Expertise visualization: an implementation and study based on cognitive fit theory

  • Authors:

  • Zan Huang;Hsinchun Chen;Fei Guo;Jennifer J. Xu;Soushan Wu;Wun-Hwa Chen

  • Affiliations:

  • Department of Supply Chain and Information Systems, Smeal College of Business, The Pennsylvania State University, PA;Department of Management Information Systems, Eller College of Management, The University of Arizona, Tucson, AZ;Department of Management Information Systems, Eller College of Management, The University of Arizona, Tucson, AZ;Department of Computer Information Systems, Bentley College, Waltham, MA;College of Management, Chang-Gung University, Taiwan;Department of Business Administration, National Taiwan University, Taiwan

  • Venue:
  • Decision Support Systems
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Expertise management systems are being widely adopted in organizations to manage tacit knowledge. These systems have successfully applied many information technologies developed for document management to support collection, processing, and distribution of expertise information. In this paper, we report a study on the potential of applying visualization techniques to support more effective and efficient exploration of the expertise information space. We implemented two widely applied dimensionality reduction visualization techniques, the self-organizing map (SOM) and multidimensional scaling (MDS), to generate compact but distorted (due to the dimensionality reduction) map visualizations for an expertise data set. We tested cognitive fit theory in our context by comparing the SOM and MDS displays with a standard table display for five tasks selected from a low-level, domain-independent visual task taxonomy. The experimental results based on a survey data set of research expertise of the business school professors suggested that using both SOM and MDS visualizations is more efficient than using the table display for the associate, compare, distinguish, and cluster tasks, but not the rank task. Users generally achieved comparable effectiveness for all tasks using the tabular and map displays in our study.