This study reviews the literature on Supply Chain Management (SCM) and Project Management (PM) to serve the Sustainable Development Goals (SDGs) through technological integration. Technological innovations may enhance operational efficiency and decision-making as per SDGs 8 and 9. However, the success of such innovations depends on managerial competency. In this regard, operational coordination can optimize multi-actor networks, which can improve resource allocation and productivity. Moreover, inter-organizational relationships would nurture governance and trust. Additionally, lifecycle project management and stakeholder engagement can enhance operational continuity and sustainability, which can further be supported by stochastic optimization and AI-enabled decision making. The study recommends to integrate circular economy, lean practices, and environmentally responsible frameworks with operational objectives to achieve SDGs. Thus, the interdependence of technology, human capital, governance, and strategy is necessary to achieve efficient SCM and PM.

This study aims to examine the effect of Green Supply Chain Management (GSCM) and Lean Manufacturing (LM) on the achievement of Sustainable Development Goals (SDGs) by including Green Innovation Resilience (GIR) as a mediating variable and Environmental Regulation (ER) as a moderating variable. The problem raised is the lack of research linking GSCM and LM directly or indirectly to SDGs, especially in the furniture industry sector in developing countries. This study uses a quantitative approach with a purposive sampling technique of 230 medium and large-scale furniture companies in East Java. Data was collected through questionnaires distributed online to managers. Data analysis was conducted with SmartPLS 3.2. The uniqueness of this research lies in developing and testing the new concept of GIR as a mediating variable that strengthens the relationship between GSCM and LM on the achievement of SDGs in the furniture industry of developing countries, as well as considering the moderating role of environmental regulation-an integrative approach that has not been comprehensively explored in previous research. The results showed that GSCM and LM have a significant effect on SDGs both directly and through the mediation of GIR. In addition, ER was shown to strengthen the relationship between GSCM and LM on SDGs. These findings indicate the importance of integrating green practices and process efficiency with sustainable innovation and regulatory support in improving industry sustainability performance.

Indonesia is a country dominated by rural areas. Addressing rural poverty is a priority of the Indonesian government work program and an effort to achieve the Sustainable Development Goals (SDGs). One of the actual programs dealing with poverty is a digital village which is implemented in a smart village ecosystem. Since 2018, Indonesia has initiated various pilots of smart village projects. The success of a smart village is closely related to citizen science. The purpose of this research was to build a citizen science prospect model for a smart economy in a smart village ecosystem using Structural Equation Model – Partial Least Square (SEM-PLS) approach. This study proposes a novelty of measuring villagers' readiness to build a smart economy in a smart village ecosystem based on the strength of community support. We propose an assessment of the prospect of developing a smart economy in a smart village through the citizen science level that integrates exogenous variables of community support for the environment, citizen character, empowerment, entrepreneurship, innovation, and the smart economy. The citizen science model towards a smart economy showed a high level of predictive relevance, which was 87,2%. The citizen science model towards a smart economy can also explain empirical data with a GoF value of 0,488. This research showed that the indicators of Information Communication Technology (ICT), ICT literacy, access to education and research and development (R & D) facilitation, motivation for smart villages, and innovation in villages were driven by family participation. The collaboration with the private sector, local government, and communities drive the village's smart economy. The SEM PLS approach has not been widely used in research on the smart village component, especially the relationship between citizen science and the smart economy. Therefore, this research can fill the gap in smart village research, which is still dominated by a descriptive approach.