Research Article

Introduction

The Fourth Industrial Revolution has caused a paradigm shift in various organisations and enhanced globalisation, even as the world has gone digital [1]. Glaringly, this has paved the way for Information Technology in various sectors, governments, and individuals globally, especially regarding work performance [2]. Sub-saharan Africa is included, as there has been tremendous advancement in technology adoption across various sectors [3], thereby developing the digital space [4]. This development has led to changes in our lives and how the world operates, making it an indispensable tool used by all [5]. Considering the delicate condition of the information technology sector, it has been noted that employees need to gain more confidence, focus, and zeal in the workplace, resulting in stress and a lack of motivation towards their work [6]. The information technology sector is known for heavy workload schedules, constant sitting in one place, and frequent travel for training [7]. Due to frequent advancement and enormous pressure at work, employees of the IT sector have been noted as the most susceptible group of individuals to mental health issues [2]. According to Bhargava et al. [8], having a high demand for services rendered by the industry and being an indispensable tool used across different individuals, governments, and the globe may lead to an increase in the schedule and workload of employees, thereby affecting the work-life balance of employees, their well-being, and their level of productivity. On that note, the current study specifically addresses work-life balance in the Information Technology sector. As an indispensable asset in every nation and economy, the information technology sector needs to be studied and understood as it enhances organisational and employee productivity. This refers to companies that produce software, hardware, or semiconductor equipment and provide Internet or related services. It also refers to individuals who work in information technology organizations that produce, sell, and distribute human and material resources for individual, organizational, and national use. This reveals the necessity of this sector and the need to ensure their workers experience positive career choices, such as flexible work hours or remote work options, and psychological capital, such as resilience or selfefficacy, even as other industries and the world solely depend on their services. Many recent studies [9-12] have related optimism, psychological capital, resilience, remote jobs, productivity, gender, health of different generations, household size, hope, and children care to positive work-related attitudes, higher performance, and an individual’s well-being in any work environment. Acccording to Mordi et al. [7], the permeable infiltrations, work-life balance and spillover experiences of IT employees is a challenge that has caught the attention of researchers, academics, and leaders. This results from the demanding situations in the workplace and the sophistication of their activities (Bhargava et al., 2024). Moreover, there have been some research gaps that this study seeks to address, including a shortage of research on work-life balance among IT employees and how these employees’ psychological capital and career choices, such as prioritising family time or pursuing higher education with career, can affect their work-life balance.

Therefore, this study examines the role of career choice and psychological capital on work-life balance among information technology employees in Nigeria. A balanced and objective employee is a happy employee [13]. A balance between work and non-work activities can significantly influence the degree of productivity at the workplace, improving the output of an organisation [14]. The more control employees feel over their lives, the more they can balance and commit to work and personal life [15]. It has been noted that a balance can be achieved when there is harmony between employees’ work and non-work activities [16]. According to Adnan [17], every employee desires to enjoy every aspect of their life, which includes work and personal life (family, leisure, social activities and others). Thus, making them feel fulfilled and satisfied and motivating their effectiveness and efficiency in each domain [18]. However, worklife balance has become a major issue in the workplace. Over the years, several researchers [16-20]) have conducted studies on work-life balance and how it affects employees’ well-being and the impact on organisational output. In these studies, several factors, which include flourishing, partnership status, burnout, work-family balance, turnover intention, fatigue, workplace support, job engagement and dissatisfaction, were noted to be the outcome of an employee with a work-life imbalance. However, none of these studies have examined why people choose a career in the information technology sector. Work-life balance has been a significant concern for those desiring to enjoy the quality of life [21]. It refers to the ability of an individual, irrespective of gender, to adequately harmonise work and family duties (Hjálmsdóttir et al., 2021). Refers to the state in which an employee experiences a degree of harmony between personal life and work [22]. Work-life balance refers to the well-being of employees in an organisation [23]. Work-life balance can also be defined as the degree to which individuals are satisfied and involved with their work and family roles [24].

