Consignment or wholesale: Retailer and supplier preferences and incentives for compromise

We consider two independently managed parties, a retailer and a supplier, that are considering either a wholesale or a consignment contract to produce and market a single good. Both parties have an interest in reaching an agreement, but their first choice of contract type are generally not the same. We define the strength of retailer and supplier preferences for their respective choices of contract type as the ratio of their expected profits for their first choice of contract type over that for the alternative contract type. We study how uncontrollable factors as well as controllable factors affect the strength of retailer and supplier contract preferences. We develop incentive payments that can potentially be used to increase the likelihood of success in negotiating an agreement.     

Inventory record inaccuracy – The impact of structural complexity and lead time variability

This article presents a rigorous prospective analysis of the impact of Inventory Record Inaccuracy (IRI) on complex multi-echelon Supply Chains (SCs). Specifically, key operational factors (i.e., the magnitude of the error, frequency of the inventory audits and lead time variability) and SC structure are systematically assessed. We find that the detrimental effects of IRI are exacerbated by the structural complexity of the SC and lead time variability. Furthermore, we show how the efficacy of countermeasure strategies may vary depending on SC configuration and operational conditions. These results allow us to provide interesting managerial recommendations to guarantee investment in prevention and correction strategies.     

Stages of Supply Chain Disruption Response: Direct,Constraining, and Mediating Factors for Impact Mitigation

It is well established that supply chain disruptions can have a severe negative impact on firms and general wisdom suggests that this impact can be mitigated by quick responses. Aside from a few anecdotes, however, little is known about the decision‐making process that leads to speedy responses and about its impeding and supporting antecedents. Using the organizational information‐processing perspective, this empirical study unravels the disruption management process along a sequence of four stages—disruption recognition, disruption diagnosis, response development, and response implementation—and hypothesizes constraining and mediating effects of these stages. The findings contribute to an improved understanding of the role that the decision stages play in mitigating supply chain disruptions, and confirm the prediction that the speed with which information is processed and the stages are worked through positively affects supply chain performance. In addition, the findings suggest that one of the stages, diagnosis, acts as a constraining factor to the other stages. The stages also play a mediating role between the impact that the disruption has and a firm's readiness (prior to a disruption), dependence on a key supplier, and supply chain complexity. This provides guidance to decision makers in the application of resources both prior to a negative event and during a disruption recovery.     

A delayed demand supply chain: Incentives for upstream players

We study a decentralized supply chain where only delayed market demand information is available for making replenishment decisions. The impact of this delay is quantified in a serially linked two-level supply chain where each player exploits the order-up-to replenishment policy. The market demand is assumed to be a first-order autoregressive process. It is shown that the first level of the supply chain benefits from shorter time delays; however, the benefit for the second level is quite minor at best and can sometimes even be (counter-intuitively) detrimental. We conclude that the second level does not have a strong incentive to reduce the time delays in the shared market demand information.     

On service degrade at a discount: Capacity, demand pooling, and optimal discounting

In this paper we study the capacity investment decisions and operational strategies of a firm providing two-class services facing uncertain demands. The capacity decisions of the resources are made before demands are observed. Each service can be implemented by its corresponding resource. Should a mismatch between the capacity and the actual demand for the services arise, the low-class resource can be used as a substitute for the high-class service. We introduce an operational strategy called degrade-at-a-discount, where a price discount is offered to motivate customers to accept a lower class service when their original choice is out of capacity. By formulating the problem as a one-period, two-stage stochastic problem, we analyze how to set up the optimal capacity and the optimal discount. We also conduct a comprehensive numerical study to show the benefits of the degrade-at-a-discount strategy.     

