Analysis of the Supply Chain in Industrial Companies in Guayaquil,Ecuador-A Secondary Publication

This research clearly outlines the supply chain in a process of evolution and digital transformation,where the collaboration of its members is concentrated,having technological tools to help chain management.To analyze the advantages that this transformation produces in the supply chain,as well as its different processes,this study has a systemic perspective that involves precise elements for organizational development,such as the different phases of each process,operations,logistics,and distribution.It must be borne in mind that any strategy in industrial companies grants the automation of procedures in the supply chain and determines a product in any phase of production,making the organization more sensitive to any variation in orders.The methodology included a bibliographic and non-experimental review that allows a descriptive and analytical study,which details the various characteristics of the fact that is being investigated,collecting information through interviews with different people who are involved with industrial companies.Among the results obtained,it was identified that digital transformation helps reduce costs and generates greater profitability.In conclusion,it was obtained that the digital supply chain helps in each of the phases of the processes,these are supervised by devices that help to have fast and effective information.

Automobile Transportation Logistics Supply Chain Management Strategy

To enhance the management level and quality of the automobile transportation logistics supply chain and promote innovation and development in automobile transportation logistics enterprises,it is essential to strengthen the construction of the automobile transportation logistics supply chain management model.This can be achieved through the gradual improvement of the automobile transportation logistics management process,ensuring that the management of the automobile transportation logistics supply chain proceeds in an orderly manner.The aim is to improve automobile transportation and logistics service levels while meeting the changing market supply needs.This will enable automobile transportation and logistics enterprises to maintain steady economic benefits and enhance their core competitiveness in the market.Therefore,this paper has conducted a comprehensive exploration and research on managing the automobile transportation logistics supply chain.Corresponding management strategies are proposed as a starting point to achieve the aforementioned goals.

Dynamic decision and its complex dynamics analysis of low-carbon supply chain considering risk-aversion under carbon tax policy

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability,especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation.

Leveraging Blockchain with Optimal Deep Learning-Based Drug Supply Chain Management for Pharmaceutical Industries

Due to its complexity and involvement of numerous stakeholders,the pharmaceutical supply chain presents many challenges that companies must overcome to deliver necessary medications to patients efficiently.The pharmaceutical supply chain poses different challenging issues,encompasses supply chain visibility,cold-chain shipping,drug counterfeiting,and rising prescription drug prices,which can considerably surge out-of-pocket patient costs.Blockchain(BC)offers the technical base for such a scheme,as it could track legitimate drugs and avoid fake circulation.The designers presented the procedure of BC with fabric for creating a secured drug supplychain management(DSCM)method.With this motivation,the study presents a new blockchain with optimal deep learning-enabled DSCM and recommendation scheme(BCODL-DSCMRS)for Pharmaceutical Industries.Firstly,Hyperledger fabric is used for DSC management,enabling effective tracking processes in the smart pharmaceutical industry.In addition,a hybrid deep belief network(HDBN)model is used to suggest the best or top-rated medicines to healthcare providers and consumers.The spotted hyena optimizer(SHO)algorithm is used to optimize the performance of the HDBN model.The design of the HSO algorithm for tuning the HDBN model demonstrates the novelty of the work.The presented model is tested on the UCI repository’s open-access drug reviews database.

Multimodal Fuzzy Downstream Petroleum Supply Chain:A Novel Pentagonal Fuzzy Optimization

The petroleum industry has a complex,inflexible and challenging supply chain(SC)that impacts both the national economy as well as people’s daily lives with a range of services,including transportation,heating,electricity,lubricants,as well as chemicals and petrochemicals.In the petroleum industry,supply chain management presents several challenges,especially in the logistics sector,that are not found in other industries.In addition,logistical challenges contribute significantly to the cost of oil.Uncertainty regarding customer demand and supply significantly affects SC networks.Hence,SC flexibility can be maintained by addressing uncertainty.On the other hand,in the real world,decision-making challenges are often ambiguous or vague.In some cases,measurements are incorrect owing to measurement errors,instrument faults,etc.,which lead to a pentagonal fuzzy number(PFN)which is the extension of a fuzzy number.Therefore,it is necessary to develop quantitative models to optimize logistics operations and supply chain networks.This study proposed a linear programming model under an uncertain environment.The model minimizes the cost along the refineries,depots,multimode transport and demand nodes.Further developed pentagonal fuzzy optimization,an alternative approach is developed to solve the downstream supply chain using themixed-integer linear programming(MILP)model to obtain a feasible solution to the fuzzy transportation cost problem.In this model,the coefficient of the transportation costs and parameters is assumed to be a pentagonal fuzzy number.Furthermore,defuzzification is performed using an accuracy function.To validate the model and technique and feasibility solution,an illustrative example of the oil and gas SC is considered,providing improved results compared with existing techniques and demonstrating its ability to benefit petroleum companies is the objective of this study.

Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain.In an Internet of Things(IoT)environment,accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain.As an example,this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit(the Shatian pomelo)in a comparative study.The root means square error(RMSE)values of regression analysis,exponential smoothing,grey prediction,grey neural network,support vector regression(SVR),and long short-term memory(LSTM)neural network methods were 53.715,6.707,18.440,1.580,and 1.436,respectively.Among these,the mean square error(MSE)values of the grey neural network,SVR,and LSTM neural network methods were 2.4979,31.652,and 2.0618,respectively;and theirRvalues were 0.99905,0.94,and 0.94501,respectively.The results demonstrated that the RMSE of the deep learning model is generally lower than that of a traditional prediction model,and the prediction results are more accurate.The prediction performance of the grey neural network was shown to be superior to that of SVR,and LSTM neural network,based on the comparison of parameters.

Trade credit financing for supply chain coordination under financial challenges:a multi‑leader–follower game approach

This study is designed to solve supply chain inefficiencies caused by some members’financial problems,such as capital shortages and financing restrictions in a stochastic environment.To this end,we have established a supply chain finance framework by designing two novel coordinating contracts based on trade credit financing for different problem settings.These contracts are modeled in the form of multi-leader Stackelberg games that address horizontal and vertical competition in a supply chain consisting of multiple suppliers and a financially constrained manufacturer.However,previous studies in the trade credit literature have addressed only simple vertical competition,that is,seller-buyer competition.To solve the proposed models,two algorithms were developed by combining population-based metaheuristics,the Nash-domination concept,and the Nikaido-Isoda function.The results demonstrate that the proposed supply chain finance framework can eliminate supply chain inefficiencies and make a large profit for suppliers,as well as the financially constrained manufacturer.Furthermore,the results of the contracts’analysis showed that if the manufacturer is required to settle its payments to suppliers before the end of the period,the trade credit contract cannot coordinate the supply chain because of a lack of incentive for suppliers.However,if the manufacturer is allowed to extend its payments to the end of the period,the proposed trade credit financing contract can coordinate the supply chain.Finally,the sensitivity analysis results indicate that the worse the financial status of the manufacturer,the more bargaining power suppliers have in determining the contract parameters for more profit.

Study on pricing decision of new energy vehicle supply chain under Baa S model

Based on the Baa S model,a new energy vehicle supply chain game model composed of battery-swapping operators and vehicle manufacturers was constructed,and the corresponding optimal decisions of the supply chain members were obtained.The influence of related parameters on the equilibrium results was analyzed,and the Matlab was used for example analysis.The results show that:(1)The increase in the average consumer commuter mileage over the life of the vehicle can promote the increase in the demand for new energy vehicles and the profits of the supply chain members,which has a driving effect on the development of the battery swap industry.(2)Consumer sensitivity coefficient to the price of battery swap has a negative impact on battery-swapping price,new energy vehicle price,market demand for new energy vehicles,and profits of vehicle manufacturers and battery-swapping operators.

Impacts of Transparency and Traceability on Fashion Supply Chain System

The level of fashion consumer awareness and communication regarding sustainable consumption is rising. Organizations are working to provide clarity and guidance on fashion consumption. Brands are experimenting with new materials and supply chain strategies, and suppliers are improving the manufacturing processes and quality of products. However, given the size and complexity of the industrial process, these efforts are not adequate in ensuring a sustainable fashion supply chain. Transparency and traceability in the fashion supply chain are needed to improve the fashion industry by supporting sustainable and ethical practices in the apparel supply chain. Key gaps include a lack of comprehensive and transparent information about how, where, and by whom materials are sourced, processed, and assembled;a lack of transparency in the supply chain practices and procedures affects the environment, working conditions, and human health. The industry has to build the capacity to manage its supply chain, more effectively and responsibly, by improving transparency and traceability as the top goals. So, in this context, the main purpose of this research paper is to study the impacts of transparency and traceability on the dimensions of sustainability in fashion supply chain. The researchers have applied descriptive research methods in which secondary data are collected and analyzed through a literature review of peer-reviewed research papers and the primary data are collected through the survey method by distributing a semi structured questionnaire. The data collected are analyzed using statistical tools and techniques. Finally, the results are discussed and presented.

