IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v82y2023ics0301420723002192.html
   My bibliography  Save this article

A comparative framework for criticality assessment of strategic raw materials in Turkey

Author

Listed:
  • Göçmen Polat, Elifcan
  • Yücesan, Melih
  • Gül, Muhammet

Abstract

The rapid development of innovative technologies, population growth, shifting resource management patterns, and decarbonization challenges are expected to increase the demand for raw materials labeled as critical in the following years. The increasing concerns have led to evaluate the critical raw materials (CRMs) with high economic importance and supply risk. In this context, this paper aims to develop a conceptual methodology to identify CRMs in Turkey. The methodology integrates a multi-criteria decision-making method (MCDM) to provide the raw material criticality matrix regarding various criteria, the EU (European Union) method, which represents supply risk and economic importance indicators, and the time series analysis method, in which dynamic evaluation of materials over time instead of the static indicators. We first provide a Bayesian Best-Worst method (B-BWM) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) based model for the criticality matrix, which enables evaluations of participated experts to be combined to reveal the weights of the criteria and sub-criteria from a probabilistic point of view without loss of knowledge. The main and sub-criteria include supply risk and economic importance, which are frequently studied in the literature, but also environment, price, secondary production, and socio-economic indicators are evaluated in the criticality matrix. Then, exponential smoothing forecast, one of the Time Series Analysis models, which determine the element criticality in the perspective of future years with the data of import figures of Turkey, is superior to the other models. Finally, with some modifications, the EU criticality methodology is used to quantify the raw materials regarding each material associated with the sector applications and their value-added and supply disruptions. Thus, a comprehensive criticality list integrating the results of the three mentioned methods is important because Turkey's raw materials characterize many sectors. The findings should also interest practitioners and researchers as the detailed assessment of raw material criticality ensures a sufficient database for future studies.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jrpoli:v:82:y:2023:i:c:s0301420723002192
    DOI: 10.1016/j.resourpol.2023.103511
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723002192
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103511?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sarita Gajbhiye Meshram & Ehsan Alvandi & Chandrashekhar Meshram & Ercan Kahya & Ayad M. Fadhil Al-Quraishi, 2020. "Application of SAW and TOPSIS in Prioritizing Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 715-732, January.
    2. T. E. Graedel & Barbara K. Reck, 2016. "Six Years of Criticality Assessments: What Have We Learned So Far?," Journal of Industrial Ecology, Yale University, vol. 20(4), pages 692-699, August.
    3. Blengini, Gian Andrea & Nuss, Philip & Dewulf, Jo & Nita, Viorel & Peirò, Laura Talens & Vidal-Legaz, Beatriz & Latunussa, Cynthia & Mancini, Lucia & Blagoeva, Darina & Pennington, David & Pellegrini,, 2017. "EU methodology for critical raw materials assessment: Policy needs and proposed solutions for incremental improvements," Resources Policy, Elsevier, vol. 53(C), pages 12-19.
    4. Glöser, Simon & Tercero Espinoza, Luis & Gandenberger, Carsten & Faulstich, Martin, 2015. "Raw material criticality in the context of classical risk assessment," Resources Policy, Elsevier, vol. 44(C), pages 35-46.
    5. Christoph Helbig & Martin Bruckler & Andrea Thorenz & Axel Tuma, 2021. "An Overview of Indicator Choice and Normalization in Raw Material Supply Risk Assessments," Resources, MDPI, vol. 10(8), pages 1-26, August.
    6. Disna Eheliyagoda & Xianlai Zeng & Jinhui Li, 2020. "A method to assess national metal criticality: the environment as a foremost measurement," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-12, December.
    7. Kim, Juhan & Lee, Jungbae & Kim, BumChoong & Kim, Jinsoo, 2019. "Raw material criticality assessment with weighted indicators: An application of fuzzy analytic hierarchy process," Resources Policy, Elsevier, vol. 60(C), pages 225-233.
    8. 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).
    9. 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.
    10. Mehmet Balcilar & Gizem Uzuner & Chinazaekpere Nwani & Festus Victor Bekun, 2023. "Boosting Energy Efficiency in Turkey: The Role of Public–Private Partnership Investment," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    11. Pranith Kumar Roy & Krishnendu Shaw, 2022. "Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5368-5399, April.
    12. Huang, Chun-Nen & Liou, James J.H. & Lo, Huai-Wei & Chang, Fu-Jung, 2021. "Building an assessment model for measuring airport resilience," Journal of Air Transport Management, Elsevier, vol. 95(C).
    13. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    14. Hasan Mahbub Tusher & Ziaul Haque Munim & Theo E. Notteboom & Tae-Eun Kim & Salman Nazir, 2022. "Cyber security risk assessment in autonomous shipping," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 208-227, June.
    15. Wan-Chi Jackie Hsu & Huai-Wei Lo & Chin-Cheng Yang, 2021. "The Formulation of Epidemic Prevention Work of COVID-19 for Colleges and Universities: Priorities and Recommendations," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    16. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    17. Hayes, Sarah M. & McCullough, Erin A., 2018. "Critical minerals: A review of elemental trends in comprehensive criticality studies," Resources Policy, Elsevier, vol. 59(C), pages 192-199.
    18. Longxiao Li & Xu Wang & Jafar Rezaei, 2020. "A Bayesian Best-Worst Method-Based Multicriteria Competence Analysis of Crowdsourcing Delivery Personnel," Complexity, Hindawi, vol. 2020, pages 1-17, October.
    19. Mingliang Liang & Wenxuan Li & Jie Ji & Zhenxi Zhou & Yihang Zhao & Huiru Zhao & Sen Guo & Chiranjibe Jana, 2022. "Evaluating the Comprehensive Performance of 5G Base Station: A Hybrid MCDM Model Based on Bayesian Best-Worst Method and DQ-GRA Technique," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-15, January.
    20. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    21. Goe, Michele & Gaustad, Gabrielle, 2014. "Identifying critical materials for photovoltaics in the US: A multi-metric approach," Applied Energy, Elsevier, vol. 123(C), pages 387-396.
    22. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    23. Jen-Jen Yang & Yen-Ching Chuang & Huai-Wei Lo & Ting-I Lee, 2020. "A Two-Stage MCDM Model for Exploring the Influential Relationships of Sustainable Sports Tourism Criteria in Taichung City," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    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. Daniele Perossa & Paolo Rosa & Sergio Terzi, 2024. "A Systematic Literature Review of Existing Methods and Tools for the Criticality Assessment of Raw Materials: A Focus on the Relations between the Concepts of Criticality and Environmental Sustainabil," Resources, MDPI, vol. 13(9), pages 1-18, September.

