A continuous approximation procedure for determining inventory distribution schemas within supply chains

This paper presents an integrated inventory distribution optimization model that simultaneously incorporates the issues of location, production, inventory, and transportation within a supply chain. The objective is to determine the optimal number and size of shipments under varying but commonly practiced production and shipping scenarios. A continuous approximation procedure is proposed to determine the optimal number and size of shipments. Three production and shipping scenarios are investigated and closed form expressions for the optimal number of shipments for each scenario are obtained. A numerical example is presented to demonstrate the usefulness of the model.     

A multi-layer demand-responsive logistics control methodology for alleviating the bullwhip effect of supply chains

This paper presents a multi-layer demand-responsive logistics control strategy for alleviating, effectively and efficiently, the bullwhip effect of a supply chain. Utilizing stochastic optimal control methodology, the proposed method estimates the time-varying demand-oriented logistics system states, which originate directly and indirectly downstream to the targeted member of a supply chain, and associate these estimated demands with estimates of different time-varying weights under the goal of systematically optimizing the logistical performance of chain members. In addition, an experimental design is conducted where the proposed method is evaluated with the two specified criteria. Numerical results indicate that the proposed method permits alleviating, to a great extent, the bullwhip effect in comparison with the existing logistics management strategies. Furthermore, the methodology presented in this study is expected to help address issues regarding the uncertainty and complexity of the distortion of demand-related information existing broadly among supply chain members for an efficient supply chain coordination.     

A simulation model to investigate impacts of facilitating quality data within organic fresh food supply chains

Annals of Operations Research - Demand for and production of organic fresh food play an increasing role worldwide. As a result, a growing amount of fresh fruits and vegetables has to be transported...     

A note on competitive supply chains with generalised supply costs

This note generalises models from two influential papers in the theory of supply chain outsourcing under competition: 9 and 1. The first paper studies the impact of competitive intensity on the outsourcing decision from the supplier’s point of view for linear supply cost; the second paper examines the impact of supply economies of scale from the retailer’s point of view when selling perfectly substitutable products. By considering competitive intensity and supply economies of scale simultaneously, we find that equilibrium channel structures are primarily determined by the competitive intensity, which is true even under supply diseconomies of scale; the key message in the second paper of scale economies driving retailer’s outsourcing supply decision is highly dependent on the assumption of perfect substitutes. Our finding has no qualitative difference when either the suppliers or the retailers are modeled as the channel leader and make the outsourcing decisions.     

A methodology for modeling inter-company supply chains and for evaluating a method of integrated product and process documentation

Due to the increasing complexity in products and in the resulting enterprise processes, new concepts for process optimization are necessary. One innovative concept, resulting from the requirements of the automotive industry, is the method of an integrated product and process documentation. In order to evaluate the benefits of an inter-company use of this documentation approach a simulation-based decision support system using a modular modeling concept for intra- and inter-company process chains has been developed. This concept is based on the Supply Chain Operations Reference-model (SCOR-model). The developed concept allows the evaluation of different configurations of process chains with different sets of parameters describing realistic production and inventory processes. Focussed on supply chains with high variant and complex products within the automotive industry first scenarios have been built up and the benefits of this integrated documentation approach can be visualized. This approach is the future basis for optimization methods coming from control theory.     

A flexible and generic approach to dynamic modelling of supply chains

In this paper, we present a new modelling approach for realistic supply chain simulation. The model provides an experimental environment for informed comparison between different supply chain policies. A basic simulation model for a generic node, from which a supply chain network can be built, has been developed using an object-oriented approach. This generic model allows the incorporation of the information and physical systems and decision-making policies used by each node. The object-oriented approach gives the flexibility in specifying the supply chain configuration and operation decisions, and policies. Stochastic simulations are achieved by applying Latin Supercube Sampling to the uncertain variables in descending order of importance, which reduces the number of simulations required. We also present a case study to show that the model is applicable to a real-life situation for dynamic stochastic studies.     

A method for analysing operational complexity in supply chains

This paper proposes a method for analysing the operational complexity in supply chains by using an entropic measure based on information theory. The proposed approach estimates the operational complexity at each stage of the supply chain and analyses the changes between stages. In this paper a stage is identified by the exchange of data and/or material. Through analysis the method identifies the stages where the operational complexity is both generated and propagated (exported, imported, generated or absorbed). Central to the method is the identification of a reference point within the supply chain. This is where the operational complexity is at a local minimum along the data transfer stages. Such a point can be thought of as a ‘sink’ for turbulence generated in the supply chain. Where it exists, it has the merit of stabilising the supply chain by attenuating uncertainty. However, the location of the reference point is also a matter of choice. If the preferred location is other than the current one, this is a trigger for management action. The analysis can help decide appropriate remedial action. More generally, the approach can assist logistics management by highlighting problem areas. An industrial application is presented to demonstrate the applicability of the method.     

