Supply Chain Structure Research Articles

Challenge or opportunity? Impact of a two-invoice mechanism on pharmaceutical supply chains with channel promotion

Two-invoice mechanism (TIM) was introduced by the Chinese government with the purpose of reducing pharmaceutical prices. This paper studies the impact of the TIM on a pharmaceutical supply chain consisting of a manufacturer, buyer, and agent (in the absence of a TIM) or a third-party company (in the presence of a TIM). Considering the promotion effort, we establish game theoretical models for different supply chain structures. The pharmaceutical agent conducts channel promotion in the absence of the TIM. However, under the TIM, the agent is ruled out, and channel promotion is thus performed by the manufacturer or third-party company. Interestingly, we find that although the original intention of the TIM is to reduce pharmaceutical prices, it may fail to do so when channel promotion is performed by the manufacturer. Nevertheless, the TIM increases pharmaceutical demand and consumer surplus, thus benefiting the public. Moreover, whether the manufacturer can benefit from the TIM depends on the promotion mode and its investment cost of setting up a promotion channel. Particularly, when the manufacturer performs self-promotion and the investment cost is high, the profit is reduced. In contrast, the buyer always benefits from the TIM. Finally, we propose coordination schemes based on revenue-sharing contracts (RSCs) and performance-based contracts (PBCs) to improve the performance of the supply chain with the TIM.

Supply Chain Inventory Management from the Perspective of “Cloud Supply Chain”—A Data Driven Approach

This study systematically investigates the pivotal role of inventory management within the framework of “cloud supply chain” operations, emphasizing the efficacy of leveraging machine learning methodologies for inventory allocation with the dual objectives of cost reduction and heightened customer satisfaction. Employing a rigorous data-driven approach, the research endeavors to address inventory allocation challenges inherent in the complex dynamics of a “cloud supply chain” through the implementation of a two-stage model. Initially, machine learning is harnessed for demand forecasting, subsequently refined through the empirical distribution of forecast errors, culminating in the optimization of inventory allocation across various service levels.The empirical evaluation draws upon data derived from a reputable home appliance logistics company in China, revealing that, under conditions of ample data, the application of data-driven methods for inventory allocation surpasses the performance of traditional methods across diverse supply chain structures. Specifically, there is an improvement in accuracy by approximately 13% in an independent structure and about 16% in a dependent structure. This study transcends the constraints associated with examining a singular node, adopting an innovative research perspective that intricately explores the interplay among multiple nodes while elucidating the nuanced considerations germane to supply chain structure. Furthermore, it underscores the methodological significance of relying on extensive, large-scale data. The investigation brings to light the substantial impact of supply chain structure on safety stock allocation. In the context of a market characterized by highly uncertain demand, the strategic adaptation of the supply chain structure emerges as a proactive measure to avert potential disruptions in the supply chain.

Supply chain strategies in response to a black-swan event: a comparison of USA, French and Polish firms

PurposeThis research aims to analyse the perceptions of practitioners in three regions regarding the challenges faced by their firms during the pandemic, considered a black-swan event. It examines the strategies implemented to mitigate and recover from risks, evaluates the effectiveness of these strategies and assesses the difficulties encountered in their implementation.Design/methodology/approachIn the summer of 2022, an online survey was conducted among supply chain (SC) practitioners in France, Poland and the St. Louis, Missouri region of the USA. The survey aimed to understand the impact of COVID-19 on their firms and the SC strategies employed to sustain operations. These regions were selected due to their varying levels of SC development, including infrastructure, economic resources and expertise. Moreover, they exhibited different responses in safeguarding the well-being of their citizens during the pandemic.FindingsThe study reveals consistent perceptions among practitioners from the three regions regarding the impact of COVID-19 on SCs. Their actions to enhance SC resilience primarily relied on strengthening collaborative efforts within their firms and SCs, thus validating the tenets of the relational view.Originality/valueCOVID-19 is (hopefully) our black-swan pandemic occurrence during our lifetime. Nevertheless, the lessons learned from it can inform future SC risk management practices, particularly in dealing with rare crises. During times of crisis, leveraging existing SC structures may prove more effective and efficient than developing new ones. These findings underscore the significance of relationships in ensuring SC resilience.

