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ارزیابی خطر زنجیره تأمین شرکتهای کوچک و متوسط در اثر تهدیدات اقتصادی با رویکرد یکپارچه فازی | ||
پدافند غیرعامل | ||
دوره 15، شماره 3 - شماره پیاپی 59، آبان 1403، صفحه 39-53 اصل مقاله (1.48 M) | ||
نوع مقاله: مقاله پژوهشی | ||
نویسندگان | ||
حامد اصغری1؛ محمد اسکندری* 2؛ مسعود دارابی3؛ مهدی مدیری4 | ||
1کارشناسی ارشد مدیریت بحران، مجتمع دانشگاهی مهندسی و پدافند غیر عامل، دانشگاه صنعتی مالک اشتر، تهران، ایران | ||
2استادیار، مجتمع دانشگاهی مهندسی و پدافند غیر عامل، دانشگاه صنعتی مالک اشتر ، تهران، ایران | ||
3استادیار، مجتمع دانشگاهی مهندسی و پدافند غیر عامل، دانشگاه صنعتی مالک اشتر، تهران، ایران | ||
4استاد، مجتمع دانشگاهی مهندسی و پدافند غیر عامل، دانشگاه صنعتی مالک اشتر، تهران، ایران | ||
تاریخ دریافت: 01 خرداد 1403، تاریخ بازنگری: 28 مرداد 1403، تاریخ پذیرش: 01 مهر 1403 | ||
چکیده | ||
زنجیره تأمین از چندین حلقه تشکیل شده است که از نقطه تولید تا نقطه مصرف امتداد دارد؛ ایجاد تحریمهای بینالمللی در تأمین تجهیزات و تعمیر قطعات زیرساختهای حیاتی و حساس کشور چالشهای زیادی را ممکن است ایجاد کند که این پدافند غیرعامل اقتصادی نقش بسزایی در رشد اقتصادی، تابآوری، ایجاد اشتغال و... دارند؛ یک زنجیره تأمین ناقص ممکن است یک فاجعه ایجاد کند؛ در چنین شرایطی، شناسایی مناسب عوامل خطر برای دستیابی به یک زنجیره تأمین تابآور در برابر اثرات مخرب تهدیدات و اختلالات حیاتی است؛ از اینرو، این تحقیق با شناسایی عوامل زنجیره تأمین و تجزیه و تحلیل ارتباط آنها با استفاده از یک رویکرد یکپارچه، از جمله تحلیل پارتو، نظریه فازی، مدلسازی ساختاری تفسیری کل و یک تحلیل طبقهبندی شده و تعیین سطح و رتبهبندی خطرها، این خلاء تحقیقاتی را پر میکند؛ یافتههای تحقیق نشان میدهد که دانش ناکافی، تغییرات زیست محیطی و عدم وجود سامانه ردیابی و کنترل، مهمترین عوامل هستند؛ علاوه بر آن، عدم ثبات سیاسی و نظارتی، آلودگی و عدم صلاحیت پیمانکاران نیز برخی از خطرات حیاتی هستند که ممکن است مانع تابآوری و عملکرد مطلوب در شرکتهای کوچک و متوسط شوند. نتایج تحقیق به مدیران جهت شناسایی موفقیتآمیز عوامل خطر برای دستیابی به تابآوری عملیاتی و بلندمدت کمک میکند؛ همچنین میتواند، توانایی سیاستگذاران را برای تدوین راهبردهای کاهش پیشگیرانه و کارآمد افزایش دهد. | ||
کلیدواژهها | ||
مدلسازی ساختاری تفسیری؛ تحلیل پارتو؛ پدافند غیرعامل اقتصادی؛ تابآوری؛ زنجیره تأمین | ||
عنوان مقاله [English] | ||
Assessing the Supply Chain Risk of Small and Medium Companies Due to Economic Threats with a Fuzzy Integrated Approach | ||
نویسندگان [English] | ||
hamed asghari1؛ Mohammad Eskandari2؛ masuod darabi3؛ Mahdi Modiri4 | ||
1- | ||
2Researcher Malek Ashtar University of Technology, Tehran, Iran | ||
3Director-in-Charge | ||
4Maleke- Ashtar University of Technology | ||
چکیده [English] | ||
The supply chain consists of several links that extend from the point of production to the point of consumption; The establishment of international sanctions in the provision of equipment and repair of vital and sensitive infrastructure parts of the country may create many challenges, as these non-functional economic defenses play a significant role in economic growth, resilience, job creation, etc.; A flawed supply chain can create a disaster; In such a situation, proper identification of risk factors is critical to achieve a resilient supply chain against the destructive effects of threats and disruptions; Hence, this research by identifying the factors of the supply chain and analyzing their relationship using an integrated approach, including Pareto analysis, fuzzy theory, total interpretative structural modeling and a categorical analysis and determining the level and ranking of risks, this research gap. fills The findings of the research show that insufficient knowledge, environmental changes and the absence of a diagnosis and control system are the most important factors; In addition to that, political and regulatory instability, pollution and contractors' incompetence are some of the critical risks that may hinder resilience and optimal performance in small and medium-sized companies. Research results help managers to successfully identify risk factors to achieve operational and long-term resilience; It can also increase the ability of policy makers to formulate preventive and efficient mitigation strategies. | ||
