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Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks

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  • Zhujie Chu

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China
    Research Institute of Disaster and Crisis Management, School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Wenna Wang

    (School of Economics and Management, Harbin Engineering University, Harbin 150001, China
    Research Institute of Disaster and Crisis Management, School of Economics and Management, Harbin Engineering University, Harbin 150001, China)

  • Bairong Wang

    (Department of Industrial and Systems Engineering, University at Buffalo, State University of New York, 317 Bell Hall, Buffalo, NY 14260-2050, USA)

  • Jun Zhuang

    (Department of Industrial and Systems Engineering, University at Buffalo, State University of New York, 317 Bell Hall, Buffalo, NY 14260-2050, USA)

Abstract

Municipal household solid waste (MHSW) has become a serious problem in China over the course of the last two decades, resulting in significant side effects to the environment. Therefore, effective management of MHSW has attracted wide attention from both researchers and practitioners. Separate collection, the first and crucial step to solve the MHSW problem, however, has not been thoroughly studied to date. An empirical survey has been conducted among 387 households in Harbin, China in this study. We use Bayesian Belief Networks model to determine the influencing factors on separate collection. Four types of factors are identified, including political, economic, social cultural and technological based on the PEST (political, economic, social and technological) analytical method. In addition, we further analyze the influential power of different factors, based on the network structure and probability changes obtained by Netica software. Results indicate that technological dimension has the greatest impact on MHSW separate collection, followed by the political dimension and economic dimension; social cultural dimension impacts MHSW the least.

Suggested Citation

  • Zhujie Chu & Wenna Wang & Bairong Wang & Jun Zhuang, 2016. "Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks," Sustainability, MDPI, vol. 8(2), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:2:p:152-:d:63500
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    References listed on IDEAS

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    1. Hua Zhang & Zong-Guo Wen, 2014. "Residents’ Household Solid Waste (HSW) Source Separation Activity: A Case Study of Suzhou, China," Sustainability, MDPI, vol. 6(9), pages 1-21, September.
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    5. Giovanni De Feo & Sabino De Gisi, 2010. "Domestic Separation and Collection of Municipal Solid Waste: Opinion and Awareness of Citizens and Workers," Sustainability, MDPI, vol. 2(5), pages 1-30, May.
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    Cited by:

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    2. Fu Chen & Xiaoxiao Li & Jing Ma & Yongjun Yang & Gang-Jun Liu, 2018. "An Exploration of the Impacts of Compulsory Source-Separated Policy in Improving Household Solid Waste-Sorting in Pilot Megacities, China: A Case Study of Nanjing," Sustainability, MDPI, vol. 10(5), pages 1-14, April.
    3. Eglė Baltranaitė & Loreta Kelpšaitė-Rimkienė & Ramūnas Povilanskas & Ilona Šakurova & Vitalijus Kondrat, 2021. "Measuring the Impact of Physical Geographical Factors on the Use of Coastal Zones Based on Bayesian Networks," Sustainability, MDPI, vol. 13(13), pages 1-18, June.
    4. Navarro Ferronato & Carolina D’Avino & Marco Ragazzi & Vincenzo Torretta & Giovanni De Feo, 2017. "Social Surveys about Solid Waste Management within Higher Education Institutes: A Comparison," Sustainability, MDPI, vol. 9(3), pages 1-17, March.
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