Developing And Proposing A Conceptual Model Of The Flow Experience During Online Information Search
Information search is an essential part of the consumer`s decision making process. The online medium offers new opportunities and challenges for information search activities (in and outside the marketing context). We are interested in the way human information experiences and behaviors are affected by this. Very often online games and social web activities are perceived as challenging, engaging and enjoyable, while online information search is far below this evaluation. Our research proposal implies that using the online medium for information search may provoke enjoyable experiences through the flow state, which may in turn positively influence an individual`s exploratory information behavior and encourage his/her pro-active market behavior. The present study sets out to improve the understanding of the online medium`s impact on human`s exploratory behavior. We hypothesize that the inclusion of the online flow experience in our research model will better explain exploratory information search behaviors. A 11-component conceptual framework is proposed to explain the manifestations of flow, its personal and technological determinants and its behavioral consequence in the context of online information search. Our research has the primary purpose to present an integrated online flow model. Its secondary objective is to stimulate extended research in the area of informational behaviors in the digital age. The paper is organized in three sections. In the first section we briefly report the analysis results of the most relevant online flow theory literature and, drawing on it, we are trying to identify variables and relationships among these. In the second part we propose a research model and use prior flow models to specify a range of testable hypothesis. Drawing on the conceptual model developed, the last section of our study presents the final conclusions and proposes further steps in evaluating the model`s validity. Future research directions include improving the model and hypotheses testing.
Volume (Year): 1 (2012)
Issue (Month): 1 (July)
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