A Methodology to Support Product Differentiation Decisions

IEEE Transactions on Engineering Management. Vol 57, No 4. 649 - 660. November 2010.

30 Pages Posted: 8 Jun 2013

See all articles by Kamalini Ramdas

Kamalini Ramdas

London Business School - Department of Management Science and Operations

Oleksandr Zhylyevskyy

Iowa State University, Department of Economics

William L. Moore

University of Utah - Department of Marketing

Date Written: October 1, 2009

Abstract

Choosing the right set of new products to offer is a key driver of protability. New products often share some design attributes with existing products, so firms need to decide which attributes to keep common, and which to differentiate. We propose and empirically implement a new methodology that can help managers navigate the complex decision of where to focus differentiation, using “looks like” prototypes that typically become available in the later stages of the product development process. Our methodology complements early stage product positioning methods such as conjoint analysis and perceptual mapping. It also offers a way to estimate the impact of context dependence on choice. Finally, our methodology provides a way to test empirically whether perceptual mapping based on pairwise similarity judgments is appropriate for a product category. Using data obtained from a major wristwatch manufacturer, we are able to suggest guidelines on how to differentiate the firm’s offerings, and estimate the magnitude of context dependent effects. We also find that for wristwatches, attributes that drive perceptions differ from those that drive choice. Overall, our approach can help avoid falling into the trap of focusing variety on attributes that are costly to differentiate and have little impact on choice.

Keywords: Product differentiation, Product similarity, Consumer choice, “Looks like” prototype, Context dependence

Suggested Citation

Ramdas, Kamalini and Zhylyevskyy, Oleksandr and Moore, William L., A Methodology to Support Product Differentiation Decisions (October 1, 2009). IEEE Transactions on Engineering Management. Vol 57, No 4. 649 - 660. November 2010. , Available at SSRN: https://ssrn.com/abstract=2273193

Kamalini Ramdas (Contact Author)

London Business School - Department of Management Science and Operations ( email )

Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom

Oleksandr Zhylyevskyy

Iowa State University, Department of Economics ( email )

260 Heady Hall
Ames, IA 50011
United States
(515) 294-6311 (Phone)
(515) 29406644 (Fax)

HOME PAGE: http://www.econ.iastate.edu

William L. Moore

University of Utah - Department of Marketing ( email )

1645 E. Campus Center Drive
Salt Lake City, UT 84112-9304
United States

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