온라인 동영상 플랫폼에서의 추천품질이 추천시스템 만족과 충성도에 미치는 영향 연구
The Effect of the Recommendation Quality of Online Video Platforms on the Satisfaction of the Recommender System and Loyalty
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초록
온라인 동영상 플랫폼에서 추천시스템의 적절한 활용은 맞춤화된 추천대안들을 제시하여 이용자들이 더 많이 방문하고, 오래 머물게 하는데 기여할 수 있어 서비스의 차별적 경쟁우위 원천이 될 수 있다. 본 연구는 온라인 동영상 플랫폼에서 제안하는 추천대안들을 정보품질의 측면에서 평가하고, 이들이 소비자경험에 미치는 영향을 확인하고자 하였다. 본 연구는 추천품질을 정확성, 발견, 친숙성, 다양성으로 구분하였으며, 이들이 지각된 추천품질과 즐거움에 영향을 미치고, 추천시스템에 대한 만족과 플랫폼에 대한 충성도로 이어지는 연구모형을 제안하였다. 유튜브 이용자 251명을 대상으로 설문을 수행한 결과, 추천시스템이 이용자의 선호와 부합하는 대안을 제시해 정확성을 높였을 경우, 뜻밖의 재미를 줄 수 있는 대안을 제시해 발견을 높였을 경우, 그리고 다양한 선택의 폭을 제공해 다양성을 높였을 경우 지각된 추천품질이 높아짐을 확인하였다. 높은 추천품질의 지각은 즐거움과 추천시스템에 대한 만족으로 이어졌으며, 이는 이용자들의 행동적 충성도로 연결되었다. 본 연구결과는 추천시스템의 성과를 사용자경험의 측면에서 평가할 필요성과 함께, 온라인 동영상 플랫폼 운영은 물론, 동영상 소비가 늘어나고 있는 포털 및 SNS 서비스 운영에서의 추천시스템 운영에 대한 시사점을 제공해 줄 수 있을 것이다.
Abstract
Proper use of the recommender system in the online video platform can provide personalized recommendation alternatives hence it can make users visit more and stay longer. The study investigates the recommended alternatives in terms of information quality and how they are affecting the consumer experience. Classifying the recommendation quality into accuracy, discovery, familiarity, and diversity, the study proposed a research model that those qualities impact perceived recommendation quality, enjoyment, satisfaction, and loyalty. A survey on 251 YouTube users confirms that the perceived recommendation quality is increased when the system improves the accuracy by matching users’ preference, when it improves the discovery by suggesting unexpected fun to users, and when it provides users with a variety of choices. The perception of quality leads to enjoyment and satisfaction, and behavioral loyalty. The results suggest the necessity to evaluate the recommender system in terms of user experience and the implication for the operation of online video platforms. And it also provides implications for portal services and SNS services where video consumption by users is increasing.
참고문헌 (30)
- 유지훈, "글로벌 OTT 서비스 이용자의 지속적 이용 의도에 미치는 요인 연구 넷플릭스 사례를 중심으로", 방송통신연구, (102), pp.46~79 (2018), 한국방송학회[DOI]
- "2020년 4월 인크로스 미디어 데이터 클리핑 - 동영상 플랫폼 편" (2020)[URL]
- Bagozzi, Richard P., "Principles of Marketing Management" (1986), Science Research Associates
- Bagozzi, Richard P., "On the Evaluation of Structural Equation Models", Journal of the Academy of Marketing Science, 16(1), pp.74~94 (1988)
- Benlian, Alexander, "Web Personalization Cues and Their Differential Effects on User Assessments of Website Value", Journal of Management Information Systems, 32(1), pp.225~260 (2015)
- Berman, Barry, "Should Your Firm Adopt a Mass Customization Strategy?", Business Horizons, 45(4), pp.51~51 (2002)
- Burke, Robin, "Hybrid Recommender Systems : Survey and Experiments", User Modeling and User-Adapted Interaction, 12(4), pp.331~370 (2002)
- Chen, Li, "Critiquing-based Recommenders: Survey and Emerging Trends", User Modeling and User-Adapted Interaction, 22(1-2), pp.125~150 (2012)
- Fornell, Claes, "Evaluating Structural Equation Models with Unobservable Variables and Measurement Error", Journal of Marketing Research, 18(1), pp.39~50 (1981)
- Fornell, Claes, "A National Customer Satisfaction Barometer : The Swedish Experience", Journal of Marketing, 56(1), pp.6~21 (1992)
