Beklenti Onay Modeli Kapsamında Tüketicilerin Çevrimiçi Ev Aletleri Kullanmaya Devam Etme Niyetlerini Etkileyen Faktörler

Year 2022, Volume: 7 Issue: 2, 483 - 495, 30.12.2022

Nur Çağlar Çetinkaya , Cihat Kartal

Abstract

Teknolojik gelişmelerle birlikte satın alma davranışları önemli değişikliklere uğrayan tüketiciler, hayatlarını kolaylaştıran ürünleri tercih etmektedirler. İnternet donanımlı nesnelerin insan hayatındaki önemi giderek artmaktadır. Elektronik cihaz, bilgisayar ve internetin birleşmesi ile ortaya çıkan çevrimiçi nesnelerden biri olan robot süpürgeler bu araştırmanın çalışma alanını oluşturmaktadır. Robot teknolojilerinin en az kullanıldığı alanlar olan evlerde robot süpürgelerin kullanımında gözlenen artış araştırmayı gerekli kılmaktadır. Yapılan analizler sonucunda ürün deneyiminin sonucu olan olumlu onayın algılanan fayda ve memnuniyet üzerinde olumlu etkisi olduğu tespit edilmiştir. Ayrıca algılanan faydanın memnuniyet ve devam etme niyeti üzerinde pozitif etkiye sahip olduğu, hedonik faydanın tatmin ve devam etme niyeti üzerinde pozitif etkiye sahip olduğu ve alışkanlık ve tatminin devam etme niyeti üzerinde pozitif etkiye sahip olduğu bulunmuştur.

Keywords

Çevrimiçi nesneler, Kullanmaya devam etme niyeti, Beklenti doğrulama teorisi

Factors Affecting Consumers' Continuance Intention Online Home Appliances Under The Expectation Confirmation Model

Abstract

Consumers, whose purchasing behaviors have under gone significant changes with the technological developments, prefer products that make their lives easier. The importance of internet-equipped objects is increasing in human life. Robot vacuums, one of the online objects that emerged with the combination of electronic device, computer and internet, constitute the field of study of this research. The increase observed in the use of service robots in homes, which are the most minimal areas where robot technologies are used, necessitates research. As a result of the analyzes, it was found that the positive confirmation, which is the result of product experience, has a positive effect on perceived usefulness and satisfaction. In addition, it was found that perceived usefulness had a positive effect on satisfaction and continuance intention, hedonic benefit had a positive effect on satisfaction and continuance intention, and habit and satisfaction had a positive effect on continuance intention.

Keywords

online objects, continuance intention, expectation confirmation theory, Çevrimiçi nesneler, Kullanmaya devam etme niyeti, Beklenti doğrulama teorisi

