A decision support system assessing the trust level in supply chains based on information sharing dimensions

Assessing customer trust in suppliers with regards to its influencing factors is an important open issue in supply chain management literature. In this paper, a customer trust index is designed as the trust level arising from the information sharing degree and quality, related to the information shared by a supplier with his customer. The customer trust level is evaluated using a fuzzy decision support system integrating information sharing dimensions. The core is a rule-based system designed using the results of questionnaires and interviews with supply chain experts. Several tests were generated in order to analyze the impact of the different information sharing attributes on the customer trust index. The developed approach is then applied to a real supply chain from the textile industry. Results show large differences of weight and impact between the different information-related factors that build the customer trust index. It is also shown that the proposed system has an important role in ensuring the objectivity of the trust assessment process and in helping decision makers evaluate their business partners.     

Information sharing under different warranty policies with cost sharing in supply chains

In practice, it is found that a product warranty can be provided by either the supplier or the manufacturer. As supply chains are increasingly integrated today, warranty costs are usually shared between the supplier and the manufacturer. In this paper, we model two different warranty policies based on which party provides the warranty: manufacturer warranty and supplier warranty. Considering the demand uncertainty and demand forecast, we analyze the information sharing strategy under these two warranty policies. Our results show that the manufacturer has an incentive to share the demand forecast information under both warranty policies when the cost efficiency in providing a warranty is high, which is different from the existing literature on the incentive for demand information sharing in the supply chain. Moreover, we find that it will hurt the party who determines the warranty period but benefit the other party.     

Information sharing and business systems leveraging in supply chains: An empirical investigation of one web-based application

Web-based supply chain applications promise to provide information sharing capabilities that will enhance the participating organizations’ information capabilities and business benefits. We performed an empirical study of a sophisticated Web-based supply chain application to determine the effect of such information sharing and business systems leveraging on business benefits. We also examined the importance of relational concurrence (i.e., shared business interests among supply chain partners), as an antecedent to both information sharing and business systems leveraging. Our work showed that both information sharing and business system leveraging provided important business benefits and that relational concurrence was only marginally related to information sharing and not at all related to business systems leveraging, limiting the significance attributed to this factor in prior research on inter-organizational systems.     

Closing the gap: towards a process model of post-merger knowledge sharing

Abstract.  We develop a process model of post-merger knowledge sharing based on distributed cognition, a systems perspective and path dependence. The framework conceptualizes knowledge sharing by layers of management choice and employee appropriation of knowledge resources seen as knowledge as content and knowledge as connection. We use the framework to study a merger of two polymer companies. The study reveals that mergers represent a discontinuity in knowledge sharing. Yet, chosen strategies often mirror the learned knowledge-sharing practices of one of the merged companies and match poorly with the post-merger knowledge-sharing needs. Five factors emerged contribute to this knowledge gap: (a) the nature of the merger; (b) a lack of shared context; (c) the incompatibility of existing knowledge systems; (d) the tacit dimension of knowledge; and (e) time pressures of the merger. Our study shows that, employees enacted knowledge new sharing practices that differed significantly from the official strategy to close to the post-merger knowledge gap.     

Flexible business strategies to enhance resilience in manufacturing supply chains: An empirical study

Resilience and flexibility in manufacturing and supply chains are widely discussed at times of the present crises situation due to COVID-19 pandemic. It is a question of ongoing debate among practitioners about the role of flexibility and complexity in building resilience for firms and their supply chains. In this research, we examine the flexible business strategies at the demand, supply, and process side of supply chains contributing to resilience. Five of the major flexible business strategies were acknowledged in this research and the single items for constructing them were posited. In this study, we observe the correlations among the constructs based on survey-based research in electronics manufacturing firms, followed by a dimensionality reduction of constructs using factor analysis. The data collected were subject to several initial tests for ensuring validity, reliability, and adequacy using relevant statistical indicators. The measurement model was converted into a structural model and path coefficients were determined. From the path analysis, the latent variables contributing to flexibility in supply chains were found to be independent estimators of resilience. Adding to it, we observe that the single items for measuring the flexibility of supply, process, product, and pricing strategies were evidenced to be strongly correlated. The results are useful to managers for taking decisions related to flexibility implementation, towards enhancing resilience in supply chains.     

