Three-echelon Supply Chain Research Articles

Carbon emission reduction cooperation of three-echelon supply chain under consumer environmental awareness and cap-and-trade regulation.

Considering that both the manufacturer's production process and the transporter's freight process produce carbon emissions, this paper constructed a three-echelon supply chain composed of a manufacturer, a transporter, and a retailer. This article studies the cooperative carbon emission reduction among the supply chain members under the carbon cap-and-trade policy and consumer environmental awareness. We used the Stackelberg game to explore four scenarios as follows: (1) in the non-cooperative decision model, no cooperation takes place among all supply chain members; (2) in the local cooperation decision of the manufacturer and the transporter alliance model, the manufacturer and the transporter work together to make decisions reducing carbon emissions, but each member of the supply chain makes its own pricing decisions; (3) in the local cooperation decision of the retailer-transporter alliance model, there is no cooperation except that the retailer and the transporter cooperate with each other to determine the selling price of the product; and (4) in the overall-cooperative decision model, there is complete cooperation among the members of the supply chain, who collectively decide on carbon emission reduction and the selling price of the product. Then, using the backward induction method, we derived and compared the equilibrium solutions and the profits of the supply chain system. The results showed that the scenario of complete cooperation among all supply chain members had the best performance in carbon emission reduction, market equilibrium quantity, and the supply chain system's profit, but the selling price of the product was likely to be higher than other scenarios. Two contracts have been proposed to coordinate the supply chain system. The cost-sharing contract is effective but imperfect under limited constraints. The two-part tariff contract can realize perfect coordination of the supply chain. Finally, we obtained several interesting conclusions from the numerical example and provide managerial insights and policy implications from the analytical results.

Pricing and green decision-making in a three-echelon supply chain considering fairness concern with the participation of green logistics

Pricing and green decision-making in a three-echelon supply chain considering fairness concern with the participation of green logistics

Pricing strategy and order quantity allocation with price-sensitive demand in three-echelon supply chain

A key objective of this paper is to investigate the supply chain coordination frameworks to minimize the double marginalization effect in the case of price-sensitive demand. This paper investigates the impact of pricing strategy and ordering/production policy on the performance of a three-layer supply chain by using the Salop spatial model. The Nash Game approach determines the best price and order quantity to locally maximize the expected profits of the individual members in the decentralized supply chain. The total profit of the centralized structure is used as the benchmark to validate the channel member’s decision on the selling price and order quantity. A numerical analysis has been conducted to confirm the theoretical results.

Applied real-valued genetic algorithm for an extended model of economic lot, purchase and delivery scheduling problem

Abstract Supply chain management intends to integrate supply chains' activities such as material flow, information flow and financial issues. Material flow management is the most significant issue since the inventory level in the whole supply chain could be optimized by an integrated plan. In other words, when one member of the supply chain plans to reduce its inventory level solely, despite reducing inventory in this node the inventory will be stocked in other partners' warehouses. Therefore, in this paper a new mathematical model has been developed to facilitate the process of finding the optimum solution in economic production, purchase and delivery lots and their schedules in a three-echelon supply chain environment; including raw material in suppliers, manufacturer and assembly facility as a customer. The manufacturer with a flow shop system provides its requirements from supplier, assemble multiple products, and delivers products to the customer (automotive OEM alike) on an optimum multiple delivery points. The delivery cycles would be identified through the production common cycle regarding the supply chain flexibility. Finally, a modified real-valued Genetic Algorithm (MRGA), and an Optimal Enumeration Method (OEM) are developed, and some numerical experiments have been done and compared as well.

Financing and operating strategies for blockchain technology-driven accounts receivable chains

We focus on blockchain technology (BCT) adoption in a three-echelon supply chain in which upstream sellers offer trade credits to capital-constrained downstream buyers, forming an accounts receivable chain. According to different supply chain partners adopting BCT, we analyze the game equilibrium of the no, upper-stream, lower-stream, and entire BCT-driven accounts receivable chains (NBC, UBC, LBC, and EBC) to understand participants’ motivation and condition to adopt BCT and the different roles of participants in blockchain introduction. We find that trade credit management cost-saving and repayment risk-sharing effects, as facilitated by BCT, help increase the equilibrium order quantity, thereby increasing supply chain efficiency and participants’ profits, although BCT cannot fully coordinate the supply chain. Regarding supply chain efficiency, EBC is superior to LBC, which is better than UBC or NBC. As a supply chain leader and creditor, the supplier plays a passive role in achieving the positive effect of BCT. Given that the retailer and manufacturer are supply chain followers and debtors, their adoption of BCT is the key to enhancing supply chain efficiency and profits. The BCT platform can set appropriate technology-usage fees to guide participants to form the EBC structure through different paths. Meanwhile, the retailer’s initial working capital can evaluate the risk-sharing degree of the supply chain, and the stable EBC selection region defined by the risk-sharing degree can be ascertained. We further find that with the trade credit insurance premium increasing, supply chain participants have become more active in adopting BCT.

