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Customer-Salesperson Relationships and Teaching the Lens Model

Dale Rude
Houston, Texas

I have been engaged in several activities that may be of interest to the Society. The first is a research project with Eli Jones, a marketing faculty member whose primary research area is relationship selling. We are doing a dyadic study to see if customer-salesperson relationship variables (e.g., similarity, frequency of contact, trustworthiness, length of relationship) predict how well the salesperson understands the customer's decision strategy for making a purchase. Customer and salesperson rate the same series of policy capturing scenarios, the salesperson attempting to predict the customer's responses. The dependent variable is the agreement between salesperson and customer's policy/decision strategies.

The second activity involves software and text materials that I have written for teaching Brunswik's lens model to undergraduate business majors. These students have a limited understanding of statistics and no research methods background. One software program is an APL DOS-based horse race task (modeled after the Harmon and Rohrbaugh horse race task) which I use for introducing the lens model. Students make bets and judgments of order of finish and odds using four cues including speed rating, jockey winning percentage, and post position. Their judgments are then analyzed to produce achievement indices, etc. Students also compare their performances to that of an expert handicapper. The second software program is APL DOS-based and is used in my classes for a team project. Teams of three students identify a decision environment and problem for study and collect judgments, cues, and outcomes. After the data are entered, the software performs the statistical analyses and produces the relevant lens model indices. The students then write a 20-page report summarizing their findings and do a class presentation. When finished, the students thoroughly understand the lens model.

The text materials consist of class notes, assignments, and problems that I use. These include a review of relevant statistical concepts (mean, standard deviation, correlation, regression, etc.), the lens model, and some application problems. I have simplified the lens model terminology because students find some of the traditional lens model terminology to be very confusing (e.g., criterion is commonly confused with cue). For example, I have substituted "outcome" for "criterion," "cue validity" for "ecological validity," and "outcome predictability" for "environmental predictability."

Anyone who would like the software and/or teaching materials should email me and provide a "snail mail" address. I will send you several floppy disks containing the software and teaching materials.

Contact Dale Rude

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