- Davidson, James, "The YouTube Video Recommendation System", Proceedings of the Fourth ACM Conference on Recommender Systems, pp.293~296 (2010)
- Hassenzahl, Marc, "User Experience (UX) towards an Experiential Perspective on Product Quality", Proceedings of the 20th Conference on Interaction Homme- Machine, pp.11~15 (2008)
- Ho, Shuk Ying, "Nudging Moods to Induce Unplanned Purchases in Imperfect Mobile Personalization Contexts", MIS Quarterly, 42(3), pp.757~778 (2018)
- Kamis, Arnold, "Personalizing to Product Category Knowledge: Exploring the Mediating Effect of Shopping Tools on Decision Confidence", Proceedings of the 37th Hawaii International Conference on System Sciences-2004, pp.10~19 (2004)
- Klobas, Jane E., "Compulsive YouTube Usage: A Comparison of Use Motivation and Personality Effects", Computers in Human Behavior, 87, pp.129~139 (2018)
- Knijnenburg, Bart P., "Explaining the User Experience of Recommender Systems", User Modeling and User-Adapted Interaction, 22(4-5), pp.441~504 (2012)
- Koren, Yehuda, "Factor in the Neighbors: Scalable and Accurate Collaborative Filtering", ACM Transactions on Knowledge Discovery from Data (TKDD), 4(1), pp.1~24 (2010)
- Liang, Ting-Peng, "Personalized Content Recommendation and User Satisfaction: Theoretical Synthesis and Empirical Findings", Journal of Management Information Systems, 23(3), pp.45~70 (2006)
- McNee, Sean M., "Being Accurate is not Enough: How Accuracy Metrics Have Hurt Recommender Systems", CHI'06 Extended Abstracts on Human Factors in Computing Systems, pp.1097~1101 (2006)
- Nilashi, Mehrbakhsh, "Recommendation Quality, Transparency, and Website Quality for Trust-building in Recommendation Agents", Electronic Commerce Research and Applications, 19, pp.70~84 (2016)
- Pu, Pearl, "A User-centric Evaluation Framework for Recommender Systems", Proceedings of the Fifth ACM Conference on Recommender Systems, pp.157~164 (2011)
- Pu, Pearl, "Critiquing Recommenders for Public Taste Products", Proceedings of the Third ACM Conference on Recommender Systems, pp.249~252 (2009)
- Sujata, Joshi, "Impact of Over the Top (OTT) Services on Telecom Service Providers", Indian Journal of Science and Technology, 8(S4), pp.145~160 (2015)
- Tam, Kar Yan, "Web Personalization as a Persuasion Strategy : An Elaboration Likelihood Model Perspective", Information Systems Research, 16(3), pp.271~291 (2005)
- Toufaily, Elissar, "Customer Loyalty to a Commercial Website : Descriptive Meta-analysis of the Empirical Literature and Proposal of an Integrative Model", Journal of Business Research, 66(9), pp.1436~1447 (2013)
- Wang, Weiquan, "Interactive Decision Aids for Consumer Decision Making in e-Commerce : The Influence of Perceived Strategy Restrictiveness", MIS Quarterly, 33(2), pp.293~320 (2009)
- Xiao, Bo, "E-commerce Product Recommendation Agents : Use, Characteristics, and Impact", MIS Quarterly, 31(1), pp.137~209 (2007)
- Xu, Jingjun, "The Nature and Consequences of Trade-off Transparency in the Context of Recommendation Agents", MIS Quarterly, 38(2), pp.379~406 (2014)
- Zhang, Tongxiao, "The Value of IT-enabled Retailer Learning : Personalized Product Recommendations and Customer Store Loyalty in Electronic Markets", MIS Quarterly, 35(4), pp.859~881 (2011)
- Zink, Michael, "Watch Global, Cache Local: YouTube Network Traffic at a Campus Network: Measurements and Implications", Proceedings of SPIE, 2008, ~