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Article

An Exploratory Study on Factors Influencing Construction Workers’ Modal Shift Intentions: The Mediating Role of Construction Site Characteristics

건설근로자의 수단전환 의사 영향요인 탐색적 분석: 건설현장 특성의 매개효과 중심으로

Jaeyoung JUNG1
,
Taekyoung KIM1*
,
Youngkyun KANG1
정 재영1
,
김 태경1*
,
강 영균1
1Senior Researcher, HMG Construction R&D Division, Hyundai Engineering & Construction, Seoul 03058, Korea
1현대건설 HMG건설기술연구원 책임연구원
*Corresponding Author
31 August 2026. pp. 511-537
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Abstract

This study explores factors influencing construction workers’ intentions to shift from private car use to commuter buses, addressing concerns that commuting-related traffic congestion around large construction site may affect site operations and productivity. A survey was conducted at a large construction site in Ulsan, South Korea, and 92 valid samples were analyzed after integrating residence-based spatial information. Missing data were examined using Little’s MCAR test and imputed, and partial least squares structural equation modeling (PLS-SEM) was applied to account for the small sample size. The model included conventional mobility management constructs—environmental awareness (EA), perceptions of private car use (CUP), social and personal norms (SPN), and commuter-bus service environment (CBE)—together with construction-context variables such as worksite situational factors (WSF) and worksite traffic and pedestrian environment (TPE). The results indicate that worksite-related factors have limited direct effects on behavioral intention but influence behavioral change intention indirectly through mediating perceptual and normative variables as built environment. Social and personal norms (SPN) and the commuter-bus service environment (CBE) emerged as the strongest predictors of behavioral intention, while the staged decision-making structure from behavioral intention to implementation intention and behavioral change intention was statistically supported. These findings provide empirical evidence for mobility management–based transportation policies in construction-site contexts and suggest practical implications for promoting commuter-bus use to improve site traffic management and productivity.

Keywords
construction traffic management (CTM)
mobility management (MM)
structural equation modeling (SEM)
theory of planned behaviour (TPB)
traffic demand management (TDM)

본 연구는 대형 건설현장에서 근로자 출퇴근 통행으로 인해 발생하는 교통혼잡이 현장 운영과 생산성에 영향을 미칠 수 있다는 문제의식에서 출발하여, 자가용 이용에서 통근버스로의 수단전환 의사에 영향을 미치는 요인을 탐색적으로 분석하였다. 울산 소재 건설현장의 근로자 123명을 대상으로 설문조사를 수행하였으며, 거주지 기반 공간정보를 결합한 92건의 유효 표본을 분석에 활용하였다. 결측값의 통계적 특성은 Little’s MCAR Test를 통해 검토·보정하였고, 분석 방법으로는 소표본에 적합한 부분 최소제곱 구조방정식모델링(PLS-SEM)을 적용하였다. 분석 모형에는 기존 모빌리티 매니지먼트 연구에서 제시된 환경의식, 승용차 이용 인식, 사회·개인 규범, 통근버스 이용 환경과 함께 건설현장 특성 및 현장 교통·보행 환경을 잠재변수로 반영하였다. 분석 결과, 건설현장 관련 변수들은 행동의도에 대한 직접효과는 제한적이었으나, 객관적 환경(Built environment)으로써 다른 인지적·규범적 요인을 매개로 수단전환 행동변화 의사에 간접적인 영향을 미치는 것으로 나타났다. 또한 사회·개인 규범과 통근버스 이용 환경이 행동의도에 가장 큰 영향을 미쳤으며, 행동의도–실행의도–행동변화 의사로 이어지는 모빌리티 매니지먼트의 단계적 의사결정 구조 역시 통계적으로 유의한 것으로 확인되었다. 이를 통해 건설현장 교통관리 관점에서 모빌리티 매니지먼트 기반 교통정책의 실증적 근거를 제시하고, 통근버스로의 수단전환을 촉진하기 위한 현장 차원의 정책적 시사점을 도출하였다.

