We incorporate information flow between a supplier and a retailer in a two-echelon model that captures the capacitated setting of a typical supply chain. We consider three situations: (1) a traditional model where there is no information to the supplier prior to a demand to him except for past data; (2) the supplier knows the (s, S) policy used by the retailer as well as the end-item demand distribution; and (3) the supplier has full information about the state of the retailer. Order up-to policies continue to be optimal for models with information flow for the finite horizon, the infinite horizon discounted and the infinite horizon average cost cases. Study of these three models enables us to understand the relationships between capacity, inventory, and information at the supplier level, as well as how they are affected by the retailer's (S - s) values and end-item demand distribution. We estimate the savings at the supplier due to information flow and study when information is most beneficial.information sharing, (s, S) policy, optimal policies, capacitated production-inventory model, infinitesimal perturbation analysis

S upply chain management is likely to play an important role in the digital economy. In this paper, we first describe major issues in traditional supply chain management. Next, we focus our attention on the supply chain issues of visibility, supplier relationships, distribution and pricing, customization, and real-time decision technologies that have risen to importance with the prevalence of e-business. We present an overview of relevant analytical research models that have been developed in these areas, discuss their contributions, and conclude with a discussion on future modeling opportunities in this area.

In an attempt to reduce cost while maintaining good customer service, some of the leading manufacturers in the computer industry are delaying product differentiation (by exploiting component commonality) while managing broader product lines. In an environment where demands are stochastic, it seems a good strategy to store inventory in the form of semi-finished products (vanilla boxes) that can serve more than one final product. However, finding the optimal configurations and inventory levels of the vanilla boxes could be a challenging task. In this paper, we model the above problem as a two-stage integer program with recourse. By utilizing structural decomposition of the problem and (sub)gradient derivative methods, we provide an effective solution procedure. A special case, a variant, and several extensions are also discussed. In our computational section, we utilize our model to study several new research issues. We provide insights on the effect of demand variance, correlation, and capacity limitations on the optimal configuration and inventory levels of vanilla boxes and the performance of a vanilla assembly process. In addition, we compare the performance of the vanilla assembly process to make-to-stock and assemble-to-order processes and provide managerial insights on the conditions under which one might be better than the others. Finally, we discuss the characteristics of an IBM product line (which motivated this work) and the effectiveness of a heuristic tailored for that application.

This study investigates whether VCs' assessment policies of new venture survival are consistent with those arising from the strategy literature (using two established strategy perspectives). Strategy scholars suggest the nature of the markets, competition, and decisions made by the management team affect a new venture's survival chances. The findings demonstrate that VCs' assessment policies are predominantly consistent with those proposed by strategy scholars---providing insight into why VCs consider certain criteria in their assessment of new venture survival as well as why some criteria are more important in their assessment than others. Through this increased understanding of venture capitalists' decision making, entrepreneurs seeking capital may be better able to address their requests for funding to those criteria venture capitalists find most critical to the survival of a new venture. Venture capitalists may use these findings to better understand their own decision making process, which, in turn, provides the opportunity to increase evaluation efficiency.venture capital, decision models, new venture strategy, survival, conjoint analysis

Effective management of inventories in large-scale production and distribution systems requires methods for bringing model solutions closer to the complexities of real systems. Motivated by this need, we develop simulation-based methods for estimating sensitivities of inventory costs with respect to policy parameters. These sensitivity estimates are useful in adjusting optimal parameters predicted by a simplified model to complexities that can be incorporated in a simulation. We consider capacitated, multiechelon systems operating under base-stock policies and develop estimators of derivatives with respect to base-stock levels. We show that these estimates converge to the correct value for finite-horizon and infinite-horizon discounted and average cost criteria. Our methods are easy to implement and experiments suggest that they converge quickly. We illustrate their use by optimizing base-stock levels for a subsystem of the PC assembly and distribution system of a major computer manufacturer.capacitated inventory systems, optimal base-stock policies, assembly systems, simulation, derivative estimation, perturbation analysis

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For a single product, single-stage capacitated production-inventory model with stochastic, periodic (cyclic) demand, we nd the optimal policy and characterize some of its properties. We study the nite-horizon, the discounted in nite-horizon and the in nitehorizon average cases. A simulation based optimization method is provided to compute the optimal parameters. Based on a numerical study, several insights into the model are also provided.

Counterfeit goods are becoming more sophisticated from shoes to infant milk powder and aircraft parts, creating problems for consumers, …rms, and governments. By comparing two types of counterfeiters -deceptive, so in…ltrating a licit (but complicit) distributor, or non-deceptive in an illicit channel, we provide insights into the impact of anti-counterfeiting strategies on a brand-name company, a counterfeiter, and consumers. Our analysis highlights that the e¤ectiveness of these strategies depends critically on whether a brand-name company faces a non-deceptive or deceptive counterfeiter. For example, by improving quality, the brand-name company can improve her expected pro…t against a non-deceptive counterfeiter when the counterfeiter steals an insigni…cant amount of brand value. However, the same strategy does not work well against the deceptive counterfeiter unless high quality facilitates the seizure of deceptive counterfeits signi…cantly. Similarly, reducing price works well in combating the non-deceptive counterfeiter, but it could be ine¤ective against the deceptive counterfeiter. Moreover, the strategies that improve the pro…t of the brand-name company may bene…t the counterfeiter inadvertently and even hurt consumer welfare.Therefore, …rms and governments should carefully consider a trade-o¤ among di¤erent objectives in implementing an anti-counterfeiting strategy.