Showing papers on "Information sharing published in 2021"

A blockchain-based system to enhance aircraft parts traceability and trackability for inventory management

Abstract: Aircraft spare parts inventory management (ASPM) has played a critical role in tracing and tracking spare parts as any related maintenance or movement shall be recorded. Traceability and trackability of data ensure the compliance of airworthiness requirements. The International Air Transport Association (IATA) has strongly emphasised the significance of quality traceability data throughout the aircraft part’s life cycle, leading to enhanced inventory control accuracy, reduced maintenance error, and effective decision-making processes. However, with the rapid increase of spare parts types, the complexity of aircraft parts multi-stage supply chains leads to inefficient tracing and tracking operations with unsatisfactory traceability data quality and information security. This paper proposed a blockchain-based system that provided a managerial platform for accurate recording of spare parts traceability data with organisational consensus and validation using Hyperledger Fabric and Hyperledger Composer. A data model has been determined based on the existing ASPM, enabling information integrity during transaction operations. The channel mechanism has yielded a trustful data sharing platform between each contracting organisation for logistics and operational arrangements, which has enhanced information visibility and security. The blockchain-based system, executed under a decentralised ledger mechanism, shall improve the quality of traceability data and reliable information sharing within the spare parts supply chain. The enhanced blockchain-based inventory management system can establish the digital twin of aviation as part of Industry 4.0 in the future.

Potentials of blockchain technologies for supply chain collaboration: a conceptual framework

Abstract: The purpose of this study is to investigate the potentials of blockchain technologies (BC) for supply chain collaboration (SCC).,Building on a narrative literature review and analysis of seminal SCC research, BC characteristics are integrated into a conceptual framework consisting of seven key dimensions: information sharing, resource sharing, decision synchronization, goal congruence, incentive alignment, collaborative communication and joint knowledge creation. The relevance of each category is briefly assessed.,BC technologies can impact collaboration between transaction partners in modern supply chains (SCs) by streamlining information sharing processes, by supporting decision and reward models and by strengthening communicative relationships with SC partners. BC promises important future capabilities in SCs by facilitating auditability, improving accountability, enhancing data and information transparency and improving trust in B2B relationships. The technology also promises to strengthen collaboration and to overcome vulnerabilities related to moral hazard and shortcomings found in legacy technologies.,The paper is mainly focused on the potentials of BC technologies on SCC as envisioned in the current academic literature. Hence, there is a need to validate the theoretical inferences with other approaches such as expert interviews and empirical tests. This study is of use to practitioners and decision-makers seeking to engage in BC-collaborative SC models.,The value of this paper lies in its call for an increased focus on the possibilities of BC technologies to support SCC. This study also contributes to the literature by filling the knowledge gap of how BC potentially impacts SC management.

Information Sharing in an Online Marketplace with Co-opetitive Sellers

Abstract: In recent years, the rapid development of online marketplaces has given rise not only to co-opetitive relationships between sellers but also to information asymmetries between online marketplaces and sellers. This paper studies information sharing in an e-commerce setting consisting of an online marketplace, an upstream manufacturer and a reseller, where the online marketplace possesses superior demand information, while the manufacturer and reseller engage in a co-opetitive structure. The reseller procures products from the manufacturer under a wholesale price contract, and both the manufacturer and reseller sell the products through the online marketplace by paying a proportional commission fee. We examine four information-sharing scenarios: no information sharing (S1), full information sharing (S2), information sharing only with the manufacturer (S3) and information sharing only with the reseller (S4). Our analysis shows that when the intensity of competition between the manufacturer and reseller is relatively low and demand variability is moderate, the online marketplace prefers full information sharing; otherwise, it prefers to share its demand information only with the manufacturer. Moreover, interestingly, we find that the manufacturer always prefers the scenario with full information sharing to the scenario that endows her with an informational advantage over the reseller. In contrast, depending on the competitive intensity and demand variability, the reseller prefers either the scenario in which the online marketplace shares demand information with him only or that in which demand information is shared with the manufacturer only. Furthermore, we find that the equilibrium information-sharing outcome can be either full information sharing or information sharing only with the manufacturer. The rationale behind these results hinges on the interactions among the signaling cost, efficiency effect, and co-opetitive relationship between the manufacturer and reseller.