키워드
건설교통관리(CTM)
모빌리티 매니지먼트(MM)
구조방정식(SEM)
계획행동이론(TPB)
교통수요관리(TDM)
References
1

Ajzen I. (1991), The Theory of Planned Behavior, Organizational Behavior and Human Decision Processes, 50(2), 179-211.

10.1016/0749-5978(91)90020-T
2

Alshalalfah B., Nafakh J., Al Banna Y., Kaysi I. (2018), Traffic Management of Mega Infrastructure Construction Projects: Success Story and Lessons Learned from the Riyadh Metro Project, Transport and the City, 89.

10.2495/TDI-V2-N1-84-97
3

Bamberg S., Fujii S., Friman M., Gärling T. (2011), Behaviour Theory and Soft Transport Policy Measures, Transport policy, 18(1), 228-235.

10.1016/j.tranpol.2010.08.006
4

Cairns S., Newson C., Davis A. (2010), Understanding Successful Workplace Travel Initiatives in the UK, Transportation Research Part A: Policy and Practice, 44(7), 473-494.

10.1016/j.tra.2010.03.010
5

Chaparro D. A., Ying F. J., Rotimi F. E., Egbelakin T. (2020), Commute and Labour Productivity: Investigation of Inner City Construction Sites, Journal of Engineering, Design and Technology, 18(5), 1305-1319.

10.1108/JEDT-12-2019-0336
6

De Vos J., Cheng L., Kamruzzaman M., Witlox F. (2021), The Indirect Effect of the Built Environment on Travel Mode Choice: A Focus on Recent Movers, Journal of Transport Geography, 91, 102983.

10.1016/j.jtrangeo.2021.102983
7

Dong Y., Peng C. Y. J. (2013), Principled Missing Data Methods for Researchers, Springerplus, 2(1), 222.

10.1186/2193-1801-2-22223853744PMC3701793
8

European Platform on Mobility Management. (2013), Mobility Management: The Smart Way to Sustainable Mobility in European Countries, Regions and Cities. EPOMM-European Platform on Mobility Management.

9

Fujii S., Taniguchi A. (2006), Determinants of the Effectiveness of Travel Feedback Programs—A Review of Communicative Mobility Management Measures for Changing Travel Behaviour in Japan, Transport policy, 13(5), 339-348.

10.1016/j.tranpol.2005.12.007
10

Ha J., Jung H. Y. (2017), The Analysis of Awareness on Transportation Demand Management Policy and A Study on Mobility Management, J. Korean Soc. Transp., 35(1), Korean Society of Transportation, 50-62.

10.7470/jkst.2017.35.1.050
11

Ha J., Jung H. Y. (2018), A Study on the Effect of Providing Information Using Mobility Management on the Change of Consciousness About the Use of Passenger Car, J. Korean Soc. Transp., 36(5), Korean Society of Transportation, 346-359.

10.7470/jkst.2018.36.5.346
12

Hair J. F. (2009), Multivariate Data Analysis.

13

Hair J. F. (2018), Multivariate Data Analysis(8th ed.), CENGAGE.

14

Hair J. F., Ringle C. M., Sarstedt M. (2011), PLS-SEM: Indeed a Silver Bullet, Journal of Marketing Theory and Practice, 19(2), 139-152.

10.2753/MTP1069-6679190202
15

Hair J. F., Hult G. T. M., Ringle C. M., Sarstedt M. (2017), A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications.

16

Hartini E. (2018), Classification of Missing Values Handling Method During Data Mining, SIGMA EPSILON-Buletin Ilmiah Teknologi Keselamatan Reaktor Nuklir, 21(2).

17

He Y., Sun Y., Zhao Z., Chen M., Waygood E. O. D., Shu Y. (2024), Impact of Social-Psychological Factors on Low-Carbon Travel Intention: Merging Hheory of Planned Behavior and Value-Belief-Norm Theory, Heliyon, 10(6).

10.1016/j.heliyon.2024.e2816138545213PMC10966703
18

Hyari K. H., El-Mashaleh M. S., Rababeh S. M. (2015), Framework for Managing the Traffic Impacts of Building Construction Projects, Journal of Construction in Developing Countries, 20(2), 97.

