IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i14p2401-d858684.html
   My bibliography  Save this article

The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America

Author

Listed:
  • Sarfaraz Hashemkhani Zolfani

    (School of Engineering, Universidad Catolica del Norte, Larrondo 1281, Coquimbo 1780000, Chile)

  • Ramin Bazrafshan

    (Department of Industrial Engineering and Management Systems, Amirkabir University of Technology (Teran Polytechnic), Tehran 15875-4413, Iran)

  • Fatih Ecer

    (Sub-Department of Operations Research, Faculty of Economics and Administrative Sciences, Afyon Kocatepe University, 03200 Afyonkarahisar, Turkey)

  • Çağlar Karamaşa

    (Faculty of Business, Department of Business Administration, Anadolu University, 26470 Eskişehir, Turkey)

Abstract

This study aims to help managers develop a proper strategy and policy for their company’s future. After the global COVID-19 pandemic, developed countries decided to change their production and relocate and re-industrialize. The U.S.’s big electronics and automobile companies are not an exception to this rule. The lithium batteries are the main instrument of mobile phone and electric vehicles. The leading lithium battery supplier for the U.S mobile phone companies is China. Argentina, Bolivia, and Chile (in South America) have some of the largest lithium mines in the world; these countries are known as the lithium triangle. Among the 86 million tonnes of lithium resources worldwide, 49.9 million tonnes exist in this area. The researchers in this study surveyed the best country for constructing a battery for companies in the U.S. Because of the growth of electric vehicles and their use of the lithium battery, the world is facing astronomical prices for lithium. To emphasize this issue and help managers create good policy, this study combined multiple methods. The improved suitability-feasibility-acceptability (SFA) strategy is integrated with the Bayesian best-worst method (BBWM) and measurement of alternatives and rankings according to compromise solution (MARCOS) multicriteria methods to determine the best destination. For comparison, based on the SFA strategy, seven criteria are introduced: commercially viable reserves, national minimum wage, corporate income tax, accessibility to mining companies, accessibility to the waterway, population, and political stability index. The Bayesian BWM analysis reveals that the foremost factor is corporate income tax, whereas MARCOS’s findings indicate that Chile is the best country to construct the lithium battery industry. To verify the proposed approach, a comparison analysis also is performed.

Suggested Citation

  • Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2401-:d:858684
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/14/2401/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/14/2401/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jigu Seo & Junhong Park & Yunjung Oh & Sungwook Park, 2016. "Estimation of Total Transport CO 2 Emissions Generated by Medium- and Heavy-Duty Vehicles (MHDVs) in a Sector of Korea," Energies, MDPI, vol. 9(8), pages 1-13, August.
    2. M. Tadaros & A. Migdalas & B. Samuelsson & A. Segerstedt, 2022. "Location of facilities and network design for reverse logistics of lithium-ion batteries in Sweden," Operational Research, Springer, vol. 22(2), pages 895-915, April.
    3. Zhang, Yuanyuan & Zhao, Huiru & Li, Bingkang & Zhao, Yihang & Qi, Ze, 2022. "Research on credit rating and risk measurement of electricity retailers based on Bayesian Best Worst Method-Cloud Model and improved Credit Metrics model in China's power market," Energy, Elsevier, vol. 252(C).
    4. Halit Serdar Saner & Melih Yucesan & Muhammet Gul, 2022. "A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1603-1635, March.
    5. Sina Salimian & Seyed Meysam Mousavi & Jurgita Antucheviciene, 2022. "An Interval-Valued Intuitionistic Fuzzy Model Based on Extended VIKOR and MARCOS for Sustainable Supplier Selection in Organ Transplantation Networks for Healthcare Devices," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    6. Miomir Stanković & Željko Stević & Dillip Kumar Das & Marko Subotić & Dragan Pamučar, 2020. "A New Fuzzy MARCOS Method for Road Traffic Risk Analysis," Mathematics, MDPI, vol. 8(3), pages 1-18, March.
    7. Zhuola Zhang & Shiyuan Lin & Yingjin Ye & Zhao Xu & Yihang Zhao & Huiru Zhao & Jingqi Sun, 2022. "A Hybrid MCDM Model for Evaluating the Market-Oriented Business Regulatory Risk of Power Grid Enterprises Based on the Bayesian Best-Worst Method and MARCOS Approach," Energies, MDPI, vol. 15(9), pages 1-17, April.
    8. Torkayesh, Ali Ebadi & Pamucar, Dragan & Ecer, Fatih & Chatterjee, Prasenjit, 2021. "An integrated BWM-LBWA-CoCoSo framework for evaluation of healthcare sectors in Eastern Europe," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    9. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    10. 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.
    11. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    12. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    13. Jain, P.C., 1993. "Greenhouse effect and climate change: scientific basis and overview," Renewable Energy, Elsevier, vol. 3(4), pages 403-420.
    14. Ecer, Fatih, 2021. "A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tanrıverdi, Gökhan & Ecer, Fatih & Durak, Mehmet Şahin, 2022. "Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology," Journal of Air Transport Management, Elsevier, vol. 105(C).
    2. Marcos Antonio Alves & Ivan Reinaldo Meneghini & António Gaspar-Cunha & Frederico Gadelha Guimarães, 2023. "Machine Learning-Driven Approach for Large Scale Decision Making with the Analytic Hierarchy Process," Mathematics, MDPI, vol. 11(3), pages 1-18, January.

