Information Sharing Model Research Articles

A community-centric model for conference co-creation: the world conference on CDG for patients, families and professionals

BackgroundPatient and public co-creation and involvement in health initiatives have been witnessing great expansion in recent years. From healthcare to research settings, collaborative approaches are becoming increasingly prevalent and diverse, especially in the field of rare diseases which faces complex challenges. Conference development and implementation, however, have been primarily guided by passive, information-sharing models. There is a need for conferences to evolve towards more inclusive, interactive, collaborative, and problem-solving platforms. Here, we aimed to report on a pioneer model, emphasizing a community partnership approach to conference co-creation that takes the World Conference on Congenital Glycosylation Disorders (CDG) as an exemplary case.MethodsTo answer the need to overcome the lack of access to high-quality information which limits CDG diagnosis, research and treatment options, the World CDG Organization has been refining a community-centric model for conference co-creation. Focusing on the 5th edition of the conference, data on stakeholders’ preferences was collected using an online survey and a poll to define the conference agenda, guide its development and select optimal dates for an all-stakeholder inclusive, relevant and participatory event.ResultsWe describe the complexities of the community-centric conference co-creation model, detailing its refined methodology and the outcomes achieved. The model is grounded on a participative approach to promote people-centered research and care for CDG patients. The involvement of the public in the conference co-creation and in participatory methods allowed the generation of knowledge on community needs and preferences.ConclusionThis paper describes a reliable, highly adaptable conference co-creation model that fosters community-building, disseminates understandable information, and serves as a borderless platform to incentivize multiple stakeholder collaborations towards CDG research and drug development. We argue this is a reproducible model that can be endorsed and more widely adopted by other disease communities and events.

Price discovery and volatility spillovers in the interest rate derivatives market

The interest rate derivatives market is an important force in promoting the development of the bond market and is an effective tool to manage interest rate risk. The research on price discovery and volatility spillover of the market can help provide valuable reference information for investors. Based on treasury bond futures and interest rate swaps, the paper aims to discuss the price discovery function and spillover structure of the interest rate derivatives market. The paper establishes the information share model and spillover index model for empirical analysis. The results show that: First, the calculation results of the information share model show that the price discovery of treasury bond futures and interest rate swap markets is stronger than that of the spot market. Second, based on structural break analysis, treasury bond futures and interest rate swaps do not have breakpoints, while the treasury bond spot has three breakpoints. The paper divides the entire sample into four stages based on structural breakpoints and finds that the price discovery ability of the interest rate derivative market dynamically changed. Third, as a net spillover in the market, treasury bond futures have developed relatively stable. Both treasury bond futures and interest rate swaps have spillover effects on the spot market, indicating that China’s interest rate derivatives market can impact the treasury bond spot market.

Examining Sustainable Overseas Investment Information-Sharing Model for Automobile Enterprises: A Multi-Modal Weight Network Approach

AbstractIn an era of globalization, automotive companies are increasingly looking to make overseas investments to expand their production capacity and explore foreign markets. However, the outcomes of such investments are often influenced by a myriad of factors, including policy changes, social dynamics, and market conditions. To address the need for a comprehensive overseas investment information-sharing model, this research proposes an innovative approach based on a multi-modal weight network. This model aims to provide users with a global perspective on overseas investment opportunities, encompassing policy insights, and market dynamics. It integrates data from various sources, offering multi-dimensional information on investment regions, scales, fields, motivations, and strategies. Real-time updates ensure the timeliness and accuracy of the information, enabling users to adapt to the rapidly changing international economic landscape. Challenges such as data collection, privacy concerns, investment diversity, advanced analytics, and real-time updates are carefully considered and addressed. The model incorporates sophisticated analytical methods to extract valuable insights from vast data, guiding sound decision-making for automotive enterprises. Experimental results demonstrate an impressive accuracy rate of 87.9% and an mAP value of 86.8%, highlighting the model’s effectiveness in providing precise and reliable investment information. This innovative multi-modal weight network model empowers automotive companies to navigate the complexities of international investments, enabling them to make informed decisions and achieve success in the global market.

