Abstract
Brand extension is one of the most popular strategies in marketing. This is due to the fact that consumers usually take into account the brand first because it indirectly reflects the design, quality, and functions. According to the significant role of brand in creating benefit and diminishing risk for a new product, this study intended to develop a novel model for selecting the most appropriate strategy in brand extension. However, there are a number of criteria influencing the possible strategies, and they often are interdependent. Therefore, a multi-criteria decision making model based on Analytic Network Process and Additive Ratio Assessment methods has been developed to systematically clarify the interdependent relationships among the evaluation criteria of brand extension and then, scientifically evaluate the feasible strategies and rank the priorities of brand extension strategies. The results of the proposed model show that “Production cost” is the most important factor, followed by “Quality of parent brand” and “Perceived risk” while “Ice cream” is the highest satisfaction of brand extension.
Highlights
Brand extension, defined as the use of an established brand name for new-product categories, is one of the most common strategies used in developing an existing brand, which can reduce risk and increase investment by enhancing consumer perception
Additive Ratio Assessment (ARAS), introduced by Zavadskas and Turskis (2010), is based on the concept that the phenomena of complicated world could be understood by using simple relative comparisons (Turskis, Zavadskas 2010)
This paper proposes a new integrated model based on Analytic network process (ANP) and fuzzy Additive Ratio Assessment Method (ARAS) methods that is capable of handling both subjective judgment and objective information in the process of formulating a decision making problem
Summary
Brand extension, defined as the use of an established brand name for new-product categories, is one of the most common strategies used in developing an existing brand, which can reduce risk and increase investment by enhancing consumer perception. After defining the problem under consideration and identifying the evaluation criteria and feasible alternatives, the ANP method is employed for obtaining the relative weights of the evaluation criteria but not the entire evaluation process to reduce the large number of pairwise comparison For this reason, fuzzy ARAS is used to calculate the performance of alternatives, and. The ANP technique extends the AHP to facilitate the process of formulating the problems with feed-back and dependence (Fouladgar et al 2012) This method replaces the hierarchy in the AHP with a network to equip the ANP for modelling the interrelationships among decision elements in order to solve the problems that are nonlinear and more complex.
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