Yıl 2025,
Sayı: 30, 483 - 495, 29.10.2025
Bulut Dülek
,
Hamza Koçak
,
Mehmet Emin Yaşar
Kaynakça
-
Ain, N., Kaur, K., & Waheed, M. (2016). The influence of learning value on learning management system use: An extension of UTAUT2. Information Development, 32(5), 1306-1321.
-
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
-
Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2020). A systematic review of social media acceptance from the perspective of educational and information systems theories and models. Journal of Educational Computing Research, 57(8), 2085-2109.
-
Avci, I., Kocan, M., & Kirmizibiber, A. (2024). Evaluation of consumers’ use of smart robotic vacuum cleaners under extended expectation-confirmation model. Market-Tržište, 36(1), 25-42.
-
Bali, S., Suwandi, E., Chen, T. C., Lin, C. Y., & Liu, M. C. (2024). Social influence, personal views, and behavioral intention in ChatGPT Adoption. Journal of Computer Information Systems, 1-12.
-
Bilici, F. (2025). Tüketicilerin akıllı robot süpürgeleri kullanma niyeti üzerinde iyimserlik ve yenilikçiliğin rolü. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(1), 243-270.
-
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652.
-
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers' intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209- 218.
-
Christensen, H., Amato, N., Yanco, H., Mataric, M., Choset, H., Drobnis, A., . & Sukhatme, G. (2021). A roadmap for us robotics–from internet to robotics 2020 edition. Foundations and Trends® in Robotics, 8(4), 307-424.
-
Çoban, Ş., Fethi, S., Tanova, C., & Obaegbulam, O. (2024). Adoption of e-government services in the northern part of cyprus: the role of blockchain technology awareness. SAGE Open, 14(4), 21582440241292898.
-
Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205(219), 5.
-
Durukal, E. (2020) Müşterilerin mobil alışveriş davranışının utaut2 modeli ile incelenmesi. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 11(3), 870-887.
-
Erdoğan, G. (2023). Bireylerin mobil bankacılığı benimsemesini etkileyen faktörler: genişletilmiş birleşik teknoloji kabulü ve kullanımı teorisi (utaut) modeli çerçevesinde bir araştırma. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 121-142.
-
Fishbein, M., & Ajzen, I. (1975). Beliefs, attitude, intention, and behavior: An introduction to theory and research.
-
Fitrianie, S., Horsch, C., Beun, R. J., Griffioen-Both, F., & Brinkman, W. P. (2021). Factors affecting user’s behavioral intention and use of a mobile-phone-delivered cognitive behavioral therapy for insomnia: A small-scale UTAUT analysis. Journal of Medical Systems, 45, 1-18.
-
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
-
Fridayani, H. D., & Nurmandi, A. (2019). Do smart citizens make a smart city? A case study on the factors influencing citizen behavior using Lapor Sleman online-based. CosmoGov: Jurnal Ilmu Pemerintahan, 5(1), 71-100.
-
Fu, J. R., Lu, I. W., Chen, J. H., & Farn, C. K. (2020). Investigating consumers’ online social shopping intention: An information processing perspective. International Journal of Information Management, 54, 102189.
-
Hair, J.F. & R.E. Anderson & R.L. Tatham & W.C. Black (2009), Multivariate data analysis, PrenticeHall, New Jersey.
-
Hertzum, M. (2024). Inferior, yet transformative: the user experience with robotic vacuum cleaners. Interacting with Computers, 36(1), 16-29.
-
Indrawati & Marhaeni, G. A. M. M. (2015). Predicting instant messenger application adoption using a unified theory of acceptance and use of technology 2[Paper presentation]. Proceedings of the 5th International Conference on Computing and Informatics. Istanbul, Turkey.
-
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7).
-
Karaoğlan, S. (2022). Mobil alışveriş uygulamalarına yönelik davranışsal niyetin ve kullanım davranışının utaut2 modeli ile incelenmesi. Yaşar Üniversitesi E-Dergisi, 17(68), 930-948.