کلیدواژهها [English] | ||
Interpretive Structural Modeling, Pareto Analysis, Economic Passive Defense, Resilience, Supply Chain | ||
مراجع | ||
[1] S. Das et al., “A systematic assessment of multi‐dimensional risk factors for sustainable development in food grain supply chains: A business strategic prospective analysis,” Apr. 2023, doi: https://doi.org/10.1002/bse.3435. [2] D. Kumar and P. Kalita, “Reducing Postharvest Losses during Storage of Grain Crops to Strengthen Food Security in Developing Countries,” Foods, vol. 6, no. 1, p. 8, Jan. 2017, doi: https://doi.org/10.3390/foods6010008. [3] Pallawi Baldeo Sangode, “Supply chain risk model for cement industry based on interpretive structural model driven by FMEA,” Journal of Industrial Engineering and Management, vol. 16, no. 3, pp. 473–473, Oct. 2023, doi: https://doi.org/10.3926/jiem.5643. [4] S. Lahane and R. Kant, “Evaluation and Ranking of Solutions to Mitigate Circular Supply Chain Risks,” Sustainable Production and Consumption, Feb. 2021, doi: https://doi.org/10.1016/j.spc.2021.01.034. [5] C.-Y. Chu, K. Park, and G. E. Kremer, “A global supply chain risk management framework: An application of text-mining to identify region-specific supply chain risks,” Advanced Engineering Informatics, vol. 45, p. 101053, Aug. 2020, doi: https://doi.org/10.1016/j.aei.2020.101053. [6] Y. Yang, L. Xu, X. Chu, R. Pang, and Z. Zhang, “Research on financing availability of small and micro logistics enterprises in China,” International Journal of Applied Decision Sciences, vol. 16, no. 5, pp. 587–612, Jan. 2023, doi: https://doi.org/10.1504/ijads.2023.133150. [7] S. Weaven, S. Quach, P. Thaichon, L. Frazer, K. Billot, and D. Grace, “Surviving an economic downturn: Dynamic capabilities of SMEs,” Journal of Business Research, vol. 128, pp. 109–123, May 2021. [8] S. Rakshit, N. Islam, S. Mondal, and T. Paul, “Influence of blockchain technology in SME internationalization: Evidence from high-tech SMEs in India,” Technovation, vol. 115, p. 102518, Mar. 2022, doi: https://doi.org/10.1016/j.technovation.2022.102518. [9] H. Babu and S. Yadav, “A Supply Chain Risk Assessment Index for Small and Medium Enterprises in Post COVID-19 Era,” pp. 100023–100023, Jun. 2023, doi: https://doi.org/10.1016/j.sca.2023.100023. [10] A. Spieske, M. Gebhardt, M. Kopyto, H. Birkel, and E. Hartmann, “The future of industry 4.0 and supply chain resilience after the COVID-19 pandemic: Empirical evidence from a Delphi study,” Computers & Industrial Engineering, vol. 181, p. 109344, Jul. 2023, doi: https://doi.org/10.1016/j.cie.2023.109344. [11] S. Chatterjee, R. Chaudhuri, M. Shah, and P. Maheshwari, “Big data driven innovation for sustaining SME supply chain operation in post COVID-19 scenario: Moderating role of SME technology leadership,” Computers & Industrial Engineering, vol. 168, p. 108058, Mar. 2022, doi: https://doi.org/10.1016/j.cie.2022.108058. [12] T. Mishra, S. Chatterjee, and J. J. Thakkar, “Effect of coronavirus pandemic in changing the performance barriers for textile and apparel industry in an emerging market,” Journal of Cleaner Production, p. 136097, Jan. 2023, doi: https://doi.org/10.1016/j.jclepro.2023.136097. [13] S. Gokarn and T. S. Kuthambalayan, “Analysis of challenges inhibiting the reduction of waste in food supply chain,” Journal of Cleaner Production, vol. 168, pp. 595–604, Dec. 2017, doi: https://doi.org/10.1016/j.jclepro.2017.09.028. [14] S. Mithun Ali, Md. A. Moktadir, G. Kabir, J. Chakma, Md. J. U. Rumi, and Md. T. Islam, “Framework for evaluating risks in food supply chain: Implications in food wastage reduction,” Journal of Cleaner Production, vol. 228, no. 1, pp. 786–800, Aug. 2019, doi: https://doi.org/10.1016/j.jclepro.2019.04.322. [15] A. Kumar, S. K. Mangla, P. Kumar, and S. Karamperidis, “Challenges in perishable food supply chains for sustainability management: A developing economy perspective,” Business Strategy and the Environment, vol. 29, no. 5, Jan. 2020, doi: https://doi.org/10.1002/bse.2470. [16] E. K. Ling and S. N. Wahab, “Integrity of food supply chain: going beyond food safety and food quality,” International Journal of Productivity and Quality Management, vol. 29, no. 2, p. 216, 2020, doi: https://doi.org/10.1504/ijpqm.2020.105963. [17] A. Gurtu and J. Johny, “Supply chain risk management: Literature review,” Risks, vol. 9, no. 1, pp. 1–16, 2021, doi: https://doi.org/10.3390/risks9010016. [18] R. Rathore, J. J. Thakkar, and J. K. Jha, “Evaluation of risks in foodgrains supply chain using failure mode effect analysis and fuzzy VIKOR,” International Journal of Quality & Reliability Management, vol. 38, no. 2, pp. 551–580, Jul. 2020, doi: https://doi.org/10.1108/ijqrm-02-2019-0070. [19] A. Díaz-Curbelo, R. A. Espin Andrade, and Á. M. Gento Municio, “The Role of Fuzzy Logic to Dealing with Epistemic Uncertainty in Supply Chain Risk Assessment: Review Standpoints,” International Journal of Fuzzy Systems, vol. 22, no. 8, pp. 2769–2791, Jun. 2020, doi: https://doi.org/10.1007/s40815-020-00846-5. [20] S. Prakash, G. Soni, A. P. S. Rathore, and S. Singh, “Risk analysis and mitigation for perishable food supply chain: a case of dairy industry,” Benchmarking: An International Journal, vol. 24, no. 1, pp. 2–23, Feb. 2017, doi: https://doi.org/10.1108/bij-07-2015-0070. [21] H. Babu, P. Bhardwaj, and A. K. Agrawal, “Modelling the supply chain risk variables using ISM: a case study on Indian manufacturing SMEs,” Journal of Modelling in Management, vol. 16, no. 1, pp. 215–239, Jun. 2020, doi: https://doi.org/10.1108/jm2-06-2019-0126. [22] Tigist Mekonnen Melesse, Thủy Nguyễn, and Getachew Mullu Kassa, “Tracking the COVID-19 vaccine equity, distribution, and cases in the global south,” medRxiv (Cold Spring Harbor Laboratory), Dec. 2022, doi: https://doi.org/10.1101/2022.12.19.22283681. [23] D. Ivanov, B. Sokolov, and A. Dolgui, “The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management,” International Journal of Production Research, vol. 52, no. 7, pp. 2154–2172, Nov. 2014, doi: https://doi.org/10.1080/00207543.2013.858836. [24] D. A. Rangel, T. K. de Oliveira, and M. S. A. Leite, “Supply chain risk classification: discussion and proposal,” International Journal of Production Research, vol. 53, no. 22, pp. 6868–6887, May 2015, doi: https://doi.org/10.1080/00207543.2014.910620. [25] A. Dolgui, D. Ivanov, and B. Sokolov, “Ripple effect in the supply chain: an analysis and recent literature,” International Journal of. [26] A. Asgary, A. I. Ozdemir, and H. Özyürek, “Small and Medium Enterprises and Global Risks: Evidence from Manufacturing SMEs in Turkey,” International Journal of Disaster Risk Science, vol. 11, no. 1, pp. 59–73, Feb. 2020, doi: https://doi.org/10.1007/s13753-020-00247-0. [27] U. S. K. D. Silva, A. Paul, K. W. Hasan, S. K. Paul, S. M. Ali, and R. K. Chakrabortty, “Examining risks and strategies for the spice processing supply chain in the context of an emerging economy,” International Journal of Emerging Markets, Jun. 2021, doi: https://doi.org/10.1108/ijoem-07-2020-0776. [28] R. Kumar, R. K. Singh, and R. Shankar, “Strategy development by Indian SMEs for improving coordination in