A person can live a successful and happy life with a worklife balance (Bataineh et al., 2020). An employee’s life consists of several domains, including the workplace, their families, and other social activities, and they want to enjoy or be satisfied in each of these domains. Recently, work-life balance has often been used in organisations to distinguish between work and life domains [25]. Flexible work patterns, downsizing, and globalisation have left many employees feeling increased work pressure and demand and a daily struggle to effectively manage their family and work duties (Bharathi et al., 2020). In the context of the Nigerian workplace, work-life imbalance has been a challenge, leading to several consequences in the organisation, such as psychological detachment, absenteeism, psychological contract breach, and low productivity [26]. This shows how an employee’s well-being could negatively affect the organisation. When an employee’s home is happy, the workplace becomes enjoyable [3]. The more control employees feel over their lives, the more they can balance and commit to work and personal life [15]. However, Aderibigbe [27] posits that work-life balance connotes work and family life and work and other life activities. This indicates that experiencing work-life balance involves a level at which employees. A career is one of the most crucial aspects of one’s life and has become an asset of utmost imperative, as competent employees will not function to the best of their potential if they are not committed to their work [28]. A career is defined as the progress and actions taken by an individual throughout one’s lifetime, often related to one’s occupation, vocation, profession, and job [29]. Career choice refers to choosing a career path, often influenced by parental guidance, skills, and personal interests [30].

Career choice enables an individual to define goals that yield focus in search of life purpose, resulting in opportunities; it has become a complex science through the emergence of information technology, the post-industrial revolution, and job competition [31]. Factors determining a career choice might be intrinsic, extrinsic, or both, educational, appearance, and vary across countries, religions, cultures, and ethnic groups [32]. For example, various factors often influence career choices, including personalities, skills, interests, families, peers, income, religion, age, socio-economic status, and job security [32]. However, it is expedient for employees to have positive attitudes towards work and enhance their organisational performance. Against this backdrop, Luthans and Youssef [33] introduced the concept of psychological capital, which was referred to as psychological capital and is within the emerging positive organisational behaviour movement. This psychological capital is the second independent variable in the current study. This variable was chosen as the second independent variable because previous studies have suggested that it could correlate with or predict employees’ work-life balance. As such, it was selected to help researchers, practitioners, and academicians understand the need for psychological capital in our general work lives. Psychological capital is portrayed as an individual’s approving psychological state of maturation [34]. According to Nolzen [35], psychological capital refers to an individual’s positive psychological state of development, comprising four components: hope, self-efficacy, resilience, and optimism. Purwanto et al. [32] posited that psychological capital captures the psychological capacity of individuals who can be measured, developed, and utilised for work performance enhancement. Novitasari et al. [36] established that psychological capital has four features: self-efficacy, hope, optimism, and resiliency. Demystifying further:

a) Self-efficacy concerns itself with self-confidence to take every opportunity as a form of effort to attain success in challenging tasks. For instance, I feel confident in finding a solution to a long-term problem.

b) Hope relates to perseverance in achieving goals, deciphering opportunities, and raising beliefs for success. For instance, believing that there are many ways out of every challenge.

c) Optimism is an individual’s ability to develop positive attributes to succeed in challenging tasks. For instance, think positively about work-related matters.

d) Resilience refers to overcoming and sustaining life’s challenges. For example, I can solve complex tasks on a job. People with high psychological capital evenly allocate their resources [37].

Conversely, individuals with a low level of psychological capital exhibit lower motivation and confidence in handling conflicts [27]. Psychological capital, noted as a positive resource in combating work-life conflicts [38], is a higher-order core construct that helps prevent employees from succumbing to work stress [39]. It has the potential to instil positivity in employees, leading them towards higher well-being [40] and a vast spectrum of upbeat developments such as happiness and thriving at work [41], psychological and physical health, satisfaction in vital domains of life towards work-life balance (Da et al., 2020), and personal striving as well as coping with stress [36]. Therefore, our study aims to examine the influence of psychological capital on career choice and work-life balance among information technology employees in Nigeria, highlighting the implications of low psychological capital. The current study has advanced social cognitive career theory as our anchor theory. Lent et al. [42] social cognitive career theory extends Bandura’s social cognitive theory (1986). It explains how individuals create career choices through interest and make vocational choices. The theory attempts to explain the development of career interests, career choices, and career paths [43].

