Customer-centric Pricing: Maximizing Revenue Through Understanding Customer Behavior

Date

December 2023

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Abstract

Advances in online retail infrastructure allows retailers and researchers to keep track of various attributes including customer demographics and online behaviors on the website. The thesis studies the gaps between theoretical results and empirical data that can be attributed to human behavior when faced with pricing and operational situations. In particular, we study the effect of anticipated regret on purchase decisions of customers who face a markdown pricing structure. In subsequent study, we assess the impact of a retailer’s frequent price adjustments on customers’ long term expenditure in the retailer. By this, we aim to fill the gap in the revenue management literature that mainly focuses on retailer’s pricing optimization problem and thus, leaves room for deeper understanding of customer’s perception towards frequent price changes. I identify these behavioral motives that have previously received less attention from conventional pricing and operations management literature, carefully model them using probabilistic and/or statistical modeling methods, and estimate and quantify the effects to operationalize these factors.

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Business Administration, General, Operations Research

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