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Immobility or soft refusal? An empirical analysis of the association between respondents’ diligence and reported immobility in household travel surveys

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  • Zhang, Zhiwei
  • Maruyama, Takuya

Abstract

In household travel surveys (HTS), some respondents may report immobility despite having actually traveled on the survey day to reduce survey burden, which is an instance of soft refusal. Since this can deteriorate the data quality of HTS, detecting possible soft refusals is important for HTS organizers and users. The respondents’ diligence can be used to detect possible soft refusals, but its examination is not sufficient. The objective of this study is to explore the association between their diligence and possible soft refusals in HTS. Data from the 2023 Kumamoto Metropolitan Area Household Travel Survey in Japan were used to examine this association. Firstly, we defined five types of less diligent respondents: item nonrespondents, nonrespondents to the open-ended questions (OEQ), proxy respondents, incentive seekers, and late submitters. Then, their immobility rates were compared with those of their more diligent counterparts. Binomial logit models were estimated to investigate the association comprehensively, and the model incorporating diligence variables was used to correct possible soft refusal bias. The results suggest that most less diligent respondents are more likely to report immobility, especially for the nonrespondents to OEQ and item nonrespondents. In contrast, incentive seekers are less likely to report immobility than non-incentive seekers, and late submitters show similar immobility rates to punctual ones. These findings suggest that handling less diligent respondents helps correct the overstated immobility rates. The results of this study contribute to the assessment and improvement of HTS data quality, which is important for transportation research and policymaking.

Suggested Citation

  • Zhang, Zhiwei & Maruyama, Takuya, 2026. "Immobility or soft refusal? An empirical analysis of the association between respondents’ diligence and reported immobility in household travel surveys," Transportation Research Part A: Policy and Practice, Elsevier, vol. 204(C).
  • Handle: RePEc:eee:transa:v:204:y:2026:i:c:s0965856425004483
    DOI: 10.1016/j.tra.2025.104815
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    References listed on IDEAS

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    1. Brög, Werner & Erl, Erhard & Ker, Ian & Ryle, James & Wall, Rob, 2009. "Evaluation of voluntary travel behaviour change: Experiences from three continents," Transport Policy, Elsevier, vol. 16(6), pages 281-292, November.
    2. Ralph Buehler & John Pucher, 2024. "The challenge of measuring walk trips in travel surveys: problems of undercounting and incomparability among countries and over time," Transport Reviews, Taylor & Francis Journals, vol. 44(5), pages 937-943, September.
    3. Chao Chen & Caspar Chorus & Eric Molin & Bert Wee, 2016. "Effects of task complexity and time pressure on activity-travel choices: heteroscedastic logit model and activity-travel simulator experiment," Transportation, Springer, vol. 43(3), pages 455-472, May.
    4. Hong, Shuyao & Zhao, Fang & Livshits, Vladimir & Gershenfeld, Shari & Santos, Jorge & Ben-Akiva, Moshe, 2021. "Insights on data quality from a large-scale application of smartphone-based travel survey technology in the Phoenix metropolitan area, Arizona, USA," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 413-429.
    5. Gerike, Regine & Gehlert, Tina & Leisch, Friedrich, 2015. "Time use in travel surveys and time use surveys – Two sides of the same coin?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 4-24.
    6. Peter Stopher & Camden FitzGerald & Min Xu, 2007. "Assessing the accuracy of the Sydney Household Travel Survey with GPS," Transportation, Springer, vol. 34(6), pages 723-741, November.
    7. Stopher, Peter R. & Greaves, Stephen P., 2007. "Household travel surveys: Where are we going?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 367-381, June.
    8. Egu, Oscar & Bonnel, Patrick, 2020. "How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? An empirical investigation in Lyon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 267-282.
    9. Eleanor Singer & Cong Ye, 2013. "The Use and Effects of Incentives in Surveys," The ANNALS of the American Academy of Political and Social Science, , vol. 645(1), pages 112-141, January.
    10. Louafi Bouzouina & Karima Kourtit & Peter Nijkamp, 2022. "Impact of immobility and mobility activities on the spread of COVID‐19: Evidence from European countries," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 6-20, November.
    11. Md. Sakoat Hossan & Hamidreza Asgari & Xia Jin, 2018. "Trip misreporting forecast using count data model in a GPS enhanced travel survey," Transportation, Springer, vol. 45(6), pages 1687-1700, November.
    12. Aschauer, Florian & Hössinger, Reinhard & Jara-Diaz, Sergio & Schmid, Basil & Axhausen, Kay & Gerike, Regine, 2021. "Comprehensive data validation of a combined weekly time use and travel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 66-82.
    13. Jean‐Paul Hubert & Jimmy Armoogum & Kay W. Axhausen & Jean‐Loup Madre, 2008. "Immobility and Mobility Seen Through Trip‐Based Versus Time‐Use Surveys," Transport Reviews, Taylor & Francis Journals, vol. 28(5), pages 641-658, February.
    14. Yoshikawa, Shunta & Maruyama, Takuya, 2025. "Extended Whipple’s index approach to analyze proxy response and rounding in travel surveys," Transportation Research Part A: Policy and Practice, Elsevier, vol. 191(C).
    15. Jean-Loup Madre & Kay Axhausen & Werner Brög, 2007. "Immobility in travel diary surveys," Transportation, Springer, vol. 34(1), pages 107-128, January.
    16. Wang, Xiang & Tong, Jiaxin & Zong, Weiyan & Lv, Yanqing & Shen, Jiayan, 2024. "Trip misreporting mining and expansion method for household travel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    17. Keishi Fujiwara & Varun Varghese & Makoto Chikaraishi & Takuya Maruyama & Akimasa Fujiwara, 2025. "Does response lag affect travelers’ stated preference? Evidence from a real-time stated adaptation survey," Transportation, Springer, vol. 52(2), pages 693-713, April.
    18. Fabio Milani, 2021. "COVID-19 outbreak, social response, and early economic effects: a global VAR analysis of cross-country interdependencies," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 223-252, January.
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