Abdelmotaleb, M., & Saha, S. K. (2019). Socially responsible human resources management, perceived organizational morality, and employee well-being. Public Organization Review, 20(2), 385-399.
Ab Wahab, M., & Tatoglu, E. (2020). Chasing productivity demands, worker well-being, and firm performance: The moderating effects of HR support and flexible work arrangements. Personnel review, 49(9), 1823-1843.
Abubakar, A. M., Behravesh, E., Rezapouraghdam, H., & Yildiz, S. B. (2019). Applying artificial intelligence technique to predict knowledge hiding behavior. International Journal of Information Management, 49, 45-57.
Adula, M., Kant, S., & Birbirsa, Z. A. (2022). Systematic Literature Review on Human Resource Management Effect on Organization Performance. Annals of Human Resource Management Research, 2(2), 131-146.
Aditya, Y. (2023, February). Significance of artificial intelligence to deal with stress during the organisational changes. In 2023 IEEE 2nd International Conference on AI in Cybersecurity (ICAIC) (pp. 1-6). IEEE.
Agrawal, A., Gans, J., & Goldfarb, A. (2017). What to expect from artificial intelligence. MIT Sloan Management Review, 58(3), 23-26.
http://mitsmr.com/2jZdf1Y.
Agarwal, M., Yadav, A., & Sharma, S. K. (2021). Role of artificial intelligence on job engagement and employee behavior in an organization. Dr. Dy patil b-school, pune, india, 792.
Alvarado, P. (2017). Building the Machine Learning Infrastructure. Teradata Operation, Inc.
Aouadni, I., & Rebai, A. (2017). Decision support system based on genetic algorithm and multi-criteria satisfaction analysis (MUSA) method for measuring job satisfaction. Annals of Operations Research, 256, 3-20.
Anand, S., & Singh, M. A. (2022). EMPLOYEE WELLBEING AND MENTAL HEALTH.
Ang, S. H., Cavanagh, J., Southcombe, A., Bartram, T., Marjoribanks, T., & McNeil, N. (2017). Human resource management, social connectedness and health and well-being of older and retired men: The role of Men’s Sheds. The International Journal of Human Resource Management, 28(14), 1986-2016.
Arora, M., Gupta, J., Mittal, A., & Prakash, A. (2024). A bibliometric review of artificial intelligence technologies in human resource management: an overview of research trends. Global Knowledge, Memory and Communication.
Arslan, A., Cooper, C., Khan, Z., Golgeci, I., & Ali, I. (2021). Artificial intelligence and human workers interaction at team level: a conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower, 43(1), 75-88.
Aslanova, I. V., & Kulichkina, A. I. (2020, May). Digital maturity: Definition and model. In 2nd International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2020) (pp. 443-449). Atlantis Press.
Ashraf, F. (2022). The Changing Landscape of Human Resource Management: Adapting to New Challenges. Scholar Spheres Journal of Arts and Humanities, 2(01), 17-20.
Azadeh, A., & Zarrin, M. (2016). An intelligent framework for productivity assessment and analysis of human resource from resilience engineering, motivational factors, HSE and ergonomics perspectives. Safety Science, 89, 55–71.
https://doi.org/10.1016/j. ssci.2016.06.001.
Babaita, I. S., Rafiu, A. J., & Aremu, S. A. (2018). Impact of information technology on human resource management procurement functions: a case of a Nigerian university. Malaysian management journal, 22, 139-151.
Baldegger, R., Caon, M., & Sadiku, K. (2020). Correlation between entrepreneurial orientation and implementation of AI in human resources management (HRM). Technology innovation management review.
Baluch, A. M. (2017). Employee perceptions of HRM and well-being in nonprofit organizations: Unpacking the unintended. The International Journal of Human Resource Management, 28(14), 1912-1937.
Bankins, S., Formosa, P., Griep, Y., & Richards, D. (2022). AI decision making with dignity? Contrasting workers’ justice perceptions of human and AI decision making in a human resource management context. Information Systems Frontiers, 24(3), 857-875.
Bastida, M., Neira, I., & Lacalle-Calderon, M. (2022). Employee's subjective-well-being and job discretion: Designing gendered happy jobs. European Research on Management and Business Economics, 28(2), 100189.
Bersin, J., & Chamorro-Premuzic, T. (2019). The case for hiring older workers. Harvard Business Review, 26, 2019.
Beraldin, A. R., Danese, P., & Romano, P. (2019). An investigation of the relationship between lean and well-being based on the job demands-resources model. International Journal of Operations & Production Management, 39(12), 1295-1322.
Behúnová, A., Knapcikova, L., Behún, M. (2023). Dimensions of the Implementation of Controlling in the Company. In: Company Controlling. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
https://doi.org/10.1007/978-3-031-13153-0_3.
Belk, R., Weijo, H., & Kozinets, R. V. (2021). Enchantment and perpetual desire: Theorizing disenchanted enchantment and technology adoption. Marketing Theory, 21(1), 25-52.
Boehmer, N., & Schinnenburg, H. (2023). Critical exploration of AI-driven HRM to build up organizational capabilities. Employee Relations: The International Journal, 45(5), 1057-1082.
Boehnlein, P., & Baum, M. (2022). Does job crafting always lead to employee well-being and performance? Meta-analytical evidence on the moderating role of societal culture. The International Journal of Human Resource Management, 33(4), 647-685.
Bousdekis, A., Apostolou, D., & Mentzas, G. (2020). A human cyber physical system framework for operator 4.0–artificial intelligence symbiosis. Manufacturing letters, 25, 10-15.
Boxall, P., Guthrie, J. P., & Paauwe, J. (2016). Editorial introduction: Progressing our understanding of the mediating variables linking HRM, employee well-being and organisational performance. Human Resource Management Journal, 26(2).
Boxall, P. (2021). Studying mutuality and perversity in the impacts of human resource management on societal well‐being: Advancing a pluralist agenda. Human Resource Management Journal, 31(4), 834-846.
Braganza, A., Chen, W., Canhoto, A., & Sap, S. (2021). Productive employment and decent work: The impact of AI adoption on psychological contracts, job engagement and employee trust. Journal of business research, 131, 485-494.
Bulboli Qadiklai, Samia and Parsania, Hamid. (2023). A systematic review of the ethical implications of using artificial intelligence in digital technologies and its relationship with the ethics of flourishing. Social and cultural strategy (In Persian).
Budhwar, P., Malik, A., De Silva, M. T., & Thevisuthan, P. (2023). Introduction: Artificial intelligence–challenges and opportunities for international HRM: a review and research agenda. Artificial Intelligence and International HRM, 1-32.
