On the role of revenue-sharing contracts in supply chains

The supply chain coordinating role of revenue-sharing has, to date, been examined only in static models. With downstream competition, the central conclusion in these models is negative: revenue-sharing cannot, except in degenerate form, achieve coordination. Incorporating dynamics, by allowing inventory carryover in discrete time, this paper establishes a foundation for revenue-sharing contracts in aligning incentives.     

Modeling inventory routing problems in supply chains of high consumption products

Given a distribution center and a set of sales-points with their demand rates, the objective of the inventory routing problem (IRP) is to determine a distribution plan that minimizes fleet operating and average total distribution and inventory holding costs without causing a stock-out at any of the sales-points during a given planning horizon. We propose a new model for the long-term IRP when demand rates are stable and economic order quantity-like policies are used to manage inventories of the sales-points. The proposed model extends the concept of vehicle routes (tours) to vehicle multi-tours. To solve the nonlinear mixed integer formulation of this problem, a column generation based approximation method is suggested. The resulting sub-problems are solved using a savings-based approximation method. The approach is tested on randomly generated problems with different settings of some critical factors to compare our model using multi-tours as basic constructs to the model using simple tours as basic constructs.     

Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products

This paper proposes a mixed integer mathematical programming model to support the complex order promising process in fruit supply chains. Due to natural factors, such as land, weather or harvesting time, these supply chains present units of the same product that differ in certain relevant attributes to customers (subtypes). This becomes a managerial problem when customers require specific subtypes in their orders. Additionally, the deterioration of the original characteristics of subtypes over time generates waste and gives rise to a shelf life-based pricing policy. Therefore, the developed model should ensure that customers are served not only the quantities and dates, but also the required homogeneity and freshness. The model aims to maximise two conflicting objectives: total profit and mean product freshness. The novelty of the model derives from considering both homogeneity in subtypes as a requirement in customer orders and the traceability of product deterioration over time. Different scenarios are defined according to the weight assigned to each objective, shelf-life length and pricing policy in a rolling horizon scheme. The numerical experiments conducted for a real orange and tangerine supply chain, show the model’s validity and the conflicting behaviour of the two objectives. The highest profit is made at the expense of the lowest mean freshness delivered, which is reinforced by the narrower the price variation with freshness. Finally, the positive impact of prolonging the product’s shelf life on both objectives is shown.     

An examination of HMM‐based investment strategies for asset allocation

We develop and analyse investment strategies relying on hidden Markov model approaches. In particular, we use filtering techniques to aid an investor in his decision to allocate all of his investment fund to either growth or value stocks at a given time. As this allows the investor to switch between growth and value stocks, we call this first strategy a switching investment strategy. This switching strategy is compared with the strategies of purely investing in growth or value stocks by tracking the quarterly terminal wealth of a hypothetical portfolio for each strategy. Using the data sets on Russell 3000 growth index and Russell 3000 value index compiled by Russell Investment Services for the period 1995–2008, we find that the overall risk‐adjusted performance of the switching strategy is better than that of solely investing in either one of the indices. We also consider a second strategy referred to as a mixed investment strategy which enables the investor to allocate an optimal proportion of his investment between growth and value stocks given a level of risk aversion. Numerical demonstrations are provided using the same data sets on Russell 3000 growth and value indices. The switching investment strategy yields the best or second best Sharpe ratio as compared with those obtained from the pure index strategies and mixed strategy in 14 intervals. The performance of the mixed investment strategy under the HMM setting is also compared with that of the classical mean–variance approach. To make the comparison valid, we choose the same level of risk aversion for each set‐up. Our findings show that the mixed investment strategy within the HMM framework gives higher Sharpe ratios in 5 intervals of the time series than that given by the standard mean–variance approach. The calculated weights through time from the strategy incorporating the HMM set‐up are more stable. A simulation analysis further shows a higher performance stability of the HMM strategies compared with the pure strategies and the mean–variance strategy. Copyright © 2009 John Wiley & Sons, Ltd.     

