Essays on the elements of consumer journeys in retailing

By: Material type: TextTextPublication details: Ahmedabad Indian Institute of Management 2023Description: 126p.; ill. Includes tablesSubject(s): DDC classification:
  • TH 2023-15
Summary: I bring in the network theory perspective as an element to study online consumer behaviour. Using the clickstream data, I show how consumer browsing can be interpreted as a network to gain richer insights. I hypothesize using the tenets of network theory, flow of information and orchestration of the flow. I show that when consumers browse, they visit websites multiple times, revisit websites, and sometimes visit only one website to make their decisions. This behaviour is depicted by using three network properties, i.e., total connections (TCs), betweenness centralization (BC), and network density (ND), to determine their average basket value. Further, I examine the moderating role of contingent variables, variety and volume of information on consumer online search behaviour. I find that the ABV decreases when the TCs and BCs increase. However, ABV increases when ND increases. To validate the results, I conduct several robustness checks (involving endogeneity, benchmark models, sample selection bias, omitted variable bias, alternative dependent and independent variables, and four product categories).
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Item type Current library Collection Shelving location Call number Status Date due Barcode
Thesis (FPM) Vikram Sarabhai Library Non-fiction Reference TH 2023-15 (Browse shelf(Opens below)) Not for Issue (Restricted Access) CD002714

Thesis Advisory Committee
Prof. Sourav B. Borah (Chair Person)
Prof. Praveen K. Kopalle (Member)
Prof. Anuj Kapoor (Member)

I bring in the network theory perspective as an element to study online consumer behaviour. Using the clickstream data, I show how consumer browsing can be interpreted as a network to gain richer insights. I hypothesize using the tenets of network theory, flow of information and orchestration of the flow. I show that when consumers browse, they visit websites multiple times, revisit websites, and sometimes visit only one website to make their decisions. This behaviour is depicted by using three network properties, i.e., total connections (TCs), betweenness centralization (BC), and network density (ND), to determine their average basket value. Further, I examine the moderating role of contingent variables, variety and volume of information on consumer online search behaviour. I find that the ABV decreases when the TCs and BCs increase. However, ABV increases when ND increases. To validate the results, I conduct several robustness checks (involving endogeneity, benchmark models, sample selection bias, omitted variable bias, alternative dependent and independent variables, and four product categories).

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