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Application of logit regression models for the identification of market segments

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  • Marija Burinskiene
  • Vitalija Rudzkiene

Abstract

A success of the currently implemented projects and measures is determined not only by the urgency and soundness of idea and the size of the budget, but also by the direction of resources to those users and organizations, from which the largest return could be expected, by the public opinion about the current business and a success of project presentation in various forms of mass media. For identification of target market, to which the business strategy will be directed, one should know the features, needs and opinions of the users in order to define the coherent homogenous groups. Various mathematical models are applied to define these groups. When developing the empirical topology the factor and cluster analysis methods are mostly used. Logit regression may be used to analyse and forecast relations of the dependent dichotomic variable and independent variables measured at any scale. Above‐given algorithms of the quality data analysis are illustrated by the case when the dependent variable is of dichotomic nature. Drafting general plans of Akmene region a questionnaire survey of inhabitants of the region and towns was carried out. Application of quality analysis methods is a valuable measure enabling specialists and planners to apply the proposed solutions by taking account of their specific features and peculiarities.

Suggested Citation

  • Marija Burinskiene & Vitalija Rudzkiene, 2007. "Application of logit regression models for the identification of market segments," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 8(4), pages 253-258.
  • Handle: RePEc:taf:jbemgt:v:8:y:2007:i:4:p:253-258
    DOI: 10.1080/16111699.2007.9636177
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