The Innovation Resistance Theory: The Case of Cryptocurrencies

PurposeThe rise of virtual streamers in live streaming commerce has gained momentum, driven by the increasing prevalence of human–computer interactivity and artificial intelligence. However, achieving its broader adoption necessitates a comprehensive understanding of consumers' intention to switch from conventional human streamers to virtual streamer services as alternatives. To bridge this knowledge gap, this study endeavours to introduce and substantiate an asymmetric model incorporating innovation barriers, shopping motivations and personalities, shedding light on consumers' intention to switch.Design/methodology/approachAn online survey was conducted in the United Kingdom and analysed using a comprehensive approach that integrates Necessary Conditions Analysis (NCA), Artificial Neural Networks (ANNs) and fuzzy-set Qualitative Comparative Analysis (fsQCA).FindingsThe results unveiled six configurations of arrangements, each of them characterised by a unique combination of causation.Originality/valueIn knowledge, this study presents a significant contribution by revealing both the determinants that stimulate or hamper the desire to switch based on consumer-centric perspectives. In practice, this study is critical for helping practitioners overcome difficulties related to adoption and make educated judgements when promoting virtual streamers and developing marketing strategies in live streaming commerce.

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Artificial Intelligence and Consumer’s Perception: A Research on Environmentally Conscious Consumer

Bhatnagar,

Sharma

2024

JMv

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The purpose of this study is to explore the limited exploration of the simultaneous influence of beneficial artificial intelligence, destructive artificial intelligence, and risky artificial intelligence on green purchase intention and green purchase behaviour using the Technology Acceptance Model (TAM) and Innovation Resistance Theory (IRT). Further, it also checks the impact of green purchase intention on green purchase behaviour. Data was collected using a well-structured questionnaire from 124 consumers through online mode and analyzed using Confirmatory Factor Analysis (CFA) for reliability and validity concerns and Structural Equation Modelling (SEM) for interaction among the variables. The study's results exhibit the positive impact of beneficial artificial intelligence on green purchase intention and green purchase behaviour. Also, it reveals that destructive artificial intelligence has a positive impact on green purchase intention but a negative impact on green purchase behaviour. In addition, green purchase intention is found to be the predictor of green purchase behaviour. The extant literature is found on the impact of artificial intelligence on purchase behaviour. However, no research has been done on consumer perception of artificial intelligence and its impact on green purchase intention and green purchase behaviour as per the author’s knowledge. This study contributes to the literature of artificial intelligence as well as green consumer behaviour.

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The Innovation Resistance Theory: The Case of Cryptocurrencies

Cited by 3 publications

References 22 publications

The Perceived Barriers to the Adoption of Blockchain in Addressing Cybersecurity Concerns in the Financial Services Industry

The Perceived Barriers to the Adoption of Blockchain in Addressing Cybersecurity Concerns in the Financial Services Industry

Understanding the switching intention to virtual streamers in live streaming commerce: innovation resistances, shopping motivations and personalities

Artificial Intelligence and Consumer’s Perception: A Research on Environmentally Conscious Consumer

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