Bullwhip and inventory variance in a closed loop supply chain

A simple dynamic model of a hybrid manufacturing/remanufacturing system is investigated. In particular we study an infinite horizon, continuous time, APIOBPCS (Automatic Pipeline Inventory and Order Based Production Control System) model. We use Åström’s method to quantify variance ratios in the closed loop supply chain. Specifically we highlight the effect of a combined “in-use” and remanufacturing lead-time and the return rate on the inventory variance and bullwhip produced by the ordering policy. Our results clearly show that a larger return rate leads to less bullwhip and less inventory variance in the plant producing new components. Thus returns can be used to absorb demand fluctuations to some extent. Longer remanufacturing and “in-use” lead-times have less impact at reducing inventory variance and bullwhip than shorter lead-times. We find that, within our specified system, that inventory variance and bullwhip is always less in supply chains with returns than supply chains without returns. We conclude by separating out the remanufacturing lead-time from the “in-use” lead-time and investigating its impact on our findings. We find that short remanufacturing lead-times do not qualitatively change our results.     

Modelling customer and technical requirements for sustainable supply chain planning

Sustainable supply chains are the need of modern times. In order to make them successful, listening to voice of the customer and integrating them in the design and development phases of supply chains are very important. In this paper, we propose a technique called sustainability function deployment (SFD) developed on the concept of quality function deployment (QFD) to model customer and technical requirements, establish relationship between them and prioritise them for developing sustainable supply chains. SFD gathers customer and technical requirements for sustainable supply chain planning using C-REQ and T-REQ surveys, generates priority of customer requirements using Priority Matrix, performs screening of technical requirements using gap analysis, and generates requirements weights using QFD, thereby providing a structured approach to the decision-makers to select the right areas of improvement. Both the customer and technical requirements are captured from a socio-economic-environmental perspective. Results of application of the proposed technique are provided. The strength of the proposed approach is its novelty in integration of priority matrix and gap analysis in prioritising requirements based on their importance and performance in SFD. Besides, SFD facilitates modelling of complex, interrelated requirements in sustainable supply chain planning.     

Additive manufacturing technology in spare parts supply chain: a comparative study

Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains.     

Sustainable supply chains for supply chain sustainability: impact of sustainability efforts on supply chain risk

Supply chain managers across the globe are finding it difficult to manage the increasingly complex supply chains despite adopting a variety of risk mitigation strategies. Firms on the other hand have also been adopting various kinds of environmental and social sustainability practices in recent times to reduce carbon footprint and improve their image on the social front. However, very few studies in the extant literature have examined the impact of sustainability practices on supply chain risk. We address this important gap in literature by empirically testing this relationship, using primary data from six manufacturing sectors and 21 different countries including developed as well as emerging markets across the globe. Our findings indicate that risk mitigation strategies do not always reduce the actual supply chain risk experienced by firms, whereas sustainability efforts help reduce supply chain risk, especially in emerging market contexts. In addition, we find that, while reactive risk mitigation strategies on their own fail to reduce supply chain risk, they are effective when used in conjunction with sustainability efforts. We also find that preventive risk mitigation efforts are only effective in mature supply chains such as the OECD countries.     

Metrics for supply chain sustainability

Most interpretations of sustainable development recognise that there are constraints on long-term human activities imposed by material and energy availability and by the capacity of the planet to accommodate wastes and emissions; inter- and intra-generational equity within these constraints is then an ethical principle underlying sustainability. This leads to identifying three dimensions of sustainable development: techno-economic, ecological and social. This paper reviews the development of indicators to reflect these three dimensions, applicable to industrial sectors, companies and broad groups of products or services. Indicators of environmental and economic performance are relatively well established. They can be combined to indicate the sustainability of products, services and supply chains. Indicators of social performance are more problematic, particularly indicators to describe the social value of products and services. Cases from the process, petroleum and petrochemicals, electronics and fast moving consumer goods sectors are reviewed, showing that social indicators must be developed through public participation.     

