A CONCEPTUAL MODEL PROPOSAL FOR CONSUMERS' FLOW EXPERIENCES IN THE ONLINE INFORMATION SEARCH PROCESS

Yıl 2022, , 66 - 76, 04.04.2022

Zübeyir Çelik

https://doi.org/10.35344/japss.1076358

Öz

Many previous studies have explained the relationship between flow experience and consumer behavior in the context of human-computer interaction. However, studies have inconsistently evaluated the flow experience in terms of its relevant dimensions. Autotelic experience, curiosity, intrinsic interest, sense of control, focused attention, and time distortion are dimensions of online flow experience that have been inconsistently evaluated across different studies. Unlike previous studies, this current study characterizes flow experience with these six dimensions. This study aims to put forth a conceptual model suggestion on the flow experiences of consumers in their online information search processes. It is thought that this conceptual model will contribute to future consumer studies in explaining the effect of flow situations that occur in consumers' computer interactions on their behavior.

Anahtar Kelimeler

Online Flow Experience, Conceptual Model, Consumer Behavior

ONLİNE BİLGİ ARAMA SÜRECİNDE TÜKETİCİLERİN AKIŞ DENEYİMLERİNE YÖNELİK KAVRAMSAL BİR MODEL ÖNERİSİ

Öz

Daha önceki birçok çalışma, akış deneyimi ile tüketici davranışı arasındaki ilişkiyi insan-bilgisayar etkileşimi bağlamında açıklamıştır. Bununla birlikte, çalışmalar akış deneyimini ilgili boyutları açısından tutarsız bir şekilde değerlendirmiştir. Ototelik deneyim, merak, içsel ilgi, kontrol duygusu, dikkatin yoğunlaşması ve zamanın dönüşümü, online akış deneyiminin farklı çalışmalarda tutarsız bir şekilde değerlendirilen boyutlarıdır. Önceki çalışmalardan farklı olarak, bu mevcut çalışma akış deneyimini bu altı boyutla karakterize etmektedir. Bu çalışma, tüketicilerin online bilgi arama süreçlerindeki akış deneyimleri üzerine kavramsal bir model önerisi ortaya koymayı amaçlamaktadır. Bu kavramsal modelin, tüketicilerin bilgisayar etkileşimlerinde meydana gelen akış durumlarının davranışları üzerindeki etkisini açıklamada gelecekteki tüketici çalışmalarına katkı sağlayacağı düşünülmektedir.

