Showing papers on "Information sharing published in 2015"

Information sharing in a supply chain with a common retailer

Abstract: We study the problem of information sharing in a supply chain with two competing manufacturers selling substitutable products through a common retailer. Our analysis shows that the retailer’s incentive to share information strongly depends on nonlinear production cost, competition intensity, and whether the retailer can offer a contract to charge a payment for the information. Without information contracting, the retailer has an incentive to share information for free when production economy is large but has no incentive to do so when there is production diseconomy. With information contracting, the retailer has an incentive to share information when either production diseconomy/economy is large or competition is intense. We characterize the conditions under which the retailer shares information with none, one, or both of the manufacturers. We also show that the retailer prefers to sell information sequentially rather than concurrently to the manufacturers, whereas the manufacturers’ preferences are rever...

Factors affecting the Adoption Level of C-Commerce: An Empirical Study

Abstract: The major objective of this paper is to examine the determinants of collaborative commerce (c-commerce) adoption with special emphasis on Electrical and Electronic organizations in Malaysia. Original research using a self-administered questionnaire was distributed to 400 Malaysian organizations. Out of the 400 questionnaires posted, 109 usable questionnaires were returned, yielding a response rate of 27.25%. Data were analysed by using correlation and multiple regression analysis.External environment, organization readiness and information sharing culture were found to be significant in affecting organizations decision to adopt c-commerce. Information sharing culture factor was found to have the strongest influence on the adoption of c-commerce, followed by organization readiness and external environment. Contrary to other technology adoption studies, this research found that innovation attributes have no significant influence on the adoption of c-commerce.In terms of theoretical contributions, this study...

Exploration of synergistic and redundant information sharing in static and dynamical Gaussian systems

Abstract: To fully characterize the information that two source variables carry about a third target variable, one must decompose the total information into redundant, unique, and synergistic components, i.e., obtain a partial information decomposition (PID). However, Shannon's theory of information does not provide formulas to fully determine these quantities. Several recent studies have begun addressing this. Some possible definitions for PID quantities have been proposed and some analyses have been carried out on systems composed of discrete variables. Here we present an in-depth analysis of PIDs on Gaussian systems, both static and dynamical. We show that, for a broad class of Gaussian systems, previously proposed PID formulas imply that (i) redundancy reduces to the minimum information provided by either source variable and hence is independent of correlation between sources, and (ii) synergy is the extra information contributed by the weaker source when the stronger source is known and can either increase or decrease with correlation between sources. We find that Gaussian systems frequently exhibit net synergy, i.e., the information carried jointly by both sources is greater than the sum of information carried by each source individually. Drawing from several explicit examples, we discuss the implications of these findings for measures of information transfer and information-based measures of complexity, both generally and within a neuroscience setting. Importantly, by providing independent formulas for synergy and redundancy applicable to continuous time-series data, we provide an approach to characterizing and quantifying information sharing amongst complex system variables.

Connected Through Crisis: Emotional Proximity and the Spread of Misinformation Online

Abstract: During crises, the ability to access relevant information is extremely important for those affected. Previous research shows that social media have become popular for rapid information exchange between members of the online community after crisis events. This study focuses on the effects of proximity to a crisis on information sharing behaviors. Using constructivist grounded theory to guide our inquiry, we conducted interviews with eleven people who used social media in the aftermath of the 2013 Boston Marathon Bombings. Salient themes emerging from this study suggest that both physical and emotional proximity to a crisis influence online information seeking and sharing behaviors. Additionally, speed of information sharing and information access renders social media especially useful during crisis and particularly susceptible to the spread of misinformation. We view the latter as a consequence of the inevitable sensemaking process that occurs as individuals attempt to make sense of incomplete information.

The invisible work of personal health information management among people with multiple chronic conditions: qualitative interview study among patients and providers.

