Social and Environmental Conflict Analysis on Energy Projects: Bayesian Predictive Network Approach
Publisher: Energy Policy
Author(s): Isaac Hernández-Cedeñoa, Pamela F. Nelsona, and Marisol Anglés-Hernández
Date: 2021
Topics: Conflict Prevention, Governance, Land, Programming
This paper analyzes the social and environmental aspects of energy and large-scale projects through the use of Bayesian Networks. To do this, a database was created that includes conflict causes related to 267 projects in Mexico with 12 well-defined and orthogonal social and environmental conflict causes. These are lack of information and participation, fear of change to local communities, health and environmental damage, reduction of primary sector activities, proximity to cultural landmarks, employee dissatisfaction, political interests, violence to the community, water use, non-compliance of agreements, land use disputes, and others not defined. The database was the input for two Bayesian Networks, network “A” estimates the likelihood of approval or risk of suspension of a project because of the conflict causes, with an overall accuracy of 80.3%. The network “B” estimates the costs of conflictive situations and how likely they can be resolved by adding benefits. A sensitivity analysis found that five conflict causes can reduce the probability of a project's success by 10–39%. Finally, policy implications were identified, resulting in four recommendations for implementation in national regulations. The tools developed here enable measurement of the benefits of energy projects, provide policymakers tools to improve public decisions, and help avoid conflicts.