literature review on construction project

• DOI: 10.4018/IJRCM.2016100101
• Corpus ID: 114138549

A Comprehensive Literature Review on Construction Project Risk Analysis

• Ermias Tesfaye , E. Berhan , D. Kitaw
• Published 1 October 2016
• Engineering

9 Citations

A review of risk management process in construction projects of developing countries, risk identification and applying risk management technique in construction project, a fuzzy-based risk assessment methodology for construction projects under epistemic uncertainty, multidimensional modelling of complex and strategic construction projects for a more effective risk management, identification of critical risks in international engineering procurement construction projects of chinese contractors from the network perspective, practical use and effects of scope reductions in the form of reduction lists: cost control at the price of sustainability, schedule overruns as a barrier for liquefied natural gas projects: a review of the literature and research agenda, development of loop destructive network analysis, identifikasi faktor risiko keselamatan pada proyek konstruksi bangunan gedung di indonesia dalam 10 tahun terakhir (2011-2021): kajian literatur, 99 references, risk assessment of construction projects, a proposal for construction project risk assessment using fuzzy logic, a comparison of fuzzy logic and multiple regression analysis models in determining contingency in international construction projects, construction projects selection and risk assessment by fuzzy ahp and fuzzy topsis methodologies, risk assessment model selection in construction industry, application of a fuzzy based decision making methodology to construction project risk assessment, contingency modelling for construction projects using fuzzy-set theory, a fuzzy approach to constuction project risk assessment and analysis: construction project risk management system, using fuzzy risk assessment to rate cost overrun risk in international construction projects, a fuzzy approach to construction project risk assessment, related papers.

Showing 1 through 3 of 0 Related Papers

We apologize for the inconvenience...

To ensure we keep this website safe, please can you confirm you are a human by ticking the box below.

If you are unable to complete the above request please contact us using the below link, providing a screenshot of your experience.

https://ioppublishing.org/contacts/

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

A Comprehensive Literature Review of Research Trends of Applying AI to Construction Project Management

Proceedings of the 6th IPMA SENET Project Management Conference “Digital Transformation and Sustainable Development in Project Management”

Artificial Intelligence (AI) is universally reaching every industry thus far, it is coming to the fore in construction industry by redesigning project world and altering the role of project managers. It provides the ability for computers to simulate human-like thinking and is comprised of machine learning, Internet of things (IoT), automation, natural language processing and robotics. In construction industry, AI is affecting project planning, time and cost management, optimization of resources as well as post-construction activities. Along with assessing teamwork patterns and making recommendations, it also has an impact on the workforce and how individuals handle projects. Despite a broad range of research papers written about this theme there are still not so much of practical applications conducted in practice. Therefore, the aim of this study is to provide an overview of using AI in Project Management and to show how it is affecting construction industry along with exhibiting f...

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Strategizing and Project Management in Construction Projects: An Exploratory Literature Review

10th Nordic Conference on Construction Economics and Organization

eISBN : 978-1-83867-051-1

ISSN : 2516-2853

Publication date: 1 May 2019

The study aims to investigate the concept of strategy-as-practice in construction management literature has been investigated. The focus is on the link between strategizing practices and project management.

Design/Methodology/Approach

An exploratory literature review is carried out based on fifteen journal articles on strategizing practices in the construction industry.

The analysis shows how strategy-as-practice questions and contradicts project management practices as depicted in the dominant deterministic perspective. Strategy-as-practice has a focus on reacting and adapting to a chaotic and changing environment, while project management is concerned with creating and maintaining a stable working environment. The findings point to the necessity of considering the organizational and institutional context of project management practices, and hence the values the strategy-as-practice lens, when considering new avenues for improving the industry.

Research Limitations/Implications

As the study is based on an exploratory literature review of only 15 articles, generalizations should be made with caution. The identified literature is restricted by search words and choice of database.

Practical Implications

The differences between strategizing and project management practices are very clear, and a focus on both may offer insights into how the construction industry could improve its productivity by developing more robust management practices.

Originality/Value

The paper illustrates the benefit of applying a strategizing perspective, which hitherto has been under-investigated in construction management research.

• Construction industry
• Project management
• Project-based organization
• Strategizing
• Strategy as Practice

Klitgaard, A. and Gottlieb, S.C. (2019), "Strategizing and Project Management in Construction Projects: An Exploratory Literature Review", Lill, I. and Witt, E. (Ed.) 10th Nordic Conference on Construction Economics and Organization ( Emerald Reach Proceedings Series, Vol. 2 ), Emerald Publishing Limited, Leeds, pp. 253-258. https://doi.org/10.1108/S2516-285320190000002040

Emerald Publishing Limited

Copyright © 2019, Anne Klitgaard, Stefan Christoffer Gottlieb.

Published in the Emerald Reach Proceedings Series. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Project management (PM) has traditionally been dominated by a deterministic perspective, which implies the possibility of planning, managing and controlling the construction project phenomena ( Padalkar and Gopinath, 2016 ). Clear roles and responsibilities of the project actors are regarded as the way to ensure efficiency in collaboration ( Gustavsson and Gohary, 2012 ). This approach to PM overlooks how projects exist in an external environment ( Kreiner, 1996 ), which is constantly changing and influencing the original intentions and aims of the projects. While this is no longer a new or controversial insight, we see the deterministic approach as a so-called dominant logic ( Bettis and Prahalad, 1995 ) that still is the norm in the construction industry.

Recently, the focus has shifted toward trying to create a better understanding of the contextual factors that shape projects and project practices. This includes also non-deterministic and explanatory approaches focusing on, e.g. project uncertainty, governance and project portfolio management ( Padalkar and Gopinath, 2016 ).

One such theory or approach is that of strategy-as-practice (SAP). The traditional definition of strategy assumes that a strategy is something organizations own or have, argues Johnson et al. (2007) , and stresses that in the SAP perspective, strategy is something people do. In SAP, strategizing (or doing strategy as practice) “comprises those actions, interactions and negotiations of multiple actors and the situated practices that they draw upon in accomplishing that activity” ( Jarzabkowski and Spee., 2009 : 70). With this turn toward practice, research into strategy shifts from a focus on the firm and why strategy is needed, to a concern for people and how they achieve the wanted strategy ( Johnson et al., 2007 ).

Drawing on practice perspective, Söderholm) (2008 : 81) argues that PM can be seen as an on-going social accomplishment or “everyday struggle to keep projects on track and on schedule” within a given context and that this can shed new light on situations that are nrmally not include in PM models.

While SAP is a well-established perspective in business management research, it is less used in construction management. On this basis, we ask

(RQ1) How is SAP and the role of context treated in the construction management literature?

(RQ2) How can SAP contribute to project management in construction?

The paper is based on an exploratory literature review. The literature search was conducted in the EBSCO database Business Source Complete, which covers all disciplines of business. A two-block “free text” search was conducted with a limitation to peer-reviewed journals. The first block containing the phenomena of interest represented by the search words “strategizing” and “strategy-as-practice” (722 hits). Another context block was created using the search words ”construction industry” (12,521 hits). A combination of blocks one and two gave seven articles; this was reduced to five articles by removing copies.

The first block was combined with another block containing the search query “project management” (14,662 hits), which gave ten combined hits. Eight of these were concerned with the construction industry, bringing the total of articles up to thirteen articles. In a final quality control of the search, two additional articles were found that were added to the sample, bringing it up to a total of 15 articles.

This search will at a later stage be extended with a snowballing search back and forth Löwstedt et al. (2018) “Doing strategy in project-based organizations: Actors and patterns of action”, which puts emphasis on the relation between strategizing and project management.

3. Analysis and Findings

3.1. strategy as practice and the project-based construction industry (rq1).

The final result of 15 articles in the search indicates a relatively low interest from the construction industry in the SAP concept. With one exception, all the empirical articles were written within the last six years, indicating a growing interest in the concept.

We divided the articles into two groups comprising empirical articles (11) and theoretical articles (4). The empirical articles were then further divided into three categories depending on the context in which strategizing took place (see Table 1 ).

The empirical articles, the terms in the brackets are the authors’ interpretation

The literature illustrates an interest in the difference between the practice of project managing and strategizing as the two practices are difficult to combine owing to their different focus.

In the theoretical articles, Clegg et al. (2018) set out to provide an agenda for further practice-based research in project portfolio management. Biesenthal et al . (2018) suggest a value in studying the institutional differences in megaproject and doing this by “taking a cue” from the strategy-as-practice approach. Flood and Issa (2010) suggest that the research practitioner should use strategizing as a step in developing an empirical model. Finally, the use of sensemaking, to create scenarios and narratives as a mean of strategizing, is addressed by ( Wright, 2005 ). He stresses that practitioners working at the periphery of the firm (project manager) tend to construct their strategy by induction rather than the rational strategists at the center of the firm.

This is an indication of how the project can shape the strategizing process of project managers. Several of the empirical articles also discuss the role of the firm. Sage et al. (2012) note in their study (on lean construction strategizing) that concepts are continuously translated and transformed during their journey through different contextual settings – and so are people. A group of practitioners working mainly in the firm will thus be working under the influence of the organizational context of the firm, while the practitioners working in projects will be working under the institutional influence of both the firm and the project.

Also, Löwsted et al. (2018) and Koch et al. (2015) discuss how “project actualities” and “nature of the situated practices which surround” operational strategizing afford project actors’ legitimacy and shape practices. Their findings suggest that the traditional PM focusses on principles of project fulfillment, and a narrow focus on how the project performs according to these, is insufficient and can benefit from a more nuanced perspective of the contextual factors that influence project practices. This is also noted by Vit (2011 ) who suggests that technical rationality is overridden in certain contexts. Davies et al. (2016) illustrate how specific dynamic capabilities, including strategic behaviors and collaborative processes, that are required to deliver complex projects, are based on the ability to balance routine and innovative action in changing and uncertain project environments.

3.2. SAP and a new understanding of project management (RQ2)

The SAP perspective may thus also offer some insights into the opportunities for building construction project teams. In SAP, practitioners are those involved in doing strategy. The strategy practitioner may refer to an individual or a group of individuals ( Jarzabkowski and Spee, 2009 ). This group of practitioners will often be joined in communities of actors or project teams. As Baiden et al. (2006) argue, a failure to collaborate effectively in the project teams has been seen as a major cause behind the productivity issue, stressing the need for effective PM.

In the construction industry, a belief in clearly planned and defined project roles and responsibilities as a basis for PM exists. This is, however, contrary to Whittington et al. ’s (2006) claim that strategizing and organizing run together as a smooth simultaneous activity.

The industry needs to ask itself if the deterministic PM approach focusing on stability could cause a loss of opportunity to develop practices toward better productivity. One way to address this issue may be with the introduction of new organization forms in guise of, e.g. integrated project delivery or strategic partnerships ( Gottlieb et al. , 2018 ).

