sector
George et al. Nigeria/ Intelligence- 2. The cognitive– Quantitative - a serial
14 Individual Accepted employees/
(2022) Public PsyCap - motivational– mediation model
Cross-sectional
Independent reactional theory
Romania/
Lupsa et al. PsyCap - 1. JD-R Theory 193 social workers/
15 Public and Individual Accepted Quantitative- SEM
(2020) Independent 2. COR Theory Cross-sectional
Private
Italy/
Alessandri et PsyCap - 420 white-collar employees/
16 Multiple Individual Accepted 1. COR Theory Quantitative- SEM
al. (2018) Independent Cross-sectional
Sectors
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
274 full‒time frontline
Psychological
Ampofo Ghana/ employees - 2 wave data
17 Contract - Individual Accepted 1. COR Theory Quantitative- SEM
(2021) Hotel collection/
Independent
Non-experimental
United 348 entrepreneurs- 1002
1JD-R Theory
Obschonka et Kingdom/ PsyCap - employees- 4-wave data
18 Individual Accepted 2. Work Recovery Quantitative- SEM
al. (2023) Multiple Mediating collection/
Approach
Sectors Non-experimental
Spain and
Peláez Latin
PsyCap - 1. JD-R Theory 252 employees/
19 Zuberbühler et American Individual Accepted Quantitative- SEM
Mediating 2. COR Theory Cross-sectional
al. (2021) Countries/
Service Sector
Gupta et al. India/ PsyCap - 1. Social Cognitive Theory 530 salespeople/
20 Individual Accepted Quantitative- SEM
(2022) B2B Sales Independent 2. JD-R Theory Cross-sectional
Greece/ Personal
Katou et al. Quantitative- 1011 employees/
21 Multiple Resource- Individual Accepted 1. JD-R Theory
(2022) Multilevel SEM Cross-sectional
Sectors Independent
Personal 1145 manufacturing
Döbler et al. Germany/
22 Resource- Individual Accepted 1. JD-R Theory Quantitative- SEM employees/
(2022) Manufacturing
Moderating Cross-sectional
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Türkiye/ Psychological
Koroglu & 416 employees/
23 Multiple Well-Being- Individual Accepted 1. JD-R Theory Quantitative- SEM
Ozmen (2022) Cross-sectional
Sectors Independent
China/
Psychological
Su et al. Social 276 employees/
24 Ownership - Individual Accepted 1. JD-R Theory Quantitative- SEM
(2022) Services Cross-sectional
Mediating
Sector
Personal
Borst et al. Netherlands/ Quantitative- Mplus 9,465 employees/
25 Resource- Individual Accepted 1. JD-R Theory
(2019) Public SEM Cross-sectional
Independent
Study 1 - 185 employees/
Self-Efficacy, Mixed Method- Semi survey
Indonesia/
Nandini et al. and growth Structured Interview,
26 Digital Start- Individual Accepted 1. JD-R Theory
(2022) mindset - content analysis and Study 2 - 17 managers/semi-
up
Independent SEM structured interview
Cross-Sectional
1. JD-R Theory
Pathardikar et India/ Self-Esteem - 630 Indian school teachers/
27 Individual Accepted Quantitative- SEM
al. (2023) Education Independent 2. Social cognitive career Cross-Sectional
theory
Signature
Mubashar & Pakistan/ 202 top managers/
28 Strength Use - Individual Accepted 1. JD-R Theory Quantitative- SEM
Harzer (2023) Banking Cross-Sectional
Independent
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Amponsah- Ghana/ Emotional Individual Accepted 1. Appraisal Theory Quantitative- SEM 482 bank employees/
29 Tawiah et al. Banking Intelligence - Cross-Sectional
(2023) Independent
Abuaigah &
Jordan/ Religiosity - Quantitative -PLS- 338 telecom employees/
30 Koburtay, Individual Accepted 1. JD-R Theory
Telecom Independent SEM Cross-Sectional
(2023)
Career 202 public schools’
Tanzania/
Jiang et al. Adaptability employees- 3-wave data
31 Private and Individual Accepted 1. JD-R Theory Quantitative- CFA
(2023) - Mediating collection/
Public Sector
Variable Non-experimental
1Self-regulatory theory
Public Service Quantitative- SPSS 306 employees in
Saudi Arabia/
32 Alamri (2023) motivation - Individual Accepted PROCESS MACRO Government organisations/
Public 2. Public Service
Moderating model Cross-Sectional
Motivation Theory
Kataria et al. India/ PsyCap- 284 HR managers/
33 Individual Accepted 1. Social Exchange Theory Quantitative- SEM
