IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i16p5765-d396782.html
   My bibliography  Save this article

A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation

Author

Listed:
  • Fumin Deng

    (Business School, Sichuan University, Chengdu 610065, China
    The Economy and Enterprise Development Institute, Sichuan University, Chengdu 610065, China)

  • Yanjie Li

    (Business School, Sichuan University, Chengdu 610065, China)

  • Huirong Lin

    (National Environmental Protection Hazardous Waste Disposal Engineering Technology (Chongqing) Center, Chongqing 401120, China)

  • Jinrui Miao

    (Business School, Sichuan University, Chengdu 610065, China)

  • Xuedong Liang

    (Business School, Sichuan University, Chengdu 610065, China)

Abstract

Hazardous waste can cause severe environmental pollution if not disposed of properly, which in turn can seriously affect the sustainable development of the entire ecology and will inevitably bring disaster to companies. However, because of limited available disposal capacity, it is often difficult to safely dispose of hazardous waste, meaning that it must be kept as passive inventory. For the passive inventory of hazardous waste, risk evaluation of safe operation of the inventory is crucial and urgently needs to be resolved. Based on this, this paper focuses on the risk management of hazardous waste inventory of waste-producing companies and proposes a risk evaluation system for safely dealing with hazardous waste inventory, which expands the scope of inventory safety management and provides guidance to companies on developing appropriate measures to ensure hazardous waste inventory safety. First, the risk evaluation index system for hazardous waste inventory is constructed from equipment, management level, nature of hazardous waste and operational aspects. Then, the best worst method (BWM) is employed to calculate the criteria weights and the technique for order performance by similarity to ideal solution (TOPSIS) is employed to rank the alternatives. Finally, risk evaluation on four waste-producing companies was conducted using the developed method. The results show that Case Company 4 has the greatest risk of hazardous waste inventory, which should be reduced by improving storage method and the amount of hazardous waste. It was found that the proposed evaluation system was effective for hazardous waste inventory safety risk assessments and that the designed index system could assist companies improve their hazardous waste inventory management.

