WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR
Sayed AbdelGhany Yasin, E., Ezzat Saad, H., Elsayed Qoura, O., Elsayed Abdelmaboud, A. (2022). WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR. EKB Journal Management System, 11(1), 349-403. doi: 10.21608/mkaf.2022.241703
ESlam Sayed AbdelGhany Yasin; Hesham Ezzat Saad; Omar Elsayed Qoura; Ashraf Elsayed Abdelmaboud. "WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR". EKB Journal Management System, 11, 1, 2022, 349-403. doi: 10.21608/mkaf.2022.241703
Sayed AbdelGhany Yasin, E., Ezzat Saad, H., Elsayed Qoura, O., Elsayed Abdelmaboud, A. (2022). 'WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR', EKB Journal Management System, 11(1), pp. 349-403. doi: 10.21608/mkaf.2022.241703
Sayed AbdelGhany Yasin, E., Ezzat Saad, H., Elsayed Qoura, O., Elsayed Abdelmaboud, A. WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR. EKB Journal Management System, 2022; 11(1): 349-403. doi: 10.21608/mkaf.2022.241703

WHEN TECHNOLOGY MEETS STAFF: THE INTERPLAY OF SERVICE AUTOMATION AND HUMAN RESOURCE PERFORMANCE IN THE EGYPTIAN HOTEL SECTOR

مجلة کلية السياحة والفنادق. جامعة المنصورة
Article 14, Volume 11, Issue 1 - Serial Number 11, June 2022, Page 349-403  XML PDF (913.36 K)
Document Type: المقالة الأصلية
DOI: 10.21608/mkaf.2022.241703
View on SCiNiTO View on SCiNiTO
Authors
ESlam Sayed AbdelGhany Yasin1; Hesham Ezzat Saad2; Omar Elsayed Qoura2; Ashraf Elsayed Abdelmaboud2
1Faculty of tourism and hotels , Fayoum University
2Faculty of tourism and hotels, Fayoum University
Abstract
Robots (R), artificial intelligence (AI), and service automation (SA) (RAISA) technologies are commonly used in the tourism and hospitality industries around the world. Although research in this area is gaining traction, it has been largely ignored in the Egyptian tourism and hospitality industries. As a result, there is a dearth of research on artificial intelligence and employee performance in the hotel industry, one of the most important fields to benefit from these technologies is employees. On the other hand, however, it poses a threat to job replacement. The purpose of this research is to explore the impact of artificial intelligence on employee performance in the hotel sector. To complete this research, data were gathered from managers and employees working in five-star hotels in greater Cairo, Egypt. while the primary data was collected through an empirical study conducted using a questionnaire strategy on a convenience sample of employees and managers in hotels. Finally, using SPSS version 25, simple linear regressions were used to check the effect. The results show that there is a correlation between artificial intelligence dimensions and employee performance dimensions. Finally, the results show that the total dimensions of artificial intelligence have a significant impact on the total dimensions of employee performance in the hotel industry. Efficiency has the greatest impact on employee performance, followed by ease of use, whereas automation has no significant impact on total employee performance dimensions. Furthermore, the researcher reveals that the hotel industry is undergoing major technological changes in Egypt Vision 2030.
Keywords
Artificial Intelligence; Employees' Performance; Hotels; greater Cairo; Egypt
References
  • Albus, J. (1983) From Washington: the robot revolution: an interview with James Albus. Communications of the ACM, 26 (3), 179-180.

  • Altemeyer, B. (2019). Making the business case for AI in HR: two case

    studies. Strategic HR Review, 18 (2), 66-70.

  • Arntz, M., Gregory, T., and Zierahn, U. (2016).The Risk of automation for jobs in OECD Countries: A Comparative Analysis, Paris, OECD Publishing.

  • Ashtiani Abdi, A., Nour mohammadian, F., Mohammadi, Y., and Saeb, M. R.

    (2019). Control over power conversion efficiency of bhj solar cells:

    learn more from less, with artificial intelligence. Progress in Color, Colorants, and Coatings, 12 (1), 1-14.