Bussler, L., & Davis, E. (2002). Information systems: The quiet revolution in human resource management. Journal of computer information systems, 42(2), 17-20.
Buxmann, P., Hess, T., & Thatcher, J. (2019). Call for papers, issue 1/2021. Business & Information Systems Engineering, 61(4), 545–547.
https://doi.org/10.1007/s12599-019-00606-2.
Castellacci, F., & Viñas-Bardolet, C. (2019). Internet use and job satisfaction. Computers in Human Behavior, 90, 141-152.
Calvard, T. S., & Sang, K. J. (2017). Complementing psychological approaches to employee well-being with a socio-structural perspective on violence in the workplace: An alternative research agenda. The International Journal of Human Resource Management, 28(16), 2256-2274.
Chai, D. S., & Park, S. (2022). The increased use of virtual teams during the Covid-19 pandemic: implications for psychological well-being. Human Resource Development International, 25(2), 199-218.
Chaudhuri, R., Chatterjee, S., Vrontis, D., & Alessio, I. (2022). Work from anywhere and employee psychological well-being: moderating role of HR leadership support. Personnel Review, 51(8), 1967-1989.
Chambel, M. J., & Farina, A. (2014). HRM and temporary workers’ well-being: A study in Portugal and Brazil. Cross Cultural Management, 22(3), 447-463.
Charlier, R., & Kloppenburg, S. (2017). Artificial Intelligence in HR: a No-brainer. Pwc. at.
Clark, C. M., & Gevorkyan, A. V. (2020). Artificial intelligence and human flourishing. American Journal of Economics and Sociology, 79(4), 1307-1344.
Cheng, M.M., Hackett, R.D., 2019. A critical review of algorithms in HRM: definition, theory, and practice. Hum. Resour. Manag. Rev. 31 (1), 100698
https://doi.org/10.1016/j.hrmr.2019.100698.
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2022). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human resource management review, 33(1), 100899.
Conway, E., Fu, N., Monks, K., Alfes, K., & Bailey, C. (2016). Demands or resources? The relationship between HR practices, employee engagement, and emotional exhaustion within a hybrid model of employment relations. Human Resource Management, 55(5), 901-917.
Cooper, B., Wang, J., Bartram, T., & Cooke, F. L. (2018). Well‐being‐oriented human resource management practices and employee performance in the Chinese banking sector: The role of social climate and resilience. Human Resource Management, 58(1), 85-97.
Cooper, C. L., Liu, Y., & Tarba, S. Y. (2014). Resilience, HRM practices and impact on organizational performance and employee well-being: International Journal of Human Resource Management 2015 Special Issue.
Cubric, M. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62, 101257.
Daovisan, H., & Chamaratana, T. (2021). Do linking social, human and financial capital matter for the labour force in Lao PDR? The relationship between occupational well-being and life satisfaction. Employee Relations: The International Journal, 43(4), 873-891.
D’Alfonso, S. (2020). AI in mental health. Current opinion in psychology, 36, 112-117.
Delecraz, S., Eltarr, L., Becuwe, M., Bouxin, H., Boutin, N., & Oullier, O. (2022). Responsible Artificial Intelligence in Human Resources Technology: An innovative inclusive and fair by design matching algorithm for job recruitment purposes. Journal of Responsible Technology, 11, 100041.
De Koeijer, R., Paauwe, J., Huijsman, R., & Strating, M. (2021). Examining of the effect of HRM in mitigating negative effects of LM&SS on employee well-being in health care. International Journal of Lean Six Sigma, 13(1), 67-100.
DiClaudio, M. (2019). People analytics and the rise of HR: how data, analytics and emerging technology can transform human resources (HR) into a profit center. Strategic HR Review, 18(2), 42-46.
Diener, E., Wirtz, D., Tov, W., Kim-Prieto, C., Choi, D. W., Oishi, S., & Biswas-Diener, R. (2010). New well-being measures: Short scales to assess flourishing and positive and negative feelings. Social indicators research, 97, 143-156.
in the age of artificial intelligence. In Research Handbook on Line Managers (pp. 367-387). Edward Elgar Publishing.
Du, J. (2024). Do Humans Trust AI in HRM? Why Do? Why Not? —Insights from a Decade of Research. Journal of Research in Social Science and Humanities, 3(7), 20-48.
Duggan, J., Sherman, U., Carbery, R., & McDonnell, A. (2020). Algorithmic management and app‐work in the gig economy: A research agenda for employment relations and HRM. Human resource management journal, 30(1), 114-132.
Durairaj, S., & Vetrivel, V. (2024, June). The Effect of AI (Artificial Intelligence) in Employee Performance Evaluation on Employee Retention in the Information Technology Sector. In International Conference on Digital Transformation in Business: Navigating the New Frontiers Beyond Boundaries (DTBNNF 2024) (pp. 88-108). Atlantis Press.
Dvorakova, Z. DIGITAL WELLBEING FOR HIGHLY SKILLED STAFF. health, 2(2), 45.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International journal of information management, 57, 101994.
El-Sharkawy, S. A., Nafea, M. S., & Hassan, E. E. D. H. (2023). HRM and organizational learning in knowledge economy: investigating the impact of happiness at work (HAW) on organizational learning capability (OLC). Future Business Journal, 9(1), 10.
Feng, J., & Yuan, J. (2016). Effect of technology innovation and spillovers on the carbon intensity of human well-being. SpringerPlus, 5, 1-8.
Ferreira, M. C., Santos, L. A., & Paschoal, T. (2022). Well-being, Malaise and Quality of Work Life Management. Revista Psicologia: Teoria e Prática, 24(3), ePTPSS15511-ePTPSS15511.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., & Vayena, E. (2018). AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds and machines, 28, 689-707.
Franco-Santos, M., & Doherty, N. (2017). Performance management and well-being: a close look at the changing nature of the UK higher education workplace. The International Journal of Human Resource Management, 28(16), 2319-2350.
Fulmer, I. S., Gerhart, B., & Kim, J. H. (2023). Compensation and performance: A review and recommendations for the future. Personnel Psychology, 76(2), 687-718.
Guenole, N., & Feinzig, S. (2018). The business case for AI in HR. With Insights and Tips on Getting Started. Armonk: IBM Smarter Workforce Institute, IBM Corporation.
Guerci, M., Radaelli, G., Siletti, E., Cirella, S., & Rami Shani, A. B. (2013). The impact of human resource management practices and corporate sustainability on organizational ethical climates: An employee perspective. Journal of Business Ethics, 126, 325-342.
Guerci, M., Hauff, S., & Gilardi, S. (2022). High performance work practices and their associations with health, happiness and relational well-being: are there any tradeoffs?. The International Journal of Human Resource Management, 33(2), 329-359.