It suggests that career calling, occupational self-efficacy, and outcome expectations predict occupational choice, job satisfaction, and interest for better productivity and well-being [44]. The authors connote that developing people’s work-life balance and career goals start from career choice, calling, and interest to the degree of psychological capital. Studies [42,43,45-47] defined self-efficacy beliefs as an individual’s capacity judgment, such as the psychological capital needed to carry out a required activity for attaining a particular degree of performance, work-life balance, and expectations. Therefore, this statement shows that psychological capital is needed to attain a work-life balance for employees after making a career choice. They further defined outcome expectations as people’s presumption of a tendency of a consequence to occur (e.g., work-life balance) as a result of behaviour exhibited (career choice and psychological capital). Lent et al. [42] denote that people make vocational decisions and career choices based on their beliefs, psychological capital, and thriving at work about the likely outcomes at the workplace, such as prestige, work-life balance, and expected remuneration. They further hypothesised that learning experiences such as psychological capital impact self-efficacy and vice versa. Sources of self-efficacy include vicarious learning, low levels of anxiety, support and encouragement from others, performance accomplishment and low degree of conflicts and stress [48]. Also, the authors believed that internal and external factors influence people’s career choices, which may include gender, society, socioeconomic status, and belief in an individual’s ability. Lent [43] further explained the theory as how individuals build vocational interests, make occupational choices and attain a degree of career success (Figure 1).

Hypotheses

In the current study, the following hypotheses were tested. i. Career choice will significantly predict work-life balance among Nigerian information technology employees.

ii. Psychological capital will significantly predict work-life balance among Nigerian information technology employees.

iii. Career choice will moderate the relationship between psychological capital and work-life balance among Nigerian Information Technology employees.

Method

Participants

A total of two hundred and eighty-five (285) employees drawn from twenty (20) Information Technology (IT) organisations voluntarily and conveniently participated in the current study, representing a diverse range of backgrounds and experiences. Organisations in the Lagos State of Nigeria were sampled using a convenient sampling technique to select participants. Of the total participants (two hundred and eighty-five; 285) sampled, 283 were males, representing 99.3% of the participants, and 2 were females, representing .7% of the participants. Their age ranged from 20 to 51 years (M=34.09; SD=5.54). Other demographic details were provided, including marital status, religion, highest education qualification, and duration spent in the organisation.

Instruments

Three sets of questionnaire scales were used in the present study. They include the Psychological Capital Questionnaire (PCQ) [49], the Career Choice Scale [30], and the Work-Life Balance Questionnaire [22].

Psychological Capital Questionnaire

The psychological capital questionnaire (PCQ) was developed by Luthans et al. [34]. PCQ is a 24-item questionnaire designed to measure an individual’s state of psychological capital, consisting of four dimensions which were pooled items from four previously published scales: Hope (State Hope Scale by Snyder et al., 1996), Optimism (Life Orientation Test by Scheider& Carver, 1985), Resilience (Resilience Scale by Wagnild & Young, 1993), and Selfefficacy (Role Breadth Self-Efficacy Scale by Parker, 1998). Each sub-scale consists of six items. However, the questionnaire is answered on a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Items 1, 8 and 11 are reversely scored. We conducted a pilot study to validate the Psychological Capital Scale on 100 IT personnel drawn from Tenace Technology Consulting Services. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was .78, and Bartlett’s test of Sphericity was 795.49 (p<.001), indicating that the sample was sufficient to test for factorial validity of the scale. A one-component factor structure of the scale was extracted, accounting for 27.68% of the variance. Loadings of the items ranged from .33 to .67. The items yielded high internal consistency reliability, with Cronbach’s alpha of .76.

Career Choice Scale

The career choice scale, developed by Borchert [30], was adopted and meticulously adapted to conform to the Informational Technology organizational context. This nine-item questionnaire, originally designed to assess factors influencing career choice among high school students in German town high school, Milwaukee, Wisconsin, was modified to align with the IT context. For example, the term ‘military’ was replaced with ‘IT’ and was replaced with ‘had’. An example of an item in the scale is, “Parents had the greatest influence in my career choice”. The questionnaire is answered on a 5-point Likert scale, which is represented by Strongly Disagree (1), Disagree (2), Neither Agree nor Disagree (3), Agree (4) and Strongly Disagree (5). We conducted a pilot study to validate the Career Choice Scale for the present research on a sample of 100 IT personnel. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was .76, and Bartlett’s test of Sphericity was 330.61 (p<.001), indicating that the sample size was sufficient to test for factorial validity of the scale, instilling confidence in the scale’s validity. A one-component factor structure of the scale was extracted, accounting for 43.23% of the variance. Loadings of the items ranged from .31 to .58. The items yielded high internal consistency reliability, Cronbach’s alpha of .81.