丰田JIT实现方法分析

通过系统分析丰田车辆计划、订单物流模式以及工厂内物流方式,在操作层面提供了一套实现JIT的方法,并总结提出了实现JIT的三个必要条件:平准化、进度引取和小批量多频次物流.     

A blockchain-based approach for a multi-echelon sustainable supply chain

Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.     

Pricing decisions for a supply chain with refurbished products

This paper considers a supply chain consisting of a supplier and a retailer where a fixed portion of new products sold will be returned to the retailer and then be repaired and resold as refurbished products at a lower price. Using the utility model, we formulate how consumers will make their choices when facing both new and refurbished products. Then, using the divide-and-conquer method, we derive the supplier and retailer's equilibrium decisions, including the supplier's wholesale price and the retailer's prices for both the new and refurbished products. The main findings include the following. First, refurbished products will be sold in the market only when the refurbishing cost is small. In this situation, as the refurbishing cost increases, most of the negative impact on the retailer will be transferred to the supplier. Second, in the same condition, as the refurbishing cost increases, the wholesale price and retail price of the new product will change in opposite directions. This result contrasts with the traditional pass-through effect. Third, when the repair cost is moderate, the retailer will eventually not sell refurbished products, but its profit can be significantly improved and the double marginalisation effect can be mitigated.     

A green supply chain is a requirement for profitability

Many companies are not dramatically changing to more sustainable environmental practices despite pressure from the investment community, the government and consumers. This study explores a simple model that companies can use to understand and improve supply chain sustainability practices. It applies this model in two case studies, Coca-Cola, a leader in global sustainability, and Apple, a company that has only recently started to develop a sustainability strategy. The model was developed through a review of existing research and an application of supply chain principles. The results of this study demonstrate that following this model to eliminate waste throughout the supply chain will make the supply chain more profitable. The outcomes from this study highlight the importance for every company to do so in order to stay competitive. This study is unique in the relative simplicity of its model, combined with the supporting evidence that a sustainable supply chain is the same as a supply chain that is using best practices to reduce waste.     

Policy mechanisms for supply chain coordination

The problem is to determine a review period and stocking policy that are mutually beneficial to a producer and a retailer. In our model, the retailer uses a periodic review, base stock policy for ordering the item from the producer's Distribution Center (DC). Excess customer demand is assumed to be lost. A make-to-order production system supplies to the DC. We show that given a review period, unless the manufacturer agrees to share the cost of carrying a fraction of the safety stocks at the retailer, the two will not agree upon the level of stocks to be carried in the store. We prove that there is an equilibrium value for this fraction, such that the retailer and the manufacturer are always in agreement with regard to the stocking level. We then show that complete coordination on the stocking level as well as the review period can be achieved solely through carrying out negotiations on credit terms. These theoretical results are used to construct an algorithm for calculating the optimal policy parameters for a supply chain. As part of the analysis we suggest a modification of the base stock policy for the positive lag lost sales case of periodic review inventory models that consistently outperforms the base stock policy in our numerical studies.     

Implications of postponement for the supply chain

As a marketing, logistics and manufacturing concept, postponement has been around in the literature for a long time. Its application can also be dated to the 1920s. However, only in recent times has it been used as a supply chain strategy. Postponement fosters a new way of thinking about product design, process design and supply chain management. In this paper, we rethink the supply chain from a postponement point of view and present the implications of postponement for the decoupling point, supply chain integration, control of the supply chain and capacity planning issues. The objective is to extend the significance of postponement towards the perspective of a holistic supply chain context.     

