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Machine Learning Methods Analysis of Preceding Factors Affecting Behavioral Intentions to Purchase Reduced Plastic Products

Author

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  • David Jericho B. Villanueva

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Ardvin Kester S. Ong

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    E.T. Yuchengco School of Business, Mapúa University, 1191 Pablo Ocampo Sr. Ext, Makati 1204, Philippines)

  • Josephine D. German

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

Abstract

The COVID-19 pandemic has led to an increase in the use of personal protective equipment and single-use plastics, which has exacerbated plastic littering on land and in marine environments. Consumer behaviors with regards to eco-friendly products, their acceptance, and intentions to purchase need to be explored to help businesses achieve their sustainability goals. This paper establishes the Sustainability Theory of Planned Behavior (STPB), an integration of the TPB and sustainability domains, in order to analyze the said objectives. The study employed a machine learning ensemble method and used MATLAB to analyze the data. The results showed that support and attitude from perceived authorities were the main variables influencing customers’ intentions for purchasing reduced plastic products. Customers with a high level of environmental awareness were more likely to embrace reduced plastic items as a way to lessen their ecological footprint and support environmental conservation, making perceived environmental concern another important factor. This shows that authorities play a big role in the community in influencing people to choose reduced plastic products, making it the duty of governments and companies to promote environmental awareness. This study emphasizes the significance of the latent variables considered when developing marketing plans and activities meant to promote products with less plastic.

Suggested Citation

  • David Jericho B. Villanueva & Ardvin Kester S. Ong & Josephine D. German, 2024. "Machine Learning Methods Analysis of Preceding Factors Affecting Behavioral Intentions to Purchase Reduced Plastic Products," Sustainability, MDPI, vol. 16(7), pages 1-26, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2978-:d:1369485
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    References listed on IDEAS

    as
    1. Shahida Anusha Siddiqui & Adriano Profeta & Thomas Decker & Sergiy Smetana & Klaus Menrad, 2023. "Influencing Factors for Consumers’ Intention to Reduce Plastic Packaging in Different Groups of Fast-Moving Consumer Goods in Germany," Sustainability, MDPI, vol. 15(9), pages 1-21, May.
    2. Ma. Janice J. Gumasing & Alyssa Bayola & Sebastian Luis Bugayong & Keithzi Rhaz Cantona, 2023. "Determining the Factors Affecting Filipinos’ Acceptance of the Use of Renewable Energies: A Pro-Environmental Planned Behavior Model," Sustainability, MDPI, vol. 15(9), pages 1-21, May.
    3. Marko Šostar & Vladimir Ristanović, 2023. "Assessment of Influencing Factors on Consumer Behavior Using the AHP Model," Sustainability, MDPI, vol. 15(13), pages 1-24, June.
    4. Vítor de Castro Paes & Clinton Hudson Moreira Pessoa & Rodrigo Pereira Pagliusi & Carlos Eduardo Barbosa & Matheus Argôlo & Yuri Oliveira de Lima & Herbert Salazar & Alan Lyra & Jano Moreira de Souza, 2023. "Analyzing the Challenges for Future Smart and Sustainable Cities," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
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