Work-Life Balance Scale

Work-Life Balance (WLB) was measured using the work-life balance scale adopted by Hayman (2005). It is a 15-item scale designed to measure the three dimensions of work-life balance: work-personal life enchantment (WPLE), work interference with personal life (WIPL) and personal life with work (PLIW). The scale is scored on a five-point Likert scale, ranging from 1(strongly disagree) to 5(strongly agree). Some samples of the items include “personal life suffers because of work”, “better mood because of my job”, and “too tired to be effective at work”. We conducted a pilot study to validate the Work-life Balance Scale for the present research on a sample of 100 IT personnel. The Kaiser-Meyer- Olkin Measure of Sampling Adequacy was .60, and Bartlett’s test of Sphericity was 336.72 (p<.001), indicating that the sample was sufficient to test for factorial validity of the scale. A onecomponent factor structure of the scale was extracted, accounting for 25.63% of the variance. The loadings of the items ranged from .30 to .70. The items yielded high internal consistency reliability, Cronbach’s alpha of .74.

Procedure

A convenient sampling technique was adopted in the study. As a result of the information technology staff being remote workers, only some were present at the workplace. We administered copies of the questionnaires to the available staffers. The research was conducted in twenty (20) IT companies. We approached each organisation’s management with a staff identification card authorised by the institution to seek permission to conduct a research study. The management granted permission to distribute the copies of the questionnaires among workers. The receptionists and administrative staff assisted in sharing questionnaires among available workers. We assured confidentiality and instructions for responding to the questionnaires were clearly stated. Due to the unavailability of sufficient workers, the receptionist and administrative staff gathered the questionnaires, which were answered and handed to us. The researcher returned a few days later to retrieve these questionnaires and verbally appreciated the workers and management. This meticulous process ensured that we collected a comprehensive dataset. Three hundred and thirty (330) questionnaires were distributed, while two hundred and eighty-five (285), indicating 86% of the return rate, were wholly and accurately responded to.

Design/Statistics

This is primarily survey research, and a cross-sectional design was adopted. The Hayes PROCESS Macro was used for statistical analysis of the data.

Results

This section presents the study’s findings. Table 1 shows the descriptive statistics and correlations of the variables. Table 2 shows the Hayes PROCESS Macro results for predicting worklife balance among Information Technology employees by career choice and psychological capital (Table1).

Table 1 showed that older age was negatively associated with organization duration (r = -.18, p<.01). Being female was associated with organizational duration (r = .20, p<.01). Psychological capital was positively related with work-life-balance among IT employees (r = .42, p<.001).

Results in Table 2 showed that career choice was not significantly associated with work-life balance among IT employees (B = -.03). Psychological capital was positively associated with work-life balance among IT employees (B = .23, p<.001). The B showed that each unit’s rise in psychological capital was associated with a .23 increase in work-life balance among IT employees. The interaction of career choice and psychological capital was insignificant (B = -.00), indicating that psychological capital did not moderate the relationship between career choice and work-life balance among IT employees. The R2 of .18 for the model showed that 18% of the variance in worklife balance among IT employees was explained on account of the entire variables, F (3, 281) = 20.67.

Discussion

This study examined the moderating role of psychological capital in the relationship between career choice and worklife balance among Information Technology employees. The current study revealed that career choice was not significantly associated with work-life balance among Information Technology employees. Thus, the first hypothesis, which states that career choice will significantly predict work-life balance among Nigerian information technology employees, still needs to be confirmed but has been rejected in the current study. This finding of the present research disagrees with the works of [50] and Shang et al. [44], who found a significant relationship between career selection and career calling on job satisfaction and occupational self-efficacy. The Social Cognitive Career Theory can help our readers understand the complex nature of work-life balance among IT employees. This theory, developed by Lent et al. [42], provides a comprehensive framework for understanding career development, focusing on the interplay between personal attributes, external environmental factors, and behavioural outcomes. It integrates concepts from Bandura’s social cognitive theory, particularly self-efficacy, outcome expectations, and personal goals, to explain careerrelated choices and behaviours. By applying this theory to the finding that career choice was not significantly associated with work-life balance among IT employees, we can suggest that worklife balance is a complex construct influenced by multiple factors. The interaction of self-efficacy, coping strategies, organizational environment, support systems, and contextual challenges can mediate the impact of career choice on work-life balance. Therefore, interventions to improve work-life balance among IT employees should address these multifaceted influences rather than focusing solely on career choice. Second, the current study showed that psychological capital was positively associated with work-life balance. Thus, the second hypothesis, which states that psychological capital will significantly predict work-life balance, was accepted and confirmed. This study finding is consistent with Demir’s [51] and Christy et al. [52] finding that psychological capital would significantly impact job satisfaction and work-life balance. This finding can be further explained and supported using the conservation of resource theory [53]. This theory states how employees are motivated to obtain, retain, and promote the necessary resources in psychological capital to achieve a successful performance outcome [54]. Conservation of resource theory denotes the capability of an employee’s psychological capital level to attain a certain fulfilment and actualise a goal. According to [55], the basic tenet of conservation of resource theory is that individuals strive to acquire resources (psychological capital), retain and promote these resources and enhance those things they value (work-life balance).