-
Karamete, F. (2023). From modernism to postmodernism: getting drifted by vacuuming power. Journal of Economic & Social Research (2148-1407), 10(19).
-
Lin, S. P., Hsieh, C. Y., & Ho, T. M. (2014). Innovative healthcare cloud service model. Applied Mechanics and Materials, 543, 4511-4513.
-
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the ınternet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
-
Meiranto, W., Farlyagiza, F., Faisal, F., Nur Afri Yuyetta, E., & Puspitasari, E. (2024). The mediating role of behavioral intention on factors influencing user behavior in the E-government state financial application system at the Indonesian Ministry of Finance. Cogent Business & Management, 11(1), 2373341.
-
Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model. Heliyon, 9(11).
-
Mensah, I. K., Zeng, G., & Luo, C. (2020). E-Government services adoption: an extension of the unified model of electronic government adoption. Sage Open, 10(2), 2158244020933593.
-
Morita, P. P., Sahu, K. S., & Oetomo, A. (2023). Health monitoring using smart home technologies: scoping review. JMIR mHealth and uHealth, 11, e37347.
-
Muriithi, P., Horner, D., & Pemberton, L. (2016). Factors contributing to adoption and use of information and communication technologies within research collaborations in Kenya. Information Technology for Development, 22(sup1), 84-100.
-
Oktal, Ö. (2013). Kullanıcıların bilgi sistemini kabulünü etkileyen faktörlerin UTAUT perspektifinden incelenmesi. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 31(1), 153-170.
-
Queiroz, M.M., Fosso Wamba, S., De Bourmont, M. & Telles, R., (2021). Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy. Int. J. Prod. Res. 59 (20), 6087–6103.
-
Özmen, M. M., Eylence, M., & Aksoy, B. (2024). Yapay zekâ tabanlı görüntü işleme ile akıllı robot süpürgelerde tehlike ve engel algılama. Uluslararası Sürdürülebilir Mühendislik ve Teknoloji Dergisi, 8(2), 154-163.
-
Rodrigues, I. L., Camponogara, S., Soares, S. G. A., Beck, C. L. C., & Santos, T. M. D. (2016). Difficulties and facilities in intensive care work: a nursing staff's perspective. Revista de Pesquisa: Cuidado é Fundamental Online, 8(3), 4757-4765.
-
Rogers, E.M. (2003). Diffusion of innovations. Free Press, New York.
-
Ruslim, O. O. T. S. (2023). The impact of performance expectancy, effort expectancy, habit, and price value on the behavioral intention of tokopedia users in jakarta. International Journal of Application on Economics and Business (IJAEB), 1(1). 437-445.
-
Samartha, V.; Shenoy Basthikar, S.; Hawaldar, I.T.; Spulbar, C.; Birau, R.& Filip, R.D. (2022) A study on the acceptance of mobile-banking applications in ındia—unified theory of acceptance and sustainable use of technology model (utaut). Sustainability, 14, 14506
-
Sarfaraz, J. (2017). Unified theory of acceptance and use of technology (UTAUT) model-mobile banking. Journal of Internet Banking and Commerce, 22(3), 1-20.
-
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
-
Siahaan, A., & Thiodore, J. (2022). Analysis influence of consumer behavior to purchase organic foods in Jakarta. In 6th International Conference of Food, Agriculture, and Natural Resource (IC-FANRES 2021) (pp. 57-65). Atlantis Press.
-
Sovacool, B. K., & Del Rio, D. D. F. (2020). Smart home technologies in Europe: A critical review of concepts, benefits, risks and policies. Renewable and Sustainable Energy Reviews, 120, 109663.
-
Stevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum
-
Šumak, B., Pušnik, M., Herièko, M., & Šorgo, A. (2017). Differences between prospective, existing, and former users of interactive whiteboards on external factors affecting their adoption, usage and abandonment. Comput. Hum. Behav. 72, 733–756. doi: 10.1016/j.chb.2016.09.006
-
Suwuh, J. L. A., Kindangen, P., & Saerang, R. T. (2022). The influence of korean wave, brand ambassador, and brand image on purchase intention of somethinc skincare products in manado. Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis Dan Akuntansi, 10(4), 1146-1155.
