Deriving Consensus Rankings Via Multicriteria Decision Making Methodology

Topics: Decision theory, Decision making software, Decision making Pages: 15 (4331 words) Published: August 11, 2013
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DERIVING CONSENSUS RANKINGS VIA MULTICRITERIA DECISION MAKING METHODOLOGY 1AmyPoh. AL, 2M. N. Saludin, 1M. Mukaidono
1Faculty of Science and Technology, Meiji University
2Faculty of Management & Defense Study, National Defense University of Malaysia ABSTRACT
Purpose – This paper takes a cautionary stance to the impact of marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach – ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4Ps. Descriptive analysis is used to analyze the 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 has looked 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 rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats. Originality/value – This paper interestingly portrays the effective usage of multicriteria decision making and ranking method to help marketing manager predict their marketing trend. Keywords: Marketing mix, Customer satisfaction, Retailing, Benchmarking, Multicriteria decision-making, ELECTRE I method Type of paper: Research Paper

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1. INTRODUCTION
With increasing globalization, local retailers find themselves having to compete with large foreign players by targeting niche markets. To excel and flaunt as a market leader in an ultramodern era and a globalize world, the organizations must strive to harvest from its marketing strategies, benchmarking and company quality policy. Ranking and selecting projects is a relatively common, yet often difficult task. It is complicated because there is usually more than one dimension for measuring the impact of each criteria and more than one decision maker. This paper considers a real application of project selection for the marketing mix element, using an approach called ELECTRE. The ELECTRE method has several unique features not found in other solution methods; these are the concepts of outranking and indifference and preference thresholds. The ELECTRE method applied to the project selection problem using SPSS (Statistical Package for the Social Sciences) application. Our contribution is to show the potential of Marketing mix model in deriving a consensus ranking for benchmarking. According to the feedback from the respondents, we dynamically rank out the best element to be benchmark. The decision problem faced by management has been translated into our market research problem in the form of questions that define the information that is required to make the decision and how this information obtained. The corresponding research problem is to assess whether the market would accept the consensus rankings derive from benchmarking result from the impact of marketing mix on customer satisfaction using a multi-criteria decision making outranking methodology. 3

2. LITERATURE REVIEW
The project ranking problem is, like many decision problems, challenging for at least two reasons. First, there is no single criterion in marketing mix model which adequately captures the effect or impact of each element; in other words, it is a multiple criteria problem. Second, there is no single decision maker; instead the project ranking requires a consensus from a group of decision makers. (Henig and Buchanan and Buchanan et al.) Buchanan et al. have debated that effective decisions come from effective decision process and proposed that where potential the subjective and objective parts of the decision process...

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