Greening the Supply Chain: Drivers and Outcomes in the Korean Manufacturing Industry

This research investigates the determinants of green supply chain management(GSCM)adoption and its impact on organizational performance,while considering the potential moderating factors influencing GSCM adoption.Despite the growing prevalence of GSCM practices among Korean firms,the factors driving their adoption have not received sufficient attention.To bridge this gap,the study uses structural equation modeling,integrating stakeholder theory and resource-based theory to explore how green entrepreneurial orientation(GEO),institutional pressure,and relational capital affect GSCM adoption.Additionally,the study explores the effects of GSCM implementation on competi­tiveness and economic performance.Drawing data from a sample of 213 Korean manufacturing firms,the PLS-SEM analysis highlights the significant influence of GEO,institutional pressure,and relational capital on GSCM adoption.Additionally,the study emphasizes the positive impact of GSCM implementation on firm competitiveness.These find­ings provide valuable insights for enhancing sustainability in supply chain management and are applicable to similar context countries such as Taiwan,China,Japan,and the Netherlands.

Revisiting Port Regulatory Governance & Substance: Towards a Holistic Supply Chain Approach

The evolution and integration of ports in global logistics chains has altered their traditional role while has initiated restructuring processes in many ports worldwide. While most of the research addresses this issue by highlighting the need for re-positioning and redefining the role of the port within the supply chains, not much attention has been given to the structure, scope and reach as well as to the tools of regulation hat competent authorities could exploit in order to avert potential abusive actions of global powerful actors along the containerized transport chain, that would affect the competitive functioning of distinct segment or the integrity of supply chains. In this context, we propose the reconceptualization and reinforcement of the regulatory governance structures of ports on a national and international level as well as the extension of the scope of ports’ regulations along the supply chain to counterbalance the globalization, consolidation and integration of containerized transport actors.

Financing Decisions Analysis of E-commerce Supply Chain Finance for Fresh Agricultural Products in China

The supply chain finance(SCF)solutions are becoming increasingly diversified with the continuous perfection of the economic system.However,financing for small and medium sized enterprises(SMEs)is still a difficult issue waiting to be solved by enterprises and the government in China.SCF solutions based on e-commerce platforms have developed rapidly in China that provide an alternative for SMEs when few studies have been conducted on e-commerce SCF solutions which focus on fresh agricultural products.Therefore,this research focuses on the SCF solutions applicable to e-commerce enterprises of fresh agricultural products.

Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.

Issues on Supply Chain Management

Although supply chain is regarded as an integrated pr ocess, actually, researchers and practitioners have primarily investigated the v arious processes of the supply chain individually. The competitive field in most markets requires well-designed integrated supply chain instead of individual o perations. In this paper, some traditional thinking of supply chain is given fir st, then SCM (Supply Chain Management) is introduced, which views the entire sup ply chain as a whole rather than individual process and aims to increase transpa rency and alignment of the supply chain’s coordination and configuration, regar dless of functional or corporate boundaries. Secondly, issues regarding the significance and the situation of supply chain management in enterprises of Chin a are briefly described. In china, most enterprises haven’t established the ide a of supply chain management, supply chain are just focused on the step from sup pliers to manufacturers, which is a partial but not whole supply chain. Challeng ed by intense competition in the global market, further research on supply chain management is badly needed in China, if not, traditional pattern must be overwh elmed by world competition. Finally, suggestions for future research, especial ly the required conditions for a successful adoption of supply chain managemen t, are outlined. Organizations with Supply chain management can realize the advantages of backward vertical integration. However the following issues must b e paid attention to before supply chain management pattern is established.(1) Ch anging the corporate cultures of all members in the value chain to make it condu cive to supply chain management.(2) Developing long-term, cooperative and certi fied relationship with key suppliers.(3) Developing supply chain management soft ware that includes a completely integrated information system based on distr ibuted database throughout supply chain.(4) Reconstructing organization structur e adapting to supply chain management pattern.(5) Developing evaluation system f or performance measures of supply chain. In a word, supply chain management patt ern is necessary for domestic enterprises to win in intense world competition, w hile developing fitting pattern with key prerequisites is the most important.

