Preferences for contractual forms in supply chains

The supply chain contracting literature has focused on incentive contracts designed to align supply chain members’ individual interests. A key finding of this literature is that members’ preferences for contractual forms are often at odds: the upstream supplier prefers relatively complex contracts that can coordinate the supply chain; however, the downstream retailer prefers a wholesale price-only contract because it leaves more surplus (than does a coordinating contract), which the retailer can capture. This paper addresses the following question: Under what circumstances do suppliers and retailers prefer the same contractual form? We study supply chain members’ preferences for contractual forms under three different competitive settings in which multiple supply chains compete to sell substitutable products in the same market. Our analysis suggests that both upstream and downstream sides of the supply chain may prefer the same “quantity discount” contract, which would eliminate the conflicts of interest that otherwise typify contracting situations. More interesting still is that both sides may also prefer the wholesale price-only contract; this finding provides a theoretical explanation for why that inefficient (but simple) contract is widely adopted in supply chain transactions.     

An optimal batch size for integrated production–inventory policy in a supply chain

This study presents a new integrated production–inventory policy under a finite planning horizon and a linear trend in demand. We assume that the vendor makes a single product and supplies it to a buyer with a non-periodic and just-in-time (JIT) replenishment policy in a supply chain environment. The objective is to minimize the joint total costs incurred by the vendor and the buyer. In this study, first, we develop a mathematical model and prove that it has the optimal solution. Then, we describe an explicit solution procedure for obtaining the optimal solution. Finally, we provide two numerical examples to illustrate both increasing and decreasing demands in our proposed model, and we show that the performance of the integrated consideration is better than the performance of any independent decision from either the buyer or the vendor.     

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.     

A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a fuzzy linear programming model for tactical supply chain planning in a multi-echelon, multi-product, multi-level, multi-period supply chain network. In this approach, the demand, process and supply uncertainties are jointly considered. The aim is to centralize multi-node decisions simultaneously to achieve the best use of the available resources along the time horizon so that customer demands are met at a minimum cost. This proposal is tested by using data from a real automobile SC. The fuzzy model provides the decision maker (DM) with alternative decision plans with different degrees of satisfaction.     

Ship-to-order supplies: Contract breachability and the impact of a manufacturer-owned direct channel

We address the issue of contract breachability in a supply chain involving a retailer and a manufacturer operating under ship-to-order contract terms and stochastic demands. The manufacturer is required to fulfill the retailer’s demands on a continuous basis with little or no advance notice. The issue in such an environment is whether the retailer can “naively” assume that she will get a very high fill rate from the manufacturer and therefore has no need for contract penalties in case the manufacturer’s inventory falls short. We suggest a stochastic calculus framework to study the problem and derive a condition when the retailer’s naïve assumption is justified since the probability of stock-outs of the manufacturer is negligible. That is, the ship-to-order contract will not be breached and the fill rate will be more than a predetermined threshold. Furthermore we find that although the manufacturer-owned direct channel generates more revenue and may reduce the volatility of both inventory and production orders, the ratio between expected direct channel and retail sales affects the benefits.     

Value of capacity pooling in supply chains with heterogeneous customers

We investigate the value of pooling capacity in supply chains that serve product demands of different variabilities. We build and analyze models that integrate production queuing models with base stock inventory systems serving demands with different inter-arrival time distributions. The first model combines hyperexponential and exponential demand inter-arrival time distributions. Exact analysis of the model allows us to develop insights into the impact of the difference in demand variabilities on the value of pooling capacity. Simulation experiments allow us to validate these insights for more general settings. We then find one special case that combines exponential and deterministic demand arrivals with deterministic service, where pooling capacity results in increasing the total cost.     

Production and availability policies through the Markov Decision Process and myopic methods for contractual and selective orders

In this paper, we consider a supply chain with one manufacturer, one retailer, and some online customers. In addition to supplying the retailer, manufacturers may selectively take orders from individuals online. Through the Markov Decision Process, we explore the optimal production and availability policy for a manufacturer to determine whether to produce one more unit of products and whether to indicate “in stock” or “out of stock” on website. We measure the benefits and influences of adding online customers with and without the retailer’s inventory information sharing. We also simulate the production and availability policy via a myopic method, which can be implemented easily in the real world. Prediction of simple switching functions for the production and availability is proposed. We find the information sharing, production capacity and unit profit from online orders are the primary factors influencing manufacturer profits and optimal policy. The manufacturer might reserve 50% production capacity for contractual orders from the retailer and devote the remaining capacity to selective orders from spontaneous online customers.     

