Workplace Assignment to Workers in Synthetic Populations in Japan

Tadahiko Murata, Daiki Iwase, Takuya Harada

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In this article, we assign workplace attributes to each worker in each household in a synthetic population using multiple censuses conducted in Japan. The synthetic population is a set of artificial individual attributes for each resident that is synthesized according to census data. We have synthesized a set of the synthetic populations of Japan. We assign a workplace attribute to each worker to estimate daytime population distribution and develop activity-based models in agent-based or microsimulations. Although statistical information in a residential area or a working place is released by the government and some individual moving data are released by cellphone companies, it is hard to collect the information with home and workplace location of a worker with their family and working information. We employ origin-destination-industry (ODI) statistics to estimate workplaces for workers. Since some attributes in ODI statistics are not available for privacy reasons, we propose a workplace assignment method for all cities, towns, and villages using restricted ODI and OD statistics in Japan. We show how much difference there are between the number of workers using the complete ODI statistics and the number of workers by the proposed workplace assignment method. We show that 88.2% of workers in a city in Japan are assigned to correct cities as workplaces by our proposed method. We also show several maps of daytime population distributions by our proposed method. Synthetic populations with workplace attributes enable real-scale social simulations to design transport or business systems in times of peace or to estimate victims and plan recoveries in times of emergency, such as disasters or pandemics.

Original languageEnglish
Pages (from-to)1914-1923
Number of pages10
JournalIEEE Transactions on Computational Social Systems
Issue number4
Publication statusPublished - 2023 Aug 1


  • Agent-based modeling
  • daytime population distribution
  • microsimulations
  • social simulations
  • synthetic population
  • workplace assignment

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Social Sciences (miscellaneous)
  • Modelling and Simulation


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