Complexity in three-echelon supply chain network and manufacturing firm’s operational performance

The purpose of this paper is to understand the combined impact of supply chain structural complexity and operational complexity on the operational performance of manufacturing firms in a three-echelon supply chain network. The paper uses Shannon’s information entropy theory and agent-based modeling to find the intended relationships. The structural complexity is represented by the numbers of customers and suppliers associated with the focal manufacturing firm, whereas the operational complexity is represented by demand variability experienced by the manufacturing firm. The operational performance of the manufacturing firm is measured in terms of its capacity utilization, demand fulfillment, and inventory level. The paper finds that increasing the number of customers reduces capacity utilization and demand fulfillment, and increases inventory level whereas increasing the number of suppliers increases capacity utilization, demand fulfillment, and inventory level for the focal manufacturing firm. The results also show that increasing the number of customers and suppliers together initially improves the capacity utilization and demand fulfillment of the manufacturing firm but these deteriorate subsequently. Furthermore, increasing operational complexity reduces the operational performance of the firm. Thus, the paper finds how the operational performance of the focal manufacturing firm changes with the changes in supply chain structural complexity and operational complexity in a three-echelon supply chain. The results imply that manufacturing firms need to carefully orchestrate their supply chain network as increasing the number of customers and suppliers in the network does not necessarily improve their operational performance.

Backup Agreement as a Coordination Mechanism in a Decentralized Fruit Chain in a Developing Country

This paper aims to analyze the impacts of a backup agreement contract on the performance of a small agricultural producers’ citrus supply chain. A backup agreement contract, which ensures for each echelon that a quantity of products will be bought independently of real demand, is proposed to coordinate a three-echelon supply chain, aimed at improving income. After presenting an overview of the literature that shows various coordination mechanisms but no backup agreement proposals for supply chain coordination, this paper develops a decentralized three-echelon supply chain facing stochastic customer demand and includes the backup agreement as a coordination mechanism to guarantee a balanced relationship between the chain members. The model is tested in a real case study in Colombia, and a sensitivity analysis is provided. Results show that a backup agreement contract coordinates the small agricultural producers’ supply chain and improves income for each echelon, especially for the small producer. However, the economic mechanism complexity can limit coordination among echelons, mainly because of a lack of trust and consolidated supply capacity from small farmers. The foregoing requires the development of an associative structure by small producers, which is proposed as future research work.

Integrated inventory and transportation management with stochastic demands: A scenario-based economic model predictive control approach

The integration of inventory and transportation operations is a challenging task in multi-echelon supply chain management. Uncertainties in customer demands can have serious consequences, such as inventory fluctuations and transportation changes. Policies of integrated inventory and transportation management aim to find a balance between supply and demand and can minimize the total operating cost for the entire supply chain. In this study, we propose a scenario-based economic model predictive control (EMPC) framework for integrated inventory and transportation management of multi-echelon supply chains with stochastic demands. The proposed scenario-based EMPC framework can provide real-time optimal operations for automated inventory and transportation management with a minimum operating cost and a guaranteed risk probability. As the number of scenarios is linked with the risk probability, we develop a design condition to choose the number of scenarios and ensure that optimal operations from the proposed framework can guarantee the desired risk probability. Finally, we present a case study of a three-echelon supply chain benchmark to demonstrate the effectiveness of the proposed EMPC framework and provide several comparison results to show its performance.