Wholesale price rebate vs. capacity expansion: The optimal strategy for seasonal products in a supply chain

We consider a supply chain in which one manufacturer sells a seasonal product to the end market through a retailer. Faced with uncertain market demand and limited capacity, the manufacturer can maximize its profits by adopting one of two strategies, namely, wholesale price rebate or capacity expansion. In the former, the manufacturer provides the retailer with a discount for accepting early delivery in an earlier period. In the latter, the production capacity of the manufacturer in the second period can be raised so that production is delayed until in the period close to the selling season to avoid holding costs. Our research shows that the best strategy for the manufacturer is determined by three driving forces: the unit cost of holding inventory for the manufacturer, the unit cost of holding inventory for the retailer, and the unit cost of capacity expansion. When the single period capacity is low, adopting the capacity expansion strategy dominates as both parties can improve their profits compared to the wholesale price rebate strategy. When the single period capacity is high, on the other hand, the equilibrium outcome is the wholesale price rebate strategy.     

Evolutionary stability of auction and supply chain contracting: An analysis based on disintermediation in the Indian tea supply chains

The purpose of this paper is to show that evolutionary stable market equilibrium is achievable through complete disintermediation of auctioneers if the option of bargaining-based supply chain contracting exists. The paper analyzes the evolutionary dynamics of a market that caters both the scopes of auction-intermediation and supply chain contracting to a set of homogeneous buyers and sellers. The motivation of this work developed from the contradiction between the theoretical framework of Lu and McAfee (1996) that identifies auction to be evolutionary stable over bargaining and the real instance of sustained disintermediation of auctioneers in the world’s largest tea industry in India where supply chain contracting is the other option of trading.     

On the impact of advertising initiatives in supply chains

Advertising plays an important role in affecting consumer demand. Socially responsible firms are expected to use advertising judiciously, limiting advertising of “bad” products. An example is the advertising initiative adopted by several major food manufacturers to limit the advertising of unhealthy food categories to children. Such initiatives are based on the belief that less advertising will lead to less consumption of these unhealthy food categories. However, food manufacturers usually distribute products to consumers through retailers whose advertising is not restricted by those initiative programs. In this paper, we examine the effectiveness of such advertising initiative in a leader–follower supply chain with one manufacturer and one retailer. We assume that both the manufacturer and the retailer can choose to participate in the advertising initiative by reducing their advertising levels. The problem is formulated as a Stackelberg game. We show that the effectiveness of the advertising initiative critically depends on the leader’s participation in the initiative. If the leader is willing to reduce the advertising level below a threshold, the market coverage of the product can drop significantly. On the other hand, if only the follower participates in the initiative, the market coverage is likely to expand in the majority of cases. Managerial implications of this research are also discussed.     

An analytical method for cost analysis in multi-stage supply chains: A stochastic network model approach

This paper studies the cost distribution characteristics in multi-stage supply chain networks. Based on the graphical evaluation and review technique, we propose a novel stochastic network mathematical model for cost distribution analysis in multi-stage supply chain networks. Further, to investigate the effects of cost components, including the procurement costs, inventory costs, shortage costs, production costs and transportation costs of supply chain members, on the total supply chain operation cost, we propose the concept of cost sensitivity and provide corresponding algorithms based on the proposed stochastic network model. Then the model is extended to analyze the cost performance of supply chain robustness under different order compensation ability scenarios and the corresponding algorithms are developed. Simulation experiment shows the effectiveness and flexibility of the proposed model, and also promotes a better understanding of the model approach and its managerial implications in cost management of supply chains.     

Robust tests for the bullwhip effect in supply chains with stochastic dynamics

This paper analyzes the bullwhip effect in single-echelon supply chains driven by arbitrary customer demands and operated nondeterministically. The supply chain, with stochastic system parameters, is modeled as a Markovian jump linear system. The paper presents robust analytical conditions to diagnose the bullwhip effect and bound its magnitude. The tests are independent of the customer demand. Examples are given. Ordering policies that pass these tests, and thus avoid the bullwhip effect in random environments for arbitrary customer demands, are shown to exist. The paper also presents possible extensions to multi-echelon chains.     