-
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
-
Terblanche, N., & Kidd, M. (2022). Adoption factors and moderating effects of age and gender that influence the intention to use a non-directive reflective coaching chatbot. Sage Open, 12(2), 21582440221096136.
-
Tor-Kadioğlu, C. (2020). Tüketicilerin akıllı robot süpürge kullanımı üzerine bir araştırma. Üçüncü Sektör Sosyal Ekonomi Dergisi, 55(4), 2515-2537.
-
Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960-991.
-
Vărzaru, A. A., Bocean, C. G., Rotea, C. C., & Budică-Iacob, A. F. (2021). Assessing antecedents of behavioral intention to use mobile technologies in e-commerce. Electronics, 10(18), 2231.
-
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478.
-
Vishnupriya R., & Lilly, J. (2022). Customers’ perception towards robotic vacuum cleaner in coımbatore city. Journal of Emerging Technologies and Innovative Research (JETIR), 9(10), 372-378.
-
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of Enterprise Information Management, 28(3), 443-488.
-
Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: Keşfedici ve doğrulayıcı faktör analizlerinin kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85.
-
Yu, Y., Fu, Q., Zhang, D., & Gu, Q. (2024). Understanding user experience with smart home products. Journal of Computer Information Systems, 1-23.
-
Yuliantie, E. (2024). The effect of performance expectancy on behavioral intention: The mediating role of satisfaction. Journal of Management and Business Insight, 2(1), 80-89.
ANALYZING PERCEPTIONS TOWARD SMART HOME DEVICES THROUGH THE UTAUT MODEL: A STUDY ON ROBOT VACUUM USERS
Yıl 2025,
Sayı: 30, 483 - 495, 29.10.2025
Bulut Dülek
,
Hamza Koçak
,
Mehmet Emin Yaşar
Öz
This study aims to investigate how users view smart home technology using the Unified Technology Acceptance and Usage Theory (UTAUT) model. In this context, a survey was conducted with 288 robot vacuum cleaner users. In the study, the effects of performance expectancy, effort expectancy, social influence and facilitating conditions on behavioral intention and usage behavior were analyzed. SPSS 25 and AMOS 26 software were used to analyze the data. The research model was tested and validated using structural equation modeling. The results showed that while facilitating factors and behavioral intention influence usage behavior, performance expectancy, effort expectancy, and social influence affect behavioral intention. The study's conclusion included recommendations and theoretical and practical implications.
Kaynakça
-
Ain, N., Kaur, K., & Waheed, M. (2016). The influence of learning value on learning management system use: An extension of UTAUT2. Information Development, 32(5), 1306-1321.
-
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
-
Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2020). A systematic review of social media acceptance from the perspective of educational and information systems theories and models. Journal of Educational Computing Research, 57(8), 2085-2109.
-
Avci, I., Kocan, M., & Kirmizibiber, A. (2024). Evaluation of consumers’ use of smart robotic vacuum cleaners under extended expectation-confirmation model. Market-Tržište, 36(1), 25-42.
-
Bali, S., Suwandi, E., Chen, T. C., Lin, C. Y., & Liu, M. C. (2024). Social influence, personal views, and behavioral intention in ChatGPT Adoption. Journal of Computer Information Systems, 1-12.
-
Bilici, F. (2025). Tüketicilerin akıllı robot süpürgeleri kullanma niyeti üzerinde iyimserlik ve yenilikçiliğin rolü. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(1), 243-270.
-
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652.
-
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers' intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209- 218.
-
Christensen, H., Amato, N., Yanco, H., Mataric, M., Choset, H., Drobnis, A., . & Sukhatme, G. (2021). A roadmap for us robotics–from internet to robotics 2020 edition. Foundations and Trends® in Robotics, 8(4), 307-424.
