Altruism and Pricing Strategy in Dual-Channel Supply Chains

With the development of behavioral operational management, human behavior such as altruism, fairness and trust has received considerable attention. This paper studies the effect of altruism on retailer’s and manufacturer’s pricing strategy in two classic dual-channel supply chains by presenting Stackelberg game models. The analysis shows that the player’s altruism preference strongly affects their pricing strategies. The more altruistic one player is, the more profits the other player obtains. Moreover, the effect of manufacturer’s altruistic preference is larger than that of retailer’s. In addition, online price is always lower than offline price in dual-channel supply chain, which still holds true considering altruism. The results also reveal that the product web-fit has significant effect on the player’s optimal pricing strategies. The more compatible with online market the product is, the lower the retail price is set, and the more profit the manufacturer obtains whereas the less the retailer gets.

International Supply Chain Cooperation and China’s Role

In recent years,the challenges facing the development of international supply chains have been increasing.Major country competition,COVID pandemic and geopolitical conflicts have impacted the development of international supply chains and continue to have negative effects.Against this background,the international community should cooperate to deal with the risks and challenges.

Global Supply Chain Governance and the Future of Globalization

Over the past 30 years or so,globalization has been underpinned by ever-evolving supply chains.The heightened attention to supply chain issues in recent years has been due to a series of global events in the world that have had a significant and profound impact.Factors such as the COVID pandemic,the Ukraine Crisis and increased geopolitical tensions have led to supply chain crises globally or regionally.

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.

Research on the Digital Transformation of the Whole Industry Chain of Guangdong Supply and Marketing Cooperative

Guangdong Supply and Marketing Cooperative serves as an important institution for the“Three Rural Areas”in the Guangdong-Hong Kong-Macao Greater Bay Area.Its digital transformation and optimization serve as powerful supports for rural revitalization.This paper systematically reviews the main practices and effectiveness of the digital transformation within the Guangdong Supply and Marketing Cooperative.It also analyzes the current development dilemmas faced in the construction of digital supply and marketing.Additionally,it proposes targeted solutions,including building a big data resource base,optimizing the digital supply and marketing cloud platform,developing digital publictype agricultural social service applications,establishing a new model of rural e-commerce,enhancing the traceability management system for agricultural products,and strengthening the construction of the digital human resources system.These proposals aim to further promote the strategy for revitalizing the countryside.

The Effect of Money-Back Guarantee and Customer Value on Dual-Channel Supply Chain

This paper investigates the effect of money-back guarantee (MBG) and customer value on dualchannel supply chain.Manufacturer could produce and sell old generation product by direct channel to compete with new generation product by retail channel.Both retailer and manufacturer could choose whether implementing the MBG strategy or not.This paper discusses whether manufacturer should open the direct channel,how to make MBG strategy to realize maximum profits,and how customer value influences the supply chain.We give the boundary conditions of four situations about the decisions of retailer and manufacturer GG situation,GN situation,NG situation and NN situation.We find that MBG strategy by retailer brings higher retail unit price,MBG strategy by manufacturer brings higher direct unit price and influences the wholesale price by the net salvage value of new generation product.This paper shows that if the demand was positive,opening the direct channel always benefits the manufacturer.Besides,customer value affects demands of two channels and the threshold value of parameter is given in this paper.

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.

Measuring Global Supply Chain Vulnerabilities Using Trade Network Analysis Method

With the trade network analysis method and bilateral country-product level trade data of 2017-2020,this paper reveals the overall characteristics and intrinsic vulnerabilities of China’s global supply chains.Our research finds that first,most global supply-chain-vulnerable products are from technology-intensive sectors.For advanced economies,their supply chain vulnerabilities are primarily exposed to political and economic alliances.In comparison,developing economies are more dependent on regional communities.Second,China has a significant export advantage with over 80%of highly vulnerable intermediate inputs relying on imports of high-end electrical,mechanical and chemical products from advanced economies or their multinational companies.China also relies on developing economies for the import of some resource products.Third,during the trade frictions from 2018 to 2019 and the subsequent COVID-19 pandemic,there was a significant reduction in the supply chain vulnerabilities of China and the US for critical products compared with other products,which reflects a shift in the layout of critical product supply chains to ensure not just efficiency but security.China should address supply chain vulnerabilities by bolstering supply-side weaknesses,diversifying import sources,and promoting international coordination and cooperation.