The impact of information sharing on supply chain learning and flexibility performance

Abstract: Despite the importance of supply chain learning for competitiveness, little is known about how to enable such learning. This study empirically investigates the impact of information sharing on diff...

Method of Reaching Consensus on Probability of Food Safety Based on the Integration of Finite Credible Data on Block Chain

Abstract: The use of new technologies to empower the social co-governance of food safety is a consensus in the theoretical and practical fields of food safety governance modernization. Based on the innovative features of the block chain such as non-tampering, consensus mechanism, and a smart contract, this paper proposes a new method to facilitate the achievement of the effect of social co-governance of food safety. Firstly, it provides a profound analysis of the causes of food safety problems and the drawbacks of traditional centralized supervision, and proposes a solution with decentralized features and the design process of smart contracts to realize the chaining and integration of finite credible data in the process of food circulation; secondly, it constructs a mathematical model through finite credible data on the chain and obtains the probabilistic consensus results of food safety through rigorous derivation; Finally, the scheme, model and algorithm are effectively practiced through the experimental environment of mature block chain platform and provincial food supervision platform. The example shows that the market failure problem in food safety can be greatly alleviated by the non-tampering feature of block chain; the consensus results formed by the credible data uploading, model construction and data derivation through smart contracts can greatly alleviate the problem of involution of government administrative supervision; and the social co-governance capacity of food safety can be improved through information sharing with the active synergy of multiple subjects of co-governance.

A Privacy-Preserving Distributed Contextual Federated Online Learning Framework with Big Data Support in Social Recommender Systems

Abstract: Nowadays, the booming demand of big data analytics and the constraints of computational ability and network bandwidth have made it difficult for a stand-alone agent/service provider to provide suitable information for every user from the large volume online data within the limited time. To handle this challenge, a recommender system (RS) can call in a group of agents to collaborate to learn users’ preference and taste, which is known as a distributed recommender system (DRS). DRSs can improve the accuracy of a traditional RS by requesting agents to share information with each other. However, it is challenging for DRSs to make personalized recommendations for each user due to the large amount of candidates. In addition, information sharing among agents raises a privacy concern. Thus, we propose a privacy-preserving DRS in this paper, and then model each service provider as a distributed online learner with context-awareness. Service providers collaborate to make personalized recommendations by learning users’ preferences according to the user context and users’ history behaviors. We adopt the federated learning framework to help train a high quality privacy- preserving centralized model over a large number of distributed agents which is probably unreliable with relatively slow network connections. To handle big data scenario, we build an item-cluster tree to deal with online and increasing datasets from top to the bottom . We further consider the structure of social network and present an efficient algorithm to avoid more performance loss adaptively. Theoretical proofs show that our proposed algorithm can achieve sublinear regret and differential privacy protection simultaneously for service providers and users. Numerical results confirm that our novel framework can handle increasing big datasets and strike a trade-off between privacy-preserving level and the prediction accuracy.

Blockchain-driven supply chain decentralized operations – information sharing perspective

Abstract: Information sharing helps improve the efficiency of the supply chain. However, there are some problems in the multi-stage structure supply chain, such as untimely information feedback and distortion. Despite recent progress in ensuring improved collaboration in the past decade or so, the inefficiency status continues to persist. It is also difficult to add value to the supply chain. The information sharing framework and decentralized model designed in this paper are to deal with existing problems.,This paper is based on the theoretical research of supply chain information asymmetry and synergetics. We attempt to introduce blockchain technology into supply chain operation management, reconstruct information sharing architecture and provide a new decentralized mode to promote the collaborative operation of all nodes. The information sharing and decentralization operational model are built, which has changed the hierarchical relationship between upstream and downstream enterprises, regarding customers as the center of the whole system and effectively reducing the bullwhip effect. Finally, we selected the home supply chain as an example design and performed system dynamics simulation on the blockchain-based operation process.,The model of setting up the scene application mode based on blockchain is helpful to realize the goal of supply chain management to reduce cost, improve quality and enhance the overall efficiency of the system.,Based on the blockchain technology, this paper constructed a new supply chain operation mode and used the synergetic theory and the concept of the product–service system to explain the process of value increment in detail.

