An efficient hybrid delivery technology for a broadcast TV service

Kim, Taejung; Kim, Changki; Kim, Byung-Gyu

doi:10.1007/s00779-017-1059-4

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…With users’ personal data, smart service systems can develop broader customer understanding (Demirkan et al., 2015; Peters et al., 2016) and thus, create a better user experience based on innovative value propositions, as well as deeper customer relationships, as a result of personalization (Ostrom et al., 2015; Thomas et al., 2017). In the context of a content service, smart media can offer personalized services (Kim, Kim and Kim, 2017a). AI functions, such as AI speaker recognition, make personalized service for each individual user feasible.…”

Section: Theory Development and Hypothesesmentioning

confidence: 99%

Understanding interactive user behavior in smart media content service: An integration of TAM and smart service belief factors

Gao

Huang

2019

Heliyon

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Smart media combines media and artificial intelligence (AI) and can also be a user-centered content service market. However, existing research lacks an understanding of user's perceptions concerning smart services generated by different user experience types across different payment groups. Taking AI-powered Smart TV (AI TV) as a typical research object, this study (1) develops a theoretical model by integrating the technology acceptance model with users' smart service belief factors and (2) employs the user experience type as an original moderator. Using data from 585 AI TV users, the structural equation modeling analysis suggests that perceived two-way communication, perceived personalization, and perceived co-creation as three belief factors, are important antecedent constructs in the extended technology acceptance model. The analysis also suggests that the user experience type exerts positive moderating effects on two-way communication and personalization to attitude toward behavior and purchase intention. This study thus contributes to the literature on smart service by identifying and studying smart service belief factors. The addition of smart service belief factors as antecedents, as well as user experience type as a moderator, are crucial to expand the generalizability of TAM to the smart media service context. From a customer experience management perspective, this study shows how to convert ad-supported users into new paid subscribers, while keeping existing subscribers by fulfilling their smart service requirements.

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