Search results

This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint, financing cost, channel power structure and cost-reducing efficiency on green R&D and supply chain profitability.

A two-echelon supply chain is considered. The upstream firm engages in green R&D but has capital constraints that can be overcome by external financing. Green R&D is beneficial to reduce production costs and increase consumer demand. Based on whether or not the upstream firm is capital constrained and dominates the supply chain, four models are developed.

Capital constraints significantly lower green R&D and supply chain profitability. Transferring leadership from the upstream to the downstream firms leads to higher green R&D levels and downstream firm profitability, whereas the upstream firm's profitability is increased (decreased) if green R&D investment efficiency is high (low) enough. Greater financing costs reduce green R&D and downstream firm profitability; however, the upstream firm's profitability under the model in which it functions as the follower increases if the initial capital is sufficient. More importantly, empirical analysis based on practice data is used to verify the theoretical results reported above.

This study reveals how upstream firms in supply chains decide green R&D decisions in situations with capital constraints, providing managers and governments with an understanding of the impact of capital constraint, channel power structure, financing cost and cost-reducing efficiency on supply chain green R&D and profitability.

The major contributions are the exploration of supply chain green R&D by taking into consideration channel power structures and cost-reducing efficiency and the validation of theoretical results using practice data.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

This study aims to identify empirically proven strategies for reducing healthcare supply chain inventory costs.

The author conducted in-depth interviews in 80 hospitals covering different supply chains. The author treated the healthcare firm as the unit of analysis and examined Vrat's taxonomy of inventory models based on the static and dynamic complexity theories of inventory models to identify an appropriate approach. The author addressed 33 highly priced and moderately priced stock-keeping units from 1,432 items and test several inventory policies. Next, the author applied combinations of inventory models, testing probabilistic hybrid inventory models.

The study finds that medical supplies, equipment, and medications are indispensable for a quality healthcare system. Hence, healthcare supply chain management (SCM) professionals must adopt basic inventory cost-reduction strategies, implementing inventory software functionalities effectively and efficiently. This study shows that probabilistic hybrid inventory techniques in healthcare SCM effectively determine an optimal stocking level, significantly reducing costs.

This study analyzes data from primary care and (to some extent) secondary care institutions. Although tertiary and quaternary care systems do not represent a large portion of the healthcare system, future research should also address these highly specialized organizations' needs.

This study proposes practical strategies to help continuously improve supply chain operations in healthcare organizations worldwide.

This study suggests probabilistic hybrid inventory models as empirically proven solutions for evaluating stock-keeping units in the healthcare sector. In doing so, the study provides a new healthcare supply chain approach, proposing a modified taxonomy of inventory models.

Currently, digital technology has been proposed as a new archetype for developing an effective traceability system in the perishable food supply chain (FSC). Implementation of such a system needs significant investment and the burden lies with the members of the supply chain. The purpose of this paper is to examine the impact on the profit of the supply chain members due to the implementation of an effective traceability system with such a large investment. The study also tries to explore the impact of the implementation of such a system by coordination among the members through a cost-sharing mechanism.

A two-level supply chain that comprises a supplier and retailer is analyzed using a game-theoretic approach. The mathematical models are developed considering the scenario for an individual, centralized and both members invest using a cost-sharing mechanism. For each of the models, the impact of product selling price, information sensing price and quality improvement level on profit is analyzed through numerical analysis.

The study reveals that consumer involvement can be a strong motivation for the supply chain members to initiate investment in the traceability system. Further, from an investment perspective cost-sharing model is beneficial compared to the individual investment-bearing model. This mechanism can coordinate as well as benefit the FSC members. However, the model is less beneficial to the centralized model from profit and quality improvement levels.

Food wastage can be less from supplier and retailer perspectives. Moreover, consumers can purchase food items only after verifying their shipping conditions. Consequently the food safety scandals can be reduced remarkably.

Digital technology adoption in the perishable FSC is still considered emerging. The present study helps organizations to implement a traceability system in the perishable FSC through consumer involvement and a cost-sharing mechanism.

The aim of the study has been performed to investigate the relationship between sustainable supply chain management (SSCM) practices and the cost performance of manufacturing firms in Bangladesh. Moreover, this paper highlights the key environment-friendly approaches and their association with financial performance in Bangladesh.

The paper empirically assesses sustainable supply chain performance using four major supply chain practices, including sustainable procurement, sustainable production, sustainable distribution and investment recovery, and compares it with the cost performance. Twenty-four variables were identified through different literature and distributed as a structured questionnaire among the managers appointed in different manufacturing firms in Bangladesh. An empirical study was conducted using the Partial Least Square-Structural Equation Modeling (PLS-SEM) technique to examine the hypothesized relationships.

