A Human-Centered Approach to Green Apparel Advertising: Decision Tree Predictive Modeling of Consumer Choice

So Young Song and Youn-Kyung Kim
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So Young Song: Department of Merchandising, University College, The University of Memphis, 408B Manning Hall Building, Memphis, TN 38152, USA
Youn-Kyung Kim: Department of Retail, Hospitality and Tourism Management, University of Tennessee, Knoxville, 110 Jessie Harris Building, 1215 W. Cumberland Avenue, Knoxville, TN 37996, USA

Sustainability, 2018, vol. 10, issue 10, 1-20

Abstract: This study uses a human-centered approach to environmental ethics to examine which perceived factors in advertising predict consumers’ intention to purchase “green”, or sustainably and ethically produced, apparel. We use eight different types of green apparel advertisements to build a decision tree model to determine the most influential factors that lead to future purchases of green apparel. We classify consumers’ perceptions of green advertising as either humanistic, environmental, or product-related responses and propose a conceptual framework to outline the essential elements of an effective green advertising strategy. We use a sample of 829 US consumers from the period January 2015 to December 2017 in our empirical research. Our results show that four factors, namely, perception of the apparel’s quality, its uniqueness, caring, and nature connectedness, predict consumers’ intention to purchase green apparel. Notably, the largest segment of consumers (36%), those who perceive high levels of apparel quality and caring in the advertising, are identified as the high-purchase group. Our findings could improve strategies in green apparel advertising by providing a new analytical approach to model consumers’ behavioral intention to purchase green apparel.

Keywords: decision tree; green advertising; green apparel; green marketing; segmentation; sustainable fashion; sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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