An analysis of barriers for successful implementation of municipal solid waste management in Beijing: an integrated DEMATEL-MMDE-ISM approach
| DOI | https://doi.org/10.1108/IMDS-08-2022-0464 |
| Published date | 14 February 2023 |
| Date | 14 February 2023 |
| Pages | 931-966 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Chao Wang,Yongkang Sun,Ming K. Lim,Pezhman Ghadimi,Amir Hossein Azadnia |
An analysis of barriers
for successful implementation of
municipal solid waste management
in Beijing: an integrated
DEMATEL-MMDE-ISM approach
Chao Wang
Research Base of Beijing Modern Manufacturing Development,
College of Economics and Management, Beijing University of Technology,
Beijing, China and
Department of Physics, Center for Polymer Studies, Boston University,
Boston, Massachusetts, USA
Yongkang Sun
College of Economics and Management, Beijing University of Technology,
Beijing, China
Ming K. Lim
Adam Smith Business School, University of Glasgow, Glasgow, UK and
UKM-Graduate School of Business, Universiti Kebangsaan Malaysia,
Bangi, Malaysia
Pezhman Ghadimi
School of Mechanical and Materials Engineering, University College Dublin,
Dublin, Ireland, and
Amir Hossein Azadnia
School of Business, Maynooth University, Maynooth, Ireland
Abstract
Purpose –With rapid industrialization and urbanization, municipal solid waste (MSW) management has
become a serious challenge worldwide, especially in developing countries. The Beijing Municipality is a
representative example of many local governments in China that are facing MSW management issues.
Although there have been studies in the area of MSW management in the literature, less attention has been
devoted to developing a structured framework that identifies and interprets the barriers to MSW management
in megacities, especially in Beijing. Therefore,this study focuses on identifying a comprehensive list of barriers
affecting the successful implementation of MSW management in Beijing.
Design/methodology/approach –Through an extensive review of related literature, 12 barriers are
identified and classified into five categories: government, waste, knowledge dissemination, MSW management
process and market. Using an integrated approach including the decision-making trial and evaluation
laboratory (DEMATEL), maximum mean de-entropy algorithm (MMDE) and interpretive structural modeling
(ISM), a conceptual structural model of MSW implementation barriers is constructed to provide insights for
industrial decision-makers and policymakers.
Findings –The results show that a lack of economic supportfrom the government, imperfect MSW-related laws and
regulations, the low education of residents and the lack of publicity of waste recycling knowledge are the main barriers
to MSW management in Beijing. Combined with expert opinions, the paper provides suggestions and guidance to
municipal authorities and industry practitioners to guide the successful implementation of MSW management.
Municipal solid
waste
management
931
This research is funded by the National Natural Science Foundation of China (72071006).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 9 August 2022
Revised 23 November 2022
Accepted 16 December 2022
Industrial Management & Data
Systems
Vol. 123 No. 3, 2023
pp. 931-966
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-08-2022-0464
Practical implications –The findings of this study can provide a reference for MSW management in other
metropolises in China and other developing countries.
Originality/value –This study proposes a hybrid DEMATEL-MMDE-ISM approach to resolve the
subjectivity issues of the traditional ISM approach and it analyzes the barriers that hinder MSW management
practices in Beijing.
Keywords Municipal solid waste, Barrier analysis, Interpretive structural modeling, DEMATEL
Paper type Research paper
1. Introduction
With rapid industrialization and urbanization, municipal solidwaste (MSW) managementhas
become a serious challenge worldwide, especially for developing countries (Wang and Wang,
2013;World Bank, 2005;Cheng et al., 2020). Developed nations hold the leading position in MSW
management. For example, Sweden and Japan have achieved high waste recycling and waste-to-
energy through detailed and specific waste classification rules, strict waste recycling regulations
and extended waste producer responsibility systems (Mekonnen and Tokai, 2020;Malinauskaite
et al., 2017).For instance, in Japan,subsidieswere provided forthe constructionof environmental
facilities, public-private partnerships wereencouraged in technology and innovations and end-
users are engaged in the current monitoring of waste management programs and tracking the
futureemerging needs.Compared withdeveloped countries,China’s MSW recycling is still in its
infancy. Facing the substantial growth of MSW generation, the Chinese government has set up
eight pilot cities, including Beijing and Shanghai, to implement classification for the recycling of
MSW. However, the resultsof the pilot project were not ideal (Lv et al., 2020).
In the past four decades, Beijing has experienced substantial growth in MSW generation,
growing from 1.04 million tons in 1978 to 10.11 million tons in 2019. The recycling and utilization
rate is low in Beijing compared with other cities in developed countries (Chu et al., 2019).