A three-echelon based sustainable supply chain scheduling decision-making framework under the blockchain environment

The Supply Chain Scheduling (SCS) decision making is a challenging task under the blockchain environment because the supply chain is composed of multi-players in all layers. To utilise the information sharing by multiplayers with equal rights in all layers to maximise the supply chain’s utility for reducing the carbon emission, this study proposed a three-echelon supply chain integrated scheduling model that considers the production capacity and multi-product with different delivery time factors. The objective is to minimise the total cost incurred in production and transportation under the blockchain environment. To cope with the complexity arising from multiplayers with equal rights in all layers, a metaheuristic based sequential brain storm optimisation (SBSO) algorithm with a novel encoding scheme and the hybrid crossover and mutation strategy is proposed to enhance the performance. A case study comparing the proposed decision-making framework with the artificial bee colony algorithm (ABC) and the backtracking search algorithm (BSA) is conducted, and results show the superiority of the proposed framework. With the help of the proposed SCS decision-making framework, not only can the SCS decision be made, but also the low efficient nodes within the supply chain under the blockchain environment can be identified for potential sustainable upgrading.

A joint economic lot-size model with collaboration of supply chain members

PurposeThe purpose of this study is to investigate a joint economic lot-size model with the possibility of cofinancing between members of a three-echelon supply chain (SC) including one supplier, one manufacture and one retailer. Given the differences in credit as well as differences in access to capital markets, SC members will be able to create a financial alliance to maximize the profits of each member. This study proposed a model to maximize the annuity stream of the SC by considering the financial interaction between SC members.Design/methodology/approachThis joint economic lot-sizing problem was described and modeled mathematically. To evaluate the mathematical model, different scenarios were considered with (and without) the possibility of financial interaction.FindingsIt is suggested that, in addition to the goods and information flow among SC members, proper financial flow can also have an impact on the improvement of SC performance.Originality/valueWhile previous studies consider cofinancing between members of a two-echelon SC, this paper considers a three-echelon SC including one supplier, one manufacturer and one retailer where financial cooperation between different levels of the SC in both upstream and reverse directions will be possible.

Optimal inventory replenishment and shipment policies in a three-echelon supply chain for growing items with expiration dates

Optimal inventory replenishment and shipment policies in a three-echelon supply chain for growing items with expiration dates

Green sustainable supply chain under cap and trade regulation involving government introspection

This paper investigates Government intervention in a three-echelon supply chain comprising one manufacturer and one retailer. Government is the top level member trying to reduce environmental impacts based on the amount of carbon emission during the production process. Government controls the chain by collecting tax from the retailer which is indirectly paid by the customer and paying subsidy/imposing fine on the manufacturer. Government encourages manufacturer to reduce carbon emission by contributing some subsidy and also makes an effort to generate Government net revenue (GNR) by imposing tax. The GNR is generated by collecting tax from the retailer on the sold product and penalty from the manufacturer at the trading price for the extra amount of emissions. The retail price is decided based on the selling price, tax and greening level. We aim to determine optimal levels of pricing, greening and amount of tax to be levied. The models for both linear and iso-elastic demand patterns are developed. The aim of this piece research is two-fold: (i) review the existent literature on the relationship between environmental collaboration and sustainability performance and (ii) render a tenable prototype of supply chain to illuminate the relationship between sustainability and profitability. According to the aforesaid goals this paper has carried out a detailed empirical research by using advanced structural equation modelling approaches. The research findings will be particularly important for manufacturing companies struggling to find techniques to achieve sustainability performance. Also it will aid the supply chains in developing environmental collaboration with the Govt. in order to attain the targets of GSCM.

Dynamical Investigation, Electronic Circuit Realization and Emulation of a Fractional-Order Chaotic Three-Echelon Supply Chain System

This study is concerned with dynamical investigation, electrical circuit realization, and emulation of a fractional three-echelon supply chain system. In the financial realm, long-term memory effects play important roles. On the other hand, most financial systems are uncertain with unknown nonlinear dynamics. However, most studies on nonlinear supply chains neither consider the fractional calculus nor take advantage of state-of-the-art emulation methods. These issues motivated the current study. A fractional-order chaotic three-echelon supply chain system is studied. At first, the system’s dynamic is studied through Lyapunov exponent and bifurcation diagrams. It is shown that a slight deferent in some parameters of the system can dramatically change the behavior of the system. Then, a real-time analog circuit is designed and implemented to investigate the system’s chaotic behavior. This way, the system’s chaotic attractors are empirically demonstrated. Finally, emulation and interpolation of the fractional-order chaotic system using the Gaussian process have been studied, and its luminous results have been presented.