(2023) IT Moderating Cross-Sectional
Nigeria/ Self-Efficacy, Quantitative-
Balogun 233 nurses/
34 Healtcare and and resilience Individual Accepted 1. COR Theory Moderated
(2023) Cross-Sectional
Public - Moderating Regression
compassionate
Quantitative-random
Etzel et al. U.S./ goal 1. Egosystem-Ecosystem 850 employees- 3-wave/
35 Individual not accepted intercepts cross-
(2023) IT orientation - theory of social motivation Longitudinal study design
lagged panel model
mediating
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Study 1- 279 employees-
3-wave data collection
Quantitative-
Brennan et al. Ireland / optimism -
36 Individual Accepted 1. COR Theory Hierarchical linear
(2023) Public Moderating Study 2- 46 supervisors/
regression
Longitudinal and Cross
sectional
Jordan/
Abualigah et Religiosity - Quantitative -PLS- 367 telecom employees/
37 Multiple Individual Accepted 1. JD-R Theory
al. (2023) Moderating SEM Cross-sectional
Sectors
Palestine/ 1. JD-R Theory
Abukhalifa et PsyCap - 423 employees/
38 Non-Profit Individual Accepted 2. Broaden and Buiild Quantitative- SEM
al. (2023) Moderating Cross-sectional
Sector theory
Nigeria/
Edokpolor et Public Self-Efficacy- Quantitative- Simple 139 lecturers/
39 Individual Accepted 1. JD-R Theory
al. (2022) Education Independent linear regression Cross-sectional
Sector
Romania/ Quantitative 87 employees- 5-daysdata
Pap et al. Stength Use - 1. JD-R Theory
40 Multinational Individual Accepted -Hierarchical Linear collection/
(2022) Moderating 2. COR Theory
Company Modeling Daily diary studies
1. Work-life
segmentation
Netherlands/ 1. Accepted
van Gelder et preference, 144 employees/
41 Multiple Individual 2. Not 1. JD-R Theory Quantitative- CFA
al. (2022) and 2. digital Cross-sectional
Sectors accepted
leadership-
Moderating
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Poland/ Personal
Wojtczuk- 450 knowledge workers/
42 Multiple Values- Individual Accepted 1. JD-R Theory Quantitative- CFA
Turek (2022) Cross-sectional
Sectors Moderating
PsyCap -
Independent
Grover et al. Australia/ 401 nurses /
43 Psychological Individual Accepted 1. JD-R Theory Quantitative- SEM
(2018) Healthcare Cross-sectional
Well-Being -
Mediating
Personal
resources at
Quantitative
Chen & China/ home and 97 employees- 2-days study
44 Individual Accepted 1. COR Theory -Hierarchical Linear
Fellenz (2020) Service Sector at work - Daily diary studies
Modeling
Independent
and mediating
1. JD-R Theory
141 bank employees-
Karatepe et al. Russia/ Self-Efficacy- 2. COR Theory
45 Individual Accepted Quantitative- SEM 3-wave data collection
(2019) Banking Independent 3. Social Information
Non-experimental
Processes
da Silva et al. Brazil/ Self-Efficacy- 451 teachers/
46 Individual Accepted 1. JD-R Theory Quantitative- SEM
(2021) Education Independent Cross-sectional
PsyCap, and
(Vermooten et South Africa/ emotional 353 teachers/
47 Individual Accepted 1. JD-R Theory Quantitative- SEM
al., 2021) Education intelligence - Cross-sectional
Independent
Authors Country of the Personal Unit of Sample/
between PR Theory Used Method and Analysis
(Citation) Study/Sector Resource and Analysis Study Design
and WE
Its Role
Personal
Truong et al. Vietnam / 1. JD-R Theory Quantitative -PLS- 602 employees /
48 Resources - Individual Accepted
(2021) SME 2. Social exchange theory SEM Cross-sectional
Independent
Optimism,
Mazzetti & Netherlands/ efficacy, 1,048 employees- 2-wave
Team and 1. Self-determination
49 Schaufeli Public Service resiliency, and Accepted Quantitative- SEM data collection/
Multilevel theory
(2022) Agency flexibility - Longitudinal study design
Mediating
Finland/ 396 academic engineers and
Toth et al. PsyCap -
50 Multiple Individual Accepted 1. COR Theory Quantitative- SEM architects/
(2023) Independent
Sectors Cross-sectional
Indonesia/ Quantitative-
Zulkarnain et Personality 1. Work Engagement 782 employees /
51 Palm Oil Individual Accepted Hierarchical
al. (2023) Character Theory Cross-sectional
Sector Regression
China/
Paradox 358 employees/
