SavedAdd your journal

Journals / İş ve İnsan Dergisi / 2026 / Cilt: 13 Sayı: 1

The Mediating Role of IoT Awareness and Artificial Intelligence Anxiety on Resistance to Organizational Change

IoT Farkındalığının Örgütsel Değişime Direnç Üzerinde Yapay Zekâ Kaygısının Aracı Rolü

Şükrü Mustafa Kaya(İSTANBUL AYDIN ÜNİVERSİTESİ)0000-0003-2710-0063
Vildan Bayram(ISTANBUL AYDIN UNIVERSITY)0000-0001-7526-6485
Pages
—
Publication Date
2026-03-27
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Findings: The results indicate that IoT awareness has a negative and significant effect on AI anxiety (β = -0.23; t = -4.19; p < 0.05).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Purpose: This study aims to examine the relationship between Internet of Things (IoT) awareness and resistance to organizational change in businesses, and to investigate the potential mediating role of artificial intelligence (AI) anxiety in this relationship.
📊
Key Findings & Data:Data were collected through a survey administered to 427 participants working in the energy sector between November 15, 2024, and December 5, 2024, using a convenience sampling method.
💡
Conclusion & Impact:Findings: The results indicate that IoT awareness has a negative and significant effect on AI anxiety (β = -0.23; t = -4.19; p < 0.05).
🔬Design:Survey & Empirical Study
📍Scope:2024 Verileri
⚙️Variables:Nesnelerin İnterneti · Değişime Direnç · Yapay Zeka

Abstract

Purpose: This study aims to examine the relationship between Internet of Things (IoT) awareness and resistance to organizational change in businesses, and to investigate the potential mediating role of artificial intelligence (AI) anxiety in this relationship. Method: The research was conducted using a quantitative research design. Data were collected through a survey administered to 427 participants working in the energy sector between November 15, 2024, and December 5, 2024, using a convenience sampling method. The collected data were analyzed using SPSS and AMOS statistical software, and structural equation modeling was employed. Findings: The results indicate that IoT awareness has a negative and significant effect on AI anxiety (β = -0.23; t = -4.19; p < 0.05). AI anxiety was found to have a positive and significant effect on resistance to organizational change (β = 0.38; t = 6.80; p < 0.05). Additionally, IoT awareness has a negative and significant effect on resistance to organizational change (β = -0.44; t = -7.94; p < 0.05). Mediation analysis revealed that AI anxiety plays a significant mediating role in the relationship between IoT awareness and resistance to organizational change (IE = -0.08; SBT = -3.33; p < 0.05). The findings demonstrate that increasing IoT awareness reduces resistance to organizational change while also contributing to a decrease in AI anxiety. Original Contribution: This study contributes to the literature by examining the relationships among IoT awareness, AI anxiety, and resistance to organizational change within an integrated conceptual framework. By revealing the mediating role of AI anxiety, the study highlights the importance of human and psychological factors in the adoption of IoT technologies and digital transformation processes within organizations.