An integrated system for knowledge sharing among heterogeneous knowledge derivation systems

Solving problems in a complex application domain often requires a seamles integration of some existing knowledge derivation systems which have been independently developed for solving subproblems using different inferencing schemes. This paper presents the design and implementation of an Integrated Knowledge Derivation System (IKDS) which allows the user to query against a global database containing data derivable by the rules and constraints of a number of cooperative heterogeneous systems. The global knowledge representation scheme, the global knowledge manipulation language and the global knowledge processing mechanism of IKDS are described in detail. For global knowledge representation, the dynamic aspects of knowledge such as derivational relationships and restrictive dependencies among data items are modeled by a Function Graph to uniformly represent the capabilities (or knowledge) of the rule-based systems, while the usual static aspects such as data items and their structural interrelationships are modeled by an object-oriented model. For knowledge manipulation, three types of high-level, exploratory queries are introduced to allow the user to query the global knowledge base. For deriving the best global answers for queries, the global knowledge processing mechanism allows the rules and constraints in different component systems to be indiscriminately exploited despite the incompatibilities in their inferencing mechanisms and interpretation schemes. Several key algorithms required for the knowledge processing mechanism are described in this paper. The main advantage of this integration approach is that rules and constraints can in effect be shared among heterogeneous rule-based systems so that they can freely exchange their data and operate as parts of a single system. IKDS achieves the integration at the rule level instead of at the system level. It has been implemented in C running in a network of heterogenous component systems which contain three independently developed expert systems with different rule formats and inferencing mechanisms.Database Systems Research and Development Center, Department of Computer Information Sciences, Department of Electrical Engineering, University of Florida     

供应链环境下的RFID标签所有权转换方案

针对供应链环境中存在的企业数据安全问题,提出了一个供应链环境下的RFID标签所有权转换方案.该方案由标签通信协议和标签所有权转换协议两部分组成.当标签处于节点实体内部时,对标签进行查询认证,保证了通信的安全.当标签在节点实体间进行所有权转换时,执行所有权转换协议,通过标签密钥的更新保护了新所有者的安全隐私.该方案满足供应链的可视性需求,可以抵抗内部攻击,具有较好的通信健壮性,且通信成本较低,具有一定的可行性.     

Knowledge sharing—A key role in the downstream supply chain

We explore the role of knowledge sharing within a downstream two-echelon supply chain. Drawing on chaos theory and the literature on knowledge management, we contrasted the information and knowledge sharing contexts. More specifically, we have provided a real-world case study of knowledge management practice at a U.S. Fortune 40 firm. We reviewed the major issues in this firm's downstream supply chain operations and have described its knowledge management initiative. Finally, we discuss the implications of knowledge management on managerial practice.     

基于成本共担策略的服务供应链协调研究

研究由服务提供商和支持服务供应商组成的两级服务供应链.其中市场需求与支持服务供应商的努力水平相关,服务容量与服务提供商的努力水平相关.建立了基于成本共担策略的服务供应链模型,分析得到了供应链成员同时决策与序贯决策情况下供应链的Nash均衡解.研究表明,成本共担策略能提高供应链的总利润,实现供应链协调.通过大量算例分析了最优协调参数解与供应链中重要参数的关系,同时指出了供应链协调的效果.     

A service-oriented framework for agent-based simulations of collaborative supply chains

Current collaborative practices of supply chain management are limited to some known configurations where a dominant member sets the pace for the collaboration extent. Extending collaborative models to supply chains without a dominant member requires defining a fair assessment of costs and benefits and how they are distributed among members. To understand collaborative models and their mechanisms, simulation-based approaches are recommended as they can afford the complexity of real scenarios. However, building ad-hoc simulation models for studying complex supply chain interactions can be prohibitive in terms of both cost and time. Therefore, the availability of simulation frameworks, to be used easily by business managers and facilitating the development of those models, has a strong incentive in the quest of current business efforts to increase their supply chain performance. The objective of this work is to present a systematic and reusable serviceoriented framework for agent based simulation to support the analysis of collaborative interactions in supply chains. Results of a requirement analysis performed to this aim are described, and the fulfillment of identified requirements by the proposed framework, and capabilities thereof, are discussed.     

