Constrained Supply Chain Research Articles

Horizontal cooperation strategies for competing manufacturers in a capital constrained supply chain

Many studies concentrate on the vertical collaboration between upstream and downstream enterprises in the supply chain. However, we have observed that some competing manufacturers also engage in horizontal collaboration in practice, where they hold minority ownership shares in their rival, especially for those with limited initial capital. Although such collaboration has become increasingly prevalent, achieving the expected effects remains challenging due to frequent conflicts in collaboration mechanisms. This study considers a two-echelon supply chain with one supplier and two manufacturers with different financial statuses, where manufacturer 2 not only engages in Cournot competition with manufacturer 1, but also offers a horizontal collaboration contract as a collaborator. By incorporating the initial capital of manufacturer 1, we develop a benchmark sufficient capital model, and two other models such as capital constrained model and the horizontal collaboration model. The impact of horizontal cooperation on the optimal decisions of manufacturers is analyzed to investigate whether a collaboration strategy exists that can mitigate these conflicts while improving the profits of all participants. We prove that the horizontal collaboration can benefit both manufacturers when manufacturer 1 is highly capital constrained and holds a large equity share in itself. However, collaborating with a competing manufacturer 2 does not always benefit the capital-constrained manufacturer 1 compared to a situation where both manufacturers have sufficient capital, but it can increase the profits of manufacturer 2 and the entire supply chain in certain conditions. There exists an optimal collaboration mechanism that can achieve a win–win situation, where manufacturer 2 transfers partial payments to the capital-constrained manufacturer 1. The transfer payment is influenced by the cost differences between the manufacturers and the shareholding ratio. These findings can provide valuable management insights to enable competitors to adopt the optimal collaboration method in the face of capital constraints.

Blockchain-Enabled Deep-Tier Supply Chain Finance

Problem definition: For many supply chains, deep-tier suppliers, due to their small size and lack of access to capital, are most vulnerable to disruptions. We study the use of advance payment (AP) as a financing instrument in a multitier supply chain to mitigate the supply disruption risk in a traditional system (with limited visibility) and a blockchain-enabled system (with perfect visibility). The main goal of this paper is to shed light on how blockchain adoption impacts agents’ operational and financial decisions as well as profit levels in a multitier supply chain. Academic/practical relevance: Traditionally, because of the limited visibility in the deep tiers, powerful downstream manufacturers’ financing schemes offered to their immediate upstream suppliers are not effective in instilling capital into the deep tiers. Advancements in blockchain technology improve the supply chain visibility and enable the manufacturer to better devise deep-tier financing to improve supply chain resilience. Methodology: We develop a three-tier supply chain model and take a game-theoretic approach to compare how blockchain-enabled deep-tier financing schemes affect a financially constrained supply chain’s optimal risk-mitigation and financial strategies. Results: We find that although improved visibility via blockchain adoption can help the manufacturer make informed supply chain financing decisions, whether it can benefit all supply chain members depends on the financing schemes in use. Blockchain-enabled delegate financing increases risk-mitigation investments and benefits all three tiers of the supply chain only when the tier 2 supplier is severely capital-constrained with the working capital below a threshold. Because delegate financing endows the intermediary tier 1 supplier with leverage over the manufacturer, the inefficiency inhibits an all-win outcome when the tier 2 supplier is not severely capital-constrained. Blockchain-enabled cross-tier direct financing exhibits a compelling performance as it always leads to win-win-win outcomes (and is thus ubiquitously implementable) regardless of the suppliers’ working capital profile. Managerial implications: Our insights help firms assess opportunities and challenges associated with enhancing supply chain visibility via blockchain adoption.