Anahtar Kelimeler

Online Akış Deneyimi, Kavramsal Model, Tüketici Davranışı

Kaynakça

• Agarwal, R. and Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
• Bei, L. T., Chen, E. Y. and Widdows, R. (2004). Consumers' online information search behavior and the phenomenon of search vs. experience products. Journal of Family and Economic Issues, 25(4), 449-467.
• Baytar, U. (2018). Tüketicilerin çevrimiçi alışveriş kanallarındaki akış deneyimlerinin memnuniyet ve satın alma kararlarına etkisi, bilgi ve kanal kalitesinin rolü. Yayımlanmamış Doktora Tezi, İstanbul: Beykent Üniversitesi SBE.
• Baytar, U. and Yükselen, C. (2018). Tüketicilerin çevrimiçi alışveriş kanallarındaki akış deneyimlerinin memnuniyet ve satın alma kararlarına etkisi, bilgi ve kanal kalitesinin rolü. Beykent Üniversitesi Sosyal Bilimler Dergisi, 11(2), 19-35.
• Bar-Ilan, J. (2005). Information hub blogs. Journal of Information Science, 31(4), 297-307.
• Bilgihan, A., Nusair, K., Okumus, F. and Cobanoglu, C. (2015). Applying flow theory to booking experiences: An integrated model in an online service context. Information & Management, 52(6), 668-678.
• Calvo-Porral, C., Faíña-Medín, A. and Nieto-Mengotti, M. (2017). Exploring technology satisfaction: An approach through the flow experience. Computers in Human Behavior, 66, 400-408.
• Chau, P. Y., Au, G. And Tam, K. Y. (2000). Impact of information presentation modes on online shopping: an empirical evaluation of a broadband interactive shopping service. Journal of Organizational Computing and Electronic Commerce, 10(1), 1-20.
• Chen, C. C. and Lin, Y. C. (2018). What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), 293-303.
• Chen, H., Wigand, R. T., & Nilan, M. S. (1999). Optimal experience of web activities. Computers in Human Behavior, 15(5), 585-608.
• Chen, H., Wigand, R. T. and Nilan, M. (2000). Exploring web users’ optimal flow experiences. Information Technology & People, 13(4), 263-281.
• Choi, D. H., Kim, J. and Kim, S. H. (2007). ERP training with a web-based electronic learning system: The flow theory perspective. International Journal of Human-Computer Studies, 65(3), 223-243.
• Csikszentmihalyi, M. (1975a). Play and intrinsic rewards. Journal of Humanistic Psychology, 15(3), 290.
• Csikzentimihalyi, M. (1975b). Beyond boredom and anxiety: Experiencing flow in work and play. San Francisco/Washington/London.
• Csikszentmihalyi, M. (1982). Toward a psychology of optimal experience. In: Wheeler, L. (Ed.), Review of Personality and Social Psychology (pp. 13–36). Sage Publications. USA.
• Csikszentmihalyi, M. (1988). The flow experience and ıts significance for human psychology. In M. Csikszentmihalyi & I. S. Csikszentmihalyi (Eds.), Optimal experience: Psychological Studies of Flow in Consciousness (pp. 15–35). Cambridge University Press.
• Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper & Row.
• Csikszentmihalyi, M. (1997). Finding flow: The psychology of engagement with everyday life. Basic Books.
• Çabuk, S. and Kuş, A. S. (2019). E-perakende sitelerinde yaşanan akış deneyiminin tüketici satın alma niyetine etkisi: giyim ve ayakkabı sektöründe faaliyet gösteren markalar üzerinde bir inceleme. Business & Management Studies: An International Journal, 7(3), 257-279.
• De Jans, S., Cauberghe, V. and Hudders, L. (2018). How an advertising disclosure alerts young adolescents to sponsored vlogs: The moderating role of a peer-based advertising literacy intervention through an informational vlog. Journal of Advertising, 47(4), 309-325.
• Deng, L., Turner, D. E., Gehling, R. and Prince, B. (2010). User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19(1), 60-75.
• Ettis, S. A. (2017). Examining the relationships between online store atmospheric color, flow experience and consumer behavior. Journal of Retailing and Consumer Services, 37, 43-55.
• Evanschitzky, H., Iyer, G. R., Hesse, J. and Ahlert, D. (2004). E-satisfaction: a re-examination. Journal of Retailing, 80(3), 239-247.
• Fang, X., Brzezinski, J., Watson, K., Xu, S. and Chan, S. (2004). An empirical study of dual-modal information presentation. AMCIS 2004 Proceedings, 395.
• Finneran, C. M. and Zhang, P. (2005). Flow in computer-mediated environments: Promises and challenges. Communications of the Association for Information Systems, 15(1), (Article 4), 82-101.