Performance of three-echelon supply chain under uncertainty: influence of contract sequence and individual rationality

PurposeIn the paper, the authors study the simultaneous influence of incentive compatibility and individual rationality (IR) on a multi-echelon supply chain (SC) under uncertainty. The authors study the impact of contract sequence on coordination strategies of a serial three-echelon SC consisting of a supplier, a manufacturer and a retailer in an uncertain environment.Design/methodology/approachThe authors develop a game-theoretic framework of a serial decentralized three-echelon SC. Under a decentralized setting, the supplier and the manufacturer can choose from two contract types namely, wholesale price (WP) and linear two-part tariff (LTT) and it leads to four different cases of contract sequence.FindingsThe study show that SC coordination is possible when both the supplier and the manufacturer choose LTT contract. This study not only identifies the influence of contract sequence on profit distribution among SC agents, but also establishes cut-off policies for all SC agents for each contract sequence. This study also examine the influence of chosen contract sequence on optimal profit distribution among SC agents.Research limitations/implicationsThree-echelon SC coordination under uncertain environment depends upon the contract sequence chosen by SC agents.Practical implicationsThis study results will be helpful to managers of various SCs to take operational decisions under uncertain situations.Originality/valueThe main contribution of this study is that it explores the possibility of coordination by supply contracts for three-echelon SC in a fuzzy environment.

Off-Site Construction Three-Echelon Supply Chain Management with Stochastic Constraints: A Modelling Approach

Off-site construction is becoming more popular as more companies recognise the benefits of shifting the construction process away from the construction site and into a controlled manufacturing environment. However, challenges associated with the component supply chain have not been fully addressed. As a result, this study proposes a model for three-echelon supply chain supply management in off-site construction with stochastic constraints. In this paper, multiple off-site factories produce various types of components and ship them to supplier warehouses to meet the needs of the construction sites. Each construction site is directly served by a supplier warehouse. The service level for each supplier warehouse is assumed to be different based on regional conditions. Because of the unpredictable nature of construction projects, demand at each construction site is stochastic, so each supplier warehouse should stock a certain number of components. The inventory control policy is reviewed regularly and is in (R, s, S) form. Two objectives are considered: minimising total cost while achieving the desired delivery time for construction sites due to their demands and balancing driver workloads during the routeing stage. A grasshopper optimisation algorithm (GOA) and an exact method are used to solve this NP-hard problem. The findings of this study contribute new theoretical and practical insights to a growing body of knowledge about supply chain management strategies in off-site construction and have implications for project planners and suppliers, policymakers, and managers, particularly in companies where an unplanned supply chain exacerbates project delays and overrun costs.

Designing a locating-routing three-echelon supply chain network under uncertainty

PurposeIn the present research, location and routing problems, as well as the supply chain, which includes manufacturers, distributor candidate sites and retailers, are explored. The goal of addressing the issue is to reduce delivery times and system costs for retailers so that routing and distributor location may be determined.Design/methodology/approachBy adding certain unique criteria and limits, the issue becomes more realistic. Customers expect simultaneous deliveries and pickups, and retail service start times have soft and hard time windows. Transportation expenses, noncompliance with the soft time window, distributor construction, vehicle purchase or leasing, and manufacturing costs are all part of the system costs. The problem's conceptual model is developed and modeled first, and then General Algebraic Modeling System software (GAMS) and Multiple Objective Particle Swarm Optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGAII) algorithms are used to solve it in small dimensions.FindingsAccording to the mathematical model's solution, the average error of the two suggested methods, in contrast to the exact answer, is less than 0.7%. In addition, the performance of algorithms in terms of deviation from the GAMS exact solution is pretty satisfactory, with a divergence of 0.4% for the biggest problem (N = 100). As a result, NSGAII is shown to be superior to MOSPSO.Research limitations/implicationsSince this paper deals with two bi-objective models, the priorities of decision-makers in selecting the best solution were not taken into account, and each of the objective functions was given an equal weight based on the weighting procedures. The model has not been compared or studied in both robust and deterministic modes. This is because, with the exception of the variable that indicates traffic mode uncertainty, all variables are deterministic, and the uncertainty character of demand in each level of the supply chain is ignored.Practical implicationsThe suggested model's conclusions are useful for any group of decision-makers concerned with optimizing production patterns at any level. The employment of a diverse fleet of delivery vehicles, as well as the use of stochastic optimization techniques to define the time windows, demonstrates how successful distribution networks are in lowering operational costs.Originality/valueAccording to a multi-objective model in a three-echelon supply chain, this research fills in the gaps in the link between routing and location choices in a realistic manner, taking into account the actual restrictions of a distribution network. The model may reduce the uncertainty in vehicle performance while choosing a refueling strategy or dealing with diverse traffic scenarios, bringing it closer to certainty. In addition, two modified MOPSO and NSGA-II algorithms are presented for solving the model, with the results compared to the exact GAMS approach for medium- and small-sized problems.

