Azyanee Luqman

The COVID-19 pandemic had an immediate and significant impact on consumer behavior, radically changing attitudes and behaviors, as reflected in sales figures. While some researchers believed the pandemic would lead to lasting changes, others expected a return to pre-pandemic behavioral patterns. Despite this ambiguity, there has been little research on the factors influencing consumer behavior, especially about the demand for everyday goods. This study, rooted in the theory of planned behavior (TPB) and the protection motivation theory (PMT), investigated the determinants of consumer behavior in the purchase of daily necessities following the COVID-19 outbreak. In light of the possibility that the pandemic could have caused a new pattern of consumer behavior during the endemic phase, a convenience sampling of 1438 respondents was conducted. Using Partial Least Square Structural Equation Modelling (PLS-SEM), the present study found that choice, information, and perceived economic stability (PES) positively affected consumer behavior, while COVID-19 and risk had negative effects. Interestingly, stress had no impact on consumer behavior. These findings provide valuable insights for companies desiring to understand and anticipate customer behavior during and beyond the pandemic. The present study not only identifies the factors influencing consumer behavior but also enables salespeople to develop strategies to proactively address changes in consumer behaviors.

After almost two years of stalling, the tourism sector is now thriving as we move into the Covid-19 endemic phase, making travel safer. Therefore, continuous use of personalized immersive technology that can deliver timely information and shield users from the outbreak is essential. This study looks at how travellers intend to continue using e-tourism technologies which include augmented reality, social media, smartphone apps, smart technologies, websites and reservation systems. Purposive sampling was used to select 200 respondents who were above 18 years old to participate in a survey that was based on the ExpectationConfirmation Model. The acquired data was then examined using PLS SEM for hypothesis testing. The results showed that satisfaction with e-tourism technologies was the most significant predictor of motivation to keep using such technologies. Further discussion includes contributions to the field of knowledge as well as for players, developers and service providers in the tourism sector.