Supply Chain Structure of Gedong Mango in Jatigede District, Sumedang Regency, West Java

District Jatigede is the center of production of mango gedong gincu, the bigst in the Regency of Sumedang. Mango gedong gincu is unique because it has a little red color between the color yellow dominant. Although District Jatigede is one center of production of mango gedong in the Regency Sumedang, it is the second bigst production of mango gedong at the province Level after Regency Indramayu based on 2021 data. Even so, it has yet to be widely known by consumers or people. Hence, the chain supply of mango gedong is interesting to study. This case study uses an analysis structure chain supply to see the flow of products, information, and money linked to commodities mango gedong. Actor tracing in this study approaches the rapid market appraisal method. This study shows four supply chain structures; generally, the chain supplies mango gedong in the Regency Sumedang were sold to local collectors to sell to the big collectors in the Regency of Majalengka or Cirebon. That is due to the center city Majalengka and Cirebon's proximity to District Jatigede compared to Sumedang city center. Apart from that, there are packing houses in Majalengka and Cirebon that are also representative.

Owards Energy Efficiency in Integrated Inventory Supply Chain Models: A Review

Amidst the sustainability concerns of the industrial sector to fulfil the increase in customer demands, this study emphasizes on the characteristics of integrated inventory supply chains that is closely related to energy efficiency. Environmental and economic perspectives must be given equal consideration to ensure a competitive supply chain (SC). In response to global calls for sustainable energy and lower carbon emissions, the Malaysian government currently provides tax exemptions and allowances for the provision of green technology services and the acquisition of green technology assets. Furthermore, as sources of electricity are highly variable, efficient SC activities can feasibly minimise the cost of energy. Therefore, multiple studies have integrated the green concepts in SCs to develop energy efficient integrated inventory SC models. This present review examined 42 articles that assessed the environmental impact of integrated inventory SC models with a focus on energy efficiency and energy-related issues. A systematic literature review (SLR) was conducted to identify gaps in the existing literature and offer directions for future studies. The articles were categorised according to the SC dimensions of an integrated inventory model; such as categories of SC participants, structures, processes, and decision-making variables. Of the reviewed articles, only 35% examined energy efficiency or energy-related issues in integrated inventory models. Therefore, future studies should examine the energy efficiency or energy-related issues that integrated inventory SCs face.

Supplier development strategy considering technical uncertainty

Previous literature on supplier development was mostly based on the assumption that investments are bound to succeed, with little consideration given to the impact of technological uncertainty on supplier development strategies. We examine a supply chain structure consisting of two suppliers (Suppliers 1 and 2) and one manufacturer, considering the technical uncertainty when the manufacturer implements supplier development to reduce production costs. We use the success rate of technological investment to measure technological uncertainty and considers the varying levels of different strategies. Research shows that (1) more intense competition may benefit both the manufacturer and suppliers, but a higher success rate of technology investment may hurt suppliers' profit when the manufacturer participates in developing investment. Furthermore, (2) regardless of the level of technological uncertainty, the manufacturer sets a higher profit margin if he participates in developing investment, which makes suppliers lower their wholesale prices. Then, (3) the manufacturer always participates in developing investment activity. Whether to invest in one or two suppliers depends on the manufacturer's development capability and the relative success rate of technology investment. When the manufacturer's development capacity is weak, the manufacturer should invest in the two suppliers, which can be strengthened when the success rates of investing in one supplier and two suppliers are close. Last, (4) Supplier 1 always prefers the strategy where the manufacturer invests in two suppliers simultaneously but the preference of Supplier 2 relies on the manufacturer's development capacity, the production cost, and the potential market.