Sustainable supply chain finance through digital platforms: a pathway to green entrepreneurship

This paper studies the green new product development (GNPD) problem of a risk-averse capital constrained supply chain (SC). The SC is managed by an SME entrepreneur, seeking financial support from a multi-sided FinTech platform (MSP) to develop a portfolio of green and non-green products. The MSP offers the SC a combination of equity financing (EF) and debt financing (DF) facilities and must decide on the interest rate of its DF facility. Using a benchmark model, we first characterize the SC’s production and the MSP’s financing decisions under a deregulated scenario. Focusing on an alternative case with government intervention (i.e., hybrid environmental-green entrepreneurship policy), we next develop a three-level game theoretical model and sequentially characterize the decision-making behavior of government, MSP, and SC. The model outcomes are analyzed by considering the policy approach (i.e., economic influence vs. social welfare) and the platform’s risk attitude. The results reveal that, when coupled with an appropriate government intervention policy, a regulated scenario leads to a better outcome, particularly when the MSP is risk-neutral and strikes a right balance between the EF and DF. The win–win situation may not be realized when the MSP is risk-averse and the host government is merely focused on its economic influence. To successfully promote sustainable supply chain finance (SSCF) through digital platforms, policy makers are urged to leverage their legislative power and prioritize green entrepreneurship and social welfare over their financial maximization agenda.

Pareto-Optimal Coordination and Financing Selection for a Capital Constrained Supply Chain Under a Buyback Contract

Pareto-Optimal Coordination and Financing Selection for a Capital Constrained Supply Chain Under a Buyback Contract

Financing equilibrium in a capital constrained supply Chain: The impact of credit rating

In this study, we investigate a supply chain comprising one well-funded supplier and one small-sized retailer with capital constraints. The supplier acts as a leader to distribute one newsvendor-type product via the retailer in the uncertain market demand. In the presence of capital shortages, the retailer has two different financing alternatives: bank financing and trade credit. Moreover, the small-sized retailer has an imperfect credit rating, which reflects the exogenous credit risk beyond the current supply chain transaction. By capturing both the demand risk and credit risk, we model each financing strategy and derive the optimal solutions. When both financing strategies are feasible, we prove that the retailer always benefits from bank financing, while the supplier’s preferences are determined by two critical factors (i.e., the retailer’s credit rating and the production cost). Considering that the supplier’s preferences are not always aligned with the retailer’s, we characterize a wholesale price Pareto zone, in which trade credit is the unique equilibrium. We further generalize our model to consider that the retailer with a positive initial budget, finding that the feasible regions of two financing formats shrink as the initial budget builds up. Interestingly, when the initial capital of the retailer is moderate (still capital shortages), we observe that trade credit is more likely to be the financing equilibrium if the retailer’s credit rating is low. These findings enrich our understanding of the impact of credit rating on financially constrained supply chain operational and financial decisions.

A Dual-Channel Sale System in Financially Constrained Supply Chain

In order to realize the sustainable development of the communication industry, many banks have developed some new projects to provide loan to the mobile phone brand companies (MPBCs). This paper studies a perfect information game among three parties: telecom operator (TO), MPBC, and bank. In the first stage, the bank decides an interest rate and shows it to the TO and the competitive MPBC. In the second stage, the TO and MPBC are engaged in Cournot games: a simultaneous subgame, a TO-as-leader sequential subgame, and an MPBC-as-leader sequential subgame. The TO’s and the MPBC’s decisions and the production/sale quantities are investigated. The impacts of the interest rate and the substitute factor on the TO’s and the MPBC’s optimal decisions are analyzed. When the substitute factor is high, at a low interest rate, the total sales in the simultaneous subgame is higher than those in the other two subgames; at a high interest rate, the total sales in the MPBC-as-leader subgame is higher than those in the other two subgames. However, when the substitute factor is low, at a low enough interest rate, the total sales in the simultaneous subgame is higher than those in the other two subgames; at a high enough interest rate, the total sales in the MPBC-as-leader subgame is higher than those in the other two subgames; at a moderate interest rate, the total sales in the TO-as-leader subgame is higher than those in the other two subgames. Besides, the optimal interest rate of the bank is investigated and the impact of the substitute factor on the optimal interest rate is analyzed. The bank sets a higher interest rate in the MPBC-as-leader subgame than those in the other two subgames. Besides, when the substitute factor is low, the bank sets a lower interest rate in the TO-as-leader subgame than that in the simultaneous subgame; however, when the substitute factor is high, the bank sets a higher interest rate in the TO-as-leader subgame than that in the simultaneous subgame.