Another approach is that of knotworking, a new form of collaboration which shows promising results ( Buhl et al . 2017 ). Results, which offer a more fluid, approach to the matter. Finally, a developing practice, which may link PM and strategizing, is the use of facilitation for changing existing routines to develop practices ( Klitgaard et al ., 2017 )

4. Conclusions

In this paper, we investigated the link between strategizing practices and project management practices. This literature study shows that the role of SAP in the construction industry is an area of increasing interest and that the literature is sensitive to the practioners’ double obligation; toward their firm and toward the project in which they are involved.

The dominant logic concept suggests that awareness of the primary perspective on practice is necessary. It seems that as long as the determinisitic approach toward PM is so dominant in the industry, it may hinder strategizing practices. Strategizing and project management practice are clearly distinct practices although there is a clear co-dependency between them. We argue that a focus on both may offer insights into how the construction industry could improve its productivity by developing more robust management practices.

This literature study is based on a limited number of articles so further studies are necessary.

Baiden, Price, and Dainty, 2006 Baiden , B. K. , Price , A. D. F. and Dainty , A. R. J. ( 2006 ), “ The extent of team integration within construction projects ”, International Journal of Project Management , Vol. 24 , No. 1 , pp. 13 – 23 .

Bettis, and Prahalad, 1995 Bettis , R. A. and Prahalad , C. K. ( 1995 ), “ The Dominant Logic: Retrospective and Extension ”, Strategic Management Journal , Vol. 16 , No. 1 , pp. 5 – 14 .

Bhattacharya, Momaya, and Iyer, 2012 Bhattacharya , S. , Momaya , K. S. and Iyer , K. C. ( 2012 ), “ Strategic Change for Growth: A Case of Construction Company in India ”, Global Journal of Flexible Systems Management . Vol. 13 , No 4 , pp. 195 – 205 .

Biesenthal, Clegg, Mahalingam, Sankaran, 2018 Biesenthal , C. , Clegg , S. , Mahalingam , A. , Sankaran , S. , ( 2018 ), “ Applying institutional theories to managing megaprojects ”, International Journal of Project Management , Vol. 36 , No. 1 , pp. 43 – 54 .

Buhl, Andersen, and Kerosuo, 2017 Buhl , H. , Andersen , M. , and Kerosuo , H. ( 2017 ), “A Knot – breaking the inertia in construction?”, In Buser , M. , Lindahl , G. and Räisänen , C. (Ed), “9th Nordic Conference on Construction Economics and Organization, 13-14 June, Chalmers University of Technology.

Clegg, Killen, Biesenthal, and Sankaran, 2018 Clegg , S. , Killen , C. P. , Biesenthal , C. and Sankaran , S. , ( 2018 ), “ Practices, projects and portfolios: Current research trends and new directions ”, International Journal of Project Management , Vol. 36 , No. 5 , pp. 762 – 772 .

Comi, and Whyte, 2018 Comi , A. and Whyte , J. ( 2018 ) “ Future Making and Visual Artefacts: An Ethnographic Study of a Design Project ”, Organization Studies , Vol. 39 , No. 8 , pp. 1,055 – 1,083 .

Davies, Dogdson, and Gann, 2016 Davies , A. , Dogdson , M. and Gann , D. ( 2016 ) “ Dynamic capabilities in complex projects: The case of London Heathrow Terminal 5 ”, Project Management Journal , Vol. 47 , No. 2 , pp. 26 – 47 .

Flood, and Issa, 2010 Flood , I. and Issa , R. R. A. ( 2010 ), “ Empirical Modeling Methodologies for Construction ”, Journal of Construction Engineering & Management , Vol. 136 , No. 1 , pp. 36 – 48 .

Floricel, and Miller, 2001 Floricel , S. and Miller , R. ( 2001 ), “ Strategizing for anticipated risks and turbulence in large-scale engineering projects ”, International Journal of Project Management , Vol. 19 , No. 8 , pp. 445 – 455 .

Gottlieb, Frederiksen, Koch, and Thuesen, 2018 Gottlieb , S. C. , Frederiksen , N. , Koch , C. and Thuesen , C. ( 2018 ), Institutional Logics and Hybrid Organizing in Public-Private Partnerships . In: Gorse , C. and Neilson , C. J. (Eds.), Proceedings 34th Annual ARCOM Conference, 3-5 September 2018, Queen’s University, Belfast, UK. Association of Researchers in Construction Management, pp. 383 – 392 .

Gustavsson, and Gohary, 2012 Gustavsson , T. K. and Gohary , H. ( 2012 ), “ Boundary action in construction projects: new collaborative project practices ”, International Journal of Managing Projects in Business , Vol. 5 , No. 3 , pp. 364 – 376 .

Jarzabkowski, and Spee, 2009 Jarzabkowski , P. and Spee , A. P. ( 2009 ) “ Strategy-as-practice: A review and future directions for the field ”, International Journal of Management Reviews , Vol. 11 , No. 1 , pp. 69 – 95 .

Johnson, Langley, Melin, and Whittington, 2007 Johnson , G. , Langley , A. , Melin , L. and Whittington , R. ( 2007 ), Strategy as Practice – Research Directions and Resources , Cambridge University Press .

Ju, and Rowlinson, 2014 Ju , C. and Rowlinson , S. ( 2014 ) “ Institutional determinants of construction safety management strategies of contractors in Hong Kong ”, Construction Management & Economics . Vol. 32 ( 7/8 ), pp. 725 – 736 .

Klitgaard, Beck, Andersen, Jeppesen, Nissen, and Buhl, 2017 Klitgaard , A. , Beck , F. , Andersen , M. , Jeppesen , R. D. , Nissen , S. B. , and Buhl , H. ( 2017 ). “Towards the use of knotworking for increasing innovation in construction projects In: Chan , P. W. (Ed.) and Neilson , C. J. (Ed.), Proceedings 33rd Annual ARCOM Conference, 4-6 September 2017, Fitzwilliam College, Cambridge, UK. Association of Researchers in Construction Management, 420 – 429 .

Koch, Sage, Dainty, and Simonsen, 2015 Koch , C. , Sage , D. , Dainty , A. , and Simonsen , R. ( 2015 ). Understanding operations strategizing in project-based organisations: middle managers’ interaction and strategy praxis . Engineering Project Organization Journal , Vol. 5 ( 2-3 ), 106 – 117 .

Kreiner, 1996 Kreiner , K. ( 1996 ) “ In search of relevance: Project management in drifting environments ”, Scandinavian Journal of Mangement , Vol. 11 , No. 4 , pp. 335 – 346 .

Ling, and Lee, 2012 Ling , F. Y. Y. and Lee , S. Y. ( 2012 ) “ Careers development in construction firms: application of Sun Tzu’s Art of War principles ”, Engineering Construction & Architectural Management , Vol. 19 , No. 2 , pp. 173 – 191 .

Löwstedt, Räisänen, and Leiringer, 2018 Löwstedt , M. , Räisänen , C. and Leiringer , R. ( 2018 ). “ Doing strategy in project-based organizations: Actors and patterns of action ”, International Journal of Project Management , Vol. 36 , No. 6 , pp. 889 – 898 .

Padalkar, and Gopinath, 2016 Padalkar , M. and Gopinath , S. ( 2016 ), “ Six decades of project management research: Thematic trends and future opportunities ”, International Journal of Project Management . Vol. 34 , No. 7 , pp. 1,305 – 1,321 .

Sage, Dainty, and Brookes, 2012 Sage , D. , Dainty , A. and Brookes , N. ( 2012 ) “ A ‘Strategy-as-Practice’” exploration of lean construction strategizing. ”, Building Research & Information . Vol. No. 2 , pp. 221 – 230 .

Söderholm, 2008 Söderholm , A. ( 2008 ). “ Project management of unexpected events ”. International Journal of Project Management , Vol. 26 , No 1 , pp. 80 – 86 .

Vit, 2011 Vit , G. B. ( 2011 ), “ Competing logics: Project failure in Gaspesia ”, European Management Journal . Vol. 29 , No. 3 , pp. 234 – 244 .

Whittington, Molloy, Mayer, and Smith, 2006 Whittington , R. , Molloy , E. , Mayer , M. and Smith , A. ( 2006 ), “ Practices of Strategising/Organising-broadening Strategy Work and Skills ”, Long Range Planning , Vol. 39 , No. 6 , pp. 615 – 629 .

Whyte, Ewenstein, Hales, and Tidd Whyte , J. , Ewenstein , B. , Hales , M. and Tidd , J. , “ Visualizing Knowledge in Project-Based Work ”, Long Range Planning , Vol. 41 , No. 1 , pp. 74 – 92 .

Wright, 2005 Wright , A. ( 2005 ), “ The role of scenarios as prospective sensemaking devices ”, Management Decision , Vol. 43 , No. 1 , pp. 86 – 101 .

Book Chapters

All feedback is valuable.

Please share your general feedback

Report an issue or find answers to frequently asked questions

Contact Customer Support

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

A systematic review of the evolution of the concept of resilience in the construction industry.

1. Introduction

2. methodology, 2.1. search strategy, 2.2. selection, 2.3. extraction, 2.4. assessment, 3.1. the subject of resilience, 3.1.1. specific class, 3.1.2. general class, 3.1.3. temporal distribution of resilience subjects, 3.2. the impact factors, 3.2.1. natural and environmental factors, 3.2.2. human and external factors, 3.2.3. temporal distribution of impact factors, 3.3. capabilities of the subject, 3.3.1. management and operations, 3.3.2. performance and development, 3.3.3. temporal distribution of subject capabilities, 4. discussion, 4.1. the evolution and ambiguity of the early concept of resilience, 4.2. complexity of impact types and functional failures, 4.3. redefining the concept of resilience in a vuca environment, 4.4. future directions and suggestions, 5. conclusions, data availability statement, acknowledgments, conflicts of interest.