Özet

Amaç: Bu çalışmanın amacı, işletmelerde Nesnelerin İnterneti (IoT) farkındalığının örgütsel değişime direnç üzerindeki etkisini incelemek ve bu ilişkide yapay zekâ (YZ) kaygısının olası aracılık rolünü ortaya koymaktır. Yöntem: Araştırma, nicel araştırma yaklaşımı çerçevesinde gerçekleştirilmiştir. Veri toplama sürecinde enerji sektöründe faaliyet gösteren çalışanlardan kolayda örnekleme yöntemiyle 15.11.2024–05.12.2024 tarihleri arasında 427 katılımcıya anket uygulanmıştır. Elde edilen verilerin analizinde SPSS ve AMOS istatistik paket programları kullanılmış ve yapısal eşitlik modellemesi uygulanmıştır. Bulgular: Analiz sonuçları, IoT farkındalığının yapay zekâ kaygısı üzerinde negatif yönlü ve anlamlı bir etkisinin olduğunu göstermektedir (β = -0,23; t = -4,19; p < 0,05). Yapay zekâ kaygısının örgütsel değişime direnç üzerinde pozitif yönlü ve anlamlı bir etkisi olduğu tespit edilmiştir (β = 0,38; t = 6,80; p < 0,05). Ayrıca IoT farkındalığının örgütsel değişime direnç üzerinde negatif yönlü ve anlamlı bir etkisinin bulunduğu belirlenmiştir (β = -0,44; t = -7,94; p < 0,05). Yapılan aracılık analizi sonuçları, IoT farkındalığı ile örgütsel değişime direnç arasındaki ilişkide yapay zekâ kaygısının anlamlı bir aracılık rolü üstlendiğini göstermektedir (IE = -0,08; SBT = -3,33; p < 0,05). Bulgular, IoT farkındalığının örgütsel değişime direnci azalttığını ve bu etkinin aynı zamanda yapay zekâ kaygısının azalmasına katkı sağladığını ortaya koymaktadır. Özgün Katkı: Bu çalışma, IoT farkındalığı, yapay zekâ kaygısı ve örgütsel değişime direnç arasındaki ilişkileri bütüncül bir model çerçevesinde inceleyerek literatüre katkı sunmaktadır. Özellikle yapay zekâ kaygısının aracılık rolünün ortaya konulması, işletmelerin dijital dönüşüm ve IoT teknolojilerinin benimsenmesi süreçlerinde insan faktörünün önemini vurgulayan önemli bulgular sağlamaktadır.

🔖

Cite This Article

Kaya, Ş. M., Bayram, V. (2026). The Mediating Role of IoT Awareness and Artificial Intelligence Anxiety on Resistance to Organizational Change. İş ve İnsan Dergisi, Cilt: 13 Sayı: 1. https://doi.org/10.18394/iid.1697899

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (62)

