建筑企业供应链管理中的不确定性研究

对建筑企业供应链管理中的不确定性因素进行了详细的剖析，分析了它们对建筑企业供应链管理的影响，并深入探讨了降低建筑企业供应链管理中不确定性影响的措施。     

Information sharing and profit allotment based on supply chain cooperation

To maximize customer value created by a supply chain system as a whole, one of the key issues in supply chain management is how to have profit and benefit properly shared between partners in an effective manner of the supply chain integration. In this regard, information sharing between partners plays a rather important role in business process and management integration of the supply chain. The paper focuses on analyzing the value created from information sharing by decreasing inventory level and on investigating the collaborative mechanism of providing incentive to retailer by upstream partner via sharing profit gained information sharing in the context of three-echelon supply chain system. The issue of dealing with the interest conflict between the supply chain as a whole and individual partners is addressed based on information sharing analysis by means of cooperative game approach, a graphic model with three-dimensions is developed to depict the possible cooperative solutions of profit allotment between partners, and a problem solving method addressing how the profit allotment between partners can effectively motivate the partners to be cooperative with each other is presented as well.     

The impact of flexibility on operational supply chain planning

We study in this paper the effects of volume flexibility, delivery flexibility and operational decision flexibility in operational supply chain planning under uncertain demand. We use a rolling schedule to plan supply chain operations for a whole year. The planning horizon is 4 weeks with deterministic demand in the first week and predicted for the following 3 weeks. Using a case from the Norwegian meat industry, we compare the annual operating results of using a two-stage stochastic programming model to the deterministic expected value problem in order to discuss the impact of flexibility in the supply chain.     

Retailer policy, uncertainty reduction, and supply chain performance

We investigate how the retailer’s inventory policy affects the total cost of a serial supply chain. When the retailer uses the locally optimal (s,S) policy, there is randomness in order time and order quantity to the supplier whereas the supplier sees randomness only in order quantity for the suboptimal (R,T) policy and only in order time for another suboptimal (Q,r) policy. Using an extensive computational study, we find that the suboptimal policies perform better from the total supply chain perspective. The benefit of policy changes is magnified when the retailer costs are low, when the supplier costs are high, and when there is information sharing.     

Distribution contracts to support optimal inventory holdings under demand uncertainty

When suppliers produce products for which demand is uncertain, they face a problem of inducing downstream distributors to stock inventory levels that the suppliers prefer. This paper considers a wide array of alternative supply contracts, each of which consists of a mixture of constant per-unit wholesale prices, buy-back arrangements, and post sale payments contingent on sales made, such as revenue sharing or buybacks. We show that linear supply contracts specifying any combination of two of these three instruments can implement the vertical integrated outcome for a monopoly, thereby generating the supplier's preferred inventory configuration and price distribution. We extend our results to differentiated product oligopoly, demonstrating that each supplier obtains its preferred inventory configuration and price distribution, given the choices of its rival. Distributors choose optimal inventories from the suppliers' standpoint, even if suppliers do not know the distribution of demand uncertainty, and, given the perfect competition among distributors, all profits in the supply chain are captured by suppliers. Thus, suppliers are able to deal with demand uncertainty with remarkably little information about demand, and without the need to control dealer actions in detail. In particular, suppliers need not specify either dealer inventories or resale prices, but instead encourage distributors to order based on information in their possession and to set prices that generate desirable resale price dispersion.     

Managing demand uncertainty through order overplanning

Most techniques for managing demand uncertainty require a certain degree of stability in the environment, since they are completely or partially based on the observation of historical data. When applied to a context characterized by irregular and sporadic demand these techniques show poor performances. In fact, in such a case uncertainty management calls for the gathering of information that directly anticipates future requirements. Although contexts with irregular and sporadic demand have received only minor attention in the past, they are currently gaining ever more importance and extending their occurrence. This paper illustrates and discusses a method, called order overplanning, specifically designed to cope with uncertainty in these environments. It consists of an articulate and coherent set of forecasting procedures, planning principles and slack control techniques. From a Master Production Scheduling (MPS) perspective, order overplanning is similar to hedging and option overplanning: gross requirements are larger than expected demand. The major difference is that order overplanning uses two distinct units in the MPS and forecasting procedures: while the MPS unit is an end item or a module, the forecasting unit is a customer order. This makes order overplanning able to exploit early information generated by each customer during its purchasing process, information that otherwise would be lost. This marked advantage comes to the detriment of an increased effort of integration between Sales and Manufacturing, especially for controlling the slack created to handle uncertainty.The paper first infers the principles and procedures of order overplanning by analysing the case study of an Italian telecommunications manufacturer. Then, it discusses the main advantages and disadvantages of this method, in order to identify the main factors affecting its performances and to determine the planning environments where it fits coherently.     