-
Çoban, Ş., Fethi, S., Tanova, C., & Obaegbulam, O. (2024). Adoption of e-government services in the northern part of cyprus: the role of blockchain technology awareness. SAGE Open, 14(4), 21582440241292898.
-
Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205(219), 5.
-
Durukal, E. (2020) Müşterilerin mobil alışveriş davranışının utaut2 modeli ile incelenmesi. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 11(3), 870-887.
-
Erdoğan, G. (2023). Bireylerin mobil bankacılığı benimsemesini etkileyen faktörler: genişletilmiş birleşik teknoloji kabulü ve kullanımı teorisi (utaut) modeli çerçevesinde bir araştırma. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 121-142.
-
Fishbein, M., & Ajzen, I. (1975). Beliefs, attitude, intention, and behavior: An introduction to theory and research.
-
Fitrianie, S., Horsch, C., Beun, R. J., Griffioen-Both, F., & Brinkman, W. P. (2021). Factors affecting user’s behavioral intention and use of a mobile-phone-delivered cognitive behavioral therapy for insomnia: A small-scale UTAUT analysis. Journal of Medical Systems, 45, 1-18.
-
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
-
Fridayani, H. D., & Nurmandi, A. (2019). Do smart citizens make a smart city? A case study on the factors influencing citizen behavior using Lapor Sleman online-based. CosmoGov: Jurnal Ilmu Pemerintahan, 5(1), 71-100.
-
Fu, J. R., Lu, I. W., Chen, J. H., & Farn, C. K. (2020). Investigating consumers’ online social shopping intention: An information processing perspective. International Journal of Information Management, 54, 102189.
-
Hair, J.F. & R.E. Anderson & R.L. Tatham & W.C. Black (2009), Multivariate data analysis, PrenticeHall, New Jersey.
-
Hertzum, M. (2024). Inferior, yet transformative: the user experience with robotic vacuum cleaners. Interacting with Computers, 36(1), 16-29.
-
Indrawati & Marhaeni, G. A. M. M. (2015). Predicting instant messenger application adoption using a unified theory of acceptance and use of technology 2[Paper presentation]. Proceedings of the 5th International Conference on Computing and Informatics. Istanbul, Turkey.
-
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7).
-
Karaoğlan, S. (2022). Mobil alışveriş uygulamalarına yönelik davranışsal niyetin ve kullanım davranışının utaut2 modeli ile incelenmesi. Yaşar Üniversitesi E-Dergisi, 17(68), 930-948.
-
Karamete, F. (2023). From modernism to postmodernism: getting drifted by vacuuming power. Journal of Economic & Social Research (2148-1407), 10(19).
-
Lin, S. P., Hsieh, C. Y., & Ho, T. M. (2014). Innovative healthcare cloud service model. Applied Mechanics and Materials, 543, 4511-4513.
-
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the ınternet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
-
Meiranto, W., Farlyagiza, F., Faisal, F., Nur Afri Yuyetta, E., & Puspitasari, E. (2024). The mediating role of behavioral intention on factors influencing user behavior in the E-government state financial application system at the Indonesian Ministry of Finance. Cogent Business & Management, 11(1), 2373341.
-
Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model. Heliyon, 9(11).
-
Mensah, I. K., Zeng, G., & Luo, C. (2020). E-Government services adoption: an extension of the unified model of electronic government adoption. Sage Open, 10(2), 2158244020933593.
-
Morita, P. P., Sahu, K. S., & Oetomo, A. (2023). Health monitoring using smart home technologies: scoping review. JMIR mHealth and uHealth, 11, e37347.
-
Muriithi, P., Horner, D., & Pemberton, L. (2016). Factors contributing to adoption and use of information and communication technologies within research collaborations in Kenya. Information Technology for Development, 22(sup1), 84-100.