  1. Al-Fuqaha A., Guizani M., Mohammadi M., Aledhari M., Ayyash M. (2015). Internet of things: a survey on enabling technologies, protocols and applications, IEEE Communications Surveys & Tutorials, Page(s): 2347–2376, E-ISSN: 1553-877X https://doi.org/10.1109/COMST.2015.2444095.
  2. Alsharari, N. M. (2024). The interplay of strategic management accounting, business strategy and organizational change: as influenced by a configurational theory. Journal of Accounting & Organizational Change, 20(1), 153-176. https://doi.org/10.1108/JAOC-09-2021-0130
  3. Atzori, L., Iera, A., & Morabito, G. (2010). The ınternet of things: a survey. Computer networks, 54(15), 2787-2805. https://doi.org/10.1016/j.comnet.2010.05.010
  4. Balaman, F. & Baş, M. (2021). Örgütsel değişime direnç ölçeği’nin Türkçe’ye uyarlanması: geçerlik- güvenirlik çalışması. Cumhuriyet Uluslararası Eğitim Dergisi, 10 (2), 676-697. https://doi.org/10.30703/cije.751810
  5. Bausch, D., Kraemer, T., & Mauroner, O. (2024). Technology-induced stress and employee resistance in the context of digital transformation and identification of countermeasures. International Journal of Innovation and Technology Management, 21(04), 2450029. https://doi.org/10.1142/S0219877024500299
  6. Bayram V, Kaya Ş. M. (2023). The contributions of metaverse technology on management ınformation systems in strategic planning and decision-making processes of businesses, Uluslararası Yönetim Akademisi Dergisi, 6(3),794-807, https://doi.org/10.33712/mana.1326478
  7. Bayram, V. & Kaya, Ş. M. (2024a). İşletmelerde açık inovasyon kavramının yapay zekâ ve IoT teknolojisi ile ilişkisinin sektörel bazda incelenmesi. Uluslararası Akademik Birikim Dergisi, 7(5), 977-992. https://doi.org/10.5281/zenodo.14583465
  8. Bayram, V., & Kaya, Ş. M. (2024b). İşletmelerde nesnelerin interneti (IoT) farkındalık ölçeği geliştirme çalışması. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 9(24), 447-465. https://doi.org/10.25204/iktisad.1434292
  9. Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. In the Cambridge Handbook of Artificial Intelligence Cambridge University Press. https://doi.org/10.1017/CBO9781139046855.020
  10. Butt, A., Imran, F., Helo, P., & Kantola, J. (2024). Strategic design of culture for digital transformation. Long Range Planning, 57(2), 102415. https://doi.org/10.1016/j.lrp.2024.102415
  11. Bühler, J. L., Orth, U., Bleidorn, W., Weber, E., Kretzschmar, A., Scheling, L., & Hopwood, C. J. (2024). Life events and personality change: A systematic review and meta-analysis. European Journal of Personality, 38(3), 544-568. https://doi.org/10.1177/08902070231190219
  12. Büyüköztürk, Ş. (2011). Sosyal bilimler için veri analizi el kitabı. 14. Baskı, Ankara: PEGEM Akademi.
  13. Castro, C. A., Zambaldi, F., & Ponchio, M. C. (2020). Cognitive and emotional resistance to innovations: concept and measurement. Journal of Product & Brand Management, 29(4), 441-455. https://doi.org/10.1108/JPBM-10-2018-2092
  14. Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2020). Cutof criteria for overall model ft indexes in generalized structured component analysis. Journal of Marketing Analytics, 8, 189-202.
  15. Choi, M., & Ruona, W. E. A. (2011). Individual readiness for organizational change and its implications for human resource and organization development. Human Resource Development Review, 10(1), 46–73. https://doi.org/10.1177/1534484310384957
  16. Çokluk, Ö., Şekercioğlu, G. ve Büyüköztürk, Ş. (2010). Sosyal Bilimler İçin Çok Değişkenli İstatistik. PEGEM Yayınları. Ankara.
  17. Dar, N., Ahmad, S., Badar, K., & Kundi, Y. M. (2024). Unraveling the link between innovative work behavior and despotic leadership: the roles of supervisor conflict and dispositional resistance to change trait. International Journal of Conflict Management., 35(4), 816-834. https://doi.org/10.1108/IJCMA-09-2023-0180
  18. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  19. De Clercq, D., Dayan, M., & Ng, P. Y. (2024). When performance demands enable change: how employees can overcome emotional dissonance and organizational underappreciation. European Management Journal, 42(4), 565-575. https://doi.org/10.1016/j.emj.2023.02.004
