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Mingwei He

Biographic Data

ID4417940
NAMEMingwei He
GIVEN NAMESMingwei
FAMILY NAMEHe
SIGNATUREHE M
AFFILIATIONSKunming University of Science and Technology
ORCID0000-0002-2718-4466
VERIFIEDYes
TOTAL WORKS15
TOTAL CITATIONS22
AUTHOR COUNT15
EDITOR COUNT0
FIRST PUBLICATION YEAR2016
LATEST PUBLICATION YEAR2026
H-INDEX3
  • Navigating social networks: How do concentric and extended ties influence rural leisure participation

    Open Access•Yueren He, Mingwei He et al.•ARTICLE•Journal of Transport Geography•2026•References: 5

  • Gender differences in mobility among rural residents: Evidence from Guiyang, Western China

    Open Access•Yueren He, Mingwei He et al.•ARTICLE•Journal of Rural Studies•2026•References: 52

  • Understanding passenger route choice behavior under the influence of detailed route information based on smart card data

    Open Access•Zhuangbin Shi, Wenqin Pan et al.•ARTICLE•Transportation•2025

  • Shared mobility choices in metro connectivity: Shared bikes versus shared e-bikes

    Open Access•Yang Liu, Rui Tang et al.•ARTICLE•Transportation•2025

  • Gender differences in commuting travel mode choices among young adults: A spatial heterogeneity perspective

    Open Access•Yang Liu, Ren Fang Shen et al.•ARTICLE•Journal of Transport Geography•2025•Cited by: 5•References: 4

  • Identifying the daily activity-travel patterns of rural residents: A case study of Guiyang, China

    Open Access•Yueren He, Yulong He et al.•ARTICLE•Habitat International•2025•Cited by: 1•References: 49

  • Exploring the Activity-Travel Patterns of Multi-Purpose Commuters on Workdays Based on Activity Chains and Time Allocation: Evidence from Kunming, China

    Open Access•Mingwei He, Na Chen et al.•ARTICLE•ISPRS International Journal of…•2024

    Understanding activity-travel patterns and their determinants with regard to multi-purpose commuters is essential for enhancing commuting efficiency and ensuring equal participation in activities. This study applies sequence analysis and hierarchical clustering to identify distinct activity-travel patterns of Kunming commuters using 2016 Household Travel Survey data. Subsequently, a multinomial logistic regression model (MNL) examines the factors…

  • How does the built environment affect intermodal transit demand across different spatiotemporal contexts

    Open Access•Jiayou Lei, Min He et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 1•References: 10

  • Exploring students' choice of active travel to school in different spatial environments: A case study in a mountain city

    Open Access•Yang Liu, Shisheng Min et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 4•References: 2

  • Juggling commutes and cribs: Insights into commuting efficiency in young dual-earner families

    Open Access•Yang Liu, Wei Yang et al.•ARTICLE•Cities•2024•Cited by: 1•References: 2

  • Predictability of short-term passengers’ origin and destination demands in urban rail transit

    Open Access•Fang Yang, Chunyan Shuai et al.•ARTICLE•Transportation•2023

  • A delicacy evaluation method for park walkability considering multidimensional quality heterogeneity

    Open Access•Na Wu, Qingsong Tian et al.•ARTICLE•Journal of Transport Geography•2023•References: 5

  • Exploring the Nonlinear and Threshold Effects of Travel Distance on the Travel Mode Choice across Different Groups: An Empirical Study of Guiyang, China

    Open Access•Mingwei He, Jianbo Li et al.•ARTICLE•International Journal of…•2022

    Examining how travel distance is associated with travel mode choice is essential for understanding traveler travel patterns and the potential mechanisms of behavioral changes. Although existing studies have explored the effect of travel distance on travel mode choice, most overlook their non-linear relationship and the heterogeneity between groups. In this study, the correlation between travel distance and travel mode choice is explored by applyi…

  • Spatiotemporal heterogeneous effects of socio-demographic and built environment on private car usage: An empirical study of Kunming, China

    Open Access•Mingwei He, Chengfeng He et al.•ARTICLE•Journal of Transport Geography•2022•Cited by: 2•References: 2

  • Tolerance threshold of commuting time: Evidence from Kunming, China

    Open Access•Mingwei He, Shengchuan Zhao et al.•ARTICLE•Journal of Transport Geography•2016•Cited by: 8•References: 4

  • Tolerance threshold of commuting time: Evidence from Kunming, China

    Open Access•Mingwei He, Shengchuan Zhao et al.•ARTICLE•Journal of Transport Geography•2016•Cited by: 8•References: 4

  • Gender differences in commuting travel mode choices among young adults: A spatial heterogeneity perspective

    Open Access•Yang Liu, Ren Fang Shen et al.•ARTICLE•Journal of Transport Geography•2025•Cited by: 5•References: 4

  • Exploring students' choice of active travel to school in different spatial environments: A case study in a mountain city

    Open Access•Yang Liu, Shisheng Min et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 4•References: 2

