Mobile shoppers' response to Covid-19 phobia, pessimism and smartphone addiction: Does social influence matter?

Because of the Covid-19 pandemic, there has been a variety of changes identified in customers' shopping behaviours, and development of new practices as a response to the crisis. The purpose of this research is to examine the effects of Covid-19 phobia, and news exposure on individuals' psychological states, and their resulting mobile shopping behaviour. Relying upon the Activate, Belief and Consequences (ABC) model of the Cognitive-Behaviour Theory, this research applies the partial least square structural modelling (PLS-SEM) methodology for analysing the data from 302 mobile shoppers from India. The results confirm that Covid-19 phobia and Covid-19 news exposure are substantial determinants of consumers' smartphone addictive use and pessimism, which in turn affect mobile shopping frequency. Additionally, social influence is found to play a vital role in moderating mobile shopping frequency for individuals, who experience smartphone addiction. The current study is a pioneering effort to examine the influence of Covid-19-induced phobia on consumers' psychological states and their subsequent impact on their mobile shopping frequency. The study provides several contributions to theory and practice within the areas of technology use and mobile shopping in particular.

Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator.

Objectives: Contact tracing applications are technological solutions that can quickly trace and notify users of their potential exposure to the Covid-19 virus and help contain the spread of the disease. However, extant research delineating the various factors predicting the adoption of contact tracing apps is scant. The study's primary objective is to develop and validate a research model based on the unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), perceived privacy risk and perceived security risk to understand the adoption of contact tracing application. Methods: An online survey was carried out among users of the 'Aarogya Setu' contact tracing app in India. The partial least squares structural equation modelling (PLS-SEM) tool was employed to analyze data from 307 respondents. Results: The results showed that performance expectancy, social influence, and facilitating conditions positively influenced users' intention to adopt the app. In contrast, perceived privacy and security risks were significant barriers to app adoption. Perceived disease threat as a moderator mitigated the adverse impact of perceived privacy risk on users' intention to adopt contact tracing apps. Conclusions: The current study gives insights on both drivers and barriers to the adoption of contract tracing applications. Various theoretical and practical implications of significance are provided for academicians and practitioners to effectively promote app adoption to tackle the Covid-19 pandemic.