Price competition,cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers

This paper studies the coordination of a supply chain with one manufacturer and two competing retailers after the production cost of the manufacturer was disrupted. We consider two coordination mechanisms: an all-unit quantity discount and an incremental quantity discount. For each mechanism, we develop the conditions under which the supply chain is coordinated and discuss how the cost disruption may affect the coordination mechanisms. For the all-unit quantity discount scheme, we find that the manufacturer charges the lower-cost retailer for a lower unit wholesale price in order to induce him to order more products. If the costs of two retailers have a remarkable difference, then the all-unit quantity discount scheme cannot coordinate the supply chain with disruptions. While the cost disruption may affect the wholesale prices, order quantities as well as retail prices, it is optimal for the supply chain to keep the original coordination mechanism if the production cost change is sufficiently small. The model is also extended to the case with both cost and demand disruptions. The equilibrium strategies of the retailers are investigated when the manufacturer cannot timely react to the disruptions such that she has to keep the original mechanism. We illustrate the results by numerical examples.     

Strategic inventory deployment for retail and e-tail stores

In this paper, we study a supply chain comprising one manufacturer and one retailer. Customers can make purchases either from the retailer or directly from the manufacturer via an e-tail channel. From the manufacturer's perspective of managing the two channels, we study three different inventory strategies, namely centralized inventory strategy, a Stackelberg inventory strategy, and a strategy where the e-tail operation is outsourced to a third party logistics provider (3PL). For each strategy, we obtain the optimal inventory levels in retail and e-tail stores and the respective expected profits. We compare the performance of various strategies. Managerial insights are provided through analytical and numerical analyses to illustrate the applicability of different strategies.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

Universal supplier selection via multi-dimensional auction mechanisms for two-way competition in oligopoly market of supply chain

Allocation of the tasks in competitive market conditions at each echelon of the supply chain is an important activity in the supply chain. The task allocation problem, referred to as supply chain formation process, normally faces information asymmetry in the supply chain. The information asymmetry is caused by rational and intelligent players trying to maximize their own profit rather than opt for the supply chain profit as a whole. Thus, the process of allocating tasks in such situations becomes difficult and will result in externalities in the supply chain trades. These externalities can be internalized with present methodologies in the literature. In this paper, the major internalization methods in different contexts are considered. Lagrange relaxation and Vickery Clarke Groves (VCG) auction mechanism are explored in order to form a supply chain. This paper proposes the multi-stage auction mechanism analyzing two-way competitions, a Bertrand and Cournot competition where price per unit and quantity are the underlying two parameters in a utility analysis. To analyze the problem in real life, the industry example of Indian Railway Catering and Tourism Corporation Ltd. (IRCTC) procurement process has been taken which demonstrates the usability of the proposed framework.     

Decision support system for the batching problems of steelmaking and continuous-casting production

This paper investigates two batching problems for steelmaking and continuous-casting (SCC) production in an integrated iron and steel enterprise. The tasks of the problems are to make the decisions as how to consolidate ordered slabs into charges, and then how to group charges into casts. The effective decisions on these batching problems can help to balance the requirements of materials in downstream production lines, improve the customer satisfaction levels, and reduce production costs (including reduction of open ordered slabs, less slabs quality upgrading, reduction of steel-grade changeovers, and reduction of inefficient utilization of tundishes lives). We first formulate the problems as integer-programming models by consider practical constraints and requirements, and then develop the two heuristic algorithms for the corresponding batching problems. By embedding above models and algorithms, we develop decision support system (DSS) software with interactive planning editor. The DSS has been tested by using practical data set collected from the steelmaking plant in Baosteel which is one of the most advanced iron and steel enterprises in China. Computational experiments demonstrate that the models and algorithms developed can generate the satisfactory solutions when they work together with the planning editor in the DSS.     

A demand classification scheme for spare part inventory model subject to stochastic demand and lead time

In this study, we aim to develop a demand classification methodology for classifying and controlling inventory spare parts subject to stochastic demand and lead time. Using real data, the developed models were tested and their performances were evaluated and compared. The results show that the Laplace model provided superior performance in terms of service level, fill rate (FR) and inventory cost. Compared with the current system based on normal distribution, the proposed Laplace model yielded significant savings and good results in terms of the service level and the FR. The Laplace and Gamma optimisation models resulted in savings of 82 and 81%, respectively.     