52 Yin (2023) Multiple Individual Accepted 1. JD-R Theory Quantitative- SEM
Mindset Cross-sectional
Sectors
France/ Secure Quantitative- SPSS
Hamel et al. 472 employees/
53 Multiple Workplace Individual Accepted 1. JD-R Theory PROCESS MACRO
(2023) Cross-sectional
Sectors attachment model
Chile/ Quantitative- SPSS
Juyumaya psychological 200 employees/
54 Textile Individual Accepted 1. JD-R Theory PROCESS MACRO
(2022) empowerment Cross-sectional
industry model
Malaysia/
Ojo et al. Resilience - Quantitative -PLS- 259 employees/
55 Knowledge- Individual Accepted 1. COR Theory
(2021) Independent SEM Cross-sectional
based sector
Theme 2: Theoretical Underpinnings
Among the 55 studies analysed, all studies employed theoretical frameworks to explore work engagement and personal resources. The most frequent was the JD-R (Job Demands-Resources) theory, which appeared in 31 studies. This theory posits that individuals high in personal resources are more successful in leveraging job resources, effectively dealing with job demands, and thus remaining more engaged in their work (Xanthopoulou et al., 2007). Following closely, the Conservation of Resources (COR) Theory was used in 13 studies. This theory, focusing on the resource caravan principle (‘resources travel in packs’), suggests that individuals with rich personal resources tend to use these resources to acquire others, thereby helping them stay engaged in their work (Hobfoll et al., 2018). Six studies combined JD-R and COR theories to explain their models. Studies that have used both COR and JD-R theories have explained the relationship between personal resources and work engagement, by using the characteristic in the theories that personal resources, when coupled with job resources, contribute synergistically to improved work engagement.
Additionally, several studies proposed diverse models: Ryan & Deci’s (2000) Self-Determination Theory was mentioned eight times, Bandura’s (1999) Social Cognitive Theory seven times, and Fredrickson’s (2001) Broaden-and-Build Theory three times. Other theories, each cited once, include Cognitive Appraisal Theory (Zhu et al., 2022), Unconscious Thought Theory (Ghosh et al., 2020), Social Exchange Theory (Kataria et al., 2023), Intrinsic Motivation Theory (Inam et al., 2021), Cognitive–Motivational–Reactional Theory (George et al., 2022), Appraisal Theory (Amponsah-Tawiah et al., 2023), and Public Service Motivation Theory (Alamri, 2023). Collectively, the variety of theories used could indicate the complexity of the subject matter, or it might suggest evolving perspectives in the field of work engagement and personal resources.
Theme 3: Methods Used
Almost all the articles reviewed used quantitative methods, except for one study that used a mixed method (Nandini et al., 2022). There were no qualitative studies. Structural Equation Modeling (SEM) was used in 27 of the studies, with other quantitative methods including Partial
Least Squares (PLS-SEM) and Hierarchical Linear Modeling. These findings highlight the prevalence of advanced statistical techniques in this research area.
The studies’ sample sizes varied significantly, ranging from 87 in a daily diary study (Pap et al., 2022) to 9,465 participants in the largest study (Borst et al., 2019) The mean sample size was approximately 551 (SD = 1,221.20). To determine the sample size, the researcher considered 57 studies as two of the articles contained two separate studies each (Brennan et al., 2023; Matsuo, 2022).
Of the 54 quantitative studies, 46 were non-experimental and cross- sectional (eight of which collected data in two or more waves), four used a longitudinal study design, including two daily diary studies, four conducted quasi-experimental designs involving pre-post tests, and one was a non-experimental study with data collected at two or more time points. The unit of analysis was predominantly at the individual level, except for one study that assessed both multilevel and team levels (Mazzetti & Schaufeli, 2022).