Supply Chain Priority Strategy and Added Value of Jackfruit in Tambang Sub-District, Kampar District, Riau Province

This research aimed to a) identify the flow of the jackfruit supply chain; b) obtain the added value of the jackfruit chips agroindustry; c) analyze the level of efficiency of the jackfruit chips agroindustry; d) formulate strategies and determine strategic priorities for increasing the supply chain and added value of jackfruit. The methods used in this research are both qualitative and quantitative. The research stage starts by analyzing the jackfruit supply chain using a framework of the food supply chain network (FSCN), calculating the added value of chips in the jackfruit chips agroindustry using the Hayami method and analyzing the level of efficiency of the jackfruit chips agroindustry. The researchers then formulate a strategy using SWOT and select priority strategies using the method of analytical hierarchy process (AHP). The research results showed that the supply chain structure consists of two structures, namely structure 1 (supplier-jackfruit chips agroindustry-consumer) and structure 2 (supplier-jackfruit chips agroindustry-retail-consumer). The flow of goods occurs from suppliers to consumers, the flow of money from consumers to suppliers, and the flow of information from suppliers to consumers and vice versa. The calculation of added value obtained from micro, small, and medium enterprises (SMEs) in Sinar Hidayah was IDR 8,198.71/kg, Usaha Baru Ibu was IDR 13,960.58/kg, and Restu was IDR 4,718.75/kg. The R/C ratio in SME Sinar Hidayah is 1.72, Usaha Baru Ibu is 2.42, and Restu is 1.26. Based on the results of the strategy formulation, the priority strategy was obtained, namely expanding the raw material and marketing network for jackfruit chips with a weight of 0.331, and the selected criteria was logistics with a weight of 0.322.

Investigate How CEAT Manages its Raw Materials, Production Processes, and Distribution Channels

The research paper aims to provide a comprehensive understanding of CEAT's supply chain management practices, focusing on three critical areas: raw materials management, production processes, and distribution channels. The combination of primary and secondary data collection methods ensures a robust and nuanced exploration of these aspects. The primary data collection involves interviews with key personnel directly engaged in CEAT's supply chain operations. This approach offers firsthand insights into the company's strategies, challenges, and successes in managing raw materials, optimizing production, and streamlining distribution channels. These interviews provide a qualitative dimension to the research, offering a deeper understanding of the day-to-day decision-making processes within CEAT's supply chain. Complementing the primary data, secondary data collection involves an extensive review of existing literature, company reports, and industry publications. This approach allows for a broader contextualization of CEAT's practices within the global tire manufacturing sector. By benchmarking against industry best practices, the study can identify areas where CEAT excels and areas for potential improvement. The paper's structure facilitates a systematic exploration of CEAT's supply chain, starting with an overview of the company's supply chain structure. This sets the stage for a detailed examination of how CEAT manages its raw materials, delving into procurement strategies ensuring a stable and reliable supply chain. The investigation then shifts to production processes, assessing the adoption of technology, implementation of quality control measures, and the overall operational efficiency in tire manufacturing.

How does green manufacturing promote the recycling of renewable solid waste and carbon reduction?

Solid waste recycling plays a key role in the manufacturer's green transition. By introducing recycled materials into production, manufacturers can enjoy both the benefits of carbon reduction and the addressing of the carbon lock-in problem. However, given the inadequacy of recycling legislation, the supply of recycled material is subject to yield uncertainty. This creates a challenging decision for manufacturers in need of transition: should they build a new carbon-neutral production line or only upgrade the existing production line? We formulate the key tradeoffs including the varying consumer evaluations, the production quality control, and the reform of the supply chain structure. We find that building a new carbon-neutral production line is preferred when the carbon emission level is moderate, the market competition is intensified, and the recycling efficiency is high. We further identify the multi-win opportunities for both environmental and economic sustainability, which shed light on the government's green policy design.

