Integrating Theory of Planned Behavior and Value-Belief-Norm Theory to Explain Residents’ Intention on Garbage Classification

Authors

  • Jiayi Huang
  • Yuxin Jing
  • Liangshu Zhang
  • Zhizheng Huang
  • Qiudi Chen

DOI:

https://doi.org/10.54097/pnjyk833

Keywords:

TPB model, VBN theory, Garbage Classification, Intention.

Abstract

Guiding residents’ garbage classification behavior is one of the important ways to alleviate urban environmental pollution. Based on the theory of planned behavior (TPB) and the theory of value-belief-norm (VBN), 440 questionnaires were analyzed by using partial least squares structural equation modeling (PLS-SEM) to study the factors affecting residents’ intention (I) of garbage classification. The results show that the integrated TPB and VBN model developed in this study has a stronger ability to predict and explain the Intention (I) of residents’ garbage classification. The residents’ Perceived Behavioral Norms (PBN), Subjective Norms (SN), and Personal Norms (PN) directly affect the behavioral intention (I) of residents’ garbage classification, and Perceived Behavioral Control (PBC) is the biggest factor affecting the Intention (I) of residents’ garbage classification. Besides, Residents’ Subjective Norm (SN), Awareness of Consequences (AC), and Ascribed Responsibility (AR) explain residents’ Personal Norms (PN), among which Subjective Norm (SN) have the most significant impact on Personal Norms (PN). Personal norm is a mediator between social norms and Intention (I) on garbage classification. The study further enriches the research on residents’ garbage classification intention (I) and inspires for enhancing residents’ garbage classification intention (I).

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Published

29-12-2023

How to Cite

Huang, J., Jing, Y., Zhang, L., Huang, Z., & Chen, Q. (2023). Integrating Theory of Planned Behavior and Value-Belief-Norm Theory to Explain Residents’ Intention on Garbage Classification. Journal of Education, Humanities and Social Sciences, 24, 9-17. https://doi.org/10.54097/pnjyk833