The Application of an Innovative Marketing Strategy MADM Model-SIVA-Need: A Case Study of Apple Company

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Abstract

A review of studies on marketing strategies during the past thirty years has indicated a lack of consistent evaluation of corporate marketing strategies due to the unavailability of a standard multiple attribute decision making (MADM) model of marketing strategy. Drawing on the SIVA marketing mix and Maslow's hierarchy of needs, this study first generated latent attributes classification references through conceptualization, and established a validated classification matrix based on the data obtained through nominal group techniques (NGT) with 7 experts. With a reliability of 0.95, the resulting classification matrix contained 4 dimensions and 20 attributes, which were then used to develop an MADM model of marketing strategy-"SIVA-Need"-which seeks to probe deeply into customers' thinking. Based on the SIVA-Need model, this study designed a questionnaire, which was administered to heavy users of Apple products. A total number of 326 valid questionnaires were collected. Analyses of weights obtained through Consistent Fuzzy Linguistic Preferences Relations (CFLPR) suggested that "brand community value" was the crucial attribute, as it ranked highest (0.0631) among the 20 attributes. However, "brand community value" was found to have the biggest performance gap (1.50) while "product benefit" had the best performance (0.235). The 4 dimensions and 20 attributes of SIVA-Need model may provide more valuable information for future studies and a consistent evaluation model for companies to conduct extensive marketing strategy selection. The results of this study suggested that Apple should invest more resources in the improvement of "brand community value" to create more satisfied and repeat-purchase customers.

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APA

Hsu, T. H., Her, S. T., Chang, Y. H., & Hou, J. J. (2022). The Application of an Innovative Marketing Strategy MADM Model-SIVA-Need: A Case Study of Apple Company. International Journal of Electronic Commerce Studies. Academy of Taiwan Information Systems Research. https://doi.org/10.7903/ijecs.1972

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