Three Essays on Modeling Consumer Behavior and Its Operations Management Implications.

Traditionally, models used in operations management have considered the firm side of the problem by making simplifying assumptions on demand or market. In practice, however, consumers or agents in the market actively make decisions or choices based on self interest. This dissertation aims to analyze how insights and results from traditional models are affected when we account for such active decision making by consumers or the market. In Chapter II, we study how the customers' decision of joining the queue to receive a service varies by the individual incentive as well as the firm's capacity decision, which also depends on the firm’s selfishness. By considering three customer types: individual, collective, and social, and two firm types: profit maximizing and welfare maximizing, we are able to disentangle the effects of selfishness of the customers and the firm, and the interactions between these two in equilibrium. Among other results, we find that there can be a ``benefit of selfishness'' to consumers and the system, in contrast to the price of anarchy literature. In Chapter III, we discuss the customers' redemption behavior of loyalty points and its impact on the seller's pricing and inventory rationing strategy. We model the customer choice between cash or loyalty points by characterizing consumers in three dimensions: the reservation price, the point balance, and their perceived valuation of points. Applying this choice model into the seller's dynamic pricing model, we characterize the seller's optimal strategy that specifies the optimal price, the control of reward sales (black-out), and the redemption points. In Chapter IV, we study the customers’ substitution behavior when their preferred product is not available, and the seller's assortment optimization problem. Motivated by the exogenous demand model and the recently developed Markov chain model, we propose a new approximation to the random utility customer choice model called rescaled multi-attempt model. The key feature of our proposed approach is that the resulting approximate choice probability can be explicitly written. From a practical perspective, this allows the decision maker to use an off-the-shelf solver to solve a general assortment optimization problem with a variety of real-world constraints.PhDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133387/1/hakjin_1.pd

Dynamic Pricing with Point Redemption

Many sellers allow consumers to pay with reward points instead of cash or credit card. While the revenue implications of cash purchases are transparent, the implication of reward sales is not trivial, when a firm that issues points is not a seller. In this case, a seller receives a compensation from the point issuer when a consumer purchases the good with points. We examine how reward sales influence a seller's pricing and inventory decisions. We consider a consumer who can choose to pay with cash or points based on reservation price, point balance, and the perceived value of a point. Then, we incorporate this into a pricing model where a seller earns revenues from both cash and reward sales. In contrast to an intuition that reward sales will increase sales and revenue, we show that the effect of reward sales on the seller's price is non-trivial as the seller could either add a premium or discount depending on the inventory level, time, and the reimbursement rate. Furthermore, such price adjustments can attenuate the optimal mark-up or mark-down level, and reduce the price fluctuation caused by inventory level and remaining time. We investigate settings where the seller has different operational controls over reward sales and find that allowing reward sales is still better even when the revenue from the reward sales is smaller than the cash sales. We also find that a seller with an ability to control availability (i.e., allow a reward sale or not) can achieve a revenue similar to the revenue of a seller with an ability to change point requirements and price.https://deepblue.lib.umich.edu/bitstream/2027.42/142796/1/1377_Ahn.pd

On (Re-Scaled) Multi-Attempt Approximation of Customer Choice Model and its Application to Assortment Optimization

Motivated by the classic exogenous demand model and the recently developed Markov chain model, we propose a new approximation to the general customer choice model based on random utility called multi-attempt model, in which a customer may consider several substitutes before finally deciding to not purchase anything. We show that the approximation error of multi-attempt model decreases exponentially in the number of attempts. However, despite its strong theoretical performance, the empirical performance of multi-attempt model is not satisfactory. This motivates us to construct a modification of multi-attempt model called re-scaled multi-attempt model. We show that re-scaled 2-attempt model is exact when the underlying true choice model is Multinomial Logit (MNL); if, however, the underlying true choice model is not MNL, we show numerically that the approximation quality of re-scaled 2-attempt model is very close to that of Markov chain model. The key feature of our proposed approach is that the resulting approximate choice probability can be explicitly written. From a practical perspective, this allows the decision maker to use off-the-shelf solvers, or borrow existing algorithms from literature, to solve a general assortment optimization problem with a variety of real-world constraints.http://deepblue.lib.umich.edu/bitstream/2027.42/122455/1/1322_Ahn.pd

The Effects of Operational Efficiency and Environmental Risk on the Adoption of Environmental Management Practices

Given that prior research has provided inconsistent findings on the relationship between financial performance and the adoption of environmental management practices (EMPs), we aim to resolve the inconsistency by positing that the firm may consider different components of financial performance when making decisions. Specifically, we maintain that operational efficiency, measured based on net profit margin, is a key determinant of a firm’s decision to adopt EMPs. Additionally, we aim to examine environmental risk as one contingency that moderates the relationship between operational efficiency and EMP adoption. Employing a firm-fixed effect model to examine the effects of various measures of financial performance, including the net profit margin, return on asset (ROA), return on equity (ROE), and asset turnover, on the adoption rates of EMPs by firms, we find that firms with higher operational efficiency measured based on net profit margin are more inclined to adopt EMPs, while measures such as ROA, ROE, and asset turnover do not demonstrate any substantial effect. This study also finds that while environmental risk increases the possibility of adopting EMPs, it weakens the impact of operational efficiency on the adoption rates of EMPs