References

• Agrebi, S. & Jallais, J. (2015). Explain The Intention to Use Smart Phones for Mobile Shopping. Journal of Retailing and Consumer Services, 22, 16-23.
• Alraimi, K.M., Zo, H. & Ciganek, A.P. (2015). Understanding the MOOCs Continuance: The Role of Openness and Reputation. Computers & Education, 80, 28-38.
• Amoroso, D. & Lim, R. (2017). The Mediating Effects of Habit on Continuance Intention. International Journal of Information Management, 37(6), 693–702.
• Anderson, E. W. & Sullivan, M. W. (1993). The Antecedents and Consequences of Customer Satisfaction for Firms. Marketing Science, 12(2), 125-143.
• Arıkan, R. (2018). Anket Yöntemi Üzerinde Bir Değerlendirme, Haliç Üniversitesi Sosyal Bilimler Dergisi, 1, 97-159.
• Ayanso, A., Herath, T.C. & O’Brien, N. (2015). Understanding Continuance Intentions of Physicians with Electronic Medical Records (EMR): An Expectancy-Confirmation Perspective. Decision Support Systems, 77,112-122.
• Bae, M. (2018). Understanding the Effect of the Discrepancy Between Sought and Obtained Gratification on Social Networking Site Users’ Satisfaction and Continuance Intention. Computers in Human Behavior, 79, 137-153.
• Bargh, J.A. (1996). Automaticity in Social Psychology, in: E.T. Higgins. A.W. Kruglanski (Eds.), Social Psychology: Handbook of Basic Principles, New York: Guilford Press.
• Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351-370.
• Biemer, P. P. & Lyberg, L. E. (2003). Introduction to Survey Quality, Wiley.
• Blyth, B. (2008). Mixed Mode: The Only‘Fitness’Regime? International Journal of Market Research, 50, 241–266.
• Bolen, M. C., Ozen, U. & Karaman, E. (2017). Mobil Alışveriş Bağlamında Sürekli Kullanım Niyetinin İncelenmesi: İki Kuramsal Modelin Karşılaştırılması. ActaInfologica, 1(2), 74-84.
• Bolen, M.C. (2020). Exploring the Determinants of Users’Continuance Intention in Smart Watches, Technology in Society, 60, 101209.
• Chung, Y. (2015). Hedonic and Utilitarian Shopping Values in Airport Shopping Behavior. Journal of Air Transport Management, 49, 28-34.
• Churchill, G.A. & Surprenant, C. (1982). An Investigation into the Determinants of Customer Satisfaction. Journal of Marketing Research, 19(4), 491-504.
• Cross, T. (2018). Human Obsolescence, Science and Technology. The World in 2018, The Economist, (Erişim: 06 Temmuz 2022), https://theworldin.economist.com/edition/2018/ article/14586/human-obsolescence
• Dabholkar, P. A., Shepherd, C. D., & Thorpe, D. I. (2000). A Comprehensive Frame Work for Service Quality: An Investigation of Critical Conceptual and Measurement Issues Through a Longitudinal Study. Journal of Retailing, 76(2), 139-173.
• Dautenhahn, K., Woods, S., Kaouri, C., Walters, M. L., Koay, K. L., & Werry, I. P. (2005). “What is A Robot Companion-Friend, Assistant or Butler? Intelligent Robots and Systems”, 2005 IEEE/RSJ International Conference on New York.
• Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
• De Leeuw, E.D. (2005). To Mix or Not to Mix Data Collections in Surveys. Journal of Official Statistics, 21, 233–255.
• De Leeuw, E.D., Hox, J.J. & Dillman, D.A. (2008). Mixed-Mode Surveys: When and Why, In International Hand Book of Survey Methodology, eds E.D. De Leeuw, J.J. Hox, and D.A. Dillman (NewYork, NY: Erlbaum/Taylor and Francis), 299-316.
• Dillman, D.A., Smyth, J.D. & Christian, L.M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys. NewYork, NY: Wiley.
• Fink, J., Bauwens, V., Kaplan, F., & Dillenbourg, P. (2013). Living with a Vacuum Cleaning Robot. International Journal of Social Robotics, 5(3), 389-408.
• Fong, T., Nourbakhsh, I., & Dautenhahn, K. (2003). A Survey of Socially Interactive Robots. Robotics and Autonomous Systems, 42(3-4), 143–166.
• Forlizzi, J. & DiSalvo C. (2006). “Service Robots in the Domestic Environment: A Study of the Roomba Vacuum in the Home”, Conference: Proceedings of the ACM SIGCHI/SIGART Conference on Human-Robot Interaction, Salt Lake City, Utah, USA.