Blockchain and Its Impacts on Agri-Food Supply Chain Network Management

Abstract: Blockchain is an emerging meta-technology and considered a new institutional technology with the potential to change the governance of vertically integrated food supply chains. This paper investigates the effects on coordination mechanisms in vertically cooperating agri-food networks that result from the implementation of different blockchain technology platform types (BCTPT). The research is based on an extensive literature overview and exploratory use cases of BCTPT implementations in the agri-food industry which are presented to illustrate the applicability of the findings. Our analysis shows that BCTPT predominantly differentiate through the coordination mechanisms exerting of power, information sharing, decision-making, and collective learning benefits. We also reveal that blockchain use cases with high success rates typically operate in a vertical ecosystem where a focal firm assumes the responsibility for coordinating the activities in the supply chain network. These use cases are typically operationalized in tracking and tracing applications as well as in provenance-based information provision, which either operate in vertically coordinated private blockchain or consortium-type blockchain platforms. We conclude that the choice of a specific BCTPT with its respective coordination mechanisms is a key determinant of the economic success of the intended use case, the efficient management of the supply chain network, and eventually for the chosen digital business model. This paper will close a research gap, as the potential impacts of different blockchain technology platform types on digital agri-food business models and its supply chain management have scarcely been researched.

How to leverage manufacturing digitalization for green process innovation: an information processing perspective

Abstract: The aim of this study was to examine how manufacturing digitalization can be leveraged to promote green innovation in the digital era by investigating the effects of manufacturing digitalization on green process innovation, and thus firm performance. The authors also explored how the role of manufacturing digitalization varies with horizontal information sharing, vertical bottom-up learning and technological modularization.,Five hypotheses were examined by performing regression analyses on survey data from 334 manufacturing firms in China.,Manufacturing digitalization positively affects green process innovation, and thus firm performance. Furthermore, this positive effect is strengthened by horizontal information sharing and technological modularization and weakened by vertical bottom-up learning.,This study extends the literature rooted in the natural-resource-based view by identifying the crucial role of green process innovation and investigating the value of manufacturing digitalization for developing green capabilities in the digital era. It also contributes to this line of research by revealing contingent factors to leverage manufacturing digitalization from the information processing perspective. Furthermore, this study extends information processing theory to the digital context and identifies the interaction of organizational design (vertical bottom-up learning and horizontal information sharing) and digital investment (manufacturing digitalization).

Blockchain adoption for information sharing: risk decision-making in spacecraft supply chain

Abstract: This research studies the risk decision-making (RDM) problem faced by participants in a spacecraft supply chain, considering the adoption of the blockchain technology to facilitate information shar...

Source Trust and COVID-19 Information Sharing: The Mediating Roles of Emotions and Beliefs About Sharing.

Abstract: Health information sharing has become especially important during the COVID-19 (coronavirus disease 2019) pandemic because people need to learn about the disease and then act accordingly. This study examines the perceived trust of different COVID-19 information sources (health professionals, academic institutions, government agencies, news media, social media, family, and friends) and sharing of COVID-19 information in China. Specifically, it investigates how beliefs about sharing and emotions mediate the effects of perceived source trust on source-specific information sharing intentions. Results suggest that health professionals, academic institutions, and government agencies are trusted sources of information and that people share information from these sources because they think doing so will increase disease awareness and promote disease prevention. People may also choose to share COVID-19 information from news media, social media, and family as they cope with anxiety, anger, and fear. Taken together, a better understanding of the distinct psychological mechanisms underlying health information sharing from different sources can help contribute to more effective sharing of information about COVID-19 prevention and to manage negative emotion contagion during the pandemic.