-
Oktal, Ö. (2013). Kullanıcıların bilgi sistemini kabulünü etkileyen faktörlerin UTAUT perspektifinden incelenmesi. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 31(1), 153-170.
-
Queiroz, M.M., Fosso Wamba, S., De Bourmont, M. & Telles, R., (2021). Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy. Int. J. Prod. Res. 59 (20), 6087–6103.
-
Özmen, M. M., Eylence, M., & Aksoy, B. (2024). Yapay zekâ tabanlı görüntü işleme ile akıllı robot süpürgelerde tehlike ve engel algılama. Uluslararası Sürdürülebilir Mühendislik ve Teknoloji Dergisi, 8(2), 154-163.
-
Rodrigues, I. L., Camponogara, S., Soares, S. G. A., Beck, C. L. C., & Santos, T. M. D. (2016). Difficulties and facilities in intensive care work: a nursing staff's perspective. Revista de Pesquisa: Cuidado é Fundamental Online, 8(3), 4757-4765.
-
Rogers, E.M. (2003). Diffusion of innovations. Free Press, New York.
-
Ruslim, O. O. T. S. (2023). The impact of performance expectancy, effort expectancy, habit, and price value on the behavioral intention of tokopedia users in jakarta. International Journal of Application on Economics and Business (IJAEB), 1(1). 437-445.
-
Samartha, V.; Shenoy Basthikar, S.; Hawaldar, I.T.; Spulbar, C.; Birau, R.& Filip, R.D. (2022) A study on the acceptance of mobile-banking applications in ındia—unified theory of acceptance and sustainable use of technology model (utaut). Sustainability, 14, 14506
-
Sarfaraz, J. (2017). Unified theory of acceptance and use of technology (UTAUT) model-mobile banking. Journal of Internet Banking and Commerce, 22(3), 1-20.
-
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
-
Siahaan, A., & Thiodore, J. (2022). Analysis influence of consumer behavior to purchase organic foods in Jakarta. In 6th International Conference of Food, Agriculture, and Natural Resource (IC-FANRES 2021) (pp. 57-65). Atlantis Press.
-
Sovacool, B. K., & Del Rio, D. D. F. (2020). Smart home technologies in Europe: A critical review of concepts, benefits, risks and policies. Renewable and Sustainable Energy Reviews, 120, 109663.
-
Stevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum
-
Šumak, B., Pušnik, M., Herièko, M., & Šorgo, A. (2017). Differences between prospective, existing, and former users of interactive whiteboards on external factors affecting their adoption, usage and abandonment. Comput. Hum. Behav. 72, 733–756. doi: 10.1016/j.chb.2016.09.006
-
Suwuh, J. L. A., Kindangen, P., & Saerang, R. T. (2022). The influence of korean wave, brand ambassador, and brand image on purchase intention of somethinc skincare products in manado. Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis Dan Akuntansi, 10(4), 1146-1155.
-
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
-
Terblanche, N., & Kidd, M. (2022). Adoption factors and moderating effects of age and gender that influence the intention to use a non-directive reflective coaching chatbot. Sage Open, 12(2), 21582440221096136.
-
Tor-Kadioğlu, C. (2020). Tüketicilerin akıllı robot süpürge kullanımı üzerine bir araştırma. Üçüncü Sektör Sosyal Ekonomi Dergisi, 55(4), 2515-2537.
-
Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960-991.
-
Vărzaru, A. A., Bocean, C. G., Rotea, C. C., & Budică-Iacob, A. F. (2021). Assessing antecedents of behavioral intention to use mobile technologies in e-commerce. Electronics, 10(18), 2231.
-
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478.
-
Vishnupriya R., & Lilly, J. (2022). Customers’ perception towards robotic vacuum cleaner in coımbatore city. Journal of Emerging Technologies and Innovative Research (JETIR), 9(10), 372-378.
-
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of Enterprise Information Management, 28(3), 443-488.
-
Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: Keşfedici ve doğrulayıcı faktör analizlerinin kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85.
