An Interpretive Structural Model Approach to Strategic Management Modelling for Sustainable Smart Village Development in Indonesia

Smart Villages(SV) promote sustainable development and improve the quality of life in rural areas by utilizing ICT. They involve efficient resource use, local customs, and better governance. Research on smart villages helps understand challenges, identify best practices, and evaluate the impact on rural communities. Unfortunately, SV development has multifacet and various problems are still high rates rate of urbanization, inequality and the gap in the region's development, lack of budget, lack of clear strategies, lack of collaboration, lack of knowledge, lack of agricultural digitalization, lack of environmental aspect, lack of socio-economic factor and lack of village technology. It's a need for a good Decision Support System for better comprehensive strategies in developing SV. Previous research on SV has identified several enabler drivers for SV development, but none try to make hierarchical and modeling relationships among the enabler. This research aim is to make a hierarchical modeling relationship of SV enabler. This research uses the Interpretive Structural Model(ISM) approach, a form of ranking elements introduced by J. Warfield based on the relationship between elements. This research was conducted through deep interviews and expert judgment of ten experts that have enough SV development that Smart Government (A1), Smart Community (A2), and Smart Relationships (A7) (Level 1) are the Crisis Factors most likely to affect the Smart Village. The Critical Strategy (Level 3) includes the Sustainable planning approach (A4) and Empowerment (A5), whereas the Smart Economy (A8) is at Level 2. Level5: Smart infrastructure (A13). Level 6 covers smart mobility (A9), empowerment (A14), and service (A15), while Level 7 includes smart tourism (A10) and education (A12). In the creation of a Smart Village, Smart Government (A1), Smart Community (A2), and Smart Relationships (A7) must be prioritized over Smart Health (A11) at Level 8. These findings indicate that, when developing smart villages, policymakers and governments should pay increased focus on a particular hierarchy of crucial factors that affect the development of smart villages.