KMS中用户知识共享行为模型的构建

用户知识共享行为是影响知识管理系统KMS（knowledge management systems,KMS）能否取得预期运行效果的关键因素。现有的一些KMS还不具有根据用户日常的知识活动自动评估用户知识共享行为的功能,限制了KMS在知识共享文化形成中的作用。在此从行为和动作的表示入手,基于BNF的行为表示体系、知识共享行为ontology和行为树映射方法,提出了一个动态、实时、自适应、交互式用户知识共享行为模型,该模型包括基于BNF的行为和动作的表示、知识共享行为ontology、用户知识共享行为树及其动态创建过程等内容,能够实现从数量上对用户知识共享的参与度做出评价,可以作为开发实现该功能的Agent程序的一般框架。     

OpenClinical.net: A platform for creating and sharing knowledge and promoting best practice in healthcare

It is well known that medical knowledge is growing so rapidly that it is difficult or impossible for healthcare professionals to keep up. More and more techniques for diagnosing and treating diseases are becoming available, yet new research findings and clinical practices are slow to spread. Information technology and the internet are providing important new ways of disseminating knowledge in healthcare as in many other domains. Knowledge engineering techniques for supporting decision-making and process management are also becoming available, and can be used to support busy clinicians, helping to ensure that their decisions are consistent with current knowledge and clinical procedures are carried out in a timely, efficient and safe way. The OpenClinical.net project is building on these techniques to demonstrate a new paradigm for disseminating knowledge and promoting best practice. The key idea is that much professional expertise can be modelled as computer-interpretable knowledge and used to assist decision-making, workflow management, communication and coordination of care and many other professional tasks. The central goal of OpenClinical.net is to demonstrate how this might be done at scale, through a form of “crowd sourcing”, in order to create and maintain a sharable knowledge base that is available in an open access and open source repository. This paper provides an overview of the project and a summary of progress to date.     

一种支持软件知识共享的本体模型研究

为了支持分布式环境下项目团队成员之间软件开发知识有效的共享,需要对软件开发知识以及它们之间的关系进行分析和定义。根据软件开发知识的内容、特点以及它们之间的关系,对软件开发知识进行了形式化的表示,并创建了软件开发知识本体和软件开发知识本体规则。通过protégé 和Jena实现对此本体的创建、存储和对此本体规则的SPARQL形式转换,据此形成知识本体库来支持软件开发知识共享。     

Advanced quality prediction model for software architectural knowledge sharing

In the field of software architecture, a paradigm shift is occurring from describing the outcome of architecting process to describing the Architectural Knowledge (AK) created and used during architecting. Many AK models have been defined to represent domain concepts and their relationships, and they can be used for sharing and reusing AK across organizations, especially in geographically distributed contexts. However, different AK domain models can represent concepts that are different, thereby making effective AK sharing challenging. In order to understand the mapping quality from one AK model to another when more than one AK model coexists, AK sharing quality prediction based on the concept differences across AK models is necessary. Previous works in this area lack validation in the actual practice of AK sharing. In this paper, we carry out validation using four AK sharing case studies. We also improve the previous prediction models. We developed a new advanced mapping quality prediction model, this model (i) improves the prediction accuracy of the recall rate of AK sharing quality; (ii) provides a better balance between prediction effort and accuracy for AK sharing quality.     

Vertical pricing competition in supply chains: the effect of production experience and coordination

We consider a two‐echelon supply chain consisting of a single supplier (producer) and a retailer. The supplier determines the wholesale price with a production cost decreasing with experience. The retailer orders products from the supplier to meet demands. Negative effects of a vertical competition in static supply chain models are typically attributed to a double marginalization. Using an intertemporal supply chain problem, defined by a differential game, we show that in addition to the “cost” of double marginalization, the margin gained from reducing production costs affects the supply chain performance as well. In our analysis, performance is shown to deteriorate even more than the deterioration observed in static problems with no learning (experience). To improve the performance, we provide a time‐variant version to the well‐known, pure, two‐part tariff strategy, which in its dynamic framework may coordinate the supply chain only partially. Efficient coordination in a supply chain is shown to be possible if a mixed two‐part tariff strategy is employed, however.     

