Towards Efficient Information Sharing in Network Markets

2021 ◽  
Author(s):  
Bertin Martens ◽  
Geoffrey Parker ◽  
Georgios Petropoulos ◽  
Marshall W. Van Alstyne
Keyword(s):  
Information Sharing ◽  
Efficient Information ◽  
Network Markets

scholarly journals Intersecting social-capital and perceived-efficacy perspectives to explain underperformance in community-based monitoring

Evaluation ◽  
2017 ◽  
Vol 23 (3) ◽  
pp. 339-357 ◽  
Author(s):  
Sara Dewachter ◽  
Nathalie Holvoet
Keyword(s):  
Social Capital ◽  
Information Sharing ◽  
Information Network ◽  
Community Based ◽  
Perceived Efficacy ◽  
Leadership Efficacy ◽  
Efficient Information ◽  
Social Capital Perspective ◽  
The Village ◽  
Efficacy Profile

While community-based monitoring is becoming increasingly commonplace, evidence as to its functioning remains inconsistent. Based on Ugandan village network and survey data, this article studies community-based monitoring from a social-capital and perceived-efficacy perspective. From a social-capital perspective, the prospects for community-based monitoring look promising as there is a high social-capital stock and an efficient information-sharing network galvanizing information for a few key individuals. The dominant efficacy profiles are also encouraging as there is an abundance of ‘followers’ (with high belief in collective capabilities) and some ‘leaders’ for collective action (with high belief in individual and collective capabilities). And yet, few community-based monitoring activities are undertaken. Our article shows that only the intersection of both theoretical lenses explains the underperformance in community-based monitoring, as those actors who are central in the information-sharing network do not have a ‘leadership’ efficacy profile while those who are ‘leaders’ are not central in the village information network.

Learning Individual Behavior Using Sensor Data: The Case of Global Positioning System Traces and Taxi Drivers

2020 ◽  
Vol 31 (4) ◽  
pp. 1301-1321
Author(s):  
Yingjie Zhang ◽  
Beibei Li ◽  
Ramayya Krishnan
Keyword(s):  
Information Sharing ◽  
Bayesian Learning ◽  
Sensor Data ◽  
Local Market ◽  
Data Set ◽  
Taxi Drivers ◽  
Individual Level ◽  
Market Expansion ◽  
Aggregate Information ◽  
Efficient Information

In this study, using a Bayesian learning model with a rich data set consisting of 2 million fine-grained GPS observations, we study the role of information observable by or made available to taxi drivers in enabling them to learn the distribution of demand for their services over space and time. We find significant differences between new and experienced drivers in both learning behavior and driving decisions. Drivers benefit significantly from their ability to learn from not only information directly observable in the local market but also aggregate information on demand flows across markets. Interestingly, our policy simulations indicate that information that is noisy at the individual level becomes valuable when aggregated across relevant spatial and temporal dimensions. Moreover, we find that the value of information does not increase monotonically with the scale and frequency of information sharing. Our results also provide important evidence that efficient information sharing can lead to a welfare increase because of potential market expansion. Efficient information sharing can bring additional income-generating opportunities that could be unfulfilled. Overall, this study not only explains driver decision-making behavior but also provides taxi companies with an implementable information-sharing strategy to improve overall market efficiency.

Information Sharing Framework for the Integrated Collaborative Operation in Through Transport of Railway Freight

2012 ◽  
Vol 253-255 ◽  
pp. 1213-1217
Author(s):  
Wei Ya Chen
Keyword(s):  
Information Sharing ◽  
Information Technologies ◽  
Freight Transport ◽  
Information Collection ◽  
Current Information ◽  
Railway Freight ◽  
High Efficient ◽  
Key Factor ◽  
Efficient Information ◽  
Railway Freight Transport