Modeling reverse logistic tasks within closed-loop supply chains: An example from the automotive industry

In this contribution, the peculiarities of establishing a closed-loop supply chain (CLSC) are presented, based on an example considering the end-of-life vehicle (ELV) treatment in Germany. Different design options for a CLSC are put up, concentrating on how reverse material flows can be handled with regard to reintegrate them into their genuine supply chains. Reverse logistics aspects are modeled with vehicle routing planning. Introducing a problem-tailored algorithm, results of several CLSC scenarios are discussed which are based on real case data, depicting measures from German ELV stakeholders.     

A simple heuristic for echelon policies in serial supply chains

This paper proposes a simple heuristic that generates a solution for echelon (r,nQ,T) policies by sequentially solving a deterministic demand problem, a subproblem with fixed reorder intervals, and a subproblem with fixed batch sizes. For each of these problems, we further simplify the computation by solving a series of single-stage systems whose parameters are obtained directly from the original problem data. In a numerical study, we find that this heuristic outperforms an existing one in the literature.     

A new revenue sharing mechanism for coordinating multi-echelon supply chains

A new type of revenue sharing (RS) contract mechanism for multi-echelon supply chains between the most downstream entity and all upstream entities is proposed. The new RS contract is analyzed in the linear supply chain setting facing stochastic demand. Advantages over mechanisms with RS contracts between all pairs of adjacent entities are discussed and demonstrated.     

A new methodology for sustainability measurement of banks based on rough set theory

Central European Journal of Operations Research - Sustainability measurement of banks is a complicated process, mainly dependent on the intuition of banking and sustainability experts. In this...     

A game theoretic approach to coordinate pricing and vertical co-op advertising in manufacturer-retailer supply chains

Vertical cooperative (co-op) advertising is a marketing strategy in which the retailer runs local advertising and the manufacturer pays for a portion of its entire costs. This paper considers vertical co-op advertising along with pricing decisions in a supply chain; this consists of one manufacturer and one retailer where demand is influenced by both price and advertisement. Four game-theoretic models are established in order to study the effect of supply chain power balance on the optimal decisions of supply chain members. Comparisons and insights are developed. These embrace three non-cooperative games including Nash, Stackelberg-manufacturer and Stackelberg-retailer, and one cooperative game. In the latter case, both the manufacturer and the retailer reach the highest profit level; subsequently, the feasibility of bargaining game is discussed in a bid to determine a scheme to share the extra joint profit.     

Integrated modeling of extended agro-food supply chains: A systems approach

The current intense food production-consumption is one of the main sources of environmental pollution and contributes to anthropogenic greenhouse gas emissions. Organic farming is a potential way to reduce environmental impacts by excluding synthetic pesticides and fertilizers from the process. Despite ecological benefits, it is unlikely that conversion to organic can be financially viable for farmers, without additional support and incentives from consumers. This study models the interplay between consumer preferences and socio-environmental issues related to agriculture and food production. We operationalize the novel concept of extended agro-food supply chain and simulate adaptive behavior of farmers, food processors, retailers, and customers. Not only the operational factors (e.g., price, quantity, and lead time), but also the behavioral factors (e.g., attitude, perceived control, social norms, habits, and personal goals) of the food suppliers and consumers are considered in order to foster organic farming. We propose an integrated approach combining agent-based, discrete-event, and system dynamics modeling for a case of wine supply chain. Findings demonstrate the feasibility and superiority of the proposed model over the traditional sustainable supply chain models in incorporating the feedback between consumers and producers and analyzing management scenarios that can urge farmers to expand organic agriculture. Results further indicate that demand-side participation in transition pathways towards sustainable agriculture can become a time-consuming effort if not accompanied by the middle actors between consumers and farmers. In practice, our proposed model may serve as a decision-support tool to guide evidence-based policymaking in the food and agriculture sector.     

