Currently, the population structure is changing due to a declining population and aging population in Japan. Therefore, local governments are making plans for the maintenance and renewal of their public facilities. In the plans, various attempts are being made to prioritize which facilities should be renewed, and which facilities should be consolidated or abolished without renewal.
Under these circumstances, we evaluated and prioritized public facilities by considering the usage status, user attributes, facility attributes, etc. for each facility, and also considered the benefits these public facilities provide.
Therefore, this section presents a method for estimating parameters related to facility selection so that the benefits of the public facilities can be determined. Samples with different attributes were divided into several categories, and parameters estimated together with the facility attributes. In the future, we will show that local governments nationwide can estimate the selection behaviors required for facility management from simple usage surveys and facility information owned by the local governments.
We have shown new possibilities for public facility management methods that utilize latent class analysis. Dfficulties of the public facility problems are prioritizing which facilities to start with due to financial constraints. Various proposals have been made for this problem, but subpopulations are estimated from user attributes by latent class analysis, and each group is used in combination with facility attributes. By analyzing the choice behavior of the people, it is possible the people’s will can be determined more accurately.
In this paper, the estimations were made based on the data of 3 local governments for which detailed data on facility attributes are available. All three cities were characteristic castle towns, so the selection behavior of owned facilities and residents maybe biased compared to other general local governments. Issues of external validity have also risen as a result, so we anticipate many local governments will disclose facility information in the future, and we can then also include these issues in the analyses.
JEL Classifications:D61, H83, R53
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