Cilt 13 Sayı 3 (2025): Business & Management Studies: An International Journal
Makaleler

Planlı davranış teorisi kapsamında tüketicilerin akıllı ev teknolojilerini kullanım algılarının teknoloji kabul modeli ile incelenmesi

PDF
  • Güner Çöl,
  • Yonca Nilay Baş
Güner Çöl
Dr. Öğr. Üyesi, İstanbul Üniversitesi-Cerrahpaşa, İstanbul, Türkiye
Yonca Nilay Baş
Dr. Öğr. Üyesi, İstanbul Üniversitesi-Cerrahpaşa, İstanbul, Türkiye

Yayınlanmış 25.09.2025

Anahtar Kelimeler

  • Smart Home Technologies, Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB)
  • Akıllı Ev Teknolojileri, Teknoloji Kabul Modeli (TKM), Planlı Davranış Teorisi (PDT)

Nasıl Atıf Yapılır

Planlı davranış teorisi kapsamında tüketicilerin akıllı ev teknolojilerini kullanım algılarının teknoloji kabul modeli ile incelenmesi. (2025). Business & Management Studies: An International Journal, 13(3), 1073-1089. https://doi.org/10.15295/bmij.v13i3.2602

Telif Hakkı (c) 2025 Güner Çöl- Yonca Nilay Baş

Creative Commons License

Bu çalışma Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License ile lisanslanmıştır.

Nasıl Atıf Yapılır

Planlı davranış teorisi kapsamında tüketicilerin akıllı ev teknolojilerini kullanım algılarının teknoloji kabul modeli ile incelenmesi. (2025). Business & Management Studies: An International Journal, 13(3), 1073-1089. https://doi.org/10.15295/bmij.v13i3.2602

Öz

Bu çalışmanın amacı akıllı ev teknolojilerinin kullanıcılar tarafından benimsenme sürecini Teknoloji Kabul Modeli (TKM) ve Planlı Davranış Teorisi (PDT) çerçevesinde incelemektir. Araştırmada teorik çerçeve olarak TKM ve PDT benimsenmiş; bu kapsamda tutum, öznel norm ve algılanan davranışsal kontrol gibi PDT öğeleri ile algılanan yararlılık ve algılanan kullanım kolaylığı gibi TKM öğeleri bir arada ele alınmıştır. Ayrıca araştırmada, güven, farkındalık, eğlence, kişisel yenilikçilik ve algılanan maliyet gibi faktörlerin de tutum üzerindeki etkisi incelenmiştir. Bu amaç doğrultusunda nicel araştırma yöntemi kullanılmış, 306 katılımcıyla yapılan anket ile toplanan veriler yapısal eşitlik modellemesi ile analiz edilmiştir. Analiz sonuçlarına göre kullanıcıların tutumu, algılanan davranışsal kontrolü ve öznel normu akıllı ev teknolojilerini kullanma niyetini anlamlı bir şekilde etkilemektedir. Ayrıca tutum üzerinde algılanan yararlılığın, kişisel yenilikçiliğin ve eğlence faktörünün belirleyici etkileri olduğu belirlenmiştir. Bu bulgular tutumun benimseme niyetindeki merkezi rolünü ve eğlence faktörünün önemini ortaya koymaktadır. Buna karşın algılanan kullanım kolaylığı, algılanan maliyet, farkındalık ve güven gibi dışsal faktörlerin tutum üzerinde anlamlı bir etkisi tespit edilmemiştir.

