Effects of self-esteem on supply chain decisions

We study the effects of self-esteem on supply chain decisions and profits. To this end, the data obtained in computerized decision-making experiments in which human subjects participated as manufacturers (who offer a contract) and retailers (who either reject the contract, or accept and set the order quantity from the manufacturer) that engage in a long run relationship is used. Rosenberg scale survey data is used to categorize the manufacturers and retailers into high and low self-esteem classes. We find low selfesteem manufacturers to offer more attractive contracts to retailers, obtain lower profits themselves and cause higher supply chain total profit. Contrary to our expectations, we find high self-esteem retailers to end up accepting less favorable contracts compared to low self-esteem retailers, though the difference is not statistically significant. We explain this phenomena with the overordering tendency of the high self-esteem retailers: They overorder more frequently, and make larger overorders. We observe manufacturers to increase the attractiveness of their contract offer in the next period following a rejection. Finally, we develop a regression model to explain retailer order quantity decisions based on the retailer self-esteem score, lost demand in the previous period, number of contract rejections in the relationship, and the optimal order quantity. Our results indicate the importance of self-esteem as a significant factor in supply chain decisions and firms’ profit performance

Retail Demand Management: Forecasting, Assortment Planning and Pricing

In the first part of the dissertation, we focus on the retailer\u27s problem of forecasting demand for products in a category (including those that they have never carried before), optimizing the selected assortment, and customizing the assortment by store to maximize chain-wide revenues or profits. We develop algorithms for demand forecasting and assortment optimization, and demonstrate their use in practical applications. In the second part, we study the sensitivity of the optimal assortment to the underlying assumptions made about demand, substitution and inventory. In particular, we explore the impact of choice model mis-specification and ignoring stock-outs on the optimal profits. We develop bounds on the optimality gap in terms of demand variability, in-stock rate and consumer heterogeneity. Understanding this sensitivity is key to developing more robust approaches to assortment optimization. In the third and final part of the dissertation, we study how the seat value perceived by consumers attending an event in a stadium, depends on the location of their seat relative to the field. We develop a measure of seat value, called the Seat Value Index (SVI), and relate it to seat location and consumer characteristics. We apply our methodology to a proprietary dataset collected by a professional baseball franchise in Japan. Based on the observed heterogeneity in SVI, we provide segment-specific pricing recommendations to achieve a service level objective

The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior

“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic.postprin

Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm\u27s demand and cares about the short-term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least-cost separating equilibrium will result, in which a low-quality firm chooses its optimal capacity and a high-quality firm over-invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low-quality firms over-invest and high-quality firms under-invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least-cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used

COOPERATION OR COMPETITION: A STUDY OF SOCIAL CAPITAL AND PRODUCTION DECISION UNDER POTENTIAL VERTICAL COMPETITION

Since the 2000s when retailers recognised the huge market potential, the growth of private labels has been unstoppable worldwide. As a result of the recession of national brands, manufacturers are in a relatively weaker position when dealing with large retailers. The relationship between manufacturers and retailers has transformed from pure cooperation to a delicate balance of cooperation and competition. Yet, how such a balance influences supply chain dynamics is an intriguing and overdue issue. This thesis explores the influence of social capital over manufacturers’ perceptions regarding their retailers’ trustworthiness in the presence of potential vertical competition, as well as the consequential performance from the perspective of cognitive abilities. Data was collected through an online scenario-based role play (SBRP) experiment, where 371 participants were recruited and put in three groups. In each group, participants were provided with a scenario depicting the product substitution level between a newly launched private label and a national brand. The data was analysed statistically to test the hypotheses. The results identify relational capital as the most influential dimension of social capital in suppressing manufacturer’s perception of opportunistic information sharing behaviour from retailers, and suggest that such suppression is moderated by the level of product substitution between private labels and national brands. This thesis has reference value to academia by looking into the overlapping issues of supply chain management and marketing and providing empirical evidence of the influences induced by the introduction of private labels. It also benefits industry, especially manufacturers, by giving a brief standard regarding whether to cooperate or compete when faced with potential vertical competition with retailers

Strategic risk in contract design

Supply chains facing asymmetric information can either operate in a cooperative mode with information and benefit sharing or can choose a non-cooperative form of interaction and align their incentives via screening contracts. In the cooperative mode, supply chain efficiency can be achieved, but high levels of trust and trustworthiness are required. In the non-cooperative mode, the contract mechanism guarantees a second best supply chain performance, but only if all parties choose their equilibrium strategies without trembles. Experimental evidence, however, shows that both operating modes often fail due to strategic risk. Cooperation is disrupted by deceptive signals and the lack of trust, whereas non-cooperative strategies suffer from persistent out-of-equilibrium behavior. We present an experiment on supply chain interaction with reduced strategic risk in both operating modes. We find that supply chain performance can reach a second-best level in either operating mode, if strategic risk is sufficiently reduced. We present two means to reduce strategic risk. First, a punishment mechanism leads to a better matching of trust and trustworthiness and supports the cooperative operating mode. Second, an enforcement of self-selection supports the non-cooperative equilibrium by increasing the attractiveness of screening contracts. We conclude that supply chain managers should seek to reduce the variability of the supply chain partners\u27 behavior no matter what operating mode is considered