Gupta, P., Fernandes, S. F., & Jain, M. (2018). Automation in recruitment: a new frontier. Journal of Information Technology Teaching Cases, 8(2), 118-125.
Guest, D. E. (2017). Human resource management and employee well‐being: Towards a new analytic framework. Human resource management journal, 27(1), 22-38.
Grueman, J. A., & Budworth, M. H. (2022). Positive psychology and human resource management: Building an HR architecture to support human flourishing. Human Resource Management Review, 32(3), 100911.
Haricharan, S. J. (2023). Leadership, management and organisational implications for public service employee well-being and performance. SA Journal of Human Resource Management, 21, 2080.
Hauff, S., Guerci, M., & Gilardi, S. (2020, July). Well-being-oriented HRM configurations: diffusion, contingencies and outcomes. In Evidence-based HRM: A Global Forum for Empirical Scholarship (Vol. 8, No. 3, pp. 253-271). Emerald Publishing Limited.
Haslinda, A. (2009). Evolving terms of human resource management and development. The journal of International social research, 2(9), 180-186.
Heffernan, M., & Dundon, T. (2016). Cross‐level effects of high‐performance work systems (HPWS) and employee well‐being: the mediating effect of organisational justice. Human Resource Management Journal, 26(2), 211-231.
Hetenyi, G., Lengyel, A., & Szilasi, M. (2019). Quantitative analysis of qualitative data: Using voyant tools to investigate the sales-marketing interface. Journal of Industrial Engineering and Management (JIEM), 12(3), 393-404.
Higgs, M., & Dulewicz, S. V. (2003). The design of a new instrument to assess leadership dimensions and styles.
Hickok, M. (2021). Lessons learned from AI ethics principles for future actions. AI and Ethics, 1(1), 41-47.
Hmoud, B., & Laszlo, V. (2019). Will Artificial Intelligence Take over Human resources Recruitment And Selection?. Network Intelligence Studies, 7(13), 21-30.
Ho, H., & Kuvaas, B. (2018). Human resource management systems, employee well‐being, and firm performance from the mutual gains and critical perspectives: The well‐being paradox. Human Resource Management, 59(3), 235-253.
Huang, L. C., Ahlstrom, D., Lee, A. Y. P., Chen, S. Y., & Hsieh, M. J. (2016). High performance work systems, employee well-being, and job involvement: An empirical study. Personnel Review, 45(2), 296-314.
Huettermann, H., & Bruch, H. (2019). Mutual gains? Health‐related HRM, collective well‐being and organizational performance. Journal of Management Studies, 56(6), 1045-1072.
Huppert, F. A., & So, T. T. (2013). Flourishing across Europe: Application of a new conceptual framework for defining well-being. Social indicators research, 110, 837-861.
Islam, M. S., & Amin, M. (2021). A systematic review of human capital and employee well-being: putting human capital back on the track. European Journal of Training and Development, 46(5/6), 504-534.
Jain, H., Padmanabhan, B., Pavlou, P. A. & Santanam, R.T. (Eds). (2018). Call for papers—Special Issue of Information Systems Research—Humans, algorithms, and augmented intelligence: The future of work, organisations, and society. Information Systems Research, 29, 250–251.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business horizons, 61(4), 577-586.
Jaiswal, A., Arun, C. J., & Varma, A. (2021). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. In Artificial Intelligence and International HRM (pp. 114-143). Routledge.
Jaiswal, A., Gupta, S., & Prasanna, S. (2022). Theorizing employee stress, well-being, resilience and boundary management in the context of forced work from home during COVID-19. South Asian Journal of Business and Management Cases, 11(2), 86-104.
Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37–50.
https://doi.org/10.1016/j.bushor.2019.09.003.
Kapadia, M., & Dagar, C. (2022). Understanding self and well-being based on Ayurveda: Implications for Indian management. In Indigenous Indian management:
conceptualization, practical applications and pedagogical initiatives (pp. 157-197). Cham: Springer International Publishing.
Kakatkar, C., Bilgram, V., & Füller, J. (2020). Innovation analytics: Leveraging artificial intelligence in the innovation process. Business Horizons, 63(2), 171-181.
Kanungo, S. (2020). REVOLUTIONIZING DATA PROCESSING: ADVANCED CLOUD COMPUTING AND AI SYNERGY FOR IOT INNOVATION. International Research Journal of Modernization in Engineering Technology and Science, 2, 1032-1040.
Kanungo, S. (2020). REVOLUTIONIZING DATA PROCESSING: ADVANCED CLOUD COMPUTING AND AI SYNERGY FOR IOT INNOVATION. International Research Journal of Modernization in Engineering Technology and Science, 2, 1032-1040.
Karatop, B., Kubat, C., & Uygun, Ö. (2015). Talent management in manufacturing system using fuzzy logic approach. Computers & Industrial Engineering, 86, 127-136.
Kazim, E., & Koshiyama, A. S. (2021). A high-level overview of AI ethics. Patterns, 2(9).
Kowalski, T., Loretto, W., & Redman, T. (2015). Special Issue of International Journal of Human Resource Management: Well-being and HRM in the changing workplace.
Kowalski, T. H., & Loretto, W. (2017). Well-being and HRM in the changing workplace. The International Journal of Human Resource Management, 28(16), 2229-2255.
Kondapaka, P., Khanra, S., Malik, A., Kagzi, M., & Hemachandran, K. (2023). Finding a fit between CXO’s experience and AI usage in CXO decision-making: evidence from knowledge-intensive professional service firms. Journal of Service Theory and Practice, 33(2), 280-308.
Kundu, SC, & Kadian, R. (2012). Applications of HRIS in human resource management in India: A study. European Journal of Business and Management, 4(21), 34-41.
Kshetri, N. (2021). Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence. Management Research Review, 44(7), 970-990.
Kwan, A., Forbes, P. A., Mitchell, D. E., Blouin, J. S., & Cullen, K. E. (2019). Neural substrates, dynamics and thresholds of galvanic vestibular stimulation in the behaving primate. Nature communications, 10(1), 1904.
Långstedt, J., & Arrowsmith, J. (2023). Values, Work and Well-being in Artificial Intelligence Society: Exacerbating Dilemmas in Human Resource Management. In Algorithmic Ethics (pp. 22-38). Routledge.
Leikas, J., Koivisto, R., & Gotcheva, N. (2019). Ethical framework for designing autonomous intelligent systems. Journal of Open Innovation: Technology, Market, and Complexity, 5(1), 18.
LEWICKA, D., STAROWICZ-RAJCA, H., BLBAS, R., & WILCZEWSKI, A. (2024). CULTIVATING SUCCESS: A PRACTICAL EXPLORATION OF APPLYING ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCES MANAGEMENT. Scientific Papers of Silesian University of Technology. Organization & Management/Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie, (199).