According to China City Statistical Yearbook (2018), there are 27 existing waste treatment
facilities in Beijing, representing an average daily treatment capacity of 24.3 thousand tons,
including 10.1 thousand tons incinerated, 3.7 thousand tons treated with biochemicals and 10.5
thousand tons destined for a landfill. Nearly half of MSW in Beijing goes to landfills.
Hence, Beijing authorities urgently need to accelerate their MSW management. Multiple
constraints from the government, residents, infrastructure, funds and supervision hinder MSW
management. Wang and Geng (2012) and Ferronato et al. (2019) stated that deficient relevant
regulations and government finances, as well as a lack of public participation, are the main
barriers to MSW management. Similarly, the disorder in the informal recycling market and
inconvenient recycling facilities are the dominant barriers to MSW management (Xiao et al.,
2018;Kumar and Dixit, 2018;Conke, 2018). Lack of regulations and supervision, ineffective
management, insufficient funds and limited infrastructure are other barriers to effective solid
waste management (Negash et al., 2021;Bui et al., 2022). In general, a large amount of literature
has been accumulated on the barriers to the implementation of MSW management. Most
previous studies focus on the status, characteristics and challenges of MSW management at the
city and country levels in China, but none of these studies analyzes the barriers that hinder MSW
management practices in Beijing. Facing multiple barriers, a research question is raised: “what
are the dominant barriers to MSW management practices in Beijing?”The answers to this
question can help Beijing Municipality improve its MSW management performance.
During the past decade, several researchers have tried to identify and analyze MSW
management implementation barriers. Table 1 provides relevant information about these
studies. As shown in Table 1, a variety of methods have been used in order to analyze the
MSW barriers. Multi-criteria decision-making (MCDM) techniques, interpretive structural
modelling (ISM) and statistical analysis are the most used methods for barrier analysis in the
area of MSW. Some researchers also used a mixture of the above-mentioned methods.
IMDS
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DEMATEL and ISM are common methods for studying the complex problems of waste
management and waste recovery. However, both DEMATEL and ISM depend on thresholds
determined by experts in the calculation procedure and such subjective opinions will
inevitably affect the results. Therefore, it is necessary to find a new approach to solve the
complex relationship between multiple variables without subjectivity. The maximum mean
de-entropy algorithm (MMDE) presented by Li and Tzeng (2009) is applied to obtain
the appropriate threshold value. This algorithm provides a structured method to show the
impact-relation plot between the barriers (Singh and Bhanot, 2020).
Based on the information provided in Table 1 and the above mentioned discussion, there is
a lack of research in the area of MSW management in a megacity such as Beijing and the
study tries to address the threshold issue of ISM to provide a structured hierarchy and
framework of potential barriers. To address this gap, a hybrid DEMATEL-MMDE-ISM
model is proposed in this research to analyze the barriers and the relationship between them
and identify the key barriers affecting MSW management implementation. The main
contributions of this study include the following:
(1) Identifies 12 barriers hindering the successful implementation of MSW management
based on the literature and expert opinions.
(2) Combine the DEMATEL with the MMDE and ISM to form a hybrid approach and
resolve the subjectivity issues of the traditional ISM approach.
(3) Develops a conceptual hierarchical model of the identified barriers, prioritizes the
dominant barriers hindering MSW management practices in Beijing and provides
policy suggestions according to the results.
The rest of thepaper is structured as follows.Section 2 introduces the relevantliterature in the
waste management area to identify the barriers that impede the implementation of MSW
management. Section 3 introduces the hybrid approach and explains the data acquisition
Reference Area Method
Country/
region
Tseng (2009) MSW management ANP-DEMATEL Manila
Dursun et al. (2011) Health care waste
management
Fuzzy MCDM Istanbul
Dos Muchangos et al. (2015) MSW management ISM-DEMATEL Maputo city
Mir et al. (2016) MSW management TOPSIS-VIKOR Iran
Thakur and Anbanandam (2016) Health care waste
management
ISM-MICMAC India
Yukalang et al. (2017) MSW management SWOT analysis Thailand
Chauhan et al. (2018) MSW management ISM-DEMATEL India
Coban et al. (2018) MSW management TOPSIS-
PROMETHEE
Turkey
Kumar and Dixit (2018) E-waste management ISM-DEMATEL India
Abdullah et al. (2019) MSW management Fuzzy DEMATEL –
Fernando (2019) MSW management Statistical analysis Sri Lanka
Sharma et al. (2020) E-wastemanagement DEMATEL India
Ayçin and Kayapinar Kaya
(2021)
MSW management Fuzzy DEMATEL Turkey
Deus et al. (2022) MSW management Statistical analysis Brazil
Thakur et al. (2022) MSW management Total-ISM India
Current study MSW management ISM-MMDE-
MICMAC
Beijing
Table 1.
Recent publications
related to barrier
analysis for MSW
Municipal solid
waste
management
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