Platform Information Transparency and Effects on Third-Party Suppliers and Offline Retailers

Abstract: We examine a model in which a supplier sells products through an online platform and an offline retailer under conditions of demand uncertainty. The actual demand potential can be observed (or predicted accurately using rich sales data) by the platform and retailer, but not by the supplier. The model addresses the following issues. First, the supplier optimizes its multi‐channel strategy, including a selling format choice in the online channel and optimal pricing. Specifically, although a traditional wholesale model is used offline, both wholesale and agency models are prepared online. Given a commission rate set by the platform for the agency model, the supplier chooses one selling format from the two models. The second one is related to the platform's information‐sharing policy. The platform can commit to sharing its demand information with the supplier. This study elucidates how the platform's information sharing alters the supplier's multi‐channel management and subsequently affects the retailer eventually. Results show that the platform charges its commission rate so that the supplier chooses the agency model, unless the consumer demand is sufficiently uncertain. We also demonstrate that the platform's information sharing capability makes the agency model more likely to be adopted. However, information transparency arising from the platform's voluntary information disclosure can be unfavorable to the retailer. Finally, we demonstrate that, with information sharing, a shift from wholesale to agency models can be desirable not only for the platform and supplier, but also for the retailer (i.e., Pareto‐improving).

Information sharing strategies in a hybrid-format online retailing supply chain

Abstract: This paper considers a hybrid-format online retailing supply chain in which a manufacturer sells products to an online retailer and an intermediary with a wholesale contract, the retailer sells the...

Quality of e-commerce agricultural products and the safety of the ecological environment of the origin based on 5G Internet of Things technology

Abstract: The quality and safety of agricultural products is not only related to the consumption and health of residents, but also related to the sustainable development of agriculture. It is one of the hot spots for the government and residents. In addition to the rapid development of e-commerce and the continuous improvement of consumption levels of urban and rural populations, the quality and safety of agricultural products pose new risks and new hidden dangers. The purpose of this paper is to study the quality and safety of e-commerce agricultural products based on 5G Internet of Things technology. This paper mainly studies and uses the key technologies of 5G Internet of Things to build a circulation information system for agricultural products based on 5G Internet of Things, so as to realize the real-time positioning, information sharing and security of circulation in the supply chain of agricultural products. Experiments show that 5g Internet of things can not only provide agricultural producers, sellers and ordinary users with more efficient, convenient and accurate quality and safety information of agricultural products, but also improve the efficiency of agricultural products circulation and effectively reduce the cost of agricultural products circulation. In this paper, the RFID technology of 5G Internet of Things is used. The experimental result is that the revenue growth rate of the e-commerce business is 30%. We can see that the increase in e-commerce business revenue is due to the 5G Internet of Things improving the quality of e-commerce produce to some extent.

Effect of information sharing in supply chains: understanding the roles of supply chain visibility, agility, collaboration on supply chain performance

Abstract: Exploring ways to acquire, sustain and improve competitive positions in supply chains through information sharing, supply chain visibility, collaboration and agility have been essential for scholars and practitioners. Basing on the relational view, resource based view and the extended resource based view, this study assesses the critical role of information sharing in supply chains through emphasizing its effect on supply chain visibility, collaboration, agility and supply chain performance. Particularly, the study proposes that information sharing, supply chain visibility, collaboration and agility collectively have crucial direct and indirect influences on supply chain performance which lead to superior gains, competitiveness and flexibility.,The study adopted a survey research design, a quantitative approach and partial least square structural equation modeling (PLS-SEM) in making data analysis and interpretations due to its suitability for predictive research models.,The results indicate information sharing positively and significantly influenced supply chain visibility, collaboration, agility and performance. Supply chain visibility presented significant effects on collaboration, agility and performance, while supply chain collaboration and agility had significant impact on supply chain performance. The study findings connote that information sharing is key to enhancing competitive gains and superior supply chain performance.,The study is among the few to probe on how information sharing as a variable interacts with supply chain visibility, collaboration, agility and performance. Although, information sharing has received a lot of attention in supply chains, this study is among the first to capture the study variables in a single model and thus, exposes the vital need for information sharing in improving supply chain performance seeing that it ensured significant and robust impacts on the study variables.

