ESSAYS IN (I) STRATEGIC ORDERING WITH ENDOGENOUS SEQUENCE OF EVENTS IN SUPPLY CHAIN (II) STRATEGIC MANAGEMENT OF NEW PRODUCT INNOVATION AND PROCESS IMPROVEMENT

This dissertation discusses two research problems. First topic is strategic information management in supply chain, and second topic is analytical modeling approach in productivity dilemma. The first two chapters of dissertation discuss the impact of information asymmetry and competition on vertical contractual relationships, and risk neutral firms' strategic ordering decisions with minimal assumptions. Modern business environment caused by competition and information asymmetry plagues most firms across industries, often leading to suboptimal outcomes. Given the lead times in planning capacity, suppliers prefer earlier orders from their downstream partners (retailers). Much attention has been given in the literature to Advance Purchase Discount (APD), where the supplier lowers the wholesale price to entice the retailers to order early. In this dissertation, we suggest another avenue of early purchase model considering more realistic ways - competition between downstream retailers and information flows (from information acquisition to dissemination) in supply chain. We show that with one retailer having "better" market demand information on uncertain demand than the other, the supplier can induce earlier ordering from the better-informed retailer without any reduction in the wholesale price, or creating rationing risk. In addition, we investigate firm's information investment decisions corresponding to the timing of the orders. We extend the model with different information structures of firms such as imperfect and evolving information. In reality, firms can have more accurate market information near the selling season by acquiring it from more diverse resources. Consistent with practice, we explorer firm's equilibrium outcomes of endogenous sequencing game with this setting. The third chapter of dissertation is in the trade-off between production efficiency and new product innovation. A firm's ability to compete over time has been rooted not only in improved efficiency, but also in its ability to be simultaneously innovative (Abernathy (1978)). This trade-off between efficiency and innovation has long been discussed in the business context, but limited analytical research has been done using the `extreme value theory' (Dahan & Mendelson (2001)) to investigate this issue. Our model considers important exogenous innovation factors such as innovation characteristics (Benner & Tushman (2003)) and degree of competition, which has yielded the following theoretical results and practical implications. First, we highlight new product characteristics. If R&D projects are paradigm-shifting innovations, there is a stronger adverse effect between efficiency and innovation than incremental innovation. Second, competition results in underinvestment effort in innovation performance for the firms. For example, in the symmetric firms' competition, the optimal size of R&D projects decreased, as competition increases. On the other hand, firms are more likely to focus on process improvement activities

The Newsvendor Problem: Review and Directions for Future Research

In this paper, we review the contributions to date for analyzing the newsvendor problem. Our focus is on examining the specific extensions for analyzing this problem in the context of modeling customer demand, supplier costs, and the buyer risk profile. More specifically, we analyze the impact of market price, marketing effort, and stocking quantity on customer demand; how supplier prices can serve as a coordination mechanism in a supply chain setting; integrating alternative supplier pricing policies within the newsvendor framework; and how the buyer’s risk profile moderates the newsvendor order quantity decision. For each of these areas,we summarize the current literature and develop extensions. Finally, we also propose directions for future research

Behavioral analyses of retailers’ ordering decisions

The main objective I pursue in this thesis is to better understand how different factors may independently and in combination influence retailers' ordering decisions under different supply chain structures (single agent and multi agent), different demand uncertainty (deterministic and stochastic), and different interaction among retailers (no interaction, competition and cooperation). I developed three different studies where I build on different formal management model and then run multiple behavioral studies to better understand subjects’ behavior. The first study analyzes order amplification in a single-supplier single-retailer supply chain. I used a behavioral experiment to test retailers’ orders under different ordering delays and different times to build supplier’s capacity. Results provide (i) a better understanding of the endogenous dynamics leading to retailers’ ordering amplification, and (ii) a description of subjects’ biases and deviation from optimal trajectories; despite subjects have full information about the system structure. The second study analyzes how order amplification can also take place when there is fierce retailer competition and limited supplier capacity. I study how different factors (different time to build supplier capacity, different levels of competition among retailers, different magnitudes of supply shortage and different allocation mechanisms) may independently and in combination influence retailers’ order in a system with two retailers under supply competition. Results show that (i) the bullwhip effect persists even when subjects do not have incentives to deviate, (ii) subjects amplify their orders in an attempt to build an unnecessary safety stock to respond to potential deviations from the other retailers, and (iii) retailers’ underperformance varies with the allocation mechanism used by the supplier. In the last study, I analyze retailers’ orders in a system where there is uncertainty in the final customer demand. I experimentally explore the effect of transshipments among retailers in a single-supplier multi-retailer supply chain. Specifically, I explore retailers’ orders under different profit and communication conditions. In addition, I integrate analytical and behavioral models to improve supply chain performance. Results show that (i) the persistence of common biases in a newsvendor problem (pull-to-center, demand chasing, loss aversion, psychological disutility), (ii) communication could improve coordination and may reduce demand chasing behavior, (iii) supply chain performance increases with the use of behavioral strategies embedded within a traditional optimization model, and (iv) dynamic heuristics improve overall coordination, outperforming a simple Nash Equilibrium strategy