    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. Christoph Helbig & Martin Bruckler & Andrea Thorenz & Axel Tuma, 2021. "An Overview of Indicator Choice and Normalization in Raw Material Supply Risk Assessments," Resources, MDPI, vol. 10(8), pages 1-26, August.
    2. Clement Bonnet & Samuel Carcanague & Emmanuel Hache & Gondia Seck & Marine Simoën, 2019. "Vers une Géopolitique de l'énergie plus complexe ? Une analyse prospective tridimensionnelle de la transition énergétique," Working Papers hal-02971706, HAL.
    3. 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).
    4. Clément Bonnet & Samuel Carcanague & Emmanuel Hache & Gondia Sokhna Seck & Marine Simoën, 2019. "Some Geopolitical issues of the Energy Transition," Working Papers hal-03191388, HAL.
    5. Kim, Juhan & Lee, Jungbae & Kim, BumChoong & Kim, Jinsoo, 2019. "Raw material criticality assessment with weighted indicators: An application of fuzzy analytic hierarchy process," Resources Policy, Elsevier, vol. 60(C), pages 225-233.
    6. 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.
    7. Corrente, Salvatore & Greco, Salvatore & Rezaei, Jafar, 2024. "Better decisions with less cognitive load: The Parsimonious BWM," Omega, Elsevier, vol. 126(C).
    8. 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).
    9. 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.
    10. Marie K. Schellens & Johanna Gisladottir, 2018. "Critical Natural Resources: Challenging the Current Discourse and Proposal for a Holistic Definition," Resources, MDPI, vol. 7(4), pages 1-28, December.
    11. Alexander Kuan Daiy & Kao-Yi Shen & Jim-Yuh Huang & Tom Meng-Yen Lin, 2021. "A Hybrid MCDM Model for Evaluating Open Banking Business Partners," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    12. 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).
    13. Vineet Kaushik & Shobha Tewari, 2023. "Modeling Opportunity Indicators Fostering Social Entrepreneurship: A Hybrid Delphi and Best-Worst Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 667-698, August.
    14. Vidal, Rosario & Alberola-Borràs, Jaume-Adrià & Mora-Seró, Iván, 2020. "Abiotic depletion and the potential risk to the supply of cesium," Resources Policy, Elsevier, vol. 68(C).
    15. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    16. Wu, Qun & Liu, Xinwang & Zhou, Ligang & Qin, Jindong & Rezaei, Jafar, 2024. "An analytical framework for the best–worst method," Omega, Elsevier, vol. 123(C).
    17. 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).
    18. Mitja Mori & Rok Stropnik & Mihael Sekavčnik & Andrej Lotrič, 2021. "Criticality and Life-Cycle Assessment of Materials Used in Fuel-Cell and Hydrogen Technologies," Sustainability, MDPI, vol. 13(6), pages 1-29, March.
    19. Fahim, Patrick B.M. & Rezaei, Jafar & Montreuil, Benoit & Tavasszy, Lorant, 2022. "Port performance evaluation and selection in the Physical Internet," Transport Policy, Elsevier, vol. 124(C), pages 83-94.
    20. Kühnel, Konstantin & Schütte, Philip & Bach, Vanessa & Franken, Gudrun & Finkbeiner, Matthias, 2023. "Correlation analysis of country governance indicators and the magnitude of environmental and social incidents in mining," Resources Policy, Elsevier, vol. 85(PA).

    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:eee:jrpoli:v:82:y:2023:i:c:s0301420723002192. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.