PDF

Referanslar

  1. Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, 9(2), 204-215.
  2. Ajzen, I. (1991). The theory of planned behavior. Organisational behavior and human decision processes, 50(2), 179-211.
  3. Alam, M. R., Reaz, M. B. I., & Ali, M. A. M. (2012). A review of smart homes—Past, present, and future. IEEE transactions on systems, man, and cybernetics, part C (applications and reviews), 42(6), 1190-1203.
  4. Aldossari, M. Q., & Sidorova, A. (2020). Consumer acceptance of Internet of Things (IoT): Smart home context. Journal of Computer Information Systems, 60(6), 507-517.
  5. Al-Husamiyah, A., & Al-Bashayreh, M. (2022). A comprehensive acceptance model for smart home services. International Journal of Data & Network Science, 6(1).
  6. AlNahdi, T., Larabi, C., & Kayani, F. N. (2025). Behavioural Determinants of Smart Home Device Adoption: An Empirical Study in Jeddah, Saudi Arabia. Decision Making: Applications in Management and Engineering, 295-305.
  7. Aybek, E. C., & Toraman, C. (2022). How many response categories are sufficient for Likert type scales? An empirical study based on the Item Response Theory. International Journal of Assessment Tools in Education, 9(2), 534-547.
  8. Balta-Ozkan, N., Davidson, R., Bicket, M., & Whitmarsh, L. (2013). Social barriers to the adoption of smart homes. Energy policy, 63, 363-374.
  9. Basarir-Ozel, B., Turker, H. B., & Nasir, V. A. (2022). Identifying the key drivers and barriers of smart home adoption: A thematic analysis from the business perspective. Sustainability, 14(15), 9053.
  10. Becks, E., Zdankin, P., Matkovic, V., & Weis, T. (2023). Complexity of smart home setups: a qualitative user study on smart home assistance and implications on technical requirements. Technologies, 11(1),9.
  11. Cohen, J. (1988), Statistical Power Analysis for the Behavioral Sciences, Lawrence Erlbaum, Mahwah, NJ.
  12. Davis, F. (1989) Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340. https://doi.org/10.2307/249008
  13. Etemad-Sajadi, R., & Gomes Dos Santos, G. (2019). Senior citizens' acceptance of connected health technologies in their homes. International journal of health care quality assurance, 32(8), 1162-1174.
  14. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
  15. Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), pp. 382- 388
  16. Gøthesen, S., Haddara, M., & Kumar, K. N. (2023). Empowering homes with intelligence: An investigation of smart home technology adoption and usage. Internet of Things, 24, 100944.
  17. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis. Upper Saddle River, NJ: Pearson Prentice Hall.
  18. Hair, J. F., Sarstedt, M., Hopkins, L., & G Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) an emerging tool in business research. European business review, 26(2), 106-121.
  19. Hair, J.F., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2017) A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd Edition, Sage Publications Inc., Thousand Oaks, CA.
  20. Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., Ray, & S. (2021). Evaluation of the Structural Model. In: Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Classroom Companion: Business. Springer, Cham. https://doi.org/10.1007/978-3-030-80519-7_6
  21. Hinkin, T. R. (1995). A review of scale development in the study of behavior in organisations. Journal of management, 21(5), 967-988.
  22. Hong, A., Nam, C., & Kim, S. (2020). What will be the possible barriers to consumers' adoption of smart home services?. Telecommunications Policy, 44(2), 101867.
  23. Jaspers, E. D., & Pearson, E. (2022). Consumers' acceptance of domestic Internet-of-Things: The role of trust and privacy concerns. Journal of Business Research, 142, 255-265.
  24. Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for information systems, 12(1), 50.
  25. Li, Y., & Wang, C. (2022). Effect of customer's perception on service robot acceptance. International Journal of Consumer Studies, 46(4), 1241-1261.
  26. Li, W., Yigitcanlar, T., Erol, I., & Liu, A. (2021). Motivations, barriers and risks of smart home adoption: From systematic literature review to conceptual framework. Energy Research & Social Science, 80, 102211.