Applications of Differential Privacy in Social Network Analysis: A Survey

Abstract: Differential privacy provides strong privacy preservation guarantee in information sharing. As social network analysis has been enjoying many applications, it opens a new arena for applications of differential privacy. This article presents a comprehensive survey connecting the basic principles of differential privacy and applications in social network analysis. We concisely review the foundations of differential privacy and the major variants. Then, we discuss how differential privacy is applied to social network analysis, including privacy attacks in social networks, models of differential privacy in social network analysis, and a series of popular tasks, such as analyzing degree distribution, counting subgraphs and assigning weights to edges. We also discuss a series of challenges for future work.

Big data use and its outcomes in supply chain context: the roles of information sharing and technological innovation

Abstract: This paper aims to investigate the use of big data (BDU) in predicting technological innovation, supply chain and SMEs' performance and whether technological innovation mediates the association between BDU and firm performance. Additionally, this research also seeks to explore the moderating effect of information sharing in the association between BDU and technological innovation.,Using survey methods and structural associations in AMOS 24.0., the proposed model was tested on SME managers recruited from the largest economic and manufacturing hub of China, Pearl River Delta.,The findings suggest that BDU is positively related to technological innovation (product and process) and organizational outcomes (e.g., supply chain and SMEs performance). Technological innovation (i.e., product and process) significantly mediates the association between BDU and organizational outcomes. Moreover, information sharing positively moderates the association between BDU and technological innovations.,This research provides deeper insights into how BDU is useful for SME managers in achieving the firm’s goals. Particularly, SME managers can bring technological innovation into their business processes, overcome the challenges of forecasting, and generate dynamic capabilities for attaining the best SMEs’ performance. Additionally, BDU with information sharing enables SMEs reduce their risk and decrease production costs in their manufacturing process.,Firms always need to adopt new ways to enhance their productivity using available resources. This is the first study that contributes to big data and performance management literature by exploring the moderating and mediation mechanism of information sharing and technological innovation respectively using RBVT. The study and research model enhances our insights on BDU, information sharing, and technological innovation as valuable resources for organizations to improve supply chain performance, which subsequently increases SME productivity. This gap was overlooked by previous researchers in the domain of big data.

Integrating BLE Beacon Technology with Intelligent Information Systems IIS for Operations’ Performance: A Managerial Perspective

Abstract: Hyper competition in the digital era adds more challenges and complexity to value creation in business operations. Running the operations’ transactions in real-time probably will decrease the transactions’ lead-time, increase the transactions’ accuracy and lower the cost. The BLE Beacon technology provides a noticeable chance for enhancing operations’ performance. It uses advanced Bluetooth capabilities to provide source automation features that improve information sharing ability among users. As a new generation of Information Systems, Intelligent Information Systems use artificial intelligence agents to simulate real-time transactions. When we integrate the BLE Beacon Technology with IIS, we provide IIS with required information in real-time and intelligence agents’ auto-communication capability. In this paper, BLE Beacon Technology with Intelligent Information Systems structure is proposed to enhance the retail industry’s operations’ performance.

Social media affordances and information abundance: Enabling fake news sharing during the COVID-19 health crisis.

Abstract: This study modelled factors that predict fake news sharing during the COVID-19 health crisis using the perspective of the affordance and cognitive load theory. Data were drawn from 385 social media users in Nigeria, and Partial Least Squares (PLS) was used to analyse the data. We found that news-find-me perception, information overload, trust in online information, status seeking, self-expression and information sharing predicted fake news sharing related to COVID-19 pandemic among social media users in Nigeria. Greater effects of news-find-me perception and information overload were found on fake news sharing behaviour as compared to trust in online information, status seeking, self-expression and information sharing. Theoretically, our study enriches the current literature by focusing on the affordances of social media and the abundance of online information in predicting fake news sharing behaviour among social media users, especially in Nigeria. Practically, we suggest intervention strategies which nudge people to be sceptical of the information they come across on social media.

