A Network View of Customer Browsing and Purchase Decisions
(A2024-119459)

AUTHORS

Laxminarayana Yashaswy Akella, Indian Institute of Management Ahmedabad; praveen kopalle, Dartmouth College; Anirban Adhikary, Indian Institute of Management Udaipur; Sourav Borah, Indian Institute of Management Ahmedabad; Amalesh Sharma, Mays Business School, Texas A&M University

ABSTRACT

We simulate customers’ browsing behaviour across several websites as by considering the network theory approach. Accordingly, we ask: (i) whether a network perspective significantly explain customers’ online purchase behavior, (ii) identify which network properties significantly impact customers’ average basket value (ABV), and (iii) examine the moderating role of variety and volume of information on consumers’ online search behavior. We analyse the influence of network characteristics (i.e., total connections, betweenness centralization, and network density) on ABV using clickstream data from 1,261 consumers and find that the ABV decreases when total connections and betweenness centralization increase. Meanwhile, we find that ABV increases when network density increases. For robustness, we include benchmark models, sample selection bias, omitted variable bias, alternate dependent and independent variables, and four product categories. Finally, we discuss the management implications of our research in terms of classifying customers and predicting their average basket value.