Assessing the value of information sharing and its impact on the performance of the various partners in supply chains

With major developments in information and communication technologies, real-time information sharing becomes a significant challenge and has a considerable impact on the overall performance of supply chains. Here, we study the influence of information sharing for a monoproduct serial supply chain consisting of a supplier, warehouse, retailer and customers in the context of a decentralized decision. The objectives of this study are twofold: (1) to estimate the gains from sharing different types of information on each elementary cost and for each partner of the supply chain in detail and (2) to determine the cumulative impact of simultaneously sharing different types of information.A mathematical model is developed to assess the value of information sharing in terms of logistic costs and for different combinations related to the sharing or non-sharing of three types of upstream and downstream information: the customer demand and the supplier-warehouse and warehouse-retailer lead times. A perturbation is also injected to consider the intended or unintended distortion in the communicated information.Our study clearly showed that the gains are not cumulative when we simultaneously share different types of information. The results also highlighted the necessity to establish incentive cooperation mechanisms between the different links in the supply chain in many scenarios where the gains are not balanced. A distortion in the communicated information can also have a significant effect on the gains from sharing.     

基于粗糙集和灰色的供应链知识共享风险预警

从分析供应链的重要组织形式—虚拟企业的知识共享风险预警的评价标准入手,提出具有层次结构的风险预警评价属性模型。然后,利用粗糙集和灰色的基本理论和方法,建立基于粗糙集和灰色理论的供应链知识共享风险预警模型框架结构图,并给出其中的基于分辨矩阵的指标属性约简算法,优化评价指标。在此基础上,使用灰色理论对知识共享的风险进行评估。最后通过实例说明该预警模型的有效性及实用性。     

Formal Ontology: Foundation of Domain Knowledge Sharing and Reusing

Domain analysis is the activity of identifying and representing the relevant information in a domain,so that the information can be shared and reused in similar systems.But until now,no efficient approaches are available for capturing and representing the results of domain analysis and then for sharing and reusing the domain knowledge.This paper proposes an ontology-oriented approach for formalizing the domain models.The architecture for the multiple-layer structure of the domain knowledge base is also discussed.And finally,some genetic algorithm-based methods have been given for supporting the knowledge sharing and reusing.     

CyberGIS-enabled decision support platform for biomass supply chain optimization

Biomass supply chain optimization aims to facilitate large-scale production of biofuels by improving the efficiency and effectiveness of biomass feedstock provision. Most existing models are not web based, limited by the accessibility for real-world applications. A CyberGIS-enabled biomass supply chain decision support platform was developed to improve model accessibility and computational performance. The platform includes four major components: BioScope optimization model, GISolve middleware, high-performance cyberinfrastructure, and an interactive web interface. The workflow and functions of each component are provided to illustrate the development and usage of the platform. Case studies and associated system performance have been evaluated to demonstrate the utility of the CyberGIS-enabled decision support platform. Through leveraging cyberinfrastructure resources and interactive web-based interface, the platform enables solving complex biomass supply chain optimization problems. The improved computational performance could provide responsive decision support for group-based applications.     

A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains

Product recovery operations in reverse supply chains face continually and rapidly changing product demand characterized by an ever increasing number of product offerings with reduced lifecycles due to both technological advancements and environmental concerns. Capacity planning is a strategic issue of increased complexity importance for the profitability of reverse supply chains due to their highly variable return flows. In this work we tackle the development of efficient capacity planning policies for remanufacturing facilities in reverse supply chains, taking into account not only economic but also environmental issues, such as the take-back obligation imposed by legislation and the “green image” effect on customer demand. The behavior of the generic system under study is analyzed through a simulation model based on the principles of the system dynamics methodology. The simulation model provides an experimental tool, which can be used to evaluate alternative long-term capacity planning policies (“what-if” analysis) using total supply chain profit as measure of policy effectiveness. Validation and numerical experimentation further illustrate the applicability of the developed methodology, while providing additional intuitively sound insights.