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Bentley University Associate Professor Dipayan Biswas Wins Best Research Paper Award at the American Marketing Association Annual Summer Conference
Bentley University faculty member Dipayan Biswas received an award from the American Marketing Association (AMA) at their Annual Summer Marketing Educators' Conference held August 13 to 16, 2010 in Boston, Massachusetts. Biswas received the Award for Best Paper in the Consumer Behavior Track at the AMA Conference for his research on how consumers might make erroneous judgments when trying to compute mathematical averages.
The research paper, "Evaluating Ratio Data and the Role of Consumer Processing Mode: Can Analytical Processing Bias Judgments?" examines how consumer judgments might be biased when attempting to analyze commonly used ratios, such as loads per container for laundry detergent or calories per minute for fitness equipment. The research was co-authored with Patricia Norberg of Quinnipiac University, Hamden and Donald Lehmann of Columbia University, New York.
"Understanding how consumers process ratio information is a relatively unstudied topic," Biswas explains. "Ultimately, the goal of our larger research project was to uncover how figuring out ratio data influences consumers' true understanding of a product's effectiveness."
Biswas, Norberg, and Lehmann's research included three specific studies focusing on consumers' analysis of fitness machines based on calories burned per minute, speed data for choosing between routes based on miles per hour, and laundry detergent based on loads per container. The research results found that in general, most marketers currently use data metrics, labeling methods and information formats that tend to lead to inaccurate consumer judgments, and that commonly used ratio formats do, in fact, bias consumer judgments when consumers are left to compute averages in their head. However, they found that that the bias can be corrected if the data are presented in alternative, easier-to-compute formats.
Biswas et al. found that correcting consumer judgment bias can lead to more efficient use of resources. For instance, buying a more efficient detergent not only saves money but also reduces overall impact on the environment. Similarly, knowing the accurate average calories burned per minute across multiple exercise routines or fitness equipments can lead to healthier exercise patterns.
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