The construction of a shared resource base of enterprise financial informationization for intelligent terminal platform

Abstract This paper uses an adaptive load-balancing algorithm to calculate an intelligent terminal platform on the basis of an enterprise financial information-sharing model. Firstly, a new server performance evaluation index is established based on the hierarchical analysis method, and the load performance of each node is reacted using the influence factors. Then a judgment matrix is constructed for the set of evaluation factors based on the change in the average load utilization rate of nodes. Finally, the results of the matrix are normalized to derive the evaluation weights of each node of the server, which completes the construction of the intelligent terminal platform. An enterprise’s quarterly bills for 2018-2020 were selected for analysis, and after running the financial information sharing, the processing time of a single voucher could be saved by 0.3 hours. It shows that the constructed information-sharing resource base can not only significantly reduce operation costs but also access the business data of subsidiaries at any time to effectively prevent operation risks.

Hyperconnected Logistic Platform for Heavy-Duty Machinery: Leveraging Physical Internet Principles to Drive the Composting Industry

The Physical Internet (PI) envisions a global logistics system that integrates physical, digital and operational connections. This study aims to develop a hyperconnected logistic platform for heavy-duty machinery (HDM) in the composting industry by utilizing a systematic methodology. The proposed architecture consists of four layers: the Domain Model, the MBSE Model, the Information Sharing Model and the Agent-based Simulation Platform. The Domain Model analyzes the current situation and investigates stakeholder viewpoints, and the MBSE Model reduces complexity and describes mutual interactions between requirements and needs. The Information Sharing Model focuses on the information exchange among the main components, and the Agent-based Simulation Platform implements the proposed platform. The feasibility of the proposed architecture is demonstrated through a use case in Styria, Austria. Three simulation-based scenarios are analyzed, starting from the semi-hyperconnected approach up to the hyperconnected approach with PI vision integration. The results indicate that the hyperconnected platform is successful in serving all composting facilities, leveraging underutilized resources and promoting high-quality compost production. Thus, the platform provides support in a local, communal setting, resulting in enhancing the circular economy within the composting sector. Our efforts aim to contribute to the realization of the Physical Internet vision and promote composting to ultimately achieve a more sustainable future.

Research on Evolutionary Game and Simulation of Information Sharing in Prefabricated Building Supply Chain

Enterprises in the prefabricated building supply chain (PBSC) only share information according to their interests, which is bound to cause conflicts of interest and reduce the efficiency of supply chain operations. To promote information sharing (IS) in PBSC, it is necessary to construct an evolutionary game model that fits the realistic network. In this paper, based on the integration of existing research, 13 influencing factors of IS in PBSC are analyzed comprehensively from the perspective of information ecology theory. In addition, due to the complexity and uncertainty of the PBSC, enterprise interaction and supply chain network structure affect the IS decision. Therefore, this paper builds an evolutionary game model of IS in PBSC under a scale-free network, and conducts numerical simulation analysis with MATLAB 2017 software to analyze the evolution law of enterprise IS under different situations. The results show that (1) when the network scale is large, the density of information sharers generally increases, and the speed of network evolution to a steady state generally slows down; (2) eight factors can promote the increase in information sharers’ density, and five factors can inhibit it, but factors have no significant effect on the speed of network evolution to reach the steady state. Based on the simulation results, this paper proposes countermeasures and suggestions such as strengthening the support of the policy environment and social environment, setting up the demonstration benchmark of leading construction enterprises, establishing a directional information resource database, and improving information technologies and risk management systems to provide the scientific basis for government supervision and enterprise decision making.

Hyperledger Fabric-based Reliable Personal Health Information Sharing Model

To provide optimized individual-oriented medical service, an open eco system is required so that personal health information could be safely recorded, managed, shared and viewed. However, the current health information is being separately collected, stored, managed by various management institutions, so data linkage is not guaranteed. The data ownership for personal health information belongs to management entities not an individual and also health information is electronically recorded and managed, so it’s vulnerable to forgery and leakage like other electronic data. This paper proposes a personal health information sharing platform applying the Hyperledger fabric. The proposed platform was designed based on blockchain to provide user-oriented health information management and access rights. Therefore, it is possible to create, manage and share reliable medical data.

On the impact of information-sharing model between subpopulations in the Island-based evolutionary algorithms: search manager framework as a case study

On the impact of information-sharing model between subpopulations in the Island-based evolutionary algorithms: search manager framework as a case study

Optimized Demand Information Sharing Model of Dual-Channel Supply Chain in E-Commerce

In the dual-channel supply chain, the relationship between the electronic direct selling channel and the traditional selling channel is situated in an antagonistic game. The present study used the master-slave game model to analyze the dual-channel supply chain structure, where the manufacturer is the leader of the game, and the seller is the follower of the game. Based on the game analysis theory, the game order of manufacturer and seller is analyzed in the state of demand information sharing. The decision model of each member in the dual-channel supply chain is constructed, and the optimal production decision and product price decision under the demand information sharing between the seller and the manufacturer are determined by the reverse induction method. The expected economic benefits of both are calculated, respectively. The experimental results showed that the economic benefit of the model is higher than that of the traditional demand information nonsharing model, which could enhance the economic benefit of the manufacturer and the seller at the same time and alleviate the contradiction between the electronic direct selling channel and the traditional selling channel.

