Artificial Intelligence Lab, Department of MIS, University of Arizona / The volume of qualitative data (QD)available via the Internet is growing at an increasing pace and firms are anxious to extract and understand user's thought processes, wants and needs, attitudes, and purchase intentions contained therein. An information systems (IS) methodology to meaningfully analyze this vase resource of QD could provide useful information, knowledge, or wisdom firms could use for a number of purposes including new product development and quality improvement, target marketing, accurate "user focused" profiling, and future sales prediction. In this paper, we present an IS methodology for analysis of Internet-based QD consisting of three steps: elicitation; reduction through IS-facilitated selection, coding, and clustering; and visualization to provide at-a-glance understanding.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105374 |
| Date | January 2003 |
| Creators | Romano, Nicholas C., Donovan, Christina, Chen, Hsinchun, Nunamaker, Jay F. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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