Consumers' behavioral intention toward online shopping in the post-COVID-19 period

Infectious COVID-19 transformed the world overnight, freezing all physical activities and forcing the majority toward online mode. Technology came up as a savior to alleviate the consequences of COVID-19 on the economy, causing a rapid transformation in consumers' behavior, and an overall jump in the sale of e-commerce could be witnessed globally. This paper aims to explore the factors that caused the transformation in consumers' behavioral attitude (AT) and intention toward online shopping (BITOS). The study integrates the TPB and UTAUT models while adding two additional variables, namely, perceived risks (PR) and perceived benefits (PB), to predict consumers' BITOS. A survey was conducted to collect a sample of 402 consumers Aligarh city, and the National Capital Region of India using the mall intercept sampling method. The data were analysed to establish the measurement model and test the hypothesized structural model with the Smart-PLS software. The study's findings confirmed that PB, subjective social norms, perceived ease of use, and perceived usefulness positively affect AT and BITOS, whereas PR does not influence AT and BITOS. The study also indicated that AT has a positive effect on BITOS. Concerning AT, it does not mediate the relationship between PR and BITOS; however, it mediates between the direct link PB and BITOS, making it stronger. The study's findings help the E-commerce industry understand consumers' transformed attitudes/intentions and restructure their strategies to strengthen their online business further. Despite its regional and design limitations, it contributes significantly to the current research on online shopping behavior in India during COVID-19.