Blockchain-Enabled Deep-Tier Supply Chain Finance

Problem Definition: For many supply chains, deep-tier suppliers, due to their small sizes and lack of access to capital, are most vulnerable to disruptions. In this paper, we study the use of advance payment (AP) as a financing instrument in a multitier supply chain to mitigate the supply disruption risk and compare the traditional system (deep-tier financing with limited visibility) with the blockchain-enabled system (financing with perfect visibility). The main goal of this paper is to shed light on how blockchain adoption impacts agents' operational and financial decisions as well profit levels in a multitier supply chain. Academic/Practical Relevance: Traditionally, because of the limited visibility in the deep-tiers, powerful downstream manufacturers' financing schemes offered to their immediate upstream suppliers are not effective in instilling capital into the deep-tiers. Advancements in blockchain technology improve the supply chain visibility and enable the manufacturer to better devise deep-tier financing to improve supply chain resilience. Methodology: We develop a three-tier supply chain model and take a game-theoretic approach to understand a financially constrained supply chain's optimal operational and financial strategies. Results: We find that the improved supply chain visibility (by blockchain adoption) always benefits the manufacturer by enabling her to induce the desired operational risk-mitigation investment from the tier-1 and tier-2 suppliers. However, depending on the directional change in the operational risk-mitigation investment, which depends on the suppliers' initial wealth levels, the tier-1 and tier-2 suppliers can be worse-off. The win-win-win outcome takes place only when all operational risk-mitigation measures increase, that is, when the tier-1 supplier is severely capital constrained but the tier-2 supplier is moderately capital constrained. Comparing the two types of blockchain-enabled deep-tier financing schemes, adjacent-tier delegated financing versus cross-tier direct financing, the manufacturer strictly prefers the latter. In contrast, the tier-1 supplier strictly prefers the former because the former endows the tier-1 with financial leverage over the manufacturer. The tier-2 supplier prefers the latter only when the emergency source is expensive. Managerial Implications: Our insights help firms assess opportunities and challenges associated with enhancing supply chain visibility via blockchain adoption.

Constrained Supply Chain Scheduling Model Using Sequential Quadratic Programming Algorithm

Challenges such as advances in technology, demands of the global market, and limited warehouse spaces resort manufacturing industries to subcontracting. Subcontracting has been a considerable alternative in the manufacturing industries and is utilized as a strategic tool to diminish operation costs primarily to address the problem of scarcity when the firm faces a large demand on the commodity it supplies. The present study employed a mathematical model among firms engaging in subcontracting in search of an optimal schedule in the manufacture of the product and distribution of production time involved with an objective of obtaining a maximum profit. The constraints in the mathematical formulation included the total demand, processing capacity, available supply, processing rate, and time. The plausibility and the possible utility of the mathematical model has been explored employing sequential quadratic programming algorithm in the search of the optimal solutions.

Coordinating Contracts for a Financially Constrained Supply Chain

We consider a financially constrained supply chain in which a supplier (leader) sells products to a retailer (follower) who has no access to bank financing due to her low credit rating. However, the supplier can borrow from a bank and offer trade credit to the retailer to alleviate her financial constraint. Failure to pay off a bank loan or trade credit incurs a variable default cost. We analyze the centralized version of the supply chain to obtain new coordination requirements. We then examine whether revenue-sharing, buyback, and all-unit quantity discount contracts can coordinate our supply chain. We show that the all-unit quantity discount contract fails to coordinate. However, the revenue-sharing and buyback contracts can coordinate the supply chain, but only when the supply chain has a sufficient total working capital. Moreover, they cannot allocate profit flexibly unless the supplier has a large enough working capital. Finally, we design a generalized revenue-sharing contract that coordinates the supply chain with flexible profit allocation, and also show by numerical examples its superiority over the revenue-sharing and buyback contracts.