-
Yu, Y., Fu, Q., Zhang, D., & Gu, Q. (2024). Understanding user experience with smart home products. Journal of Computer Information Systems, 1-23.
-
Yuliantie, E. (2024). The effect of performance expectancy on behavioral intention: The mediating role of satisfaction. Journal of Management and Business Insight, 2(1), 80-89.
AKILLI EV ALETLERİNE YÖNELİK ALGILAMALARIN UTAUT MODELİ İLE ANALİZ EDİLMESİ: ROBOT SÜPÜRGE KULLANICILARI ÜZERİNE BİR ARAŞTIRMA
Yıl 2025,
Sayı: 30, 483 - 495, 29.10.2025
Bulut Dülek
,
Hamza Koçak
,
Mehmet Emin Yaşar
Öz
Bu çalışma akıllı ev teknolojilerine yönelik kullanıcı algılarını Birleşik Teknoloji Kabul ve Kullanım Teorisi (UTAUT) modeli çerçevesinde incelemeyi amaçlamaktadır. Bu bağlamda robot süpürge kullanıcısı 288 kişi ile anket uygulaması gerçekleştirilmiştir. Araştırmada performans beklentisi, çaba beklentisi, sosyal etki ve kolaylaştırıcı şartların davranışsal niyet ve kullanım davranışı üzerindeki etkisi analiz edilmiştir. Verilerin analiz edilmesinde SPSS 25 ve AMOS 26 yazılımları kullanılmıştır. Araştırma modelinin doğrulanması ve test edilmesinde yapısal eşitlik modellemesi kullanılmıştır. Elde edilen bulgular performans beklentisi, çaba beklentisi ve sosyal etkinin davranışsal niyet üzerinde, kolaylaştırıcı şartlar ve davranışsal niyetin de kullanım davranışı üzerinde etkisi olduğunu ortaya koymuştur. Çalışma teorik ve pratik çıkarımlar ve önerilere yer verilerek nihayete erdirilmiştir.
Etik Beyan
Araştırmanın yapılabilmesi için Van Yüzüncü Yıl Üniversitesi Etik Kurulu'nun 20.03.2025 tarih ve 29248 sayılı onayı alınmıştır.
Kaynakça
-
Ain, N., Kaur, K., & Waheed, M. (2016). The influence of learning value on learning management system use: An extension of UTAUT2. Information Development, 32(5), 1306-1321.
-
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
-
Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2020). A systematic review of social media acceptance from the perspective of educational and information systems theories and models. Journal of Educational Computing Research, 57(8), 2085-2109.
-
Avci, I., Kocan, M., & Kirmizibiber, A. (2024). Evaluation of consumers’ use of smart robotic vacuum cleaners under extended expectation-confirmation model. Market-Tržište, 36(1), 25-42.
-
Bali, S., Suwandi, E., Chen, T. C., Lin, C. Y., & Liu, M. C. (2024). Social influence, personal views, and behavioral intention in ChatGPT Adoption. Journal of Computer Information Systems, 1-12.
-
Bilici, F. (2025). Tüketicilerin akıllı robot süpürgeleri kullanma niyeti üzerinde iyimserlik ve yenilikçiliğin rolü. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(1), 243-270.
-
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652.
-
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers' intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209- 218.
-
Christensen, H., Amato, N., Yanco, H., Mataric, M., Choset, H., Drobnis, A., . & Sukhatme, G. (2021). A roadmap for us robotics–from internet to robotics 2020 edition. Foundations and Trends® in Robotics, 8(4), 307-424.
-
Çoban, Ş., Fethi, S., Tanova, C., & Obaegbulam, O. (2024). Adoption of e-government services in the northern part of cyprus: the role of blockchain technology awareness. SAGE Open, 14(4), 21582440241292898.
-
Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information Seeking Behavior and Technology Adoption, 205(219), 5.
-
Durukal, E. (2020) Müşterilerin mobil alışveriş davranışının utaut2 modeli ile incelenmesi. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 11(3), 870-887.