Modeling agility of supply chain

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent and volatile markets, which are becoming norms as product life cycles shorten and environmental forces create additional uncertainty resulting in higher risk in the supply chain management. Agility further helps in providing the right product, at the right time to the consumer, which is the main objective of any supply chain. In the present paper, using interpretive structural modeling, interrelationships of the variables, influencing supply chain agility, have been derived. These variables have been categorized according to their driving power and dependence. This methodology provides a means by which order can be imposed on the complexity of such variables. The insight from model would help supply chain managers in strategic planning for improving supply chain agility.     

Strategic safety stock placement in supply chain design with due-date based demand

We present a strategic safety stock placement model in supply chain design for assembly-type product with due-date based demand, where demand data are based on dates when company has to ship to customers rather than order receiving dates. We formulate multi-echelon stock placement by guaranteed-service model with demand propagation equations through backward explosion, where demand can be either stationary or nonstationary. The stock placement model is incorporated into network design problem and its optimization procedure is provided. We show effectiveness of the optimization procedure and other significant features of the model through numerical examples of a machinery product supply chain.     

Ordering and pricing policies in a manufacturing and distribution supply chain for fashion products

In the paper, we develop a model of manufacturing and distribution supply chains that are operating to meet price-sensitive random demand for products with short life cycles such as fashion products. Two specific scenarios are considered. The manufacturer-controlled scenario is one where the distributor shares price-sensitive random demand with the manufacturer, and the manufacturer controls the supply chain stocking decisions and bears the risk of overstocking costs. The distributor-controlled scenario works in the opposite direction. Prevailing wisdom suggests that the manufacturer should control supply chain decisions (e.g., via vendor-managed inventory). Our results indicate that such an arrangement is against the interest of a distributor selling short life-cycle products. Furthermore, we find that the total supply chain profit is generally higher when the distributor controls the supply chain stocking decisions and bears the risk of overstocking costs.     

The impact of trust on innovativeness and supply chain performance

Trust is identified as a significant predictor of positive performance in business relationships. On the premise that the effects of trust have not been given the deserved scholarly attention in the supply chain context, this paper investigates the effects of trust on innovativeness and supply chain performance. The hypothesised model is operationalised with survey data and analysed using structural equation modelling. The findings add credence to the positive effects of trust and identify trust and innovativeness as antecedents to higher performance in the supply chain.     

Robust supply base management: Determining the optimal number of suppliers utilized by contractors

The importance of robust supply base management under demand uncertainty requires an understanding of the benefits associated with a contractor having an optimal number of suppliers. The key benefit is a reduction in a contractor's total cost of supply base management. However, few supplier-optimizing models incorporate the perspectives of both demand uncertainty and supply base management costs. The objective of this paper is twofold: (1) to investigate the dynamics between demand uncertainty and coordination; and (2) to develop a model that determines the optimal number of suppliers that a contractor should maintain in its supply base to become more flexible and maximize its profits.     

Electronic marketplaces and supply chain relationships

Electronic marketplaces and supply chain management (SCM) are two notions, which have attracted much attention among both academicians and practitioners during the last 5 years. However, the discussion of the relationship between the two notions has been limited and fragmented. In this paper, we will present a critical summary of the discussion of Internet-driven electronic marketplaces (IEMPs) based on an extensive literature review. Then, we will discuss the interrelation between IEMP and SCM from a procurement portfolio perspective. Our proposition is that different types of buyer-supplier relationships require different types of IEMPs. We propose a relationship/IEMP-grid that should help to identify the right selection strategy for IEMP in various procurement situations. Finally, we present proposals for future research within this area.     