Abstract: Background: A critical problem for patients with chronic conditions who see multiple health care providers is incomplete or inaccurate information, which can contribute to lack of care coordination, low quality of care, and medical errors. Objective: As part of a larger project on applications of consumer health information technology (HIT) and barriers to its use, we conducted a semistructured interview study with patients with multiple chronic conditions (MCC) with the objective of exploring their role in managing their personal health information. Methods: Semistructured interviews were conducted with patients and providers. Patients were eligible if they had multiple chronic conditions and were in regular care with one of two medical organizations in New York City; health care providers were eligible if they had experience caring for patients with multiple chronic conditions. Analysis was conducted from a grounded theory perspective, and recruitment was concluded when saturation was achieved. Results: A total of 22 patients and 7 providers were interviewed; patients had an average of 3.5 (SD 1.5) chronic conditions and reported having regular relationships with an average of 5 providers. Four major themes arose: (1) Responsibility for managing medical information: some patients perceived information management and sharing as the responsibility of health care providers; others—particularly those who had had bad experiences in the past—took primary responsibility for information sharing; (2) What information should be shared: although privacy concerns did influence some patients’ perceptions of sharing of medical data, decisions about what to share were also heavily influenced by their understanding of health and disease and by the degree to which they understood the health care system; (3) Methods and tools varied: those patients who did take an active role in managing their records used a variety of electronic tools, paper tools, and memory; and (4) Information management as invisible work: managing transfers of medical information to solve problems was a tremendous amount of work that was largely unrecognized by the medical establishment. Conclusions: We conclude that personal health information management should be recognized as an additional burden that MCC places upon patients. Effective structural solutions for information sharing, whether institutional ones such as care management or technological ones such as electronic health information exchange, are likely not only to improve the quality of information shared but reduce the burden on patients already weighed down by MCC. [J Med Internet Res 2015;17(6):e137]

Adoption of travel information in user-generated content on social media: the moderating effect of social presence

Abstract: Travel patterns have gradually changed from group travel to individual travel. An increasing number of people acquire travel information through various types of media. One of the alternative information sources is social media, which enables users to exchange information among members. However, one of the characteristics of social media is information sharing, not information search, which involves both giving i.e. posting and taking i.e. selective reading, forwarding, replying, linking, and liking information. Compared to the ‘giving’ side of information-sharing research, less effort has been spent on the ‘taking’ side of information research. Therefore, we investigate travel information adoption in social media as well as how individuals communicate with each other. We use the elaboration likelihood model, which measures the impact of central e.g. argument quality and peripheral e.g. credibility cues on traveller information-sharing behaviour corresponding with social presence on social media. The results of an empirical analysis of 527 respondents, who were experienced in travel information adoption via social media, were examined. Our findings revealed that argument quality had a positive effect on perceived usefulness and source credibility positively affected perceived usefulness and social relationships. Perceived usefulness had a significant positive effect on social relationships. Both perceived usefulness and social relationships affected travel information adoption. Lastly, the levels of argument quality and source credibility perceived by social media members were found to differ according to the level of social presence.

Information sharing in a supply chain with a make-to-stock manufacturer ☆

Abstract: We study ex ante information sharing in a supply chain consisting of a downstream retailer and a make-to-stock upstream manufacturer. The retailer has imperfect demand information and may choose to share it with the manufacturer. Based on the information sharing arrangement, the manufacturer makes the wholesale price and the stocking level decisions. Then the retailer decides the order quantity and the manufacturer fulfills the order up to the available stock level. We find that the retailer has an incentive to voluntarily share the information with the make-to-stock manufacturer if the magnitude of demand uncertainty is intermediate. This stands in sharp contrast with the existing studies which show that the retailer never shares information when the manufacturer is make-to-order. Our results highlight the interdependence between the retailer׳s incentive to share information and the manufacturer׳s operational and marketing decisions.