Finally, the current study showed that psychological capital did not moderate the relationship between IT employees’ career choices and work-life balance. Thus, the third hypothesis, which states that psychological capital will significantly moderate the relationship between IT employees’ career choice and work-life balance, was not accepted and confirmed. This study finding is inconsistent with several previous studies, including those by Aderibigbe and Mjoli [38], Baig et al. [37], Kim et al. [11], Kole and Kurt’s [39], and Obeng et al. [24], which found that psychological capital significantly moderated various relationships such as organisational support, hope, high-performance work practices, leadership styles, efficacy, occupational stress, resilience, employees performance, optimism, turnover intention, organisational citizenship behaviour, and work-family balance. This finding can be further explained and supported using the theory of work adjustment [56]. When exploring the relationship between career choices and work-life balance among IT employees, Psychological Capital (PsyCap) may not always act as a moderating variable. To understand why this might be the case, we can look at the Theory of Work Adjustment (TWA). The TWA emphasises the interaction between an individual and their work environment, focusing on the degree of correspondence between individual abilities and job requirements and between personal needs and job rewards. Career choices in IT should ideally align with an individual’s skills and interests. However, the dynamic nature of IT jobs may result in evolving demands that can cause misalignment over time. While PsyCap can enhance an individual’s ability to adjust to job demands, it does not change the fundamental alignment between job requirements and personal skills or needs. Thus, PsyCap may not effectively moderate the relationship if the career choice inherently leads to poor worklife balance due to misalignment. Factors beyond personal control, such as organisational culture, industry standards, and external demands, influence work-life balance. PsyCap, being an individual-level construct, may need to sufficiently address these broader environmental and structural factors. Therefore, addressing work-life balance in the IT sector might require more systemic and organisational interventions rather than relying solely on enhancing individual PsyCap.

Implication of the Study

The result of the study showed that career choice was not significantly associated with work-life balance among Information Technology employees. The finding has shown that specific jobs in developing countries like Nigeria cannot determine the worklife balance of such employees. Also, the result has confirmed the work of Ujoatuonu et al. [46], who stated that most employees in developing countries enter vocations, professions, and careers accidentally. This accidental method and the long waiting periods before getting employed or in the unemployment stage must have prepared most employees to manage work-life balance so they cannot afford to lose any job, career, or work. Therefore, factors influencing an employee’s career choice could negatively affect one’s work-life balance. Similarly, from career construction theory (Savickas, 2005), individuals have learnt that there is only one perfect work-life balance. As a result, they have structured their lives and work by believing in themselves and prioritizing things, increasing their social relationships and becoming socially intelligent, prioritizing things, staying organized, learning to be assertive, and talking to their boss. This involves them being intentional about their various spheres of life.

The study found that psychological capital was positively associated with work-life balance among Information Technology employees. Indicating that an employee with psychological capital has a high tendency to experience a work-life balance. On the other hand, employees with a lower level of psychological capital may likely not experience a work-life balance. This confirmed the work of Christy et al. [52], who stated that psychological capital significantly impacts work-life balance. The research finding that PsyCap does not moderate the relationship between IT employees’ career choices and work-life balance suggests that organisations have a pivotal role. Simply enhancing individual psychological resources is not sufficient to address work-life balance issues. Instead, a comprehensive approach is essential, encompassing organisational policy changes, supportive work environments, holistic well-being programs, and personalised interventions. By embracing these strategies, organisations can effectively support their employees in achieving a healthy work-life balance, improving job satisfaction and productivity [53-60].

Limitation of the Study

The first limitation of the study is the sample size used. A total number of two hundred and eighty-five (285) employees were used in the study. This population is not a justified representation of the IT employees in Lagos State and Nigeria. Meanwhile, 93% of participants who participated in the study were males, while 3% were females, showing an imbalance in gender status. Moreover, because we selected a few of the target population who were available in the office as a result of the IT staff who were remote workers, we had little control over the sample and minimal knowledge as to whether the sample was an actual representation of the target population. Some participants gave random answers while filling out the questionnaire, which may have affected the results. The use of quantitative self-administered questionnaires did not allow us to fully explore why the employees chose their present career and how their choice of career affected their worklife balance. There is the possibility of bias in self-reporting by the participants. The data in the current study were collated at one point in time. Consequently, the respondents’ viewpoint may have been influenced by covariate factors. Thus, the interpretation of the results is constrained by the cross-sectional nature of the data [61-63].