The role of e-marketplaces in supply chain management

Electronic marketplaces (e-marketplaces) have a profound influence on the way in which organizations manage their supply chains. Proponents of the e-marketplace concept suggest that web-based trading systems, such as World Wide Retail Exchange (WWRE) and GlobalNetXchange (GNX), would enable companies to more efficiently buy, sell, and manage their supply chain processes on a global scale. This study investigates the extent to which e-business tools of the e-marketplace are used by channel members in the retail sector for business-to-business supply chain management (SCM). The study is based on a survey involving food service companies, retailers, and wholesalers in the UK. It is shown that the e-marketplace supply chain applications enable the majority of companies to automate transaction-based activities and procurement-related processes rather than strategic supply chain activities. The results also indicate that full participation in e-marketplaces requires companies to integrate their internal and external supply chain activities and share strategic information.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Optimization of a vendor managed inventory supply chain with guaranteed stability and robustness

In this work we address the steady state optimization of a supply chain model that belongs to the class of vendor managed inventory, automatic pipeline, inventory and order based production control systems (VMI-APIOBPCS). The supply chain is optimized with the so-called normal vector method, which has specifically been developed for the economic optimization of uncertain dynamical systems with constraints on dynamics. We demonstrate that the normal vector method provides robust optimal points of operation for a number of scenarios. Since the method strictly distinguishes economic optimality, which is treated as the optimization objective, from dynamical requirements, which are incorporate by appropriate constraints, it provides a measure for the cost of stability and robustness as a desired side-effect.     

Short-term financing in a cash-constrained supply chain

In this paper we consider a two-level supply chain with a single retailer and a manufacturer, where both the firms are facing financial constraints and can not produce/order their optimal quantity. Our work shows that a lender who finances the manufacturer has a motivation to finance the retailer as well. Motivated by this, we investigate lender's problem of financing both the firms by making a joint decision on the loan amount and comparing it with the case when lender makes independent decision on loan amount for both the firms. Our numerical study indicates that if one of the firms in the supply chain has sufficiently low cash, joint decision (we refer to it as supply chain financing) may be better not only for the lender but for the retailer and manufacturer as well.     

Decision models in global supply chain management

Integrative decision making is key to effective supply chain management (SCM). This article examines five illustrative supply chain decision models that demonstrate the importance of integrating the decisions across the supply chain. The models that are discussed illustrate the diversity of analytical approaches and their usefulness in managing global supply chain issues. The paper identifies potential areas of additional research where analytical modeling can generate useful insights. The paper also presents a short categorization of decision models from literature.     

The effects of management inertia on the supply chain performance of produce-to-stock firms

This article examines the impact of inertia on the management of the firm's supply chain operations and the effects it can have on a produce-to-stock firm's ability to respond to external market pressure and develop corrective strategies. The research methodology used is based on earlier Catastrophe Modeling that looked at inertia in organizational design, competitive pressure, and competitive response. The model demonstrates how latent variables, such as customer pressure and supply chain inertia can influence a finished goods supply chain management's response under various conditions. The model was tested and validated using questionnaire data gathered from a sample of members of the Council of Logistics Management. The model was used to estimate individual finished goods firm inertia response estimates. We incorporate these estimates in a brief examination of three produce-to-stock firms from the sample to give readers an idea of the usefulness of the approach in examining supply chain inertia.     

Agility index in the supply chain

To achieve a competitive edge in the rapidly changing business environment, companies must align with suppliers and customers to streamline operations, as well as working together to achieve a level of agility beyond individual companies. Consequently, agile supply chains are the dominant competitive vehicles. Embracing agile supply chain requires asking some important questions, namely: what exactly is agility and how can it be measured? Moreover, how can agility be effectively achieved and enhanced? Due to the ambiguity of agility assessment, most measures are described subjectively using linguistic terms. Thus, this study develops a fuzzy agility index (FAI) based on agility providers using fuzzy logic. The FAI comprises attribute’ ratings and corresponding weights, and is aggregated by a fuzzy weighted average. To illustrate the efficacy of the method, this study also evaluates the supply chain agility of a Taiwanese company. This evaluation demonstrates that the method can provide analysts with more informative and reliable information for decision.