Work-Life Balance, Job Performance and Knowledge Risks: Comparison
View Latest Version
Please note this is a comparison between Version 3 by Rita Xu and Version 2 by Maura La Torre.

Despite the focus on knowledge risks in the literature, a limited number of studies have empirically examined technological knowledge risks in terms of digitalization, old technologies, and cybercrime as moderating variables in the relationship between work-life balance and job performance. To address this gap, this paper investigated the moderation effects of technological knowledge risks on the relationship between work-life balance and job performance during the pandemic period in employees of cooperative credit banks. A quantitative approach that involved gathering surveys was adopted. Applying PLS-SEM, the empirical findings revealed that technological knowledge risks have a significant impact on the relationship between work-life balance and job performance. Additionally, this research encourages managers to create and maintain a healthy work environment that promotes valuable employees’ job performance while also evaluating the use of new technological advances and their related risks.

Despite the focus on knowledge risks in the literature, a limited number of studies have empirically examined technological knowledge risks in terms of digitalization, old technologies, and cybercrime as moderating variables in the relationship between work-life balance and job performance. To address this gap, this entry investigated the moderation effects of technological knowledge risks on the relationship between work-life balance and job performance during the pandemic period in employees of cooperative credit banks. A quantitative approach that involved gathering surveys was adopted. Applying PLS-SEM, the empirical findings revealed that technological knowledge risks have a significant impact on the relationship between work-life balance and job performance. Additionally, this research encourages managers to create and maintain a healthy work environment that promotes valuable employees’ job performance while also evaluating the use of new technological advances and their related risks.

  • knowledge risks
  • work-life balance
  • job performance

1. Introduction

The COVID-19 pandemic, in addition to causing humanitarian and socio-economic emergencies, exposed companies of all sizes and sectors to different and complex challenges, which impacted various aspects of organizational design and behavior [1]. This is especially the case for small and medium-sized enterprises (SMEs) due to the difficulties that these organizations may encounter in finding the financial resources and human skills necessary to promptly and effectively manage the turmoil deriving from these crises [2,3][2][3]. Regarding work occupation, the COVID-19 pandemic caused career shocks that were differentiated in the short and long term [4], as well as significant changes in the status of some occupations and their relative value [5]. Therefore, organizations and employees had to face a work environment that was profoundly changed by the crisis [6], with the implementation of remote work practices influencing organizational performance [7], leading to financial and bureaucratic constraints and making it harder to monitor workers’ output [8]. Sudden changes following the COVID-19 pandemic could also have a positive or negative impact on employee work-life balance and job performance [9,10][9][10]. Technological advances, routine planning, and self-discipline become essential to maintaining good standards of work performance, especially when workers had to work from home (WFH) [11], in which case it was also important to ensure a home environment conducive to work, which could protect physical and mental health at the same time [12].
This changed situation after the COVID-19 pandemic also led organizations to be exposed to a greater number of risks, including risks related to knowledge management [13]. Considering the knowledge risks mapped and classified by Durst and Zieba [14] into human, technological, and operational domains, it can be noted that some of the threats associated with these risks became more serious during the COVID-19 pandemic. Human knowledge risks such as knowledge hiding, unlearning, and forgetting may be more likely to occur in the context of remote working. Employees can easily hide knowledge behind their private screens, while the lack of direct contact with workmates could favor the unlearning and forgetting of valuable knowledge due to communication being virtual and contacts filtered [13]. Knowledge risks most likely to affect employees who WFH are those related to the use of technology. Knowledge risks related to cybercrime, for example, could occur more easily in a less secure home internet network that could possibly be exposed to hacker attacks or through risky behaviors, such as sharing sensitive files via private devices. Knowledge risks related to old technologies could also affect remote workers, as employees may use outdated programs that do not allow IT security devices to be updated [13,14][13][14]. SMEs may find it more difficult to maintain their organizational balance—in particular, the balance between work and private life in the case of WFH, while also considering the effects of possible exposure to knowledge risks linked to the use of technology [15,16][15][16].
Considering the above, this paper aims to investigate the possible effects of technological knowledge risks (KRT) on the work-life balance (WLB) and job performance (JP) of employees of small banks. In particular, it investigates the moderating effects of KRT in terms of the risk of knowledge digitalization (KRTD), risks related to old technologies (KRTO), and risks related to cybercrime (KRTC) [17] on the relationship between WLB and JP in cooperative credit banks (CCBs). Haider, Jabeen, and Ahmad [18] stated that, although many scholars have investigated the WLB/JP relationship, the mechanisms that explain its functioning have still received little consideration. To fill this gap, it may be useful to introduce variables that mediate or moderate this relationship. A statistical analysis of mediation can be applied to check whether the effect of one variable on a second variable is transmitted through a third variable [19], while moderation occurs when the direction of the effect of a predictor variable on a result variable varies as a function of the value of another variable—that is, the moderator [20]. The extant literature has highlighted mediating and moderating effects of several variables on the WLB/JP relationship. Baral and Bhargava [21] examined the mediating role of work-family enrichment in the relationships between organizational interventions for WLB; in another study, optimism was tested as a mediator of the relationship between WLB, life satisfaction, and creative performance [22]. Furthermore, Sari and Seniati [23] investigated the effects of WLB on lecturers’ organizational commitment, using job satisfaction as a mediator; meanwhile, Rasheed, Mukhtar, Anwar, and Hayat [24] focused on the moderating role of obligation felt on employees’ desire for revenge.