• Flynn, L. R. and Goldsmith, R. E. (2001). The impact of internet knowledge on online buying attitudes, behavior, and future intentions: A structural modeling approach. Society for Marketing Advances Proceedings, 193-196.
• Gao, L. and Bai, X. (2014). Online consumer behaviour and its relationship to website atmospheric induced flow: Insights into online travel agencies in China. Journal of Retailing and Consumer Services, 21(4), 653-665.
• Gao, W., Tian, Y., Huang, T. and Yang, Q. (2010). Vlogging: A survey of videoblogging technology on the web. ACM Computing Surveys (CSUR), 42(4), 1-57.
• Ghani, J. A. and Deshpande, S. P. (1994). Task characteristics and the experience of optimal flow in human—computer interaction. The Journal of Psychology, 128(4), 381-391.
• Ghani, J. A., Supnick, R. and Rooney, P. (1991). The Experience of flow in computer-mediated and in face-to-face groups, In Icıs, 91(6), 229-237.
• Hill, S. R., Troshani, I. and Chandrasekar, D. (2017). Signalling effects of vlogger popularity on online consumers. Journal of Computer Information Systems, 1-9.
• Hoffman, D. L. and Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(3), 50-68.
• Hoffman, D. L. and Novak, T. P. (2009). Flow online: lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23-34.
• Hsu, C. L., Chang, K. C. and Chen, M. C. (2012). The impact of website quality on customer satisfaction and purchase intention: perceived playfulness and perceived flow as mediators. Information Systems and e-Business Management, 10(4), 549-570.
• Hsu, C. L. and Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
• Hsu, H. Y. and Tsou, H. T. (2011). Understanding customer experiences in online blog environments. International Journal of Information Management, 31(6), 510-523.
• Huang, M. H. (2006). Flow, enduring, and situational involvement in the Web environment: A tripartite second‐order examination. Psychology & Marketing, 23(5), 383-411.
• Jackson, S. A. and Marsh, H. W. (1996). Development and validation of a scale to measure optimal experience: The Flow State Scale. Journal of Sport and Exercise Psychology, 18(1), 17-35.
• Kaur, P., Dhir, A. and Rajala, R. (2016). Assessing flow experience in social networking site based brand communities. Computers in Human Behavior, 64, 217-225.
• Kim, M. and Lennon, S. (2008). The effects of visual and verbal information on attitudes and purchase intentions in internet shopping. Psychology & Marketing, 25(2), 146-178.
• Kim, C., Oh, E. and Shin, N. (2010). An empirical investigation of digital content characteristics, value, and flow. Journal of Computer Information Systems, 50(4), 79-87.
• Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior, Information Systems Research, 13(2), 205-223.
• Koufaris, M., Kambil, A. and LaBarbera, P. A. (2001). Consumer behavior in web-based commerce: an empirical study. International journal of electronic commerce, 6(2), 115-138.
• Kulviwat, S., Guo, C. and Engchanil, N. (2004). Determinants of online information search: a critical review and assessment. Internet Research, 14(3), 245-253.
• Lee, J. E. and Watkins, B. (2016). YouTube vloggers' influence on consumer luxury brand perceptions and intentions. Journal of Business Research, 69(12), 5753-5760.
• Lee, C. H. and Wu, J. J. (2017). Consumer online flow experience: The relationship between utilitarian and hedonic value, satisfaction and unplanned purchase. Industrial Management & Data Systems, 117(10), 2452-2467.
• Li, D. and Browne, G. J. (2006). The role of need for cognition and mood in online flow experience. Journal of Computer Information Systems, 46(3), 11-17.
• Liu, H., Chu, H., Huang, Q. and Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306-314.
• Litman, J. A., Collins, R. P. and Spielberger, C. D. (2005). The nature and measurement of sensory curiosity. Personality and Individual Differences, 39(6), 1123-1133.
• Loewenstein, G. (1994). The psychology of curiosity: A review and reinterpretation. Psychological Bulletin, 116(1), 75.
• Lu, Y., Zhou, T. and Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39.
• Metzger, M. J. (2007). Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research. Journal of the American Society for Information Science and Technology, 58(13), 2078-2091.
• Morgan-Thomas, A. and Veloutsou, C. (2013). Beyond technology acceptance: Brand relationships and online brand experience. Journal of Business Research, 66(1), 21-27.