  20. Esmaili Jobani, A., & Kaya, Ş. M. (2025). Hybrid IoT and AI-based Solution for Energy Management in Data Centres under Various Climate Conditions. Anadolu Bil Meslek Yüksekokulu Dergisi, 20(72), 107-124. https://izlik.org/JA98XW23JN
  21. Fast, E., & Horvitz, E. (2017). Long-term trends in the public perception of artificial intelligence. Proceedings of the thirty-first aaaı conference on artificial ıntelligence (pp. 963-969). https://doi.org/10.1609/aaai.v31i1.10635
  22. Frey, C. B., & Osborne, M. A. (2017). The future of employment: how susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019
  23. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). ınternet of things (ıot): a vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-1660. https://doi.org/10.1016/j.future.2013.01.010
  24. Gursoy, D., Chi, C. G., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157–169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008
  25. Haenlein, M., Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Rreview, 61(4), 5-14. https://doi.org/10.1177/0008125619864925
  26. Hagl, C., Kanitz, R., Gonzalez, K., & Hoegl, M. (2024). Change management interventions: taking stock and moving forward. Human Resource Management Review, 34(1), 101000.
  27. Hall, A. K., Oswald, A., Frank, J. R., Dalseg, T., Cheung, W. J., Cooke, L.,. & Van Melle, E. (2024). Evaluating competence by design as a large system change initiative: readiness, fidelity, and outcomes. Perspectives on Medical Education, 13(1), 95-107. https://doi.org/10.5334/pme.962
  28. Heilmann, P. (2007). High level competence: a tool for coping with organizational change. Journal of european ındustrial training, 31(9), 727-741. https://doi.org/10.1108/03090590710846684
  29. Hornstein, H. A. (2015). The integration of project management and organizational change management is now a necessity. International Journal of Project Management, 33(2), 291–298. https://doi.org/10.1016/j.ijproman.2014.08.005
  30. İşler, B., Kaya, Ş. M., & Kılıç, F. R. (2025). Fog-Enabled Machine Learning Approaches for Weather Prediction in IoT Systems: A Case Study. Sensors, 25(13), 4070. https://doi.org/10.3390/s25134070
  31. Kartal E., (2021). Machine learning and artificial ıntelligence, tıp bilişimi, 18. Bölüm, İstanbul Üniversitesi, Enformatik Bölümü, İstanbul, Türkiye, https://10.26650/B/ET07.2021.003.18
  32. Kaya, Ş.M., Erdem, A., & Güneş, A. (2021). A smart data preprocessing approach to effective management of big health data in IoT edge, Smart Homecare Technology and TeleHealth, 9-21, Volume 8:9-21 https://doi.org/10.2147/SHTT.S313666
  33. Kaya, Ş.M., Erdem, A., & Güneş, A. (2022). Anomaly detection and performance analysis by using big data filtering techniques for healthcare on IoT edges. Sakarya University Journal of Science, 26(1), 1-13, https://doi.org/10.16984/saufenbilder.903915
  34. Kaya, Ş.M., İşler, B.; Abu-Mahfouz, A.M.; Rasheed, J. & AlShammari, A. (2023). An intelligent anomaly detection approach for accurate and reliable weather forecasting at IoT Edges: A case study. Sensors, 23, 2426. https://doi.org/10.3390/s23052426
  35. Kaya, Ş.M., Bayram, V. & Özkan, M. (2025) Evaluation of the intergenerational relationship of IoT awareness in businesses, Journal of Information and Optimization Sciences, 46:5, 1753–1772, DOI: 10.47974/JIOS-1971
  36. Kim, B. J., & Lee, D. G. (2025). Self-efficacy in using artificial intelligence as a shield: mitigating the detrimental effects of organizationally prescribed perfectionism on employee stress and anxiety. Current Psychology, 44(3), 1805-1831.
  37. Kotter, J. P., Akhtar, V., & Gupta, G. (2025). Change: how organizations achieve hard-to-imagine results in uncertain and volatile times. John Wiley & Sons. ISBN: 978-1-119-81584-6
  38. López, D., & González, R. (2020). Artificial intelligence anxiety: Understanding the role of emotions in the adoption of AI technologies. Journal of Technology and Society, 32(1), 45-56. https://doi.org/10.1016/j.jts.2020.02.004
  39. Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature review. Journal of Computer and Communications, 3(5), 164–173. https://doi.org/10.4236/jcc.2015.35021
  40. Manyika, J., Chui, M., Bisson, P., Woetzel, J., Dobbs, R., Bughin, J., & Aharon, D. (2021). Unlocking the potential of the ınternet of things. McKinsey Global Institute.
