Exploring the recycled water acceptance based on the technological perspective of UTAUT2: a hybrid analytical approach

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5 Scopus citations

Abstract

Introduction: The development of advanced sewage technologies empowers the industry to produce high-quality recycled water, which greatly influences human’s life and health. Thus, this study investigates the mechanism of individuals’ adoption of recycled water from the technology adoption perspective. Methods: Employing the mixed method of structural equation modeling and artificial neural network analysis, we examined a research model developed from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. To examine the research model, this study employs a leading web-survey company (Sojump) to collect 308 valid samples from the residents in mainland China. Results: The structural equation modeling results verified the associations between the six predictors (performance expectancy, effort expectancy, social influence, facilitating conditions, environmental motivation, and price value), individuals’ cognitive and emotional attitudes, and acceptance intention. The artificial neural network analysis validates and complements the structural equation modeling results by unveiling the importance rank of the significant determinants of the acceptance decisions. Discussion: The study provides theoretical implications for recycled water research and useful insights for practitioners and policymakers to reduce the environmental hazards of water scarcity.

Original languageEnglish
Article number1384635
JournalFrontiers in Psychology
Volume15
DOIs
StatePublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation

Keywords

  • artificial neural network (ANN)
  • extended Unified Theory of Acceptance and Use of Technology (UTAUT2)
  • mixed-method
  • recycled water acceptance
  • structural equation modeling (SEM)

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