The Two-Stage Decision Process During Online Purchasing -Empirical and Observation Field Studies on Cognitive, Affective and Behavior Outcomes

Of the past 20 years, online shopping has gained growing importance in both consumers' daily life and the retail industry. E-retailers such as Amazon create new sales records yearly. However, there is a big challenge for e-retailers to maintain impressive sales and meanwhile handle the increasing returns (i.e., consumers returning products to get their money back). Although several researchers have identified a need for more research regarding why and how consumers make series decisions to purchase and return items, limited research has been conducted in this context. Utility theory is widely used to explain consumers’ purchase and return decisions separately. However, less research considers emotions as part of consumers’ decision-making process. Against this backdrop, this thesis presents three studies of consumers’ purchase decisions, return decisions and the integrated reaction process. The first draws on the random utility model by using the choice based conjoint analysis method. A laboratory experiment reveals that providing comprehensive services could efficiently enhance consumers’ purchase intentions in the electric vehicle market. The second study is from the perspective of small- and middle-size e-retailers. We analyzed the transactional data from a Chinese e-platform, and found that return policies' credibility has a positive influence on both sales and returns. The third study focuses on identifying the processes involved in consumers’ return decisions in online purchasing markets by considering both cognitive reactions (utility-based) and affective reactions (emotion-based). The results of two experiments and a field study show that comprehensive services such as a gift and a colorful package can reduce consumers’ return intentions by increasing the perceived utilities and creating positive emotions. By demonstrating why and how businesses can influence purchase and return decisions, this thesis enriches the consumer behavior research. E-retailers may use the results to understand consumer behavior better and provide advanced services and policies to attract purchases and meanwhile avoid unnecessary returns.