2. Knowledge Risks: The State of the Art

Knowledge risk is an emerging field within the areas of knowledge management (KM) and intellectual capital (IC) [25] that aims to offer solutions to problems related to conventional risk management methods, applying KM tools and techniques for the management of organizational risks [26]. Knowledge risks have seldom been defined in the literature [14]. A more complete definition was proposed by Durst and Zieba [14] (p. 2), who describe knowledge risk as “a measure of the probability and severity of adverse effects of any activities engaging or related somehow to knowledge that can affect the functioning of an organization on any level”. This definition highlights the potential harmfulness of knowledge risks for organizations of all types and sizes, as well as the need to address these risks in relation to each other, preferably following an integrated approach [27]. The scientific literature on knowledge risks is still fragmented at present, addressing knowledge risks in isolation and often without comparing the organizational contexts involved [28]. Durst and Zieba [29] proposed the first taxonomy for knowledge risks to foster more rigorous research on this topic and, at the same time, support organizations in preventing or reducing these risks. Some types of knowledge risks were then identified and categorized according to their origin—internal or external to the organization. The risk of knowledge waste is another problem that occurs within organizations; it arises when valuable knowledge that is available in the organization is not used. An example of a knowledge risk originating outside an organization is knowledge spillover, which occurs when knowledge spills over to competitors, who gain a competitive advantage from it [29]. In order to further highlight the differences between types of knowledge risk, the same authors [14] divided knowledge risks into human, technological, and operational types. Human knowledge risks include knowledge hiding, forgetting, and unlearning—i.e., risks linked to the personal, social, psychological, and cultural factors of individuals. An organization is exposed to the risk of knowledge hiding, which is when people intentionally hide knowledge that has been requested by another person for reasons related to their fear of losing a competitive advantage or a position of power. The second category includes knowledge risks related to the use of technology by organizations, such as the risk of cybercrime (e.g., hacker attacks); the risk of digitalization—namely, the excessive dependence of organizations on technology rather than human factors; and risks associated with the obsolescence of organizational technological equipment [14]. The COVID-19 pandemic has heightened companies’ risk of exposure to KRT, as organizations during this period often resorted to WFH solutions due to the implementation of lockdown measures [13]. In this regard, it is important to ensure the adoption of cyber-safety behaviors based on digital safety skills in order to maintain a safe digital work environment [30] and encourage the development of employees’ digital skills to enable them to better cope with the new paradigm of Industry 4.0 [31]. These skills should also be adequately defined and measured [32,33][32][33] in order to avoid phenomena such as digital divides and inequality [34,35[34][35][36][37],36,37], especially in the era of the COVID-19 pandemic, which required considerable efforts from human resources departments to improve the digital skills of employees to allow them to maintain a satisfactory WLB even working remotely [38,39][38][39]. Operational knowledge risks that can affect organizations in their regular operations include knowledge outsourcing risks, the risk of using outdated/unreliable knowledge, and the risk of knowledge waste [14]. All organizations can be exposed to one or more knowledge risks, both private [17,40][17][40] and public [41]. SMEs are at particular risk, as they may experience greater difficulties in managing knowledge risks due to their lower capital endowments [42]. Organizational performance [43], as well as organizations’ ability to achieve economic, social, and environmental sustainability goals, can also be affected by knowledge risks [44,45][44][45]. Despite these valuable contributions, the research on knowledge risks still needs to be expanded, as this field is in an early stage of development [46], especially in relation to organizations belonging to the banking and financial sectors. Recent contributions have confirmed these findings, highlighting that very few studies clearly refer to one or more knowledge risks affecting banks or other financial companies [47], despite risk culture being strongly rooted in these organizations [48].