• Zhang, B.; Mei, Y.; Xiong, Y.; Liu, Y. Can Digital Transformation Promote Service Innovation Performance of Construction Enterprises? The Mediating Role of Dual Innovation. Sustainability 2024 , 16 , 1176. [ Google Scholar ] [ CrossRef ]
• Murtagh, N.; Scott, L.; Fan, J. Sustainable and Resilient Construction: Current Status and Future Challenges. J. Clean. Prod. 2020 , 268 , 122264. [ Google Scholar ] [ CrossRef ]
• Cambraia, F.B.; Saurin, T.A.; Bulhões, I.R.; Formoso, C.T. A Knowledge Framework of Participation Supportive of Resilient and Safe Construction Projects: A Systematic Review. Saf. Sci. 2024 , 175 , 106494. [ Google Scholar ] [ CrossRef ]
• Ranasinghe, U.; Jefferies, M.; Davis, P.; Pillay, M. Resilience Engineering Indicators and Safety Management: A Systematic Review. Saf. Health Work 2020 , 11 , 127–135. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Robbins, J.D.; Wang, J.; Esmaeili, B. Review of Safety Resilience in Construction: Current Research Status, Challenges, and Future Needs. In Proceedings of the Construction Research Congress 2022: Health and Safety, Workforce, and Education, Arlington, VA, USA, 9–12 March 2022; Jazizadeh, F., Shealy, T., Garvin, M.J., Eds.; Amer Soc Civil Engineers: New York, NY, USA, 2022; pp. 393–402. [ Google Scholar ]
• Bhamra, R.; Dani, S.; Burnard, K. Resilience: The Concept, a Literature Review and Future Directions. Int. J. Prod. Res. 2011 , 49 , 5375–5393. [ Google Scholar ] [ CrossRef ]
• Bocchini, P.; Frangopol, D.M.; Ummenhofer, T.; Zinke, T. Resilience and Sustainability of Civil Infrastructure: Toward a Unified Approach. J. Infrastruct. Syst. 2014 , 20 , 04014004. [ Google Scholar ] [ CrossRef ]
• Holling, C.S. Resilience and Stability of Ecological Systems. Annu. Rev. Ecol. Evol. Syst. 1973 , 4 , 1–23. [ Google Scholar ] [ CrossRef ]
• Annarelli, A.; Nonino, F. Strategic and Operational Management of Organizational Resilience: Current State of Research and Future Directions. Omega 2016 , 62 , 1–18. [ Google Scholar ] [ CrossRef ]
• Pires Ribeiro, J.; Barbosa-Povoa, A. Supply Chain Resilience: Definitions and Quantitative Modelling Approaches—A Literature Review. Comput. Ind. Eng. 2018 , 115 , 109–122. [ Google Scholar ] [ CrossRef ]
• Conz, E.; Magnani, G. A Dynamic Perspective on the Resilience of Firms: A Systematic Literature Review and a Framework for Future Research. Eur. Manag. J. 2020 , 38 , 400–412. [ Google Scholar ] [ CrossRef ]
• Zhou, Y.; Wang, J.; Yang, H. Resilience of Transportation Systems: Concepts and Comprehensive Review. IEEE Trans. Intell. Transp. Syst. 2019 , 20 , 4262–4276. [ Google Scholar ] [ CrossRef ]
• Liu, W.; Song, Z. Review of Studies on the Resilience of Urban Critical Infrastructure Networks. Reliab. Eng. Syst. Saf. 2020 , 193 , 106617. [ Google Scholar ] [ CrossRef ]
• Foster, K.; Roche, M.; Delgado, C.; Cuzzillo, C.; Giandinoto, J.-A.; Furness, T. Resilience and Mental Health Nursing: An Integrative Review of International Literature. Int. J. Ment. Health Nurs. 2019 , 28 , 71–85. [ Google Scholar ] [ CrossRef ]
• Quitana, G.; Molinos-Senante, M.; Chamorro, A. Resilience of Critical Infrastructure to Natural Hazards: A Review Focused on Drinking Water Systems. Int. J. Disaster Risk Reduct. 2020 , 48 , 101575. [ Google Scholar ] [ CrossRef ]
• Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021 , 372 , n71. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Afzal, M.; Li, R.Y.M.; Shoaib, M.; Ayyub, M.F.; Tagliabue, L.C.; Bilal, M.; Ghafoor, H.; Manta, O. Delving into the Digital Twin Developments and Applications in the Construction Industry: A PRISMA Approach. Sustainability 2023 , 15 , 16436. [ Google Scholar ] [ CrossRef ]
• Li, R.Y.M.; Li, Y.L.; Crabbe, M.J.C.; Manta, O.; Shoaib, M. The Impact of Sustainability Awareness and Moral Values on Environmental Laws. Sustainability 2021 , 13 , 5882. [ Google Scholar ] [ CrossRef ]
• Liao, L.; Yang, C.; Quan, L. Construction Supply Chain Management: A Systematic Literature Review and Future Development. J. Clean. Prod. 2023 , 382 , 135230. [ Google Scholar ] [ CrossRef ]
• Ning, Y.; Gao, S. A Resilience Framework to Explorative Quality Management in Innovative Building Projects. J. Eng. Technol. Manag. 2021 , 62 , 101654. [ Google Scholar ] [ CrossRef ]
• Wedawatta, G.; Ingirige, B.; Amaratunga, D. Building up resilienc e of construction sector smes and their supply chains to extreme weather events. Int. J. Strateg. Prop. Manag. 2010 , 14 , 362–375. [ Google Scholar ] [ CrossRef ]
• Ranasinghe, U.; Jefferies, M.; Davis, P.; Pillay, M. Enabling a Resilient Work Environment: An Analysis of Causal Relationships between Resilience Engineering Factors in Construction Refurbishment Projects. J. Constr. Eng. Manage. 2023 , 149 , 04023078. [ Google Scholar ] [ CrossRef ]
• Zhang, W.; Dong, H.; Wen, J.; Han, Q. A Resilience-Based Decision Framework for Post-Earthquake Restoration of Bridge Networks under Uncertainty. Struct. Infrastruct. Eng. 2023 , 1–16. [ Google Scholar ] [ CrossRef ]
• Li, Y.; Dong, Y.; Frangopol, D.M.; Gautam, D. Long-Term Resilience and Loss Assessment of Highway Bridges under Multiple Natural Hazards. Struct. Infrastruct. Eng. 2020 , 16 , 626–641. [ Google Scholar ] [ CrossRef ]
• Dong, Y.; Frangopol, D.M. Probabilistic Time-Dependent Multihazard Life-Cycle Assessment and Resilience of Bridges Considering Climate Change. J. Perform. Constr. Facil. 2016 , 30 , 04016034. [ Google Scholar ] [ CrossRef ]
• Akiyama, M.; Frangopol, D.M.; Ishibashi, H. Toward Life-Cycle Reliability-, Risk- and Resilience-Based Design and Assessment of Bridges and Bridge Networks under Independent and Interacting Hazards: Emphasis on Earthquake, Tsunami and Corrosion. Struct. Infrastruct. Eng. 2020 , 16 , 26–50. [ Google Scholar ] [ CrossRef ]
• Shafieezadeh, A.; Ivey Burden, L. Scenario-Based Resilience Assessment Framework for Critical Infrastructure Systems: Case Study for Seismic Resilience of Seaports. Reliab. Eng. Syst. Saf. 2014 , 132 , 207–219. [ Google Scholar ] [ CrossRef ]
• Verschuur, J.; Pant, R.; Koks, E.; Hall, J. A Systemic Risk Framework to Improve the Resilience of Port and Supply-Chain Networks to Natural Hazards. Marit. Econ. Logist. 2022 , 24 , 489–506. [ Google Scholar ] [ CrossRef ]
• John, A.; Yang, Z.; Riahi, R.; Wang, J. A Risk Assessment Approach to Improve the Resilience of a Seaport System Using Bayesian Networks. Ocean Eng. 2016 , 111 , 136–147. [ Google Scholar ] [ CrossRef ]
• Azadeh, A.; Salehi, V.; Arvan, M.; Dolatkhah, M. Assessment of Resilience Engineering Factors in High-Risk Environments by Fuzzy Cognitive Maps: A Petrochemical Plant. Saf. Sci. 2014 , 68 , 99–107. [ Google Scholar ] [ CrossRef ]
• Xiong, C.; Huang, J.; Lu, X. Framework for City-scale Building Seismic Resilience Simulation and Repair Scheduling with Labor Constraints Driven by Time–History Analysis. Comput. Aided Civ. Eng 2020 , 35 , 322–341. [ Google Scholar ] [ CrossRef ]
• Katal, A.; Mortezazadeh, M.; Wang, L. (Leon) Modeling Building Resilience against Extreme Weather by Integrated CityFFD and CityBEM Simulations. Appl. Energy 2019 , 250 , 1402–1417. [ Google Scholar ] [ CrossRef ]
• Bruneau, M.; Reinhorn, A. Exploring the Concept of Seismic Resilience for Acute Care Facilities. Earthq. Spectra 2007 , 23 , 41–62. [ Google Scholar ] [ CrossRef ]
• Osman, M.M.; Sevinc, H. Adaptation of Climate-Responsive Building Design Strategies and Resilience to Climate Change in the Hot/Arid Region of Khartoum, Sudan. Sustain. Cities Soc. 2019 , 47 , 101429. [ Google Scholar ] [ CrossRef ]
• Feng, X.; Xiu, C.; Bai, L.; Zhong, Y.; Wei, Y. Comprehensive Evaluation of Urban Resilience Based on the Perspective of Landscape Pattern: A Case Study of Shenyang City. Cities 2020 , 104 , 102722. [ Google Scholar ] [ CrossRef ]
• Angulo, A.M.; Mur, J.; Trívez, F.J. Measuring Resilience to Economic Shocks: An Application to Spain. Ann. Reg. Sci. 2018 , 60 , 349–373. [ Google Scholar ] [ CrossRef ]
• Molina Hutt, C.; Almufti, I.; Willford, M.; Deierlein, G. Seismic Loss and Downtime Assessment of Existing Tall Steel-Framed Buildings and Strategies for Increased Resilience. J. Struct. Eng. 2016 , 142 , C4015005. [ Google Scholar ] [ CrossRef ]
• Azmi, N.A.; Sweis, G.; Sweis, R.; Sammour, F. Exploring Implementation of Blockchain for the Supply Chain Resilience and Sustainability of the Construction Industry in Saudi Arabia. Sustainability 2022 , 14 , 6427. [ Google Scholar ] [ CrossRef ]
• Yao, H.; Wang, K. Concentrated or Dispersed: The Effects of Subcontracting Organizational Arrangements on Construction Project Resilience. J. Manag. Eng. 2024 , 40 , 04024017. [ Google Scholar ] [ CrossRef ]
• Gerami Seresht, N. Enhancing Resilience in Construction against Infectious Diseases Using Stochastic Multi-Agent Approach. Autom. Constr. 2022 , 140 , 104315. [ Google Scholar ] [ CrossRef ]
• Trinh, M.T.; Feng, Y.; Mohamed, S. Framework for Measuring Resilient Safety Culture in Vietnam’s Construction Environment. J. Constr. Eng. Manag. 2019 , 145 , 04018127. [ Google Scholar ] [ CrossRef ]
• Wang, D.; Wu, Y.; Zhang, K. Interplay of Resources and Institutions in Improving Organizational Resilience of Construction Projects: A Dynamic Perspective. EMJ-Eng. Manag. J. 2023 , 35 , 346–357. [ Google Scholar ] [ CrossRef ]
• He, Z.; Wang, G.; Chen, H.; Zou, Z.; Yan, H.; Liu, L. Measuring the Construction Project Resilience from the Perspective of Employee Behaviors. Buildings 2022 , 12 , 56. [ Google Scholar ] [ CrossRef ]
• Peñaloza, G.A.; Saurin, T.A.; Formoso, C.T. Monitoring Complexity and Resilience in Construction Projects: The Contribution of Safety Performance Measurement Systems. Appl. Ergon. 2020 , 82 , 102978. [ Google Scholar ] [ CrossRef ]
• Hilu, K.A.; Hiyassat, M.A. Qualitative Assessment of Resilience in Construction Projects. Constr. Innov. 2023 , 24 , 1297–1319. [ Google Scholar ] [ CrossRef ]
• Milat, M.; Knezić, S.; Sedlar, J. Resilient Scheduling as a Response to Uncertainty in Construction Projects. Appl. Sci. 2021 , 11 , 6493. [ Google Scholar ] [ CrossRef ]
• Hamerski, D.C.; Saurin, T.A.; Formoso, C.T.; Isatto, E.L. The Contributions of the Last Planner System to Resilient Performance in Construction Projects. Constr. Manag. Econ. 2024 , 42 , 328–345. [ Google Scholar ] [ CrossRef ]
• Wang, D.; Wang, P.; Liu, Y. The Emergence Process of Construction Project Resilience: A Social Network Analysis Approach. Buildings 2022 , 12 , 822. [ Google Scholar ] [ CrossRef ]
• Trinh, M.T.; Feng, Y. A Maturity Model for Resilient Safety Culture Development in Construction Companies. Buildings 2022 , 12 , 733. [ Google Scholar ] [ CrossRef ]
• Feng, Y.; Trinh, M.T. Developing Resilient Safety Culture for Construction Projects. J. Constr. Eng. Manag. 2019 , 145 , 04019069. [ Google Scholar ] [ CrossRef ]
• Saldanha, M.C.W.; Araújo, L.L.F.; Arcuri, R.; Vidal, M.C.R.; De Carvalho, P.V.R.; De Carvalho, R.J.M. Identifying Routes and Organizational Practices for Resilient Performance: A Study in the Construction Industry. Cogn. Technol. Work 2022 , 24 , 521–535. [ Google Scholar ] [ CrossRef ]
• Trinh, M.T.; Feng, Y. Impact of Project Complexity on Construction Safety Performance: Moderating Role of Resilient Safety Culture. J. Constr. Eng. Manag. 2020 , 146 , 04019103. [ Google Scholar ] [ CrossRef ]
• Chih, Y.-Y.; Hsiao, C.Y.-L.; Zolghadr, A.; Naderpajouh, N. Resilience of Organizations in the Construction Industry in the Face of COVID-19 Disturbances: Dynamic Capabilities Perspective. J. Manag. Eng. 2022 , 38 , 04022002. [ Google Scholar ] [ CrossRef ]
