I joined Bocconi University in 2016 and my research lies in the field of quantitative marketing with a strong focus on empirical analysis of the inter-related decisions made by manufacturers, retailers and consumers.
I earned a PhD in marketing from London Business School, an MSc in economics from the London School of Economics, and a BA in economics from Sogang University. Prior to my doctoral studies, I gained industry experience in the marketing field at Unilever and Nielsen (KR) and I worked as a research fellow at International Growth Centre (UK).
Throughout the courses, I provide students with hands-on experience in analyzing various real-word data associated with marketing decision making.
In my recent study, I look at firms’ product assortment decisions in response to commodity tax change. Many countries around the world are adopting new commodity taxes to reduce consumption of unhealthy products. The policy and academic discussions have focused on tax implications via final price change. This study shows that a tax increase is also followed by a significant drop in number and variety of product offerings. The findings have important policy implications for research examining the impact of taxes on market outcomes.
My research efforts aim to apply theories and methods from economics and econometrics to interesting marketing problems. My early work investigates how grocers’ product assortment from multiple product categories in a common retail space influences consumers’ purchase decisions. The article has been published in Journal of Marketing and featured as “Journal Selection” by Marketing Science Institute in 2017.
My recent work expands the research domain by 1) looking at the firm’s product assortment decision as a response to a government intervention (e.g., taxation), and 2) studying firm’s competition in quality of products and services. The empirical study of competition in product quality is particularly challenging as there is little reliable data available. To overcome this, my recent study extracts previously non-available information from various text data (e.g., online customer reviews) using latest text analysis methods.