Green supply chain integration and financial performance: A social contagion and information sharing perspective

Abstract: Although green supply chain integration (GSCI) has received wide attention, how it diffuses among supply chain members to affect the manufacturer's performance is still unclear This study examines the relationships among GSCI, information sharing, and financial performance from a social contagion lens By conceptualizing GSCI into three forms, two types of contagion mechanisms (ie, cohesion and structural equivalence) were identified to investigate the underlying contagion effects between different forms of GSCI and the effects of various GSCI on information sharing and financial performance Survey data were collected from 206 Chinese manufacturers and analyzed using structural equation modeling to test hypotheses The results indicate that green supplier integration directly promotes green internal integration, green customer integration, and information sharing with suppliers Green internal integration positively influences green customer integration and financial performance Green customer integration enhances information sharing with customers Both information sharing with suppliers and customers improve financial performance This study contributes to the GSCI literature and provides novel managerial implications for manufacturers

Health Information Consumption under COVID-19 Lockdown: An Interview Study of Residents of Hubei Province, China.

Abstract: Emerging infectious disease (EID) outbreaks such as the ongoing COVID-19 pandemic create unknown risks, uncertainty, and anxiety around the world. Accurate and timely information can help the public understand the outbreak and manage their lives. Presented here is a study of how residents of Hubei Province, the epicenter of the COVID-19 outbreak in China, use media for information seeking, scanning, and sharing while under lockdown through in-depth interviews. We find that (1) individuals primarily acquire information through information scanning from official governmental sources, (2) information sharing is more frequent with family members through private channels than with one's extended social networks and the general public through pubic channels mostly due to concerns with censorship, and (3) individuals' information need and information use change substantially during different stages of the outbreak. These findings provide insights into how individuals in China use different media for information during an unprecedented public health crisis and make sense of the limited and often confusing and contradictory information that is available to them. Such findings can inform future health communication efforts during EID outbreaks.

Edge computing-based joint client selection and networking scheme for federated learning in vehicular IoT

Abstract: In order to support advanced vehicular Internet-of-Things (IoT) applications, information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments. Federated learning (FL), which is a type of distributed learning technology, has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy. However, client selection and networking scheme for enabling FL in dynamic vehicular environments, which determines the communication delay between FL clients and the central server that aggregates the models received from the clients, is still under-explored. In this paper, we propose an edge computing-based joint client selection and networking scheme for vehicular IoT. The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach, and uses the edge vehicles as FL clients to conduct the training of local models, which learns optimal behaviors based on the interaction with environments. The clients also work as forwarder nodes in information sharing among network entities. The client selection takes into account the vehicle velocity, vehicle distribution, and the wireless link connectivity between vehicles using a fuzzy logic algorithm, resulting in an efficient learning and networking architecture. We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

Blockchain-based secure information sharing for supply chain management: Optimization assisted data sanitization process

Abstract: Currently, the furious competitiveness in global markets and speedy improvements in information technology lead to shorter product life cycles, lesser transportation capabilities, and increased demands as well. In most business scenarios, the supply chain network is becoming one of the most vital focusing areas. In the supply chain network, blockchain technology is a promising solution for secure information sharing. However, it is a bit critical in maintaining security at each level of the blockchain and hence the public–private–key cryptography is more commonly preferred. This study intends to construct a new privacy preservation model in the field of supply chain networks based on blockchain technology by undergoing three major phases, namely, (a) data sanitization, (b) key generation, and (c) restoration. Further, the sensitive fields in the original data are selected during the data sanitization phase, and in the key generation phase; the optimal key is generated to hide the selected sensitive fields. The hidden data with the secured key is transferred from the source (manufacturer) to destination (vendor) in the supply chain network via the blockchain. The restoration process takes place in the receiver side with the help of the same key. Among all these data flow methods, the optimal key selection is the critical issue that needs to be overridden to make the data transmission secured. As a novelty, a new optimization algorithm referred to as Whale with New Crosspoint‐based Update (WNU), which is the advanced version of Whale Optimization Algorithm (WOA), is developed here to select the optimal key. Finally, the proposed WNU model is analyzed in terms of Hiding Failure (HF) rate, Information Preservation (IP) Rate, and False Rule generation (FR), and Degree of Modification (DM). The proposed secured information sharing in supply chain management (SCM) with blockchain technology will be validated by comparing it over the traditional models in terms of security as well.