1,721,010 research outputs found
Product recall timing optimization using dynamic programming
No full textIn this paper we treat the optimal timing of product recall decisions as a dynamic process with defect rate as a random variable. We first develop an optimal stopping model where the defect rate is a beta random variable that is constant across all periods. We solve the problem using stochastic dynamic programming (DP) and develop thresholds for optimal stopping based on the observed value of the number of returns as a state variable. We then extend the model where the beta defect rate random variable is revised using Bayesian updating in each period after observing the number of product returns from the preceding period. Employing the conjugate property of the beta and binomial, we again solve the problem as a stochastic DP and determine the thresholds based on the values of the state vector with three variables. We show that for the more general version, the computational difficulty increases dramatically with problem size. For this problem we present a simulation optimization approach that selects the best functional form for the threshold curve. Several examples and managerial insights illustrate our findings
Optimal Ordering Decision and Incentives for Yield Improvement under Random Demand
Full text linkIn this thesis, we focus on the applications of incentive mechanism design in operations and supply chain management (OSCM). Most significant--and interesting--topics arising in OSCM are concerned with the management of relationships among supply chain members under asymmetric information. Since the incentive mechanism design based on the principal-agent model deals with asymmetric information in a satisfactory way, it has become an important tool in investigating OSCM-related asymmetric information problems.
We start with an introduction in Chapter 1. In this chapter, we briefly describe the theory of incentive mechanism design and its applications to OSCM, and the organization structure of this thesis. In Chapter 2, we study the optimal wage scheme and effort level in a contracting problem where both the principal and the agent are risk-averse. This chapter is a starting point for analyzing the buyer's optimal ordering decision and incentives for yield improvement in Chapters 3 and 4. Chapter 3 investigates the buyer's optimal ordering decision and incentives for yield improvement in the setting of random yield for the critical component and uncertain demand for the finished product. In Chapter 4, we assume the supplier's effort and yield become continuous and study a continuous optimization problem where the buyer decides the optimal order quantities and incentives for yield improvement under random demand. Our thesis ends with a conclusion and addresses the future research in Chapter 5.ThesisDoctor of Philosophy (PhD
Game Theoretic Revenue Management Models for Hotel Room Inventory Control
No full text In this thesis, we focus on the rationing polices for the hotel room inventory control problems. Our study begins with a brief overview of revenue management in hotel industry, emphasizing the importance of room inventory control in revenue management problems. Mathematical models for controlling the room inventory in the literature are then reviewed along with recently developed game theoretic applications in revenue management. In game theoretic context, we establish three types of models to solve the hotel room inventory control problem in three different situations: 1) two-player two-fare-class static single-period game with complete information; 2) two-player two-fare-class dynamic multiple-period game with complete information; and 3) two-player two-fare-class single-period game with incomplete information. In the first situation, we find the existence of unique Nash equilibrium and Stackelberg equilibrium in the non-cooperative case. We provide the exact forms for these equilibria and corresponding conditions. Next, under the dynamic game settings, we provide the sufficient conditions for the unique Nash equilibrium. In the last situation, we consider the static single-period games with incomplete information and discuss the optimal strategies for the uninformed case, secret information case, private information case and public information case. The unique Bayesian Nash equilibrium in each case is found. We then analyze the values of different types of information and study their relations in different situations. Under each game theoretic setting, we present the managerial implications of our solutions along with the numerical examples. The thesis is concluded by a discussion of how game theory can is useful in hotel industry, and its relationship to other topics in revenue management.ThesisDoctor of Philosophy (PhD
Three Essays on Product Recall Decision Optimization
Full text linkThis thesis examines decision optimization of product recalls. Product recalls in recent years have shown unprecedented impact on both immediate economic and reputational damage to the company and long-lasting impact on the brand and industry. Admittedly, imperfect product quality makes recalls inevitable. Thus, we explore from three perspectives to elicit business insights regarding better management and risk control.
Chapter 1 introduces the topic of product recall management optimization and its real-world motivation.
Chapter 2 views the decision making of "when to initiate a product recall" as a dynamic process and takes the feedback of customer returns to update the product defect rate. Updating is simplified by the conjugate properties of beta distribution and Bernoulli trials. We develop the optimal stopping model to find the thresholds of total product returns above which initiating recall is optimal. We implement dynamic programming to solve the model optimally. For large-size problems, we propose a simulation method to balance computation time with solution quality.
Chapter 3 allows the company to control the recall risk by investing in quality. We adopt the one-stage stochastic newsvendor model and add quality-dependent recall risk. The resulting model is not concave in production quantity and quality levels. The parametric analysis reveals several interesting features such as the optimal ordering quantity and quality level have a conflicting relationship. We further extend our model from internal supply to external supply from multiple sources.
