Set Semantic Similarity for Image Prosthetic Knowledge Exchange

2019 ◽  
pp. 513-525 ◽  
Author(s):  
Valentina Franzoni ◽  
Yuanxi Li ◽  
Alfredo Milani
Keyword(s):  
Semantic Similarity ◽  
Knowledge Exchange

Knowledge Contribution in Organizations via Social Media

2017 ◽  
Vol 16 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Nicole Behringer ◽  
Kai Sassenberg ◽  
Annika Scholl
Keyword(s):  
Social Media ◽  
Social Identity ◽  
Social Identity Theory ◽  
Knowledge Exchange ◽  
Expectancy Theory ◽  
Perceived Usefulness ◽  
Abstract Knowledge ◽  
The Social ◽  
Willingness To Contribute ◽  
Social Media Tool

Abstract. Knowledge exchange via social media is crucial for organizational success. Yet, many employees only read others’ contributions without actively contributing their knowledge. We thus examined predictors of the willingness to contribute knowledge. Applying social identity theory and expectancy theory to knowledge exchange, we investigated the interplay of users’ identification with their organization and perceived usefulness of a social media tool. In two studies, identification facilitated users’ willingness to contribute knowledge – provided that the social media tool seemed useful (vs. not-useful). Interestingly, identification also raised the importance of acquiring knowledge collectively, which could in turn compensate for low usefulness of the tool. Hence, considering both social and media factors is crucial to enhance employees’ willingness to share knowledge via social media.

Building Canadian knowledge exchange infrastructure for chronic disease prevention

2005 ◽  
Author(s):  
Roy Cameron ◽  
Sharon Campbell ◽  
Cheryl Moyer ◽  
Maureen Summers
Keyword(s):  
Chronic Disease ◽  
Disease Prevention ◽  
Knowledge Exchange ◽  
Chronic Disease Prevention

Towards an interdisciplinary knowledge exchange model

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Santiago DE FRANCISCO ◽  
Diego MAZO
Keyword(s):  
Design Research ◽  
Knowledge Exchange ◽  
Academic Research ◽  
Innovation Process ◽  
The United States ◽  
Design Environment ◽  
Interdisciplinary Knowledge ◽  
One Year ◽  
The University ◽  
Common Situation

Universities and corporates, in Europe and the United States, have come to a win-win relationship to accomplish goals that serve research and industry. However, this is not a common situation in Latin America. Knowledge exchange and the co-creation of new projects by applying academic research to solve company problems does not happen naturally.To bridge this gap, the Design School of Universidad de los Andes, together with Avianca, are exploring new formats to understand the knowledge transfer impact in an open innovation network aiming to create fluid channels between different stakeholders. The primary goal was to help Avianca to strengthen their innovation department by apply design methodologies. First, allowing design students to proposed novel solutions for the traveller experience. Then, engaging Avianca employees to learn the design process. These explorations gave the opportunity to the university to apply design research and academic findings in a professional and commercial environment.After one year of collaboration and ten prototypes tested at the airport, we can say that Avianca’s innovation mindset has evolved by implementing a user-centric perspective in the customer experience touch points, building prototypes and quickly iterate. Furthermore, this partnership helped Avianca’s employees to experience a design environment in which they were actively interacting in the innovation process.

Document- and Keyword-based Author Co-citation Analysis

2018 ◽  
Vol 2 (2) ◽  
pp. 70-82 ◽  
Author(s):  
Binglu Wang ◽  
Yi Bu ◽  
Win-bin Huang
Keyword(s):  
Citation Analysis ◽  
Semantic Similarity ◽  
Method Validation ◽  
New Method ◽  
Global Network ◽  
Network Visualization ◽  
Knowledge Domain ◽  
Knowledge Domains ◽  
Domain Mapping ◽  
The Relationship

AbstractIn the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

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