• Malik, A.; Khan, K.I.A.; Qayyum, S.; Ullah, F.; Maqsoom, A. Resilient Capabilities to Tackle Supply Chain Risks: Managing Integration Complexities in Construction Projects. Buildings 2022 , 12 , 1322. [ Google Scholar ] [ CrossRef ]
• Nassereddine, H.; Seo, K.W.; Rybkowski, Z.K.; Schranz, C.; Urban, H. Propositions for a Resilient, Post-COVID-19 Future for the AEC Industry. Front. Built Environ. 2021 , 7 , 687021. [ Google Scholar ] [ CrossRef ]
• Chen, Y.; McCabe, B.; Hyatt, D. A Resilience Safety Climate Model Predicting Construction Safety Performance. Saf. Sci. 2018 , 109 , 434–445. [ Google Scholar ] [ CrossRef ]
• Gao, L.; Luo, X.; Wang, Y.; Zhang, N.; Deng, X. Retention in Challenging International Construction Assignments: Role of Expatriate Resilience. J. Constr. Eng. Manag. 2024 , 150 , 04023158. [ Google Scholar ] [ CrossRef ]
• Liu, K.; Liu, Y.; Kou, Y. Study on Construction Safety Management in Megaprojects from the Perspective of Resilient Governance. Saf. Sci. 2024 , 173 , 106442. [ Google Scholar ] [ CrossRef ]
• Xu, S.; Lin, B.; Zou, P.X.W. Examining Construction Group’s Safety Attitude Resilience under Major Disruptions: An Agent-Based Modelling Approach. Saf. Sci. 2023 , 161 , 106071. [ Google Scholar ] [ CrossRef ]
• Cai, B.; Xie, M.; Liu, Y.; Liu, Y.; Feng, Q. Availability-Based Engineering Resilience Metric and Its Corresponding Evaluation Methodology. Reliab. Eng. Syst. Saf. 2018 , 172 , 216–224. [ Google Scholar ] [ CrossRef ]
• Kilanitis, I.; Sextos, A. Integrated Seismic Risk and Resilience Assessment of Roadway Networks in Earthquake Prone Areas. Bull. Earthq. Eng. 2019 , 17 , 181–210. [ Google Scholar ] [ CrossRef ]
• Wang, H.; Zhou, J.; Dun, Z.; Cheng, J.; Li, H.; Dun, Z. Resilience Evaluation of High-Speed Railway Subgrade Construction Systems in Goaf Sites. Sustainability 2022 , 14 , 7806. [ Google Scholar ] [ CrossRef ]
• Zhang, W.; Wang, N.; Nicholson, C. Resilience-Based Post-Disaster Recovery Strategies for Road-Bridge Networks. Struct. Infrastruct. Eng. 2017 , 13 , 1404–1413. [ Google Scholar ] [ CrossRef ]
• Zhang, W.; Wang, N. Resilience-Based Risk Mitigation for Road Networks. Struct. Saf. 2016 , 62 , 57–65. [ Google Scholar ] [ CrossRef ]
• Dong, Y.; Frangopol, D.M. Risk and Resilience Assessment of Bridges under Mainshock and Aftershocks Incorporating Uncertainties. Eng. Struct. 2015 , 83 , 198–208. [ Google Scholar ] [ CrossRef ]
• Alipour, A.; Shafei, B. Seismic Resilience of Transportation Networks with Deteriorating Components. J. Struct. Eng. 2016 , 142 , C4015015. [ Google Scholar ] [ CrossRef ]
• Chen, Z.; Hammad, A.W.A.; Alyami, M. Building Construction Supply Chain Resilience under Supply and Demand Uncertainties. Autom. Constr. 2024 , 158 , 105190. [ Google Scholar ] [ CrossRef ]
• Xie, D.; Xin, J.; Wang, H.; Xiao, L. Identifying Critical Factors Affecting the Resilience of Additive Manufacturing Architecture Supply Chain. Buildings 2023 , 13 , 997. [ Google Scholar ] [ CrossRef ]
• Cherian, T.M.; Mathivathanan, D.; Arun SJ, C.J.; Ramasubramaniam, M.; Alathur, S. Influence of Supply Chain Resilience, Information Technology Capabilities and Agility on Cost and Delivery Performance in Construction Supply Chains: An Indian Perspective. Int. J. Logist. Manag. 2022 , 34 , 1050–1076. [ Google Scholar ] [ CrossRef ]
• Ekanayake, E.M.A.C.; Shen, G.Q.P.; Kumaraswamy, M.M.; Owusu, E.K.; Saka, A.B. Modeling Supply Chain Resilience in Industrialized Construction: A Hong Kong Case. J. Constr. Eng. Manag. 2021 , 147 , 05021009. [ Google Scholar ] [ CrossRef ]
• Cheng, S.; Zhou, X.; Zhang, Y.; Duan, M.; Gao, J. Study on Resilience Factors and Enhancement Strategies in Prefabricated Building Supply Chains. Buildings 2024 , 14 , 195. [ Google Scholar ] [ CrossRef ]
• Wehbe, F.; Hattab, M.A.; Hamzeh, F. Exploring Associations between Resilience and Construction Safety Performance in Safety Networks. Saf. Sci. 2016 , 82 , 338–351. [ Google Scholar ] [ CrossRef ]
• Guo, Q.; Amin, S.; Hao, Q.; Haas, O. Resilience Assessment of Safety System at Subway Construction Sites Applying Analytic Network Process and Extension Cloud Models. Reliab. Eng. Syst. Saf. 2020 , 201 , 106956. [ Google Scholar ] [ CrossRef ]
• Argyroudis, S.A.; Mitoulis, S.A.; Chatzi, E.; Baker, J.W.; Brilakis, I.; Gkoumas, K.; Vousdoukas, M.; Hynes, W.; Carluccio, S.; Keou, O.; et al. Digital Technologies Can Enhance Climate Resilience of Critical Infrastructure. Clim. Risk Manag. 2022 , 35 , 100387. [ Google Scholar ] [ CrossRef ]
• Iannacone, L.; Sharma, N.; Tabandeh, A.; Gardoni, P. Modeling Time-Varying Reliability and Resilience of Deteriorating Infrastructure. Reliab. Eng. Syst. Saf. 2022 , 217 , 108074. [ Google Scholar ] [ CrossRef ]
• Lounis, Z.; McAllister, T.P. Risk-Based Decision Making for Sustainable and Resilient Infrastructure Systems. J. Struct. Eng. 2016 , 142 , F4016005. [ Google Scholar ] [ CrossRef ]
• Dao, J.; Ng, S.T.; Yang, Y.; Zhou, S.; Xu, F.J.; Skitmore, M. Semantic Framework for Interdependent Infrastructure Resilience Decision Support. Autom. Constr. 2021 , 130 , 103852. [ Google Scholar ] [ CrossRef ]
• Burton, H.V.; Deierlein, G.; Lallemant, D.; Lin, T. Framework for Incorporating Probabilistic Building Performance in the Assessment of Community Seismic Resilience. J. Struct. Eng. 2016 , 142 , C4015007. [ Google Scholar ] [ CrossRef ]
• Franchin, P.; Cavalieri, F. Probabilistic Assessment of Civil Infrastructure Resilience to Earthquakes. Comput. Aided Civ. Eng 2015 , 30 , 583–600. [ Google Scholar ] [ CrossRef ]
• Wei, W.; Mojtahedi, M.; Yazdani, M.; Kabirifar, K. The Alignment of Australia’s National Construction Code and the Sendai Framework for Disaster Risk Reduction in Achieving Resilient Buildings and Communities. Buildings 2021 , 11 , 429. [ Google Scholar ] [ CrossRef ]
• Yang, Y.; Ng, S.T.; Xu, F.J.; Skitmore, M. Towards Sustainable and Resilient High Density Cities through Better Integration of Infrastructure Networks. Sustain. Cities Soc. 2018 , 42 , 407–422. [ Google Scholar ] [ CrossRef ]
• Jiang, S.; Ling, F.Y.Y.; Ma, G. Fostering Resilience in Project Teams: Adaptive Structuration Perspective. J. Manag. Eng. 2024 , 40 , 04023047. [ Google Scholar ] [ CrossRef ]
• Lu, C.; Yu, D.; Luo, Q.; Xu, C. A Study of the Effects of Job Stress on the Psychosocial Safety Behavior of Construction Workers: The Mediating Role of Psychological Resilience. Buildings 2023 , 13 , 1930. [ Google Scholar ] [ CrossRef ]
• Aasen, A.F.; Klakegg, O.J. Human Resilience and Cultural Change in the Construction Industry: Communication and Relationships in a Time of Enforced Adaptation. Front. Built Environ. 2023 , 9 , 1287483. [ Google Scholar ] [ CrossRef ]
• Chen, Y.; McCabe, B.; Hyatt, D. Impact of Individual Resilience and Safety Climate on Safety Performance and Psychological Stress of Construction Workers: A Case Study of the Ontario Construction Industry. J. Saf. Res. 2017 , 61 , 167–176. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Nwaogu, J.M.; Chan, A.P.C. The Impact of Coping Strategies and Individual Resilience on Anxiety and Depression among Construction Supervisors. Buildings 2022 , 12 , 2148. [ Google Scholar ] [ CrossRef ]
• Wang, T.-K.; Zhang, Q.; Chong, H.-Y.; Wang, X. Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA). Sustainability 2017 , 9 , 289. [ Google Scholar ] [ CrossRef ]
• Shishodia, A.; Verma, P.; Dixit, V. Supplier Evaluation for Resilient Project Driven Supply Chain. Comput. Ind. Eng. 2019 , 129 , 465–478. [ Google Scholar ] [ CrossRef ]
• Thurber, C. An Introduction to Seismology, Earthquakes, and Earth Structure. EoS Trans. 2003 , 84 , 209–210. [ Google Scholar ] [ CrossRef ]
• Morse, S.S.; Mazet, J.A.; Woolhouse, M.; Parrish, C.R.; Carroll, D.; Karesh, W.B.; Zambrana-Torrelio, C.; Lipkin, W.I.; Daszak, P. Prediction and Prevention of the next Pandemic Zoonosis. Lancet 2012 , 380 , 1956–1965. [ Google Scholar ] [ CrossRef ]
• Cutter, S.L.; Boruff, B.J.; Shirley, W.L. Social Vulnerability to Environmental Hazards*. Soc. Sci. Q. 2003 , 84 , 242–261. [ Google Scholar ] [ CrossRef ]
• Sauter, S.L.; Murphy, L.R.; Hurrell, J.J. Prevention of Work-Related Psychological Disorders. A National Strategy Proposed by the National Institute for Occupational Safety and Health (NIOSH). Am. Psychol. 1990 , 45 , 1146–1158. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Daboun, O.; Md Yusof, A.; Khoso, A.R. Relationship Management in Construction Projects: Systematic Literature Review. Eng. Manag. J. 2023 , 35 , 120–143. [ Google Scholar ] [ CrossRef ]
• Karuppiah, K.; Sankaranarayanan, B.; Ali, S.M. A Systematic Review of Sustainable Business Models: Opportunities, Challenges, and Future Research Directions. Decis. Anal. J. 2023 , 8 , 100272. [ Google Scholar ] [ CrossRef ]
• Grzybowska, K.; Tubis, A.A. Supply Chain Resilience in Reality VUCA-An International Delphi Study. Sustainability 2022 , 14 , 10711. [ Google Scholar ] [ CrossRef ]
• Li, K.; Ma, J.; Gao, J.; Xu, C.; Li, W.; Mao, Y.; Jiang, S. Resilience Assessment of Urban Distribution Network Under Heavy Rain: A Knowledge- Informed Data-Driven Approach. IEEE Access 2023 , 11 , 63741–63750. [ Google Scholar ] [ CrossRef ]
• Yang, Y.; Ng, S.T.; Zhou, S.; Xu, F.J.; Li, D.; Li, H. A Federated Pre-Event Community Resilience Approach for Assessing Physical and Social Sub-Systems: An Extreme Rainfall Case in Hong Kong. Sustain. Cities Soc. 2020 , 52 , 101859. [ Google Scholar ] [ CrossRef ]
• Bozza, A.; Asprone, D.; Fabbrocino, F. Urban Resilience: A Civil Engineering Perspective. Sustainability 2017 , 9 , 103. [ Google Scholar ] [ CrossRef ]
• Hao, H.; Bi, K.; Chen, W.; Pham, T.M.; Li, J. Towards next Generation Design of Sustainable, Durable, Multi-Hazard Resistant, Resilient, and Smart Civil Engineering Structures. Eng. Struct. 2023 , 277 , 115477. [ Google Scholar ] [ CrossRef ]
• Herrera, H. Resilience for Whom? The Problem Structuring Process of the Resilience Analysis. Sustainability 2017 , 9 , 1196. [ Google Scholar ] [ CrossRef ]
• Juncos, A.E. Resilience in Peacebuilding: Contesting Uncertainty, Ambiguity, and Complexity. Contemp. Secur. Policy 2018 , 39 , 559–574. [ Google Scholar ] [ CrossRef ]
• Li, Y.; Lei, S.; Sun, W.; Hu, C.; Hou, Y. A Distributionally Robust Resilience Enhancement Strategy for Distribution Networks Considering Decision-Dependent Contingencies. IEEE Trans. Smart Grid 2024 , 15 , 1450–1465. [ Google Scholar ] [ CrossRef ]
• Dolla, T.; Jain, K.; Delhi, V.S.K. Strategies for Digital Transformation in Construction Projects: Stakeholders’ Perceptions and Actor Dynamics for Industry 4.0. J. Inf. Technol. Constr. 2023 , 28 , 151–175. [ Google Scholar ] [ CrossRef ]
• Browder, R.E.; Dwyer, S.M.; Koch, H. Upgrading Adaptation: How Digital Transformation Promotes Organizational Resilience. Strateg. Entrep. J. 2024 , 18 , 128–164. [ Google Scholar ] [ CrossRef ]
• Yang, Y.; Ng, S.T.; Li, N.; Xu, X.; Xu, P.; Xu, F.J. Adapting HLA-Based Co-Simulation for Interdependent Infrastructure Resilience Management. Autom. Constr. 2023 , 150 , 104860. [ Google Scholar ] [ CrossRef ]
• Rathnasiri, P.; Adeniyi, O.; Thurairajah, N. Data-Driven Approaches to Built Environment Flood Resilience: A Scientometric and Critical Review. Adv. Eng. Inform. 2023 , 57 , 102085. [ Google Scholar ] [ CrossRef ]
• Heidari, A.; Peyvastehgar, Y.; Amanzadegan, M. A Systematic Review of the BIM in Construction: From Smart Building Management to Interoperability of BIM & AI. Archit. Sci. Rev. 2024 , 67 , 237–254. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Share and Cite