Chapter 4 examines managing product recalls from the closed-loop supply chain management and disruption management perspectives. We model the location and allocation decisions of both manufacturing plants and reprocessing facilities where facilities are built after the recalls. Numerical experiments show the costs of overlooking potential recalls vary greatly, indicating the necessity of considering recalls in initial designs and the importance of accurate recall probability prediction.
Chapter 5 summarizes.ThesisDoctor of Philosophy (PhD
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
REVENUE AND RETURN MANAGEMENT IN E-COMMERCE
No full textIn this dissertation, we explore the intersection of return management and dynamic pricing strategies in online retailing. The dissertation consists of five chapters. In Chapter 1, we present the research motivations and provide an overview of the problems studied. Chapter 2 investigates the \Returnless Refund" policy, a novel return strategy in which retailers offer a full refund without requiring customers to return the product. We show that the optimal returnless refund policy is in the form of a threshold policy, offering a returnless refund when the salvage value of the returned product is below a positive threshold. This method allows retailers to decide between granting a refund and reselling the product efficiently. It is also shown that, for items with a high expected salvage value, this threshold-based policy is advantageous for both retailers and customers. We also show that in the early stages of policy implementation, when customers are unaware of returnless refunds, a naive policy is optimal, but the threshold rises as customer awareness increases. Furthermore, our findings show that dishonest customers, who may fake request a return to exploit this policy, can enhance the retailer profits when the price exceeds a certain level. In Chapter 3, we study a conservative dynamic pricing problem with demand learning in the presence of covariates, where the demand function follows a generalized linear model. We address managers’ concerns about transitioning from a legacy pricing system to a learning-based approach, focusing on risks of revenue loss. We propose two dynamic pricing models. The first, a stage-wise safe model, ensures that the instantaneous expected revenue from algorithmic pricing matches or exceeds a fraction of the baseline policy’s revenue in each period. Using a modified UCB algorithm, we show that the regret of this model is composed of two parts: the regret from the learning process and the regret from applying perturbed baseline prices. The second, a cumulative revenue safe, model extends this by ensuring the algorithm’s cumulative revenue meets a target compared to the baseline. Our analysis shows that the algorithm uses the baseline prices a finite number of times, even when the expected revenue of the baseline prices must be learned, offering a balance between exploration and revenue safety constraints.
Chapter 4 addresses a dynamic pricing problem where customers can return products within a specified grace window, and purchasing and returning probabilities are unknown. We propose two approaches: in the first approach, the retailer learns the probabilities separately, leading to a higher regret due to censored data from return decisions. The second approach focuses on joint learning, where the final demand |calculated as the product of purchasing and keeping probabilities |is learned directly, resulting in lower overall regret. For both approaches, we extend the analysis to scenarios where return delays are dominated by a Pareto distribution. Finally, Chapter 5 summarizes the contributions and suggests directions for future research.DissertationDoctor of Philosophy (PhD
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Pricing, Returns, and Donations in Single- and Dual-Channel Retailing
Full text linkIn this dissertation, we study the operational planning problem of a retailer under single- and dual-channel settings with product returns and donations considerations. It is composed of 6 chapters. Having provided the overview and motivation of this work in Chapter 1, we present a structured literature review of the bricks-and-clicks dual-channels in Chapter 2. Next, we propose a quality-dependent newsvendor problem, which models a socially responsible food-retailer's operational planning problem for a continuously deteriorating inventory over two periods with the consideration of donation and quality-sensitive customers in Chapter 3. The retailer's operational planning comprises of inventory and pricing decisions, where she plans not only for the purchase of the goods but also for donating them. We assume each unit of donation generates a constant reward derived from a blend of government incentives and the improved public image of the company due to its corporate social responsibility effort. Our results reveal that charitable donations can enhance the profit while at the same time mitigate the waste and the retailer's optimal donation volume is increasing (decreasing) in the donation reward (quality of the goods). We extend this model in Chapter 4 to incorporate a tax deduction policy into the retailer's problem and examine the impacts of quality and tax subsidy parameters on the retailer's optimal decisions. Although the retailer is still better off engaging in donations, we observe that a larger tax subsidy (higher quality) does not always bring in more (less) donations. In Chapter 5, we develop an analytical model to help a bricks-and-clicks dual channel retailer determine the optimal price in each channel and whether to welcome the cross-channel returns to her physical facility. We find that the cross-channel returns are likely to cannibalize the physical channel sales and may hurt the retailer's profit when customer returns are highly sensitive to refund. Finally, Chapter 6 summarizes our main contributions and proposes future research directions.ThesisCandidate in Philosoph
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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