Adaptive fuzzy vendor managed inventory control for mitigating the Bullwhip effect in supply chains

This paper proposes an adaptive fuzzy control application to support a vendor managed inventory (VMI). The methodology applies fuzzy control to generate an adaptive smoothing constant in the forecast method, production and delivery plan to eliminate, for example, the rationing and gaming or the Houlihan effect and the order batching effect or the Burbidge effects and finally the Bullwhip effect. The results show that the adaptive fuzzy VMI control surpasses fuzzy VMI control and traditional VMI in terms of mitigating the Bullwhip effect and lower delivery overshoots and backorders. This paper also guides management in allocating inventory by coordinating suppliers and buyers to ensure minimum inventory levels across a supply chain. Adaptive fuzzy VMI control is the main contribution of this paper.     

A novel advanced grey incidence analysis for investigating the level of resilience in supply chains

Annals of Operations Research - Supply chain risk management embroils quite a lot of situations of managerial decision-making under uncertainties. As contemporary supply chains are intricate...     

Analysis of the effectiveness of manufacturer-sponsored retailer gift cards in supply chains

Some manufacturers sponsor “free” retailer gift cards to be given to consumers who purchase their products. These gift cards are paid for by the manufacturer and are redeemable on all products at the retailer. We develop a model of such a supply chain. We analyze cases in which the gift cards’ redemption rate is constant or increasing in gift card value. The results indicate that in addition to the redemption rate and consumers’ valuation for gift card dollars, the profitability of manufacturer-sponsored gift cards depends on the average gross margin of the retailer and the type of purchases consumers make with gift cards. Furthermore, we show that under certain conditions, free gift cards will increase the expected profits of the retailer and manufacturer as well as decrease the retail price of the product. These conditions include a retailer with large average gross margin and consumers using gift cards to purchase products they would not buy with cash otherwise. Furthermore, all consumers, including those who do not redeem the gift card, are more likely to benefit from a reduced retail price when their probability of redeeming the gift card after purchase is equal to their estimated redemption probability at purchase time. We show the conditions under which gift cards are more profitable than cash mail-in rebates. We develop an incentive scheme to improve the performance of supply chains with gift cards.     

Optimal investment and reinsurance policies in insurance markets under the effect of inside information

In this paper, we study the problem of optimal investment and proportional reinsurance coverage in the presence of inside information. To be more precise, we consider two firms: an insurer and a reinsurer who are both allowed to invest their surplus in a Black–Scholes‐type financial market. The insurer faces a claims process that is modeled by a Brownian motion with drift and has the possibility to reduce the risk involved with this process by purchasing proportional reinsurance coverage. Moreover, the insurer has some extra information at her disposal concerning the future realizations of her claims process, available from the beginning of the trading interval and hidden from the reinsurer, thus introducing in this way inside information aspects to our model. The optimal investment and proportional reinsurance decision for both firms is determined by the solution of suitable expected utility maximization problems, taking into account explicitly their different information sets. The solution of these problems also determines the reinsurance premia via a partial equilibrium approach. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Network Simulation Method for the evaluation of perturbed supply chains on a finite horizon

Due to lead times and other delays in a chain, the Net Present Value (NPV) can be easily estimated if Laplace transforms in MRP models are employed. This leads to the estimation of NPV on an infinite horizon. However, for the simultaneous perturbations of several parameters in a supply chain and activities running on the finite horizon, NPV could be overestimated. Therefore, we suggest the parallel use of the Network Simulation Method (NSM) with the MRP theory to reduce these overestimations. This paper aims to present the NSM to evaluate supply chains on a finite horizon when stochastic behaviour of time delays and other perturbations of parameters are also essential, which is typical for food and drug supply chains. The circuit simulator NGSPICE, which was previously used by certain authors in thermodynamics, also evaluates the financial consequences of simultaneous perturbations in a finite chain. This approach holds better for the stochastic processes of simultaneous perturbations, compared to our results achieved using MRP theory without these corrections. As presented in the numerical example, the shorter the horizon and lower the interest rate, the more important it is to use the correction factors obtained from the NGSPICE simulator.