Risk tolerance and a retailer's pricing and ordering policies within a newsvendor framework

This paper evaluates the pricing and ordering policies of a retailer, facing a price-dependent stochastic demand, within a newsvendor framework, under different degrees of risk tolerance and under a variety of optimizing objectives. These are (i) maximizing expected profit, for a retailer who may be risk-seeker, risk-averse or risk neutral; (ii) deriving a maximin strategy of maximizing a minimum guaranteed profit and (iii) modeling the probability of exceeding a target profit, as a constraint or as an objective. Some analytical properties and numerical examples illustrate the main features of the models and provide some comparative policy analysis across the model.     

Decision support systems for production scheduling tasks- Part I of a case study: Analysis and task redesign

The first three steps of a new design method for decision support systems in production scheduling tasks are applied to a large bulk terminal. The operational characteristics of the company largely correspond with those of typical semiprocess industries. The design model used consists of five steps: production analysis, task analysis, task redesign, decision support design and decision support implementation. The results of the application of the design model up to the task redesign step are described.     

Multi-criteria decision support and evaluation of strategies for nuclear remediation management

Environmental emergency situations can differ in many ways, for instance according to their causes and the dimension of their impacts. Yet, they share the characteristic of sudden onset and the necessity for a coherent and effective emergency management. In this paper we consider decision support in the event of a nuclear or radiological accident in Europe. RODOS, an acronym for real-time on-line decision support system, is a decision support system designed to provide support from the early phases through to the medium and long-term phases. This work highlights the role of multi-criteria decision analysis (MCDA) within RODOS in ensuring the transparency of decision processes within emergency and remediation management. Special emphasis is placed on the evaluation of alternative remediation or countermeasure strategies using the multi-criteria decision support tool Web-HIPRE in scenario focused decision making workshops involving different stakeholder and expert groups. Decision support is enhanced by a module that generates natural language explanations to facilitate the understanding of the evaluation process, therefore contributing to the direct involvement of the decision makers, with the aim of increasing their confidence in the results of the analyses carried out, forming an audit trail for the decision making process and improving the acceptability of the system as a whole.     

Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications

In the last decades, green and sustainable supply chain management practices have been developed, trying to integrate environmental concerns into organisations by reducing unintended negative consequences on the environment of production and consumption processes. In parallel to this, the circular economy discourse has been propagated in the industrial ecology literature and practice. Circular economy pushes the frontiers of environmental sustainability by emphasising the idea of transforming products in such a way that there are workable relationships between ecological systems and economic growth. Therefore, circular economy is not just concerned with the reduction of the use of the environment as a sink for residuals but rather with the creation of self-sustaining production systems in which materials are used over and over again.Through two case studies from different process industries (chemical and food), this paper compares the performances of traditional and circular production systems across a range of indicators. Direct, indirect and total lifecycle emissions, waste recovered, virgin resources use, as well as carbon maps (which provide a holistic visibility of the entire supply chain) are presented. The paper asserts that an integration of circular economy principles within sustainable supply chain management can provide clear advantages from an environmental point view. Emerging supply chain management challenges and market dynamics are also highlighted and discussed.     

Supply Chain Strategies for Perishable Products: The Case of Fresh Produce

This paper examines supply chain design strategies for a specific type of perishable product—fresh produce—using melons and sweet corn as examples. Melons and other types of produce reach their peak value at the time of harvest; product value deteriorates exponentially post‐harvest until the product is cooled to dampen the deterioration. Using the product's marginal value of time (MVT), the rate at which the product loses value over time in the supply chain, we show that the appropriate model to minimize lost value in the supply chain is a hybrid of a responsive model from post‐harvest to cooling, followed by an efficient model in the remainder of the chain. We also show that these two segments of the supply chain are only loosely linked, implying that little coordination is required across the chain to achieve value maximization. The models we develop also provide insights into the use of a product's MVT to develop supply chain strategies for other perishable products.     

面向短生命周期产品的供应链订购批量与交货期协调决策模型

考虑了由一个分销商和制造商构成的单一短生命周期产品的两级供应链系统,当市场需求和制造商的交货期都是随机变化时,建立了分散决策和协调决策模式下交货期与批量的决策模型,解析分析了两种决策模式下供应链的优化决策;解析分析和算例分析表明,双方合作不仅可以缩短产品交货期、增加供应链系统的整体收益,而且还能增加产品的市场供给量。