• Forlizzi, J. (2007). “How Robotic Products Become Social Products: An Ethnographic Study of Cleaning in the Home”, HRI'07: Proceedings of the ACM/IEEE international conference on Human-robot interaction, March, 129–136,
• Fornell, C. & Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Erros. Journal of Marketing Research, 18(1), 39-50.
• Gates, B., (2008). A Robot in Everyhome. Scientific American, 296(1), 58–65.
• Guriting, P. & OlyNdubisi, N. (2006). Borneoonline Banking: Evaluating Customer Perceptions and Behavioural Intention. Management Research News, 29(1/2), 6-15.
• Gyampah, K. A. & Salam, A. F. (2004). An Extension of The Technology Acceptance Model in an ERP Implementation Environment. Information & Management, 41(6), 731-745.
• Hayashi A., Chen C., Ryan T. & Wu J. (2004). The Role of Social Presence and Moderating Role of Computer Self-Efficacy in Predicting the Continuance Usage of e-learning Systems. Journal of Information Systems Education, 15(2), 139-154.
• Heerink, M., Kröse, B., Evers, V. & Wielinga, B. (2010). Assessing Acceptance of Assistive Social Agent Technology by Older Adults: The Almere model. International Journal of Social Robotics, 2, 361–375.
• Hew, J.-J., Badaruddin, M.N.B.A., & Moorthy, M.K. (2017). Crafting a Smart Phone Repurchase Decision Making Process. Telematics Informatics, 34(4), 34–56.
• Hong, J. C., Lin, P. H. & Hsieh, P. C. (2017). The Effect of Consumer Innovativeness on Perceived Value and Continuance Intention to Use Smart Watch. Computers in Human Behavior, 67, 264-272.
• Hong, S. J., Thong, J.Y.L. & Tam, K.Y. (2006). Understanding Continued Information Technology Usage Behavior: A Comparison of Three Models in the Context of Mobile Internet. Decision Support Systems, 42(3), 1819-1834.
• Hsiao, C.H., Chang, J.J. & Tang, K.Y. (2016). Exploring the Influential Factors in Continuance Usage of Mobile Social Apps: Satisfaction, Habit, and Customer Value Perspectives. Telematics and Informatics, 33(2), 342–355.
• Hsu, C.L., & Lin, J.C.C. (2015). What Drives Purchase Intention for Paid Mobile Apps? - An Expectation Confirmation Model with Perceived Valu. Electronic Commerce Research and Applications, 14(1), 46-57.
• Hsu, M.H., Chang, C.M. & Chuang, L.W. (2015). Understanding the Determinants of Online Repeat Purchase Intention and Moderating Role of Habit. International Journal of Information Management, 35(1), 45–56,
• Inteco (1998). Why Do People Choose ISPs and Why Do They Drop Them? Stamford Connecticut, USA. Inteco Corporation Press Report
• Karahanna, E., Straub, D.W. & Chervany, N.L. (1999). Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs. MIS Quarterly, 23(2), 183-213.
• Khalifa, M. & Liu, V. (2007). Online Consumer retention: Contingent Effects of Online Shopping Habit and Online Shopping Experience. European Journal of Information Systems, 16(6), 780–792.
• Kwok, S., & Uncles, M. (2005). Sales Promotion Effectiveness: The Impact of Consumer Differences at an Ethnic-Group Level. Journal of Product and Brand Management, 14(3), 170-186.
• Lee, K. M., Jung, Y., Jaywoo. K., & Sang-Ryong, K. (2006). Are Physically Embodied Social Agents Better than Disembodied Social Agents? The Effects of Physical Embodiment, Tactile Interaction, and People’s Loneliness in Human-Robot Interaction. International Journal of Human-Computer Studies, 64(10), 962-973.
• Li, H.X. & Liu Y. (2014) Understanding Post-Adoption Behaviors of e-Service Users in the Context of Online Travel Services. Information and Management, 51(8), 1043-1052.
• Limayem, M. & Hirt, S.G. (2003). Force of Habit and Information systems Usage: The Oryandinitial Validation. Journal of the Association for Information Systems, 4(1).
• Limayem, M., Hirt, S.G. & Cheung, C.M.K. (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Quarterly, 31(4), 705-737.
