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Department of Communications/
News Bureau
22 Davis Hall, 10 Lippitt Road, Kingston, RI 0288
Phone: 401-874-2116 Fax: 401-874-7872

URI business professor earns major
award for marketing research
Kingston resident cited for advancing field

KINGSTON, R.I. -- December 5, 2001 -- A University of Rhode Island College of Business Administration professor has been awarded the 2001 Donald R. Lehmann Award for (the) Outstanding Dissertation-Based Article in Marketing Research.

Sajeev Varki, an assistant professor of marketing and a resident of Kingston, was presented the Lehmann Award for the paper "Modeling Fuzzy Data in Qualitative Marketing Research," which appeared in the Journal of Marketing Research. Varki’s work was singled out as the best dissertation-based paper to have appeared in the last two years in either the Journal of Marketing or the Journal of Marketing Research; two of the leading journals published by the American Marketing Association.

Varki’s was one of about 20 papers submitted nationally from top business institutions, such as the Wharton School of Business at the University of Pennsylvania.

"It took me four years to get this published," Varki said, "because it can be applied to all of the social sciences."

His paper was also a finalist for the 2001 Paul Green Award, also awarded by the Journal of Marketing Research. "The Paul Green Award is like the Oscar for best picture, while the Lehmann Award is like the Oscar for best actor," Varki joked.

Varki said the research discussed in the paper tackles the problem of determining how good or bad a particular classification system is and identifying the judges who are good at classification. Some of the applications cited by Varki include the classification of credit risks by banks, the hiring of job applicants in sales management, determining the nature of media coverage in communication studies, and in the development of measurement scales in the social sciences.

"My paper addresses the accuracy of typologies," he said. "There is no classification scheme so perfect that every item can fit into one category. An item can belong to several categories, which is why the data become fuzzy and must be modeled."

He said he could use the model to analyze judges’ performance. "I can pull out how biased judges are by using this model," he said.

In the introduction to his paper, co-authored with Bruce Cooil, an associate professor in Statistics at the Graduate School of Management at Vanderbilt University, and Roland T. Rust, the David Bruce Smith Chair in Marketing at the University of Maryland, Varki states that qualitative data are used in theory development to investigate marketing phenomena more in depth. After data are collected, the judgment-based classification of items into categories is routinely used to summarize and communicate the information contained in the article.

The model written about by Varki is called the fuzzy latent class model because it frees data from the restrictive assumption that they can fit neatly into single categorizations.

"Instead, FLCM allows for items to be either crisp or fuzzy. Crisp items belong exclusively to one category, whereas fuzzy items belong—in varying degree—to multiple categories. This relaxation in the assumption about the nature of qualitative data makes the model more widely applicable," Varki said in his introduction.

Varki, holds a Ph.D. in marketing from the Owen School of Management, Vanderbilt University; his MBA from the Indian Institute of Management, Ahmedabad, and his bachelor’s degree from the Indian Institute of Technology, Kharagpur. His areas of expertise are strategy, service marketing and methodology. Previous awards include the 1999 Davidson Award from the Journal of Retailing published by New York University for his paper on "customer delight" and the 2001 Literati Club Award from the International Journal of Service Industry Management for his 2001 paper on using service quality data for competitive marketing decisions.

For Information: Sajeev Varki 401-874-4372, Dave Lavallee 401-874-2116

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