Procedure Modeling and Analyzing of Supply Chain Collaborative Decision Mode

There has been ongoing controversy among scholars as to whether the Customer to Manufactory (C2M) supply chain can generate revenue through information technology investment and how to distribute revenue obtained by information sharing. First, this dissertation constructs two kinds of revenue distribution models, namely models based on independent decision-making and collaborative decision-making. Then, according to the status differences between the manufacturer and the distribution enterprise in the supply chain, the C2M supply chain is divided into three situations for example analysis. The research revealed that under the condition of equal input level of information sharing, the revenue of information sharing is greater when the manufacturer and the distribution enterprise collaborate with each other. When manufacturers of equal status cooperate with distribution companies, their revenues of information sharing are directly proportional to their information sharing investment levels. However, when status is not equivalent, most of the revenues generated by information sharing are dominated by the dominant company. Therefore, there is insufficient motivation for cooperation between the two parties. Finally, this paper points out that a well-designed revenue redistribution mechanism can improve the efficiency of information sharing, achieve the rationality and effectiveness of supply chain profit distribution as well as maximize the value of C2M e-commerce supply chain information sharing.

We study the interplay between inventory replenishment policies and information sharing in the context of a two-tier supply chain with a single supplier and a single retailer serving an independent and identically distributed Gaussian market demand. We investigate how the retailer’s inventory policy impacts the supply chain’s cumulative expected long-term average inventory costs [Formula: see text] in two extreme information-sharing cases: (a) full information sharing and (b) no information sharing. To find the retailer’s inventory policy that minimizes [Formula: see text], we formulate an infinite-dimensional optimization problem whose decision variables are the MA([Formula: see text]) coefficients that characterize a stationary ordering policy. Under full information sharing, the optimization problem admits a simple solution and the optimal policy is given by an MA(1) process. On the other hand, to solve the optimization problem under no information sharing, we reformulate the optimization from its time domain formulation to an equivalent z-transform formulation in which the decision variables correspond to elements of the Hardy space H2. This alternative representation allows us to use a number of results from H2 theory to compute the optimal value of [Formula: see text] and characterize a sequence of ϵ-optimal inventory policies under some mild technical conditions. By comparing the optimal solution under full information sharing and no information sharing, we derive a number of important practical takeaways. For instance, we show that there is value in information sharing if and only if the retailer’s optimal policy under full information sharing is not invertible with respect to the sequence of demand shocks. Furthermore, we derive a fundamental mathematical identity that reveals the value of information sharing by exploiting the canonical Smirnov–Beurling inner–outer factorization of the retailer’s orders when viewed as an element of H2. We also show that the value of information sharing can grow unboundedly when the cumulative supply chain costs are dominated by the supplier’s inventory costs. Funding: R. Caldentey acknowledges the University of Chicago Booth School of Business for financial support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/moor.2023.0008 .

This paper aims to study the collaborative replenishment issue in the prefabricated supply chain of electronic products. Firstly, it analyzes the current situation of the replenishment mechanism in the electronic product supply chain, reveals the limitations of the traditional replenishment mechanism, and emphasizes the importance of collaborative replenishment. Secondly, it studies the impact of supply chain collaborative management on replenishment, including the concept and principle of collaborative management, the application of collaborative management in replenishment, as well as the benefits and limitations brought by collaborative management. Then, it discusses the impact of demand forecasting on replenishment decisions, including demand forecasting methods and their applicability, the impact of prediction accuracy on replenishment efficiency, and the challenges of demand volatility to the replenishment plan. Finally, it proposes optimization and implementation suggestions for replenishment strategies, including the exploration of new replenishment modes, data-driven replenishment decisions, and the path and obstacles of cross-organizational collaborative replenishment. The results of this study can provide theoretical support and practical guidance for the replenishment management of the electronic product supply chain. They can also help promote enterprises to achieve sustainable development in the highly competitive market.

Societal Effects of Collaborative Decision-Making in Florida: The Impact of Environmental Conflict Resolution Institutions on Public Choice, Civic Culture and Environmental Management Systems

In today's global business competition environment, the significant changes in the market environment make it very difficult for supply chain enterprises to gain a place in the fierce market only by their strength. This article will do the following research work to effectively play the role of supply chain management. First, the concepts, and characteristics, related applications of supply chain information sharing (IS) and genetic algorithm back propagation (GABP) neural networks, are expounded. Then, the feasibility of applying BP neural network (BPNN) to evaluate supply chain IS is analysed. Next, the assessment indicator system for IS is constructed from four aspects: IS infrastructure, IS member characteristics, IS content, and the quality of supply chain enterprises. Finally, the principle and algorithm of BPNN are analysed, the network model is constructed, the BPNN process based on GA is designed, and every step in the process is explained in detail. The sample input is provided for the network model by obtaining and sorting data. The supply chain IS assessment model based on the GABP neural network is constructed. The results show that the assessment model of supply chain IS based on the GABP neural network has high accuracy, and the highest network accuracy reaches 95.01%, which proves that the assessment model based on BPNN has certain advantages for the supply chain IS of the financial industry.