To Share or Not to Share? The Role of Retailer's Information Sharing in a Closed-Loop Supply Chain.

Retailers are faced with a dilemma of whether to share demand information with other supply chain members, and if so, how to share it. Our research interest is motivated by the grounds that the value of downstream retailers’ sales information to upstream manufacturers is to improve the accuracy of manufacturers’ order forecasting. This problem is particularly important in the remanufacturing of closed-loop supply chains (CLSCs). In this study, we consider a retailer (she) as the demand information holder, who sells new and remanufactured products in wholesale to a manufacturer (he) and, simultaneously, she and the manufacturer competitively collect used products from the customers. We explicitly characterize the role of information sharing in a CLSC. We contributed to the information-sharing literature by integrating the existing information-sharing model with dual recycling channels and channel power structure. Previous literature suggests that retailers prefer to share demand information with other firms when the market demand is high. However, surprisingly, we find that when the manufacturer does not play a leading role, the retailer shares her forecast demand information with the manufacturer if the market demand is low. We also show that information sharing reduces the overall profit of the supply chain when the manufacturer dominates the market. In addition, our results also illustrate that information sharing affects the performance of the supply chain mainly by affecting the wholesale price.

Non-Existence of Stable Social Groups in Information-Driven Networks

We study a group-formation game on an undirected complete graph G with all edge-weights in a set $\mathcal { W} \subseteq \mathbb {R} \cup \{-\infty \}$ . This work is motivated by a recent information-sharing model for social networks (Kleinberg and Ligett, Games Econ. Behav. 82, 702–716 2013). Specifically, we consider partitions of the vertex-set of G into groups. The individual utility of any vertex v is the sum of the weights on the edges uv between v and the other vertices u in her group. – Informally, u and v represent social users, and the weight of uv quantifies the extent to which u and v (dis)agree on some fixed topic. – For a fixed integer k ≥ 1, a k-stable partition is a partition in which no coalition of at most k vertices would increase their respective utilities by leaving their groups to join or create another common group. Before our work, it was known that such a partition always exists if k = 1 (Burani and Zwicker, Math. Soc. Sci. 45(1), 27–52 2003). We focus on the regime k ≥ 2. Our work hints that the emergence of stable communities in a social network requires a trade-off between the level of collusion between social users, and the diversity of their opinions.

Differential Game Model of Information Sharing among Supply Chain Finance Based on Blockchain Technology

In the development of traditional supply-chain finance, the information asymmetry of all parties in the supply chain has become the primary problem hindering its development. Blockchain technology is an effective method to solve the problem of information silos. Based on differential game theory, this paper constructs a game model of supply-chain financial information-sharing behavior based on blockchain technology. Three scenarios of independent decision, the cost-subsidy mechanism of financial institutions, and dealers and collaborative decisions are studied, and the theoretical model is verified through a simulation algorithm. The results show that information sharing in supply-chain finance based on blockchain technology is much higher than that of traditional supply-chain finance, and the use of blockchain technology can promote more sustainable development of supply chains. Blockchain technology can effectively solve the information-silo effect, and the information sharing cost-subsidy mechanism can effectively relieve the cost pressure of information sharing and optimize the supply-chain structure. In addition, the amount of information and benefits shared among the three parties of supply-chain finance based on blockchain technology and the overall benefits show an increasing and stabilized trend over time. This study provides a reference for supply-chain finance members to reasonably choose the optimal strategic behavior.

