Inventory competition in a dual-channel supply chain with delivery lead time consideration

Aimed at the inventory competition of perishable products in a dual-channel supply chain with consideration of the delivery lead time in the online direct channel, we extend the Newsvendor model considering stock-out-based consumer switching behavior to include the delivery lead time. We examine the retailer's optimal order quantity decision in the retail channel and the manufacturer's optimal inventory level decision in the online direct channel, explore the manufacturer's optimal delivery lead time decision in the online direct channel, discuss the impact of the product price and consumer switching behavior on the optimal decisions of supply chain members, and compare the optimal decisions between decentralized and centralized scenarios. The results show that, compared with the centralized scenario, at least one of the supply chain members will overstock in the decentralized scenario and that consumers in the online direct channel enjoy a shorter delivery lead time and hence better service in the decentralized scenario. Finally, we present numerical examples to analyze the impact of relevant parameters on the supply chain members’ profits and the supply chain efficiency.     

网络传媒业供应链质量控制策略与组织模式选择

网络传媒供应链由内容制作商提供有价值的信息产品(如娱乐、资讯等)并通过网站提供给消费者.产品质量控制对网络传媒供应链至关重要.首先利用博弈论的方法分析内容制作商和网站分别独立决策时的策略,纳什均衡揭示双方的"搭便车"动机使供应链整体利润无法达到最优.然后利用最优化的方法分析他们在垂直整合模式下的策略,发现协调决策可以提高整体利润.最后考虑垂直整合模式的新增成本,分析需求质量弹性、利润分配均匀性和质量控制成本等因素对供应链是否采取垂直整合模式的影响.帮助理解网络媒体产业的质量控制策略和供应链组织模式.     

An economic evaluation model of supply chain flexibility

With the advent of the supply chain management concepts, business communities have been realizing that being competitive as a single company is no longer adequate; instead, competitiveness requires consideration of all channels in the supply chain. Despite its importance, the availability of the literature addressing supply chain flexibility is still limited to date. Although relationships between various types of flexibilities have been established, the degree to which one type of flexibility affects the other types and the system performance remains to be investigated. In particular, there is a lack of rigorous analytical models elucidating the relationships between the degree of flexibility in a system and the system level of performance. In this paper, a supply chain flexibility model is developed comprising labor flexibility, machine flexibility, routing flexibility, and information technology, with total system flexibility measured by an economic index. Outputs from the model can assist in making suitable production decisions to produce multiple products under an uncertain environment. Example solutions are given. This paper can help economic evaluation when supply chain flexibility and the factors affecting flexibility are to be improved. It can also assist in making supply chain flexibility-promotion decisions.     

Service capacity procurement of logistics service supply chain with demand updating and loss-averse preference

This paper studies the impacts of loss-averse preference on the service capacity procurement decisions with demand updating in a logistics service supply chain, which consists of one logistics service integrator and one functional logistics service provider. It starts from a basic two-stage Stackelberg game model, then, extends to three scenarios where either the integrator or the provider or neither of them has loss-averse preference. The impact of loss-averse preference on the decisions of supply chain members is discussed by comparing the four models. Our results reveal, first, the loss-averse preferences do not always affect the decisions of supply chain members. If certain conditions are satisfied, the logistics service integrator can benefit from its loss-averse preference. Second, the increased service level can affect the logistics service integrator's procurement strategy and the functional logistics service provider's pricing strategy. This effect is only related to the loss-averse preference of the functional logistics service provider. Last, under certain conditions, the total service capacity decreases with the increased service level, regardless of whether or not the supply chain members have loss-averse preferences.     

Supply chain coordination with controllable lead time and asymmetric information

This paper considers coordinated decisions in a decentralized supply chain consisting of a vendor and a buyer with controllable lead time. We analyze two supply chain inventory models. In the first model we assume the vendor has complete information about the buyer’s cost structure. By taking both the vendor and the buyer’s individual rationalities into consideration, a side payment coordination mechanism is designed to realize supply chain Pareto dominance. In the second model we consider a setting where the buyer possesses private cost information. We design the coordination mechanism by using principal-agent model to induce the buyer to report his true cost structure. The solution procedures are also developed to get the optimal solutions of these two models. The results of numerical examples show that shortening lead time to certain extent can reduce inventory cost and the coordination mechanisms designed for both symmetric and asymmetric information situations are effective.     

