Next Article in Journal
The Role of Rail Transit Systems in Reducing Energy and Carbon Dioxide Emissions: The Case of The City of Rio de Janeiro
Previous Article in Journal
The Contribution of Energy-Optimized Urban Planning to Efficient Resource Use–A Case Study on Residential Settlement Development in Dhaka City, Bangladesh
Article Menu

Export Article

Open AccessArticle
Sustainability 2016, 8(2), 152; doi:10.3390/su8020152

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

1
School of Economics and Management, Harbin Engineering University, Harbin 150001, China
2
Research Institute of Disaster and Crisis Management, School of Economics and Management, Harbin Engineering University, Harbin 150001, China
3
Department of Industrial and Systems Engineering, University at Buffalo, State University of New York, 317 Bell Hall, Buffalo, NY 14260-2050, USA
*
Authors to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 23 December 2015 / Revised: 27 January 2016 / Accepted: 2 February 2016 / Published: 5 February 2016
View Full-Text   |   Download PDF [1828 KB, uploaded 5 February 2016]   |  

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. View Full-Text
Keywords: municipal household solid waste; separate collection; influence factors; Bayesian belief networks model municipal household solid waste; separate collection; influence factors; Bayesian belief networks model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chu, Z.; Wang, W.; Wang, B.; Zhuang, J. Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks. Sustainability 2016, 8, 152.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top