Exploring the Factors Influencing Continuance Usage of Over-the-Top Services: The Interactivity, Consumption Value, and Satisfaction Perspectives

Over-the-top (OTT) TV services are pervasive in local and global markets. Compared with traditional media consumption, OTT platforms afford users more control over content selection at a cheaper price. However, discussions of OTT services are limited and do not reveal the antecedents and consequences of OTT use from individual perspectives. Therefore, this study developed an empirical model by integrating perceived interactivity, perceived value, satisfaction, and continuance usage. After collecting data from 230 OTT users, we confirmed most of the researcher's proposed hypotheses and that perceived platform interactivity is the most critical indicator of OTT use. OTT users may prefer interacting with content and the social community from a value perspective. Perceived interactivity and perceived value are strong indicators of satisfaction and continuance usage of OTT services. Implications for academics and practitioners are discussed.

[1]  Xia Liu Development of a Scale to Measure the Perceived Interactivity of Websites , 2015 .

[2]  Inge Ejbye Sørensen,et al.  The revival of live TV: liveness in a multiplatform context , 2016 .

[3]  Nick Bontis,et al.  User acceptance of wireless short messaging services: Deconstructing perceived value , 2007, Inf. Manag..

[4]  Richard A. Spreng,et al.  Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business‐to‐business, services context: an empirical examination , 1997 .

[5]  Margherita Pagani,et al.  The Influence of Personal and Social-Interactive Engagement in Social TV Web Sites , 2011, Int. J. Electron. Commer..

[6]  G. Mcdougall,et al.  Customer satisfaction with services: putting perceived value into the equation , 2000 .

[7]  Byoungsoo Kim,et al.  An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation-confirmation model , 2010, Expert Syst. Appl..

[8]  Detmar W. Straub,et al.  Reconceptualizing System Usage: An Approach and Empirical Test , 2006, Inf. Syst. Res..

[9]  H. Wilson,et al.  Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives , 2010 .

[10]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[11]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[12]  Katy E. Pearce,et al.  Influences on TV Viewing and Online User-shared Video Use: Demographics, Generations, Contextual Age, Media Use, Motivations, and Audience Activity , 2012 .

[13]  Chechen Liao,et al.  Shopping motivations on Internet: A study based on utilitarian and hedonic value , 2007 .

[14]  Kar Yan Tam,et al.  The Effects of Post-Adoption Beliefs on the Expectation-Confirmation Model for Information Technology Continuance , 2006, Int. J. Hum. Comput. Stud..

[15]  M. Wohlfarth,et al.  Regulating Over-the-Top Service Providers in Two-Sided Content Markets: Insights from the Economic Literature , 2015 .

[16]  Sumeet Gupta,et al.  Investigating the intention to purchase digital items in social networking communities: A customer value perspective , 2011, Inf. Manag..

[17]  Kai-Yu Tang,et al.  Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives , 2016, Telematics Informatics.

[18]  Yuping Liu,et al.  Developing a scale to measure the interactivity of websites , 2003, Journal of Advertising Research.

[19]  Paul A. Pavlou,et al.  Understanding and Predicting Electronic Commerce Adoption: An Extension of the Theory of Planned Behavior , 2006, MIS Q..

[20]  Izak Benbasat,et al.  Quo vadis TAM? , 2007, J. Assoc. Inf. Syst..

[21]  Ingoo Han,et al.  What drives the adoption of mobile data services? An approach from a value perspective , 2009, J. Inf. Technol..

[22]  Dong Hee Shin,et al.  An empirical investigation of a modified technology acceptance model of IPTV , 2009, Behav. Inf. Technol..

[23]  Raquel Sánchez-Fernández,et al.  The concept of perceived value: a systematic review of the research , 2007 .

[24]  Jang-Sun Hwang,et al.  Measures of Perceived Interactivity: An Exploration of the Role of Direction of Communication, User Control, and Time in Shaping Perceptions of Interactivity , 2002 .

[25]  Sonja Wiley-Patton,et al.  Consumer adoption of mobile TV: Examining psychological flow and media content , 2009, Comput. Hum. Behav..

[26]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[27]  John Raacke,et al.  MySpace and Facebook: Applying the Uses and Gratifications Theory to Exploring Friend-Networking Sites , 2008, Cyberpsychology Behav. Soc. Netw..

[28]  Trisha T. C. Lin Convergence and regulation of multi-screen television: The Singapore experience , 2013 .

[29]  Oliver Quiring,et al.  What Interactivity Means to the User Essential Insights into and a Scale for Perceived Interactivity , 2008, J. Comput. Mediat. Commun..

[30]  Hokyoung Ryu,et al.  Perceived usefulness and performance of human-to-human communications on television , 2008, Comput. Hum. Behav..

[31]  Mark Colgate,et al.  Customer Value Creation: A Practical Framework , 2007 .

[32]  Guohua Wu Conceptualizing and Measuring the Perceived Interactivity of Websites , 2006 .

[33]  Margaret Meiling Luo,et al.  Post-Adoption Behaviors of E-Service Customers: The Interplay of Cognition and Emotion , 2008, Int. J. Electron. Commer..

[34]  Yuan Sun,et al.  Looking inside the “it Black Box”: Technological Effects on it Usage , 2014, J. Comput. Inf. Syst..

[35]  J KimDan,et al.  A study of mobile user engagement (MoEN) , 2013, DSS 2013.

[36]  Ali F. Farhoomand,et al.  A structural model of end user computing satisfaction and user performance , 1996, Inf. Manag..

[37]  C. Grönroos,et al.  Critical service logic: making sense of value creation and co-creation , 2013 .

[38]  Eun-Ju Lee,et al.  The effects of utilitarian and hedonic online shopping value on consumer preference and intentions , 2006 .

