Sustainable Marketing in Action : A Multi-Theoretical Model of Consumer Transformation Toward Energy-Saving Behavior
DOI:
https://doi.org/10.17010/ijom/2026/v56/i4/175414Keywords:
sustainable marketing, energy-saving behavior, theory of planned behavior (TPB), social cognitive theory (SCT), place attachment, publicity and education, artificial neural networks (ANN).Publication Chronology: Paper Submission Date : September 30, 2025 ; Paper sent back for Revision : February 23, 2026 ; Paper Acceptance Date : March 25, 2026 ; Paper Published Online : April 15, 2026.
Abstract
Purpose : The study aimed at exploring the factors that influence energy-saving behavior (ESB) among households, particularly within the context of emerging economies. Although prior studies have employed behavioral theories such as the theory of planned behavior (TPB) and social cognitive theory (SCT), there is little research that has incorporated cognitive, social, and emotional factors simultaneously within the context of emerging economies, supported by predictive analysis tools.
Methodology : The study investigated 10 latent variables, which included publicity/education, energy-saving knowledge (ESK) norms, perceived behavioral control (PBC), self-efficacy (SE), outcome expectation (OE), place attachment, etc. The study used a structured questionnaire, which was distributed among 500 households across Tamil Nadu, India. The data analysis used SMART PLS for structural modeling, while artificial neural network analysis was conducted using SPSS.
Findings : The study found that publicity/education significantly contributed to ESK, which, in turn, positively influenced PBC and normative influences. PBC turned out to be the most significant predictor of ESB, followed by subjective norms (SN) and place attachment, as revealed by the artificial network analysis.
Practical Implications : The results implied that a marketing strategy for sustainable marketing practices should include education, social influence, and geographical engagement to promote energy-saving practices.
Originality : This study differed from previous studies on these determinants because it used an integrated multi-theory model and validated it using structural equation modeling and artificial neural network analysis.
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