-
Erdoğan, G. (2023). Bireylerin mobil bankacılığı benimsemesini etkileyen faktörler: genişletilmiş birleşik teknoloji kabulü ve kullanımı teorisi (utaut) modeli çerçevesinde bir araştırma. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 25(1), 121-142.
-
Fishbein, M., & Ajzen, I. (1975). Beliefs, attitude, intention, and behavior: An introduction to theory and research.
-
Fitrianie, S., Horsch, C., Beun, R. J., Griffioen-Both, F., & Brinkman, W. P. (2021). Factors affecting user’s behavioral intention and use of a mobile-phone-delivered cognitive behavioral therapy for insomnia: A small-scale UTAUT analysis. Journal of Medical Systems, 45, 1-18.
-
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
-
Fridayani, H. D., & Nurmandi, A. (2019). Do smart citizens make a smart city? A case study on the factors influencing citizen behavior using Lapor Sleman online-based. CosmoGov: Jurnal Ilmu Pemerintahan, 5(1), 71-100.
-
Fu, J. R., Lu, I. W., Chen, J. H., & Farn, C. K. (2020). Investigating consumers’ online social shopping intention: An information processing perspective. International Journal of Information Management, 54, 102189.
-
Hair, J.F. & R.E. Anderson & R.L. Tatham & W.C. Black (2009), Multivariate data analysis, PrenticeHall, New Jersey.
-
Hertzum, M. (2024). Inferior, yet transformative: the user experience with robotic vacuum cleaners. Interacting with Computers, 36(1), 16-29.
-
Indrawati & Marhaeni, G. A. M. M. (2015). Predicting instant messenger application adoption using a unified theory of acceptance and use of technology 2[Paper presentation]. Proceedings of the 5th International Conference on Computing and Informatics. Istanbul, Turkey.
-
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioural intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34(7).
-
Karaoğlan, S. (2022). Mobil alışveriş uygulamalarına yönelik davranışsal niyetin ve kullanım davranışının utaut2 modeli ile incelenmesi. Yaşar Üniversitesi E-Dergisi, 17(68), 930-948.
-
Karamete, F. (2023). From modernism to postmodernism: getting drifted by vacuuming power. Journal of Economic & Social Research (2148-1407), 10(19).
-
Lin, S. P., Hsieh, C. Y., & Ho, T. M. (2014). Innovative healthcare cloud service model. Applied Mechanics and Materials, 543, 4511-4513.
-
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the ınternet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1-13.
-
Meiranto, W., Farlyagiza, F., Faisal, F., Nur Afri Yuyetta, E., & Puspitasari, E. (2024). The mediating role of behavioral intention on factors influencing user behavior in the E-government state financial application system at the Indonesian Ministry of Finance. Cogent Business & Management, 11(1), 2373341.
-
Menon, D., & Shilpa, K. (2023). “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model. Heliyon, 9(11).
-
Mensah, I. K., Zeng, G., & Luo, C. (2020). E-Government services adoption: an extension of the unified model of electronic government adoption. Sage Open, 10(2), 2158244020933593.
-
Morita, P. P., Sahu, K. S., & Oetomo, A. (2023). Health monitoring using smart home technologies: scoping review. JMIR mHealth and uHealth, 11, e37347.
-
Muriithi, P., Horner, D., & Pemberton, L. (2016). Factors contributing to adoption and use of information and communication technologies within research collaborations in Kenya. Information Technology for Development, 22(sup1), 84-100.
-
Oktal, Ö. (2013). Kullanıcıların bilgi sistemini kabulünü etkileyen faktörlerin UTAUT perspektifinden incelenmesi. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 31(1), 153-170.
-
Queiroz, M.M., Fosso Wamba, S., De Bourmont, M. & Telles, R., (2021). Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy. Int. J. Prod. Res. 59 (20), 6087–6103.
