Optimal pricing and trade-in policies in a dual-channel supply chain when considering market segmentation

Many companies are implementing trade-in programmes through multiple channels. This may ultimately lead to fiercer channel conflict and competition. Few studies have explored firms’ optimal trade-in policies in such an environment. To fill the gap, we build a theoretical model that captures the features of a dual-channel situation in which a manufacturer implements a trade-in programme through retail and direct channels simultaneously. Compared with the case in which there is no trade-in rebate, the results show that a trade-in programme can intensify or mitigate the double marginalisation effect if the retailer can initially decide the trade-in rebate in the retail channel. This significantly relies on market segmentation. However, when the retailer cannot decide the trade-in rebate in the retail channel, the trade-in programme aggravates the double marginalisation effect. Second, the trade-in rebate offered by the retailer may be higher than the subsidy offered by the manufacturer, as long as the retailer can autonomously decide the trade-in rebate in the retail channel. Furthermore, we find that both the manufacturer and retailer prefer to obtain the right to autonomously decide the trade-in rebate in the retail channel, but the supply chain prefers that the manufacturer do it. Some numerical examples are provided to further explain these outcomes.     

Grammatical evolution in developing optimal inventory policies for serial and distribution supply chains

Recently, there has been a growing literature on biologically inspired algorithms, particularly genetic algorithms and genetic programming, applied to supply chain modelling and inventory control optimisation. Due to the rigidity of the genetic algorithms approach, it is difficult to change the underlying model logic and add richness to the supply chain. While genetic programming provides a more flexible approach than that provided by genetic algorithms, to date its application has been limited to small supply chain modelling problems in relation to optimal inventory policies. This research applies Grammatical Evolution, a relatively new biologically inspired algorithm, to the field of supply chain optimisation, employing human readable rules called grammars. These grammars provide a single mechanism to describe a variety of complex structures and can incorporate the domain knowledge of the practitioner to bias the algorithm towards regions of the search space containing better solutions. Results are presented showing Grammatical Evolution is at least competitive in cost terms, and superior in flexibility, with these methods applicable to any supply chain of the serial or distribution type. Furthermore, Grammatical Evolution shows an adaptive ability that augurs well for supply chains in dynamic environments, such as disruption.     

Negotiation-based collaborative planning in divergent two-tier supply chains

Advanced Planning Systems are based on the principles of hierarchical planning, which—at least at the top level—grounds on centralized planning. However, central coordination requires access to all relevant information and the power to impose planning results on all organizational units. In consequence it can be realized only for parts of an inter-organizational supply chain, and the question arises whether there exist alternate ways to achieve coordination. In this paper we describe a non-hierarchical, negotiation-based process, which can be used to synchronize plans between independent partners of a two-tier supply chain consisting of one supplier and several buyers. Assuming that all partners generate plans based upon mathematical programming—as in most Advanced Planning Systems at the master planning level—we show how modified versions of these models can be utilized to support the negotiation process by evaluating given purchasing orders or supplies and by generating counter-proposals. Resulting is an iterative, negotiation-like scheme, which establishes and subsequently improves a consistent overall plan based on a limited exchange of information between the supply chain partners.     

Maximizing supply chain profits with effective order management: integration of activity-based costing and theory of constraints with mixed-integer modelling

The development of a profitable-to-promise order management model in a make-to-order manufacturing environment is presented. The primary objective is to maximize profitability while ensuring that the firm has adequate resources to satisfy demand. The effectiveness of Activity-Based Costing and Theory of Constraints-based approaches is compared to assess order profitability. This order management model uses a mixed-integer program to consider simultaneously capacity, the relevant costs of supply chain resources and profitability. The results suggest that a close examination of cost structures is necessary for choosing an effective framework for a profitable-to-promise application. In manufacturing environments where direct manufacturing costs constitute a relatively small percentage of the total manufacturing cost, it would be beneficial to consider an Activity-Based Costing approach. On the other hand, in environments where direct costs are large, a Theory of Constraints-based approach would suffice.     