Li, J. J., Bonn, M. A., & Ye, B. H. (2019). Hotel employee's artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172-181.
Li, W., Chen, J., & Hendrischke, H. (2017). An institutional perspective on individual work well-being: Evidence from China. Social Indicators Research, 132, 187-218.
Li, X., Seah, R., Wang, X., & Yuen, K. F. (2022). Investigating the role of sociotechnical factors on seafarers’ psychological capital and mental well-being. Technology in Society, 71, 102138.
Lin, C., Li, X., & Lam, L. W. (2019). Development or maintenance? Dual‐oriented human resource system, employee achievement motivation, and work well‐being. Human Resource Management, 59(4), 311-325.
Lisovskaia, A. (2022). Implementing Well‐Being Practices through Russian Context: HRD Perspective. Journal of East-West Business, 28(3), 254-269.
Liu, F., Chow, I. H. S., Xiao, D., & Huang, M. (2017). Cross-level effects of HRM bundle on employee well-being and job performance: The mediating role of psychological ownership. Chinese management studies, 11(3), 520-537.
Liu, C. (2019). Multiple Social Credit Systems in China (SSRN Scholarly Paper ID 3423057). Social Science Research Network.
https://papers.ssrn.com/abstract=3423057.
Lucia-Casademunt, A. M., Cuéllar-Molina, D., & García-Cabrera, A. M. (2018). The role of human resource practices and managers in the development of well-being: cultural differences in the changing workplace. Cross Cultural & Strategic Management, 25(4), 716-740.
Mainardi, I. (2024). Change management: artificial intelligence (AI) at the service of public administrations. AI & SOCIETY, 1-29.
Mallipeddi, D., Norell, M., Sosa, M., & Nyborg, L. (2017). Influence of running-in on surface characteristics of efficiency tested ground gears. Tribology International, 115, 45-58.
Maedche, A., Legner, C., Benlian, A., Berger, B., Gimpel, H., Hess, T., Hinz, O., Morana, S., & Söllner, M. (2019). AI-based digital assistants. Business & Information Systems Engineering, 61(4), 535–544.
https://doi.org/10.1007/s12599-019-00600-8.
Maity, S. (2019). Identifying opportunities for artificial intelligence in the evolution of training and development practices. Journal of Management Development, 38(8), 651-663.
Malik, A., De Silva, M. T., Budhwar, P., & Srikanth, N. R. (2021). Elevating talents' experience through innovative artificial intelligence-mediated knowledge sharing: Evidence from an IT-multinational enterprise. Journal of International Management, 27(4), 100871.
Malik, A., Froese, F. J., & Sharma, P. (2020). Role of HRM in knowledge integration: Towards a conceptual framework. Journal of Business Research, 109, 524-535.
Malik, A., Budhwar, P., Patel, C., & Srikanth, N. (2021). May the bots be with you! delivering hr cost-effectiveness and individualised employee experiences in an mne., 83-113.
Mansour, S., & Nogues, S. (2022). Advantages of and barriers to crafting new technology in healthcare organizations: a qualitative study in the COVID-19 context. International journal of environmental research and public health, 19(16), 9951
Marescaux, E., De Winne, S., & Forrier, A. (2019). Developmental HRM, employee well‐being and performance: The moderating role of developing leadership. European Management Review, 16(2), 317-331.
Mariappanadar, S., Maurer, I., Kramar, R., & Muller-Camen, M. (2022). Is it a sententious claim? An examination of the quality of occupational health, safety and well-being disclosures in global reporting initiative reports across industries and countries. International Business Review, 31(2), 101922.
Meijerink, J. G., Boons, M., Keegan, A., & Marler, J. (2018). Call for papers for the special issue on Digitization and the transformation of human resource management. International Journal of Human Resource Management. https://doi.org/10.1080/09585 192.2018.1503845.
Mehrabad, M. S., & Brojeny, M. F. (2007). The development of an expert system for effective selection and appointment of the jobs applicants in human resource management. Computers & Industrial Engineering, 53(2), 306–312.
Mer, A. (2023). Artificial intelligence in human resource management: Recent trends and research agenda. Digital Transformation, Strategic Resilience, Cyber Security and Risk Management, 111, 31-56.
Mezgár, I. (2021). From ethics to standards; an overview of AI ethics in CPPS. IFAC-PapersOnLine, 54(1), 723-728.
Michailidis, M. P. (2018). The challenges of AI and blockchain on HR recruiting practices. Cyprus Review, 30(2), 169-180.
Mohapatra, L. M., Kamesh, A. V. S., & Roul, J. (2023). Challenges and path ahead for artificial intelligence-aided human resource management. In The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part A (pp. 107-121). Emerald Publishing Limited.
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Bmj, 339.
McGovern, D. P., Hayes, A., Kelly, S. P., & O’Connell, R. G. (2018). Reconciling age-related changes in behavioural and neural indices of human perceptual decision-making. Nature human behaviour, 2(12), 955-966.
Murungi, D., Wiener, M., & Marabelli, M. (2017). Ups and Downs in Information Systems Projects—The Dynamic Interplay Between Control Activities and Emotions. In Thirty Eight International Conference on Information Systems (pp. 1-11).
Niks, I. M., Veldhuis, G. A., van Zwieten, M. H., Sluijs, T., Wiezer, N. M., & Wortelboer, H. M. (2022). Individual workplace well-being captured into a literature-and stakeholders-based causal loop diagram. International Journal of Environmental Research and Public Health, 19(15), 8925.
Nguyen, T. M., & Malik, A. (2022). A two‐wave cross‐lagged study on AI service quality: The moderating effects of the job level and job role. British Journal of Management, 33(3), 1221-1237.
Nunes, P. M., Proença, T., & Carozzo-Todaro, M. E. (2023). A systematic review on well-being and ill-being in working contexts: contributions of self-determination theory. Personnel Review, 53(2), 375-419.
Nor, N. I. M., Arokiasamy, L., & Balaraman, R. A. (2018). The influence of Internet of Things on employee’s engagement among generation Y at the workplace. In SHS Web of Conferences (Vol. 56, p. 03003). EDP Sciences.
Nura, A. A., & Osman, N. H. (2013). Gauging the effect of performance management and technology based human resource management on employee retention: The perspective of academics in higher educational institutions in Sokoto State Nigeria. Asian Social Science, 9(15), 295.
Okay‐Somerville, B., & Scholarios, D. (2018). A multilevel examination of skills‐oriented human resource management and perceived skill utilization during recession: Implications for the well‐being of all workers. Human Resource Management, 58(2), 139-154.