3. Latest Trends on Work-Life Balance

The extant literature on this topic has provided multiple definitions of WLB, focusing on the amount of time spent in work or on one’s private life, on the satisfaction derived from time spent in each domain, and on the importance attributed by individuals to each of these two roles [49]. Some authors have argued that the definitions of WLB adopted so far do not take into account developments in the personal sphere, in work contexts, and in relations between employees [50]. In a recent publication [51], the limits and prejudices related to the tendency to separate work from other spheres of life were highlighted, underlining the urgency of obtaining a broader view of this topic that is in step with the present times. Meanwhile, Lewis and Beauregard [52] provided an overview of definitions of WLB, integrating two literature streams—namely, work-family interface research and critical management and organizational studies. The modern concept of WLB is the result of a research evolution that has taken place in this field, attempting to respond over time to socio-economic and workplace developments [53,54,55,56][53][54][55][56]. Scientific research on the topic of WLB has intensified since the early 1990s; at present, there is a wide variety of approaches to this topic, with various definitions and different analysis perspectives having been proposed [57,58,59,60][57][58][59][60]. A significant proportion of the literature has focused on WLB perception, considering the perspectives of owners, employees, and managers [61,62][61][62] as well as gender issues [63,64,65,66][63][64][65][66]. From some of the most recent literature reviews in this area, interesting insights into how the WLB concept has evolved over time have emerged with respect to different contexts. Rashmi and Kataria [67] provided a systematic review of the literature focusing on WLB based on a bibliometric analysis; this shed light on emerging research themes such as flexible work arrangements, gender differences in WLB, the work-life interface and its related concepts, and WLB policies and practices, underlining the lack of a knowledge structure in the literature for this issue. Sirgy and Lee [68] pointed out the need for an integrative framework for WLB literature reviews, which would allow problems related to the holistic concept of WLB to be overcome, thus enabling its dimensions, antecedents, moderators, mediators, and consequences to be identified. The relationship between WLB and work engagement was considered in one literature review that explored its various antecedents, mediators, and moderators [69]. Another section of the literature has highlighted the correlation between WLB and other organizational variables, such as corporate performance and policies [70[70][71],71], while work-life concerns from the point of view of enrichment and depletion were addressed in [72]. The literature has not neglected to consider the “dark side” of WLB, in some cases associating the work-family backlash with WLB policies [73]. The COVID-19 pandemic forced many companies around the world to WFH. This affected employees’ WLB, leading to both positive outcomes by increasing organizational productivity [74] and negative impacts, given the numerous challenges experienced by workers [75]. The global pandemic also shed light on how men and women managed change, showing their different strategies for dividing their time between work and family in WFH situations [76,77][76][77] and trying to avoid gender inequalities in the distribution of duties and responsibilities [78]. Employees, even the youngest and most accustomed to technology, were forced to develop new skills to allow smart working, sometimes without strong support from e-training and e-leadership programs [79]. WLB has also been addressed with reference to the banking sector. Recent studies have dealt with WLB in commercial banks [80[80][81],81], some focusing on public sector banks [82] or gender issues [83,84,85][83][84][85]; others have considered the impacts of changes in working systems in the banking sector [86], the impacts of psychological well-being and satisfaction with coworkers on the WLB/JP relationship [18], and the role of employee assistance and leave programs [87].

4. Job Performance

Job performance (JP) can be defined as the “total expected value to the organization of the discrete behavioral episodes that an individual carries out over a standard period of time” [88] (p. 39). The state-of-the-art research on JP research highlights a proliferation of theoretical and empirical studies on JP predictors, including: employees’ ability, especially in entry-level jobs [89]; psychological well-being and job satisfaction [90]; employee engagement [91,92][91][92]; work stressors and coworker support [93]; ability and non-ability [94]; emotional and cognitive intelligence [95,96][95][96]; and cognitive reflection [97]. The relationship between JP and the age of employees has been widely discussed in the literature. Some authors have compared older employees’ performance with younger employees [98], while others have considered the relationship between employee age and JP, distinguishing professionals and non-professionals [99]. Scholars have also addressed the relationship between workers’ age and JP, including some of the ten JP dimensions, such as organizational citizenship behaviors, safety performance, general counterproductive work behaviors, and aggression in the workplace [100]. Another part of the JP literature has explored the mediating effect of resistance to change on the relationship between age and JP [101]. The relationship between JP and gender has also been analyzed in studies that found gender-based differences in performance [102] and differences in gender proportionality [103]. The COVID-19 pandemic affected the JP of employees in organizations from different sectors, particularly during WFH [104,105][104][105]. Team interactions during the pandemic period, both internal and external to the organization, were investigated in one study [106], as was the association between perceived stress, psychological distress, and job performance [107]. The JP of bank employees has also been addressed in the literature. The effects on JP of several variables, such as organizational commitment [108], training and work experience [109], and nonwork and personal resources [110], have been analyzed. Recently, the JP of bank employees has been linked with competitive intelligence [111], work-family conflicts [112], and emotional intelligence [113]. Sustainability 14 05416 g001   Sustainability 14 05416 g001

References

  1. Ratten, V. Coronavirus and international business: An entrepreneurial ecosystem perspective. Int. Bus. Rev. 2020, 62, 629–634.
