Addressing stagnation in community currencies: enhancing circulation of digital community currencies using neural network-based satisfaction prediction
摘要
Digital community currency (DCC) is a form of digital currency that is designed and used within a specific community or local area for promoting sustainable development. It is a decentralized medium of exchange that allows members of a community to engage in economic transactions without relying solely on traditional national currencies. Such sustainable development cannot be created efficiently without addressing the stagnation problem. This paper proposes the concept of a "customized community" to smooth away the stagnation problem and enhance the circulation of community currencies (CCs) by establishing a market that fits the needs of members within the community. We newly introduce a computational framework (or sequence of steps) for satisfaction prediction based on real data when building the “customized community” and conduct a comparison with Peace Coin, evaluating them across various metrics. The result of this comparison suggests that proposed concept was based on enhancing the user satisfaction by giving a “preference” in terms of bonus premium amount to members who were frequently and actively involved in the CC transactions through analyzing their Japanese text-based impressions. Our main findings suggest that the concept of "customized community" can reduce the stagnation in CCs significantly from 15 to 3% through implementing a random network model of 100 people and using computer simulation to analyze transactions.