Ouchchy, L., Coin, A., & Dubljević, V. (2020). AI in the headlines: the portrayal of the ethical issues of artificial intelligence in the media. AI & SOCIETY, 35, 927-936.
Oxtoby, D. W., Allen, D., & Brown, J. (2023). The humanities and the rise of the terabytes. Bulletin of the American Academy of Arts and Sciences, 76(3), 30-41.
Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2021). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. In Artificial intelligence and international HRM (pp. 60-82). Routledge.
Pagnozzi, F. (2022). People Analytics and Human Resource Management: How the Use of Smart Data Can Improve the Training Processes. puntOorg International Journal, 7(2), 108-123.
Pap, J., Mako, C., Illessy, M., Kis, N., & Mosavi, A. (2022). Modeling organizational performance with machine learning. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 177.
Paul, H., & Garg, P. (2014). Healing HRM through positive psychology: An outlook. Procedia-Social and Behavioral Sciences, 133, 141-150.
Paschen, U., Pitt, C., & Kietzmann, J. (2020). Artificial intelligence: Building blocks and an innovation typology. Business Horizons, 63(2), 147-155.
Peccei, R., & Van De Voorde, K. (2019). Human resource management–well‐being–performance research revisited: Past, present, and future. Human resource management journal, 29(4), 539-563.
Pessach, D., Singer, G., Avrahami, D., Ben-Gal, H. C., Shmueli, E., & Ben-Gal, I. (2020). Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming. Decision Support Systems, 134, 113290.
Piabuo, S. M., Piendiah, N. E., Njamnshi, N. L., & Tieguhong, P. J. (2017). The impact of ICT on the efficiency of HRM in Cameroonian enterprises: Case of the Mobile telephone industry. Journal of Global Entrepreneurship Research, 7(1), 7.
Pillai, R., & Sivathanu, B. (2020). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: An International Journal, 27(9), 2599-2629.
Pinnington, A. H., & Ayoko, O. B. (2021). Managing physical and virtual work environments during the COVID-19 pandemic: Improving employee well-being and achieving mutual gains. Journal of Management & Organization, 27(6), 993-1002.
Piwowar-Sulej, K. (2021). Human resources development as an element of sustainable HRM–with the focus on production engineers. Journal of cleaner production, 278, 124008.
Popo–Olaniyan, O., Elufioye, O. A., Okonkwo, F. C., Udeh, C. A., Eleogu, T. F., & Olatoye, F. O. (2022). Ai-driven talent analytics for strategic hr decision-making in the United States Of America: A Review. International Journal of Management & Entrepreneurship Research, 4(12), 607-622.
Premnath, S. N., & Arun, A. (2020). A qualitative study of artificial intelligence application framework in human resource management.
Prikshat, V., Malik, A. and Budhwar, P. (2021), “AI-augmented HRM: antecedents, assimilation and multilevel consequences”, Human Resource Management Review, Vol. ahead-of-print No. aheadof-print, p. 100860.
Prikshat, V., Islam, M., Patel, P., Malik, A., Budhwar, P., & Gupta, S. (2023). AI-Augmented HRM: Literature review and a proposed multilevel framework for future research. Technological forecasting and social change, 193, 122645.
Prikshat, V., Malik, A., & Budhwar, P. (2023). AI-augmented HRM: Antecedents, assimilation and multilevel consequences. Human Resource Management Review, 33(1), 100860.
Qamar, Y., Agrawal, R. K., Samad, T. A., & Chiappetta Jabbour, C. J. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339-1370.
Rao, S., Chitranshi, J., & Punjabi, N. (2020). Role of artificial intelligence in employee engagement and retention. Journal of Applied Management-Jidnyasa, 42-60.
Rahman, M. M., Rahaman, M. S., Uddin, M. J., Samuel, A. B., & Moral, I. H. (2022). Does organisational support moderate the relationships between work-family/family-work conflict and well-being of private university academicians?. International Journal of Business Excellence, 28(1), 32-50.
Rahimi, Farajollah, Bavorsad, Balqis, Karamzadeh, Mehshad. (2023). Identifying and prioritizing the use of Internet of Things technology in human resource management. Sustainable Human Resource Management, 5(9), 170-151. doi:
10.22080/shrm.2023.4410 (In Persian).
Raišienė, A. G., Rapuano, V., Masilionytė, G., & Raišys, S. J. (2022). " White collars" on self-reported well-being, health and work performance when teleworking from home. Problems and perspectives in management. Sumy: Business perspectives, 2022, vol. 20, iss. 2.
Rhodes, C., & Harvey, G. (2012). Agonism and the possibilities of ethics for HRM. Journal of Business Ethics, 111, 49-59.
Rodgers, W., Murray, J. M., Stefanidis, A., Degbey, W. Y., & Tarba, S. Y. (2023). An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes. Human resource management review, 33(1), 100925.
Ramanathan, K., Pramod, D., & Patil, K. (2024, July). Factors that impact AI-augmented HRM in micro, small, and medium-sized enterprises MSMEs: A task viability theory approach. In AIP Conference Proceedings (Vol. 3168, No. 1). AIP Publishing.
Rurkkhum, S. (2023). A bundle of human resource practices and employee resilience: the role of employee well-being. Asia-Pacific Journal of Business Administration, 16(3), 716-731.
Ruel, H.J., Bondarouk, T.V. & Van der Velde, M. (2007). The contribution of e‐HRM to HRM effectiveness. Employee Relations, 29(3), 280-291.
Salas‐Vallina, A., Alegre, J., & López‐Cabrales, Á. (2021). The challenge of increasing employees' well‐being and performance: How human resource management practices and engaging leadership work together toward reaching this goal. Human Resource Management, 60(3), 333-347.
Salas-Vallina, A., Pozo, M., & Fernandez-Guerrero, R. (2020). New times for HRM? Well-being oriented management (WOM), harmonious work passion and innovative work behavior. Employee Relations: The International Journal, 42(3), 561-581.
Salas-Vallina, A., Pasamar, S., & Donate, M. J. (2021). Well-being in times of ill-being: how AMO HRM practices improve organizational citizenship behavior through work-related well-being and service leadership. Employee Relations: The International Journal, 43(4), 911-935.
Samarasinghe, K. R., & Medis, A. (2020). Artificial intelligence based strategic human resource management (AISHRM) for industry 4.0. Global journal of management and business research, 20(2), 7-13.
Santos, R. S., & Lousã, E. P. (2022). Give me five: The most important social values for well-being at work. Administrative Sciences, 12(3), 101.