Factors affecting information sharing in social networking sites amongst university students

Abstract: – Drawing upon the knowledge sharing model, the purpose of this paper is to identify personal and environmental antecedents to information sharing on social networking sites (SNSs) and examines the interaction effects between the two factors. , – Data were collected via online survey with college students. Hierarchical multiple regressions were performed to test hypotheses and examine research questions. , – With regard to environmental factors, the more users perceive their audience to be a collection of weak ties, the more likely they are to share information on SNSs, independent of the size of their networks. Personal factors such as information self-efficacy, positive social outcome expectations, and sharing enjoyment feelings were found to be significant predictors of sharing activities. In addition, a significant interaction effect was found such that the effects of social outcome expectations on sharing activities on SNSs are manifested to a greater extent when users perceive their audience as weak ties rather than strong ties. , – This study extends the knowledge sharing model literature by applying it to the SNS context and advances SNS research by taking into consideration both environmental factors and personal factors and their interactions.

Examining the role of social media in California's drought risk management in 2014

Abstract: Social media creates an interactive information communication platform for disaster preparedness, mitigation, response, and recovery. Recent research has analyzed the participation of social media in natural disasters, such as the Haiti Earthquake in 2010, Queensland floods from 2010 to 2011, Hurricane Sandy in 2012, and Colorado flood in 2013, but little research has paid attention to drought risk management. In this study, the strengths, weaknesses, opportunities, and threats analysis method is used to evaluate the social media sites of governmental agencies that were directly involved in California’s Drought Task Force in the historic drought in 2014. The results show that state governmental agencies have used the popular social media platforms (Facebook, YouTube, and Twitter) as communication channels with professional stakeholders and the general public. The major functions of social media in the California drought risk management process included one-way information sharing, two-way information sharing, situational awareness, rumor control, reconnection, and decision making. However, social media was not active in donation solicitation and volunteer management. The two-way communication still stayed in relatively surficial levels with limited comments and inadequate conversations. A gap existed to reconnect public social media domain and personal social networks, even though drought risk was closely related to everyone’s daily life. During the California drought in 2014, Facebook worked actively in two-way information sharing for drought risk information and water conservation strategies; YouTube was a robust platform that attracted large number of views on drought videos; and Twitter played an effective role in reconnection of social networks to expedite drought risk information dissemination.

Information disclosure of social media users: Does control over personal information, user awareness and security notices matter?

Abstract: Purpose – The purpose of this paper is to bridge the gap in the existing literature by exploring the antecedents of information disclosure of social media users. In particular, the paper investigates the link between information disclosure, control over personal information, user awareness and security notices in the social context, all of which are shown to be different from existing studies in e-commerce environments. Design/methodology/approach – The authors collected and analysed data from 514 social network users. The model is estimated using ordinary least squares and robust standard errors are estimated using the Huber-White sandwich estimators. Findings – The results show that in social networking contexts, control over personal information is negatively and statistically associated with information disclosure. However, both user awareness and security notices have a positive statistical effect on information disclosure. Originality/value – Whilst research on issues of individual information priva...

A comprehensive review on privacy preserving data mining

Abstract: Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Ever-escalating internet phishing posed severe threat on widespread propagation of sensitive information over the web. Conversely, the dubious feelings and contentions mediated unwillingness of various information providers towards the reliability protection of data from disclosure often results utter rejection in data sharing or incorrect information sharing. This article provides a panoramic overview on new perspective and systematic interpretation of a list published literatures via their meticulous organization in subcategories. The fundamental notions of the existing privacy preserving data mining methods, their merits, and shortcomings are presented. The current privacy preserving data mining techniques are classified based on distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity, where their notable advantages and disadvantages are emphasized. This careful scrutiny reveals the past development, present research challenges, future trends, the gaps and weaknesses. Further significant enhancements for more robust privacy protection and preservation are affirmed to be mandatory.