Li, J.; Yu, H.; Deng, X. A Systematic Review of the Evolution of the Concept of Resilience in the Construction Industry. Buildings 2024 , 14 , 2643. https://doi.org/10.3390/buildings14092643

Li J, Yu H, Deng X. A Systematic Review of the Evolution of the Concept of Resilience in the Construction Industry. Buildings . 2024; 14(9):2643. https://doi.org/10.3390/buildings14092643

Li, Jinjing, Haizhe Yu, and Xiaopeng Deng. 2024. "A Systematic Review of the Evolution of the Concept of Resilience in the Construction Industry" Buildings 14, no. 9: 2643. https://doi.org/10.3390/buildings14092643

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Impacts of long-term transit system disruptions and transitional periods on travelers: a systematic review

• Open access
• Published: 27 August 2024
• Volume 1 , article number  15 , ( 2024 )

Cite this article

You have full access to this open access article

• Mohamed G. Noureldin 1 &
• Ehab Diab 1  

Governments around the world are heavily investing in building new transit infrastructures and expanding existing ones. The construction of these projects does not happen overnight and can lead to extended long-term disruptions in the transit network, which can have undesirable impacts. Research regarding such disruptive periods, or transitional periods, seems to be thematically and geographically dispersed in the literature. Similarly, a consolidated understanding of the impacts of long-term transit service disruptions due to other causes, such as labor strikes and transit system failures, on travelers’ behavior seems missing from the literature. Using a systematic review method, this study aims at providing a comprehensive review of the academic literature that focused on analyzing the impacts of the aforementioned issues on transit users’ travel behavior and perceptions, while understanding the mitigation strategies applied to address these effects. Given the wide array of disruption types, durations, spatial coverage, and the modes affected, the review indicates a dearth of knowledge regarding their impacts along with a very limited understanding of the relative benefits of mitigation strategies. The most common impacts are mode changes. Some evidence, which is rather limited, shows that transit users did return to their previous travel behavior after the end of long-term service disruptions. The study offers a better understanding of the relative impacts of transit systems’ long-term disruptions and transitional periods, while highlighting important gaps in the current literature.

Explore related subjects

• Artificial Intelligence

Avoid common mistakes on your manuscript.

1 Introduction

Governments around the world are heavily investing in building new transit infrastructure or upgrading or expanding existing ones [ 1 , 2 ]. This is in order to draw higher levels of transit ridership, while decreasing the attractiveness of non-sustainable modes of transport (such as private car use). Achieving these goals would help societies in reaching their emerging climate goals by reducing the emissions from the transport sector. The construction of these new transit projects does not happen overnight and can take from a few weeks to several months or even years, which can lead to extended long-term disruptions in the transit network. These long-term disruptions, or transitional periods, can have undesirable impacts on people’s travel behavior, and they could also increase traffic congestion as well as decrease air quality in the short and long terms. The impacts of these transitional periods, in general, seem thematically and geographically dispersed. Similarly, a consolidated understanding of the impacts of long-term disruptions due to other causes, such as labor strikes and transit system failures, on travelers’ behavior seems to be missing from the literature. Albeit different in their origins and characteristics, both transitional periods and long-term disruptions share several attributes, especially in terms of their effects on travel behavior as well as travelers’ needs and perceptions. They both impact travelers for an extended period, which can lead to them developing new habits and attitudes to adapt to such changes. Therefore, both transitional periods and long-term disruptions that resulted from transit system construction and repairs, infrastructure failure, and labor strikes were included in this study.