Dynamic allocation of uncertain supply for the perishable commodity supply chain

Dynamic logistics control of a perishable commodity is especially crucial due to the difficulties in preservation of freshness, disposal of deteriorated commodities, and uncertainty of supply caused by seasonal fluctuation or abrupt variation of the weather. First, this paper formally presents the Dynamic Allocation Problem with Uncertain Supply (DAP/US) for the perishable commodity supply chain (PC-SC). The objectives of the DAP/US problem are to maximize the total net profit of the strategic alliance of the PC-SC and to determine the optimal orders placed to suppliers and the resultant amount of perishable commodities allocated to retailers. Secondly, a two-stage extended-Genetic Algorithm (eGA) is developed to control the dynamic orders and allocation quantities to prioritized suppliers and retailers, respectively. Thirdly, simulation experiments are conducted and it is shown that eGA demonstrates promising performance under various sizes of problem domains and different statuses of supply uncertainty. Lastly, analytical simulations are also conducted to compare eGA with the traditional approach that ignores the differences among suppliers' supply uncertainties. The simulation results show that eGA achieves great improvement in both the net profit and shortage rates for all sizes of the PC-SCs, with half of their suppliers and retailers having high supply capabilities and fast turnover demands, respectively.     

The influence of additive manufacturing on the configuration of make-to-order spare parts supply chain under heterogeneous demand

Additive manufacturing (AM), alongside technological developments, has been used in the production of spare parts with positive results for spare parts supply chains. In this study, we investigate spare parts supply chains serving heterogeneous demands from multiple service locations under the mode of make-to-order. We aim to compare different configurations (i.e. centralised and distributed) of spare parts supply chains in terms of their performance (e.g. sojourn time and cost) and to further propose suggestions to better configure AM-based spare parts supply chains by effectively allocating AM machines at service locations (SLs) or regional distribution centres (RDCs). In order to realise these research objectives, the simulation approach is used as the main research method. Different from the existing perception, our results illustrate that the distributed deployment of AM machines does not always guarantee a quick response, and that centralised configuration is desirable when the demand rate is relatively high due to the pooling effect. The distributed configuration, however, can still be suitable, considering the development of AM technology. Our results also indicate the possibility of a mixed configuration of AM-based supply chains with the potential for outperforming the purely centralised/distributed configuration. The criteria to design such a mixed configuration are also offered.     

A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management

In this paper, we present a multi-stage hybrid model for analysing a supply chain network (SCN) collapse recovery possibility. In the first stage of the model, we analyse the ability of an SCN to fulfil its customers required due date (RDD). As soon as the SCN defaults to timely fulfil their customers RDD, the second stage of the model is triggered to measure the collapse recovery possibility (CRP) of the SCN. Then, we calculate the final collapse recovery possibility (FCRP) of the SCN. Since the operation times, customer demand and external supply of raw material are uncertain, we use fuzzy triangular numbers to estimate the value of foregoing parameters. Consequently, we employ fuzzy program evaluation and review technique (FPERT) to calculate the completion time of SCN operations. In the third stage, for the critical elements of the SCN obtained from FPERT, the SC simulator is developed to provide a dynamic view of the SC and assesses the impact of decisions recommended by the SC fuzzy models on SC performance. Moreover, an empirical example is presented to validate the effectiveness of the proposed model. Finally, we conduct sensitivity analysis on the parameters employed in the model to analyse the behaviour of each parameter.     

A real-options-based analysis for supply chain decisions

Flexibility allows firms to compete more effectively in a world of short product life cycles, rapid product development, and substantial demand and/or price uncertainty. We develop a supply chain model in which a manufacturing firm can have the flexibility to select different suppliers, plant locations, and market regions and there can be an implementation time lag for the supply chain operations. We use a real options approach to estimate the value of flexibility and to determine the optimum strategy to manage the flexibility under uncertainty in the currency exchange rate. To price the operational flexibility, we develop a Monte Carlo simulation technique that is able to incorporate a large number of variables into the valuation. We show that without considering time lag impact, the value of the operational flexibility can be significantly overestimated.     