Available-to-promise-based flexible order allocation in ATO supply chains

This paper presents a new available-to-promise (ATP) based order allocation model, which is different from traditional order fulfilment systems in that it considers customer priority in an assemble-to-order (ATO) supply chain environment before the order is fulfilled. First, in terms of customer priority, a pre-allocated model is proposed in order to obtain reserving production capacity ATP and reserving components ATP for each customer class. Then, two order fulfilment models are formulated: the batch order fulfilment model for processing all orders during an order reception period and the real-time order fulfilment model for making order fulfilment decisions when an order arrives immediately. In case that the available production capacity and components are not enough, the ATP searching rules are developed along four dimensions (time dimension, customer demand priority level dimension, product dimension and selling area dimension). Finally, the proposed models are illustrated through an electronic product manufacturing case. The results of the case study show that the performance of the proposed order fulfilment system is better than that of the traditional one.     

Making supply chain design the rational differentiating characteristic of the OEMs

For more complex products that require customers to undertake learning in order to retrieve or realize the products’ true values, the product design and supply management decisions are different from those of less complex products. Nonetheless, in spite of the undeniable significance of coordinating decisions across product design and supply chain structures, we know very little about how to do so in practical ways. In this paper, we build on previous findings and offer a framework to enable the application of the supply chain structure design early in the new product introduction process. The proposed framework is based on a field study of the common practices in one of the major North American automakers, but we believe that it is widely applicable in other industries.     

Inventory policies analysis under demand patterns and lead times constraints in a real supply chain

This paper reports a study on a real three-echelon supply chain operating in the beverage sector. The authors, starting from the actual supply chain configuration, propose a detailed study of the inventory systems. The test of a comprehensive set of different operative scenarios, in terms of customers’ demand intensity, customers’ demand variability and lead times, becomes a powerful tool for inventory systems analysis along the supply chain. The main objective is the comparison of the actual supply chain configuration with optimistic and pessimistic scenarios for studying the behaviour of different inventory control policies and optimizing the inventory system of each supply chain node. Due to the dynamically changing and stochastic behaviour of the supply chain variables as well as the complex interactions among its actors, the authors have been pushed to implement an advanced simulation model supported by a ‘well-planned’ experimental design. In addition the paper aims to underline the research effort for conceptualizing, modelling, validating and simulating a real stochastic supply chain.     

Integrated planning in supply chains with buy-side and sell-side marketplaces

In this paper we develop a quadratic programming model for partner selection and planning in integrated supply chain networks embedded with both sell-side and buy-side electronic marketplaces. Such a scenario arises in several practical applications. In particular, we consider a contract manufacturer who procures components from suppliers through a component marketplace and sells its manufactured sub-assemblies to original equipment manufacturers (OEMs), through a sub-assembly marketplace. In these web-enabled supply chains, embedded with upstream and downstream electronic marketplaces, we need methods for online supply-chain partner selection based on pricing and delivery schedules. In this paper, we develop and present such a model that selects partners, synchronizes supply chain activities and optimizes the profit through optimal revenue pricing and cost minimization.     

Advance demand information and a restricted production capacity: on the optimality of order base-stock policies

This paper considers the optimality of order aggregation in a single-item production/inventory problem with advance demand information and a restricted production capacity. The advance demand information is modeled by introducing a positive customer order lead time. The paper proves, when customer order lead times are less than a threshold value, it is allowed to aggregate the orders over time when establishing the optimal production decision. This implies the optimality of an order base-stock policy. It shows also that in case of linear inventory cost, the positive effect of advance demand information is equal to a cost reduction that is proportional to idle time and foreknowledge horizon. The results hold for the backlogging case as well as for the lost-sales case.     

Emerging trends in supply chain architecture

This paper traces significant developments in technology, quality, measurement, and relationships that have led to the study of supply chain networks. The paper introduces five principles of supply chain networks—velocity, variability, vocalize, visualize, and value—that have moved supply chain architecture from an art to a science. Finally, the paper uses each principle to point to an important, emerging trend in supply chain architecture.     

