Adoption of smart TVs: a Bayesian network approach

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Purpose - This study aims to identify factors that determine the smart TV buying decisions of users and analyze the relationships among the factors by using Bayesian network approach. Design/methodology/approach - This study investigates smart TV users' perception based on innovation diffusion theory (IDT) which includes five innovation attributes: relative advantage, compatibility, complexity, trialability, and observability. The authors employ Bayesian network to identify causal relationship among the innovation attributes and analyze the sensitivity of the intentions to changes in factors. Findings - The results show that relative advantage has the greatest influence on the purchase intention of smart TV, followed by compatibility, entertainment, web-browsing and n-screen. Research limitations/implications - The reliability of the results is limited as the survey is not carried out on a large number of samples. The study, however, suggests a future direction for smart TV in consumers' point of view. Practical implications - According to the findings, companies should focus on enhancing relative advantage, rather than other attributes and entertainment service, to encourage the adoption of smart TV. Originality/value - Smart TV is an evolving technology in the phase of market introduction. The definition and characteristics of smart TV are still uncertain. The previous literatures, however, were focused on the contents of smart TV and service, restructuring of broadcasting industry, and changes in the competitive landscape. The consumers have not been discussed in detail yet. This paper's contributions are twofold: first, it identifies important attributes for the adoption of smart TV in consumers' intention; second, it suggests a new methodology of Bayesian network in determining consumer buying factors.
Publisher
EMERALD GROUP PUBLISHING LIMITED
Issue Date
2012
Language
English
Article Type
Article
Keywords

TECHNOLOGY ACCEPTANCE MODEL; INFORMATION-TECHNOLOGY; MOBILE INTERNET; USER ACCEPTANCE; CLASSIFIERS; DIFFUSION; RISK

Citation

INDUSTRIAL MANAGEMENT & DATA SYSTEMS, v.112, no.5-6, pp.891 - 910

ISSN
0263-5577
DOI
10.1108/02635571211238509
URI
http://hdl.handle.net/10203/102375
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