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This study investigates organizations' non-adoption intention towards the enterprise metaverse. The innovation resistance theory (IRT) is used as an underpinning theory to examine the impact of various risks on non-adoption intention towards the enterprise metaverse.

A total of 294 responses were collected to examine the proposed hypotheses. A structural equation modelling technique was used to investigate the hypotheses using SPSS AMOS and PROCESS MACRO.

The results of this study reveal that performance, security and psychological risks are significantly associated with non-adoption intention towards enterprise metaverse. Further, distrust significantly meditates the association between performance risk, social risk, technological dependence risk, security risk and psychological risk and non-adoption intention towards enterprise metaverse. Moreover, the results of moderated-mediation hypotheses indicate that the mediating effect of distrust on the association among performance risk, social risk, psychological risk and non-adoption intention towards enterprise metaverse is higher for individuals having high technostress compared to individuals having low technostress.

The study's findings will enrich the metaverse literature. Further, it provides a deeper understanding of enterprise metaverse adoption from a B2B perspective using the underpinnings of IRT. The study helps organizations understand the risks associated with the adoption of the enterprise metaverse.

Despite the efforts of governments and firms, consumer resistance toward digital innovations in the retail finance space continues to manifest rather visibly. Yet, the causes of consumer resistance toward innovations such as online procurement of financial products continue to remain under-explored. The present study attempts to address this gap by examining barriers that may constitute Indian consumers' resistance to buying financial products marketed digitally, using insurance as an exemplar. Precisely, the study measures five classic innovation resistance theory (IRT) barriers constituting consumers' resistance toward procuring digitally marketed insurance and examines the influence of consumers' demographic characteristics, measured through age and gender.

The conceptual model, resting on the theoretical proposition of IRT, was tested using data collected from 420 smartphone users. Given that, the data did not satisfy the multivariate assumptions of normality, homoscedasticity and linearity, artificial neural network approach was used for analysis. The analysis served as the basis for determining the relative importance of the five barriers in influencing consumer resistance.

The results indicated that the image barrier was the most influential barrier impacting consumer resistance, followed by usage, tradition, risk and value barriers. Moreover, as revealed by the values of correlations, the direction of influence was positive. Notably, the relationship of all barriers except tradition with consumer resistance was found to be nonlinear.

The study makes a novel contribution in two ways – one by extending IRT to a new area, i.e., resistance to buying financial products online, thereby further enhancing its applicability, and the other by exploring consumer resistance to e-procurement of life and nonlife insurance, which to the best of the authors' knowledge, has not been examined so far despite the established exigency.