Electronic markets in support of procurement processes along the automotive supply chain

Since the introduction of the internet, firms have continued to seek ways to use these public networks to gain competitive advantage. The procurement function is beginning to take on greater strategic importance as these networks started providing firms wider opportunities such as choices of suppliers. This aims not only to reduce procurement costs, but also to build stronger relationships with suppliers to improve quality and flexibility in meeting customer demand. This type of linkage of firms with their suppliers when the product manufactured is complex and supply-chain is heavily tiered, such as the case of the automobile industry, creates challenges to any electronic market or exchange that is aiming to support such a system. Based on discussions with some key individuals in an automotive supply chain and an in-depth analysis of a supply-chain segment, this paper explores the role electronic markets may have to play, if they are to support the procurement processes of various agents along the supply chain.     

A chain game for distributed trading and negotiation

This position paper introduces a simulation gaming environment for enacting a production network. The environment aims to be an integrative laboratory for investigating supply networks, as well as being a versatile training tool. The primary focus is on food production networks. The environment enables a number of teams of participants, each representing one actor in a food chain, to conduct business together. The teams can have the role of auction, co-operation, wholesaler, factory, retail chain, and retail outlet. Producers and consumers are either enacted or simulated. The game leaders freely determine the products and production methods in each run of the game. The gaming environment takes performance, process and institutional aspects of chains into account. It is particularly suited for investigating issues of sustainability and trust. Currently the gaming environment is under development. The paper presents version 1B. This version can be found at http://www.chaingame.org. It runs on the Web, enabling to model distributed chains.     

Supply chain management: A just-in-time perspective

Just-in-time (JIT) has been a widely recognized production philosophy alternative since the early 1980s. JIT principles and techniques have been widely adopted in many manufacturing firms. More recently, supply chain management has evolved as a discipline focusing on the design, planning and control of processes linking the initial raw materials to the ultimate consumption of the finished product. Supply chain efficiency is dependent on the efficiencies of the individual manufacturing organizations and the ability to connect along the supply chain. In this paper supply chain management from a JIT perspective is investigated, focusing on the linking mechanisms between successive companies and the collective efficiency of the supply chain.     

Aligning supply chain collaboration using Analytic Hierarchy Process

The significance of collaboration among supply chain members has been sufficiently stressed in the recent literature as a powerful tool for increasing accuracy of demand forecasts and for consequent cost reductions. Since it has been recognized that naïve forecasting is no longer cost efficient, Supply Chain (SC) members have found it very important to exchange relevant information that will help improve accuracy of demand forecasting. This information differs widely in terms of their characteristics. For example, some information (e.g. historic sales data) that is cheap to exchange may not contribute to a great increase in forecast accuracy. Similarly, some information may not be very reliable (e.g. demand forecast by individual SC members). In general, there is a trade-off in the kind of information required and the kind of information exchanged. This study analyses these trade-offs using an Analytic Hierarchy Process (AHP) model. The model is then implemented based on case studies conducted in two manufacturing firms. The AHP model ranks available information in terms of their contributions to improve forecast accuracy, and can provide vital clues to SC partners for preparing exchangeable data. From the case studies using AHP model, it was proved that using the preferred SC data, the firms could enhance forecasts accuracy. This in turn can help the firms to make decisions on SC collaborative arrangements for information exchange.     

Supply vessel planning under cost,environment and robustness considerations

Offshore oil and gas installations need reliable cargo deliveries. The vessels supplying these installations on a periodic basis are expensive and constitute a source of emissions of greenhouse gases. Incorporating vessel speed optimization into the supply vessel planning process may significantly reduce fuel consumption and hence emissions. In addition, speed optimization may yield cost reductions if the number of vessels used does not increase. A main uncertainty factor, especially in the winter season, is the weather conditions which impact sailing and service times. Cost minimization and the application of speed optimization strategies may have implications on the robustness of weekly supply vessel schedules since idle times in the schedules are reduced. We develop a simulation-optimization based methodology that considers costs, emissions and robustness in the generation of weekly supply vessel schedules. Results of analyses conducted on real instances show that robustness requirements may yield both increased emissions and costs in the winter season. However, depending on instance characteristics, different degrees of robustness can be incorporated with both costs and emissions reductions through speed optimization.     

Optimal procurement of long-term contracts in the presence of imperfect spot market

B2B spot market has grown rapidly and become an effective trading channel for commodity products. Besides long-term contract procurement from conventional suppliers (forward and option), a buyer can procure or sell commodities at any time in B2B spot market to adjust her inventory level. However, spot prices are generally volatile and the market is imperfect in the sense that spot trading may be realized with uncertainty in a given period of time and often comes with extra transaction cost. This paper considers a commodity buyer who can order forward and option contracts in advance and trade in a B2B spot market when spot price and demand are observed stochastically. Based on a single-period newsvendor model, we discuss three optimal order strategies and derive respective expected profits when the buyer is risk-neutral. The sensitivity of purchase costs, market liquidity and transaction cost is investigated. We also compare the optimal expected profits for different strategies to illustrate the effects of the two long-term contracts in the presence of the B2B spot market. We then extend our model to a multi-period setting and derive the optimal strategy. Finally, we numerically compute the optimal order strategy for a risk-averse buyer and analyze the impact of spot market, risk aversion, as well as the correlation between customer demand and spot price.     

A critical review on supply chain risk – Definition,measure and modeling

Economic systems are increasingly prone to complexity and uncertainty. Therefore, making well-informed decisions requires risk analysis, control and mitigation. In some areas such as finance, insurance, crisis management and health care, the importance of considering risk is largely acknowledged and well-elaborated, yet rather heterogeneous concepts and approaches for risk management have been developed. The increased frequency and the severe consequences of past supply chain disruptions have resulted in an increasing interest in risk. This development has led to the adoption of the risk concepts, terminologies and methods from related fields. In this paper, existing approaches for quantitative supply chain risk management are reviewed by setting the focus on the definition of supply chain risk and related concepts.     

Information sharing in a supply chain with a make-to-stock manufacturer

We study ex ante information sharing in a supply chain consisting of a downstream retailer and a make-to-stock upstream manufacturer. The retailer has imperfect demand information and may choose to share it with the manufacturer. Based on the information sharing arrangement, the manufacturer makes the wholesale price and the stocking level decisions. Then the retailer decides the order quantity and the manufacturer fulfills the order up to the available stock level. We find that the retailer has an incentive to voluntarily share the information with the make-to-stock manufacturer if the magnitude of demand uncertainty is intermediate. This stands in sharp contrast with the existing studies which show that the retailer never shares information when the manufacturer is make-to-order. Our results highlight the interdependence between the retailer׳s incentive to share information and the manufacturer׳s operational and marketing decisions.     

Accurate Response with Refurbished Consumer Returns

Centering around anticipative and reactive capabilities of firms, accurate response is an important supply‐side strategy to deal with demand uncertainty. Clearly, the structure of the possible reaction will crucially influence the optimal anticipative decision making. In this article, we extend the existing literature in this area by including a new reactive capability, namely the utilization of refurbished consumer returns from early sales to react to demand later in the selling season. Because consumer returns depend on previous sales, there is also a direct link to the anticipative supply decision. We capture this effect in a newsvendor‐type model and provide both analytical and numerical insights into the optimal anticipative and reactive decisions as well as the value of refurbishing in terms of the retailer's expected profitability.