Impact of additive manufacturing and parametric design on the structure and economic efficiency of construction supply chains

Additive manufacturing and parametric design are anticipated to unfold potentially a strong momentum on costs regarding labor and material savings, as well as elevating automation and productivity within the construction industry. However, research on linking these technologies for use in the construction industry and analyzing the impact on the supply chain structure is scarce. Information in view of challenges regarding technical feasibility and requirements is limited. This paper aims to analyze the technology induced structural change of a construction supply chain and its thereby inherent influence on value creation and economic efficiency. A systematic literature review and a case study were conducted for understanding the impacts of combining additive manufacturing and parametric design. The impact on the structure of the supply chain is product specific, depending on the technology used to design, manufacture and automate as well as material performance, regulatory and technical requirements. Process steps can be encapsulated in technical modules driven by the digital characteristics of the two technologies. There are positive effects on (re-)working time, material consumption, waste reduction, strengthened innovative capacity and shorter delivery times, resulting in labour and cost optimization.

Tariff Rate Uncertainty and the Structure of Supply Chains

Tariff Rate Uncertainty and the Structure of Supply Chains

Research on inventory replenishment strategy of supply chain based on SPN

The warehousing and replenishment strategy of supply chain is comprehensively affected by various factors such as supply chain structure, demand change, supply source, inventory state. Supply chain warehousing replenishment is full of uncertain factors, in order to achieve the optimal replenishment process and the best replenishment strategy effect, this paper uses SPN(Stochastic Petri net) to build the supply chain warehousing replenishment model. Based on the basis of the traditional replenishment process, this paper optimizes the new supply chain warehousing management process, optimizes the priority management measures of goods in the process of supply chain warehousing replenishment process, designs the new replenishment strategy algorithm and designs the replenishment strategy function analysis. Using SPN model, this paper intuitively shows the warehousing management process, and describes the dynamic changes of warehousing replenishment in detail. Through the implementation of different warehousing replenishment strategies to solve the influencing factors of uncertainty, so as to avoid the problem of various supply chain warehousing shortage caused by poor warehousing management. Finally, by comparing the traditional warehouse management strategy and the SPN model optimization of the supply chain storage strategy, the research result shows that the SPN replenishment strategy model is more efficient than the traditional warehouse replenishment strategy model.

Supply chain modelling and LARG performance evaluation under severe disruptions: the case of the fast-food industry

the LARG paradigm involves and combines different perspectives: Lean, Agile, Green, and Resilience. These four perspectives are recognized as a suitable response to the strong demand fluctuations and characteristics of modern variables and unpredictable markets. Their integration into modern supply chains is also crucial from a strategic point of view. This study develops a simulation model useful for measuring and evaluating the LARG performance of a supply chain operating in the fast-food industry. Different configurations have been tested varying the number of players and the target service level. Then, different scenarios with distortions have been compared. Results show that the service level influences the LARG performance regardless of the kind of disruption. The supply chain structure can affect LARG performance when the demand increases, while it seems not relevant if the demand decreases.

Models and Methods of Applied Mathematics in Supply Chain Management and Optimization

Abstract Amidst the swift expansion of the global trade economy, enterprises are confronted with escalating competition within their industries. Enhancing market competitiveness to boost economic efficiency emerges as a pivotal strategy for ensuring corporate viability. This study employs applied mathematics to refine the optimization of supply chain management, thereby offering a novel approach to augmenting management efficacy in enterprise supply chains. Initially, the research adopts mathematical models tuned to the traditional structure of enterprise supply chains, addressing prevalent profiling issues. Subsequently, it introduces a two-tier planning model to facilitate multi-objective decision-making in supply chain management. This model is rigorously applied to resolve various decision-making scenarios. An empirical analysis is conducted using Company M as a case study. Post-optimization, Company M's inventory exhibited only one instance of material shortfall, involving 132 items. The capital tied up in inventory was significantly reduced to 214,092 yuan—a decrease of 36,319 yuan compared to the capital occupied under traditional supply chain management methods. Furthermore, the optimized supply chain management system demonstrated a notable increase in the average inventory turnover rate to 12.3507%, marking an improvement of 3.6923% over the traditional model. The findings underscore the efficacy of the proposed optimization in enhancing the economic efficiency of enterprise supply chain management. This optimization not only streamlines operations but also provides robust support for the ongoing development of enterprise supply chains.

