Position paperEnvironmental conflict analysis using an integrated grey clustering and entropy-weight method: A case study of a mining project in Peru
Introduction
Environmental conflicts often accompany the planning and implementation of projects and programs, as evidenced by studies of conflicts related to water management (Bolin et al., 2008, Saqalli et al., 2010), energy (Fontaine, 2010, Karjalainen and Järvikoski, 2010), exploitation of natural resources (Correia, 2007, Warnaars, 2012, Madani et al., 2014) or ecological tourism (Yang et al., 2013). Therefore, organizations and governments require techniques enabling them to assess social impact and then, given this information, to propose measures for preventing environmental conflicts (Barrow, 2010, Prenzel and Vanclay, 2014). Organizations have obligation as part of their corporate social responsibility to evaluate their social impact to prevent possible conflicts within the affected communities (Kemper et al., 2013). Furthermore, governments are obligated to improve population welfare to achieve sustainable development of countries; therefore, they must measure social impact of their programs and state policies to prevent possible conflicts (Franks and Vanclay, 2013). In addition, stakeholders are a dimension of integrated assessment (Hamilton et al., 2015), and environmental conflicts are generated between stakeholder groups within communities, due to the differences in the assessment of industrial projects (Arun, 2008, Luyet et al., 2012). For this reason, social impact assessment must first be performed for each stakeholder group and then the gap between the groups must be determined in order to predict and prevent possible environmental conflicts.
Thus far, ECA has been mostly carried out using qualitative methods such as those described by Prenzel and Vanclay (2014), (based on game theory), who address environmental conflict from an infrastructure development project, or by Griewald and Rauschmayer (2014), (based on a capability perspective), who consider environmental conflict in a protected nature area. In addition, there are also quantitative methods for ECA, found, for example, in the study by Al-Mutairi et al. (2008), (based on fuzzy logic) of environmental conflict over aquifer contamination caused by a chemical company. In this article, we apply a method for ECA combining the grey clustering method and the entropy-weight method (The IGCEW method), as an extension to the qualitative and quantitative methods.
The grey clustering method enables quantification of qualitative information and classification of observed objects into definable classes, as well as verification of whether the observed objects belong to predetermined classes – as shown by the studies of Zhang et al. (2013), who analysed a water rights allocation system, or by Zhang et al. (2014), who classified innovation strategic alliances. It can be argued that the grey clustering method is likely to benefit the first stage of ECA in that it helps assess social impact by quantifying the qualitative information obtained from stakeholder groups involved in a given environmental conflict.
In turn, the entropy-weight method is used to calculate objective weights of criteria. If there is a large difference between the objects for a criterion determined, this criterion can be regarded as an important factor for the analysis of alternatives, as shown by the study of Wang and Lee (2009), who resolved a software selection problem, or by Kou et al. (2011), who assessed a case of environmental pollution. In our view, the entropy-weight method would benefit the final stage of ECA, as it allows researchers to determine the criteria for which there is divergence between the stakeholder groups involved in a conflict. The combination of both methods would be beneficial for ECA because it integrates social impact assessment and divergent criteria identification. To illustrate the method we propose, a case study was conducted assessing the exploitation plans of a poly-metallic mine in northern Peru. Three stakeholder groups were identified and a set of seven criteria for ECA were established in the mining project.
The specific objectives of this article are to:
- 1.
Apply the IGCEW method for ECA to the concrete context of the exploitation plans of the poly-metallic mine in Peru.
- 2.
Explore if the IGCEW method exhibits potential for other ECA contexts.
In section 2 the literature review is described. Section 3 provides the details of the IGCEW method for ECA. In Section 4 the case study is described, followed by the results and discussion in Section 5. Conclusions are provided in Section 6.
Section snippets
Literature review
Environmental conflicts are characterized by the interaction between (1) ecological and (2) social complexity (Wittmer et al., 2006).
- (1)
One central feature of environmental conflicts is the complexity of the ecological system which is the natural base of the conflicts. Even if its understanding is accompanied by a high degree of scientific sophistication, there remains substantial uncertainty and ignorance. Therefore, the process leading to the resolution of environmental conflicts should take
Method
This section provides a summary of the grey clustering method and of the entropy-weight method, followed by details of the IGCEW method for ECA.
Case study
In order to test the IGCEW method, we performed an ECA of the expansion plans of a poly-metallic mine in northern Peru, in the department of Cajamarca (Fig. 3). Our study measured the social impact of this project on the zone of influence and, based on the results, determined the criteria likely to generate environmental conflicts between the identified stakeholder groups.
Results and discussion
The results and discussion are presented below in accordance with the two main objectives of this article.
Conclusions
The application of the IGCEW method for ECA to the mining project in Peru has made it possible to quantify the qualitative information provided by the three stakeholder groups identified, allowing us to establish the values of social impact for each stakeholder group objectively. In addition, the application of the IGCEW method determined the divergent criteria most likely to produce environmental conflicts between the stakeholder groups. The specific results obtained, we believe, could help
Acknowledgements
This paper was reviewed by Przemysław Kaszubski, PhD, from the Faculty of English at the Adam Mickiewicz University in Poznan, Poland. The authors would like to thank him for his valuable comments and suggestions.
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