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"Inventory control, production control. Distribution"
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Fashion logistics : insights into the fashion retail supply chain
\"Looking at responsible fashion retailing and cost-effective supply chain management, Fashion Logistics examines the early growth and changes in the fashion industry, leading up to the drivers of change in today's market. The book covers international sourcing, merchandising, planning and forecasting, business models, operating strategies, and design distribution models. Along with online supplementary materials for the book in general, each chapter includes figures, tables, references, suggested readings, and mini-case studies with discussion questions\"-- Provided by publisher.
Book
Goodbye Pareto Principle, Hello Long Tail: The Effect of Search Costs on the Concentration of Product Sales
Many markets have historically been dominated by a small number of best-selling products. The Pareto principle, also known as the 80/20 rule, describes this common pattern of sales concentration. However, information technology in general and Internet markets in particular have the potential to substantially increase the collective share of niche products, thereby creating a longer tail in the distribution of sales. This paper investigates the Internet's \"long tail\" phenomenon. By analyzing data collected from a multichannel retailer, it provides empirical evidence that the Internet channel exhibits a significantly less concentrated sales distribution when compared with traditional channels. Previous explanations for this result have focused on differences in product availability between channels. However, we demonstrate that the result survives even when the Internet and traditional channels share exactly the same product availability and prices. Instead, we find that consumers' usage of Internet search and discovery tools, such as recommendation engines, are associated with an increase the share of niche products. We conclude that the Internet's long tail is not solely due to the increase in product selection but may also partly reflect lower search costs on the Internet. If the relationships we uncover persist, the underlying trends in technology portend an ongoing shift in the distribution of product sales.
This paper was accepted by Ramayya Krishnan, information systems.
Journal Article
Regret in the Newsvendor Model with Partial Information
Traditional stochastic inventory models assume full knowledge of the demand probability distribution. However, in practice, it is often difficult to completely characterize the demand distribution, especially in fast-changing markets. In this paper, we study the newsvendor problem with partial information about the demand distribution (e.g., mean, variance, symmetry, unimodality). In particular, we derive the order quantities that minimize the newsvendor's maximum regret of not acting optimally. Most of our solutions are tractable, which makes them attractive for practical application. Our analysis also generates insights into the choice of the demand distribution as an input to the newsvendor model. In particular, the distributions that maximize the entropy perform well under the regret criterion. Our approach can be extended to a variety of problems that require a robust but not conservative solution.
Journal Article
Sharing Demand Information in Competing Supply Chains with Production Diseconomies
This paper studies the incentive for vertical information sharing in competing supply chains with production technologies that exhibit diseconomies of scale. We consider a model of two supply chains each consisting of one manufacturer selling to one retailer, with the retailers engaging in Cournot or Bertrand competition. For Cournot retail competition, we show that information sharing benefits a supply chain when (1) the production diseconomy is large and (2) either competition is less intense or at least one retailer's information is less accurate. A supply chain may become worse off when making its information more accurate or production diseconomy smaller, if such an improvement induces the firms in the rival supply chain to cease sharing information. For Bertrand retail competition, we show that information sharing benefits a supply chain when (1) the production diseconomy is large and (2) either competition is less intense or information is more accurate. Under Bertrand competition a manufacturer may be worse off by receiving information, which is never the case under Cournot competition. Information sharing in one supply chain triggers a competitive reaction from the other supply chain and this reaction is damaging to the first supply chain under Cournot competition but may be beneficial under Bertrand competition.
This paper was accepted by Martin Lariviere, operations management.
Journal Article
Inventory Record Inaccuracy: An Empirical Analysis
Traditional inventory models, with a few exceptions, do not account for the existence of inventory record inaccuracy (IRI), and those that do treat IRI as random. This study explores IRI observed both within and across product categories and retail stores. Examining nearly 370,000 inventory records from 37 stores of one retailer, we find 65% to be inaccurate. We characterize the distribution of IRI and show, using hierarchical linear modeling (HLM), that 26.4% of the total variance in IRI lies between product categories and that 2.7% lies between stores. We identify several factors that mitigate record inaccuracy, such as inventory auditing practices, and several factors that exacerbate record inaccuracy, such as the complexity of the store environment and the distribution structure. Collectively, these covariates explain 67.6% and 69.0% of the variance in IRI across stores and product categories, respectively. Our findings underscore the need to design processes to reduce the occurrence of IRI and highlight factors that can be incorporated into inventory planning tools developed to account for its presence.