[39]  Tae Hyun Baek,et al.  Examining the antecedents and consequences of mobile app engagement , 2018, Telematics Informatics.

[40]  Dan Jong Kim,et al.  A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention , 2013, Decis. Support Syst..

[41]  G. Wu,et al.  Perceived Interactivity and Attitude toward Web Sites, In Proceedings of the Conference of the American Academy of Advertising: . , 1999 .

[42]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[43]  Wen-Lung Shiau,et al.  What factors satisfy e-book store customers? Development of a model to evaluate e-book user behavior and satisfaction , 2017, Internet Res..

[44]  Sally J. McMillan,et al.  Defining Interactivity , 2000, New Media Soc..

[45]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[46]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[47]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[48]  Thomas E. Ruggiero Uses and Gratifications Theory in the 21st Century , 2000 .

[49]  V. Zeithaml Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence: , 1988 .

[50]  J. Hair Multivariate data analysis , 1972 .

[51]  Mario Gerla,et al.  Will IPTV ride the peer-to-peer stream? [Peer-to-Peer Multimedia Streaming] , 2007, IEEE Communications Magazine.

[52]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[53]  William R. King,et al.  A meta-analysis of the technology acceptance model , 2006, Inf. Manag..

[54]  I. Ajzen,et al.  Attitudes toward objects as predictors of sin-gle and multiple behavioral criteria , 1974 .

[55]  B. Wheaton,et al.  Assessment of Fit in Overidentified Models with Latent Variables , 1987 .

[56]  Alan M. Rubin,et al.  Psychological Predictors of Television Viewing Motivation , 1991 .

[57]  Wynne W. Chin,et al.  Extending the technology acceptance model: the influence of perceived user resources , 2001, DATB.

[58]  Anol Bhattacherjee,et al.  Understanding Post-Adoption Behavior in the Context of Online Services , 1998, Inf. Syst. Res..

[59]  Edward E. Rigdon,et al.  Experiential value: Conceptualization, measurement and application in the catalog and Internet shopping environment. , 2001 .

[60]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[61]  Gen-Yih Liao,et al.  You Can Make It: Expectancy for Growth Increases Online Gamer Loyalty , 2017, Int. J. Electron. Commer..

[62]  Jungkun Park,et al.  The role of interactivity in e-tailing: Creating value and increasing satisfaction , 2010 .

[63]  Viswanath Venkatesh,et al.  Model of Adoption and Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle , 2005, MIS Q..

[64]  Chia-Chen Chen,et al.  What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement , 2018, Telematics Informatics.

[65]  Laura D. Jolly,et al.  The effects of consumer perceived value and subjective norm on mobile data service adoption between American and Korean consumers , 2009 .

[66]  William R. Darden,et al.  Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value , 1994 .

[67]  G. Soutar,et al.  Consumer perceived value: The development of a multiple item scale , 2001 .

[68]  Chang-Hoan Cho,et al.  INTERNET USES AND GRATIFICATIONS: A Structural Equation Model of Interactive Advertising , 2005 .

[69]  Kerk F. Kee,et al.  Being Immersed in Social Networking Environment: Facebook Groups, Uses and Gratifications, and Social Outcomes , 2009, Cyberpsychology Behav. Soc. Netw..

[70]  E. Hirschman,et al.  Hedonic Consumption: Emerging Concepts, Methods and Propositions , 1982 .

[71]  Juran Kim,et al.  Experience effects on interactivity: Functions, processes, and perceptions , 2012 .

[72]  Barbara L. Gross,et al.  Why we buy what we buy: A theory of consumption values , 1991 .

[73]  Paul McDonald,et al.  Universal ideals in local realities , 2016 .

[74]  Veroline Cauberghe,et al.  The Impact of Banners on Digital Television: The Role of Program Interactivity and Product Involvement , 2008, Cyberpsychology Behav. Soc. Netw..

[75]  Jen-Her Wu,et al.  Falling in love with online games: The uses and gratifications perspective , 2010, Comput. Hum. Behav..

[76]  Heather L. O'Brien,et al.  The influence of hedonic and utilitarian motivations on user engagement: The case of online shopping experiences , 2010, Interact. Comput..

[77]  Jeng-Yi Tzeng,et al.  Perceived values and prospective users' acceptance of prospective technology: The case of a career eportfolio system , 2011, Comput. Educ..

[78]  Juran Kim,et al.  Towards a theoretical framework of motivations and interactivity for using IPTV , 2013 .

[79]  Jong-Ho Lee,et al.  Understanding the Adoption of Convergent Services: The Case of IPTV , 2011, 2011 44th Hawaii International Conference on System Sciences.

[80]  Chechen Liao,et al.  What Affects Mobile Application Use? the Roles of Consumption Values , 2013 .

[81]  Sheng Wu,et al.  The integration of value-based adoption and expectation-confirmation models: An example of IPTV continuance intention , 2012, Decis. Support Syst..

[82]  Youngjin Yoo,et al.  Computing in Everyday Life: A Call for Research on Experiential Computing , 2010, MIS Q..

[83]  Alexander Serenko,et al.  User acceptance of hedonic digital artifacts: A theory of consumption values perspective , 2010, Inf. Manag..

[84]  HsiaoChun-Hua,et al.  Exploring the influential factors in continuance usage of mobile social Apps , 2016 .

[85]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[86]  R. B. Woodruff,et al.  Customer value: The next source for competitive advantage , 1997 .

[87]  Carolyn A. Lin Modeling the Gratification‐Seeking Process of Television Viewing , 1993 .

[88]  Yaobin Lu,et al.  Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention , 2012, Decis. Support Syst..

[89]  Spiro Kiousis,et al.  Interactivity: a concept explication , 2002, New Media Soc..