Iowa Cooperative Fertilizer Retail Outlets: Farmers' Attitudes and Perceptions

Based on a sample of Iowa farmers, attributes of fertilizer retail dealers are evaluated. Honest management, making deliveries on time, relative size, willingness to negotiate price, and marketing grain are the most important attributes affecting a farmer's decision to patronize an independent or cooperative dealer. Cooperative outlets are generally in a strong competitive position. The study also shows much salient information can be generated by using such statistical methods as segmentation analysis, factor analysis, and the choice model approach.Fertilizer, supply cooperative, farmers' perception, dealer attributes, segmentation analysis, factor analysis, choice model, logit, Agribusiness,

The role of processing-by-attribute noncompensatory choice models

AbstractResearch work on modeling consumer multiple choice problems using logit, regression, and probit is gaining more attention. However, in their work, Russ (1971), Tversky (1972), Newell and Simon (1972), Tversky and Sattath (1979), and Gensch and Svestka (1979; 1984) indicate that for many problems, choice behavior appears to be context dependent and hierarchical. With this specific issue in mind, this paper discusses a mathematical model which estimates threshold tolerances, eliminates nonchosen alternatives, provides choice probabilities and finally offers diagnostic information regarding the key attributes that are responsible for making a final decision. The use of other individual specific models such as: lexicographic, conjunctive, etc., have been briefly explicated

Iowa Cooperative Fertilizer Retail Outlets: Farmers' Attitudes and Perceptions

Based on a sample of Iowa farmers, attributes of fertilizer retail dealers are evaluated. Honest management, making deliveries on time, relative size, willingness to negotiate price, and marketing grain are the most important attributes affecting a farmer's decision to patronize an independent or cooperative dealer. Cooperative outlets are generally in a strong competitive position. The study also shows much salient information can be generated by using such statistical methods as segmentation analysis, factor analysis, and the choice model approach

A Two-Stage Disaggregate Attribute Choice Model

A two-stage disaggregate attribute choice model is proposed and empirically implemented. The first stage of the model is attribute processing to screen the number of alternatives down to a lesser number. The second stage is brand (alternative) processing which considers the attributes simultaneously while allowing for tradeoffs among the attributes. This two-stage approach is then applied to the same real world data set as two single stage disaggregate models, logit and Maximum-Likelihood-Hierarchical (MLH) which are state of the art models representing the alternative and attribute processing approaches, respectively. The predictive accuracy of the two-stage approach compares favorably to the single stage models. In addition, it seems to offer diagnostic information that can provide managerial insights not found in the output of the single stage model.choice modeling, hierarchical, brand choice, multistage decisions

Targeting the Switchable Industrial Customer

This article presents a new approach to target marketing. An industrial market for electrical equipment is segmented on the basis of the strength of current preferences as defined by the probabilities of selecting the various suppliers. A modification of a disaggregate attribute choice model (logit) is used to identify the firm's “switchable” customers. The “switchable” customers are then targeted by direct personalized mail and visits by a “missionary” sales force. A major supplier of large-scale electrical equipment utilized this methodology with impressive sales results.industrial marketing, choice models, brand switching, supplier loyalty

Reply—A Response to Malhotra's Comment on Testing the Homogeneity of Segments

Author's response to the comment Malhotra, N. K. 1987. Testing the homogeneity of segments for estimating disaggregate choice models. 98–99.

Solving the "Marketing Mix" Problem using Geometric Programming

This paper investigates the optimal allocation of the marketing budget within the marketing-mix decision variables so that sales (or profit) is maximized in a planning horizon. Since the influence of marketing mix variables upon sales are, in reality, nonlinear and interactive, a geometric programming algorithm is used that solves this problem. A procedure to estimate a functional of sales on the marketing mix and environmental variables utilizing the experienced judgments of the firm's executives and the raw data is provided. The derived functional is later optimized by the Geometric Programming algorithm under a constraint set consisting of budget and strategy restrictions imposed by a firm's marketing environment, and conditions under which the optimal solution is either local or global are identified. An empirical application for a large midwestern brewery is provided which utilizes and illustrates both the estimation an optimization procedures.