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E3 Journal of Business Management and Economics

E3 Journal of Business Management and Economics Vol. 2 (4) pp. 132-146, October 2011; © E3 Journals; ISSN 2141-7482


An empirical survey: Can green marketing really entice customers to pay more?

Ming-Yuan Hsieh *
Department of International Business; National Taichung University140, Min-Shen Road, Taichung City, 40306, Taiwan (R.O.C.);Tel: +886-975-118-922
*Corresponding Author E-mail: uscpawisely@hotmail.com
Accepted 12 September 2011

Abstract

This research integrated the Social Cognition Theory and the Engel Kollat Blackwell customers’ purchasing model (EKB model) to synthetically discuss the three kinds of possible relations comprising “does negatively entice”, “does possibly entice” and “does positively entice” between green-marketing and customers’ purchasing and payment, with consideration given to environmental-protection issues. Based on the measured results, the most contributed contention of this research not only utilized three cross-analytical theories consisting of the social cognition theory (SCT) , the Fuzzy theory (FT) and the EKB model, and the novel F-ANP of the MCDM methodology to evaluate the collected data but it also manifested that Green-marketing does possibly entice customers to pay more (GMPECPM). These measured results have distinctly stunned the fundamental assumption in the traditional green-marketing research field that customers were supposed to be willing to pay more for green products and services because they were supporting green initiatives and helping environmental-protection. Further, major future research directions were also briefly demonstrated in this research as (1) the collection data have to be strengthened to gather more empirical customer feedback, corporate management comments, and professional scholars’ reports; (2) enterprises have to resoundingly establish a green-branding initiative after successfully executing green-marketing strategies.

Keywords: Green Marketing (G-marketing); Multiple Criteria Decision Making (MCDM); Analytical Network Process (F-ANP).

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