Neutrosophic Mathematical Programming for Optimization of Multi-Objective Sustainable Biomass Supply Chain Network Design

In this paper,a multi-objective sustainable biomass supply chain network under uncertainty is designed by neutrosophic programming method.In this method,for each objective function of the problem,three functions of truth membership,non-determination and falsehood are considered.Neutrosophic programming method in this paper simultaneously seeks to optimize the total costs of the supply chain network,the amount of greenhouse gas emissions,the number of potential people hired and the time of product transfer along the supply chain network.To achieve the stated objective functions,strategic decisions such as locating potential facilities and tactical decisions such as optimal product flow allocation and vehicle routing must be made.The results of the implementation of neutrosophic programming method show the high efficiency of this method in achieving the optimal values of each objective function.Also,by examining the rate of uncertainty,it was observed that with increasing this rate,the total costs of supply chain network design,greenhouse gas emissions and product transfer times have increased,and in contrast,the potential employment rate of individuals has decreased.

Cloud-Based Supply Chain Integration Service Platform

In recent years, Taiwan has enhanced the manufacturing advantages in the competitive global market because of excellent manufacturing processes, product quality, and the flexible delivery date and speed. However, how to maintain the competitive advantages in the global market has become an issue. Due the advanced development of the Internet, the cloud computing technology has significant progress and become more matured. Therefore, if the cloud computing technology can be applied in the supply chain of the manufacturing industry, the information among manufacturing, assembly, logistics, sales, and customers can be shared and accessed easily. In this study, a cloud-based supply chain integration service platform of the manufacturing industry is developed, and this platform includes the supplier management, procurement and materials management, manufacturing management, facilities planning, customer service, transportation and physical distribution, and information flow to form a supply chain integration service cloud. Thus, the members of the whole supply chain integration service cloud are able to work together, and rapidly deploy and dynamically allocate resources, and the computer hardware and software resources of the upstream and downstream can be appropriately shared. By doing so, the inventory fluctuations caused by the bullwhip effect can also be reduced. Eventually, it will achieve the goals of shortening delivery time, raising production capacity utilization, and decreasing the material preparation time.

Characteristics of Global Automotive Supply Chain

To meet the demands of rapid development of the automotive industry, a well-built supply chain system is needed urgently under the background of globalization. The implication of Global Supply Chain（GSC） is discussed at first. Then, three characteristics of global automobile supply chain such us reversibility, complexity, and synergy are analyzed, and accordingly three apocalypses related global auto supply chain are proposed.

DISRUPTION MANAGEMENT FOR SUPPLY CHAIN COORDINATION WITH EXPONENTIAL DEMAND FUNCTION

The coordination problem of a supply chain comprising one supplier and one retailer under market demand disruption is studied in this article. A novel exponential demand function is adopted, and the penalty cost is introduced explicitly to capture the deviation production cost caused by the market demand disruption. The optimal strategies are obtained for different disruption scale under the centralized mode. For the decentralized mode, it is proved that the supply chain can be fully coordinated by adjusting the price discount policy appropriately when disruption occurs. Furthermore, the authors point out that similar results can be established for more general demand functions that represent different market circumstances if certain assumptions are satisfied.

Supply Chain Coordination with Demand Disruptions under Convex Production Cost Function

This paper investigates the problem of how to handling demand disruptions ina one-supplier-one-retailer supply chain, where production cost is a convex function of productionquantity andprice-demand relationship is linear. Our results show that, ifdemand is disrupted, underthe new price-demand relationship, all-unit wholesale quantity discount policies combiningcapacitated linear pricingpolicies can also fully coordinate the supply chain.

Revenue-sharing contract to coordinate independent participants within the supply chain

To improve the performance of the supply chain with one supplier and multiple retailers under deterministic price-sensitive customer demand, an optimal strategy is proposed based on knowledge discovery. First the decentralized system in which the supplier and the retailers are independent, profit-maximizing participants with the supplier acting as a Stackelberg game leader is studied. Numerical examples illustrate the importance of the coordination. The conventional quantity discount mechanism needs to be modified to coordinate the supply chain, so a revenue-sharing contract is proposed to coordinate such supply chain. Lastly, a special decision under certain demand rates is studied. The pricing and replenishment policies can be decided sequentially, which yields much less loss comparing with optimal decision when the demand rates are sufficiently large.