- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Purpose – The purpose of this paper is to develop a comprehensive research model that can explain customers’ continuance intentions to adopt and use intelligent personal assistants. Design/methodology/approach – This study proposes and validates a new theoretical model that extends the parasocial relationship theory. Partial least squares analysis is employed to test the research model and corresponding hypotheses on data collected from 304 survey samples. Findings – Interpersonal attraction (task attraction, social attraction, and physical attraction) and security/privacy risk are important factors affecting the adoption of intelligent personal assistants. Practical implications – To increase current users’ satisfaction and continuance intention to use, manufacturers or service providers should focus on developing "human-like" and "professional" assistants based on open development echo-system and form-factor/user interface innovation. Originality/value – This study is the first empirical attempt to examine user acceptance of intelligent personal assistants, as most of the prior literature has concerned analysis of usage patterns or technical features.
This study makes several contributions to existing theory. To begin, this is the first empirical academic study to examine user acceptance of IPAs with consideration of the social characteristics attributed to IPAs. Previous studies addressed privacy issues of IPAs (Easwara Moorthy and Vu, 2015), or technical architecture (Chen et al., 2016, Dernoncourt et al., 2017). Mindmeld (2016) reported IPA usage patterns such as usage time, frequency of use, purpose of use, and satisfaction; however, this work was limited to a descriptive survey report. We expect the social aspect of IPA will be highlighted in future studies because IPAs will resemble humans more, as AI technology advances. Second, to our knowledge, no research has been conducted to test the role of PSR in the context of IPAs. This study demonstrated that PSR plays an important role in post-adoption satisfaction and continued usage of IPAs, Therefore, PSR is a powerful theory for anticipating the behavioral intentions of users in the context of human-intelligent computer interaction. Third, this study verified the robustness of the proposed model by introducing new antecedents reflecting risk-related attributes, which has not been investigated in prior PSR research. The empirical results showed that the extended research model had good explanatory power, with an R 2 value of 58.9% for satisfaction and an R2 value of 57.9% for continuance intention. This implies that this new research model creates a useful framework and theoretical basis to explain IPAs, and shows that the application of traditional theories is appropriate to reflect the attributes of this new technology. Yang and Lee (2017) argued that it is necessary to select a base theory carefully and extend the theory to fit the research context, as most technology acceptance theories have limitations.