Why do social network site users share information on Facebook and Twitter

Abstract: Users join social network sites SNSs for social network building and information sharing, however, little has been ascertained as to why users share information on SNSs. This study examined why SNS users share information, knowledge, and personal experiences with others on SNSs. Through an online survey, 10 motivation factors were tested with Facebook and Twitter users. The findings indicate that the motivations of SNS users in sharing information could be attributed to various aspects such as demographic characteristics, experiences of SNSs and Internet usage, as well as the characteristics and features of SNSs. SNS users could be highly motivated by the learning and social engagement aspects of SNS services. It is also found that the motivations could vary depending on the characteristics of services. The results of this study could be helpful for researchers in understanding the underlying reasons for social activities as well as for SNS developers in improving SNS services.

Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data

Abstract: Some of the challenges that designers face in getting broad external input from customers during and after product launch include geographic limitations and the need for physical interaction with the design artifact(s). Having to conduct such user-based studies would require huge amounts of time and financial resources. In the past decade, social media has emerged as an increasingly important medium of communication and information sharing. Being able to mine and harness product-relevant knowledge within such a massive, readily accessible collection of data would give designers an alternative way to learn customers' preferences in a timely and cost-effective manner. In this paper, we propose a data mining driven methodology that identifies product features and associated customer opinions favorably received in the market space which can then be integrated into the design of next generation products. Two unique product domains (smartphones and automobiles) are investigated to validate the proposed methodology and establish social media data as a viable source of large scale, heterogeneous data relevant to next generation product design and development. We demonstrate in our case studies that incorporating suggested features into next generation products can result in favorable sentiment from social media users.

Toward trustworthy vehicular social networks

Abstract: Wireless vehicular networks offer the promise of connectivity to vehicles that could provide a myriad of safety and driving-enhancing services to drivers and passengers. With wireless technology available in each car, it is expected that huge amounts of information will be exchanged between vehicles or between vehicles and roadside infrastructure. Due to defective sensors, software viruses, or even malicious intent, legitimate vehicles might inject untrustworthy information into the network. Besides relying on the public key infrastructure, this article proposes a social network approach to study trustworthy information sharing in a vehicular network. We first cover recent research progress in measuring direct trust and modeling indirect trust in online social networks, and then discuss how to apply them to vehicular social networks despite several pressing research challenges.

Effect of information sharing and process coordination on logistics outsourcing

Abstract: Purpose – The purpose of this paper is to test how integrative mechanisms, including information sharing and process coordination, influence logistics outsourcing, and how logistics outsourcing influence performance from an extended RBV perspective Design/methodology/approach – The structural equation modeling (SEM) method is used to examine the proposed model, based on data collected from 361 companies in greater China Findings – Integrative mechanisms are helpful for logistics outsourcing (basic, customized, and advanced outsourcing) Specially, information sharing contributes to customized and advanced outsourcing, but has no significant effect on basic outsourcing In contrast, process coordination improves basic and advanced outsourcing, but insignificantly influences customized outsourcing Besides, each type of logistics outsourcing has differently effects on 3PL users’ performance This study contributes to 3PL theories and practices Originality/value – This study empirically examines the antec

To open or not to open? Determinants of open government data

Abstract: In recent years, open government data has become an important movement among government administrations around the world. While there is still limited open data research conducted in East Asia, this study explores the complexity of open data initiatives in Taiwan. In particular, the influential factors and their impacts on open data initiatives are investigated from four perspectives: technology, organization, legislation and policy, and environment. Legislation and policy is found to have the most significant impact while agencies' existing regulations and policies act as constraints. The factors residing in organizational and environmental perspectives follow as the secondary impacts. Technological factors also exist but are considered to be relatively more easily resolved with sufficient support. While the identified factors act as determinants to influence government agencies' intentions towards open data participation, it is also found that open data is closely related to interagency information sharing, and the two activities in the long term are expected to reinforce to each other iteratively. In addition, practical implications are discussed to provide practitioners with insights. Lastly, the contributions, limitations and potential future research of the current study are listed in the Conclusion section.