  2. Kuckertz, A.; Brändle, L.; Gaudig, A.; Hinderer, S.; Reyes, C.A.M.; Prochotta, A.; Berger, E.S. Startups in times of crisis: A rapid response to the COVID-19 pandemic. J. Bus. Ventur. Insights 2020, 13, e00169.
  3. Durst, S.; Svensson, A.; Palacios Acuache, M.M.G. Peruvian Small and Medium-Sized Enterprises in Times of Crisis—Or What Is Happening over Time? Sustainability 2021, 13, 13560.
  4. Akkermans, J.; Richardson, J.; Kraimer, M.L. The COVID-19 crisis as a career shock: Implications for careers and vocational behavior. J. Vocat. Behav. 2020, 119, 103434.
  5. Kramer, A.; Kramer, K.Z. The potential impact of the COVID-19 pandemic on occupational status, work from home, and occupational mobility. J. Vocat. Behav. 2020, 119, 103442.
  6. Diab-Bahman, R.; Al-Enzi, A. The impact of COVID-19 pandemic on conventional work settings. Int. J. Sociol. Soc. Policy 2020, 40, 909–927.
  7. Zhang, T.; Gerlowski, D.; Acs, Z. Working from home: Small business performance and the COVID-19 pandemic. Small Bus. Econ. 2022, 58, 611–636.
  8. Islam, M.A.; Igwe, P.A.; Rahman, M.; Saif, A.N.M. Remote working challenges and solutions: Insights from SMEs in Bangladesh during the COVID-19 pandemic. Int. J. Qual. Innov. 2021, 5, 119–140.
  9. Putri, A.; Amran, A. Employees’ Work-Life Balance Reviewed from Work from Home Aspect During COVID-19 Pandemic. Int. J. Manag. Sci. Inf. Technol. 2021, 1, 30–34.
  10. Tušl, M.; Brauchli, R.; Kerksieck, P.; Bauer, G.F. Impact of the COVID-19 crisis on work and private life, mental well-being and self-rated health in German and Swiss employees: A cross-sectional online survey. BMC Public Health 2021, 21, 74.
  11. Kaushik, M.; Guleria, N. The impact of pandemic COVID-19 in workplace. Eur. J. Bus. Manag. 2020, 12, 1–10.
  12. Birimoglu Okuyan, C.; Begen, M.A. Working from home during the COVID-19 pandemic, its effects on health, and recommendations: The pandemic and beyond. Perspect. Psychiatr. Care 2022, 58, 173–179.
  13. Zieba, M.; Durst, S.; Gonsiorowska, M. Knowledge Risks in the COVID-19 Pandemic. In Proceedings of the IFKAD 2021: Managing Knowledge in Uncertain Times, Rome, Italy, 1–3 September 2021.
  14. Durst, S.; Zieba, M. Mapping knowledge risks: Towards a better understanding of knowledge management. Knowl. Manag. Res. Pract. 2019, 17, 1–13.
  15. Durst, S.; Ferenhof, H.A. Knowledge leakages and ways to reduce them in small and medium-sized enterprises (SMEs). Information 2014, 5, 440–450.
  16. Temel, S.; Durst, S. Knowledge risk prevention strategies for handling new technological innovations in small businesses. VINE J. Inf. Knowl. Manag. Syst. 2020, 51, 655–673.
  17. Zieba, M.; Durst, S.; Gonsiorowska, M.; Zralov, Z. Knowledge Risks in Organizations–Insights from Companies. In European Conference on Knowledge Management; Academic Conferences International Limited: Reading, UK, 2021; pp. 864–873.
  18. Haider, S.; Jabeen, S.; Ahmad, J. Moderated mediation between work life balance and employee job performance: The role of psychological wellbeing and satisfaction with coworkers. Rev. De Psicol. Del Trab. Y De Las Organ. 2018, 34, 29–37.
  19. MacKinnon, D.P.; Cheong, J.; Pirlott, A.G. Statistical mediation analysis. In APA Handbook of Research Methods in Psychology, Vol. 2. Research Designs: Quantitative, Qualitative, Neuropsychological, and Biological; Cooper, H., Camic, P.M., Long, D.L., Panter, A.T., Rindskopf, D., Sher, K.J., Eds.; American Psychological Association: Washington, DC, USA, 2012; pp. 313–331.
  20. Marsh, H.W.; Hau, K.-T.; Wen, Z.; Nagengast, B.; Morin, A.J.S. Moderation. In The Oxford Handbook of Quantitative Methods: Statistical Analysis; Little, T.D., Ed.; Oxford University Press: Oxford, UK, 2013; pp. 361–386.
  21. Baral, R.; Bhargava, S. Work-family enrichment as a mediator between organizational interventions for work-life balance and job outcomes. J. Manag. Psychol. 2010, 25, 274–300.
