Indigenous people have deep local knowledge of environmental sustainability and natural resource utilization, which are sources of innovations that often are drivers for economic growth in rural areas. This study explores the knowledge structure of indigenous innovation in village enterprises through content analysis of research publications. The resulting knowledge structure can be used to set up a roadmap for the studies on village enterprise and in a broader context to build metadata as a foundation for an evaluation system of village enterprise. The authors deploy topic modeling and co-word analyses to scrutinize 775 village enterprise research articles from the Scopus database and 665 paper from ScienceDirect. In the topic modeling, topic models village enterprises are setup. The topics found are local ownership (such as market and property), land, services (housing, health care), economy and public policy, financial service micro-credit, environmental pollution control, local business sustainability, social entrepreneurship, and household income, bioenergy based electrification, and bumdes management. Four sectors of the natural resource-based indigenous economy were identified: traditional food production, bio-energy for fuel and electricity, agriculture, and tourism. The topic models are used to comprehend knowledge structure in the village enterprises, whereby the focus is to uncover the context of indigenous village enterprise and its states of the art.

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The concept of social innovation is increasingly being discussed to pursue sustainable development. New terms and keywords are created to cope with new ideas in various contexts. How these terms are developed in the current structure of knowledge and how we can reinterpret the semantic networks with the empirical context are the primary motivation of this paper. The rural social innovation knowledge structure is constructed to understand the phenomena better and cope with future needs. A multi-methods methodology is applied to construct the knowledge structure with the primary method being topic modeling. The results from topic modeling, co-word analysis, and co-citation are combined to co-construct the knowledge structure. The narratives for the built knowledge structure are then developed in the context of rural social innovation to enhance our understanding. This study found three findings. First, the trend of keywords “community”, “governance”, and “rural” have increased significantly in the field of social innovation. Second, an investigation of the intensity of the topics found six dominant groups of topics, namely actor, business model, natural resources, food security, governance, and urban. Third, the co-word analysis shows that the word innovation is closely related to the terms: sustainable development, social entrepreneurship, social enterprise, rural community, electronic commerce, co-design, and social behavior. The mapping of key terms shows that the structure of the global social innovation research landscape is quite complex. However, it can be broken down into five main parts: objectives, inputs, transformations, outputs, and outcomes.