Supply chain disruption recovery strategies for measuring profitability and resilience in supply and demand disruption scenarios

This paper examines the recovery of a three-level manufacturing supply chain under supply and demand disruptions. The paper proposes new combined recovery strategies, which aim to cope with interruption by adjusting the supply chain structure and material flows. This study integrates both supply chain performance and supply chain capability dimensions. We develop a bi-criteria mixed integer linear programming model with profit and resilience maximization as the objective. The model combines supply-side supply expansion, manufacturer capacity impairment, and demand regulation on the demand side. In a numerical example, we find that a “reciprocal disruption overlay” occurs when supply and demand disruptions, but the supply chain still loses some profit. The results suggest that the combined recovery strategies reduce profit loss and increase supply chain resilience. Furthermore, the strategies are also the optimal recovery strategies under unilateral disruptions. This model facilitates the coordination of a disrupted supply chain and can help managers decide on the best recovery plan.

Omni-channel retail supply chain structures: a review of distribution and logistics

Omni-channel retail supply chain structures: a review of distribution and logistics

Information Communication Tools in Alternative Food Networks

Effective communication in food supply chains is increasingly important, especially in supply chains that strive to provide improved levels of information from producer to consumer. Such supply chains can be found in alternative food networks. Alternative food networks often adopt local and short supply chain strategies to provide embedded information between producers and consumers. Information in the supply chain of alternative food networks is communicated through face-to-face, proximate, or extended supply chain structures. The tools used to communicate information vary amongst the supply chains in alternative food networks; for example, face-to-face may adopt word-of-mouth, while proximate and extended supply chain structures may use labels, digital platforms, and websites. This paper uses Principal Component Analysis to provide an understanding of the categories and underlying dimensions of information communication tools in the supply chains of alternative food networks. A living lab approach and survey method were used for data collection. Using Principal Component Analysis, the data revealed two principal components of information communication tools, highlighting the use of on-packaging information communication tools such as packaging and labelling tools as a principal component. Another principal component was identified, backing a need for off-packaging information communication tools such as digital technologies, certificates, social media, and packaging technologies, enabling stakeholders who desire a further understanding of information regarding the processes and products. The paper concludes with the implications, limitations, and areas of future work.

Omni-channel retail supply chain structures: a review of distribution and logistics

Omni-channel retail supply chain structures: a review of distribution and logistics

The impact of supply chain structure on the promotion of maritime green energy consumption under carbon emission regulation

The impact of supply chain structure on the promotion of maritime green energy consumption under carbon emission regulation

Forecasting Order Delays with Artificial Intelligence-Based Applications

The digitalization trend in the world in the last two decades has begun to transform business processes. Departing from the traditional business approach, the use of technology in every field has changed business processes and, accordingly, the approach of managers. On the other hand, cloud computing, the internet of things, sensors and instant notification systems through these components brought by the last industrial revolution have transformed supply chains into a smart structure. Now, the information that a product sold by a retailer, which is the last link of a supply chain, is out of stock is transmitted to the raw material supplier in the first link of the chain. In this way, a perfect supply chain structure is formed and operations are carried out in lean working principles. The products prepared according to the reduction of the retailer's stocks are continuously supplied, which shows flawless operation. On the other hand, through digital components such as sensors and the Internet of Things, each step in workflows is instantly converted into data and stored in virtual environments called cloud computing. At this point, besides the problem of data storage and security, the main problem is to process the data in a meaningful way. Analyzing big data generated by AI-based components and systems is also possible with AI-based systems. Methods called machine learning have been developed for this situation and their application area is increasing day by day. In the light of this information, within the scope of the study, forecasts of order quantity delays for future periods using historical order data from customers for the products produced by an enterprise were analyzed using machine learning algorithms. The results of the analysis made through the Microsoft Azure Machine Learning Studio platform will contribute to the use of digital tools in the sector as well as increasing the application examples of machine learning. According to the results obtained as a result of the analyzes, recommendations were developed for the enterprise. Finally, suggestions for the application of machine learning in the field of business administration are presented.