6. Conclusion
6.3 Recommendations for future research
The study's major limitations were highlighted in the previous section. This section expands on these by offering specific suggestions for further research. To begin with, the conceptual model used in this study might be evaluated on a different sample to confirm the study's predictions and findings. Furthermore, by narrowing the scope of direct and indirect relations with AI, such as by performing a case study, the conceptual model might be evaluated in a completely new situation.
Furthermore, the conceptual model should be broadened to incorporate additional potential determinants in order to explore how AI capabilities affect employee performance. Because no relationship was discovered in this study between the moderating effect of the relation of AI on the relationship between AI capabilities and employee engagement and AI capabilities and employee performance, more research on this variable is needed to clarify its assumed influence.
Finally, because culture is a key feature of emerging technologies, but it encompasses more than just employee engagement, more study into other aspects of the idea of culture is recommended.
To the author's knowledge, the exact link between AI capabilities and a favorable impact on overall company culture has yet to be statistically studied.
58
References
Accenture. (2019). AI: Built to Scale from experimental to exponential. Accenture built to scale.
Retrieved January 25, 2022, from https://www.accenture.com/_acnmedia/Thought-Leadership-Assets/PDF-2/Accenture-Built-to-Scale-PDF-Report.pdf#zoom=50
Ahmed, U., Umrani, W. A., Zaman, U., Rajput, S. M., & Aziz, T. (2020). Corporate entrepreneurship and business performance: The mediating role of employee engagement. SAGE Open, 10(4), 2158244020962779.
Alonso, O. (2015). Challenges with label quality for supervised learning. Journal of Data and Information Quality (JDIQ), 6(1), 1-3.
AlSheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. In PACIS (p. 37).
Alsheiabni, S., Cheung, Y., & Messom, C. (2019). Towards an artificial intelligence maturity model: from science fiction to business facts.
Bailey, C., Madden, A., Alfes, K., & Fletcher, L. (2017). The meaning, antecedents and outcomes of employee engagement: A narrative synthesis. International Journal of Management Reviews, 19(1), 31-53.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management, 17(1), 99-120.
Bayless, S., Kodirov, N., Iqbal, S. M., Beschastnikh, I., Hoos, H. H., & Hu, A. J. (2020). Scalable constraint-based virtual data center allocation. Artificial Intelligence, 278, 103196.
Besson, P., & Rowe, F. (2012). Strategizing information systems-enabled organizational transformation: A transdisciplinary review and new directions. The Journal of Strategic Information Systems, 21(2), 103-124.
Borges, A. F., Laurindo, F. J., Spínola, M. M., Gonçalves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57, 102225.
Brenyah, R. S., & Obuobisa-Darko, T. (2017). Organisational culture and employee engagement within the Ghanaian public sector. Review of Public Administration and Management, 5(03).
Brock, J. K. U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61(4), 110-134.
Burgess, A. (2018). The executive guide to artificial intelligence. Palgrave.
Bush, T. (2012). Authenticity in research: Reliability, validity and triangulation. Research methods in educational leadership and management, 75-89.
Cao, L. (2021). Artificial intelligence in retail: applications and value creation logics. International Journal of Retail & Distribution Management.
Candelon, F. & Chu, M., & Min Ha, S. (2021). A.I. won’t break your company’s culture—and it might even boost morale. Commentary Artificial Intelligence. Retrieved March 24, 2022, from https://fortune.com/2021/11/05/ai-artificial-intelligence-workplace-culture-collaboration-employee-morale-bcg/
Catteeuw, F., Flynn, E., & Vonderhorst, J. (2007). Employee engagement: Boosting productivity in turbulent times. Organization development journal, 25(2), P151.
Chui, M. (2017). Artificial intelligence the next digital frontier. McKinsey and Company Global Institute, 47(3.6).
59
Cook, S. (2008). The essential guide to employee engagement: better business performance through staff satisfaction. Kogan Page Publishers.
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.
Field, A. (2013). Discovering statistics using IBM SPSS statistics. sage.
Fink, A. (2003). The Survey Handbook’, 2nd Ed., Thousand Oaks: Sage Publications.
Finlay, S. (2021). Artificial intelligence and machine learning for business: A no-nonsense guide to data driven technologies (No. 4th ed). Relativistic.
Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97(4), 62-73.
Grant, R. M. (1996, July–August). Prospering in dynamically-competitive environments:
Organizational capability as knowledge integration. Organization Science, 7, 375–387 Güngör, H. (2020). Creating value with artificial intelligence: A multi-stakeholder
perspective. Journal of Creating Value, 6(1), 72-85.
Hughes, C., Robert, L., Frady, K., & Arroyos, A. (2019). Artificial intelligence, employee engagement, fairness, and job outcomes. In Managing technology and middle-and low-skilled employees. Emerald Publishing Limited.
Jain, A., & Pandey, A. K. (2017). Multiple quality optimizations in electrical discharge drilling of mild steel sheet. Materials Today: Proceedings, 4(8), 7252-7261.
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—an interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5-20.
King, W. R., & He, J. (2005). External validity in IS survey research. Communications of the Association for Information Systems, 16(1), 45.