Integrated supply chain planning under uncertainty using an improved stochastic approach

This paper proposes an integrated model and a modified solution method for solving supply chain network design problems under uncertainty. The stochastic supply chain network design model is provided as a two-stage stochastic program where the two stages in the decision-making process correspond to the strategic and tactical decisions. The uncertainties are mostly found in the tactical stage because most tactical parameters are not fully known when the strategic decisions have to be made. The main uncertain parameters are the operational costs, the customer demand and capacity of the facilities. In the improved solution method, the sample average approximation technique is integrated with the accelerated Benders’ decomposition approach to improvement of the mixed integer linear programming solution phase. The surrogate constraints method will be utilized to acceleration of the decomposition algorithm. A computational study on randomly generated data sets is presented to highlight the efficiency of the proposed solution method. The computational results show that the modified sample average approximation method effectively expedites the computational procedure in comparison with the original approach.     

Matching product architecture with supply chain design

Product architecture is typically established in the early stages of the product development (PD) cycle. Depending on the type of architecture selected, product design, manufacturing processes, and ultimately supply chain configuration are all significantly affected. Therefore, it is important to integrate product architecture decisions with manufacturing and supply chain decisions during the early stage of the product development. In this paper, we present a multi-objective optimization framework for matching product architecture strategy to supply chain design. In contrast to the existing operations management literature, we incorporate the compatibility between the supply chain partners into our model to ensure the long term viability of the supply chain. Since much of the supplier related information may be very subjective in nature during the early stages of PD, we use fuzzy logic to compute the compatibility index of a supplier. The optimization model is formulated as a weighted goal programming (GP) model with two objectives: minimization of total supply chain costs, and maximization of total supply chain compatibility index. The GP model is solved by using genetic algorithm. We present case examples for two different products to demonstrate the model’s efficacy, and present several managerial implications that evolved from this study.     

Supply chain coordination in quality improvement with reference effects

With increasing public attention on product quality, supply chain quality management has been the focus of considerable research attention in recent years. However, only a few published articles have considered reference effects in supply chain quality management. In practice, reference effects influence consumer purchasing behaviours. Therefore, we have developed a dynamic model that incorporates the effects of the reference quality and reference price on the demand function of a ‘single-supplier single-manufacturer’ supply chain system. In our model, the demand function is assumed to be influenced by the reference price and reference quality. The reference price formation is assumed to be affected by the gap between quality and the reference quality. By utilizing differential game theory, we calculate and compare the open-loop equilibrium quality levels in two different scenarios: (i) Each channel member makes decisions within a subsidy programme and (ii) the supplier vertically integrates with the manufacturer. In addition, a total cost-sharing contract based on quality improvement efforts is proposed and proven to be effective in the supply chain system that is under consideration.     

Optimal inventory and insurance decisions for a supply chain financing system with downside risk control

This research considers a supply chain financing system consisting of a capital‐constrained retailer, a supplier and a risk‐averse bank. The retailer may be subject to credit limit because of the bank's downside risk control, and hence, credit insurance should be needed to enhance his financing ability. This paper develops a mathematical optimization model by incorporating insurance policy into the well‐known newsvendor financing model. The optimal inventory and insurance decisions under different scenarios, that is, no insurance, insurance with symmetric information and insurance with asymmetric information, are derived. This work also discusses how the retailer's capital level, the bank's risk aversion, and the insurer's loading factor affect the optimal inventory and insurance decisions. The results show that the retailer will use credit insurance if he is sufficiently capital‐constrained or the insurer's risk loading factor is low enough. Moreover, credit insurance can bring Pareto improvement to the supply chain financing system, which verifies the prevalence of credit insurance in practice. Several numerical experiments are presented to examine the sensitivities of key parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

Economic selection of process mean for single-vendor single-buyer supply chain

Process mean selection for a container-filling process is an important decision in a single-vendor single-buyer supply chain. Since the process mean determines the vendor’s conforming and yield rates, it influences the vendor–buyer decisions regarding the production lot size and number of shipments delivered from the vendor to buyer. It follows, therefore, that these decisions should be determined simultaneously in order to control the supply chain total cost. In this paper, we develop a model that integrates the single-vendor single-buyer problem with the process mean selection problem. This integrated model allows the vendor to deliver the produced lot to buyer in number of unequal-sized shipments. Moreover, every outgoing item is inspected, and each item failing to meet a lower specification limit is reprocessed. Further, in order to study the benefits of using this integrated model, two baseline cases are developed. The first of which considers a hierarchical model where the vendor determines the process mean and schedules of production and shipment separately. This hierarchical model is used to show the impact of integrating the process mean selection with production/inventory decisions. The other baseline case is studied in the sensitivity analysis where the optimal solution for a given process is compared to the optimal solution when the variation in the process output is negligible. The integrated model is expected to lead to reduction in reprocessing cost, minimal loss to customer due to the deviation from the optimum target value, and consequently, providing better products at reduced cost for customers. Also, a solution procedure is devised to find the optimal solution for the proposed model and sensitivity analysis is conducted to investigate the effect of the model key parameters on the optimal solution.     