19

Inturri G., Fiore S., Ignaccolo M., Caprì S., Le Pira M. (2020), You study, You Travel Free: When Mobility Management Strategies Meet Social Objectives, Transportation Research Procedia, 45, 193-200.

10.1016/j.trpro.2020.03.007
20

Jung Y. H., Kim D. W., Hong M. K. Jang H. S. (2020), Causal Relationship Analysis of the Factors Lowering Productivity in Construction Job Site, Korean Journal of Construction Engineering and Management, 21(1), 99-110.

10.6106/KJCEM.2020.21.1.099
21

Kang H. (2013), The Prevention and Handling of the Missing Data, Korean Journal of Anesthesiology, 64(5), The Korean Society of Anesthesiologists, 402-406.

10.4097/kjae.2013.64.5.40223741561PMC3668100
22

Ki H., Chang J. S. (2024), Analyzing the Factors Influencing Car Dependency Using the Theory of Planned Behavior, J. Korean Soc. Transp., 42(4), Korean Society of Transportation, 472-493.

10.7470/jkst.2024.42.4.472
23

Kim J. H., Kim S. H., Ryu I. G., Choe G. J. (2015), Mobility Management in Korea and Its Impacts on Modal Shift, Transportation Technology and Policy, 12(3), Korean Society of Transportation, 31-37.

24

Koo M., Yang S. W. (2025), Likert-Type Scale, Encyclopedia, 5(1), 18.

10.3390/encyclopedia5010018
25

Lee B., Kim J. K., Yi C. (2013), An Analysis of Decision Making Process in Voluntary Reducing Private Car Use, KSCE Journal of Civil and Environmental Engineering Research, 33(2), 679-689.

10.12652/Ksce.2013.33.2.679
26

Lee J. W., Sohn Y. (2017), How Effective Are Additional Variables to Predict Human Behavior Based on the Theory of Planned Behavior: A Meta-Analytic Approach to Elaborate the Theory of Planned Behavior, Journal of Practical Research in Advertising and Public Relations, 10(3), 217-243.

10.21331/jprapr.2017.10.3.009
27

Little R. J. (1988), A Test of Missing Completely at Random for Multivariate Data With Missing Values, Journal of the American Statistical Association, 83(404), 1198-1202.

10.1080/01621459.1988.10478722
28

Ma L., Cao J. (2019), How Perceptions Mediate the Effects of the Built Environment on Travel Behavior?, Transportation, 46(1), 175-197.

10.1007/s11116-017-9800-4
29

Mischke J., Stokvis K., Vermeltfoort K., Biemans B. (2024), Delivering on Construction Productivity Is No Longer Optional, McKinsey & Company, 15.

30

Park S., Yi C. (2023), The Intention of Automobile Users to Use Public Transportation: An Application of the Extended Theory of Planned Behavior, J. Korean Soc. Transp., 41(2), Korean Society of Transportation, 166-182.

10.7470/jkst.2023.41.2.166
31

Rubin D. B. (1975), Inference and Missing Data, Biometrika, 63(3), 581-592.

10.1093/biomet/63.3.581
32

Wu T., Kim S. Y., Westine C. (2023), Evaluating the Effects of Missing Data Handling Methods on Scale Linking Accuracy, Educational and Psychological Measurement, 83(6), 1202-1228.

10.1177/0013164422114094137974655PMC10638981
33

Yi C. Y. (2011), Development and Implementation of Mobility Management System, Doctoral Dissertation, Graduate School of Hanyang University.

34

Yi Choonyong, Rho C. H. (2010), Introduction of the Mobility Management Policies for Voluntary Reduction of a Passenger Car Uses, The Korea Spatial Planning Review (국토연구), 66, 3-24.

10.15793/kspr.2010.66..001
35

Zhang Z. (2016), Missing Data Imputation: Focusing on Single Imputation, Annals of Translational Medicine, 4(1), 9.

Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 44
  • No :4
  • Pages :511-537
  • Received Date : 2026-01-20
  • Revised Date : 2026-02-25
  • Accepted Date : 2026-06-03
  • DOI :https://doi.org/10.7470/jkst.2026.44.4.511
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