The results find a positive relationship in two variables of sustainable supply chain practices, including sustainable procurement and investment recovery, while sustainable distribution negatively impacted cost performance. In addition, sustainable production found no effect on cost performance.

The paper emphasizes the financial perspective of a sustainable supply chain without explicit consideration of sustainability's environmental and social dimensions.

This study has implications for the literature on the SSCM approaches of manufacturing firms in the least developed economies. In addition, this study could work as a guideline for some manufacturing industries that prefer a policy or standard to alter their traditional supply chain management system to a sustainable supply chain.

The paper provides a comprehensive framework for evaluating the coordinated effect of SSCM practices on cost performance where variables of four specific activities of SSCM and cost performance are adopted from different studies. Further studies could be initiated, including some other eco-friendly supply chain variables, and the effect could be evaluated from an environmental perspective.

Fresh product loss rates in supply chain operations are particularly high due to the nature of perishable products. The purpose of this paper is to maximize profit through the contract between retailer and supplier. The optimized prices for the retailer and the supplier, taking the fresh-keeping effort into consideration, are derived.

To address this issue, the authors consider a two-echelon supply chain consisting of a retailer and a supplier (i.e. wholesaler) for two scenarios: centralized and decentralized decision making. The authors start from investigating the optimal decision in the centralized supply chain and then comparing the results with those of the decentralized decision. Meanwhile, a fresh-keeping cost-sharing contract and a fresh-keeping cost- and revenue-sharing contract are designed. Numerical examples are provided, and managerial insights are discussed at the end.

The results show that the centralized decision is more profitable than the decentralized decision; a fresh product supply chain (FPSC) can only be coordinated through a fresh-keeping cost- and revenue-sharing contract; the optimal retail price, wholesale price and fresh-keeping effort can all be achieved; and the profit of a FPSC is positively related to consumers’ sensitivity to freshness and negatively correlated with their sensitivity to price.

This research is based on the assumption that demand is relatively stable. It has not addressed when demand is stochastic.

The findings would be useful for managers in fresh food sector in terms of how to deal with suppliers in order to maximize total profit while also provide freshest food to the customers.

Few studies have considered fresh-keeping effort as a decision variable in the modelling of supply chain. In this paper, a mathematical model for the fresh-keeping effort and for price decisions in a supply chain is developed. In particular, fresh-keeping cost-sharing contract and revenue-sharing contract are examined simultaneously in the study of the supply chain coordination problem.

The purpose of this paper is to analytically examine the viability of using blockchain technology (BT) in a public distribution system (PDS) supply chain to overcome issues of shrinkage, misplacement and ghost demand.

The authors use a standard news vendor model with two objectives, the first of which includes a reduction of the total cost of stock, while the second includes minimization of the negative impact of human suffering due to the nonavailability of subsidized food supplies to the needy people.

The authors applied the model to a real-life case to draw meaningful insights. The authors also analyzed the cost/benefit tradeoff of adopting BT in a PDS supply chain. The results show that the adoption of BT in a charitable supply chain can reduce pilferage and ghost demand significantly.

The paper is positioned for utilizing inventory visibility via consistent and tamper-resistant data stream flow capability of BT to enhance the overall efficiency of PDS. Notably, Indian PDS faces three major challenges in terms of its supply chain efficiency.

The purpose of this paper is to model the distribution stage of the public distribution system (PDS) and optimize the inventory policy during this stage of the PDS to address some of the inefficiencies present in the system. This study models this supply chain as a multistage supply chain consisting of storage depots, issue centers, fair price shops and card holders.

A two-stage modeling approach is used to model the distribution stage in the PDS. In the first stage, the authors developed a simulation model for periodic review-based stock policy with appropriate assumptions. This helped minimize the total supply chain cost (TSCC). The TSCC consists of three cost elements, namely, ordering cost, holding cost and shortage cost. These three cost elements, in turn, depend on inventory policy parameters, such as review periods and base stock levels, at various echelons. In the second stage, a Genetic Algorithm based optimization approach was used.

A set of optimal policy parameters was identified. It is observed that base stock levels at issue centers are higher as compared to those in the FPS and the TSCC is less in scenario, when backorder cost is equal to the holding cost.

Present study will be useful to policy makers in improving PDS performance. This optimization of inventory policies helps actors in the PDS supply chain to choose appropriate policy parameters in the present inventory policy so as to reduce the overall distribution cost.

Unlike the previous researchers who examined the PDS from the social security perspective and tried to address specific problems to improve functioning of the PDS, this study looked at the problem as a supply chain-related problem and optimized the inventory parameters in one of the subsets of the PDS supply chain.