This document is structured in four parts. First, the theoretical framework of the proposal's main themes is presented. Part Two presents the research design and explains the TD-SBSC. Third, the results section presents the case studies analyzed. Fourth, the conclusions and policy recommendations. 1. Theoretical Framework This section integrates key theoretical strands underlying the proposal: shared value, territorial development, AI, digital twins, social innovation approaches and smart territories. Shared value is the creation of economic value for the company in ways that simultaneously create value for society by addressing societal needs and challenges (Porter and Kramer 2011). This approach relies on a business model that creates economic, social, and environmental value by expanding the value chain within the company’s ecosystem. In mining, shared value can be embedded in the business model by linking operational decisions to core value-chain enablers—water, energy, and transport/logistics—as well as to adjacent activities such as local procurement. When designed in this way, these investments both strengthen operational performance (by reducing costs and risk exposure) and deliver lasting territorial benefits.. Community-based value creation is a key pathway for territorial development, mobilizing government, business, civil society, and academia to leverage local resources and capabilities within the ecosystem (Gallegos & Aguilar, 2023). Territorial development is a process of productive, social, and institutional transformation aimed at creating social, economic, and environmental value, with the ultimate goal of reducing inequality and poverty and improving living conditions (ECLAC & ILPES, 2019). The term “territorial development”, according to Torre (2019), emerged in the early 2000s as authors began focusing on the territorial dimension. Previously referred to as “regional, local, or bottom-up development,” the concept of territorial development initially faced resistance before gaining acceptance. Territories are not just geographical entities but collective creations shaped by citizens, governance, and organizations. They are interconnected, continuously evolving through interactions between local and external actors, and defined by cultural roots, belonging, and distinct political and organizational structures. As Gallegos and Sadagopan (2023) state, territorial development requires a performance measurement system aligned with development plans, integrating strategies from the state, private companies, civil society, and international partners to create incremental value. This system serves as a diagnostic tool to identify territorial issues and develop solutions (Gallegos, 2023). Its development must be participatory, aligning public plans and policies (ICSI 2024), building trust among local actors, and ensuring continuity through a dedicated team or entity. Therefore, decision making for territorial development requires data and information. In this regard, territorial development could be more effective and efficient if the great potential offered by artificial intelligence (AI) and new tools such as digital twins were leveraged. While digital twin models are widely used in industrial and mining operations, their application to territorial and social contexts is still emerging. Recent research, such as Huang and 132
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