supply chain,” Competitiveness Review, vol. 24, no. 5, pp. 414–432, Oct. 2014, doi: https://doi.org/10.1108/cr-06-2012-0016. [29] S. Mithun Ali et al., “Modelling of supply chain disruption analytics using an integrated approach: An emerging economy example,” Expert Systems with Applications, vol. 173, p. 114690, Jul. 2021, doi: https://doi.org/10.1016/j.eswa.2021.114690. [30] C. L. Karmaker, R. A. Aziz, T. Palit, and A. B. M. M. Bari, “Analyzing Supply Chain Risk Factors in the Small and Medium Enterprises Under Fuzzy Environment: Implications Towards Sustainability for Emerging Economies,” Sustainable Technology and Entrepreneurship, vol. 2, no. 1, p. 100032, Nov. 2022, doi: https://doi.org/10.1016/j.stae.2022.100032. [31] Md. F. B. Alam, S. R. Tushar, S. Md. Zaman, E. D. R. S. Gonzalez, A. B. M. M. Bari, and C. L. Karmaker, “Analysis of the drivers of Agriculture 4.0 implementation in the emerging economies: Implications towards sustainability and food security,” Green Technologies and Sustainability, vol. 1, no. 2, p. 100021, May 2023, doi: https://doi.org/10.1016/j.grets.2023.100021. [32] D. Adams, J. Donovan, and C. Topple, “Achieving Sustainability in Food Manufacturing Operations and their Supply Chains: Key Insights from a Systematic Literature Review,” Sustainable Production and Consumption, vol. 28, pp. 1491–1499, Aug. 2021, doi: https://doi.org/10.1016/j.spc.2021.08.019. [33] V. Desingh and B. R, “Internet of Things adoption barriers in the Indian healthcare supply chain: An ISM‐fuzzy MICMAC approach,” The International Journal of Health Planning and Management, vol. 37, no. 1, Sep. 2021, doi: https://doi.org/10.1002/hpm.3331. [34] H. Taherdoost and M. Madanchian, “Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce,” Electronics, vol. 10, no. 13, p. 1547, Jun. 2021, doi: https://doi.org/10.3390/electronics10131547. [35] V. Jain and V. K. Soni, “Modeling and analysis of FMS performance variables by fuzzy TISM,” Journal of Modelling in Management, vol. 14, no. 1, pp. 2–30, Feb. 2019, doi: https://doi.org/10.1108/jm2-03-2018-0036. [36] Md. Z. Anam, A. B. M. M. Bari, S. K. Paul, S. M. Ali, and G. Kabir, “Modelling the drivers of solar energy development in an emerging economy: Implications for sustainable development goals,” Resources, Conservation & Recycling Advances, vol. 13, p. 200068, May 2022, doi: https://doi.org/10.1016/j.rcradv.2022.200068. [37] S. R. Tushar, Md. F. B. Alam, A. B. M. M. Bari, and C. L. Karmaker, “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, p. 101513, Jan. 2023, doi: https://doi.org/10.1016/j.seps.2023.101513. [38] M. M. Rahman, A. B. M. M. Bari, S. M. Ali, and A. Taghipour, “Sustainable supplier selection in the textile dyeing industry: An integrated multi-criteria decision analytics approach,” Resources, Conservation & Recycling Advances, vol. 15, p. 200117, Nov. 2022, doi: https://doi.org/10.1016/j.rcradv.2022.200117. [39] S. Aicevarya Devi, A. Felix, S. Narayanamoorthy, A. Ahmadian, D. Balaenu, and D. Kang, “An intuitionistic fuzzy decision support system for COVID-19 lockdown relaxation protocols in India,” Computers and Electrical Engineering, vol. 102, p. 108166, Sep. 2022, doi: https://doi.org/10.1016/j.compeleceng.2022.108166. [40] E. Kanire, Elibariki Msuya, and R. Alphonce, “Drivers of dairy farmers’ engagement in informal milk markets: Policy implications for developing countries,” Journal of Agriculture and Food Research, vol. 16, pp. 101128–101128, Jun. 2024, doi: https://doi.org/10.1016/j.jafr.2024.101128. [41] M. Ammar, A. Haleem, M. Javaid, R. Walia, and S. Bahl, “Improving material quality management and manufacturing organizations system through Industry 4.0 technologies,” Materials Today: Proceedings, vol. 45, no. 6, Feb. 2021, doi: https://doi.org/10.1016/j.matpr.2021.01.585. [42] R. B. Chowdhury et al., “Environmental externalities of the COVID-19 lockdown: Insights for sustainability planning in the Anthropocene,” Science of The Total Environment, vol. 783, p. 147015, Aug. 2021, doi: https://doi.org/10.1016/j.scitotenv.2021.147015. [43] S. K. Sek, “Impact of oil price changes on domestic price inflation at disaggregated levels: Evidence from linear and nonlinear ARDL modeling,” Energy, vol. 130, pp. 204–217, Jul. 2017, doi: https://doi.org/10.1016/j.energy.2017.03.152. [44] L. Kilian and X. Zhou, “The impact of rising oil prices on U.S. inflation and inflation expectations in 2020–23,” Energy Economics, vol. 113, p. 106228, Aug. 2022, doi: https://doi.org/10.1016/j.eneco.2022.106228. [45] Y. Liang, “HTML5-based Graphic Image Processing and Collaborative Drawing Technology,” Systems and soft computing, pp. 200076–200076, Jan. 2024, doi: https://doi.org/10.1016/j.sasc.2024.200076. [46] M. Krivoshapkina, Y.-S. Choi, Maria Listan Bernal, and G.-T. Yeo, “Vitalizing logistics strategies for Tiksi Port using the interpretive structural modelling method,” The Asian Journal of Shipping and Logistics, Jan. 2024, doi: https://doi.org/10.1016/j.ajsl.2023.12.004. [47] M. Bani-Doumi, J. Serrano-Guerrero, F. Chiclana, F. P. Romero, and J. A. Olivas, “A picture fuzzy set multi criteria decision-making approach to customize hospital recommendations based on patient feedback,” Applied soft computing, vol. 153, pp. 111331–111331, Mar. 2024, doi: https://doi.org/10.1016/j.asoc.2024.111331. [48] Gülçin Büyüközkan, Yağmur Karabulut, and Fethullah Göçer, “Spherical Fuzzy Sets based Integrated DEMATEL, ANP, VIKOR Approach and its application for Renewable Energy Selection in Turkey,” Applied Soft Computing, pp. 111465–111465, Mar. 2024, doi: https://doi.org/10.1016/j.asoc.2024.111465. [49] H. Karimi, M. Sadeghi-Dastaki, and M. Javan, “A fully fuzzy best–worst multi attribute decision making method with triangular fuzzy number: A case study of maintenance assessment in the hospitals,” Applied Soft Computing, p. 105882, Oct. 2019, doi: https://doi.org/10.1016/j.asoc.2019.105882. [50] Bartłomiej Kizielewicz and L. Dobryakova, “Stochastic Triangular Fuzzy Number (S-TFN) Normalization: A New Approach for Nonmonotonic Normalization,” Procedia Computer Science, vol. 225, pp. 4901–4911, Jan. 2023, doi: https://doi.org/10.1016/j.procs.2023.10.490. [51] X. Zhang, S. Yan, and X. Liu, “Extended cognitive reliability and error analysis method for advanced control rooms of nuclear power plants,” Nuclear Engineering and Technology, Apr. 2024, doi: https://doi.org/10.1016/j.net.2024.03.044. [52] S. Vinodh, S. R. Devadasan, K. E. K. Vimal, and D. Kumar, “Design of agile supply chain assessment model and its case study in an Indian automotive components manufacturing organization,” Journal of Manufacturing Systems, vol. 32, no. 4, pp. 620–631, Oct. 2013, doi: https://doi.org/10.1016/j.jmsy.2013.04.001. [53] V. Vaishnavi and M. Suresh, “Assessment of healthcare organizational readiness for change: A fuzzy logic approach,” Journal of King Saud University - Engineering Sciences, vol. 34, no. 3, pp. 189–197, Sep. 2020, doi: https://doi.org/10.1016/j.jksues.2020.09.008. [54] C. L. Karmaker, T. Ahmed, S. Ahmed, S. M. Ali, Md. A. Moktadir, and G. Kabir, “Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: Exploring drivers using an integrated model,” Sustainable Production and Consumption, vol. 26, no. 2, pp. 411–427, Apr. 2021, doi: https://doi.org/10.1016/j.spc.2020.09.019. [55] P. Zhang, S. Ma, Y. Zhao, J. Ling, and Y. Sun, “Analysing Influencing Factors and Correlation Paths of Learning Burnout among Secondary Vocational Students in the context of Social Media: An Integrated ISM–MICMAC Approach,” Heliyon (Londen), pp. e28696–e28696, Mar. 