Supply chain finance, financial constraints and corporate performance: An explorative network analysis and future research agenda

In this paper, we examine the functional form of the relationship between working capital assets and corporate performance beyond the traditional single-company perspective. In particular, we explore how a focal company's adequate level of working capital is influenced by the presence of limited financial resources along the supply chain. Moreover, we investigate the performance impact of supply chain finance (SCF)-oriented working capital management (WCM) approaches. Based on the SCF-oriented school of thought, we subject propositions regarding the relationship between working capital and corporate performance from prior WCM research to explorative empirical testing. In doing so, we raise awareness of factors that have yet to be tested. We derive methodological implications for conducting interorganizational studies in the field of SCF and outline a future research agenda. The explorative results indicate (i) the existence of a profit-maximizing level of working capital, (ii) superior performance of companies adopting an SCF-oriented WCM approach, (iii) higher profit-maximizing levels of working capital for focal companies facing financially constrained supply chain partners, (iv) a positive performance impact of efficient inventory management, and (v) differentiated payment strategies toward up- and downstream supply chain partners.

Supply chain coordination under trade credit and retailer effort

In this paper, we study the role of trade credit in coordinating a Capital Constrained Supply Chain in the presence of retailer Effort (CCSCE), essentially because of the impact of its related default risks on the relationship between the chain’s members. We consider a CCSCE consisting of a supplier and a retailer where the retailer may exert costly promotional efforts to increase the market demand but has limited capital and no access to bank financing due to low credit rating. Conversely, the supplier has adequate funds to offer trade credit to the retailer without borrowing from external channels. We then examine whether the existing coordination contracts can still coordinate the CCSCE under trade credit. Our result shows that these contracts can achieve coordination of the supply chain when the interest rate of trade credit is competitively priced. Nevertheless, this position cannot always be reached. That’s why we propose a generalised contract based on risk compensation to coordinate the CCSCE. Using our proposed coordinating contract, the supplier perfectly coordinates the retailer’s decisions for the largest joint profit, and arbitrarily allocates the maximised joint profit among supply chain members. Finally, the numerical study allows to verify this finding. From managerial insights, our results provide the supply chain managers with novel insights on how to combine trade credit with the existing coordination contracts in order to improve the profitability of the entire supply chain as well as the individual member.

An integrated multi-product, multi-buyer supply chain under penalty, green, and quality control polices and a vendor managed inventory with consignment stock agreement: The outer approximation with equality relaxation and augmented penalty algorithm

• An integrated multiproduct, multi-buyer supply chain under penalty, green, and quality control policies and a vendor-managed inventory with consignment stock agreement. • Optimal batch-sizing policy in an integrated multiproduct constrained supply chain. • Use of the outer approximation with equality relaxation and augmented penalty algorithm for optimal batch-sizing. • New integer variables and real stochastic constraints. • Numerical results and managerial implications verify the performance of the model and the algorithm. It is of great importance to develop an optimal supply chain (SC) batch-sizing policy that collectively embodies green policies and a vendor-managed inventory (VMI) with consignment stock (CS) agreement. This article provides a mathematical model that includes the buyers' total cost (TC) and the vendor's TC in an SC under penalty, green, and quality control (QC) policies and a VMI-CS agreement. The proposed model is a multiproduct, multi-buyer model and has real stochastic constraints. Moreover, the model differentiates between the holding costs for financial and nonfinancial components, in which the first includes the investment in the space and the second includes the cost due to physical storage, movement, and insurance of the products. Financial components are carried by the vendor on implementation of the VMI-CS agreement, while holding costs for stocking items in the buyers' warehouses are carried by the buyers as nonfinancial components. The objective is to determine the optimal batch-sizing policy with the minimum TC in the integrated SC that finds both the number of the vendor's batches for each of the transported products and the volume of the batches transported to the buyers so as to minimize the TC of the integrated SC while the stochastic constraints are satisfied. Because of the complexity of the optimization model and mathematical formulations, an outer approximation with equality relaxation and augmented penalty algorithm is presented to determine the optimal batch-sizing policy. With application of this technique, the large-scale and hard-to-solve mixed-integer nonlinear programming problem is minimized. The optimality criteria results obtained in numerical examples and sensitivity analysis demonstrate the excellent performance of the method used. Finally, managerial insights, analytical results, and future research directions are provided.

