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Quality investment and price decision in a risk-averse supply chain   总被引:2,自引:0,他引:2  
In this paper, we investigate quality investment and price decision of a make-to-order (MTO) supply chain with uncertain demand in international trade. Due to volatility of orders from buyers, the supplier and the manufacturer in the supply chain are subject to financial risk. In contrast to the general assumption that players in a supply chain are risk neutral in quality investment and price decision, we consider the risk-averse behavior of the players in three different supply chain strategies: Vertical Integration (VI), Manufacturer’s Stackelberg (MS) and Supplier’s Stackelberg (SS). The study shows that both supply chain strategy and risk-averse behavior have significant impacts on quality investment and pricing. Compared to a risk-neutral supply chain, a risk-averse supply chain has lower, same and higher quality of products in VI, MS and SS, respectively. Also, we derive the conditions under which the supply chain strategy is implemented in a decentralized setting. A numerical study is used to illustrate some related issues.  相似文献
2.
This paper combines copula functions with GARCH-type models to construct the conditional joint distribution, which is used to estimate Value-at-Risk (VaR) of an equally weighted portfolio comprising crude oil futures and natural gas futures in energy market. Both constant and time-varying copulas are applied to fit the dependence structure of the two assets returns. The findings show that the constant Student t copula is a good compromise for effectively fitting the dependence structure between crude oil futures and natural gas futures. Moreover, the skewed Student t distribution has a better fit than Normal and Student t distribution to the marginal distribution of each asset. Asymmetries and excess kurtosis are found in marginal distributions as well as in dependence. We estimate VaR of the underlying portfolio to be 95% and 99%, by using the Monte Carlo simulation. Then using backtesting, we compare the out-of-sample forecasting performances of VaR estimated by different models.  相似文献
3.
Project portfolio selection is one of the most important decision-making problems for most organizations in project management and engineering management. Usually project portfolio decisions are very complicated when project interactions in terms of multiple selection criteria and preference information of decision makers (DMs) in terms of the criteria importance are taken into consideration simultaneously. In order to solve this complex decision-making problem, a multi-criteria project portfolio selection problem considering project interactions in terms of multiple selection criteria and DMs?? preferences is first formulated. Then a genetic algorithm (GA)-based nonlinear integer programming (NIP) approach is used to solve the multi-criteria project portfolio selection problem. Finally, two illustrative examples are presented for demonstration and verification purposes. Experimental results obtained indicate that the GA-based NIP approach can be used as a feasible and effective solution to multi-criteria project portfolio selection problems.  相似文献
4.
We investigate a contract setting problem faced by a manufacturer who can procure major modules from an overseas supplier, as well as a local supplier. The overseas supplier is prime and offers quality products, whereas the local supplier is viewed only as a backup, and its products are inferior in quality. As the local supplier needs to put in additional effort to fulfill the urgent orders, it is difficult for the manufacturer to estimate this urgent supplier’s production cost. This asymmetric cost information becomes an obstacle for the manufacturer in managing the urgent supplier. In this paper, we study two types of contingent contracts. One is the common price-only contract, and the other is a contract menu consisting of a transfer payment and a lead time quotation. We construct a Stackelberg game model and evaluate how the involvement of an urgent supplier with private cost information affects performances of the prime supplier and the manufacturer in different scenarios (with or without the urgent supplier, under different contingent contracts). We also conduct numerical experiments to show how the parameters of the contracts affect profits of the manufacturer.  相似文献
5.
Credit risk analysis is an active research area in financial risk management and credit scoring is one of the key analytical techniques in credit risk evaluation. In this study, a novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation. In this proposed model, some artificial intelligent techniques, which are used as intelligent agents, are first used to analyze and evaluate the risk levels of credit applicants over a set of pre-defined criteria. Then these evaluation results, generated by different intelligent agents, are fuzzified into some fuzzy opinions on credit risk level of applicants. Finally, these fuzzification opinions are aggregated into a group consensus and meantime the fuzzy aggregated consensus is defuzzified into a crisp aggregated value to support final decision for decision-makers of credit-granting institutions. For illustration and verification purposes, a simple numerical example and three real-world credit application approval datasets are presented.  相似文献
6.
We consider the replenishment routing problems of one supplier who can replenish only one of multiple retailers per period, while different retailers need different periodical replenishment. For simple cases satisfying certain conditions, we obtain the simple routing by which the supplier can replenish each retailer periodically so that shortage will not occur. For complicated cases, using number theory, especially the Chinese remainder theorem, we present an algorithm to calculate a feasible routing so that the supplier can replenish the selected retailers on the selected periods without shortages.  相似文献
7.
RFID application can improve operation performance in a supply chain by reducing or eliminating inventory misplacement and shrinkage. In this paper, we present a periodic review inventory model to investigate and characterize the multiperiod inventory control policies in both non-RFID and RFID cases when the firm encounters misplacement and shrinkage. The optimal inventory control policy is proved to be a two-control limit policy. The control limits in both the non-RFID case and the RFID case are analyzed and examined, while considering the impact of shrinkage and misplacement on inventory policies. A critical inventory level is determined to identify the relationship of higher inventory level control limits between the RFID case and the non-RFID case. An intensive numerical study with sensitivity analysis of selling price, misplacement rate, shrinkage rate, inventory recovery rate, and tag price is conducted. We find that when RFID technology is adopted, the inventory control policy in the RFID case is much more stable than that of the non-RFID case, as the misplaced inventory can be recovered perfectly and instantly for sale and the inventory shrinkage can be reduced by RFID technology. In addition, one of our intriguing findings is that when the shrinkage rate is below a threshold value which is independent of parameters, RFID application has no effect on inventory control policy if the misplaced inventory can be recovered in a timely manner by physical audit, which has not been revealed in previous studies.  相似文献
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