What effect might the development of big data and AI have on the work of real estate professionals ? This paper focuses on the degree to which AI and machine learning may be able to correctly determine real estate prices - a task which occupies a central position in the work of real estate appraisers and brokers. Real estate price determination requires a process where real estate data of varying quality is utilized in the analysis of price formation structures. Furthermore, as the market is in a constant state of flux prices must be determined in response to changes over time. Big data and AI are terms that are commonly used in general conversation. While they do have a complementary relationship they have developed, fundamentally, as diff erent technologies. Recent developments in this area have garnered attention, with a particular focus on advances in big data, and in the context of the development of such an information base the significant improvements in the methods of analysis known as AI and machine learning indicate that such techniques will eventually be able to perform the task of real estate price determination that is currently carried out by appraisers and brokers.
It will soon be 20 years since the large-scale consolidation of municipalities known as the “Great Heisei mergers” began. This policy was undertaken in response to the issue of municipalities, especially smaller ones, no longer being viable due to Japanʼs declining population and aging society. To put it another way, the aim of the policy was to pursue economies of scale by expanding the average size of municipalities through mergers and to make administrative and fi scal systems more effi cient by consolidating operations. It may therefore be said that decisions relating to municipal mergers were made based primarily on the issue of financial capability. However, it should also be noted that another purpose of the organizational reform was to strengthen municipalitiesʼ capacity to flexibly respond to policies in new areas. This paper focuses on the latter issue. Specifi cally, it takes the vacant house problem-which has received much attention as a new policy issue in recent years as an example and outlines how governments have responded to this issue and what kind of problems have emerged in light of municipal mergers.