Exploring the Role of Artificial Intelligence in Achieving a Net Zero Carbon Economy in Emerging Economies: A Combination of PLS-SEM and fsQCA Approaches to Digital Inclusion and Climate Resilience

• Published in: Sustainability 2024-12, Vol.16 (23), p.10299
• Main Authors: Mondal, Subhra, Das, Subhankar, Vrana, Vasiliki G
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Carbon; China; Climate action; Climate adaptation; Climate change; Climate policy; Collaboration; Comparative analysis; Developing countries; Digital literacy; Economic development; Economic growth; Emerging markets; Greece; Industrialized nations; Information literacy; Infrastructure; Italy; Literature reviews; Machine learning; Remote sensing; Renewable resources; Research methodology; Sustainable development; Technology adoption; Technology and civilization; Vietnam
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su162310299

In this paper, we examine the role of artificial intelligence (AI) in sovereignty and carbon neutrality, emphasizing digital inclusion and climate-resilient AI strategies for emerging markets. Considering the previous studies on AI for carbon neutrality and digital inclusion for climate research along with technology policy frameworks as a guide, this paper undertakes Partial Least Squares Structural Equation Modelling (PLS-SEM) with AI strategies and carbon neutrality outcomes. At the same time, fuzzy-set Qualitative Comparative Analysis (fsQCA) is used to reveal different configurations leading to achieving climate resilience. The model covers various aspects of AI-enabled policy, including technology adoption, policy frameworks, digital literacy, and public engagement. Survey data were collected from key stakeholders in climate policy, technology sectors, and local communities using a structured survey to understand their attitudes towards negative emissions technologies from prominent experts in emerging countries like Vietnam, Italy, Malaysia, and Greece. PLS-SEM results reveal the importance of AI in developing carbon neutrality, a critical AI strategic dimension (Data analytics capability and policy support). Some aspects of the fsQCA findings present heterogeneous outcomes, highlighting complex combinations of digital inclusion, AI adoption, and climate resilience which are industry-specific. This study would further enrich the literature concerning climate strategies by exploring AI, digital inclusion, and carbon neutrality interactions. Theoretically, practical and enriching suggestions for future research are derived to help AI intelligence infuse sustainable climate actions.