Suggested Citation

  • Fumin Deng & Yanjie Li & Huirong Lin & Jinrui Miao & Xuedong Liang, 2020. "A BWM-TOPSIS Hazardous Waste Inventory Safety Risk Evaluation," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5765-:d:396782
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/16/5765/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/16/5765/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hatami-Marbini, Adel & Tavana, Madjid, 2011. "An extension of the Electre I method for group decision-making under a fuzzy environment," Omega, Elsevier, vol. 39(4), pages 373-386, August.
    2. Esha Saha & Pradip Kumar Ray, 2019. "Modelling and analysis of healthcare inventory management systems," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1179-1198, December.
    3. Schroer, Suzanne & Modarres, Mohammad, 2013. "An event classification schema for evaluating site risk in a multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 40-51.
    4. Trucco, P. & Cagno, E. & Ruggeri, F. & Grande, O., 2008. "A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 845-856.
    5. Briggs, Th. & Kunsch, P. L. & Mareschal, B., 1990. "Nuclear waste management: An application of the multicriteria PROMETHEE methods," European Journal of Operational Research, Elsevier, vol. 44(1), pages 1-10, January.
    6. Gu, Jingyao & Zhang, Guoqing & Li, Kevin W., 2015. "Efficient aircraft spare parts inventory management under demand uncertainty," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 101-109.
    7. Kaya, Tolga & Kahraman, Cengiz, 2010. "Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul," Energy, Elsevier, vol. 35(6), pages 2517-2527.
    8. Zhao, Jiahong & Ke, Ginger Y., 2017. "Incorporating inventory risks in location-routing models for explosive waste management," International Journal of Production Economics, Elsevier, vol. 193(C), pages 123-136.
    9. Samanlioglu, Funda, 2013. "A multi-objective mathematical model for the industrial hazardous waste location-routing problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 332-340.
    10. Peipei You & Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    11. Antonio Nesticò & Piera Somma, 2019. "Comparative Analysis of Multi-Criteria Methods for the Enhancement of Historical Buildings," Sustainability, MDPI, vol. 11(17), pages 1-19, August.
    12. Rabbani, M. & Heidari, R. & Yazdanparast, R., 2019. "A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 272(3), pages 945-961.
    13. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    14. Chan, Felix T.S. & Kumar, Niraj, 2007. "Global supplier development considering risk factors using fuzzy extended AHP-based approach," Omega, Elsevier, vol. 35(4), pages 417-431, August.
    15. Louis, Garrick & Shih, Jhih-Shyang, 2007. "A flexible inventory model for municipal solid waste recycling," Socio-Economic Planning Sciences, Elsevier, vol. 41(1), pages 61-89, March.
    16. Forgionne, Guisseppi A. & Kohli, Rajiv & Jennings, Darniet, 2002. "An AHP analysis of quality in AI and DSS journals," Omega, Elsevier, vol. 30(3), pages 171-183, June.
    17. Wang, Endong, 2015. "Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach," Applied Energy, Elsevier, vol. 146(C), pages 92-103.
    18. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    19. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    2. Maghsoud Amiri & Mohammad Hashemi-Tabatabaei & Mohammad Ghahremanloo & Mehdi Keshavarz-Ghorabaee & Edmundas Kazimieras Zavadskas & Arturas Kaklauskas, 2021. "Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)," Sustainability, MDPI, vol. 13(8), pages 1-28, April.
    3. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    4. Yossi Hadad & Baruch Keren & Dima Alberg, 2023. "An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements," Energies, MDPI, vol. 16(11), pages 1-18, May.
    5. Corrente, Salvatore & Greco, Salvatore & Rezaei, Jafar, 2024. "Better decisions with less cognitive load: The Parsimonious BWM," Omega, Elsevier, vol. 126(C).
    6. Besharati Fard, Moein & Moradian, Parisa & Emarati, Mohammadreza & Ebadi, Mehdi & Gholamzadeh Chofreh, Abdoulmohammad & Klemeŝ, Jiří Jaromír, 2022. "Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    7. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    8. Xiao-Kang Wang & Wen-Hui Hou & Chao Song & Min-Hui Deng & Yong-Yi Li & Jian-Qiang Wang, 2021. "BW-MaxEnt: A Novel MCDM Method for Limited Knowledge," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    9. Dragan Pamučar & Fatih Ecer & Goran Cirovic & Melfi A. Arlasheedi, 2020. "Application of Improved Best Worst Method (BWM) in Real-World Problems," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    10. Chong Li & He Huang & Ya Luo, 2022. "An Integrated Two-Dimension Linguistic Intuitionistic Fuzzy Decision-Making Approach for Unmanned Aerial Vehicle Supplier Selection," Sustainability, MDPI, vol. 14(18), pages 1-24, September.
    11. Sarbast Moslem & Muhammet Gul & Danish Farooq & Erkan Celik & Omid Ghorbanzadeh & Thomas Blaschke, 2020. "An Integrated Approach of Best-Worst Method (BWM) and Triangular Fuzzy Sets for Evaluating Driver Behavior Factors Related to Road Safety," Mathematics, MDPI, vol. 8(3), pages 1-20, March.
    12. Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).
    13. Gholamreza Haseli & Reza Sheikh & Jianqiang Wang & Hana Tomaskova & Erfan Babaee Tirkolaee, 2021. "A Novel Approach for Group Decision Making Based on the Best–Worst Method (G-BWM): Application to Supply Chain Management," Mathematics, MDPI, vol. 9(16), pages 1-20, August.
    14. Wu, Qun & Liu, Xinwang & Zhou, Ligang & Qin, Jindong & Rezaei, Jafar, 2024. "An analytical framework for the best–worst method," Omega, Elsevier, vol. 123(C).
    15. Murad, C.A. & Bellinello, M.M. & Silva, A.J. & Netto, A. Caminada & de Souza, G.F.M. & Nabeta, S.I., 2022. "A novel methodology employed for ranking and consolidating performance indicators in holding companies with multiple power plants based on multi-criteria decision-making method," Operations Research Perspectives, Elsevier, vol. 9(C).
    16. Kheybari, Siamak & Javdanmehr, Mahsa & Rezaie, Fariba Mahdi & Rezaei, Jafar, 2021. "Corn cultivation location selection for bioethanol production: An application of BWM and extended PROMETHEE II," Energy, Elsevier, vol. 228(C).
    17. Mališa Žižović & Dragan Pamučar & Goran Ćirović & Miodrag M. Žižović & Boža D. Miljković, 2020. "A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL)," Mathematics, MDPI, vol. 8(5), pages 1-18, May.
    18. Mu-Hsin Chang & James J. H. Liou & Huai-Wei Lo, 2019. "A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry," Sustainability, MDPI, vol. 11(15), pages 1-20, July.
    19. Chunlin Xin & Jie Wang & Ziping Wang & Chia-Huei Wu & Muhammad Nawaz & Sang-Bing Tsai, 2022. "Reverse logistics research of municipal hazardous waste: a literature review," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 1495-1531, February.
    20. M. Tadaros & A. Migdalas, 2022. "Bi- and multi-objective location routing problems: classification and literature review," Operational Research, Springer, vol. 22(5), pages 4641-4683, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5765-:d:396782. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.