  • Spatiotemporal heterogeneous effects of socio-demographic and built environment on private car usage: An empirical study of Kunming, China

    Open Access•Mingwei He, Chengfeng He et al.•ARTICLE•Journal of Transport Geography•2022•Cited by: 2•References: 2

  • Identifying the daily activity-travel patterns of rural residents: A case study of Guiyang, China

    Open Access•Yueren He, Yulong He et al.•ARTICLE•Habitat International•2025•Cited by: 1•References: 49

  • How does the built environment affect intermodal transit demand across different spatiotemporal contexts

    Open Access•Jiayou Lei, Min He et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 1•References: 10

  • Juggling commutes and cribs: Insights into commuting efficiency in young dual-earner families

    Open Access•Yang Liu, Wei Yang et al.•ARTICLE•Cities•2024•Cited by: 1•References: 2

  • Tolerance threshold of commuting time: Evidence from Kunming, China

    Open Access•Mingwei He, Shengchuan Zhao et al.•ARTICLE•Journal of Transport Geography•2016•Cited by: 8•References: 4

  • Exploring the Nonlinear and Threshold Effects of Travel Distance on the Travel Mode Choice across Different Groups: An Empirical Study of Guiyang, China

    Open Access•Mingwei He, Jianbo Li et al.•ARTICLE•International Journal of…•2022

    Examining how travel distance is associated with travel mode choice is essential for understanding traveler travel patterns and the potential mechanisms of behavioral changes. Although existing studies have explored the effect of travel distance on travel mode choice, most overlook their non-linear relationship and the heterogeneity between groups. In this study, the correlation between travel distance and travel mode choice is explored by applyi…

  • Spatiotemporal heterogeneous effects of socio-demographic and built environment on private car usage: An empirical study of Kunming, China

    Open Access•Mingwei He, Chengfeng He et al.•ARTICLE•Journal of Transport Geography•2022•Cited by: 2•References: 2

  • Predictability of short-term passengers’ origin and destination demands in urban rail transit

    Open Access•Fang Yang, Chunyan Shuai et al.•ARTICLE•Transportation•2023

  • A delicacy evaluation method for park walkability considering multidimensional quality heterogeneity

    Open Access•Na Wu, Qingsong Tian et al.•ARTICLE•Journal of Transport Geography•2023•References: 5

  • Exploring the Activity-Travel Patterns of Multi-Purpose Commuters on Workdays Based on Activity Chains and Time Allocation: Evidence from Kunming, China

    Open Access•Mingwei He, Na Chen et al.•ARTICLE•ISPRS International Journal of…•2024

    Understanding activity-travel patterns and their determinants with regard to multi-purpose commuters is essential for enhancing commuting efficiency and ensuring equal participation in activities. This study applies sequence analysis and hierarchical clustering to identify distinct activity-travel patterns of Kunming commuters using 2016 Household Travel Survey data. Subsequently, a multinomial logistic regression model (MNL) examines the factors…

  • How does the built environment affect intermodal transit demand across different spatiotemporal contexts

    Open Access•Jiayou Lei, Min He et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 1•References: 10

  • Exploring students' choice of active travel to school in different spatial environments: A case study in a mountain city

    Open Access•Yang Liu, Shisheng Min et al.•ARTICLE•Journal of Transport Geography•2024•Cited by: 4•References: 2

  • Juggling commutes and cribs: Insights into commuting efficiency in young dual-earner families

    Open Access•Yang Liu, Wei Yang et al.•ARTICLE•Cities•2024•Cited by: 1•References: 2

  • Understanding passenger route choice behavior under the influence of detailed route information based on smart card data

    Open Access•Zhuangbin Shi, Wenqin Pan et al.•ARTICLE•Transportation•2025

  • Shared mobility choices in metro connectivity: Shared bikes versus shared e-bikes

    Open Access•Yang Liu, Rui Tang et al.•ARTICLE•Transportation•2025

  • Gender differences in commuting travel mode choices among young adults: A spatial heterogeneity perspective

    Open Access•Yang Liu, Ren Fang Shen et al.•ARTICLE•Journal of Transport Geography•2025•Cited by: 5•References: 4

  • Identifying the daily activity-travel patterns of rural residents: A case study of Guiyang, China

    Open Access•Yueren He, Yulong He et al.•ARTICLE•Habitat International•2025•Cited by: 1•References: 49

  • Navigating social networks: How do concentric and extended ties influence rural leisure participation

    Open Access•Yueren He, Mingwei He et al.•ARTICLE•Journal of Transport Geography•2026•References: 5

  • Gender differences in mobility among rural residents: Evidence from Guiyang, Western China

    Open Access•Yueren He, Mingwei He et al.•ARTICLE•Journal of Rural Studies•2026•References: 52

Urban Transport and Accessibility (12 works) · Engineering (10 works) · Geography (10 works) · Transport engineering (10 works) · Transportation Planning and Optimization (10 works) · China (7 works) · Business (6 works) · Economics (6 works) · Computer Science (5 works) · Mathematics (5 works)

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