• Lin, X., Featherman, M. & Sarker, S. (2017). Understanding Factors Affecting Users’ Social Networking Site Continuance: A Gender Difference Perspective. Information & Management, 54(3), 383-395.
• Locke, E.A. (1976). The Natüre and Causes of Job Satisfaction. In M.D. Dunnette (Ed.), Handbook of Industrial and Organizational Psychology, Chicago, IL: Rand McNally, 1297-1343.
• Luk, S. T. K., & Yip, L. S. (2008). The Moderator Effect of Monetary Sales Promotion on The Relationship between Brand Trust and Purchase Behaviour. Journal of Brand Management, 15(6), 452-464.
• Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173-191.
• Matzler, K., Bidmon, S. & Grabner-Krauter, S. (2006). Individual Determinants of Brand Affect: The Role of the Personality Traits of Extra Version and Openness to Experience. Journal of Product & Brand Management, 15(7), 427-434.
• Nascimento, B., Oliveira, T. & Tam, C. (2018). Wearable technology: What Explains Continuance Intention in Smart Watches? Journal of Retailingand Consumer Services, 43, 157-169.
• Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the Intention to Use Mobile Shopping Applications and Its Influence on Price Sensitivity. Journal of Retailing and Consumer Services, 37, 8-22.
• Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460-469.
• Oliver, R.L. (1981). Measurement and Evaluation of Satisfaction Processes in Retail Settings. Journal of Retailing, 57(3), 25-48.
• Picot-Coupey, K., Krey, N., Hure, E. & Ackerman, C.-L. (2021). Still Work and/or Fun? Corroboration of the Hedonic and Uilitarian Shopping Value Scale. Journal of Business Research, 126, 578-590.
• Premkumar, G. & Bhattacherjee, A. (2008). Explaining Information Technology Usage: A Test of Competing Models, Omega, 36(1), 64-75.
• Roca, J.C., Chiu, C. M. & Martínez, F. J. (2006). Understanding e-Learning Continuance Intention: An Extension of the Technology Acceptance Model, International Journal of Human-Computer Studies, 64(8), 683-696.
• Romkey, J. (2017). Toast of the IoT: The 1990 Interop Internet Toaster, IEEE Consumer Electronics Magazine, 6(1), 116-119.
• 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.
• Sorebo, O. & Eikebrokk, T.R. (2008). Explaining IS Continuance in Environments Where Usage is Mandatory. Computers in Human Behavior, 24(5), 2357-2371.
• Sung, J., Grinter, R. E. & Christensen, H. I. (2010). Domestic Robot Ecology. International Journal of Social Robotics, 2(4), 417-429.
• Taylor, S. &Todd, P.A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176.
• Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance. International Journal of Human-Computer Studies, 64(9), 799-810.
• Uyar, A. (2019). Tüketicilerin Mobil Uygulamalara İlişkin Algılarının Teknoloji Kabul Modeli ile Değerlendirilmesi. İşletme Araştırmaları Dergisi, 11(1), 687-705.
• Venkatesh, V. & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
• Venkatesh, V., Thong, J.Y., Chan, F.K., Hu, P.J.H., & Brown, S.A. (2011). Extending the Two Stage Information Systems Continuance Model: Incorporating UTAUT Predictors and the Role of Context. Information Systems Journal, 21(6), 527-555.
• Verplanken, B., &Orbell, S. (2003). Reflections on Past Behavior: A Self-Reportindex of Habit Strength. Journal of Applied Social Psychology, 33(6), 1313-1330.
• Yang, H., Yu, J., Zo, H. & Choi, M. (2016). User Acceptance of Wearable Devices: An Extended Perspective of Perceived Value. Telematics and Informatics, 33(2),256-269.
• Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An Investigation of Users’ Continuance Intention towards Mobile Banking in China. Information Development, 32(1), 20-34.
• Yurdugül, H., & Sırakaya, D. A. (2013). Çevrimiçi Öğrenme Hazır Bulunuşluluk Ölçeği: Geçerlik ve Güvenirlik Çalışması. Eğitim ve Bilim, 38(169), 391-406.