Recommendation for Further Research

Given the study’s limitations, researchers conducting similar studies should employ a larger sample size to ensure standardized generalization. Given the prevalence of remote IT workers, future researchers should consider using online questionnaires, such as Google Forms, to enable the participation of workers unable to be physically present, such as those working from home. This approach would help achieve a more balanced gender representation in the study population. Additionally, it would be beneficial for other researchers to replicate the present study to validate or refute its findings.

Summary and Conclusion

The present study explores the role of career choice and psychological capital on work-life balance among IT employees. It aims to add to the existing literature. Results showed that career choice was not significantly associated with work-life balance, psychological capital was positively related to work-life balance, and the interaction between career choice and psychological capital was insignificant. From the formulated hypotheses and variables studied, the first hypothesis on career choice and worklife balance still needs to be confirmed and, thus, rejected. The second hypothesis on psychological capital and work-life balance was confirmed. The third hypothesis on the moderating role of psychological capital in the associations between career choice and work-life balance needed to be confirmed and, thus, rejected. Therefore, career choice does not significantly predict work-life balance among IT employees in Nigeria, while psychological capital significantly predicts work-life balance among IT employees in Nigeria. Furthermore, the result showed that the interaction between career choice and psychological capital was not significant, indicating that career choice did not moderate the relationship between psychological capital and work-life balance among IT employees in Nigeria.