In this study, the term “transitional periods” refers to any planned changes in the transit system that alter the service’s structure and quality and require an extended period of disruption of regular service operations to implement, such as the construction of new transit infrastructure or the substantial upgrade of such infrastructure. After these periods, users expect to have improved transit service quality or options (Fig.  1 ), which may have an impact on their travel behavior and perception. It should be noted that not all infrastructure-related disruptions should be considered transitional periods, as some projects may not improve service afterwards. For example, maintenance-related projects can lead to similar levels of service.

Conceptual framework

The term “long-term disruptions” was used to refer to any long-term transit system disruptions in which transit returns to its initial service configuration after the disruption, with no to minor changes to the service. For both types of disruptions, transit agencies and cities implement a wide array of mitigation strategies. Therefore, this study aims at achieving the following three goals: comprehending the current state of knowledge in the academic literature regarding the impacts of long-term transit system disruptions and transitional periods on travel behavior, travelers’ perceptions and travel needs; understanding the applied mitigation strategies and technologies used to address any undesirable impacts of these disruptions; and synthesizing the findings to identify areas of overlap between studies and prominent gaps in the current state of knowledge. Exploring these issues together informs transit planners and practitioners of lessons learned across studies regarding similarities and differences in terms of impacts, thereby guiding their future practice.

2 Research context

A considerable number of academic studies explored the factors affecting travel behavior and ridership at the city, route, and stop level during regular operational periods of the transit service. Several studies provided a systematic literature review of these factors’ impacts on travel behavior and ridership [ 3 , 4 ]. Nevertheless, there are numerous types of disruptions that can affect the normal operations of the transit network. There are also various classifications for these disruptions. Some studies differentiated between them in terms of whether they are planned or unplanned [ 5 , 6 , 7 ], while another categorization can be in terms of duration (long-term or short-term disruption) as was discussed by Kattan, de Barros [ 8 ].

Disruptions can also be divided based on the transport mode or system they affect (like rail transit or road disruptions) or in terms of magnitude—whether these disruptions resulted in closures of the affected transit stations or only caused the redirection of the stations’ lines, for example [ 9 ]. Furthermore, Zhu and Levinson [ 10 ] categorized transport network disruptions based on their causes; this included transit strikes, bridge closures, earthquakes and special events. A considerable number of researchers investigated the impacts of short-term transit system disruptions that last from a few minutes to hours on travel behavior and transit users’ perceptions [ 11 ]. For example, Saxena, Hossein Rashidi [ 12 ] compared how travelers weigh trip attributes differently in the case of either canceled or delayed transit service when choosing a mode of transport. Other studies focused on understanding the impacts of long-term disruptions of the transport network [ 6 , 8 , 10 , 13 , 14 , 15 , 16 , 17 ].

In regard to review papers that focused on transport network disruptions, Shalaby, Li [ 18 ] conducted a systematic review to identify and analyze journal articles that focused on management strategies for short-term rail transit disruptions and modeling approaches. Zhang, Lo [ 19 ] provided a similar review of the academic literature concerning metro system disruption management and substitute bus service, whilst Zhu and Levinson [ 10 ] discussed theoretical and empirical studies that focus on traffic and behavioral impacts of transport network disruptions. To the best of the authors’ knowledge, none of the previous research efforts provided an in-depth systematic review of the contemporary academic literature concerning the impacts of long-term transit system disruptions and transitional periods on travel behavior, travelers’ perceptions and travel needs. To address this gap, this paper focuses on developing a comprehensive systematic review of the literature regarding the topic.

3 Methodology

A comprehensive systematic review of the academic literature was carried out. Systematic literature reviews are a powerful approach to identify and analyze all relevant research on a given topic within certain parameters. The research process followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for systematic reviews [ 20 ]. It was initiated by conducting a scan of a few relevant articles to establish the keyword search syntax that would then be used to conduct an article search on three notable research databases. These databases were the Transport Research International Documentation (TRID), the Web of Science Core Collection and Scopus. TRID is a comprehensive database that includes more than one million records of transport research [ 21 ]. Following this initial review, four different combinations of keyword search syntaxes were generated based, mainly, on the different categories of long-term transit system disruptions within the scope. More specifically, the four themes of the search queries were as follows: construction and maintenance, general disruptions and closures, labor disputes and strikes, and a more general search related to transport system upgrades or improvements (Table  1 ). It should be noted that the database search queries pertaining to the fourth keyword category were developed and carried out at a later stage to further expand the limited pool of relevant articles found.

Using EndNote, research records for all the documents, which included the abstracts, were organized and some duplicate records were removed. Afterwards, the entire list of records was uploaded to the Rayyan web application [ 22 ] where the remaining duplicates were removed and the record screening process was initialized. Rayyan provided a platform for a collaborative work environment for both authors to screen articles, add notes, label articles, and conduct keyword searches. The screening was mainly done by the first author, while checking the undecided articles was done by both authors. To establish clear guidelines to elucidate the process of determining which documents are relevant, inclusion and exclusion criteria were formulated and subsequently followed to filter out the out-of-scope documents (Table  2 ).

The criteria that guided the selection process included that all papers must be in English and must be full peer-reviewed journal articles published no earlier than in 2011. They must also be mainly concerned with the effects of long-term transit system disruptions. There is no clear distinction between short- and long-term disruptions in the literature. Some researchers generally classified short-term disruptions by lasting up to two or three days [ 23 ]. Therefore, and to increase the number of included studies in this literature review, we considered the threshold of 2 days or more for identifying long-term transit service disruption. Moreover, research articles investigating disruptions due to highway construction or road maintenance works or that study long-term disruptions of other transport modes, such as air travel and ferries, were beyond the scope of this review and, as a result, were excluded. Additionally, efforts that investigated the effects of natural disasters, epidemics, and pandemics such as the COVID-19 pandemic were removed from the analysis, as these types of events are not only impacting the transit system, but also impacting all transportation modes and people’s willingness to make trips to different destinations.

Based on the criteria presented, the number of records that had their titles and/or abstracts manually reviewed by the authors and were subsequently excluded was 6,588, while the number of records deemed preliminarily relevant and were then pursued for full text retrieval were 47 articles. The review of the articles was based on reviewing the papers’ titles first, if the paper title is not clear or suspected of inclusion, the abstract was then reviewed. Afterwards, a swift review of the full text was carried out for these 47 articles. As a result, 30 articles were excluded, and 17 were included (end of Phase 1). Phase 2, the final phase of this process, comprised scanning the reference lists of the 17 acquired articles for any new articles, while applying the same inclusion and exclusion criteria. This step led to the procurement of 5 additional articles that required a full-text review. Only 2 were deemed relevant and were included in the finalized list of articles for the systematic review (19 in total). This process is illustrated in Fig.  2 , which was adapted from Page, McKenzie [ 20 ]. Articles that made it to the finalized list were categorized based on the type of disruption that they each discuss. Subsequent to this categorization, a full review of the 19 articles was performed, and the relevant information regarding the different aspects of each paper, such as the issues addressed; the data used; the utilized research methods; and the key findings, was extracted and organized. This was followed by conducting a qualitative analysis of the papers by analyzing the information on individual, categorical, and general scales as well as synthesizing and comparing the findings and other significant features of the articles.

Flow diagram of the systematic review process conducted

In total, 19 articles were found to focus on long-term transit system disruptions and transitional periods. Even though this may seem like an inconsiderable number of articles for a systematic review, other systematic reviews in the field had similar numbers [ 24 , 25 , 26 ]. Of these 19, three focused generally on long-term disruptions. Seven papers discussed construction-related transit disruptions, and nine papers explored the effects of transit labor disputes and strikes. Appendices 1, 2, and 3 depict the results of this systematic review. In the appendices, studies that have modeled the impact of a mitigation strategy or controlled for it in the model, or  have critically discussed the effects of a mitigation strategy were highlighted.

4.1 General disruptions studies

As can be seen in Appendix 1, only three articles focused on general long-term transit service disruptions or included sections that focused on them. One paper used semi-structured interviews to understand the factors influencing the mode shift to car among transit users in the case of a transit service disruption. In this study, long-term disruptions referred to the hypothetical absence of transit for 10 years [ 27 ]. Pnevmatikou, Karlaftis [ 17 ] investigated the impact of a 5-month partial closure of a metro line in Athens, Greece. Lastly, Yap, Nijënstein [ 28 ] analyzed the impacts of four tram line disruptions in The Hague, the Netherlands. These analyzed disruptions lasted 5 and 20 days.

4.1.1 Methods and data

Nguyen-Phuoc, Currie [ 27 ] used a discourse analysis approach to analyze data collected from semi-structured interview responses of 30 transit users in Melbourne. Most of the participants were from an academic institution (i.e., Monash University). Interviews were coupled with brief questionnaires to collect participants’ socioeconomic information (age, income, occupation, car ownership and driving license) and current travel behavior (i.e., last transit trip). In contrast, Pnevmatikou, Karlaftis [ 17 ] adopted nested logit (NL) and multinomial logit (MNL) models to analyze revealed preference (RP) and stated preference (SP) data. The RP survey (1038 responses) examined the impact of a 5-month metro line closure on transport mode choice, which was conducted immediately after the line’s reopening. The SP survey of transit users was web-based and was collected to understand stated preferences towards travel patterns during hypothetical metro closures. In contrast to the previous two studies, Yap, Nijënstein [ 28 ] utilized smart card data obtained from an automated fare collection (AFC) system during disruptions to compare between predicted and realized transit ridership.

4.1.2 Studies key findings

Nguyen-Phuoc, Currie [ 27 ] found that in the long term, only context-specific factors (travel distance, travel time, travel cost, trip destination and flexibility of alternative mode) have an influence on transport mode shift. The postulated reasons were that participants did not perceive any alteration to the individual-specific factors in the future and that the authors focused on the unavailability of transit for an extremely long period (i.e., next ten years). The study indicated that the prolonged absence of transit services is expected to have an impact on land use and individuals in terms of changing their residential or workplace locations, or both. Participants did not consider trip cancellations during the long-term unavailability of the transit service.

Pnevmatikou, Karlaftis [ 17 ] showed that a metro user’s income was an important element in their decision-making process regarding whether to shift to buses or cars during metro service disruptions. Low-income metro users, regardless of car ownership, prefer using buses during metro disruptions. Additionally, during the disruptions, using a car for travel was negatively correlated with having a flexible work schedule. Yap, Nijënstein [ 28 ] indicated that in-vehicle time in the shuttle bus service (i.e., rail replacement buses) was perceived about 1.1 times more negatively compared to the in-vehicle time in the initial tram line, while waiting times for the shuttle bus service were perceived as approximately 1.3 times higher compared to the waiting times for the regular bus and tram services. The paper also indicated that if the prediction model does not account for vehicle capacity, integrating the positive effect of higher bus frequency would only overestimate the level of service provided by the shuttle buses during disruptions.