Many companies have tried to get the competitive advantage through the effective supply chain management. To manage the supply chain effectively, many strategy based on the shared information among the entities in supply chain has been developed. Although the supply chain members agree with the idea that the policy based on the shared information will be beneficial to improve the effective supply chain, they are reluctant to share their information owing to some barriers such as the expensive technology investment, personnel training and lack of mutual trust. The benefit from the sharing information may vary according to the supply chain environment. According to an environment of supply chain, the profit gained through the policy based on the shared information may be too low to collect the invested amounts or high enough to give proper compensation. To gain this insight, we analyze the impact of the Vendor Managed Inventory, which is one of the popular supply chain strategy based on the share information, in various supply chain environment. The simulation experiment shows in which environment their benefit from the policy based on the shared information will be increased (or decreased).

With an increasing focus on sustainable development and the reuse of disused infrastructure, there is a pressing need for effective decision-making methods. This study explored the use of the PROMETHEE method within a collaborative decision-making framework to assess the adaptive reuse options for a disused railway in Sicily, Italy. Using a participatory paradigm, the research actively involves stakeholders in the assessment process. The collaborative PROMETHEE approach acts as a tool for multi-criteria decision analysis, facilitating the comparison and prioritization of different reuse alternatives based on predefined criteria. The research highlights the effectiveness of PROMETHEE in streamlining decision-making processes for adaptive reuse efforts, particularly in the context of integrated conversions of abandoned railways. By combining multi-criteria decision analysis with collaborative methods, the study contributed to the formulation of sustainable and socially responsible strategies for the valorization of disused railway infrastructure. The results underline the importance of collaborative decision-making processes and the instrumental role of PROMETHEE in assisting stakeholders in evaluating and selecting adaptive reuse options for disused railways, thereby, in turn, promoting the sustainable development of these sites.

In the new context of information sharing to reshape the supply chain’s interruption risk propagation mechanism, this paper focuses on the interruption risk propagation and resilience of the supply chain of emergency medical supplies in the background of emergencies. Firstly, an emergency supply chain’s risk propagation model under information sharing is proposed by combining the information sharing mechanism with the supply chain’s risk propagation theory. Secondly, an interruption risk propagation model for the supply chain of emergency medical supplies based on a Bayesian Network is constructed, and the do-calculus technique is introduced to transform the intervention effect of information sharing into the quantification of the supply chain’s risk probability. Thirdly, a system dynamics method is used to construct a supply chain model for emergency medical supplies, which takes into account different interruption scenarios caused by emergencies and evaluates the supply chain’s resilience through the key variable “demand fulfillment rate” in the model. The results of the study indicate that the impact of different types of interruption scenarios on supply chain resilience varies significantly. Information sharing can effectively reduce the negative impact of interruption risk. This study provides theoretical basis and practical guidance for improving the resilience of the supply chain of emergency medical supplies, which is of great significance for maintaining social stability and promoting the sustainable development of the public health system.

PurposeThe purpose of this paper is to empirically examine the impact of internal and external collaborative forecasting and planning on logistics and production performance.Design/methodology/approachTo measure the degree of collaborative forecasting and planning, the concept of collaboration is categorized into three dimensions: sharing resources, collaborative process operation, and collaborative process improvement. Based on these dimensions, a survey of Japanese manufacturers was conducted and the analytical model is proposed to examine using structural equation modeling.FindingsThere are positive relationships between internal and external collaborative forecasting and planning. Upstream and downstream collaborative forecasting and planning are also positively related. Internal collaborative forecasting and planning has a positive effect on relative logistics and production performance. External collaborative forecasting and planning does not have a significant effect on relative logistics and production performance.Research limitations/implicationsThis study does not clarify how firms can achieve the improvement of forecasting and planning process. Future research should investigate the mechanism of process improvement in supply chain.Practical implicationsNot only sharing resources and collaborative process operation but also collaborative process improvement play a crucial role in gaining sustainable competitive advantage in logistics and production.Originality/valueThis study focuses on the forecasting and planning process in supply chain and proposes new dimensions measuring the degree of collaborative forecasting and planning. By focusing on the process and using the dimensions, the relationship between supply chain collaboration and performance are discussed concretely.