A general unconstrained model for transfer pricing in multinational supply chains

Multinational supply chains operate in more than one country or tax jurisdiction and face decision problems concerned with trade flows of resources, products and services, transfer prices, and allocation of transport costs between their divisions. These decisions must consider, for the sake of optimality, corporate and governmental parameters such as the payment of dividends and royalties, ownership of and control over subsidiaries, income taxes differentials, duties and quotas, etc. In this paper, we generalize and extend the Theory of the Multinational Firm to the case of multinational supply chains. We propose a model that is more general and comprehensive than the previous ones proposed in the literature. To be more specific, our model integrates many of the previous research factors and includes new ones, such as transport costs and duty drawbacks, which are critical for supply chains that operate under international trade regulations. Under the maximization of the repatriated earnings objective, we study the optimality conditions of the corporate decision variables to derive managerial guidelines and to determine how decisions regarding trade quantities, transfer prices, and transport cost allocations affect the amount of taxes to be paid to host governments as well as the total after tax repatriated earnings of the corporation.     

An integrated guaranteed- and stochastic-service approach to inventory optimization in supply chains

Multi-echelon inventory optimization literature distinguishes stochastic- (SS) and guaranteed-service (GS) approaches as mutually exclusive frameworks. While the GS approach considers flexibility measures at the stages to deal with stockouts, the SS approach only relies on safety stock. Within a supply chain, flexibility levels might differ between stages rendering them appropriate candidates for one approach or the other. The existing approaches, however, require the selection of a single framework for the entire supply chain instead of a stage-wise choice. We develop an integrated hybrid-service (HS) approach which endogenously determines the overall cost-optimal approach for each stage and computes the required inventory levels. We present a dynamic programming optimization algorithm for serial supply chains that partitions the entire system into subchains of different types. From a numerical study we find that, besides implicitly choosing the better of the two pure frameworks, whose cost differences can be considerable, the HS approach enables additional pipeline and on-hand stock cost savings. We further identify drivers for the preferability of the HS approach.     

Surplus division and investment incentives in supply chains: A biform-game analysis

In this paper, we use a biform-game approach for analyzing the impact of surplus division in supply chains on investment incentives. In the first stage of the game, firms decide non-cooperatively on investments. In the second stage, the surplus is shared according to the Shapley value. We find that all firms have inefficiently low investment incentives which, however, depend on their position in the supply chain. Cross-subsidies for investment costs can mitigate, but not eliminate the underinvestment problem. Vertical integration between at least some firms.yields efficient investments, but may nevertheless reduce the aggregated payoff of the firms. We show how the size of our effects depends on the structure of the supply chain and the efficiency of the investment technology. Various extensions demonstrate that our results are qualitatively robust.     

A heuristic for single-warehouse multiretailer supply chains with all-unit transportation cost discounts

In supply chain management research, transportation costs, if explicitly considered at all, are frequently assumed to be linear. These costs often have a more complex form, such as an all-unit discount structure – this piecewise cost function adds significant complexity when included in supply chain management problems and is therefore often ignored due to solution time or tractability concerns. We present and evaluate a new heuristic procedure which provides good solutions to problems involving all-unit discount cost functions while significantly reducing solution times. The general nature of this procedure does not require assumptions about the supply chain structure or policies, and is therefore applicable in a wide range of settings.     

Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains

Operational forecasting in supply chain management supports a variety of short-term planning decisions, such as production scheduling and inventory management. In this respect, improving short-term forecast accuracy is a way to build a more agile supply chain for manufacturing companies. Demand forecasting often relies on well-established univariate forecasting methods to extrapolate historical demand. Collaboration across the supply chain, including information sharing, is suggested in the literature to improve upon the forecast accuracy of such traditional methods. In this paper, we review empirical studies considering the use of downstream information in demand forecasting and investigate different modeling approaches and forecasting methods to incorporate such data. Where empirical findings on information sharing mainly focus on point-of-sale data in two-level supply chains, this research empirically investigates the added value of using sell-through data originating from intermediaries, next to historical demand figures, in a multi-echelon supply chain. In a case study concerning a US drug manufacturer, we evaluate different methods to incorporate this data and consider both time series methods and machine learning techniques to produce multi-step ahead weekly forecasts. The results show that the manufacturer can effectively improve its short-term forecast accuracy by integrating sell-through data into the forecasting process and provide useful insights as to the different modeling approaches used. The conclusion holds for all forecast horizons considered, though it is most pronounced for one-step ahead forecasts. Therefore, our research provides a clear incentive for manufacturers to assess the forecast accuracy that can be achieved by using sell-through data.