Academic journal article Academy of Marketing Studies Journal

Marketing a University-Affiliated Applied Research Center: An Application Involving Hull-Spence Behavioral Theory

Academic journal article Academy of Marketing Studies Journal

Marketing a University-Affiliated Applied Research Center: An Application Involving Hull-Spence Behavioral Theory

Article excerpt


This paper demonstrates a market-segmentation and targeting methodology that would benefit business-to-business marketers. Specifically, the method highlights how published, secondary data can be used to construct an aggregate choice model for segmentation purposes. Then, it highlights how Hull-Spence behavioral theory can be employed to target the segments. An online experiment confirms the effectiveness of the approach in achieving communication objectives.

(ProQuest: ... denotes formulae omitted.)


In this age of strategic networks (Gulati et al. 2000), it has become common for universities to work with businesses on issues such as new product development, technology, and marketing (Fischer, 2009; Blumenstyk, 2010). The current status of university-industry partnerships in research can be gleaned from Table 1 . As shown in the Table, R&D expenditures in universities and colleges, during the year 2008, amounted to $51.9 billion. Of this, $12.5 billion (24%) was spent on applied research. On average, businesses contribute $3 billion annually to applied research at universities.

To cater to the research needs of the industry in Western Illinois, SE Iowa and NE Missouri (see Appendix 1 for a listing of the counties in the geographical area), a medium-size university in the Midwest has created an applied research center called I2. Specifically, the center aims to help businesses plan new products; gauge competitors' actions; penetrate new markets, and manage brand equity. This paper highlights the market segmentation and targeting activities of the center. One of the salient features of this research is the reliance on published, secondary data to construct I2's marketing program. It is hoped that the methodology highlighted in the paper would be of interest to business-to-business (b2b) firms wanting to engage in market segmentation and targeting.


Market segmentation is a strategy of resource allocation given a heterogeneous customer population (Kerin et al. 2009; Wedel & Kamakura 2000). In the study area, we have a number of healthcare, government, retail, manufacturing, and hospitality businesses (Appendix 2). Since these businesses would be in different stages of their life cycle, their need for applied research would vary. For example, a start-up may like to "explore" the market potential for its new product whereas a mature firm may want to "confirm" the optimality of its marketing mix (cf. the Dorfman-Steiner theorem (Leeflang et al. 2000)).

It is also possible that the need for applied research could be latent or unfelt for some firms. Since creating primary demand for applied research is beyond the scope of I , we focus on businesses that possess the need for applied research. Specifically, we assume that past research usage is the best predictor of current and future usage, and conceptualize firms that use research services as the potential market.

To segment the potential market, we utilize the argument that applied research requires extensive manager-researcher interaction (Deshpande & Zaltman 1984). This interaction is expected to cultivate in the manager an overall evaluation or attitude towards the research supplier (Gawronski & Bodebhausen 2006). We label this attitude "supplier loyalty" and utilize it as the basis for segmenting existing users of research services.

To elaborate, supplier loyalty implies the strength of preference for a particular supplier (Wind & Thomas 1994). If we segment existing research users into supplier-loyalty categories, then marketing efforts could be directed at research users who are likely to "switch" from their existing supplier and utilize research support from I2. More specifically, we define two groups of customers: brand loyal, and switchable. As the name implies, the brand loyal cluster would exhibit a higher probability of purchasing from their existing research supplier; most often a single supplier. …

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