4.1.3 Section summary

Very few studies focused on long-term transit service disruptions or included sections that centered around long-term disruptions. One of them used a qualitative approach to develop a conceptual model of mode shift to car among transit users. The other two articles used specific case studies of partial closures of the metro and tram system in Athens and The Hague, respectively. There were no studies exploring system-wide (or a large portion of the system’s) long-term disruptions, nor were there studies that explored long-term disruptions within the North American context. All three studies focused primarily on current transit users’ travel behaviors. Nevertheless, other travelers may respond differently to additional costs imposed by increased traffic congestion. Additionally, since these studies explored only two cases of disruptions, future work is needed to include a wider array of disruptions because transit users’ responses will depend on: available travel options; duration, type, and degree of disruptions; and the used mitigation strategies’ effectiveness. The two quantitative studies investigated the impacts of providing shuttle buses and using an existing parallel transit service to mitigate the impacts of tram and metro closures, respectively. However, the effectiveness of other mitigation strategies is yet to be explored.

4.2 Construction studies

As seen in Appendix 2, seven studies explored the impacts of construction-related disruptions. Most of them focused on the impacts of heavy rail systems’ (e.g., metro and rail systems) construction and maintenance, while only two discussed light rail transit (LRT) systems [ 8 , 9 ]. Construction studies are related to the idea of transitional periods, in which people are expected to have improved transit service quality (or options) after these periods. Of the seven papers, 3 focused on the impacts of construction-related transit disruptions on bike-sharing systems usage. The four others investigated the impacts of construction on: travel behavior changes and travelers’ responses to enroute real-time information disseminated through variable message signs (VMS) [ 8 , 13 ], local air quality [ 29 ], and bus performance [ 14 ]. Additionally, only five articles critically discussed or analyzed the impacts of mitigation strategies.

4.2.1 Methods and data

Of the seven studies, five utilized statistical models to investigate construction-related transit disruptions’ effects on travel behavior and air quality. Bike-share system studies used ridership data from fixed docking stations [ 30 ] or from free-floating bike-sharing systems [ 9 ]. Based on bike-share data, these studies explored the impact of metro and LRT closures that lasted from 7 to 25 days in Washington, D.C., USA and Cologne, Germany. They used autoregressive Poisson log-level time series modeling [ 30 ], negative binomial regression [ 9 ] and linear regressions [ 31 ] to analyze ride-share data for periods before, during, and after disruptions, while controlling for a set of variables (weather conditions, season, day, time of day, etc.). One study [ 31 ] did not directly model changes in ridership due to disruptions, but rather used sensitivity analysis to explore the effects of implementing a new $2 single-trip fare (STF) on ridership, which was introduced concurrently with the SafeTrack program’s operations in Washington, D.C. Another study modeled bike-sharing usage from geographical and temporal perspectives [ 9 ].

On the other hand, other papers used participant survey data to understand changes in travel behavior using summary statistics. For example, Kattan, de Barros [ 8 ] used a revealed preference survey (430 responses) collected one year after the West LRT line’s construction in Calgary, Alberta, Canada, had started but before it ended (the construction project’s duration was ~ 3 years). Nevertheless, it did not model travel mode changes but focused on multinomial logit modeling to study travelers’ behavioral responses to VMS information. Zhu, Masud [ 13 ] used descriptive statistics to analyze panel survey data before (318 and 420 responses) and after (74 and 64 responses) two reductions and closures of service. Another study used fixed-effect modeling to understand the impacts of rail transit construction on the air quality index using air quality data from 28 cities in China [ 29 ]. Lastly, Shiqi, Zhengfeng [ 14 ] used fuzzy aggregation and summary statistics to evaluate the bus layout adjustment scheme from passenger and car driver perspectives and investigated passenger volumes at stops.

4.2.2 Studies key findings

Usage of bike-sharing systems generally increased during construction-related transit disruptions but at different levels. For example, Younes, Nasri [ 30 ] reported ridership increases on weekdays during disruption. Once the affected metro stations reopened, bike-share ridership returned to its pre-surge levels, suggesting a limited lasting effect of the studied disruptions. They also suggested the likelihood of travelers using bike-share as a first- and last-mile solution rather than as an alternative to transit. Similarly, Schimohr and Scheiner [ 9 ] reported a reversion to the original bike-share ridership levels once the disruption had ceased. On another note, Kaviti, Venigalla [ 31 ] indicated that implementing a new $2 single-trip fare increased the number of first-time bike-share riders by as much as 79% immediately after its introduction. The introduction of this new fare co-existed with metro service closures. Additionally, there was also a statistically significant increase in the daily ridership of registered members and casual users at docks near metro stations impacted by the metro service closures.

In regard to the other four studies, Kattan, de Barros [ 8 ] stated that the total demand for travel in areas affected by the construction did not decrease, neither were trip departure times rescheduled. Travel behavior changes were mainly route switching, followed by mode shifting, and then by destination changing. Zhu, Masud [ 13 ] indicated that transit users changed modes or destinations instead of departure time during the complete closure of metro stations. They also reported that ~ 20% of respondents did not return to using the metro even after the service’s full restoration. However, it is not known whether these mode changes are temporary or permanent. Additionally, they observed that wealthier riders are more likely to drive or switch to for-hire options (e.g., Uber and Lyft). On another note, Sun, Zhang [ 29 ] found that rail construction has a greater impact on improving air quality than urban road reconstruction, while Shiqi, Zhengfeng [ 14 ] suggested that factors attributed to transit service and traffic were degraded when bus routing schemes were implemented during disruptions.

4.2.3 Section summary

Few studies in the literature focus on long-term disruptions caused by transit construction or maintenance projects. Three of the seven studies focused exclusively on understanding the disruptions’ impacts on bike-share ridership rather than their effects on using active transportation modes and cycling behavior. Only two articles employed traveler surveys to gain a better picture of people’s travel behavior instead of their tendency to use one specific mode (bike-share) during such disruptions. Moreover, none modeled transport mode changes due to transit system construction projects, but they rather used descriptive statistics to provide information regarding, for example, route and mode changes, while indicating limited trip cancellations or changes in trip departure times.

Additionally, very few studies looked into long-term changes in travel behavior or home and work location decisions influenced by long-term disruptions as Nguyen-Phuoc, Currie [ 27 ] discussed. Most studies focused on immediate impacts and accounted for disruptions within limited time frames. Only five studies explored or modeled the impacts of mitigation strategies on travelers’ travel behaviors or perceptions (Appendix 2). Similarly, it was rare to find articles utilizing detailed mitigation strategy data (e.g., shuttle buses and travel information communications) and travelers’ data in combination with disruption data to explore the mitigation strategies’ effectiveness during transit construction projects. Furthermore, none of the studies were concerned with the relative impact of bus rapid transit (BRT) system construction projects; most of them focused on LRT and metro service construction.

4.3 Labor dispute and strike studies

Only nine papers focused on labor disputes and strikes (Appendix 3). Four of them discussed the impacts of transit operators’ strikes on air quality [ 32 , 33 , 34 , 35 ]. Three focused on transit service strikes’ effects on traffic conditions, while one article investigated the strikes’ impacts on the usage of bike-sharing systems. The remaining paper explored a strike’s effect on undergraduate students’ travel choices.

4.3.1 Methods and data

Of the nine articles, six utilized statistical models to investigate transit labor disputes’ effects on people’s travel behavior and on air quality. Regarding air quality studies, they used pollutant levels as proxies to investigate people’s shifting from transit to using private vehicles. Using air quality monitoring stations data, most of them used case studies that lasted from 3 days [ 32 ] to 51 days [ 33 , 34 ]. Additionally, two used a 2013 strike that occurred in Ottawa as their case study, and only one used a sample of more than one long-term strike for investigating their impacts on air quality [ 35 ]. The most commonly used data analysis methods included regression, difference-in-difference models [ 34 , 35 ], and summary statistics [ 33 ].

On the other hand, three studies explored transit strikes’ effects on traffic conditions using freeways and highways’ loop detector data [ 36 , 37 , 38 ]. These studies used different indicators to understand changes in traffic conditions such as changes in average delay, traffic flow, mean speed, and travel time. The used methodological approaches include summary statistics and developing regression and generalized linear models [ 36 , 37 ]. Only one study [ 39 ] used statistical modeling to isolate strikes’ impacts on bike-sharing system usage; it analyzed the impact of one strike that lasted 7 days in Philadelphia, Pennsylvania, USA, using interrupted time series models. Additionally, only one study [ 40 ] explored strikes’ impacts on transit users and non-users’ travel behavior using surveys and mobile phone app (called iEpi) data. Using four weeks of data, comprising two weeks during the strike and two weeks of normal operation after the strike ended, they developed descriptive statistics to understand changes in walking distance, trips frequency, and visited locations.

4.3.2 Studies key findings

Most of the air quality studies showed substantial increases in fine particulate matter (PM) concentrations during strikes, particularly in busy urban areas. Moreover, some studies indicated large increases in O 3 and CO concentrations. These impacts were mainly attributed to travel behavioral changes; transit users shifted to using private cars. In contrast, two articles reported reductions in NO concentrations during strikes. NO is a gas that is mainly produced by diesel engines, which can be found in public transit buses. Interestingly, one article suggested that PM and O 3 concentrations significantly decreased in the strike’s final 3 weeks. This was attributed to travel behavioral changes; travelers started using more environmentally friendly transport modes as they adapted to the transit service’s absence.

Regarding traffic studies, Anderson [ 37 ] reported an about 47% increase in highway delays during a 35-day strike in Los Angeles, California, USA. More delays were observed along freeways with parallel transit lines that are characterized by heavy ridership. Other researchers made the same spatial observation [ 38 ]. Furthermore, Spyropoulou [ 36 ], using a case study from Athens, Greece, of several strikes lasting between 1 and 5 days, reported similar results. Spyropoulou [ 36 ] stated that strikes increased congestions by increasing traffic flow (up to 30%), reducing mean speed (up to 27%) and increasing travel times (up to 25%).

Strikes also had significant impacts on using active transportation modes. Fuller, Luan [ 39 ] reported a 57% increase in bike-sharing system usage by members and non-members during the 7-day transit operators’ strike. However, bike-share usage quickly returned to previous trends directly after the strike. Additionally, some results suggest that non-members might have used bike-sharing for a slightly longer period. In contrast to previous studies that analyzed the usage of one mode during the strikes (i.e., car or bike-share system), Stanley, Bell [ 40 ] focused on the overall changes in the travel behavior of transit and non-transit users during a longer strike that lasted for more than 30 days. They indicated that transit users visited fewer places and walked more during the 30-day strike.

