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Consumers are increasingly connected to, and make use of, a multitude of technologies in their daily lives. The exponential growth in the use of Internet of Things (IoT)-based services is ushering in a new era of e-services, in which the service experience is becoming autonomous (intelligence), devices are intercommunicating (connectivity) and consumers can access the service anytime, anywhere and using any device (ubiquity). However, a number of challenges have arisen. The purpose of this paper is to investigate factors that reduce consumer resistance to smart services (factors against resistance) and factors that promote this resistance (factors for resistance), by means of a dual-factor approach.

To test this theoretical model, the authors developed a Web-based survey and used structural equation modeling.

Results show that consumer-lifestyle factors (individual “mobiquity” and self-image congruence) reduce consumer resistance to smart services (factors against resistance). Conversely, innovation-related factors (perceived security, perceived complexity) and ecosystem-related factors (perceived government surveillance and general skepticism toward IoT) promote consumer resistance to smart services (factors for resistance). In addition, general skepticism toward IoT has a significant positive effect on perceived complexity, perceived security risk and perceived government surveillance.

This research investigates consumer resistance to smart services using a dual-factor perspective (Cenfetelli, 2004; Claudy et al., 2015): factors reducing resistance versus factors promoting resistance. This paper provides evidence for the importance of consumer lifestyle-related factors, innovation-related factors and ecosystem-related factors in explaining consumer resistance to smart services. This work enriches previous studies of consumer resistance to innovation (Ram and Sheth, 1989; Ram, 1987) by studying original variables (individual mobiquity, technological innovativeness, government surveillance).

The purpose of this paper is to examine the resistance behavior of smart factories in small and medium-sized enterprises (SMEs). Drawing upon dual factor perspective, this study examines how two types of quality and perceived usefulness impact user resistance as enabling factors and how switching cost, skepticism, habit and inertia contribute to user resistance as inhibiting factors. Additionally, multi-group analysis is employed to compare small and medium enterprises.

Purposive sampling technique was employed to collect 460 Korean SMEs employees, consisting of 235 small enterprises and 225 medium enterprises. Partial least squares structural equation modeling was used for data analysis.

The results reveal that all three inhibiting factors, switching cost, skepticism and habit, are key antecedents of inertia. In small enterprises, skepticism has a greater impact on inertia, which in turn strongly affects resistance. Additionally, system quality is more crucial for small enterprises, whereas information quality holds more importance for medium enterprises in mitigating resistance. Moreover, when the implementation level of a smart factory is high, the effect of perceived usefulness on user resistance diminishes.

This study has revealed the importance of considering both enabling and inhibiting factors for the adoption of smart factory systems in the context of SMEs. Additionally, it has provided evidence that as the level of the smart factory system increases, the effect of perceived usefulness on user resistance decreases, thus making the transition to smart factory systems more challenging.