Research on Semantic Model of Information Sharing Based on Cognition

In view of the current demand of heterogeneous, cross domain, many service platforms, wide distribution and low-cost resource sharing platform construction of agricultural public welfare information service resources, this paper puts forward a set of standardized and orderly data acquisition and interpretation sharing methods. Methods combined with the characteristics of multi domain resource sharing, metadata semantic modeling based on cognition is proposed to establish the mapping between metadata cognition and metadata semantics to resource description model, build a basic framework of resource sharing, extract the minimum core metadata required for resource sharing, define the basic rules for the existence of resource sharing data, and give the resource sharing description model. At the same time, in order to clearly explain the semantic annotation information in the model, the construction method of shared resource semantics is introduced. In order to reduce the difficulty of resource description, sharing and publishing on heterogeneous platforms, a shared resource description tool based on "resource sharing semantic description model" is introduced. This method combines the advantages of existing methods. At the same time, through the production of description tools and the introduction of semantics, the development difficulty and development volume of each service platform are reduced, the development cost is saved, the data sharing efficiency is improved, and the requirements of low-cost, cross domain, light dependence, resource readability and machine solvability for the construction of agricultural public welfare information service resource sharing platform are better solved.

Blockchain‐Based Contact Tracing and Information Sharing Model for COVID‐19 Pandemic

COVID‐19 is the worst contagious disaster in the history of humankind, triggering a worldwide sickness pandemic. In lacking specialized treatments or immunizations, finding and eliminating the infection source is the best option to decrease disease transmission and lower sickness and degree of fatality among the general public. Generally, few significant barriers are present in the existing system of monitoring the contamination. One of the obstacles is regarding health‐related data storage. The user’s e‐health data is kept in a traditional method that might have been compromised if shared with third parties. Secondly, the current disease tracking technologies fail to monitor diseases numerous ways. The tracing system is either personal or location‐based. Apart from these, gathering individual consent and sharing their health data with unknown associations is a real‐time problem. We propose a blockchain‐based data system that maintains confidentiality with transparency. Users can acquire unlimited and nontampered vital routes as the suggested blockchain solution leverages to link the user/patient and approved solvers. Also, automatically executed smart contracts are constructed to desensitize the user ID and reallocation. The anonymous feature delivered by private blockchain with wireless technologies defends the customer’s identity secrecy. We develop a matching approach using machine learning technology. Users may take safeguards in advance by employing our suggested analytical technique for predicting the risk due to infectious source presence.

Study of the Game Model of E-Commerce Information Sharing in an Agricultural Product Supply Chain based on fuzzy big data and LSGDM

Information asymmetry is the root of agricultural product quality problems. Generally speaking, the common problems related to agricultural products are solved by effective supply chain management. From the perspective of agricultural supply chain management, this paper analyzes the shortcomings of the traditional supply chain management process by using fuzzy big data and LSGDM (Large scale group decision making), and puts forward a new method of supply chain management. In addition, from the perspective of asymmetric information sharing regarding agricultural products, an asymmetric information sharing model for agricultural products based on the evolutionary rule theory is established. Combined with fuzzy big data and LSGDM, this paper puts forward the hypothesis of each variable in the process of the information sharing game. On this basis, a mathematical model of the "pool equilibrium" of the high and low prices in the agricultural products market is put forward. Finally, a case study of products of different quality in the sea cucumber market is carried out. The results show that high quality sea cucumber products occupy a large market share in the supply chain of agricultural products. The research of this paper is of great significance, because it can increase the reliable theoretical data available for the research of the agricultural supply chain.

Estimating the Value of Destination Disclosure: A Dynamic Structural Model in a Transportation Network

Information sharing can induce supply-side selectivity in on-demand platforms such as transportation network companies (TNC) that reduce efficiency and raises equity concerns (e.g., discrimination against demand attributes). We quantitatively compare the efficiency and equity performance of TNCs under various information-sharing models associated with destination-related attributes. Specifically, we first develop and estimate a dynamic structural model of TNC drivers' valuations under a \emph{disclosure model} in which various destination-related attributes that induce drivers' dynamic consideration are revealed to drivers before their acceptance. We then leverage the model estimates to run counterfactual experiments on alternative information-sharing models, including a non-disclosure model in which those attributes are concealed before acceptance, and partial-disclosure models in which those attributes are partially revealed. From a per-period (ride) perspective, the model estimates illustrate drivers' selectivity in terms of ride attributes (e.g., trip distance), and its heterogeneity across drivers. With dynamics modeled, the simulation shows a decreasing average acceptance rate, a more dominantly increasing average per-ride utility, an increasing average cumulative utility and decreasing variance in utility of accepted rides as the information models disclose more destination-related attributes. The results substantiate that there is a clear trade-off between driver's acceptance along with the equity performance versus the utility (profit) maximization. The quantified marginal effects further uncover drivers' inter-ride, forward-looking behavior and suggest that the two partial-disclosure models are cost-effective solutions for improving equity.

