Purpose: This study aims to reveal the role of social capital and power structures in the underground economy of Pasar Maling, Malang City. Methodology: This study used a phenomenological qualitative method. To obtain data, unstructured interviews and observations were conducted with triangulation of sources and Nvivo14 was used to process the data. Results: The research reveals the role of social capital in strengthening the existence of the underground economy through four main aspects: trust, networks, information, and norms. The power structure that can provide rules or contracts at Pasar Maling Malang City is in the form of informal contracts and is dominated by the non-government community, namely the Madurese ethnic community. This market is similar to a perfect competition market, but in the ongoing economy market, Pasar Maling Malang City has restrictions on entering the market or barriers to entry. Only people of the same ethnicity can participate in and conduct trading activities in Pasar Maling Malang City. Limitations: This research only focuses on the market's internal perspective, including sellers and the surrounding community in Pasar Maling. Contribution: This research may provide additional knowledge for readers and serve as a reference for further research on underground economy.

Purpose: This study aims to measure the impact of Smart Village dimensions on rural community welfare in Lampung Province (2020–2024), with a particular focus on the Smart Economy pillar and its integration with digital transformation and technosociopreneurship. Research/methodology: A quantitative approach was employed using multiple linear regression (Ordinary Least Squares) on data collected from 70 Smart Village locations across four districts in Lampung. The independent variables included six Smart Village dimensions: Smart People, Smart Governance, Smart Mobility, Smart Environment, Smart Living, and Smart Economy. The dependent variable was community welfare. Instrument testing and classical assumption tests (normality, multicollinearity, heteroscedasticity, and autocorrelation) were conducted to validate the model. Results: All six Smart Village dimensions showed a significant positive influence on community welfare. The Smart People dimension had the strongest effect (coefficient = 0.8489). The regression model demonstrated high explanatory power (R² = 0.9535) and satisfied all classical assumptions. Notably, Smart Economy initiatives—such as MSME digitalization, inclusive market access, and technology-based entrepreneurship—directly contributed to increased income, employment opportunities, and local economic growth. Conclusions: The application of Smart Village principles, particularly in economic transformation, significantly enhances rural welfare. Digital innovation, governance quality, and community capacity-building are critical drivers of inclusive development and service improvement. Limitations: The study is limited to Lampung Province and lacks comparative data from other regions. It also does not assess long-term or behavioral impacts. Contribution: This research provides empirical support for Smart Village policies, guiding investments in digital infrastructure, entrepreneurship training, and multi-stakeholder collaboration for rural development.