Deriving consensus rankings via multicriteria decision making methodology
AbstractPurpose - This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach - The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics. Findings - Outranking methods in consequence constitute a strong base on which to found the entire structure of the behavioral theory of benchmarking applied to development of marketing strategy. Research limitations/implications - This study looks only at a limited part of the puzzle of how consumer satisfaction translates into behavioral outcomes. Practical implications - The study provides managers with guidance on how to generate a rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats. Originality/value - The paper interestingly portrays the effective usage of multicriteria decision-making and ranking method to help marketing managers predict their marketing trends.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1201.1604.
Date of creation: Jan 2012
Date of revision:
Publication status: Published in Business Strategy Series, Vol. 13 Iss: 1, pp.3 - 12 2012
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-01-18 (All new papers)
- NEP-MKT-2012-01-18 (Marketing)
- NEP-SEA-2012-01-18 (South East Asia)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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