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<p>Crop selection is essential for influencing agricultural production, food security, and environmental sustainability. Agriculturalists encounter a diverse set of issues such as climate change, economic instability, and resource limitations. This study presents a hybrid decision-making framework that integrates two prominent multi-criteria decision-making (MCDM) methods, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and WASPAS (Weighted Aggregated Sum Product Assessment), along with the CRITIC (Criteria Importance through Inter-criteria Correlation) method for the allocation of weights to evaluation criteria. Five alternative crops, such as wheat, rice, potato, sugarcane, and onion, are considered for evaluating an optimal crop selection case study. The objective weighting CRITIC approach assigned higher weights to yield (0.341), followed by fertilizer used (0.268), water requirement, and profit, emphasizing the impact of yield. Potato and sugarcane secured the top ranking and demonstrated the most suitable crops, followed by onion, wheat, and rice, respectively. In sensitivity analysis, WASPAS robustly ranks potato first and identifies it as the most stable and sustainable crop choice, whereas the stability of the TOPSIS approach is reduced. These outcomes evaluate that with greater yield and profitability, balanced resource utilization is the best choice under sustainability-driven evaluations. The proposed CRITIC-WASPAS approach provides a resilient data-driven tool for agriculture decision-making scenarios. This study limits the applicability of the findings to broader agricultural contexts. Therefore, further study may be conducted to consider more diverse criteria and alternatives to evaluate performance by integrating other criteria weighting and MCDM methods in fuzzy environments.</p>

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A CRITIC-Driven MCDM Technique for Crop Selection to Enhance Agricultural Sustainability

  • 期刊论文

  • 发表日期：

    2025年10月27日

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  • Somnath Nandi,
  • Mrinmoy Maity,
  • Somnath Das,
  • Mriganka Maity

摘要

Crop selection is essential for influencing agricultural production, food security, and environmental sustainability. Agriculturalists encounter a diverse set of issues such as climate change, economic instability, and resource limitations. This study presents a hybrid decision-making framework that integrates two prominent multi-criteria decision-making (MCDM) methods, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and WASPAS (Weighted Aggregated Sum Product Assessment), along with the CRITIC (Criteria Importance through Inter-criteria Correlation) method for the allocation of weights to evaluation criteria. Five alternative crops, such as wheat, rice, potato, sugarcane, and onion, are considered for evaluating an optimal crop selection case study. The objective weighting CRITIC approach assigned higher weights to yield (0.341), followed by fertilizer used (0.268), water requirement, and profit, emphasizing the impact of yield. Potato and sugarcane secured the top ranking and demonstrated the most suitable crops, followed by onion, wheat, and rice, respectively. In sensitivity analysis, WASPAS robustly ranks potato first and identifies it as the most stable and sustainable crop choice, whereas the stability of the TOPSIS approach is reduced. These outcomes evaluate that with greater yield and profitability, balanced resource utilization is the best choice under sustainability-driven evaluations. The proposed CRITIC-WASPAS approach provides a resilient data-driven tool for agriculture decision-making scenarios. This study limits the applicability of the findings to broader agricultural contexts. Therefore, further study may be conducted to consider more diverse criteria and alternatives to evaluate performance by integrating other criteria weighting and MCDM methods in fuzzy environments.