Dataset Information

From "Human-to-Human" to "Human-to-Non-human" - Influence Factors of Artificial Intelligence-Enabled Consumer Value Co-creation Behavior.

ABSTRACT: The emergence of artificial intelligence (AI) has changed traditional methods of value co-creation. Diverging from traditional methods, this study discusses the influencing factors of AI-supported consumer value co-creation from the perspective of human-to-non-human interactions. This study adopts the stimulus-organism-response framework with consumer engagement (CE) as the intermediary to explore the impact of consumers' personal subjective factors, community factors, and perceptions of AI technology on their value co-creating behaviors. Data were collected from 528 respondents from the Huawei Huafen Club, Xiaomi BBS, Apple China Virtual Brand, Micromobile Phone, and Lenovo communities. SPSS Amos software was used for statistical analysis, revealing that perceived personalization, autonomy, community identity, trust in AI, and self-efficacy are motivational factors that have significant effects on consumer value co-creation behaviors, in which CE plays a significant intermediary role. Our study contributes to the literature on consumer value co-creation supported by AI technology. We also offer important insights for developers of AI-enabled products and service managers.

SUBMITTER: Wen H

PROVIDER: S-EPMC9120962 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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From "Human-to-Human" to "Human-to-Non-human" - Influence Factors of Artificial Intelligence-Enabled Consumer Value Co-creation Behavior.

Wen Haitao H Zhang Lulu L Sheng Ao A Li Mingda M Guo Bingfeng B

Frontiers in psychology 20220506

The emergence of artificial intelligence (AI) has changed traditional methods of value co-creation. Diverging from traditional methods, this study discusses the influencing factors of AI-supported consumer value co-creation from the perspective of human-to-non-human interactions. This study adopts the stimulus-organism-response framework with consumer engagement (CE) as the intermediary to explore the impact of consumers' personal subjective factors, community factors, and perceptions of AI tech ...[more]

PMID: 35602701

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Project description:BackgroundGeneral practitioners (GPs) care for a large number of patients with various diseases in very short timeframes under high uncertainty. Thus, systems enabled by artificial intelligence (AI) are promising and time-saving solutions that may increase the quality of care.ObjectiveThis study aims to understand GPs' attitudes toward AI-enabled systems in medical diagnosis.MethodsWe interviewed 18 GPs from Germany between March 2020 and May 2020 to identify determinants of GPs' attitudes toward AI-based systems in diagnosis. By analyzing the interview transcripts, we identified 307 open codes, which we then further structured to derive relevant attitude determinants.ResultsWe merged the open codes into 21 concepts and finally into five categories: concerns, expectations, environmental influences, individual characteristics, and minimum requirements of AI-enabled systems. Concerns included all doubts and fears of the participants regarding AI-enabled systems. Expectations reflected GPs' thoughts and beliefs about expected benefits and limitations of AI-enabled systems in terms of GP care. Environmental influences included influences resulting from an evolving working environment, key stakeholders' perspectives and opinions, the available information technology hardware and software resources, and the media environment. Individual characteristics were determinants that describe a physician as a person, including character traits, demographic characteristics, and knowledge. In addition, the interviews also revealed the minimum requirements of AI-enabled systems, which were preconditions that must be met for GPs to contemplate using AI-enabled systems. Moreover, we identified relationships among these categories, which we conflate in our proposed model.ConclusionsThis study provides a thorough understanding of the perspective of future users of AI-enabled systems in primary care and lays the foundation for successful market penetration. We contribute to the research stream of analyzing and designing AI-enabled systems and the literature on attitudes toward technology and practice by fostering the understanding of GPs and their attitudes toward such systems. Our findings provide relevant information to technology developers, policymakers, and stakeholder institutions of GP care.

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Dataset Information

From "Human-to-Human" to "Human-to-Non-human" - Influence Factors of Artificial Intelligence-Enabled Consumer Value Co-creation Behavior.

Publications

From "Human-to-Human" to "Human-to-Non-human" - Influence Factors of Artificial Intelligence-Enabled Consumer Value Co-creation Behavior.

Similar Datasets

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