• Nel, D., van Niekerk, R., Berthon, J. P. and Davies, T. (1999). Going with the flow: Web sites and customer involvement. Internet Research, 9(2), 109-116.
• Novak, T. P. and Hoffman, D. L. (1997). Measuring the flow experience among web users. Interval Research Corporation, 31(1), 1-35.
• Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
• Pace, S. (2004). A grounded theory of the flow experiences of Web users. International Journal of Human-Computer Studies, 60(3), 327-363.
• Park, J., Lennon, S. J. and Stoel, L. (2005). On‐line product presentation: Effects on mood, perceived risk, and purchase intention. Psychology & Marketing, 22(9), 695-719.
• Parker, C. and Pfeiffer, S. (2005). Video blogging: Content to the max. IEEE MultiMedia, 12(2), 4-8.
• Pearce, J. M., Ainley, M. and Howard, S. (2005). The ebb and flow of online learning. Computers in Human Behavior, 21(5), 745-771.
• Pelet, J. É., Ettis, S. and Cowart, K. (2017). Optimal experience of flow enhanced by telepresence: Evidence from social media use. Information & Management, 54(1), 115-128.
• Ozkara, B. Y., Ozmen, M. and Kim, J. W. (2017). Examining the effect of flow experience on online purchase: A novel approach to the flow theory based on hedonic and utilitarian value. Journal of Retailing and Consumer Services, 37, 119-131.
• Özkara, B. Y. (2015). Tüketicilerin çevrimiçi bilgi aramaları bağlamında akış deneyiminin bilgiden tatmin üzerindeki etkisinin araştırılması. Yayımlanmamış Doktora Tezi, Eskişehir: Eskişehir Osmangazi Üniversitesi SBE.
• Özkara, B. Y. and Özmen, M. (2016). Akış deneyimine ilişkin kavramsal bir model önerisi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 11(3), 71-100.
• Pilke, E. M. (2004). Flow experiences in information technology use. International Journal of Human-Computer Studies, 61(3), 347-357.
• Ramadan, Z. B., Farah, M. F. and Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology Analysis & Strategic Management, 29(7), 817-828.
• Rettie, R. (2001). An exploration of flow during Internet use. Internet Research, 11(2), 103-113.
• Richard, M. O. and Chebat, J. C. (2016). Modeling online consumer behavior: Preeminence of emotions and moderating influences of need for cognition and optimal stimulation level. Journal of Business Research, 69(2), 541-553.
• Saadé, R. and Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information & Management, 42(2), 317-327.
• Shiau, W. L. and Luo, M. M. (2013). Continuance intention of blog users: the impact of perceived enjoyment, habit, user involvement and blogging time. Behaviour & Information Technology, 32(6), 570-583.
• Shin, N. (2006). Online learner’s ‘flow’experience: an empirical study. British Journal of Educational Technology, 37(5), 705-720.
• Skadberg, Y. X. and Kimmel, J. R. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in Human Behavior, 20(3), 403-422.
• Trevino, L. K. and Webster, J. (1992). Flow in computer-mediated communication: Electronic mail and voice mail evaluation and impacts. Communication Research, 19(5), 539-573.
• Vineyard, C. L. (2014). The relationship between fashion blogs and intention to purchase and word of mouth behavior. Yayımlanmamış Yüksek Lisans Tezi. Lincoln, Nebraska, ABD.
• Webster, J., Trevino, L. K. and Ryan, L. (1993). The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 9(4), 411-426.
• Xin Ding, D., Hu, P. J. H., Verma, R. and Wardell, D. G. (2010). The impact of service system design and flow experience on customer satisfaction in online financial services. Journal of Service Research, 13(1), 96-110.
• Xu, P., Chen, L. and Santhanam, R. (2015). Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type. Decision Support Systems, 73, 85-96.
• Yang, H. and Lee, H. (2018). Exploring user acceptance of streaming media devices: An extended perspective of flow theory. Information Systems and e-Business Management, 16(1), 1-27.
• Yazgan, Ş. (2012). Bilgi edinme aracı olarak blogların turistik satın alma davranışına etkisi. Yayımlanmamış Yüksek Lisans Tezi, Adnan Menderes Üniversitesi, Sosyal Bilimler Enstitüsü.
• Zhou, T. (2011). Understanding mobile Internet continuance usage from the perspectives of UTAUT and flow. Information Development, 27(3), 207-218.
• Zhou, T. (2013). The effect of flow experience on user adoption of mobile TV. Behaviour & Information Technology, 32(3), 263-272.
• Zhou, T. and Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883-889.