Supply chains are increasingly becoming more complex, making collaboration progressively difficult to establish and maintain. It is imperative to understand not only the consequences, but also the drivers of effective and efficient collaboration. In this study, we attempt to show how varying levels of collaboration impact service level and how cloud computing fosters these levels of collaboration. We introduce a framework detailing how cloud computing impacts three levels of collaboration: (1) information centralisation, (2) vendor managed inventory and continuous replenishment programmes and (3) business intelligence (BI) collaborative planning, forecasting and replenishment. In addition, we use multi-agent-based simulation to analyse how each level of collaboration (enhanced through cloud computing) impacts service level as measured by fill rate. Obtained results show that cloud computing can enhance all three levels of collaboration. Further, our results demonstrate that BI collaborative planning, forecasting and replenishment have significantly greater service level benefits in comparison to other collaboration levels.

This study examines whether the potential for hold-up in supply chains influences the extent of process integration and information sharing between partners. The analysis uses performance scorecards and financial performance data collected from a major manufacturer regarding its contractual arrangements with 156 distributors. I find that distributors engage in less extensive process integration and information sharing with the manufacturer as the potential for hold-up increases, measured by the asymmetry of interdependence between partners. I also find that distributors engage in more extensive process integration and information sharing as the potential for hold-up decreases, measured by the magnitude of interdependence between partners. Additional evidence shows that more extensive process integration and information sharing have favorable financial performance implications for supply chain partners and enhance the likelihood of distributor contract renewal. Overall, the results indicate that the potential for hold-up can restrict the performance benefits available to partners from developing more extensive supply chain integration practices. Data Availability: A confidentiality agreement restricts data availability. Some data have been modified by a common factor to preserve research site confidentiality.

The paper investigates in the relationship between supply chain management, financial information sharing and collaborative behavior to find out if there is any information sharing between different companies in a supply chain on the financial level and what could be the benefits from financial information sharing for the whole supply chain. The used method is a systematic literature review to answer the research question. The main findings show a strong relationship between information sharing on the financial level along supply chains and a positive impact on competitiveness and financial performance of the involved companies. Information sharing in supply chains has also a positive impact on the collaborative behavior of the companies and the level of trust, whereas the quantity of information sharing is not that relevant but the quality of shared information is much more important. Further research is recommended to find out if there are any differences in the research-results related to the position of the company it has in his supply chain, whether is it an original-equipment-manufacturer or a first-tier supplier or a raw-material supplier. Keywords Supply Chain Management, Financial Information Sharing, Collaborative Behavior

The purpose of this study is to analyze the impact of information technology, information sharing, and trust on supply chain performance, with supply chain integration as a mediating variable. The research method used is a quantitative approach, with questionnaires distributed to 236 individuals in the retail supply chain in Batam. Data were analyzed using the PLS method with SmartPLS 3.0. The results show that information technology and trust have a significant positive relationship with supply chain performance. Additionally, supply chain integration strengthens the relationships between information technology, information sharing, trust, and supply chain performance. However, it was found that information sharing does not have a significant relationship with supply chain performance. The implications of this study highlight the importance of effective use of information technology to enhance supply chain integration, which in turn strengthens information sharing and trust among partners, thereby improving retail performance in Batam City.

In the cross-border e-commerce transaction supply chain, information sharing can coordinate the relationship between node companies, promote long-term cooperation, and maximize the overall benefits of the supply chain. This paper uses evolutionary game to study the information sharing between retailers and manufacturers in the cross-border e-commerce supply chain, builds a related evolutionary game model, analyzes the game equilibrium conditions of retailers and manufacturers, and the influencing factors of both parties’ information sharing. The research results show that the initial sharing ratio of information, cost of information sharing, income after information sharing, risk of loss of important information, and trust level all affect the effect of information sharing between the two parties. Measures to maximize the interests of both parties include: increasing mutual trust, rational distribution of income, compliance with laws and regulations, avoidance of loss of important information, and reducing information sharing costs.

This study considers a two-echelon supply chain with one supplier and one retailer for products with seasonal demand. The effects that information sharing has on coordination and benefits of the supply chain are investigated. In order to better forecast the seasonal demand, the supplier initiates the information sharing process by offering incentives to the retailer which are proportional to the degree of information sharing. Since the variance in the supplier's inventory would marginally decrease as the degree of information sharing increases, the benefits gained by the supplier due to information sharing are thus a convex function. This can be used to obtain the optimal degree of information sharing with the aim of maximizing profits, which is a tradeoff between the benefits gained and costs incurred by information sharing. In this study, the seasonal demand is described by a SARMA time series model. Bayesian analysis is employed to investigate the value of information and determine the optimal degree of information sharing. Constructive properties are derived to provide managerial insight for effective decision making. The results of sensitivity analyses show that the correlations of demand for successive periods and estimation errors would both have great effects on the benefits gained by information sharing.