PhD Defence Wei Li


In her dissertation 'Competition in the Retail Market of Consumer Packaged Goods’, Wei Li investigated competition in the retail market of consumer packaged goods from different angles. The study on brand competitive reactions has found that the reaction is influenced by brands’ relative market shares. The study on retail chain competition has found that private label positioning has an impact on chain shares’ price sensitivities. The study on sales forecasting compared different methods of including competition information. Wei Li has defended her dissertation on Thursday, 14 January 2021 at 09:30h. Her supervisors were Prof. Dennis Fok (ESE) and Prof. Philip Hans Franses (ESE). Other members of the Doctoral Committee were Prof. Richard Paap (ESE), Prof. Bas Donkers (ESE), Prof. Francesca Sotgiu (Vrije Universiteit Amsterdam), Dr Jason Roos (RSM) and Prof. Tammo H. A. Bijmolt (University of Groningen).

About Wei Li

Wei Li was born and brought up in Hubei, China. She holds a Bachelor's and a Master's degree in International Economics from Wuhan University, China. In 2006, she joined the MPhil programme of Erasmus Research Institute of Management (ERIM) on marketing track. After she obtained a Master's degree in Business Research she continued her PhD study under the supervision of Prof. Dennis Fok and Prof. Philip Hans Franses. Her research is concerned with using quantitative methods to study competition in retail market. Her work has been presented at INFORMS Marketing Science Conferences. She moved to London in 2012 and worked for a marketing consultancy company based there. Later she moved again to Nottingham and now works for the University of Nottingham as a research and teaching fellow.

Thesis Abstract

This dissertation investigates competition in the retail market of consumer-packaged goods from different angles. Chapter 2 studies how brands react to each other’s price promotions, the focus is put on the asymmetric reactions between brands with different market shares and price levels. To this end a Hierarchical Bayes Ordered Probit model (HB-OP) is employed to study the moderating factors on reactions. The results show that the reaction intentions are influenced by brands’ relative market shares, together with some category specific characteristics. Chapter 3 investigates the competition between retail chains and the role of their private label brands. We propose a Hierarchical Bayes Market Share (HB-MS) model to investigate how a retailer’s market share depends on price changes by national brands and private labels, and how the baseline market share and the price sensitivities are influenced by private-label positioning. Chapter 4 aims to compare traditional sales forecasting models with modern techniques like factor models, Lasso, elastic net, random forests and boosting methods. We consider all possible brands as potential competitors that might be useful for the sales forecasts of a focal brand. This approach is relevant if we do not know beforehand which brands have predictive content, and in this case, we can let the data help to decide on this each time we make a forecast. The forecasting accuracy of a variety of models are compared across a large number of brands.