Global Supply Chain Promotion Report Is Released

During the first CISCE,the Global Supply Chain Promotion Report(hereinafter called report)was released.As the flagship report of the expo,the report is the world’s first research report themed around the supply chain promotion from the perspective of business community.Over the past 7 months,the CCPIT research institute has conducted a survey covering 526 domestic and overseas enterprises and has also conducted interviews with more than 100 global and domestic experts.The report is finished with about 150,000 letters.

The First CISCE-Building A Resilient Global Industrial and Supply Chain

The first China Interna-tional Supply Chain Expo(CISCE)hosted by the CCPIT and organized by China International Exhibition Group Limited,will be held in Beijing from November 28th to December 2nd.

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.

CISCE Seeks Co-operation and Draws A New Chapter for the Security and Stability of Industrial and Supply Chain——Beijing Hosts Festive 100-Day to Go Celebration for First China International Supply Chain Expo

The 100-Day to Go Celebration for the First China International Supply Chain Expo(hereinafter CISCE)took place in Beijing recently.Hosting the first CISCE represents a tangible step towards realizing Chinese President Xi Jinping’s important initiative of upholding stable and streamlined global industrial and supply chains.It also stands as a public good that contributes to fostering a robust and sustainable trajectory for economic globalization.The commencement of the 100-day countdown to the expo marks a pivotal phase characterized by intense efforts in preparation.

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.

Supplier Selection Fuzzy Model in Supply Chain Management:Vietnamese Cafe Industry Case

Supplier selection is a vital part of the supply chain and is also a current issue that concerns businesses today as supplier quality directly affects the operations of the organization.Choosing the right supplier can help businesses increase productivity,competitiveness in the market,and profits without having to lower the quality of the products.However,choosing a supplier is not a simple matter,it requires businesses to consider many aspects about their suppliers.Therefore,the goal of this study is to propose an integrated model consisting of two models:Fuzzy Analytics Network Process(Fuzzy-ANP)model and Weighted Aggregated Sum Product Assessment(WASPAS)to solve the problem above.The Fuzzy-ANP model was developed to evaluate the weightings of the supplier selection criteria,and the WASPAS Model was used to rank the suppliers.An example of supplier selection in the coffee industry in Vietnam was studied to validate the model,namely 5 main criteria,with 16 sub-criteria,and 7 suppliers.The model test results show that the Fuzzy ANP and WASPAS integration model was suitable.In future,these developing models can apply to other industries or integrate with other models.

RESEARCH ON VALUE OF INFORMATION SHARING IN ONE SUPPLIER-MULTIPLE RETAILER SUPPLY CHAIN

Prior research has generally focused on models involving a single or multiple retailers with independent demands. The value of demand information sharing is analyzed in a two-level supply chain involving one supplier-multiple retailer model in which retailer demands may be correlated. Each member in the supply chain forecasts its demand using an AR (1) demand process. Two conditions of the information sharing are considered (1) Without the information sharing, the retailers only communicate their orders to the supplier. (2) With the information sharing, retailers communicate their orders and forecasting models to the supplier. Analyses showthat the reductions of supplier's average inventory and average costs are substantial with the information sharing. However, the retailers donot get direct benefit from the information sharing. The retailers may ask the supplier to reduce the replenishment leadtime, so that the retailers will obtain substantial cost savings and inventory reduction. Both partners may obtain benefits when information sharing and leadtime reduction are implemented together.