From Cyber Security Information Sharing to Threat Management

Abstract: Across the world, organizations have teams gathering threat data to protect themselves from incoming cyber attacks and maintain a strong cyber security posture. Teams are also sharing information, because along with the data collected internally, organizations need external information to have a comprehensive view of the threat landscape. The information about cyber threats comes from a variety of sources, including sharing communities, open-source and commercial sources, and it spans many different levels and timescales. Immediately actionable information are often low-level indicators of compromise, such as known malware hash values or command-and-control IP addresses, where an actionable response can be executed automatically by a system. Threat intelligence refers to more complex cyber threat information that has been acquired or inferred through the analysis of existing information. Information such as the different malware families used over time with an attack or the network of threat actors involved in an attack, is valuable information and can be vital to understanding and predicting attacks, threat developments, as well as informing law enforcement investigations. This information is also actionable, but on a longer time scale. Moreover, it requires action and decision-making at the human level. There is a need for effective intelligence management platforms to facilitate the generation, refinement, and vetting of data, post sharing. In designing such a system, some of the key challenges that exist include: working with multiple intelligence sources, combining and enriching data for greater intelligence, determining intelligence relevance based on technical constructs, and organizational input, delivery into organizational workflows and into technological products. This paper discusses these challenges encountered and summarizes the community requirements and expectations for an all-encompassing Threat Intelligence Management Platform. The requirements expressed in this paper, when implemented, will serve as building blocks to create systems that can maximize value out of a set of collected intelligence and translate those findings into action for a broad range of stakeholders.

Exploring information sharing in the extended supply chain: an interdependence perspective

Abstract: Purpose – This paper aims to empirically explore demand-related information sharing in the extended supply chain. Design/methodology/approach – Through a single, embedded case design, a range of methods are used to collect data from companies representing three different supply chain tiers, including focal company, first-tier suppliers and first-tier customers. The collected data are analysed through the theoretical lens of interdependence. Findings – The findings indicate that the supply chain actors adapt information sharing to the pooled, serial or reciprocal type of interdependence. Information sharing is thus increased with key dyadic partners representing, for example, unique offerings and high market shares as percentage of total expenditure/sales. The study also unearths several barriers to information sharing beyond dyadic ties, including problems related to dis-aggregated, misinterpreted and/or incomplete information. Research limitations/implications – The study empirically contributes to the e...

Handle with care: How online social network providers’ privacy policies impact users’ information sharing behavior

Abstract: Privacy policies determine online social network providers’ options to monetize user data. However, these statements also intrude on users’ privacy and, thus, might reduce their willingness to disclose personal information, which in turn limits the data available for monetization. Given these conflicting interests, we conducted an experimental survey to investigate the relationship between privacy policies and users’ reactions. We show that users’ privacy risk perceptions mediate the effect that changes in policies’ monetization options have on users’ willingness to disclose information. Our findings emphasize privacy policies as a delicate managerial concept for companies relying on data monetization.

An evolutionary game-theoretic framework for cyber-threat information sharing

Abstract: The initiative to protect against future cyber crimes requires a collaborative effort from all types of agencies spanning industry, academia, federal institutions, and military agencies. Therefore, a Cybersecurity Information Exchange (CYBEX) framework is required to facilitate breach/patch related information sharing among the participants (firms) to combat cyber attacks. In this paper, we formulate a non-cooperative cybersecurity information sharing game that can guide: (i) the firms (players)1 to independently decide whether to “participate in CYBEX and share” or not; (ii) the CYBEX framework to utilize the participation cost dynamically as incentive (to attract firms toward self-enforced sharing) and as a charge (to increase revenue). We analyze the game from an evolutionary game-theoretic strategy and determine the conditions under which the players' self-enforced evolutionary stability can be achieved. We present a distributed learning heuristic to attain the evolutionary stable strategy (ESS) under various conditions. We also show how CYBEX can wisely vary its pricing for participation to increase sharing as well as its own revenue, eventually evolving toward a win-win situation.