A survey dataset on residents’ attitudes and behaviors in major cities in Japan: Geo-social survey for Urban Lifestyle Preferences (GULP)Social Science Japan Data Archive

A survey dataset on residents’ attitudes and behaviors in major cities in Japan: Geo-social survey for Urban Lifestyle Preferences (GULP)Social Science Japan Data Archive

The Geo-social survey for Urban Lifestyle Preferences (GULP) is a large-scale social survey with detailed geographic information targeting major cities in Japan. The Metro Survey—the main component of the GULP targeting metropolitan residents—was conducted online using quota sampling to collect 30,0...

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Main Authors: Tomoya Hanibuchi, Akio Muranaka, Naoto Yabe, Masakazu Yamauchi, Tomoki Nakaya, Masaya Uesugi, Kayo Nozaki, Shigeki Matsuda, Ryo Tanimoto, Ryoko Yamamoto, Mohammad Javad Koohsari
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Data in Brief
Subjects:
Online survey
Micro data
Address information
Neighborhood effect
Geospatial analysis
Multilevel data
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340925005840
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Summary:The Geo-social survey for Urban Lifestyle Preferences (GULP) is a large-scale social survey with detailed geographic information targeting major cities in Japan. The Metro Survey—the main component of the GULP targeting metropolitan residents—was conducted online using quota sampling to collect 30,000 responses from registered panelists aged 20–69 living in 21 major cities across Japan. The survey was conducted simultaneously with the 2020 Population Census (October to November 2020) to create multilevel data by linking the survey micro data with the neighborhood census data. In addition, two benchmarking surveys—the Nonmetro Survey and the Nationwide Postal Survey—were conducted in the same period. The dataset included many variables related to attitudes toward neighborhoods, such as attachment to place, social capital, livability, perceived environment, residential preferences, and disaster risk perception. This dataset enables a wide range of analyses by linking individual attitudes, behaviors, and attributes with regional characteristics. Moreover, the dataset can be linked to geospatial variables based on residential addresses for quantitative analyses of the associations between the characteristics of urban residents and neighborhood environments.
ISSN:2352-3409

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