References

1. Fenech R, Baguant P, Ivanov D (2019) The changing role of human resource management in an era of digital transformation. Journal of Management Information and Decision Sciences 22(2): 166.
2. Bradford L (2018) Why We Need to Talk About Burnout in The Tech Industry.
3. Mmakwe KA, Ojiabo U (2018) Work life balance and employee performance in Nigerian banks, Port Harcourt. International Journal of Advanced Academic Research in Social and Management Sciences 4(1): 107-119.
4. Nicolás-Agustín Á, Jiménez-Jiménez D, Maeso-Fernandez F (2021) The role of human resource practices in the implementation of digital transformation. International Journal of Manpower 43(2): 395-410.
5. Barišić, Rybacka Barišić J, & Miloloza I (2021) Digital transformation: Challenges for human resources management. ENTRENOVA - ENTerprise REsearch InNOVAtion 7(1): 357-366.
6. Gupta R (2020) Examining the Impact of Employee’s Well-Being and Mental Health on Productivity in the IT Sector. Dublin, National College of Ireland.
7. Mordi C, Ajonbadi HA, Adekoya OD (2023) Technology infiltration: Permeable boundaries and work–life spillover experiences among academics in the United Kingdom during the COVID-19 pandemic. Personnel Review
8. Bhargava S, Sharma R, Kulshreshtha M (2024) Promoting subjective well-being of IT professionals through gratitude practice: a moderated mediation analysis of gender and employee engagement. Management Research Review 47(4): 559-580.
9. Ferreira P, Gomes S (2023) Work–life balance and work from home experience: perceived organizational support and resilience of European workers during COVID-19. Administrative Sciences 13(6): 153.
10. Ivasciuc IS, Epuran G, Vuță DR, Tescașiu B (2022) Telework implications on work-life balance, productivity, and health of different generations of Romanian employees. Sustainability 14(23): 16108.
11. Kim M, Perrewé PL, Kim YK, Kim ACH (2017) Psychological capital in sport organizations: Hope, efficacy, resilience, and optimism among employees in sport (HEROES). European Sport Management Quarterly 17(5): 659-680.
12. Prati G (2024) Remote work’s impact on well-being: Longitudinal analysis and the influence of gender, household size, and childcare. International Journal of Workplace Health Management 17(1): 72-84.
13. Ujoatuonu IVN, Kanu GC, Ugwuibe OC, Mbah OP (2019) Role of workplace support on the relationship between perceived work life balance policies and flourishing among Nigerian Military personnel. Nigerian Journal of Psychological Research 15: 39-45.
14. Alex OJ, Jaspreet K (2023) A study on the work life balance of employees. SHANLAX International Journal of Management 11(1): 61-65.
15. Jaharuddin NS, Zainol LN (2019) The impact of work-life balance on job engagement and turnover intention. The Southeast Asian Journal of Management 13(1): 106-118
16. Garini RA, Muafi M (2023) The effect of digital competence, work life balance and work stress towards service performance with moderation of emotional intelligence on employees of PT.X. International Journal of Business Ecosystem & Strategy (2687-2293) 5(2): 01–11.
17. Adnan BK (2019) Impact of work-life balance, happiness at work, on employee performance. International Business Research 12(2): 99–112.
18. Kislev E (2023) Relationship-status and work-life balance satisfaction: Cross-sectional and longitudinal analyses. Applied Research Quality Life 18: 1115–1142.
19. Park Y, MacDonald G, Impett EA (2022) Partnership status and satisfaction with work–life balance. European Journal of Work and Organizational Psychology32(1): 118–127.
20. Yucel D (2021) Different types of work–family balance, social support, and job satisfaction: A latent class analysis. Applied Research in Quality of Life 16: 1343–1368.
21. Breitenecker RJ, Shah SAM (2018) Relation of work-life balance, work-family conflict, and family-work conflict with the employee performance-moderating role of job satisfaction. South Asian Journal of Business Studies 7(1):129-146.
22. Hayman J (2005) Psychometric assessment of an instrument designed to measure work-life balance. Research and Practice in Human Resource Management 13(1): 85-91.
23. Gragnano A, Simbula S, Miglioretti M (2020) Work–Life Balance: Weighing the importance of work–family and work–health balance. International Journal Of Environmental Research And Public Health 17(3): 907.
24. Obeng AF, Zhu Y, Quansah PE, Ntarmah AH, Cobbinah E (2021) High-performance work practices and turnover intention: Investigating the mediating role of employee morale and the moderating role of psychological capital. SAGE Journals 11(1).
25. Mos B, Bandar NFA, Sabil S, Halim FA, Muda AL, et al. (2018) Generation-Y employees and their perception lof work-life balance. Journal of Cognitive Sciences and Human Development 4(2): 28-41.
26. Azeez RO, Tinuke MF, Jayeoba FI (2017) Work-life balance and organizational commitment: Perception of working postgraduate students. BVIMSR’s Journal of Management Research 9(2): 178-188.
27. Aderibigbe JK (2019) Relationship between occupational stress, organisational citizenship behaviour, psychological capital and emotional intelligence among Nigerian employees. African Journal of Business and Economic Research (AJBER) pp. 1750-4562.
28. Odo VO, Ujoatuonu IVN, Ike OO, Kanu CG, Okafor CO, et al. (2021) Job characteristics, day to day experiences, and military career adaptation: Moderating role by person job fit. Trends in Psychology 30(2): 367-383.
29. Singhal H, Renu R (2018) Psychological capital and career commitment: The mediating effect of subjective well-being. Management Decisions 56(2): 458-473.
30. Borchert M (2002) Career choice factors of high school students: Masters’ Thesis, Graduate College University of Wisconsin-Stout.
31. Ngussa BM, Rehema KC (2019) Perception of students regarding the role of teachers and parents on career choice preparedness: A case of secondary schools in Meru District, Tanzania. Integrity Journal of Education and Training Volume 3(4): 60-72.
