Economic Development and Sustainability in The Amazon: A Big Data Analysis Based on The Triple Bottom Line

Objective: The objective of this study is to analyze, using big data, the research conducted over the past ten years on economic development and sustainability in the Amazon, using the Triple Bottom Line (TBL) as an analytical basis to identify patterns, knowledge gaps, and trends that may inform effective public policies. Theoretical Framework: The research is based on the concept of TBL proposed by Elkington (2018), which encompasses economic, social, and environmental dimensions as pillars of sustainable development, promoting an integrated balance between economic prosperity, social justice, and environmental protection. Method: The methodology involved data collection from the Web of Science platform, followed by big data analysis and clustering techniques using K-means and DBSCAN algorithms. Articles related to economic development and sustainability in the Amazon were identified and grouped according to the TBL pillars. Results and Discussion: The results revealed three main clusters (social, economic, and environmental), highlighting conflicts and convergences among the development objectives of the Amazon. A predominance of social studies was observed, followed by environmental and economic studies, indicating specific gaps in the integration of these pillars. Research Implications: The results provide inputs for the formulation of public policies aimed at a more balanced development of the Amazon, integrating the three TBL pillars and valuing local communities. Originality/Value: The originality of the study lies in the use of big data and clustering analysis to explore the relationship between development and sustainability in the Amazon, providing an integrated view of emerging trends and research gaps.