    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. 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.
    2. Himanshu Gupta & Manjeet Kharub & Kumar Shreshth & Ashwani Kumar & Donald Huisingh & Anil Kumar, 2023. "Evaluation of strategies to manage risks in smart, sustainable agri‐logistics sector: A Bayesian‐based group decision‐making approach," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4335-4359, November.
    3. Göçmen Polat, Elifcan & Yücesan, Melih & Gül, Muhammet, 2023. "A comparative framework for criticality assessment of strategic raw materials in Turkey," Resources Policy, Elsevier, vol. 82(C).
    4. Haseli, Gholamreza & Yaran Ögel, İlkin & Ecer, Fatih & Hajiaghaei-Keshteli, Mostafa, 2023. "Luxury in female technology (FemTech): Selection of smart jewelry for women through BCM-MARCOS group decision-making framework with fuzzy ZE-numbers," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Jurgita Kuizinaitė & Mangirdas Morkūnas & Artiom Volkov, 2023. "Assessment of the Most Appropriate Measures for Mitigation of Risks in the Agri-Food Supply Chain," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    6. Gupta, Himanshu & Yadav, Avinash Kumar & Kusi-Sarpong, Simonov & Khan, Sharfuddin Ahmed & Sharma, Shashi Chandra, 2022. "Strategies to overcome barriers to innovative digitalisation technologies for supply chain logistics resilience during pandemic," Technology in Society, Elsevier, vol. 69(C).
    7. Muhammet Deveci & Raghunathan Krishankumar & Ilgin Gokasar & Rumeysa Tuna Deveci, 2023. "Prioritization of healthcare systems during pandemics using Cronbach’s measure based fuzzy WASPAS approach," Annals of Operations Research, Springer, vol. 328(1), pages 279-307, September.
    8. Tanrıverdi, Gökhan & Ecer, Fatih & Durak, Mehmet Şahin, 2022. "Exploring factors affecting airport selection during the COVID-19 pandemic from air cargo carriers’ perspective through the triangular fuzzy Dombi-Bonferroni BWM methodology," Journal of Air Transport Management, Elsevier, vol. 105(C).
    9. Yazdani, Morteza & Torkayesh, Ali Ebadi & Chatterjee, Prasenjit & Fallahpour, Alireza & Montero-Simo, Maria Jose & Araque-Padilla, Rafael A. & Wong, Kuan Yew, 2022. "A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    10. Tushar, Saifur Rahman & Alam, Md. Fahim Bin & Bari, A.B.M. Mainul & Karmaker, Chitra Lekha, 2023. "Assessing the challenges to medical waste management during the COVID-19 pandemic: Implications for the environmental sustainability in the emerging economies," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    11. Feng, Jianghong & Guo, Ping & Xu, Guangyi & Xu, Gangyan & Ning, Yu, 2024. "An integrated decision framework for resilient sustainable waste electric vehicle battery recycling transfer station site selection," Applied Energy, Elsevier, vol. 373(C).
    12. Dilupa Nakandala & Yung Po Tsang & Henry Lau & Carman Ka Man Lee, 2022. "An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    13. Corrente, Salvatore & Greco, Salvatore & Rezaei, Jafar, 2024. "Better decisions with less cognitive load: The Parsimonious BWM," Omega, Elsevier, vol. 126(C).
    14. Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).
    15. Yalcin Kavus, Bahar & Gulum Tas, Pelin & Ayyildiz, Ertugrul & Taskin, Alev, 2022. "A three-level framework to evaluate airline service quality based on interval valued neutrosophic AHP considering the new dimensions," Journal of Air Transport Management, Elsevier, vol. 99(C).
    16. Changzheng Gao & Xiuna Wang & Dongwei Li & Chao Han & Weiyang You & Yihang Zhao, 2023. "A Novel Hybrid Power-Grid Investment Optimization Model with Collaborative Consideration of Risk and Benefit," Energies, MDPI, vol. 16(20), pages 1-23, October.
    17. 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.
    18. Gul, Muhammet & Yucesan, Melih, 2022. "Performance evaluation of Turkish Universities by an integrated Bayesian BWM-TOPSIS model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    19. 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.
    20. Lin, Xueshan & Huang, Tao & Bompard, Ettore & Wang, Beibei & Zheng, Yaxian, 2023. "Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels," Energy, Elsevier, vol. 278(C).

    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:jmathe:v:10:y:2022:i:14:p:2401-:d:858684. 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.