32. Purwanto A, Asbari M, Hartuti H, Setiana YN, Fahmi K (2021) Effect of Psychological Capital and Authentic Leadership on Innovation Work Behavior. International Journal of Social and Management Studies 2(1): 1-13.
33. Luthans F, Youssef CM (2004) Human, social and now positive psychological capital management: Investing in people for competitive advantage. Organizational Dynamics 33(2): 143-160.
34. Luthans F, Youssef CM, Avolio BJ (2007) Psychological capital: Developing the human competitive edge. Oxford University Press.
35. Nolzen N (2018) The concept of psychological capital: A comprehensive review. Management Review Quarterly 68(3): 237-277.
36. Novitasari D, Siswanto E, Purwanto A, Fahmi K (2021) Authentic Leadership and Innovation: What is the role of psychological capital?. International Journal of Social and Management Studies (IJOSMAS) 3(5): 27-42.
37. Baig SA, Iqbal S, Abrar M, Baig IA, Amjad F, et al. (2021) Impact of leadership styles on employees’ performance with moderating role of positive psychological capital. Total Quality Management & Business Excellence 32(9-10): 1085–1105.
38. Aderibigbe JK, Mjoli TQ (2018) Psychological capital as a moderator in the relationship between occupational stress and organizational citizenship behavior among Nigerian graduate employees. SA Journal of Human Resource Management 16(0): 1030.
39. Kole M, Kurt A (2018) The moderator role of psychological capital between perceived organizational support and work-family balance: A service sector research. International Journal of Electronic Finance 4(2): 134-146.
40. Bataineh KA (2019) Impact of work-life balance, happiness and work on employee performance. International Business Research 12(2): 99-112.
41. Basinska BA, Rozkwitalska M (2019) Psychological capital and happiness at work: The mediating role of employee thriving in multinational corporations. Current Psychology 41: 549-562.
42. Lent RW, Brown SD, Hackett G (1994) Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior 45(1): 79-122.
43. Lent RW (2005) A social cognitive view of career development and counseling. Career Development and Counseling: Putting Theory and Research to Work 1: 101-127.
44. Shang W, Zhang G, Wang Y (2022) Career calling and job satisfaction of ideological and political education teachers in china: The mediating role of occupational self-efficacy. Sustainability 14(20): 13066.
45. Bandura A (1986) Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall, 23-28.
46. Ujoatuonu IVN, Kanu GC, Okafor CO, Okeke CS (2022a) Work method control of Nigerian armed forces personnel: Roles of psychological detachment and conscientiousness. Journal of Psychology in Africa 32(5): 454-458.
47. Ujoatuonu IVN, Kanu GC, Okafor CO, Okeke CS (2022b) Occupational prestige and basic need satisfaction at work as predictors of pre-retirement anxiety among Nigerian University Lecturers. Ikenga International Journal of Institute of African Studies, 23(2): 1-21.
48. Bandura A (1997) Self-efficacy: The exercise of control. New York, NY: Freeman
49. Luthans F, Avolio BJ, Avey JB, Norman SM (2007) Positive psychological capital: Measurement and relationship with performance and satisfaction. Personnel Psychology 60(3): 541-572.
50. Agbanobi E (2021) Impact of Career Selection on Job Satisfaction. Published Bachelor of Arts (Hons) in Psychology project. National College of Ireland.
51. Demir S (2018) The relationship between psychological capital and stress, anxiety, burnout, job satisfaction and job involvement. Eurasian Journal of Educational Research 75: 137-154.
52. Christy F, Arokiaraj D, Choudhary N, Kalgi N, Maheswari VV (2020) Impact of psychological capacities on the work-life balance of entrepreneurs. Psychology and Education 58(3): 3869-3875
53. Hobfoll SE (1989) Conservation of Resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513-524.
54. Da S, Cen Xiamin, GongOi, Ling Siu, Xichao Zhang (2021) Psychological capital, positive effect and organizational outcomes: A three-wave cross-lagged study. Journal of Pacific Rim Psychology 15(1).
55. Hobfoll SE (2001) The influence of culture, community, and the nested self in the stress process: Advancing conservation of resources theory. Applied Psychology: An International Review 50(3): 337-421.
56. Dawis RV, England GW, Lofquist LH (1964) A theory of work adjustment (A revision). Minnesota Studies in Vocational Rehabilitation, No. 23. University of Minnesota, Industrial Relations Center.
57. Allen TD, Cho E, Meier LL (2014) Work–Family Boundary Dynamics. Annual Review of Organizational Psychology and Organizational Behavior 1(1): 99-121.
58. Dawis RV, Lofquist LH (1984) A psychological theory of work adjustment: An individual-differences model and its applications. University of Minnesota Press.
59. Hobfoll SE, Halbesleben J, Neveu JP, Westman M (2018) Conservation of resources in the organizational context: The reality of resources and their consequences. Annual Review of Organizational Psychology and Organizational Behaviour 5: 103-128.
60. Hobfoll SE (2002) Social and psychological resources and adaptation. Review of General Psychology 6(4): 307-324.
61. Lofquist LH, Dawis RV (1991) Essentials of person-environment-correspondence counseling. University of Minnesota Press.
62. Prawitasari G (2017) The Influence of Generations on Career Choice (Social Cognitive Career Theory Perspective). In Ifdil&KrishnawatiNaniek (Eds.), International Conference: 1st ASEAN School Counselor Conference on Innovation and Creativity in Counseling, 73-81. Yogyakarta: IBKS Publishing.
63. Ujoatuonu IVN, Okafor CO, Kanu GC, Ndukahie LG, Nwaleke R (2020) Roles of fear of happiness and fragility of happiness in Nigerian Military Personnel workload. International Journal of Psychological Studies 12(4): 53-60.