  27. Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019). Cognitive dissonance in technology adoption: A study of smart home users. Information Systems Frontiers, 25(3), 1101-1123.
  28. Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.
  29. Mocrii, D., Chen, Y., & Musilek, P. (2018). IoT-based smart homes: A review of system architecture, software, communications, privacy and security. Internet of Things, 1, 81-98.
  30. Neumann, N. (2018). The acceptance of smart home technology (Bachelor's thesis, University of Twente).
  31. Nikou, S. (2019). Factors driving the adoption of smart home technology: An empirical assessment. Telematics and Informatics, 45, 101283.
  32. Park, E., Cho, Y., Han, J., & Kwon, S. J. (2017). Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, 4(6), 2342-2350.
  33. Park, E., Kim, S., Kim, Y., & Kwon, S. J. (2018). Smart home services as the next mainstream of the ICT industry: determinants of the adoption of smart home services. Universal Access in the Information Society, 17, 175-190.
  34. Ringle, C. M., Wende, S. & Becker, J.-M. (2022), SmartPLS 4. Boenningstedt: SmartPLS. Retrieved from https://www.smartpls.com.
  35. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial Least Squares Structural Equation Modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of Market Research (pp. 1-40). Springer. https://doi.org/10.1007/978-3-319-05542-8_15-1
  36. Shuhaiber, A., & Mashal, I. (2019). Understanding users' acceptance of smart homes. Technology in society, 58, 101110.
  37. Sönmez Çakır, F. (2019). Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesi (PLS-SEM) ve Bir Uygulama. Sosyal Araştırmalar ve Davranış Bilimleri Dergisi, 2019, Cilt 5, Sayı 9, s. 111-128.
  38. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information systems research, 6(2), 144-176.
  39. Tokgöz, N., & Yıldız, E. (2022). Organik gıda tüketim davranışlarının ortoreksiya nervoza eğilimi üzerindeki etkileri. Çağ Üniversitesi Sosyal Bilimler Dergisi, 19(1), 1-14.
  40. Valencia-Arias, A., Cardona-Acevedo, S., Gomez-Molina, S., Gonzalez-Ruiz, J. D., & Valencia, J. (2023). Smart home adoption factors: A systematic literature review and research agenda. Plos one, 18(10), e0292558.
  41. Verkijika, S. F., & De Wet, L. (2018). E-government adoption in sub-Saharan Africa. Electronic Commerce Research and Applications, 30, 83-93.
  42. Wilson, C., Hargreaves, T., & Hauxwell-Baldwin, R. (2017). Benefits and risks of smart home technologies. Energy policy, 103, 72-83.
  43. Xu, H., Teo, H. H., Tan, B. C., & Agarwal, R. (2009). The role of push-pull technology in privacy calculus: the case of location-based services. Journal of management information systems, 26(3), 135-174.
  44. Yang, H., Lee, H., & Zo, H. (2017). User acceptance of smart home services: an extension of the theory of planned behavior. Industrial Management & Data Systems, 117(1), 68-89.
  45. Yıldız, E., & Bozoklu, Ç. P. (2019). Bilgi Toplama ile Reklam Şüpheciliği Arasındaki İlişki: Yetkisiz İkincil Bilgi Kullanımı ve Ürün Kalitesinin Seri Aracılık Rolü. Journal of Yasar University, 14 (Special Issue on Business and Organization Research November 2019), 34-45.
  46. Yıldız, E. (2023). Markaya Bağlı Müşteri Marka Evangelisti Olur Mu?. Türkiye Mesleki ve Sosyal Bilimler Dergisi, (11), 25-38.
  47. Zeng, E., Mare, S., & Roesner, F. (2017). End user security and privacy concerns with smart homes. In thirteenth symposium on usable privacy and security (SOUPS 2017) (pp. 65-80).
  48. Zhang, X., Liu, S., Wang, L., Zhang, Y., & Wang, J. (2020). Mobile health service adoption in China: integration of theory of planned behavior, protection motivation theory and personal health differences. Online Information Review, 44(1), 1-23.
  49. Zhang, W., & Luo, B. (2023). Predicting consumer intention toward eco-friendly smart home services: extending the theory of planned behavior. Economic Change and Restructuring, 56(5), 3335-3352.
  50. Zharova, A., & Lee, H. E. (2022). Understanding User Perception and Intention to Use Smart Homes for Energy Efficiency: A Survey. arXiv preprint arXiv:2212.05019.