Theme 4: Relationship Between Personal Resources and Work Engagement
In the studies reviewed, 31 constructs have been identified as personal resources positively related to work engagement. The table below lists these constructs according to their roles as independent, mediating, or moderating variables. The frequency of use varies; some constructs were used only once, others multiple times, and a few were referenced more than five times. Predominantly, these constructs have been examined as independent variables, though their mediating and moderating effects have also been subjected to empirical investigation. This review highlights PsyCap as the most frequently cited personal resource, referenced 14 times, making it the primary construct of interest. Self-Efficacy, a component of PsyCap, has been independently identified 9 times in the reviewed papers. The construct of ‘personal resource’ has been used 4 times. Resilience and Self-Leadership have each been acknowledged 3 times, indicating their perceived importance. Other constructs were mentioned only once or twice. Overall, the data suggests that PsyCap, including its constituent dimensions such as Self-Efficacy, is considered a vital personal resource, mainly due to its positive association with work engagement.
| Personal Resource | Independent | Mediating | Moderating | Total |
|---|---|---|---|---|
| Self-Leadership | 3 | 0 | 0 | 3 |
| Self-Efficacy | 7 | 1 | 1 | 9 |
| PsyCap | 10 | 2 | 2 | 14 |
| Strength Use | 1 | 0 | 1 | 2 |
| Psychological Detachment | 1 | 0 | 0 | 1 |
| Spirituality | 0 | 1 | 0 | 1 |
| Autonomous Motivation | 1 | 0 | 0 | 1 |
| Intrinsic Motivation | 1 | 1 | 0 | 2 |
| Emotional Intelligence | 2 | 0 | 0 | 2 |
| Psychological Contract | 1 | 0 | 0 | 1 |
| Personal Resource | 3 | 1 | 0 | 4 |
| Psychological Well-Being | 1 | 1 | 0 | 2 |
| Psychological Ownership | 0 | 1 | 0 | 1 |
| Growth mindset | 1 | 0 | 0 | 1 |
| Flexibility | 0 | 1 | 0 | 1 |
| Signature Strength Use | 1 | 0 | 0 | 1 |
| Religiosity | 1 | 0 | 1 | 2 |
| Career Adaptability | 0 | 1 | 0 | 1 |
| Public Service motivation | 0 | 0 | 1 | 1 |
| Mindfulness | 1 | 0 | 1 | 2 |
| Resilience | 1 | 1 | 1 | 3 |
| Compassionate goal orientation | 0 | 1 | 0 | 1 |
| Optimism | 0 | 1 | 1 | 2 |
| Work-life segmentation preference | 0 | 0 | 1 | 1 |
| Personal Values | 0 | 0 | 1 | 1 |
| Digital leadership | 0 | 0 | 1 | 1 |
| Personal resources at home and at work | 1 | 1 | 0 | 2 |
| Personality Character | 1 | 0 | 0 | 1 |
| Paradox Mindset | 1 | 0 | 0 | 1 |
| Secure Workplace attachment | 1 | 0 | 0 | 1 |
| Psychological Empowerment | 1 | 0 | 0 | 1 |
| Total | 41 | 14 | 12 | 67 |
As expected, all hypotheses were accepted except for the moderating role of digital leadership in the relationship between job characteristics and work engagement (van Gelder et al., 2022) and the mediating role of compassionate goal orientation in the relationship between job resources and work engagement (Etzel et al., 2023). The results indicate that personal resources are positively related to work engagement. Notably, personal resources are mostly identified as independent variables in relation to work engagement (N=41; Alessandri et al., 2018; Ampofo, 2021; Borst et al., 2019; Katou et al., 2022; Koroglu & Ozmen, 2022; Lupsa et al., 2020; Mubashar & Harzer, 2023; Vermooten et al., 2021), with fewer studies identifying them as mediating variables (N=14; Mazzetti & Schaufeli, 2022; Obschonka et al., 2023; Peláez Zuberbühler et al., 2021). Additionally, some research has recognised personal resources as moderating the relationship between job resources and work engagement (N=12; Abukhalifa et al., 2023; Pap et al., 2022; Wojtczuk-Turek, 2022). These findings mainly focus on the individual level, except for one study that explores both team and multilevel dimensions, including insights from both employees and managers (Mazzetti & Schaufeli, 2022). Both individual-level and multilevel studies have consistently found a positive relationship between personal resources and work engagement.
Discussion on the Findings
Theme 1: Study Characteristics
The interaction between personal resources, work engagement and cultural/sectoral context represents an interesting research landscape. While this analysis offers valuable insights from different countries and sectors, there are notable limitations. Firstly, studies from North, Central and South America and Africa are underrepresented, and a deeper understanding requires sector and culture-specific research. Investigating how cultural backgrounds influence responses to resources, alongside demographic factors such as gender and education, could enrich our understanding. However, it is not evident that there is a strong relationship between sector, country and cultural details that influence the selection and effectiveness of personal resources. For example, while sectors may prioritise resources relevant to their requirements (e.g. negotiation skills for lawyers), few sectoral or cultural nuances were identified. Studies in a Dutch public service agency emphasise resources such as communication skills and emotional intelligence for effective teamwork (Mazzetti & Schaufeli,
2022), while studies in Japan focus on mindfulness alongside self- efficacy, reflecting the cultural emphasis on focus and well-being (Matsuo, 2022). Further research that takes into account cultural, sectoral and demographic context will provide a more comprehensive understanding of the interaction between personal resources and work environments worldwide.