High efficient information sharing is the key factor to realize the integrated collaborative operation in through transport of railway freight. This paper presents a framework of information sharing among the railway enterprises and their customer enterprises. The information sharing demand was categorized into information sharing for demand-supply matching and the integrated collaborative operation. The information sharing content was defined according to the information sharing demand. Base on the current information technologies utilized in China’s railway freight transport, the framework of information sharing was constructed from four aspects: the hierarchy of information sharing, the mode architecture of information sharing, the methods of information collection and the supporting conditions of implementation.

scholarly journals The Current State of ERP Systems in Banking Sector

2017 ◽  
Vol 3 (1) ◽  
pp. 23
Author(s):  
Konstantinos Metaxiotis ◽  
Konstantinos Liagkouras
Keyword(s):  
Information Sharing ◽  
Enterprise Resource Planning ◽  
Banking Sector ◽  
Empirical Studies ◽  
Resource Planning ◽  
Erp Systems ◽  
Current State ◽  
Wide Range ◽  
Efficient Information ◽  
Potential Risks

Abstract—Enterprise resource planning (ERP) systems integrate the organizations business functions allowing efficient information sharing across all business divisions. Through the information sharing is achieved not only better coordination but also faster and more efficient adjustment to the potential risks and business opportunities alike. This paper examines the particularities of ERP systems implementation and operation for the banking sector by considering a wide range of sources such as journal and conference papers, empirical studies and reports. Finally, through the thorough examination of the available literature, we draw conclusions about the effect by the implementation of ERP systems in the banking sector.

scholarly journals Topic Jerk Detector: Detection of Tweet Bursts Related to the Fukushima Daiichi Nuclear Disaster

Information ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 368 ◽  
Author(s):  
Hiroshi Nagaya ◽  
Teruaki Hayashi ◽  
Hiroyuki A. Torii ◽  
Yukio Ohsawa
Keyword(s):  
Social Media ◽  
Information Sharing ◽  
Social Issues ◽  
Research Problem ◽  
Nuclear Disaster ◽  
Social Media Platforms ◽  
Efficient Information ◽  
Fukushima Disaster ◽  
Important Research Problem

In recent disaster situations, social media platforms, such as Twitter, played a major role in information sharing and widespread communication. These situations require efficient information sharing; therefore, it is important to understand the trends in popular topics and the underlying dynamics of information flow on social media better. Developing new methods to help us in these situations, and testing their effectiveness so that they can be used in future disasters is an important research problem. In this study, we proposed a new model, “topic jerk detector.” This model is ideal for identifying topic bursts. The main advantage of this method is that it is better fitted to sudden bursts, and accurately detects the timing of the bursts of topics compared to the existing method, topic dynamics. Our model helps capture important topics that have rapidly risen to the top of the agenda in respect of time in the study of specific social issues. It is also useful to track the transition of topics more effectively and to monitor tweets related to specific events, such as disasters. We attempted three experiments that verified its effectiveness. First, we presented a case study applied to the tweet dataset related to the Fukushima disaster to show the outcomes of the proposed method. Next, we performed a comparison experiment with the existing method. We showed that the proposed method is better fitted to sudden burst accurately detects the timing of the bursts of the topic. Finally, we received expert feedback on the validity of the results and the practicality of the methodology.

scholarly journals Against All Odds: Tentative Steps toward Efficient Information Sharing in Groups

Games ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 31
Author(s):  
Darius Schlangenotto ◽  
Wendelin Schnedler ◽  
Radovan Vadovič
Keyword(s):  
Information Sharing ◽  
First Year ◽  
Single Individual ◽  
Before And After ◽  
Efficient Information ◽  
Holding Back ◽  
Undergraduate Class

When groups face difficult problems, the voices of experts may be lost in the noise of others’ contributions. We present results from a “naturally noisy” setting, a large first-year undergraduate class, in which the expert’s voice was “lost” to such a degree that bringing forward even more inferior information was optimal. A single individual had little chance to improve the outcome and coordinating with the whole group was impossible. In this setting, we examined the change in behavior before and after people could talk to their neighbors. We found that the number of people who reduced noise by holding back their information strongly and significantly increased.

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