Supply Chain Coordination Under Financial Constraints and Yield Uncertainty

Capital deficit due to capital constraints is a very common issue in supply chains and suppliers (such as farmers) often face yield uncertainty. A coordination problem for a supply chain with capital constraints and yield uncertainty is considered in this paper. In order to improve the supply chain, a buyback and risk sharing (BBRS) mechanism is proposed, in which the distributor shares the yield uncertainty risk with the supplier by purchasing the overproduced products at the end of the production season, and the supplier buys back the unsold products from the distributor at the end of the sales season. The results indicate that under the BBRS, the profits and the strategies of the supply chain are the same with those under the centralized case. In addition, the proposed BBRS mechanism has a built-in mechanism to allocate the spillover profit between the supplier and the distributor, and the actual allocation may depend on their negotiation skills. The managerial insight is that, for the capital constrained supply chain with yield uncertainty, it can be coordinated if the yield uncertainty risk and the market demand uncertainty risk are shared between the supplier and the distributor.

Prioritizing high-risk sub-groups in a multi-manufacturer vaccine distribution program

PurposeAnnual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza vaccination program (VP). The goal is to minimize the total cost of the vaccination supply chain while guaranteeing a sufficiently high level of population protection. From a practical point of view, the analysis returns the number of shipments and the quantity of vaccines in each periodic shipment that should be delivered from the manufacturers to the distribution center (DC), from the DC to the clinics, and from the clinics to each sub-group of customers during the vaccination season.Design/methodology/approachA mixed-integer programming optimization model is developed to describe the problem for a supply chain consisting of vaccine manufacturers, the healthcare organization (HCO) (comprising the DC and clinics), and the population being vaccinated (customers). The model suggests a VP that implemented by a nation-wide HCO.FindingsThe benefits of the proposed approach are shown to be particularly salient in cases of limited resources, as the model distributes demand backlogs in an efficient manner, prioritizing high-risk sub-groups of the population over lower-risk sub-groups. In particular, the authors show a reduction in direct medical burden of consumers, such as the need for doctors, hospitalization resources, and reduction of indirect, non-medical burden, such as loss of workdays.Practical implicationsDrawing from the extended enterprise paradigm, and, in particular, taking consumer benefits into account, the authors suggest an operational-strategic model that creates impressive added value in a highly constrained supply chain. The model constitutes a powerful decision tool for the deployment of large-scale seasonal products, and its implementation can yield multiple benefits for various consumer segments.Originality/valueThe model proposed herein constitutes a decision support tool comprising operational-tactical and tactical-strategic perspectives, which logistics managers can utilize to create an enterprise-oriented plan that takes into account medical and non-medical costs.

Coordinating contracts for a financially constrained supply chain

We consider a financially constrained supply chain in which a supplier (leader) sells products to a retailer (follower) who has no access to bank financing due to her low credit rating. However, the supplier can borrow from a bank and offer trade credit to the retailer to alleviate her financial constraint. Failure to pay off a bank loan or trade credit incurs a variable default cost. We analyze the centralized version of the supply chain to obtain new coordination requirements. We then examine whether revenue-sharing, buyback, and all-unit quantity discount contracts can coordinate our supply chain. We show that the all-unit quantity discount contract fails to coordinate. However, the revenue-sharing and buyback contracts can coordinate the supply chain, but only when the supply chain has a sufficient total working capital. Moreover, they cannot allocate profit flexibly unless the supplier has a large enough working capital. Finally, we design a generalized revenue-sharing contract that coordinates the supply chain with flexible profit allocation, and also show by numerical examples its superiority over the revenue-sharing and buyback contracts.

Low carbon chance constrained supply chain network design problem: a Benders decomposition based approach

This paper proposes a chance constrained based green supply chain network design model addressing carbon emissions and carbon trading issues. The model determines the optimal flow of materials as well as emissions across the supply chain network. The basic model has been further extended into two models addressing different carbon emission issues. This study has contributed to the body of existing green supply chain literature through addressing uncertainties of suppliers’ capacities, plants’ capacities, warehouses’ capacities and demand for sustainable supply chain network design problem. This study applies Benders decomposition algorithm to handle chance constrained sustainable supply chain network design problem. The proposed models are illustrated with suitable examples and results are carefully analyzed and discussed. The results demonstrated that the flow of materials across the supply chain network varies with the change of the probability as well as carbon credit price. The number of openings of the plants is also influenced with the change of carbon credit price. Similarly, variable cost and variable emissions have been found increased and decreased, respectively with the increase of carbon credit price for the base model. The model is also equipped with dissimilar carbon prices for handling cap and trade scenario. This paper may help managers to deal uncertainties as well as managing emissions of a supply chain network.

