A Novel Approach to Integrating Community Knowledge into Fuzzy Logic-Adapted Spatial Modeling in the Analysis of Natural Resource Conflicts

Lawrence Ibeh (), Kyriakos Kouveliotis, Deepak Rajendra Unune, Nguyen Manh Cuong, Noah Mutai, Anastasios Fountis, Svitlana Samoylenko, Priyadarshini Pattanaik, Sushma Kumari, Benjamin Bensam Sambiri, Sulekha Mohamud and Alina Baskakova
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Lawrence Ibeh: Faculty of Computer Science & Informatics, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Kyriakos Kouveliotis: Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Deepak Rajendra Unune: Department of Mechanical-Mechatronics Engineering, The LNM Institute of Information Technology, Jaipur 302031, India
Nguyen Manh Cuong: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Noah Mutai: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Anastasios Fountis: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Svitlana Samoylenko: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Priyadarshini Pattanaik: Faculty of Computer Science & Informatics, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Sushma Kumari: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Benjamin Bensam Sambiri: Faculty of Economics & Business Administration, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Sulekha Mohamud: Faculty of Computer Science & Informatics, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany
Alina Baskakova: Faculty of Computer Science & Informatics, Berlin School of Business and Innovation (BSBI), Berlin Campus, 12043 Berlin, Germany

Sustainability, 2025, vol. 17, issue 5, 1-49

Abstract: Resource conflicts constitute a major global issue in areas rich in natural resources. The modeling of factors influencing natural resource conflicts (NRCs), including environmental, health, socio-economic, political, and legal aspects, presents a significant challenge compounded by inadequate data. Quantitative research frequently emphasizes large-scale conflicts. This study presents a novel multilevel approach, SEFLAME-CM—Spatially Explicit Fuzzy Logic-Adapted Model for Conflict Management—for advancing understanding of the relationship between NRCs and drivers under territorial and rebel-based typologies at a community level. SEFLAME-CM is hypothesized to yield a more robust positive correlation between the risk of NRCs and the interacting conflict drivers, provided that the conflict drivers and input variables remain the same. Local knowledge from stakeholders is integrated into spatial decision-making tools to advance sustainable peace initiatives. We compared our model with spatial multi-criteria evaluation for conflict management (SMCE-CM) and spatial statistics. The results from the Moran’s I scatter plots of the overall conflicts of the SEFLAME-CM and SMCE-CM models exhibit substantial values of 0.99 and 0.98, respectively. Territorial resource violence due to environmental drivers increases coast-wards, more than that stemming from rebellion. Weighing fuzzy rules and conflict drivers enables equal comparison. Environmental variables, including proximity to arable land, mangrove ecosystems, polluted water, and oil infrastructures are key factors in NRCs. Conversely, socio-economic and political factors seem to be of lesser importance, contradicting prior research conclusions. In Third World nations, local communities emphasize food security and access to environmental services over local political matters amid competition for resources. The synergistic integration of fuzzy logic analysis and community perception to address sustainable peace while simultaneously connecting environmental and socio-economic factors is SEFLAME-CM’s contribution. This underscores the importance of a holistic approach to resource conflicts in communities and the dissemination of knowledge among specialists and local stakeholders in the sustainable management of resource disputes. The findings can inform national policies and international efforts in addressing the intricate underlying challenges while emphasizing the knowledge and needs of impacted communities. SEFLAME-CM, with improvements, proficiently illustrates the capacity to model intricate real-world issues.

Keywords: artificial intelligence; community; fuzzy logic; natural resource conflict management; transdisciplinary-based coupled approach; remote sensing; sustainable development; sustainable peace; Niger Delta (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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