  22. Bouzari, M.; Karatepe, O.M. Does optimism mediate the influence of work-life balance on hotel salespeople’s life satisfaction and creative performance? J. Hum. Resour. Hosp. Tour. 2020, 19, 82–101.
  23. Sari, R.L.; Seniati, A.N.L. The role of job satisfaction as mediator between work-life balance and organizational commitment among lecturers. Psychol. Educ. 2020, 57, 106–110.
  24. Rasheed, K.; Mukhtar, U.; Anwar, S.; Hayat, N. Workplace knowledge hiding among front line employees: Moderation of felt obligation. VINE J. Inf. Knowl. Manag. Syst. 2022, 52, 284–302.
  25. Bratianu, C. A holistic approach to knowledge risk. Manag. Dyn. Knowl. Econ. 2018, 6, 593–607.
  26. Massingham, P. Knowledge risk management: A framework. J. Knowl. Knowl. Manag. 2010, 14, 464–485.
  27. Durst, S.; Henschel, T. Knowledge Risk Management: From Theory to Praxis; Springer: Cham, Switzerland, 2020; Volume 10, pp. 978–983.
  28. Durst, S.; Bruns, G.; Henschel, T. The management of knowledge risks: What do we really know? In Global business expansion: Concepts, Methodologies, Tools, and Applications; IGI Global: Hershey, PA, USA, 2018; pp. 258–269.
  29. Durst, S.; Zieba, M. Knowledge risks-towards a taxonomy. Int. J. Bus. Environ. 2017, 9, 51–63.
  30. Dodel, M.; Mesch, G. An integrated model for assessing cyber-safety behaviors: How cognitive, socioeconomic and digital determinants affect diverse safety practices. Comput. Secur. 2019, 86, 75–91.
  31. Garay-Rondero, C.L.; Martinez-Flores, J.L.; Smith, N.R.; Morales, S.O.C.; Aldrette-Malacara, A. Digital supply chain model in Industry 4.0. J. Manuf. Technol. Manag. 2020, 31, 887–933.
  32. Allmann, K.; Blank, G. Rethinking digital skills in the era of compulsory computing: Methods, measurement, policy and theory. Inf. Commun. Soc. 2021, 24, 633–648.
  33. Dorschel, R. Reconsidering digital labour: Bringing tech workers into the debate. In New Technology, Work and Employment; John Wiley & Sons Ltd.: Hoboken, NJ, USA, 2022.
  34. Jamil, S. Evolving Newsrooms and the Second Level of Digital Divide: Implications for Journalistic Practice in Pakistan. J. Pract. 2022, 1–18.
  35. Van Kessel, R.; Wong, B.L.H.; Rubinić, I.; O’Nuallain, E.; Czabanowska, K. Is Europe prepared to go digital? Making the case for developing digital capacity: An exploratory analysis of Eurostat survey data. PLoS Digit. Health 2022, 1, e0000013.
  36. Oyedemi, T.D.; Choung, M. Digital inequality and youth unemployment. Communication 2020, 46, 68–86.
  37. Eichhorn, T.; Jürss, S.; Hoffmann, C.P. Dimensions of digital inequality in the sharing economy. Inf. Commun. Soc. 2022, 25, 395–412.
  38. Carnevale, J.B.; Hatak, I. Employee adjustment and well-being in the era of COVID-19: Implications for human resource management. J. Bus. Res. 2020, 116, 183–187.
  39. Jeske, D. Remote workers’ experiences with electronic monitoring during COVID-19: Implications and recommendations. Int. J. Workplace Health Manag. 2022.
  40. Lee, R.W.; Yip, J.Y.; Shek, V.W. Knowledge Risk and Its Mitigation: Practices and Cases; Emerald Group Publishing: Bingley, UK, 2021.
  41. Durst, S.; Lindvall, B.; Bruns, G. Knowledge risk management in the public sector: Insights into a Swedish municipality. J. Knowl. Manag. 2018, 24, 717–735.
  42. Durst, S.; Edvardsson, I.R. Knowledge management in SMEs: A literature review. J. Knowl. Manag. 2012, 16, 879–903.
  43. Durst, S.; Hinteregger, C.; Zieba, M. The linkage between knowledge risk management and organizational performance. J. Bus. Res. 2019, 105, 1–10.
  44. Bratianu, C.; Neştian, A.Ş.; Tiţã, S.M.; Vodã, A.I.; Guţã, A.L. The impact of knowledge risk on sustainability of firms. Amfiteatru Econ. 2020, 22, 639–652.