     

Analytical approximations for prices of swap rate dependent embedded options in insurance products

Life insurance products have profit sharing features in combination with guarantees. These so-called embedded options are often dependent on or approximated by forward swap rates. In practice, these kinds of options are mostly valued by Monte Carlo simulations. However, for risk management calculations and reporting processes, lots of valuations are needed. Therefore, a more efficient method to value these options would be helpful. In this paper analytical approximations are derived for these kinds of options, based on an underlying multi-factor Gaussian interest rate model. The analytical approximation for options with direct payment is almost exact while the approximation for compounding options is also satisfactory. In addition, the proposed analytical approximation can be used as a control variate in Monte Carlo valuation of options for which no analytical approximation is available, such as similar options with management actions. Furthermore, it’s also possible to construct analytical approximations when returns on additional assets (such as equities) are part of the profit sharing rate.     

Coordinated control of distribution supply chains in the presence of fuzzy customer demand

This paper considers a single product inventory control in a Distribution Supply Chain (DSC). The DSC operates in the presence of uncertainty in customer demands. The demands are described by imprecise linguistic expressions that are modelled by discrete fuzzy sets. Inventories at each facility within the DSC are replenished by applying periodic review policies with optimal order up-to-quantities. Fuzzy customer demands imply fuzziness in inventory positions at the end of review intervals and in incurred relevant costs per unit time interval. The determination of the minimum of defuzzified total cost of the DSC is a complex problem which is solved by applying decomposition; the original problem is decomposed into a number of simpler independent optimisation subproblems, where each retailer and the warehouse determine their optimum periodic reviews and order up-to-quantities. An iterative coordination mechanism is proposed for changing the review periods and order up-to-quantities for each retailer and the warehouse in such a way that all parties within the DSC are satisfied with respect to total incurred costs per unit time interval. Coordination is performed by introducing fuzzy constraints on review periods and fuzzy tolerances on retailers and warehouse costs in local optimisation subproblems.     

A hybrid genetic algorithm for the finite horizon economic lot and delivery scheduling in supply chains

In this paper, we investigate the lot and delivery scheduling problem in a simple supply chain where a single supplier produces multiple components on a flexible flow line (FFL) and delivers them directly to an assembly facility (AF). It is assumed that all of parameters such as demand rates for the components are deterministic and constant over a finite planning horizon. The main objective is to find a lot and delivery schedule that would minimize the average of holding, setup, and transportation costs per unit time for the supply chain. We develop a new mixed integer nonlinear program (MINLP) and an optimal enumeration method to solve the problem. Due to difficulty of obtaining the optimal solution in medium and large-scaled problems, a hybrid genetic algorithm (HGA) is also developed. The proposed HGA incorporates a neighborhood search (NS) into a basic genetic algorithm that enables the algorithm to perform genetic search over the subspace of local optima. The two proposed solution methods are compared on randomly generated problems, and computational results show that the performance of HGA is very promising because it is able to find an optimal or near-optimal solution for majority of the test problems.     

Modeling and optimization of biomass quality variability for decision support systems in biomass supply chains

Annals of Operations Research - A feasible alternative to the production of fossil fuels is the production of biofuels. In order to minimize the costs of producing biofuels, we developed a...     

An EOQ model for salesmen’s initiatives, stock and price sensitive demand of similar products - A dynamical system

The paper deals with an inventory model to determine the retailer’s optimal order quantity for similar products. It is assumed that the amount of display space is limited and the demand of the products depends on the display stock level where more stock of one product makes a negative impression of the another product. Besides it, the demand rate is also dependent on selling price and salesmen’s initiatives. Also, the replenishment rate depends on the level of stock of the items. The objective of the model is to maximize the profit function, including the effect of inflation and time value of money by Pontryagin’s Maximal Principles. The stability analysis of the concerned dynamical system has been done analytically.