  • Autor, D.H., Levy, F., and Murnane, R.J. (2003) the skill content of recent technological change: an empirical exploration. The Quarterly Journal of Economics, 118 (4), 1279–1333.
  • Ernst, E. Merola, R. and Samaan, D. (2018) the economics of artificial intelligence: Implications for the future of work. International Labor Organization, 10 (13), 140.
  • Finn, M, Eiliott, M and Walton, M. (2000) Tourism and Leisure Research Methods Data Collection analysis and interpretation, Pearson Education, Malaysia, 2nd Edition.
  • Gray, D. E. (2013). Research in the real world. Sage.
  • Groover, M.P. (2014). Fundamentals of modern manufacturing: materials, processes, and systems. New Jersey: John Wiley & Sons.
  • Gursoy, D., Chi, O. H., Lu, L., and Nunkoo, R. (2019). Consumers' acceptance of artificially intelligent (AI) devices use in service delivery. International Journal of Information Management, 49, 157-169.

  • Hunter, J. E. (1986). Cognitive Ability, Cognitive Aptitudes, Job Knowledge, and Job

    Performance. Journal of Vocational Behaviour, 29, 340-362.

  • Jackson, P.C. (2019). Introduction to artificial intelligence. Courier DoverPublications.
  • Jen, YW, and Hung, C.M. (2010). An Empirical Study of Adopting Mobile Healthcare Service the Family’s Perspective on the Healthcare Needs of Their Elderly Members. TELEMEDICINE and eHEALTH JOURNAL, 16 (1), 41-48.
  • Jung, W. and Yim, H. (2016). Effects of mental model and Intrinsic Motivation on the behavioral intention of Smartphone Application Users. ETRI Journal, 38 (3), 589-598.
  • Lee, M.T., and Park, C. (2008). Mobile technology usage and B2B market performance under mandatory adaption. Industrial marketing management, 37 (7), 833-840.
  • Lim, S. Xue, L. Yen, C.C. Chang, L., Chan, C.H., Tai, C.B., Duh, B.H. and Choolani, M. (2011). A study on Singaporean women’s acceptance of using mobile phones to seek health information. International Journal of Medical Informatics, 80 (20), 189-202.
  • Mathis, R.L. and Jackson, J.H. (2009). Human Resource Management. Mason, OH, USA: South-Western Cengage Learning P: 324.
  • Na-Nan, K., Chaiprasit, K. and Pukkeeree, P. (2018), “Factor analysis-validated comprehensive employee job performance scale”, International Journal of Quality and Reliability Management,  Vol. 35 No. 10, pp. 2436-2449.
  • Noe, R.A. (2006). Human Resource Management: Gain a competitive advantage with the OLC card. McGraw-Hill.
  • Olsson, N.O., and Zidane, Y.J. (2017) Defining project efficiency, effectiveness, and efficacy. International Journal of Managing Projects in Business, 4 (2), 308–328.
  • Otley, D. (1999). Performance management: a framework for management control systems research. Management Accounting Research, 10, 363-382.
  • Palmer, S. and Torgerson, D. J. (2018). Definitions of efficiency. Bmj, 318 (7191), 1136.
  • Peterson, E. and Plowman, G.E. (1953), Business Organization and Management, Irwin, IL.
  • Prasanna Matsa, Kusuma Gullamajji (2019) To Study Impact of Artificial Intelligence on Human Resource Management. International Research Journal of Engineering and Technology (IRJET), Volume: 06 Issue: 08.
  • Rifkin, J. (1995). The end of work: the decline of the global labor force and the dawn of the post-market era, New York: G. P. Putnam's Sons.
  • Russell, S. J., and Norvig, P. (2016). Artificial intelligence: A modern approach. Malaysia: Pearson Education Limited
  • Samset, K. (1998). Project management in a high uncertainty situation: understanding risk and project management in international development projects, (Unpublished doctoral dissertation), Norwegian University of Science and Technology, Trondheim.
  • Sattar, A. A., Elhakeem, M., Rezaie-Balf, M., Gharabaghi, B. and Bonakdari, H. (2019). Artificial intelligence models for prediction of the aeration efficiency of the stepped weir. Flow Measurement and Instrumentation, 65, 78-89.
  • Sufian, F., Kamarudin, F., and Noor M. H.N. (2013) Assessing the revenue efficiency of domestic and foreign Islamic banks: empirical evidence from Malaysia, Journal Pengurusan, 37 (1), 77 – 90.
  • Tzafestas, S.G. (2009). Human and nature minding automation: an overview of concepts, methods, tools, and applications. Athens: Springer.
  • Wang, W., and Siau, K. (2019). Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work and Future of Humanity: A review and research agenda. Journal of Database Management (JDM), 30 (1), 61-79.
  • Weizenbaum, J. (1972). The impact of the computer on society. Norwood, NJ, USA: Ablex Publishing.
Statistics
Article View: 215
PDF Download: 183