An integrated approach to evaluating the production system in closed-loop supply chains

The increasing demands for environmental resource protection and sustainable development have been forcing enterprises to put sustainable supply chain management on their agendas in recent years. At the same time, intense global competition requires organisations to adopt practices that enable them to provide high-quality products and services. In this paper, we consider the problem of comprehensively evaluating the production system in closed-loop supply chains. We first propose an evaluation framework that consists of economic evaluation, product quality evaluation and ecological evaluation modules. Based on mathematical probability theory and the dynamic characteristics of reverse supply chain logistics, we then focus on the evolution dynamics in the quality evaluation dimension, where the concept of product quality, which builds on the reliability and the time-utility value of a product, is proposed. The basic production evaluation model is then extended to incorporate different sustainable procurement strategies, which take into consideration the trade-offs among cost, environment and quality. An outline and corresponding flow chart of corporate procurement strategy optimisation are provided which allow the proposed evaluation model to be implemented in computer-aided decision-making, further providing decision support for production system and supply chain management. Simulation and case studies are presented to promote a better understanding of the model approach and its managerial implications. Results also suggest that quality characteristics of components and sustainable procurement strategies are two important factors that determine the final production performance and should be paid special attention in closed-loop supply chain practice.     

Optimal echelon stock policies for multi-stage supply chains in fuzzy environments

This paper investigates decision-making in multi-echelon serial supply chain management in the presence of imprecision or uncertainty arising from human reasoning, emphasising the computational resolution. The proposed analysis method is based on a combination of the extension principle and the alpha-representation in fuzzy theory and optimisation theory. The problem is first formulated as a fuzzy optimisation model with several fuzzy parameters. To conserve the fuzziness of the input information of the supply chain, such as forecast market demands and inventory costs, a pair of two-level mathematical programs is proposed to identify the lower and upper bounds of the fuzzy performance at different possibility levels, so that the complete membership function can be described. Four example scenarios are solved to demonstrate the validity of the proposed analysis method. The proposed methodology is widely applicable with different types of membership functions for fuzzy parameters, positive lead times or other more complicated cases. The managerial implications are also discussed for reference by decision-makers.     

Optimal design methodologies for configuration of supply chains

This paper describes a methodology developed for designing an optimal configuration for a supply chain. A typical configuration for a supply chain consists of defining components of the system, assigning values to characteristics parameters of each component and setting operation policies for governing the interrelationships among these components. As such, each configuration will be defined by a set of values for quantitative parameters of the system as well as a set of policy and qualitative characteristics. Examples of quantitative variable include inventory levels and frequency of ordering where as location of distribution centres and mode of transportation between suppliers and the original equipment manufacturers (OEM) are the decision variables of policy and qualitative nature. The methodology presented here consists of a supply chain model builder coupled with two optimisation algorithms that automatically build a sequence of configurations that systematically move towards an optimum design. A combination of mixed integer programming and a genetic algorithm is used to determine simultaneously the values of quantitative as well as policy variables. The solution consists of strategic decisions regarding facility locations, stocking locations, supplier selection, production policies, production capacities, and transportation modes.     

Joint multi-objective master production scheduling and rolling horizon policy analysis in make-to-order supply chains

This research studies multi-objective master production schedule (MPS) and advanced order commitment (AOC) in two-stage supply chains. Simulation-based experimental analysis evaluates the impact of environmental and MPS design factors on schedule cost and instability. The results provide insight into multi-objective MPS design considerations through rolling schedule policies. The study reveals that the manufacturer’s production smoothness utility coefficient and its interaction with other experimental factors considerably impact on the system’s performance. In addition, it introduces a simulation framework with embedded mixed integer programming models that could be used as a framework for future research dealing with integrated multi-stage MPS/AOC policy in a variety of planning contexts.     

A study on contractual agreements in supply chains of agricultural produce

Agricultural produce deteriorates in both quality and quantity over time, and how to determine appropriate operating and marketing strategies to reduce the loss from rottenness is essential in supply chains for such items. This study considers a two-echelon supply chain in which agricultural produce is provided by a grower to a wholesaler, and the harvest quantity for the grower may decrease due to unpredictable pest problems or weather factors. In addition, agricultural produce may be damaged during transportation and thus become inferior products with less value. The two different scenarios are considered in this study: with and without a contractual agreement, to develop the corresponding optimal pricing strategies for the grower and wholesaler. The results indicate that a contractual agreement by setting moderate ordering boundaries can achieve a win-win situation for both parties by mitigating the grower’s risk, since it can encourage the grower to plant more produce and thus ensure that the wholesaler can have enough produce to sell. Besides, in case that a low proportion of inferior products and a low discount rate can be managed, the use of contractual agreements would be beneficial for the grower. Moreover, the rise in the retailing prices of both the regular and inferior agricultural produce may collectively increase the total profit of the supply chain, but can actually hurt the wholesaler’s profit.     