Kiron, D. (2017). What managers need to know about artificial intelligence. MIT sloan management review.
Kiron, D., Khodabandeh, S., Walsh, K., & Ryder, A. (2022). MIT Sloan Management Review.
Webinar How AI Spurs Employee Engagement and Innovation at Levi Strauss & Co.
Retrieved April 30, 2022, from https://sloanreview.mit.edu/video/how-al-spurs-employee-engagement-and-innovation-at-levi-strauss-co/
Kolbjørnsrud, V., Amico, R., & Thomas, R. J. (2016). How artificial intelligence will redefine management. Harvard business review, 2(1), 3-10.
Kumar, V., & Pansari, A. (2014). The construct, measurement, and impact of employee engagement: A marketing perspective. Customer Needs and Solutions, 1(1), 52-67.
Malik, N., Tripathi, S. N., Kar, A. K., & Gupta, S. (2021). Impact of artificial intelligence on employees working in industry 4.0 led organizations. International Journal of Manpower.
McCarthy, J. (2007). What is artificial intelligence.
https://kewd.pw/what_is_artificial_intelligence.pdf
McKinsey & Company. (2021). Global survey the state of AI in 2021. Our insights. Retrieved March 23, 2022, from https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/global-survey-the-state-of-ai-in-2021
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434.
60
Memon, M. A., Salleh, R., Baharom, M. N. R., & Harun, H. (2014). Person-organization fit and turnover intention: the mediating role of employee engagement. Global Business &
Management Research, 6(3).
Morgan, N. A., Slotegraaf, R. J., & Vorhies, D. W. (2009). Linking marketing capabilities with profit growth. International Journal of Research in Marketing, 26(4), 284-293.
Na-Nan, K., Chaiprasit, K., & Pukkeeree, P. (2018). Factor analysis-validated comprehensive employee job performance scale. International Journal of Quality & Reliability Management.
Nilsson, N. J. (2005). Human-level artificial intelligence? Be serious!. AI magazine, 26(4), 68-68.
Palan, S., & Schitter, C. (2018). Prolific. ac—A subject pool for online experiments. Journal of Behavioral and Experimental Finance, 17, 22-27.
Peer, E., Brandimarte, L., Samat, S., & Acquisti, A. (2017). Beyond the Turk: Alternative platforms for crowdsourcing behavioral research. Journal of Experimental Social Psychology, 70, 153-163.
PwC. (2021). What is Artificial Intelligence? Tech effect. Retrieved February 2, 2022, from https://www.pwc.com/us/en/tech-effect/ai-analytics/artificial-intelligence.html
Rachinger, M., Rauter, R., Müller, C., Vorraber, W., & Schirgi, E. (2018). Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management.
Ramachandran, K. K., Mary, A. A. S., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. R.
(2022). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings, 51, 2327-2331.
Ransbotham, S., Candelon, F., Kiron, D., Lafountain, B., & Khodabandeh, S. (2021). The cultural benefits of artificial intelligence in the enterprise. Projects. Retrieved March 24, 2022, from
https://sloanreview.mit.edu/projects/the-cultural-benefits-of-artificial-intelligence-in-the-enterprise/
Ransbotham, S., Gerbert, P., Reeves, M., Kiron, D., & Spira, M. (2018). Artificial intelligence in business gets real. MIT sloan management review, 60280.
Reijseger, G., Peeters, M. C., Taris, T. W., & Schaufeli, W. B. (2017). From motivation to activation: Why engaged workers are better performers. Journal of Business and Psychology, 32(2), 117-130.
Roscoe, J. T. (1975). Fundamental research statistics for the behavioral sciences [by] John T.
Roscoe.
Rowell-Jones, A., Howard C., (2019). 2019 CIO Survey: CIOs Have Awoken to the Importance of
AI. Gartner Research. Retrieved March, 24, 2022 from
https://www.gartner.com/en/documents/3897266
Saunders, M., Lewis, P. & Thornhill, A. (2016). Research Methods for Business Students,' Seventh Ed., Pearson Education Limited, Edinburgh Gate, Harlow, Essex CM20 2JE, England.
Shrotryia, V. K., & Dhanda, U. (2020). Exploring employee engagement using grounded theory:
experiences from the best firms in India. Vision, 24(2), 171-183.
Spector, J. M., & Ma, S. (2019). Inquiry and critical thinking skills for the next generation: from artificial intelligence back to human intelligence. Smart Learning Environments, 6(1), 1-11.
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic management journal, 18(7), 509-533.
61
Wamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal.
Wijayati, D. T., Rahman, Z., Rahman, M. F. W., Arifah, I. D. C., & Kautsar, A. (2022). A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership. International Journal of Manpower.
Wiljer, D., & Hakim, Z. (2019). Developing an artificial intelligence–enabled health care practice:
rewiring health care professions for better care. Journal of medical imaging and radiation sciences, 50(4), S8-S14.
Winter, G. (2000). A comparative discussion of the notion of validity in qualitative and quantitative research. The qualitative report, 4(3), 1-14.
62
Appendices
Appendix I – Questionnaires and sources