  45. Durst, S.; Zieba, M. Knowledge risks inherent in business sustainability. J. Clean. Prod. 2020, 251, 119670.
  46. Durst, S. How far have we come with the study of knowledge risks? VINE J. Inf. Knowl. Manag. Syst. 2019, 49, 21–34.
  47. La Torre, M. Risk in Banking: Developing a Knowledge Risk Management Framework for Cooperative Credit Banks; Springer: Berlin/Heidelberg, Germany, 2020.
  48. Carretta, A.; Fiordelisi, F.; Schwizer, P. Risk Culture in Banking; Springer: Berlin/Heidelberg, Germany, 2017.
  49. Brough, P.; Timms, C.; Chan, X.W.; Hawkes, A.; Rasmussen, L. Work–life balance: Definitions, causes, and consequences. In Handbook of Socioeconomic Determinants of Occupational Health: From Macro-Level to Micro-Level Evidence; Springer: Cham, Switzerland, 2020; pp. 473–487.
  50. Kelliher, C.; Richardson, J.; Boiarintseva, G. All of work? All of life? Reconceptualising work-life balance for the 21st century. Hum. Resour. Manag. J. 2019, 29, 97–112.
  51. Bertolini, S.; Poggio, B. Introduction to the Research Handbook on Work-Life Balance. In Research Handbook on Work–Life Balance; Edward Elgar Publishing: Cheltenham, UK, 2022.
  52. Lewis, S.; Beauregard, T.A. The meanings of work-life balance: A cultural perspective. In The Cambridge Handbook of the Global Work-Family Interface; Cambridge Handbooks in, Psychology; Shockley, K., Shen, W., Johnson, R., Eds.; Cambridge University Press: Cambridge, UK, 2018; pp. 720–732. ISBN 9781108235556.
  53. Kalliath, T.; Brough, P. Work–life balance: A review of the meaning of the balance construct. J. Manag. Organ. 2008, 14, 323–327.
  54. Gregory, A.; Milner, S.; Windebank, J. Work-life balance in times of economic crisis and austerity. Int. J. Sociol. Soc. Policy 2013, 33, 528–541.
  55. Swathi, R.; Mohapatra, A. Work-life balance: Evolution and models—A study in the Indian context. Int. J. Sci. Res. 2015, 6, 1910–1914.
  56. Bertolini, S.; Musumeci, R. Doing research on work-life balance. In Research Handbook on Work–Life Balance; Edward Elgar Publishing: Cheltenham, UK, 2022.
  57. Powell, G.N.; Greenhaus, J.H.; Allen, T.D.; Johnson, R.E. Introduction to special topic forum: Advancing and expanding work-life theory from multiple perspectives. Acad. Manag. Rev. 2019, 44, 54–71.
  58. Chatrakul Na Ayudhya, U.; Prouska, R.; Beauregard, T.A. The impact of global economic crisis and austerity on quality of working life and work-life balance: A capabilities perspective. Eur. Manag. Rev. 2019, 16, 847–862.
  59. Khateeb, F.R. Work Life Balance—A Review of Theories, Definitions and Policies. Cross Cult. Manag. J. 2021, XXIII, 27–55.
  60. Muafi, M.; Siswanti, Y.; Anwar, M.Z. Work life balance in Islamic perspective (WLBIP) and its impact on organizational citizenship behavior in islamic perspective (OCBIP) and service performance. Int. J. Res. Bus. Soc. Sci. 2021, 10, 223–230.
  61. Helmle, J.R.; Botero, I.C.; Seibold, D.R. Factors that influence perceptions of work-life balance in owners of copreneurial firms. J. Fam. Bus. Manag. 2014, 4, 110–132.
  62. Braun, S.; Peus, C. Crossover of work–life balance perceptions: Does authentic leadership matter? J. Bus. Ethics 2018, 149, 875–893.
  63. Fujimoto, Y.; Azmat, F.; Härtel, C.E. Gender perceptions of work-life balance: Management implications for full-time employees in Australia. Aust. J. Manag. 2013, 38, 147–170.
  64. Naz, S.; Fazal, S.; Khan, M.I. Perceptions of women academics regarding work–life balance: A Pakistan case. Manag. Educ. 2017, 31, 88–93.
  65. Matulevicius, S.A.; Kho, K.A.; Reisch, J.; Yin, H. Academic medicine faculty perceptions of work-life balance before and since the COVID-19 pandemic. JAMA Netw. Open 2021, 4, e2113539.
  66. Lekchiri, S.; Eversole, B.A. Perceived work-life balance: Exploring the experiences of professional Moroccan women. Hum. Resour. Dev. Q. 2021, 32, 35–53.
  67. Rashmi, K.; Kataria, A. Work–life balance: A systematic literature review and bibliometric analysis. Int. J. Sociol. Soc. Policy 2021.
