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

Year 2022, Issue: 1, 66 - 76, 04.04.2022
https://doi.org/10.35344/japss.1076358

Abstract

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.

References

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

Year 2022, Issue: 1, 66 - 76, 04.04.2022
https://doi.org/10.35344/japss.1076358

Abstract

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.

References

  • 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.
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There are 83 citations in total.

Details

Primary Language English
Subjects Business Administration
Journal Section Articles
Authors

Zübeyir Çelik 0000-0003-1692-9378

Publication Date April 4, 2022
Submission Date February 20, 2022
Published in Issue Year 2022 Issue: 1

Cite

APA Çelik, Z. (2022). A CONCEPTUAL MODEL PROPOSAL FOR CONSUMERS’ FLOW EXPERIENCES IN THE ONLINE INFORMATION SEARCH PROCESS. Journal of Academic Perspective on Social Studies(1), 66-76. https://doi.org/10.35344/japss.1076358