-
Özmen, M. M., Eylence, M., & Aksoy, B. (2024). Yapay zekâ tabanlı görüntü işleme ile akıllı robot süpürgelerde tehlike ve engel algılama. Uluslararası Sürdürülebilir Mühendislik ve Teknoloji Dergisi, 8(2), 154-163.
-
Rodrigues, I. L., Camponogara, S., Soares, S. G. A., Beck, C. L. C., & Santos, T. M. D. (2016). Difficulties and facilities in intensive care work: a nursing staff's perspective. Revista de Pesquisa: Cuidado é Fundamental Online, 8(3), 4757-4765.
-
Rogers, E.M. (2003). Diffusion of innovations. Free Press, New York.
-
Ruslim, O. O. T. S. (2023). The impact of performance expectancy, effort expectancy, habit, and price value on the behavioral intention of tokopedia users in jakarta. International Journal of Application on Economics and Business (IJAEB), 1(1). 437-445.
-
Samartha, V.; Shenoy Basthikar, S.; Hawaldar, I.T.; Spulbar, C.; Birau, R.& Filip, R.D. (2022) A study on the acceptance of mobile-banking applications in ındia—unified theory of acceptance and sustainable use of technology model (utaut). Sustainability, 14, 14506
-
Sarfaraz, J. (2017). Unified theory of acceptance and use of technology (UTAUT) model-mobile banking. Journal of Internet Banking and Commerce, 22(3), 1-20.
-
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
-
Siahaan, A., & Thiodore, J. (2022). Analysis influence of consumer behavior to purchase organic foods in Jakarta. In 6th International Conference of Food, Agriculture, and Natural Resource (IC-FANRES 2021) (pp. 57-65). Atlantis Press.
-
Sovacool, B. K., & Del Rio, D. D. F. (2020). Smart home technologies in Europe: A critical review of concepts, benefits, risks and policies. Renewable and Sustainable Energy Reviews, 120, 109663.
-
Stevens, J. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum
-
Šumak, B., Pušnik, M., Herièko, M., & Šorgo, A. (2017). Differences between prospective, existing, and former users of interactive whiteboards on external factors affecting their adoption, usage and abandonment. Comput. Hum. Behav. 72, 733–756. doi: 10.1016/j.chb.2016.09.006
-
Suwuh, J. L. A., Kindangen, P., & Saerang, R. T. (2022). The influence of korean wave, brand ambassador, and brand image on purchase intention of somethinc skincare products in manado. Jurnal EMBA: Jurnal Riset Ekonomi, Manajemen, Bisnis Dan Akuntansi, 10(4), 1146-1155.
-
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
-
Terblanche, N., & Kidd, M. (2022). Adoption factors and moderating effects of age and gender that influence the intention to use a non-directive reflective coaching chatbot. Sage Open, 12(2), 21582440221096136.
-
Tor-Kadioğlu, C. (2020). Tüketicilerin akıllı robot süpürge kullanımı üzerine bir araştırma. Üçüncü Sektör Sosyal Ekonomi Dergisi, 55(4), 2515-2537.
-
Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960-991.
-
Vărzaru, A. A., Bocean, C. G., Rotea, C. C., & Budică-Iacob, A. F. (2021). Assessing antecedents of behavioral intention to use mobile technologies in e-commerce. Electronics, 10(18), 2231.
-
Venkatesh, V., Morris, M. G., Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478.
-
Vishnupriya R., & Lilly, J. (2022). Customers’ perception towards robotic vacuum cleaner in coımbatore city. Journal of Emerging Technologies and Innovative Research (JETIR), 9(10), 372-378.
-
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of Enterprise Information Management, 28(3), 443-488.
-
Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: Keşfedici ve doğrulayıcı faktör analizlerinin kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85.
-
Yu, Y., Fu, Q., Zhang, D., & Gu, Q. (2024). Understanding user experience with smart home products. Journal of Computer Information Systems, 1-23.
-
Yuliantie, E. (2024). The effect of performance expectancy on behavioral intention: The mediating role of satisfaction. Journal of Management and Business Insight, 2(1), 80-89.