  41. Marjani M., Nasaruddin F., Gani A., Karım A., Hashem I.A. T., Sıddıqa A., Yaqoob I., (2017). Big IoT data analytics: Architecture, Opportunities, and Open Research Challenges, Journal IEEE Access, Volume5, Pages (from-to)5247-5261, pages15, https://doi.org/10.1109/access.2017.2689040
  42. Mattos, C. S., Pellegrini, G., Hagelaar, G., & Dolfsma, W. (2024). Systematic literature review on technological transformation in smes: a transformation encompassing technology assimilation and business model innovation. management review quarterly, 74(2), 1057-1095. https://doi.org/10.1007/s11301-023-00327-7
  43. Miorandi, D., Sicari, S., De Pellegrini, F., & Chlamtac, I. (2012). Internet of Things: Vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497-1516. https://doi.org/10.1016/j.adhoc.2012.02.016
  44. Nabiyev. V.V., (2016). Yapay zekâ: insan-bilgisayar etkileşimi, Seçkin Yayıncılık San. ve Tic.A.Ş.
  45. Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of Applied Psychology, 88(4), 680–693. https://doi.org/10.1037/0021-90-10.88.4.680
  46. Oreg, S. (2006). Personality, context, and resistance to organizational change. European Journal of Work and Organizational Psychology, 15(1), 73–101. https://doi.org/10.1080/13594320500451247
  47. Okutucu, H., & Kaya, Ş. M. (2025). Traffic Density Estimation with IoT Edge Computing In Smart City: A Case Study. Anadolu Bil Meslek Yüksekokulu Dergisi, 20(72), 189-215. https://izlik.org/JA63AK93HX
  48. Pektaş, T. (2024). The impact of artificial intelligence anxiety on employees: a comprehensive review of psychological and organizational dynamics. Int J Educ Technol Sci Res, 9(26), 194-206. https://doi.org/10.35826/ijetsar.733.
  49. Qin, W. (2024). How to unleash frugal innovation through internet of things and artificial intelligence: Moderating role of entrepreneurial knowledge and future challenges. Technological Forecasting and Social Change, 202, 123286. https://doi.org/10.1016/j.techfore.2024.123286
  50. Rafferty, A. E., & Griffin, M. A. (2006). Perceptions of organizational change: A stress and coping perspective. Journal of Applied Psychology, 91(5), 1154–1162. https://doi.org/10.1037/0021-9010.91.5.1154
  51. Riggins, F. J., & Wamba, S. F. (2015). Research directions on the adoption, usage, and impact of the Internet of Things through the use of big data analytics. Journal of Business Analytics, 1(1), 1-10. https://10.1109/HICSS.2015.186
  52. Rolls, J. (2024). The transformational leader: The wellspring of the learning organization. In Learning organizations (pp. 101-110). Productivity Press.
  53. Russell, S., & Norvig, P. (2010). Artificial intelligence: A modern approach (3rd ed.)., Prentice Hall, 2010, ISBN:0136042597, 9780136042594, S.S.: 1132
  54. Saeed, I., Khan, J., Zada, M., & Zada, S. (2024). Employee sensemaking in organizational change via knowledge management: leadership role as a moderator. Current Psychology, 43(7), 6657-6671. https://doi.org/10.1007/s12144-023-04849-x
  55. Saleh Z.M. (2019), Artificial intelligence definition, ethics and standards, the British Universty in Egypt, Electronics and Communications: Law, Standards and Practice | 18ELEC07I
  56. Santos de Souza, F. D. O., & Chimenti, P. (2024). Emotions in organizational change: an ıntegrative review. Journal of Change Management, 24(2), 137-176. https://doi.org/10.1080/14697017.2024.2345078
  57. Schumacker, R. E., & Lomax, R. G. (2010). A beginner’s guide to structural equation modeling (3rd eds). Routledge Taylor & Francis Group, New York-London.
  58. Sinha, R. (2024). Internet of Things technology skills enhancement in the digital era: absorptive capacity driven solutions. Journal of Information Technology, 39(1), 44-61.
  59. Stevens, J. P. (2012). Applied multivariate statistics for the social sciences (5th eds.). Taylor & Francis, London.
  60. Turgut Z., (2018). Mobility management for the internet of things. PhD thesis. Istanbul University Institute of Science and Technology, Department of Computer Engineering, Computer Engineering Programme, İstanbul.
  61. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
  62. Hall, A. K., Oswald, A., Frank, J. R., Dalseg, T., Cheung, W. J., Cooke, L.,. & Van Melle, E. (2024). Evaluating competence by design as a large system change initiative: readiness, fidelity, and outcomes. Perspectives on Medical Education, 13(1), 95-107. https://doi.org/10.5334/pme.962