Development of a new approach for deterministic supply chain network design

This paper proposes a mixed integer linear programming model and solution algorithm for solving supply chain network design problems in deterministic, multi-commodity, single-period contexts. The strategic level of supply chain planning and tactical level planning of supply chain are aggregated to propose an integrated model. The model integrates location and capacity choices for suppliers, plants and warehouses selection, product range assignment and production flows. The open-or-close decisions for the facilities are binary decision variables and the production and transportation flow decisions are continuous decision variables. Consequently, this problem is a binary mixed integer linear programming problem. In this paper, a modified version of Benders’ decomposition is proposed to solve the model. The most difficulty associated with the Benders’ decomposition is the solution of master problem, as in many real-life problems the model will be NP-hard and very time consuming. In the proposed procedure, the master problem will be developed using the surrogate constraints. We show that the main constraints of the master problem can be replaced by the strongest surrogate constraint. The generated problem with the strongest surrogate constraint is a valid relaxation of the main problem. Furthermore, a near-optimal initial solution is generated for a reduction in the number of iterations.     

Furniture supply chain tactical planning optimization using a time decomposition approach

We study the supply chain tactical planning problem of an integrated furniture company located in the Province of Québec, Canada. The paper presents a mathematical model for tactical planning of a subset of the supply chain. The decisions concern procurement, inventory, outsourcing and demand allocation policies. The goal is to define manufacturing and logistics policies that will allow the furniture company to have a competitive level of service at minimum cost. We consider planning horizon of 1 year and the time periods are based on weeks. We assume that customer’s demand is known and dynamic over the planning horizon. Supply chain planning is formulated as a large mixed integer programming model. We developed a heuristic using a time decomposition approach in order to obtain good solutions within reasonable time limit for large size problems. Computational results of the heuristic are reported. We also present the quantitative and qualitative results of the application of the mathematical model to a real industrial case.     

基于不同社会责任承担模式的闭环供应链决策研究

供应链成员企业对不同社会责任承担模式有自己的偏好选择,探讨供应链成员企业承担的社会责任对供应链决策的影响.对于可能的任何一种社会责任承担模式,企业承担社会责任均会使产品销售价格降低、需求量增加、回收量增加.承担企业社会责任虽然会使自身收益减少,但其他成员和系统的收益却会增加,有利于增加消费者剩余,实现社会福利最大化.当承担的社会责任程度较大时,供应链成员企业能保持长期合作关系,使供应链正常运行.当承担的社会责任程度都较小时,由于供应链成员企业之间对社会责任承担模式的偏好存在矛盾将难以维持供应链合作,最终会导致供应链断链.     

Integrated inventory management and supplier base reduction in a supply chain with multiple uncertainties

This paper considers a manufacturing supply chain with multiple suppliers in the presence of multiple uncertainties such as uncertain material supplies, stochastic production times, and random customer demands. The system is subject to supply and production capacity constraints. We formulate the integrated inventory management policy for raw material procurement and production control using the stochastic dynamic programming approach. We then investigate the supplier base reduction strategies and the supplier differentiation issue under the integrated inventory management policy. The qualitative relationships between the supplier base size, the supplier capabilities and the total expected cost are established. Insights into differentiating the procurement decisions to different suppliers are provided. The model further enables us to quantitatively achieve the trade-off between the supplier base reduction and the supplier capability improvement, and quantify the supplier differentiation in terms of procurement decisions. Numerical examples are given to illustrate the results.     

