Perils and Fiscal Liabilities in E-Commerce: Implications for Consumer Motivational Dynamics

Introduction: The explosive growth of e-commerce has transformed consumer engagement, offering unmatched convenience and global reach. However, this expansion also introduces significant risks such as data breaches, fraud, and privacy violations, impacting consumer trust and decision-making. Understanding these risks and their influence on consumer behaviours is crucial for improving e-commerce practices and regulatory frameworks. This study investigates the effects of various e-commerce risks on consumer motivation and purchasing behaviours, aiming to uncover factors that influence consumer trust and satisfaction in online shopping. Materials and Methods: The research employs a mixed-methods approach combining qualitative and quantitative techniques. Data were collected through a structured questionnaire, validated with a reliability score of 0.893, and administered to 810 respondents in Bangalore using simple random sampling. The questionnaire covered variables including security risks, privacy concerns, product misrepresentation, hidden fees, shipping costs, and return policies. Data were analyzed using statistical methods such as mean, standard deviation, and regression analysis to assess the impact of these variables on consumer motivation and behaviours. Discussion: The study reveals that security risks and privacy concerns are significant deterrents to online shopping, affecting consumer trust and motivation. Product misrepresentation and hidden fees also rank high among concerns, impacting overall satisfaction and purchase intentions. Despite these challenges, consumers remain inclined to shop online, driven by perceived value and financial incentives. The findings underscore the need for enhanced security measures and transparent practices to mitigate risks and improve consumer trust. Results: Statistical analyses indicate that security risks and hidden fees are major factors influencing consumer behaviours, with high mean scores reflecting significant concerns. Regression analysis highlights the predictive power of these risks on purchase intentions and overall satisfaction. The study concludes that addressing these risks through improved practices and robust consumer protection mechanisms can enhance trust and motivation in e-commerce.