A Double-Layer Combination Algorithm for Real-Time Information-Sharing Network Design Problem

The accumulation of real-time data has attracted the attention of various industries because valuable information can be extracted from the effective model and method design. This paper designs a low-carbon model and focuses on the real-time information-sharing network in order to get sustainable strategies promptly and exactly. The design problem is concerned with determining optimal integration strategies on a series of multilocation, multipath, and multiwarehouse freight provided by an information-sharing network to find an effective balance between the total costs and carbon emission. Firstly, the biobjective information-sharing network model is established to describe real-time problem with total cost and carbon emission factor. Secondly, a double-layer bacterial foraging algorithm is divided into inner and outer layers to solve the model, in which the inner section solves the transportation and inventory problems, and the outer section solves the supplier location problem. The double-layer bacterial foraging algorithm realizes the optimization of multisource e-commerce information-sharing model through nesting inside and outside layers. Finally, double-layer bacterial foraging algorithm can be confirmed to get the global optimal solution rapidly based on test data and the e-business case study of Jingdong, China.

OGBAC—A Group Based Access Control Framework for Information Sharing in Online Social Networks

Internet users receive various online social networks (OSNs) services, however, providers of OSNs do not always provide users fine-grained privacy protection mechanisms with sufficient privacy protection for shared resources. In this paper, we propose a formal Group-Based Access Control (oGBAC) framework for preventing privacy disclosure when sharing information within or among groups in OSNs. Our framework extends the group-centric Secure Information Sharing (g-SIS) models by adapting the concept of the group to OSNs. We impose some restrictions to the group and information flow among groups to ensure that operations cannot incur privacy disclosure when sharing information among friends in OSNs. In view of characteristics of OSNs and the requirements of secure information flow, the oGBAC model also incorporates some ideas from the Attribute-Based Access Control (ABAC) to develop information flow based rules using relationship among attributes (such as tags, time and security levels) of objects and subjects in OSNs. Administration related rules and access related rules are designed for each access operation of group based OSNs' information sharing. The security of oGBAC model is analyzed using formal methods. To demonstrate the usability of the oGBAC model, we implement the model with the Comparative Attribute-Based Encryption (CCP-CABE), and analyze the security and efficiency of the implemented system to prove the effectiveness of the implemented system.

The Value of Hybrid MTS/MTO Supply Chain Sharing Demand Forecasts under Big Data

Big data technology provides convenience for all entities in the supply chain to obtain demand forecasts and share the information. This article considers a supply chain composed of a manufacturer and two competitive retailers and analyzes the value of sharing demand information in the supply chain. In this supply chain, the manufacturer has a hybrid MTS/MTO production system and sells products to the MTS retailer and the MTO retailer. Both the manufacturer and the retailers have private demand information. We established a no-information sharing model, a full information-sharing model, and two partial-information sharing models, to study the value of sharing information. The results show that the full information sharing strategy cannot benefit all entities. However, if the demand forecasts of the two retailers are very different and lower than the manufacturer’s forecast, sharing information between the manufacturer and the retailer who has high demand prediction can benefit all entities.

‘The new oratory’: Public speaking practice in the digital, neoliberal age

This study discusses the paradigm shift that has occurred in public speaking practice in the first two decades of the 21st century, conceptualised under the term ‘the New Oratory’. The New Oratory is a product of the digital revolution in that it brings together formats that are typically relayed via videos uploaded to the Internet, and serves as a vector of the new, digital economy. Drawing on previous critical work linking language and discourse to what is referred to as the new economy, late or new capitalism or neoliberalism, the study focuses on two aspects of discourse practice that can be explained due to developments within the current economic climate: (1) the entrepreneurial speaker ethos that is embodied by the start-up generation of entrepreneurs, finds a resonance in Anglo communication culture and is closely linked to the neoliberal emphasis on branding; (2) the model of horizontal knowledge or information-sharing (in which the Internet has played a major role), whereby a move from specialist to non-specialist target audiences is shifting the frontiers of discourse communities and leading to their reorganisation. These two phenomena are illustrated via examples taken from two formats: the investor pitch and the three-minute-thesis presentation. The first belongs to the corporate sector, the second to academia. The study highlights the neoliberal forces at work outside the corporate sector per se which have come to influence most spheres of professional, social and personal lives, as well as the way these forces are ultimately being promoted by the emergence of a new, fairly homogeneous discursive setup.