Theme 2: Theoretical Underpinnings
The review shows that the JD-R and COR theories are used in the majority of studies to explain these relationships between personal resources and work engagement. In these theories, personal resources are important factors in benefiting from job resources and effectively coping with job demands in order to be engaged at work. Existing studies on personal resources have predominantly focused on self-efficacy, resilience and optimism, with more recent research emphasising additional constructs such as growth mindset, strength use, emotional intelligence, religiosity, and mindfulness.
In the literature, self-efficacy, resilience, and optimism have been successfully theorised as personal resources, as shown by the JD-R theory (Mazzetti & Schaufeli, 2022; Schaufeli & Taris, 2014). However, while several other concepts have already demonstrated personal resource capabilities in recent studies, there is a lack of theoretical integration of these concepts into models of work engagement. The present study emphasises this gap. If explored in a broader context in the future, other concepts could also be theorised into these models for their personal resource capabilities, similar to how self-efficacy, resilience and optimism have been theorised. By identifying a broad range of personal resources beyond those commonly recognised, this review extends the theoretical understanding of what constitutes personal resources in the workplace.
Theme 3: Methods Used
In this review, with the exception of one study, it is clear that the studies are mostly quantitative, and the data are collected cross-sectionally. The use of cross-sectional studies limits the possibility of establishing causality and generalisability. This necessitates a more diverse methodological approach, including longitudinal studies, qualitative studies, and daily diary methods, to broaden our understanding of these workplace resources. Furthermore, the dominance of quantitative studies points to a gap. Qualitative research is needed to explore why people in countries with very low engagement levels may not be fully engaged in today’s business world. This can help to understand how change in the business world is experienced in terms of employee wellbeing.
Theme 4: Relationship Between Personal Resources and Work Engagement
The results of this study indicate that personal resources have a significant positive influence on work engagement. This systematic review shows that personal resources are primarily seen as independent variables, but their mediating and moderating roles are also recognised. Furthermore, today’s technology-driven business environment and rapidly growing AI technologies may impact the relationship between personal resources and work engagement which is an under-researched area.
As personal resources play an independent and mediating role, some moderating factors can also be explored, such as some social, cultural, and religious factors. These further studies can broaden the understanding of how these factors play a role in this equation of resources and engagement.
CONCLUSION, PRACTICAL IMPLICATIONS, AND LIMITATIONS
This research highlights the multifaceted nature of personal resources in influencing work engagement. It identifies a range of personal resources, with PsyCap being the most prominent. This review implies that recognising and promoting personal resources among employees to increase work engagement is important for productivity and higher performance. Organisations can improve employee engagement by creating a supportive environment that encourages these personal resources. This approach can include offering training and development programmes, creating a positive work culture, and ensuring a balance between job demands and resources. By focusing on personal resources, organisations can potentially increase job satisfaction, reduce turnover intentions, and improve overall performance.
This study makes an important contribution to research by expanding the scope of personal resources considered for work engagement and proposing a more complex interaction model between these resources and engagement. As study characteristics, it is recommended to investigate the role of demographic factors such as gender, age, and education. Theoretically, this study extends the theoretical understanding of what constitutes personal resources in the workplace by identifying a wide range of personal resources beyond those commonly recognised. Methodologically, future research should explore longitudinal and qualitative methods, examine the impact of digitalisation, technology and AI, and consider cross-cultural differences. The studies reviewed rely largely on quantitative research, particularly cross-sectional studies, which limits the ability to establish causal relationships between personal resources and work engagement. Based on the relationship between personal resources and work engagement, this review shows that these resources act not only as independent factors, but also as mediators and moderators, which broadens our understanding of their role in the workplace.
The paper’s scope is limited to peer-reviewed academic journals published in English within a specific timeframe, which may overlook relevant research published in other languages or outside academic channels. This could potentially limit the diversity and comprehensiveness of the findings.
ACKNOWLEDGEMENT
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. This article is produced from Osman Kelesoglu’s PhD research.
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