Pricing and effort decisions for a supply chain with uncertain information

This paper analyses the pricing and effort decisions of a supply chain with single manufacturer and single retailer. The manufacturer produces a kind of product and then wholesales the product to the retailer, who in turn retails it to customers over a single selling season. The retailer can influence demand through her sales effort. This research depicts the consumer demand, the manufacturing cost and the sales effort cost as uncertain variables. Considering the demand expansion effectiveness of sales effort, one centralised and three decentralised game models are built on the basis of the expected value criterion, and the equilibrium solutions are obtained. We investigate the effects of the parameters’ uncertainty degrees on the pricing and effort decisions. The results indicate that the manufacturer benefits from improvement in demand and cost uncertainties when he has at least bargaining power in the supply chain. The results also imply that the uncertainty degree of sales effort elasticity has an outstanding influence on the pricing and effort decisions, whereas the uncertainty degree of price elasticity has a modest impact on these decisions. We also study the effects of the parameters’ uncertainty degrees on the supply chain from the consumers’ perspective. The results suggest that with a power retailer, the retail price should always be on the high end. Consequently, consumers do not necessarily benefit from a power retailer. When the manufacturer and the retailer have equal bargaining power, consumers do not necessarily benefit from the supply chain, either.     

On measuring company performance within a supply chain

Emerging research strengthens the connection between supply chain performance and a company's financial performance (D’Avanzo, R., Von Lewinski, H. and Van Wassenhove, L. N., 2003. The link between supply chain and financial performance. Supply Chain Management Review, November/December, 40–47). The focus on integrating functional internal processes has expanded to include the need for integrating these with external processes of business partners (Edwards, P., Peters, M. and Sharman, G., 2001. The effectiveness of information systems in supporting the extended supply chain. Journal of Business Logistics, 22(1), 1–27). This need for enterprise efficiency is compelling companies to review, to identify, and to adopt supply chain initiatives. This research investigates the use of common measurement metrics in an attempt to determine which one(s) are most useful for measuring performance as companies implement SCM practices. For firms that were engaged in SCM we found inventory and cycle time to be the most significant metrics.     

Coordinating a three-level supply chain with quantity discounts

Numerous examples exist that illustrate how companies enjoying a strong position in a supply chain unilaterally dictate terms to their suppliers and/or their customers. This paper suggests a mechanism by which a company can coordinate its purchasing and production functions and create an integrated plan that dictates order and production quantities throughout a three-firm channel. Specifically, we model a company that attempts to dictate channel lot sizes by obtaining a quantity discount from its supplier while offering perhaps a different one to its customer. Previous quantity discount research has examined supply chains consisting of only two levels, a seller and a buyer. This paper considers a three-level chain (supplier–manufacturer–retailer) and explores the benefits of using quantity discounts on both ends of the supply chain to decrease costs. We show that incorporating quantity discounts into both ends of the supply chain can significantly decrease costs compared to concentrating only on the lower end. Furthermore, the results of the decentralized procedure described here are robust vis-à-vis a centralized decision-making procedure.     

Coordination of joint pricing-production decisions in a supply chain

We consider the coordination of dynamic, joint pricing-production/ordering decisions in a decentralized supply chain where a manufacturer outsources her product distribution/retailing function to an independent distributor/retailer. The manufacturer produces and wholesales her product to the distributor who, after some further processing, sells the product to an external market. In a leader-follower setting with convex production/ordering cost functions, both parties make pricing and production/ordering decisions over a discrete, finite-time horizon (a selling season) to maximize their respective profits. For a given manufacturer's (the leader's) wholesale price schedule, we develop a simple forward algorithm to solve the distributor's problem optimally, and prove a planning horizon property of the solution. Our key result is to show the existence of a manufacturer's price schedule that induces distributor to adopt decisions in the decentralized setting to achieve the performance of a centralized supply chain. Based on this channel-optimal pricing policy we then develop an incentive scheme for the manufacturer to achieve channel coordination. A numerical example is provided to compare the performance of different policies and lo reinforce key managerial insights generated through analysis.     

Bayesian network modelling for supply chain risk propagation

Supply chain risk propagation is a cascading effect of risks on global supply chain networks. The paper attempts to measure the behaviour of risks following the assessment of supply chain risk propagation. Bayesian network theory is used to analyse the multi-echelon network faced with simultaneous disruptions. The ripple effect of node disruption is evaluated using metrics like fragility, service level, inventory cost and lost sales. Developed risk exposure and resilience indices support in assessing the vulnerability and adaptability of each node in the supply chain network. The research provides a holistic measurement approach for predicting the complex behaviour of risk propagation for improved supply chain risk management.