Bi-objective green supply chain network design under disruption risk through an extended NSGA-II algorithm

Green supply chain network design plays an important role in reducing environmental pollution and resource consumption. Furthermore, emergency events may cause disruptions and seriously reduce the performance of entire supply chain. This paper considers a three-echelon supply chain network consisting of multi-manufacturers, retailers with disruption risks and capacity constraints, and consumers with green preference. Different from traditional supply chain network design, this paper considers respectively two objectives from the manufacturers and consumers with green preference in selecting appropriate retailers under disruption risks. Moreover, we propose an extended elitist non-dominated sorting genetic algorithm (NSGA-II) to solve the bi-objective optimization model. The extended algorithm is considered to combine original NSGA-II algorithm with the migration operation of the biogeography-based optimization (BBO) algorithm, thus leading to enrich the diversity of the population and improve the ability of global searching. Compared with the traditional NSGA-II algorithm, the extended NSGA-II algorithm can obtain more Pareto solutions with higher efficiency. Furthermore, the result shows a trade-off relationship between the manufacturer cost and consumer cost. Therefore, it is necessary to separate the two objectives of manufacturers and consumers in green supply chain network design.

Encroachment in a three-echelon supply chain: manufacturer encroachment or distributor encroachment

PurposeThe purpose of this paper is to investigate manufacturer encroachment and distributor encroachment in a three-echelon supply chain consisting of an upside manufacturer, an intermediate distributor and a downside retailer.Design/methodology/approachIn this paper, the authors use the optimization theory to mathematize the proposed question and build a model. First, the authors consider sequential quantity decisions, where the encroacher decides on the direct selling quantity after determining the retailer's order quantity. Second, the authors relax this sequential decision process assumption by reconsidering a circumstance in which quantity decisions are decided simultaneously.FindingsIn contrast to previous studies, this study shows that in three-echelon supply chains, the upside firm is more likely to encroach compared with the downside firm. The “bright side” of encroachment exists for all players only when the encroachment cost is at a moderate level. However, in manufacturer encroachment under simultaneous quantity decisions, the “bright side” skips the distributor but benefits the retailer directly as the encroachment cost increases from zero to a certain level. The main reason lies in that the distributor loses its pricing power because the end-market has been disturbed by the simultaneous quantity decisions. A comparison of the results of sequential and simultaneous quantity decisions reveals the merit of simultaneous quantity decisions. The authors find that the intermediate role (the distributor in our model) in three-echelon supply chains may benefit more from simultaneous quantity decisions. That is, the distributor may achieve a better profit even in a market with intensified competition.Originality/valueThe findings of this paper contribute to the marketing science literature on encroachment. The majority of existing literature has focused on manufacturer encroachment in two-echelon supply chains. This paper innovatively investigates and compares manufacturer encroachment and distributor encroachment in a three-echelon supply chain.

Time-To-Recovery Prediction in a Disrupted Three-Echelon Supply Chain Using LSTM*

This paper introduces a Long-Short Term Memory (LSTM) neural network-based method for Time-To-Recovery (TTR) prediction within a cognitive digital supply chain twin framework to enhance supply chain resilience and improve decision-making under disruption. The introduced method is applied to a virtual three-echelon supply chain network modelled using discrete event simulation. The virtual system was used to train an LSTM neural network model to predict TTR under several disruption scenarios. Results show that predicted TTR values tend to be relatively lower than the actual values at early disruption stages, then improve throughout the progression of the disruption effect on the supply chain network.

Implications of implementing industrial symbiosis for supply chain dynamics

Industrial symbiosis has been recognized as a promising strategy to move towards a Circular Economy. However, its impact on the supply chain dynamics is still unexplored. For this reason, with this work we aim to contribute to this research gap analysing the dynamic performance of symbiotic supply chains. Through the agent-based modeling technique, we study two identical three-echelon supply chains, where there is a symbiotic exchange of waste between two manufacturers. We analyse a set of scenarios based on different demand/supply trade-ofs and lead time of the treatment process for the waste, and evaluate them in terms of bullwhip effect. Based on our results, we state that the volume of order decreases with the increase of the symbiotic flow, while the order variability increases with it. Our findings suggest that, under certain conditions, symbiotic supply chains can turn into self-contained systems.