Saukkonen, J., Kreus, P., Obermayer, N., Ruiz, Ó. R., & Haaranen, M. (2019, October). AI, RPA, ML and other emerging technologies: anticipating adoption in the HRM field. In ECIAIR 2019 European Conference on the Impact of Artificial Intelligence and Robotics (Vol. 287). Academic Conferences and publishing limited.
Šarotar Žižek, S., Mulej, M., & Treven, S. (2015). The conceptual model of well-being management based on achieving requisite personal holism. Cybernetics and Systems, 46(5), 342-354.
Saxena, N., & Khandelwal, A. R. (2022). Effectiveness of E‐HRM Tools Using the Functionalities of Artificial Intelligence During Remote Working in Lockdown Period. Impact of artificial intelligence on organizational transformation, 387-397.
Seligman, M. E. (2011). Flourish: A visionary new understanding of happiness and well-being. Simon and Schuster.
Shan, W., Wang, Z., & Su, M. Y. (2022). The impact of public responses toward healthcare workers on their work engagement and well-being during the Covid-19 pandemic. Frontiers in Psychology, 13, 949153.
Sheehan, C. (2005). A model for HRM strategic integration. Personnel review, 34(2), 192-209.
Shahvazian, S, & Hashemi Gheinani, F. (2020). The challenges of human resource management during the transition period of Corona pandemic and providing solutions in the Iran hotel industry. TOURISM MANAGEMENT STUDIES (TOURISM STUDIES), 15(Supplement ), 217-252. SID. https://sid.ir/paper/408054/en
Sharma, A. (2021). Digitalization of Human Resource Management Practice and Its Impact on Employee Well-being. Tobacco Regulatory Science (TRS), 4549-4555.
Sitzmann, T., & Weinhardt, J. M. (2019). Approaching evaluation from a multilevel perspective: A comprehensive analysis of the indicators of training effectiveness. Human Resource Management Review, 29(2), 253-269.
Straus, E., Uhlig, L., Kühnel, J., & Korunka, C. (2023). Remote workers’ well-being, perceived productivity, and engagement: which resources should HRM improve during COVID-19? A longitudinal diary study. The International Journal of Human Resource Management, 34(15), 2960-2990.
Stahl, B. C., Andreou, A., Brey, P., Hatzakis, T., Kirichenko, A., Macnish, K., & Wright, D. (2021). Artificial intelligence for human flourishing–Beyond principles for machine learning. Journal of Business Research, 124, 374-388.
Sutton, A., & Atkinson, C. (2023, November). Performance at the cost of well-being? Testing the multi-level effects of HR practices on organisational performance via employee experiences and well-being. In Evidence-Based HRM: A Global Forum for Empirical Scholarship (Vol. 11, No. 4, pp. 675-694). Emerald Publishing Limited.
Strohmeier, S., & Piazza, F. (2015). Artificial intelligence techniques in human resource management—a conceptual exploration. Intelligent Techniques in Engineering Management: Theory and Applications, 149-172.
Strohmeier, S., & Kabst, R. (2009). Organizational adoption of e‐HRM in Europe: An empirical exploration of major adoption factors. Journal of Managerial Psychology, 24(6), 482-501.
Strohmeier, S., & Kabst, R. (2014). Configurations of e-HRM‐an empirical exploration. Employee Relations, 36(4), 333-353.
Strohmeier, C. S. (2018). Foreign volunteers and their contribution towards development of South African children (Doctoral dissertation, Nelson Mandela University; Faculty of Business and Economic Sciences).
Strohmeier, S. (2020). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 34(3), 345-365.
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60-73.
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
Tortia, E. C., Sacchetti, S., & López-Arceiz, F. J. (2022). A human growth perspective on sustainable HRM practices, worker well-being and organizational performance. Sustainability, 14(17), 11064.
Tursunbayeva, A. (2019), “Human resource technology disruptions and their implications for human resources management in healthcare organizations”, BMC Health Services Research, Vol. 19 No. 1, pp. 1-8.
Trieu, V. H. (2017). Getting value from Business Intelligence systems: A review and research agenda. Decision Support Systems, 93, 111-124.
Trifu, A., Smîdu, E., Badea, D. O., Bulboacă, E., & Haralambie, V. (2022). Applying the PRISMA method for obtaining systematic reviews of occupational safety issues in literature search. In MATEC Web of Conferences (Vol. 354, p. 00052). EDP Sciences.
Upadhyay, A.K., Khandelwal, K., 2018. Applying artificial intelligence: implications for recruitment. Strategy. HR Rev. 17 (5), 255–258.
https://doi.org/10.1108/SHR-07-2018-0051 .
Uribetxebarria, U., Gago, M., Legarra, M., & Elorza, U. (2021). The link between HIWPs and well-being at work: the mediating role of trust. Employee Relations: The International Journal, 43(4), 842-857.
Vahdat, S. (2022). The role of IT-based technologies on the management of human resources in the COVID-19 era. Kybernetes, 51(6), 2065-2088.
Van De Voorde, K., Paauwe, J., & Van Veldhoven, M. (2012). Employee well‐being and the HRM–organizational performance relationship: a review of quantitative studies. International Journal of Management Reviews, 14(4), 391-407.
Van der Maden, W., Lomas, D., & Hekkert, P. (2023). A framework for designing AI systems that support community wellbeing. Frontiers in Psychology, 13, 1011883.
Van Esch, P., Black, J. S., & Arli, D. (2021). Job candidates’ reactions to AI-enabled job application processes. AI and Ethics, 1, 119-130.
Veth, K. N., Emans, B. J., Van der Heijden, B. I., Korzilius, H. P., & De Lange, A. H. (2015). Development (f) or maintenance? An empirical study on the use of and need for HR practices to retain older workers in health care organizations. Human resource development quarterly, 26(1), 53-80.
Villajos, E., Tordera, N., & Peiró, J. M. (2019). Human resource practices, eudaimonic well-being, and creative performance: The mediating role of idiosyncratic deals for sustainable human resource management. Sustainability, 11(24), 6933.
Vishwakarma, L. P., & Singh, R. K. (2023). An analysis of the challenges to human resource in implementing artificial intelligence. In The Adoption and Effect of Artificial Intelligence on Human Resources Management, Part B (pp. 81-109). Emerald Publishing Limited.
Vihari, N. S., & Rao, M. K. (2013). Analytics as a predictor for strategic and sustainable human resource function: an integrative literature review. In IIM conference (pp. 1-13).
Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial intelligence in tactical human resource management: A systematic literature review. International Journal of Information Management Data Insights, 1(2), 100047.
Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial Intelligence and International HRM, 172-201.
Wang, X. L., Wang, L., Bi, Z., Li, Y. Y., & Xu, Y. (2016). Cloud computing in human resource management (HRM) system for small and medium enterprises (SMEs). The International Journal of Advanced Manufacturing Technology, 84(1), 485-496.