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e28696. [56] Petai Chuaphun and Taweesak Samanchuen, “Exploring success factors and relationships in virtual learning using ISM and fuzzy MICMAC analysis,” Heliyon, vol. 10, no. 7, pp. e28100–e28100, Apr. 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e28100. [57] S. Kadam and P. K. Bandyopadhyay, “Modelling passenger interaction process (PIP) framework using ISM and MICMAC approach,” Journal of Rail Transport Planning & Management, vol. 14, p. 100171, Jun. 2020, doi: https://doi.org/10.1016/j.jrtpm.2019.100171. [58] H. Zhang, X. Wu, and M. Ju, “Developing a cognitive model of solid geometry based on Interpretive Structural Modeling method,” Heliyon, pp. e27063–e27063, Feb. 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e27063. [59] N. Singh, Rajeswari Panigrahi, Rashmi Ranjan Panigrahi, and A. K. Shrivastava, “An integrated total interpretive structural modeling and MICMAC model for uncovering enterprise agility barriers in the insurance industry,” Decision Analytics Journal, pp. 100421–100421, Feb. 2024, doi: https://doi.org/10.1016/j.dajour.2024.100421. [60] L. G. Bobadilla, Jonathan-Alberto Campos Trigoso, del Pilar, Pablo-Alfredo Rituay Trujillo, and M. Oliva, “Structural analysis of the future of the coffee industry in the Amazonas region using a MICMAC approach,” Heliyon, vol. 10, no. 7, pp. e27827–e27827, Apr. 2024, doi: https://doi.org/10.1016/j.heliyon.2024.e27827. [61] Wang Yi-yan et al., “Design recommendations of target size and tracking speed under circular and square trajectories for smooth pursuit with Euclidean algorithm in eye-control system,” Displays, vol. 81, pp. 102608–102608, Jan. 2024, doi: https://doi.org/10.1016/j.displa.2023.102608. [62] Maaret Jokela-Pansini, R. Ippolito, B. Greenhough, and A. Lora-Wainwright, “Creating safety amidst chronic contamination: A mixed-method analysis of residents’ experiences in a Southern Italian steel town,” Social Science & Medicine, vol. 349, pp. 116866–116866, May 2024, doi: https://doi.org/10.1016/j.socscimed.2024.116866. [63] Steven Qiang Lu, J. P. Vassallo, A. Choi, and J. Li, “The Role of Political Ideology on Variety-Seeking Behavior During Crisis-Induced Threats: Evidence from the COVID-19 Pandemic,” Journal of Retailing, Apr. 2024, doi: https://doi.org/10.1016/j.jretai.2024.03.003. [64] N. N. Kourgialas, “A critical review of water resources in Greece: The key role of agricultural adaptation to climate-water effects,” Science of The Total Environment, vol. 775, p. 145857, Jun. 2021, doi: https://doi.org/10.1016/j.scitotenv.2021.145857. [65] Y. Chen, Q. Fu, V. P. Singh, Y. Ji, M. Li, and Y. Wang, “Optimization of agricultural soil and water resources under fuzzy and random uncertainties: Synergy and trade-off between equity-based economic benefits, nonpoint pollution and water use efficiency,” Agricultural Water Management, vol. 281, p. 108264, May 2023, doi: https://doi.org/10.1016/j.agwat.2023.108264. [66] Md. Tanvir Siraj, B. Debnath, Spandan Basak Payel, A.B.M. Mainul Bari, and Abu, “Analysis of the fire risks and mitigation approaches in the apparel manufacturing industry: Implications toward operational safety and sustainability,” Heliyon, vol. 9, no. 9, pp. e20312–e20312, Sep. 2023, doi: https://doi.org/10.1016/j.heliyon.2023.e20312. [67] S. Dong, X. Gao, A. Mostafavi, J. Gao, and Utkarsh Gangwal, “Characterizing resilience of flood-disrupted dynamic transportation network through the lens of link reliability and stability,” Reliability Engineering & System Safety, vol. 232, pp. 109071–109071, Apr. 2023, doi: https://doi.org/10.1016/j.ress.2022.109071. | ||
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