Bundling decisions in supply chains

Firms often sell products in bundles to extract consumer surplus. While most bundling decisions studied in the literature are geared to integrated firms, we examine a decentralized supply chain where the suppliers retain decision rights. Using a generic distribution of customers’ reservation price we establish equilibrium solutions for three different bundling scenarios in a supply chain, and generate interesting insights for distributions with specific forms. We find that (i) in supply chain bundling the retailer’s margin equals the margin of each independent supplier, and it equals the combined margin when the suppliers are in a coalition, (ii) when the suppliers form a coalition to bundle their products the bundling gain in the supply chain is higher and retail price is lower than when the retailer bundles the products, (iii) the supply chain has more to gain from bundling relative to an integrated firm, (iv) the first-best supply chain bundling remains viable over a larger set of parameter values than those in the case of the integrated firm, (v) supplier led bundling is preferable to separate sales over a wider range of parameter values than if the retailer led the bundling, and (vi) if the reservation prices are uniformly distributed bundling can be profitable when the variable costs are low and valuations of the products are not significantly different from one another. For normally distributed reservation prices, we show that the bundling set is larger and the bundling gain is higher than that for a uniform distribution.     

Call,put and bidirectional option contracts in agricultural supply chains with sales effort

This paper develops option contracts in a supplier-retailer agricultural supply chain where the market demand depends on sales effort. First, we examine a benchmark case of integrated supply chain with the loss rate. Second, we introduce three coordinating option contracts led by the supplier to reduce the retailer's risk, where the call option contract can reduce the shortage risk, the put option contract can reduce the inventory risk and the bidirectional option contract can reduce the bilateral risk. We find that both the optimal initial order quantity and the optimal option quantity increase with the sales effort and the option price will balance the influence of the loss rate on supply chain coordination. Furthermore, the bidirectional option price is the highest while its option quantity is the least, and the put option initial order quantity is the highest. Third, we also consider an option contract led by the retailer to reduce the supplier's wholesale risk. Among the above four option contracts, we find that the option quantity led by the retailer is the highest. Finally, the numerical examples present the impact of the parameters on the optimal decisions, and provide practical managerial insights to reduce the different risk in the agricultural supply chain.     

Contract design and supply chain coordination in the electricity industry

In this article we propose a model of the supply chain in electricity markets with multiple generators and retailers and considering several market structures. We analyze how market design interacts with the different types of contract and market structure to affect the coordination between the different firms and the performance of the supply chain as a whole. We compare the implications on supply chain coordination and on the players’ profitability of two different market structures: a pool based market vs. bilateral contracts, taking into consideration the relationship between futures and spot markets. Furthermore, we analyze the use of contracts for differences and two-part-tariffs as tools for supply chain coordination. We have concluded that there are multiple equilibria in the supply chain contracts and structure and that the two-part tariff is the best contract to reduce double marginalization and increase efficiency in the management of the supply chain.     

Concurrent optimization in designing for logistics support

Concurrent Engineering has always been an important field within military industry and is gaining recognition within commercial industry as well. Studies have suggested that long-range research efforts need to be directed to the area of integrated logistics. In order to satisfy the overall logistics objectives, product designs must incorporate consideration of the impact that design decisions have on operations, maintenance, transportation and supply. This paper presents a model that carries out a concurrent optimization of a product design and its associated manufacturing and logistics support systems. We offer this model as a framework for decision support of concurrent engineering activities.     

A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations

A trend in up-to-date developments in supply chain management (SCM) is to make supply chains more agile, flexible, and responsive. In supply chains, different structures (functional, organizational, informational, financial, etc.) are (re)formed. These structures interrelate with each other and change in dynamics. The paper introduces a new conceptual framework for multi-structural planning and operations of adaptive supply chains with structure dynamics considerations. We elaborate a vision of adaptive supply chain management (A-SCM), a new dynamic model and tools for the planning and control of adaptive supply chains. SCM is addressed from perspectives of execution dynamics under uncertainty. Supply chains are modelled in terms of dynamic multi-structural macro-states, based on simultaneous consideration of the management as a function of both states and structures. The research approach is theoretically based on the combined application of control theory, operations research, and agent-based modelling. The findings suggest constructive ways to implement multi-structural supply chain management and to transit from a “one-way” partial optimization to the feedback-based, closed-loop adaptive supply chain optimization and execution management for value chain adaptability, stability and crisis-resistance. The proposed methodology enhances managerial insight into advanced supply chain management.     

Project-driven supply chains: integrating safety-stock and crashing decisions for recurrent projects

We study a new class of problems—recurrent projects with random material delays, at the interface between project and supply chain management. Recurrent projects are those similar in schedule and material requirements. We present the model of project-driven supply chain (PDSC) to jointly optimize the safety-stock decisions in material supply chains and the crashing decisions in projects. We prove certain convexity properties which allow us to characterize the optimal crashing policy. We study the interaction between supply chain inventory decisions and project crashing decisions, and demonstrate the impact of the PDSC model using examples based on real-world practice.