Supply chain structure in a market with deceptive counterfeits

Deceptive counterfeits differ from non-deceptive ones in that they are packaged and sold as authentic brand name products so that consumers may buy counterfeits unknowingly. When a distribution channel, referred to as the general channel, has been penetrated with deceptive counterfeits, a brand name company may need to restructure the way its products are distributed and rely on reliable channels such as certified stores or manufacturer-owned stores to guarantee 100% authenticity. In this paper, we first identify the conditions under which the general channel will carry deceptive counterfeits, and then analyze the optimal supply chain structure in the presence of counterfeits as well as by incorporating the wholesale price decisions, consumers’ risk attitude towards counterfeits and consumer loyalty towards the reliable stores. Our main finding is that the brand name company should continue to sell, sometimes exclusively, through the general channel despite deceptive counterfeiting under various conditions.     

Supply chains in the presence of store brands

Increased competition from store brands is forcing manufacturers to re-evaluate their strategies in regard to pricing and contracting with trade intermediaries. We analyze a supply chain in which a retailer accepts (with the appropriate contractual agreements) a national brand for resale and then determines whether to introduce a store brand, how to price the store brand, and what quantities of the product(s) to order. We show that when the national brand’s cost per unit quality (CPUQ) is larger than the store brand’s CPUQ, then the retailer seeks to introduce the store brand (SB) and the national brand (NB) manufacturer/supplier is unable to deter him from doing so. We find that the efficiency loss in the decentralized supply chain becomes smaller when a store brand is introduced. Recognizing the inadequacy of standard contracts in coordinating this supply chain, we propose a simple minimum order quantity contract that can coordinate this supply chain.     

Vendor Management Inventory with consignment contracts and the benefits of cooperative advertising

Most of the cooperative advertising literature has focused on studying the effects of such programs considering marketing variables. This paper integrates production and inventory management with pricing and advertising considerations to assess the effects of cooperative advertising programs in bilateral monopolies. We consider a supply chain where a Vendor Managed Inventory (VMI) along with a consignment contract is implemented to coordinate the chain. We develop and solve a differential model for two games. The first one is a benchmark scenario where no cooperative advertising is offered, while the manufacturer offers the cooperative program in the second game. The main results show that cooperative advertising programs, usually considered as successful marketing initiatives, can be very difficult to implement in a supply chain undertaking a VMI policy with a consignment contract, in which operations and marketing interface is taken into account. A cooperative program mainly hurts the manufacturer’s profits, and can be profit-Pareto-improving only in a few cases. Although the retailer is generally willing to receive a support from the manufacturer, she can opt for a non-cooperative program when the largest part of the supply chain profits goes to the manufacturer. We developed several special cases to strengthen our findings.     

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler’s demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method.     

Time-dependent optimization of a multi-item uncertain supply chain network: A hybrid approximation algorithm

We consider the uncertain least cost shipping problem. The input is a multi-item supply chain network with time-evolving uncertain costs and capacities. Exploiting the operational law of uncertainty theory, a mathematical model of the problem is established and the indeterminacy factors are tackled. We use the scaling idea together with transformation approach and uncertainty programming to develop a hybrid algorithm to optimize and obtain the uncertainty distribution of the total shipping cost. We analyze the practical performance of the algorithm and present an illustrative example.     

Coordinating order quantity decisions in the supply chain contract under random demand

In this paper, we are concerned with the coordinating quantity decision problem in a supply chain contract. The supply chain contract is composed of one manufacturer and one retailer to meet the random demand of a single product with a short lifecycle. Our analysis show that the retailer expects to obtain higher profit under proper ordering policies, which can also maximize the expected profit of the supply chain. The manufacturer may induce the retailer to order the coordinated quantity by adjusting the unit return price. As a result, the supply chain is expected to achieve the optimal expected profit.     

Coordination of cooperative cost-reduction efforts in a supply chain partnership

We study cooperative cost reduction in a decentralized supply chain with a single manufacturer and multiple suppliers. The manufacturer assembles components that are procured from the suppliers to produce a final product. Both the manufacturer and the suppliers invest in reducing the unit production costs of the components. We see that neither of the two well-known conventional contracts, the wholesale price contract and the cost-plus pricing contract, generally coordinates the supply chain, i.e., under both of these types of contract, the individual optimal cost-reduction efforts of players deviate from the centralized system-optimal solution. However, this result is not surprising because these contracts encourage either only the manufacturer or only the suppliers alone to invest in cost reduction.     

Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty

In this paper, a mixed integer linear programming (MILP) formulation is developed for the design and planning of supply chains with reverse flows while considering simultaneously production, distribution and reverse logistics activities. It is also considered products’ demand uncertainty using a scenario tree approach. As main goal the model defines the maximization of the expected net present value and the results provide details on sizing and location of plants, warehouses and retailers, definition of processes to install, establishment of forward and reverse flows and inventory levels to attain. The model is applied to a representative European supply chain case study and its applicability is demonstrated.     

Mean–variance analysis of a single supplier and retailer supply chain under a returns policy

In the literature, most of the supply chain coordinating policies target at improving the supply chain’s efficiency in terms of expected cost reduction or expected profit improvement. However, optimizing the expected performance alone cannot guarantee that the realized performance measure will fall within a small neighborhood of its expected value when the corresponding variance is high. Moreover, it ignores the risk aversion of supply chain members which may affect the achievability of channel coordination. As a result, we carry out in this paper a mean–variance (MV) analysis of supply chains under a returns policy. We first propose an MV formulation for a single supplier single retailer supply chain with a newsvendor type of product. The objective of each supply chain decision maker is to maximize the expected profit such that the standard deviation of profit is under the decision maker’s control. We study both the cases with centralized and decentralized supply chains. We illustrate how a returns policy can be applied for managing the supply chains to address the issues such as channel coordination and risk control. Extensive numerical studies are conducted and managerial findings are proposed.     

Measurement and optimization of robust stability of multiclass queueing networks: Applications in dynamic supply chains

Multiclass queueing networks are an essential tool for modeling and analyzing complex supply chains. Roughly speaking, stability of these networks implies that the total number of customers/jobs in the network remains bounded over time. In this context robustness characterizes the ability of a multiclass queueing network to remain stable, if the expected values of the interarrival and service times distributions are subject to uncertain shifts. A powerful starting point for the stability analysis of multiclass queueing networks is the associated fluid network. Based on the fluid network analysis we present a measure to quantify the robustness, which is indicated by a single number. This number will be called the stability radius. It represents the magnitude of the smallest shift of the expected value of the interarrival and/or service times distributions so that the associated fluid network looses the property of stability. The stability radius is a worst case measure and is a conceptual adaptation from the dynamical systems literature. Moreover, we provide a characterization of the shifts that destabilize the network. Based on these results, we formulate a mathematical program that minimizes the required network capacity, while ensuring a desired level of robustness towards shifts of the expected values of the interarrival times distributions. This approach provides a new view on long-term robust production capacity allocation in supply chains. The capabilities of our method are demonstrated using a real world supply chain.     

Option and forward contracting with asymmetric information: Valuation issues in supply chains

We investigate the role of forward commitments and option contracts between a seller (supplier) and a buyer (retailer) in the presence of asymmetric information. In our case, both parties face price and demand uncertainty but the retailer, being closer to the market, has additional information about the true demand and price. The supplier, aware of this asymmetry, and acting as a Stackelberg leader, designs a contracting arrangement that best meet his interest. We contrast the role of forward and option contracts in this environment and identify cases where combinations of the two are dominant. Finally, we investigate how alternative contracting arrangements alter the expected value of obtaining information that eliminates asymmetric information.     

Supplier quality improvement: The value of information under uncertainty

We consider supplier development decisions for prime manufacturers with extensive supply bases producing complex, highly engineered products. We propose a novel modelling approach to support supply chain managers decide the optimal level of investment to improve quality performance under uncertainty. We develop a Poisson–Gamma model within a Bayesian framework, representing both the epistemic and aleatory uncertainties in non-conformance rates. Estimates are obtained to value a supplier quality improvement activity and assess if it is worth gaining more information to reduce epistemic uncertainty. The theoretical properties of our model provide new insights about the relationship between the degree of epistemic uncertainty, the effectiveness of development programmes, and the levels of investment. We find that the optimal level of investment does not have a monotonic relationship with the rate of effectiveness. If investment is deferred until epistemic uncertainty is removed then the expected optimal investment monotonically decreases as prior variance increases but only if the prior mean is above a critical threshold. We develop methods to facilitate practical application of the model to industrial decisions by a) enabling use of the model with typical data available to major companies and b) developing computationally efficient approximations that can be implemented easily. Application to a real industry context illustrates the use of the model to support practical planning decisions to learn more about supplier quality and to invest in improving supplier capability.