Evaluating order acceptance policies for divergent production systems with co-production

The impacts of using different order acceptance policies in manufacturing sectors are usually well known and documented in the literature. However, for industries facing divergent processes with co-production (i.e. several products produced at the same time from a common raw material), the evaluation, comparison and selection of policies are not trivial tasks. This paper proposes a framework to enable this evaluation. Using a simulation model that integrates a custom-built ERP, we compare and evaluate different order acceptance policies in various market conditions. Experiments are carried out using a case from the forest products industry. Results illustrate how and when different market conditions related to divergent/co-production industries may call for available-to-promise (ATP), capable-to-promise (CTP), and other known strategies. Especially, we show that advanced order acceptance policies like CTP may generate a better income for certain types of market and, conversely to typical manufacturing industries, ATP performs better than other strategies for a specific demand patterns.     

An empirical investigation of antecedents to information exchange in supply chains

In this investigation, following the principal-agent theory, possibilities to reduce existing information asymmetries are derived and their effects on the information exchange are examined. Results of an empirical investigation based on a structural equation model confirm that monitoring measures and frequent meetings positively influence the exchange of information while explicit contracts have rather negative effects. Premiums and specific investments, however, seem to play insignificant roles. Measures, such as building a reputation mechanism, will probably prove to be effective only in the long run.     

Value of information exchange and synchronization in a multi-tier supply chain

We investigate the value of various information exchange mechanisms in a four-echelon supply chain under a material requirements planning framework. In the absence of any information sharing, each echelon would develop its own forecasts and plan its inventories based on the history of actual demand from its downstream customer (or echelon). Through a simulation study, we compare this policy with policies where each echelon has access to (i) the end-user demand history and (ii) the planned order schedule of the downstream echelon. Among all the demand information exchange mechanisms, planning inventories based on the planned downstream order schedules resulted in the lowest average inventory level for the entire supply chain. However, use of end-user demand history to forecast and plan inventories at all echelons resulted in the lowest total cost. In addition to the information exchange mechanisms, a simple synchronized replenishment system was considered and evaluated in the study. In the synchronized system, the retailer determines a fixed order interval and the upper echelons replenish only at integer multiples of this interval. The study found that synchronized inventory replenishments among the echelons, even without any exchange of demand information, can bring about more benefits and cost reduction than any of the information exchange mechanisms.     

Investigating the implications of extending synchronized sequencing in automotive supply chains: the case of suppliers in the European automotive sector

In recent years automakers have paid considerable attention to synchronizing supply chain material flow. Potential benefits associated with synchronization include stability in both demand and supply patterns, inventory reduction, elimination of demand amplification and better long-term planning. In major European production sites, the geographic proximity of suppliers to the vehicle assembly plants provided the motivation for examining the feasibility of extending the synchronized sequenced delivery of components upstream in the vehicle supply chain. The value stream used in the research concerned the seating systems at two major European production sites. The results of extending synchronized sequencing from the first to the second tier showed a reduction in demand amplification to negligible levels, achieved overall synchronization levels of 99–100% and considerably reduced overall pipeline inventory between the vehicle assembly plant and the second tier component supplier. The findings suggest how the geographic proximity of suppliers can be used to implement multi tier synchronized sequencing of components to improve supply chain performance. Based on the results of the study a series of recommendations are provided concerning the supply chain implications of multi tier synchronized sequencing.     

Measuring information distortion in real-world supply chains

After years of being thought to be an inevitable fact of life, demand information distortion (Bullwhip effect) is now increasingly coming under scrutiny by researchers, with conflicting findings being reported about its existence. The conflicting reports are partly due to the measurement issues surrounding Bullwhip, and partly due to the changed business practices in some sectors which the Bullwhip construct was perhaps not originally designed to capture. This article attempts to reconcile these issues. It integrates two distinct dimensions of information distortion: amplification of order variance and schedule instability, and proposes a framework to capture the underlying information distortion more comprehensively. The framework is illustrated through a case study of an automotive supply chain under real-world considerations such as capacity limits and contemporary IT-enabled information sharing practices. The ‘degree of over-ordering’ was found to be a good indicator of information distortion.