Karen Zheng

 

Faculty Speaker Professor Karen Zheng [Massachusetts Institute of Technology]
Title Establishing Socially Responsible Supply Chains: Transparency, Consumer Behavior, and Supply Chain Structure

Date & Time Friday, November 20, 2015 at 10:30am
Place UCLA Anderson School of Management 
Room D-310 

 

Abstract
In this talk, we will present recent research on two topics of supply chain social responsibility: responsible practices in the upstream supply chain and managing economically motivated adulteration in food products. In the first paper, we design an incentivized controlled laboratory experiment to study how much and why consumers value transparency regarding a company's responsible practices in its upstream supply chain. Lower transparency is modeled by higher uncertainty in the outcome of the company's practices. We (1) measure whether and by how much improved transparency affects consumers' willingness-to-pay (WTP), and (2) investigate how consumers' WTP may be influenced by their reciprocal motives (rewarding a company for its responsible practices) and prosocial orientations (natural propensities to care about others' well-being). Our results demonstrate that consumers are willing to pay a higher price for products with a higher level of transparency. There also exists an important interplay among transparency, reciprocal motives, and prosocial orientations. While reciprocal motives play a minimal role in affecting high prosocial consumers' WTP, low prosocial consumers demonstrate strong reciprocity as long as the level of transparency is not low. Our results provide insights into the benefits of supply chain transparency and how to better communicate social responsibility practices to consumers.

In the second paper, we empirically and analytically investigate how supply chain structure impacts the risk of economically motivated adulteration (EMA) in farming supply chains. We use farm-level data to quantify the dispersion of a farming supply chain, which measures how distributed a company's farming sources are. Combining farm-level data and quality data associated with the companies in our sample, we empirically demonstrate that a more dispersed farming supply chain is more prone to the risk of EMA. We develop a model to analytically characterize when higher dispersion leads to a higher risk of EMA, as well as the impacts of market prices and inspection frequency on EMA risk. This talk is based on joint work with subsets of the following coauthors: Tim Kraft, Retsef Levi, Somya Singhvi, Shujing Wang, and Leon Valdes.

Karen Zheng