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Artificial intelligence-based investment services (robo-advisors) are becoming increasingly commercialized. Robo-advisors are expected to expand further due to the enhancement of accessibility to investment for general investors through customized portfolio selection and automated transactions established upon the artificial intelligence-based algorithm. This study comprehensively investigates factors that influence acceptance intention of and resistance to robo-advisors using a combined model of technology acceptance model and innovation resistance model. The model was examined through conducting a choice-based conjoint analysis of 158 users with investment experience and age ranging from 20s to 60s. The independent variables of the research for robo-advisors are transparency, customization, social presence, and user control. The effects of the independent variables on acceptance intention and innovation resistance are analyzed, respectively, through mediator variables of perceived usefulness, perceived complexity, and perceived safety. This study indicates the fundamental factors for the promotion of the domestic robo-advisor market based on the analysis of further advanced overseas robo-advisor markets. The significance of this study derives from providing implications on the direction of development for companies or financial institutions in the sphere of robo-advisors.

Virtual assistants are becoming significant in the area of voice commerce. Voice commerce creates an environment where orders and payments can be done through voice recognition, increasing its accessibility in comparison to other existing commercial transaction methods. Thus, the field is expected to grow into a promising industry. However, the full bloom of voice commerce depends on user acceptance, as well as technological improvement. This study develops a conceptual framework to describe factors influencing user acceptance to voice commerce, which are analyzed with the structural equation model by combining the technology acceptance model (TAM) and the model of innovation resistance (MIR). With accuracy, social presence, and interactivity of a virtual assistant, along with user attributes such as user innovativeness and experience, as variables, a survey of 151 Koreans in their 20s and 30s is conducted. Moreover, the impact of three factors, relative advantage, perceived ease of use, and perceived risk, on innovation acceptance and resistance is analyzed to find key variables that affect the resistance to and acceptance of voice commerce. These findings provide notable implications to companies currently using voice commerce platforms and guidance to an emerging commercial trading system.

This paper examines the reasons for corporate customers' resistance to adopt industrial service innovations provided by their supplier companies. It is based on work with nine Finnish suppliers of industrial services and their potential customers. We view organizations as networks of individual adopters. We find that organizational sentiment towards adopting an innovation is often ambivalent and that resisting views reveal important drawbacks of an innovation that need to be addressed. The results clarify the effects of utility, cost, emotion and risk aversion in organizational service decisions emphasizing the fit of the service for the customer.

Little research effort has been dedicated to investigate the nature and determinants of and the differences between temporary and continuous consumer rejections of innovations. To shed light on both types of consumer rejection behaviours and their underlying psychological processes, this paper applies a mixed-method approach. First, we conducted a qualitative study to investigate whether known determinants comprehensively cover reasons for both types of consumer rejections. Based on the qualitative study’s evidence, we introduce a new type of innovation resistance (transactional innovation resistance) to complement the well-known concepts of active and passive innovation resistance as drivers of rejection behaviour. Second, we validated the derived framework using a large-scale quantitative study to empirically determine each determinant’s relative importance for temporary and continuous consumer rejection of innovations. Our results demonstrate that consumers who continuously reject an innovation are primarily driven by a combinatory effect of passive and active innovation resistance. In contrast, consumers who only temporarily reject are largely motivated by a combinatory effect of transactional and active innovation resistance.

The phenomenon of ‘consumer leapfrogging’ represents a conscious shift of consumers’ purchase decision for an innovation to a future product generation, and results in lower-than-expected demand. As consumers skip product generations, new product diffusion for the initial innovation and corresponding company turnover is capped. While previous studies highlight the importance of consumer leapfrogging behaviour, effective marketing strategies to attenuate detrimental consequences are lacking. To close this research gap, this paper empirically tests the effectiveness of various marketing strategies (trade-in program, bonus program, money-back guarantee, and product bundles) as potential countermeasures to consumer leapfrogging via a scenario-based online experiment with a 5 (four marketing strategies and control group) × 2 (low/high radical product) between-subjects design. Our results reveal that trade-in and bonus programs as well as money-back guarantees are effective countermeasures to consumer leapfrogging behaviour. Furthermore, our findings also show that the effectiveness of the instruments decreases with the degree of product radicality.