With ninety percent of all data created in the last two years (Yu, 2012), how can newly available information be effectively utilized in research, and perhaps help to “discover insights we have never imagined?” (Ayshford 2012). Visualizations support many cognitive activities such as decision-making, knowledge discovery, and hypothesis generation (Barabási, Gann, & Salter, 2003; Koua, 2003; Tufte, 1997) and have a capacity to enrich human thinking by letting human offload complex cognitive processing of information onto computers (Card, Mackinlay, & Shneiderman, 1999). Recent advancements in information and scientific visualization provide additional insights about data (e.g., spatio-temporal, social network, multivariate tools) along with data enrichment with semantic and statistical descriptions of foreign geographic locations. Visualizing multiple dimensions of a phenomenon provide often more encompassing understandings than the ones based only on statistical techniques. This workshop will aim at introducing a range of visualization tools to enhance and analyze different data types in International Management (IM). In particular, the workshop will guide participants through the choices of the most appropriate visualization tools for a research project along with their methodology of exploratory analysis. Specifically, we will demonstrate the differences in visualization using spatio- temporal, geovisualization and social network analyses along with data enrichment techniques. Visualization of complex temporal and spatial data can contribute to novel theoretical explanations of IM phenomenon by synthesizing various pieces of information into one overall comprehensive picture. Identification of existing patterns is one of the promising ways for IM theory development (Cheng, Guo, & Skousen, 2011).
Ayshford, E. (2012). The Data Age. Retrieved July 29, 2014, from http://www.mccormick.northwestern.edu/magazine/fall-2012/data-age.html
Barabasi, A. L., Gann, D., & Salter, A. (2003). Linked: how everything is connected to everything else and what it means for business, science, and everyday life. Plume.
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999). Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers.
Cheng, J. L. C., Guo, W., & Skousen, B. (2011). Advancing New Theory Development in the Field of International Management: Contributing Factors, Investigative Approach, and Proposed Topics, 51(6), 787–802.
Koua, E. L. (2003). Using Self-Orginizing Maps for Informaton Visualization and Knowledge Discovery in Complex Geospatial Datasets. Proceedings of 21st International Cartographic Renaissance (ICC), 1694–1702.
Tufte, E. R. (1997). Visual explanations: images and quantities, evidence and narrative. Graphics Press.
Yu, E. (2013, September 29). Big data deployments remain low among firms. ZDNet.com. ZDNet.com. Retrieved April 8, 2014, from http://www.zdnet.com/big-data-deployments-remain-low-among-firms-7000021079/