Wang, X., Wong, Y. D., Chen, T., & Yuen, K. F. (2021). Adoption of shopper-facing technologies under social distancing: A conceptualization and an interplay between task-technology fit and technology trust. Computers in Human Behavior, 124, 106900.
Williams, C., Schallmo, D., Lang, K., & Boardman, L. (2019). Digital maturity models for small and medium-sized enterprises: A systematic literature review. Florence: The ISPIM Innovation Conference.
Wilson, H. J., Daugherty, P., & Bianzino, N. (2017). The jobs that artificial intelligence will create. MIT Sloan Management Review, 58(4), 14.
Wohlin, C. (2014, May). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering (pp. 1-10).
Xia, J., Zhang, M. M., Zhu, J. C., Fan, D., & Samaratunge, R. (2020). HRM reforms and job-related well-being of academics. Personnel Review, 49(2), 597-619.
Xu, J., Xie, B., & Tang, B. (2020). Guanxi HRM practice and employees’ occupational well-being in China: a multi-level psychological process. International journal of environmental research and public health, 17(7), 2403.
Yang, Y. (2022). Artificial intelligence-based organizational human resource management and operation system. Frontiers in psychology, 13, 962291.
Yang, Y., Shamim, S., Herath, D. B., Secchi, D., & Homberg, F. (2023). The evolution of HRM practices: big data, data analytics, and new forms of work. Review of Managerial Science, 17(6), 1937-1942.
Yazdani, Hamidreza, Hakimini, Masoud. (2024). Identifying the challenges and opportunities of using artificial intelligence in human resources management: a hybrid approach. Sustainable Human Resource Management, 6(10), 113-139. doi:
10.22080/shrm.2024.4601 (In Persian)
Yazdanparast, R., Zadeh, S. A., Dadras, D., & Azadeh, A. (2018). An intelligent algorithm for identification of optimum mix of demographic features for trust in medical centers in Iran. Artificial intelligence in medicine, 88, 25-36.
Zahoor, N., Donbesuur, F., Christofi, M., & Miri, D. (2022). Technological innovation and employee psychological well-being: The moderating role of employee learning orientation and perceived organizational support. Technological Forecasting and Social Change, 179, 121610.
Zhang, X., Lin, Z., Liu, Y., Chen, X., & Liu, D. M. (2020). How do human resource management practices affect employee well-being? A mediated moderation model. Employee Relations: The International Journal, 42(4), 903-919.
Zhang, Y., Xu, S., Zhang, L., & Yang, M. (2021). Big data and human resource management research: An integrative review and new directions for future research. Journal of Business Research, 133, 34-50.
Zohuri, B., & Rahmani, F. M. (2020). Artificial intelligence versus human intelligence: A new technological race. Acta Scientific Pharmaceutical Sciences (ISSN: 2581-5423), 4(5).
Xie, H., & Lau, T. C. (2023). Evidence-based green human resource management: A systematic literature review. Sustainability, 15(14), 10941.
Bos-Nehles, A., Renkema, M., & Janssen, M. (2017). HRM and innovative work behaviour: A systematic literature review. Personnel review, 46(7), 1228-1253.
Rathee, R., & Malik, S. (2024). MAPPING THE LANDSCAPE OF WORKPLACE HAPPINESS: A COMPREHENSIVE ANALYSIS OF PUBLICATION PATTERNS AND TRENDS. CAHIERS MAGELLANES-NS, 6(2), 3525-3549.
Shuck, B., Adelson, J. L., & Reio Jr, T. G. (2017). The employee engagement scale: Initial evidence for construct validity and implications for theory and practice. Human Resource Management, 56(6), 953-977.
Shuck, B., & Reio Jr, T. G. (2014). Employee engagement and well-being: A moderation model and implications for practice. Journal of Leadership & Organizational Studies, 21(1), 43-58.
Marabelli, M., & Davison, R. M. (2025). Artificial intelligence and the environment: ethical challenges and strategic opportunities for organizations. The Journal of Strategic Information Systems, 34(3), 101921.
Vivek, R., & Krupskyi, O. P. (2024). EI & AI in leadership and how it can affect future leaders.
Vimaladevi, M., & Thangamani, R. (2024, August). Prediction of Alzheimer's Disease by Analyzing Handwriting Dynamics Using Machine Learning Algorithms. In 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1298-1304). IEEE.
Cramarenco, R. E., Burcă-Voicu, M. I., & Dabija, D. C. (2023). The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review. Oeconomia Copernicana, 14(3), 731-767.
Manjunath, D. S., & Dean, S. S. I. M. S. (2024). The Impact of AI in Redefining Performance Appraisal System and its Significance in the Changing Workplace–A Review of Research. ISME Manag. J., 3(1), 16.
Nemțeanu, M. S., Dinu, V., Pop, R. A., & Dabija, D. C. (2022). Predicting job satisfaction and work engagement behavior in the COVID-19 pandemic: a conservation of resources theory approach. E&M Economics and Management, 25(2), 23-40.
Sucharita, K., & Roopalatha, N. (2024). Training and Development Initiatives: Catalysts for Self-Growth in the IT Sector. In ORGANIZATION, PURPOSE, AND VALUES (pp. 434-444). Routledge.
Strack, R., Kovács-Ondrejkovic, O., Baier, J., Antebi, P., Kavanagh, K., & Gobernado, A. L. (2021). Decoding global ways of working. Boston: BCG.
Anshari, M., & Hamdan, M. (2022). Understanding knowledge management and upskilling in Fourth Industrial Revolution: transformational shift and SECI model. VINE Journal of Information and Knowledge Management Systems, 52(3), 373-393.
Sucharita, K., & Roopalatha, N. (2024). Training and Development Initiatives: Catalysts for Self-Growth in the IT Sector. In ORGANIZATION, PURPOSE, AND VALUES (pp. 434-444). Routledge.
Davidescu, A. A., Hapau, R. G., & Manta, E. M. (2022). Impact of crises on capital market volatility: a bibliometric analysis.
Devaraju, S., & Boyd, T. (2021). Domain-Driven Data Architecture for Enterprise HR-Finance Systems: Bridging Workday Analytics with Modern Data Platforms. International Journal of Scientific Research in Computer Science Engineering.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and machines, 28(4), 689-707.
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.
Walter, S. (2021). The backlash against globalization. Annual Review of Political Science, 24(1), 421-442.
Na, S., Heo, S., Choi, W., Kim, C., & Whang, S. W. (2023). Artificial intelligence (AI)-Based technology adoption in the construction industry: a cross national perspective using the technology acceptance model. Buildings, 13(10), 2518.