Journal Article
Integrated Production and Outbound Distribution Scheduling: Review and Extensions
In many applications involving make-to-order or time-sensitive (e.g., perishable, seasonal) products, finished orders are often delivered to customers immediately or shortly after the production. Consequently, there is little or no finished product inventory in the supply chain such that production and outbound distribution are very intimately linked and must be scheduled jointly to achieve a desired on-time delivery performance at minimum total cost. Research on integrated scheduling models of production and outbound distribution is relatively recent but is growing very rapidly. In this paper, we provide a survey of such existing models. We present a unified model representation scheme, classify existing models into several different classes, and for each class of the models give an overview of the optimality properties, computational tractability, and solution algorithms for the various problems studied in the literature. We clarify the tractability of some open problems left in the literature and some new problems by providing intractability proofs or polynomial-time exact algorithms. We also identify several problem areas and issues for future research.
Journal Article
Risk Aversion in Inventory Management
Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total cost over a planning horizon. In this paper, we propose a framework for incorporating risk aversion in multiperiod inventory models as well as multiperiod models that coordinate inventory and pricing strategies. We show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk-neutral inventory (and pricing) policies. These structural results are extended to models in which the decision maker has access to a (partially) complete financial market and can hedge its operational risk through trading financial securities. Computational results demonstrate that the optimal policy is relatively insensitive to small changes in the decision-maker's level of risk aversion.
Journal Article
Global Dual Sourcing: Tailored Base-Surge Allocation to Near- and Offshore Production
When designing a sourcing strategy in practice, a key task is to determine the average order rates placed to each source because that affects cost and supplier management. We consider a firm that has access to a responsive nearshore source (e.g., Mexico) and a low-cost offshore source (e.g., China). The firm must determine an inventory sourcing policy to satisfy random demand over time. Unfortunately, the optimal policy is too complex to allow a direct answer to our key question. Therefore, we analyze a tailored base-surge (TBS) sourcing policy that is simple, used in practice, and captures the classic trade-off between cost and responsiveness. The TBS policy combines push and pull controls by replenishing at a constant rate from the offshore source and producing at the nearshore plant only when inventory is below a target. The constant base allocation allows the offshore facility to focus on cost efficiency, whereas the nearshore facility's quick response capability is utilized only dynamically to guarantee high service. The research goals are to (i) determine the allocation of random demand into base and surge capacity, (ii) estimate corresponding working capital requirements, and (iii) identify and value the key drivers of dual sourcing. We present performance bounds on the optimal cost and prove that economic optimization brings the system into heavy traffic. We analyze the sourcing policy that is asymptotically optimal for high-volume systems and present a simple \"square-root\" formula that is insightful to answer our questions and sufficiently accurate for practice, as is demonstrated with a validation study.
Journal Article
A Robust Optimization Approach to Inventory Theory
We propose a general methodology based on robust optimization to address the problem of optimally controlling a supply chain subject to stochastic demand in discrete time. This problem has been studied in the past using dynamic programming, which suffers from dimensionality problems and assumes full knowledge of the demand distribution. The proposed approach takes into account the uncertainty of the demand in the supply chain without assuming a specific distribution, while remaining highly tractable and providing insight into the corresponding optimal policy. It also allows adjustment of the level of robustness of the solution to trade off performance and protection against uncertainty. An attractive feature of the proposed approach is its numerical tractability, especially when compared to multidimensional dynamic programming problems in complex supply chains, as the robust problem is of the same difficulty as the nominal problem, that is, a linear programming problem when there are no fixed costs, and a mixed-integer programming problem when fixed costs are present. Furthermore, we show that the optimal policy obtained in the robust approach is identical to the optimal policy obtained in the nominal case for a modified and explicitly computable demand sequence. In this way, we show that the structure of the optimal robust policy is of the same base-stock character as the optimal stochastic policy for a wide range of inventory problems in single installations, series systems, and general supply chains. Preliminary computational results are very promising.
Journal Article
Financing the Newsvendor: Supplier vs. Bank, and the Structure of Optimal Trade Credit Contracts
We consider a supply chain with a retailer and a supplier: A newsvendor-like retailer has a single opportunity to order a product from a supplier to satisfy future uncertain demand. Both the retailer and supplier are capital constrained and in need of short-term financing. In the presence of bankruptcy risks for both the retailer and supplier, we model their strategic interaction as a Stackelberg game with the supplier as the leader. We use the
supplier early payment discount
scheme as a decision framework to analyze all decisions involved in optimally structuring the trade credit contract (discounted wholesale price if paying early, financing rate if delaying payment) from the supplier's perspective. Under mild assumptions we conclude that a risk-neutral supplier should always finance the retailer at rates less than or equal to the risk-free rate. The retailer, if offered an optimally structured trade credit contract, will always prefer supplier financing to bank financing. Furthermore, under optimal trade credit contracts, both the supplier's profit and supply chain efficiency improve, and the retailer might improve his profits relative to under bank financing (or equivalently, a rich retailer under wholesale price contracts), depending on his current \"wealth\" (working capital and collateral).
Journal Article