  68. Sirgy, M.J.; Lee, D.J. Work-life balance: An integrative review. Appl. Res. Qual. Life 2018, 13, 229–254.
  69. Wood, J.; Oh, J.; Park, J.; Kim, W. The relationship between work engagement and work–life balance in organizations: A review of the empirical research. Hum. Resour. Dev. Rev. 2020, 19, 240–262.
  70. Leitão, J.; Pereira, D.; Gonçalves, Â. Quality of work life and organizational performance: Workers’ feelings of contributing, or not, to the organization’s productivity. Int. J. Environ. Res. Public Health 2019, 16, 3803.
  71. Chaudhuri, S.; Arora, R.; Roy, P. Work–Life balance policies and organisational outcomes–a review of literature from the Indian context. Ind. Commer. Train. 2020, 52, 155–170.
  72. Rothbard, N.P.; Beetz, A.M.; Harari, D. Balancing the scales: A configurational approach to work-life balance. Annu. Rev. Organ. Psychol. Organ. Behav. 2021, 8, 73–103.
  73. Perrigino, M.B.; Dunford, B.B.; Wilson, K.S. Work–family backlash: The “dark side” of work–life balance (WLB) policies. Acad. Manag. Ann. 2018, 12, 600–630.
  74. Irawanto, D.W.; Novianti, K.R.; Roz, K. Work from home: Measuring satisfaction between work–life balance and work stress during the COVID-19 pandemic in Indonesia. Economies 2021, 9, 96.
  75. Palumbo, R. Let me go to the office! An investigation into the side effects of working from home on work-life balance. Int. J. Public Sect. Manag. 2020, 33, 771–790.
  76. Putranti, H.R.D.; Suparmi, S.; Susilo, A. Work Life Balance (WLB) Complexity and Performance of Employees during COVID-19 Pandemic. Arthatama 2020, 4, 56–68.
  77. Rodríguez-Rivero, R.; Yáñez, S.; Fernández-Aller, C.; Carrasco-Gallego, R. Is it time for a revolution in work–life balance? Reflections from Spain. Sustainability 2020, 12, 9563.
  78. Hjálmsdóttir, A.; Bjarnadóttir, V.S. “I have turned into a foreman here at home”: Families and work–life balance in times of COVID-19 in a gender equality paradise. Gend. Work Organ. 2021, 28, 268–283.
  79. Wiradendi Wolor, C.; Solikhah, S.; Fidhyallah, N.F.; Lestari, D.P. Effectiveness of e-training, e-leadership, and work life balance on employee performance during COVID-19. J. Asian Financ. Econ. Bus. 2020, 7, 443–450.
  80. Oludayo, O.A.; Falola, H.O.; Obianuju, A.; Demilade, F. Work-life balance initiative as predictor of employees’ behavioural outcomes. Acad. Strateg. Manag. J. 2018, 17, 1–17.
  81. Pathak, R.R. Work life balance in Nepalese commercial banks. J. Bus. Soc. Sci. 2018, 2, 116–125.
  82. Lenka, S.; Subudhi, R. Work Life Balance, Job Satisfaction and Organizational Commitment: A Study on Bank Employees Bhubaneswar, Odisha. Int. J. Res. Anal. Rev. 2019, 6. Available online: https://ssrn.com/abstract=3352463 (accessed on 11 March 2022).
  83. Ratnesh, M.; Sinha, A.R.; Ali, A. Antecedents and consequences of work life balance among women bank employees: A study on selected individual level factors. JIMS8M J. Indian Manag. Strategy 2019, 24, 12–20.
  84. Uddin, M.; Ali, K.B.; Khan, M.A.; Ahmad, A. Supervisory and co-worker support on the work-life balance of working women in the banking sector: A developing country perspective. J. Fam. Stud. 2021, 1–21.
  85. Fuadiputra, I.R.; Novianti, K.R. The Effect of Work Autonomy and Workload on Job Satisfaction of Female Workers in the Banking Sector: Mediating the Role of Work Life Balance. Winners 2020, 21, 85–91.
  86. Samson, G.N.; Waiganjo, M.; Koima, J. Effect of workplace environment on the performance of commercial banks employees in Nakuru town. Int. J. Managerial Stud. Res. 2015, 3, 76–89.
  87. Ogar, C.A.; Amanze, D. Work-Life-Balance: The Nigerian Organizational Experience (A Study of Selected Banks in Ebonyi State). Int. J. Res. Innov. Soc. Sci. 2019, 3, 145–157.
  88. Motowidlo, S.J. Job performance. Handb. Psychol. Ind. Organ. Psychol. 2003, 12, 39–53.
  89. Hunter, J.E.; Hunter, R.F. Validity and utility of alternative predictors of job performance. Psychol. Bull. 1984, 96, 72.
  90. Wright, T.A.; Cropanzano, R. Psychological well-being and job satisfaction as predictors of job performance. J. Occup. Health Psychol. 2000, 5, 84.