Pronk, N. P., Whitsel, L. P., Ablah, E., Anderson III, R. E., & Imboden, M. (2025). Building a culture of healthy living in the workplace. Progress in cardiovascular diseases.
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., & Darwis, A. (2023). Exploring artificial intelligence in academic essay: higher education student's perspective. International Journal of Educational Research Open, 5, 100296.
Li, L. (2024). Reskilling and upskilling the future-ready workforce for industry 4.0 and beyond. Information systems frontiers, 26(5), 1697-1712.
Opatha, H. H. D. N. P. (2009). Human resource management. Department of HRM, University of Sri Jayewardenepura.
Skakon, J., Nielsen, K., Borg, V., & Guzman, J. (2010). Are leaders' well-being, behaviours and style associated with the affective well-being of their employees? A systematic review of three decades of research. Work & stress, 24(2), 107-139.
Khair, M. A., Mahadasa, R., Tuli, F. A., & Ande, J. R. P. K. (2020). Beyond human judgment: Exploring the impact of artificial intelligence on HR decision-making efficiency and fairness. Global Disclosure of Economics and Business, 9(2), 163-176.
Gartner, J. J., Parkhurst, M. R., Gros, A., Tran, E., Jafferji, M. S., Copeland, A., ... & Robbins, P. F. (2021). A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types. Nature cancer, 2(5), 563-574.
Safarishahrbijari, A. (2018). Workforce forecasting models: A systematic review. Journal of Forecasting, 37(7), 739-753.
Abdullah, A. A. H., & Almaqtari, F. A. (2024). The impact of artificial intelligence and Industry 4.0 on transforming accounting and auditing practices. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100218.
Chodasová, Z., Tekulová, Z., & Jacková, A. (2013). Controlling–the Current Management Tools in the Enterprise. Nierówności społeczne a wzrost gospodarczy, (31), 392-402.
Bedenik, N. O. (2015). The challenge of controlling. International Journal of Industrial Engineering and Management, 6(4), 153.
Savitha, M., & Kumar, S. P. (2025). Building an agile organizational structure to drive innovation and technology. Cuestiones de Fisioterapia, 54(2), 2321-2334.
Molnár, M., Lázár, B., Sztán, N., Végi, B., Drobnyák, Á., Buda, K., ... & Várkonyi, E. (2024). Successful formation of sperm cells from transplanted primordial germ cells in sterile interspecific avian recipients. Scientific Reports, 14(1), 24678.
Cardinal, L. B. (2001). Technological innovation in the pharmaceutical industry: The use of organizational control in managing research and development. Organization science, 12(1), 19-36.
Cardinal, S., Straka, J., & Danforth, B. N. (2010). Comprehensive phylogeny of apid bees reveals the evolutionary origins and antiquity of cleptoparasitism. Proceedings of the national Academy of Sciences, 107(37), 16207-16211.
Kirsch, L. J., Ko, D. G., & Haney, M. H. (2010). Investigating the antecedents of team-based clan control: Adding social capital as a predictor. Organization Science, 21(2), 469-489.
Sutton, P. C., Anderson, S. J., Costanza, R., & Kubiszewski, I. (2016). The ecological economics of land degradation: Impacts on ecosystem service values. Ecological Economics, 129, 182-192.
Stiglitz, J. E. (2002). Employment, social justice and societal well‐being. International Labour Review, 141(1‐2), 9-29.
Mendy, A., Percy, Z., Braun, J. M., Lanphear, B., La Guardia, M. J., Hale, R. C., ... & Chen, A. (2025). Prenatal and postnatal exposure to organophosphate esters and replacement flame retardant mixtures and childhood respiratory outcomes. Environmental research, 266, 120514.
Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial intelligence and international HRM, 172-201.
Wirtz, B. W. (2019). Digital business models (pp. 137-152). Manhattan, New York, NY: Springer International Publishing.
Torres, E. N., & Mejia, C. (2017). Asynchronous video interviews in the hospitality industry: Considerations for virtual employee selection. International Journal of Hospitality Management, 61, 4-13.
Haslinda, A. (2009). Evolving terms of human resource management and development. The journal of International social research, 2(9), 180-186.
Benbya, H., Davenport, T. H., & Pachidi, S. (2020). Artificial intelligence in organizations: Current state and future opportunities. MIS Quarterly Executive, 19(4).
Chui, M., Manyika, J., Miremadi, M., Henke, N., Chung, R., Nel, P., & Malhotra, S. (2018). Notes from the AI frontier: Insights from hundreds of use cases. McKinsey Global Institute, 2(267), 1-31.
Svergun, I., Khaustova, Y., & Svergun, M. (2025). AI-Driven Digital Transformation: Enhancing Business and Economic Sustainability Across Sectors. Digital Transformation and IT Implementation: Driving Sustainable Development Across Nations.
Karatop, B., Kubat, C., & Uygun, Ö. (2015). Talent management in manufacturing system using fuzzy logic approach. Computers & Industrial Engineering, 86, 127-136.
Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025.
Himes, D. (2025). Ethical Leadership in the Development and Integration of AI Implants for Human Enhancement (Doctoral dissertation, Alliant International University).
Zheng, J., Zhang, J. Z., Kamal, M. M., Liang, X., & Alzeiby, E. A. (2025). Unpacking human-AI interaction: Exploring unintended consequences on employee Well-being in entrepreneurial firms through an in-depth analysis. Journal of Business Research, 196, 115406.
Moghayedi, A., Michell, K., Awuzie, B., & Adama, U. J. (2024). A comprehensive analysis of the implications of artificial intelligence adoption on employee social well-being in South African facility management organizations. Journal of Corporate Real Estate, 26(3), 237-261.
Benbya, H., Strich, F., & Tamm, T. (2024). Navigating generative artificial intelligence promises and perils for knowledge and creative work. Journal of the Association for Information Systems, 25(1), 23-36
Gartner, J. J., Parkhurst, M. R., Gros, A., Tran, E., Jafferji, M. S., Copeland, A., ... & Robbins, P. F. (2021). A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types. Nature cancer, 2(5), 563-574.
Dutta, D., & Mishra, S. K. (2025). Artificial intelligence-based virtual assistant and employee engagement: an empirical investigation. Personnel Review, 54(3), 913-934.
Na, S., Heo, S., Choi, W., Kim, C., & Whang, S. W. (2023). Artificial intelligence (AI)-Based technology adoption in the construction industry: a cross national perspective using the technology acceptance model. Buildings, 13(10), 2518.
Lee, B. J. (2024). Reimagining language learning: AI-driven innovations for engagement and growth. Technology in Language Teaching & Learning, 6(3), 102773-102773.