Coping Strategies for Overcoming Constrained Supply Chain Technology: An Exploratory Study

AbstractConditions experienced in developing countries are characterized by high levels of uncertainty and differ considerably from those encountered in developed countries. Specifically, operational environments in developing countries constrain the supply chain technology (SCT) used by firms to manage supply chain operations. Hence, it is reasonable to conjecture that firm's operating in these types of environments might rely on and use SCT and the information they provide to manage their supply chain operations differently from firms in less constraining environments. To explore this phenomenon we conducted a grounded theory study collecting interview data from 46 logistics and supply chain managers at 16 firms across India, one of the largest and most dynamic of the developing countries. Our analysis of the data establishes that SCT constraints arise from external, internal, and relationship conditions. Emerging from the data we observed managerial emphasis on a phenomenon whereby management utilizes coping strategies to relax constraints that adversely affect their use of SCT. While our findings also revealed human intervention as a negative externality arising from the use of coping strategies, we found that management were aware of this externality and were actively addressing it as part of their efforts to relax the constraints on SCT.

LSP-Constrained Supply Chains: A Discrete Event Simulation Model

In this paper, we present a logistics service provider (LSP) constrained supply chain problem, particularly; we propose a novel supply chain model that consists of three layers of non-cooperative manufacturers, distribution centers and retailers. Products flow from the manufacturers across different warehouses to retailers via LSP. Inventories at warehouses follow smooth and continuous replenishment policy, i.e. , perpetual review. The supply chain is represented as an optimization model that maximizes the revenue of manufacturers meets the retailers’ demand and at the same time identifies the necessary warehouses, particularly for supply chains that are affected by leadtime (LT) variation such as fast response industry and short life products. The model solution is adaptive; it determines the best manufacturing rates and identifies the logistic bottlenecks in dynamic supply chain networks. Numerical solutions along with simulation experiments of different supply chain topologies are presented. The simulation results demonstrate the model capability to maximize the revenues by tuning the manufacturing rates and monitoring the workinprocess, products in transit as well as products in inventories

A Recommender System to Nudge Customers in a Capacity Constrained Supply Chain

We seek to develop a recommender system that takes into account supply chain constraints regarding the availability of a product while nudging the customers to purchase it. The motivation to study this problem was because a firm faced availability constraints for one of its products but the available quantities still exceeded the current demand. To identify customers to nudge, we develop a Support Vector Machine (SVM) approach to rank order the customers based on their propensity to purchase the product. The underlying notion in our approach is that Type I errors in our classifier are not necessarily problematic but are potential nudging targets. Also, as a consequence, traditional ways of evaluating classifiers (with Type I and Type II errors) are not appropriate. Therefore, we conduct a field experiment to evaluate how well the identified customers are nudged through information and/or couponing. We find that, in terms of the successful nudges, our SVM-based approach performed better than other approaches. The experiment also generated insights about when couponing as opposed to information is more effective when nudging.

Bullwhip Effect Study in a Constrained Supply Chain

Well organized supply chains are one of the best ways to compete in today's marketplaces. For make-to-stock production systems the production plans and activities are based on demand forecasting, which is one of the key causes of the bullwhip effect (BE). BE is the inherent increase in demand fluctuation up the supply chain and produces excess inventory and poor customer service. In the paper we simulated a simple three-stage supply chain using seasonal (SM) and deseasonalized (DSM) time series of the market demand data in order to identify, illustrate and discuss the impacts of different level constraints on the BE. The results are presented for different overall equipment effectiveness (OEE) and constrained inventory policies. At higher OEE level manufacturers have less variability in production processes; the BE is stronger in DSM than in SM.