  91. Keller, R.T. Job involvement and organizational commitment as longitudinal predictors of job performance: A study of scientists and engineers. J. Appl. Psychol. 1997, 82, 539.
  92. Dalal, R.S.; Baysinger, M.; Brummel, B.J.; LeBreton, J.M. The relative importance of employee engagement, other job attitudes, and trait affect as predictors of job performance. J. Appl. Soc. Psychol. 2012, 42, E295–E325.
  93. Beehr, T.A.; Jex, S.M.; Stacy, B.A.; Murray, M.A. Work stressors and coworker support as predictors of individual strain and job performance. J. Organ. Behav. 2000, 21, 391–405.
  94. Kanfer, R.; Kantrowitz, T.M. Ability and non-ability predictors of job performance. Psychol. Manag. Individ. Perform. 2002, 2, 27.
  95. Dhani, P.; Sharma, T. Emotional intelligence and personality traits as predictors of job performance of it employees. Int. J. Hum. Cap. Inf. Technol. Prof. 2018, 9, 70–83.
  96. Dhliwayo, P.; Coetzee, M. Cognitive intelligence, emotional intelligence and personality types as predictors of job performance: Exploring a model for personnel selection. SA J. Hum. Resour. Manag. 2020, 18, 13.
  97. Salgado, J.F.; Otero, I.; Moscoso, S. Cognitive reflection and general mental ability as predictors of job performance. Sustainability 2019, 11, 6498.
  98. Man, G.M.; Man, M. Competence of older employees. Sci. Bull. 2018, 23, 89–93.
  99. Waldman, D.A.; Avolio, B.J. A meta-analysis of age differences in job performance. J. Appl. Psychol. 1986, 71, 33.
  100. Ng, T.W.; Feldman, D.C. The relationship of age to ten dimensions of job performance. J. Appl. Psychol. 2008, 93, 392.
  101. Kunze, F.; Boehm, S.; Bruch, H. Age, resistance to change, and job performance. J. Manag. Psychol. 2013, 28, 741–760.
  102. Green, C.; Jegadeesh, N.; Tang, Y. Gender and job performance: Evidence from Wall Street. Financ. Anal. J. 2009, 65, 65–78.
  103. Mackey, J.D.; Roth, P.L.; Van Iddekinge, C.H.; McFarland, L.A. A meta-analysis of gender proportionality effects on job performance. Group Organ. Manag. 2019, 44, 578–610.
  104. Susilo, D. Revealing the effect of work-from-home on job performance during the COVID-19 crisis: Empirical evidence from Indonesia. J. Contemp. Issues Bus. Gov. 2020, 26, 23–40.
  105. Troll, E.S.; Venz, L.; Weitzenegger, F.; Loschelder, D.D. Working from home during the COVID-19 crisis: How self-control strategies elucidate employees’ job performance. Appl. Psychol. 2021.
  106. Wu, Y.J.; Antone, B.; Srinivas, A.; DeChurch, L.; Contractor, N. Teamwork in the time of COVID-19: Creating, dissolving, and reactivating network ties in response to a crisis. J. Appl. Psychol. 2021, 106, 1483–1492.
  107. Meunier, S.; Bouchard, L.; Coulombe, S.; Doucerain, M.; Pacheco, T.; Auger, E. The Association between Perceived Stress, Psychological Distress, and Job Performance During the COVID-19 Pandemic: The Buffering Role of Health-Promoting Management Practices. Trends Psychol. 2022, 1–21.
  108. Lovely, S.N.; Afzal, M.K.; Alam, Z. Impact of job satisfaction and organizational commitment on job performance of private bank employees in Bangladesh. USV Ann. Econ. Public Adm. 2019, 19, 112–123.
  109. Muntazeri, S.; Indrayanto, A. The impact of education, training and work experience on job satisfaction and job performance. J. Akunt. Manaj. Dan Ekon. 2018, 20, 50–69.
  110. Karatepe, O.M.; Ozturk, A.; Kim, T.T. The effects of nonwork and personal resources on frontline bank employees’ work engagement and critical job outcomes. Int. J. Bank Mark. 2019, 37, 858–879.
  111. Hanif, N.; Arshed, N.; Farid, H. Competitive intelligence process and strategic performance of banking sector in Pakistan. Int. J. Bus. Inf. Syst. 2022, 39, 52–75.
  112. Riaz, M.K.; Jamal, W.; Latif, K.F. Moderating role of intrinsic motivation on the relationship of work family conflict and job performance in frontline officers of Islamic banks. Glob. Bus. Econ. Rev. 2019, 11, 161–179.
  113. Kumari, P.; Priya, B. Impact of emotional intelligence on job performance and organizational commitment among bank managers. Int. J. Interdiscip. Multidiscip. Stud. 2017, 4, 300–311.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
ScholarVision Creations
Feedback