A coordination mechanism for supply chains with capacity expansions and order-dependent lead times

This paper considers a supply chain consisting of a retailer for short life cycle products facing stochastic customer demand and a manufacturer that initiates production upon receipt of retail orders. Departing from the common view of the newsvendor problem, we assume that the delivery lead time is not fixed, but that both the retailer and the manufacturer have the option to shorten it. Shorter lead times enable the retailer to place orders closer to the start of the selling season where additional information on customer preferences has become available, reducing demand uncertainty. In the work at hand, lead time is assumed to depend on the order quantity, on the supplier's production capacity, and a fixed transportation delay. This paper proposes a model for determining the optimal order quantity and production capacity in centralized and decentralized settings. For the uncoordinated case, we show that if the retailer's ability to gather and analyze additional demand information is revealed to the manufacturer, the arising information asymmetry between the two parties can aggravate the double marginalization effect and, in turn, erode supply chain efficiency. In a coordinated supply chain, however, both parties have an incentive to align both order quantity and investments in lead time reduction. To coordinate the decentralized supply chain, we propose a buy-back contract that helps to leverage supply chain profitability. We conclude with an outlook on future research opportunities

Inventory redistribution for fashion products under demand parameter update

Demand for fashion products is usually highly uncertain. Often, there is only one possibility for procurement before the selling season. In order to improve the traditional newsvendor-type overage-underage trade-off we study a network of two expected profit maximizing retailers selling a fashion product where there is an additional opportunity for redistribution of stock during the selling season. We distinguish between the situation where redistribution is done at the moment when one of the retailers is running out of stock and the situation where the redistribution time is already determined and fixed before the selling season. We model the demand process at a retailer by a Poisson Process with an uncertain mean and use a Bayesian approach to update the distribution parameters before transshipments are done. In a numerical study we compare the different policies and show that timing flexibility and updating are especially beneficial in situations with low profit margins and high parameter uncertainty. Further, we show that depending on the instance, an optimal predetermined transshipment timing depends on the problem parameters and may be between the middle and the end of the selling season

Essays in inventory decisions under uncertainty

Uncertainty is a norm in business decisions. In this research, we focus on the inventory decisions for companies with uncertain customer demands. We first investigate forward buying strategies for single stage inventory decisions. The situation is common in commodity industry where prices often fluctuate significantly from one purchasing opportunity to the next and demands are random. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. Second, we study the complexities of bundling of products in an Assemble-To-Order (ATO) environment. We outline a salvage manipulator mechanism that coordinates the decentralized supply chain. Third, we extend our salvage manipulator mechanism to a two stage supply chain with a long cumulative lead time. With significant lead times, the assumption that the suppliers all see the same demand distribution as the retailer cannot be used.Ph.D.Committee Chair: Yih-Long Chang; Committee Member: Paul Griffin; Committee Member: Ravi Subramanian; Committee Member: Soumen Ghosh; Committee Member: Srinagesh Gavirnen

Supply chain responsiveness for a large retailer

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 73).A large U.S. based retailer underwent a large, complex multi-year supply chain network transformation. This transformation resulted in significant savings in logistics costs. Additionally, the regional distribution center that was introduced as part of this transformation as a new node between the supplier and the store became the decision making center for placing purchase orders with suppliers and for receiving and shipping the purchase order to individual stores. This resulted in longer lead times causing a change in the in-store units held and therefore, directly impacting the net sales. This thesis focuses on establishing the relationship between the stores performance and lead-time, review-time combinations in both supply chain networks, the original direct to store and the new regional distribution based networks.by Sunil Anand and Xiaobei Song.M.Eng.in Logistic

Behavioral perspectives on risk sharing in supply chains

Over the past decade, we have witnessed the emergence of a vast body of literature contributing to our understanding of how supply chains should be designed and executed from a normative perspective. Along the way, the gap between ever-more sophisticated theory and industrial reality increased. A growing stream of recent research relaxes the overly simplistic assumptions on human behavior commonly made in supply chain models. This thesis contains a set of research papers on human behavior, casted in a unified framework of supply chain inventory risk management