4.3.3 Section summary

Traffic studies showed that the impacts on the transport network were not equal; this is usually not captured by studies that used aggregate air quality data from fixed monitoring stations. Most of the studies examined changes in using one mode, namely cars or bike-sharing systems. However, only very few studies explored and modeled overall alterations in travel behavior. Moreover, most of the articles used passive data sources from traffic loop detectors, air quality stations, or a bike-sharing system at the aggregate level; this does not offer insights into individuals’ behavioral changes in terms of route choice, departure time, travel perception and overall experience. In fact, none of the studies relied on using social surveys to investigate the short- and long-term impacts of transit operators’ strikes on users. In other words, none of them explicitly focused on understanding changes in transit users’ perceptions and needs. Instead, studies tried to draw conclusions regarding transit users’ and non-transit users’ travel behavior.

Only one study utilized mobile-phone data to explore changes in travelers’ behaviors in more detail. This calls for more investigation into possibly using such tools in obtaining larger and more representative samples that can be combined with surveys to better understand different aspects of travelers’ decision-making behaviors during transit operators’ strikes. Furthermore, none of the reviewed studies explored the impacts of service strikes and information availability on travelers’ perceptions using data collected from social media platforms such as Twitter, for example. Table 3 shows an aggregated summary of the analyzed papers from the three categories (general causes, construction-related, and labor-related disruptions) and their different aspects including users’ perceptions and travel behaviors that were investigated.

4.4 Mitigation strategies

Several mitigation strategies were discussed in the reviewed literature. They generally fall under three broad categories: backup transport services, policy-based measures, and impact assessments (Table  4 ). In the table, articles are also sorted by the disruption type that they are associated with. Of the 19 papers chosen for this review, 10 articles discussed disruption mitigation strategies in some form.

Backup transport services are mitigative actions where some alternative form(s) of transport is provided during disruptions to regular transit services. They can be considered to be a form of policy-based measures; however, a distinction has been made between the two since not all of the policy-based measures discussed in the articles were backup transport services. Several articles discussed the level of backup transport services and their impact. For example, Kattan, de Barros [ 8 ] discussed the benefits of implementing a temporary BRT service, which followed an alignment similar to that of the LRT under construction, as a proactive mitigation measure that encouraged travelers to shift to using transit. Yap, Nijënstein [ 28 ] found that people overestimated the in-vehicle and waiting times associated with using bridging buses compared to their in-vehicle and waiting times using the initial tram service. On another note, Schimohr and Scheiner [ 9 ] indicated that travelers’ proximity to stations with substitute or redirected lines was associated with a decrease in the number of bike-sharing trips, suggesting that people used transit at these locations more than they used the bike-share system during service disruption. Nevertheless, most of the studies that discuss this point agree that bus bridging involves a higher level of inconvenience for users, thereby encouraging them to change modes or destinations.

The second category is policy-based measures. This strategy includes providing and improving communications and the dissemination of information to travelers through delivering consistent updates regarding the disrupted transit services, traffic conditions, available alternative modes of transport, etc. It could also include reduced fares, for using transit or a form of active transportation for example, to promote using sustainable transport modes during the disruption to alleviate the hike in traffic congestion. The reviewed articles discussed or analyzed several policy-related amendments or measures. They include introducing a single-trip fare option to encourage riders to use the bike-sharing system and using improved communications methods to disseminate information; those approaches were studied by Kaviti, Venigalla [ 31 ] and Kattan, de Barros [ 8 ], respectively. In addition, Anderson [ 37 ] reported that an additional transit service was contracted (i.e., the Red Line Special bus service) to duplicate part of a closed metro route; this could also be considered a backup transport service. Similarly, Moylan, Foti [ 38 ] indicated that during the Bay Area Rapid Transit (BART) service shutdown, a local bus agency (i.e., AC Transit) increased frequencies on Transbay bus service routes. However, the benefits of policies like contracting new services or increasing transit services offered by other agencies were not explicitly measured in previous efforts. Regarding the third category, only one paper [ 14 ] focused on evaluating a metro construction project’s disruptive effects on bus performance in the city of Ningbo, China.

5 Discussions and policy implications

The results of this study demonstrate that there is generally a lack of academic research concerning long-term transit service disruptions and transitional periods. Nevertheless, the majority of the identified academic papers are relatively recent and were published during the past five years. This may suggest that this key topic has been gaining more traction in recent years. This showcases this topic’s relevance and the possibility of having more efforts in this area soon. This is in alignment with the increase in worldwide governmental funding opportunities to develop new transit infrastructure to foster economic growth and face climate change. For example, Canada’s federal government revealed a new sizeable funding of $14.9 B for new public transit infrastructure in February 2020 [ 41 ]. Similar efforts dedicated to providing more funding for building and upgrading public transport can be found in Europe, the US and China [ 44 , 45 , 46 ]

According to the number of identified documents, there is a wide agreement and overlap in the reviewed literature regarding the negative impacts such disruptions and transitional periods have on travelers and also regarding the importance of using a range of mitigation strategies. The most common impacts are mode changes. Very few studies indicated other types of changes such as route changes, trip departure time changes, and destination changes. Some evidence, which is rather limited, shows that transit users did return to their previous travel behavior after the end of long-term service disruptions. Nevertheless, it is not clear if these changes are temporary or permanent. Other studies indicated that bike-share systems ridership increased during disruptions. However, these ridership levels returned to their pre-disruption levels after the reopening of the transit service, suggesting a limited lasting effect of long-term disruptions on people’s mode choice to continue using the bike-sharing systems. Providing new backup transit services and rerouting and enhancing parallel services were the most common mitigation approaches widely discussed in the literature to deal with long-term transit disruptions. Previous efforts showed good use of passive data sources from air quality monitoring stations, highway loop detectors, bike-share system counters, and automated fare collection systems to establish evidence of the negative effects of such periods.

Despite these efforts in the literature, travelers’ perceptions and needs during these periods are minimally addressed or analyzed. Additionally, it was rare to find studies that explicitly incorporated or controlled for the expected impacts of the transit projects after their completion. In other words, transitional periods may have more positive outcomes on transit users’ perceptions and travel behaviors after the project is finalized, due to enhanced service quality for instance, compared to other long-term disruptions. Such effects were underexplored in the literature.

The academic literature on long-term disruptions and transitional periods is currently quite divorced from the practice. For example, there is a dearth of studies that seek to derive lessons from past and current practices to help advance the practice of using effective mitigation strategies in different contexts and for different purposes. Additionally, a considerable number of the articles focused solely on understanding the impacts of long-term service disruptions on the usage of one transport mode, such as bike-sharing system usage, or one element, such as air quality or traffic conditions, rather than drawing a complete picture of people’s decision-making process and changes in their travel behaviors and needs. It was also rare to find studies that used a statistical model to better understand travelers’ behaviors during and/or following different types of long-term disruptions and transitional periods.

Most of the studies focused on measuring the short-term impacts of transit service disruptions. This may be related to the fact that most of the analyzed disruptions in the academic literature lasted for a few days or weeks. Nevertheless, articles exploring both short- and long-term impacts of longer transit service disruptions and transitional periods that last for a few months or even years were very limited. In fact, only two studies focused on exploring the impacts of longer disruptions that lasted more than a few months. Using surveys, one study regarding disruptions in Athens explored the immediate impact of a 5-month disruption on travel behaviors, while another study from Calgary explored the 1-year impact of an LRT system construction project, which lasted for about 3 years. Therefore, it is challenging, based on the limited research available, to understand the changes in travel behavior during these prolonged periods and to understand whether these long-term disruptions have an extended or permanent impact on travelers’ behaviors. Potential changes that may not be considered in shorter disruptions include relocation and/or reductions in travel demand because of moving closer to work or school, changing jobs, joining a ride-sharing program, and increasing telecommuting. Some of the key policy recommendations of this research are listed below.

With the need for academic studies that focus on the short- and long-term impacts of different long-term disruptions and transitional periods, cities and transit agencies are encouraged to work with the academic community to test different sets of mitigation strategies in different contexts, scenarios, and at different scales. These studies should also include information about changes in travelers’ behaviors, perceptions, and well-being in order to evaluate the used mitigation strategies and their relative impacts, which would inform future policy making.

With the emergence of more academic studies, as well as non-academic reports, in this area, lessons from the literature and practice should be organized and used in more systematic ways to assist in developing a policy guide to help in managing these disruptions. This will aid in guiding future practices that should aim to maintain higher levels of the transit services’ attractiveness during such periods for both transit and non-transit users. The prospect of providing adequate active transport alternatives that would encourage people to shift to using active transportation modes should also be explored. This could potentially reduce the stress on the public transportation and road networks.

Using agreements with private bus operators, ride-hailing services, bike shops, advocacy groups, and bike-sharing and scooter-sharing companies, cities can help reduce the impact of such periods on travelers. As seen in the literature, offering bike-sharing services and making them cheaper or more accessible by offering more payment options during long-term transit service disruptions can work as a mitigation strategy. This could be coupled with looking beyond the physical availability of alternative modes by testing different pricing scenarios to provide transport alternative(s).

Research suggests that using greener transport options may be adopted more widely by travelers if adequate policies were in place during such disruptions. This would capitalize on the increased flexibility of travelers to try out new transport modes during such periods. This might help in increasing cities’ shares of active transportation if such mode changes could be sustained after the disruption and adopted permanently by travelers. Nevertheless, currently, there is limited evidence that this is the case.

People will not benefit or suffer increases in their monetary and non-monetary costs equally because of any long-term transit system disruptions or transitional periods. Therefore, transit agencies should assess the equity impacts of such extended time periods on different groups of travelers. This will be context-specific and will help in articulating more sensitive policies that match different groups of users’ needs.

Finally, it was reported in the literature that the provision of alternative public transport options with a high transit service level coupled with the efficient dissemination of pre-trip and enroute, real-time travel information (e.g., updates on traffic and on areas affected by the disruption) resulted in an increase in transit use during the disruption. Moreover, evidence of the importance of using social media, graphics, and short videos in communicating information during the COVID-19 pandemic was discussed in the literature [ 47 ]. Learning from these lessons, more understanding of the importance of efficient and timely dissemination of information plans using social media or other platforms is essential. This is to help cities in informing people about expected impacts and options, which can help in alleviating stress on transit segments.

6 Conclusions

This study aimed to explore the current state of knowledge concerning transit systems’ transitional periods and long-term disruptions and to understand the actively used disruption mitigation strategies and technologies that are implemented to address or alleviate any of their undesirable impacts on travelers. To achieve these goals, a comprehensive systematic review of the academic literature was conducted. In total, 19 peer-reviewed journal articles were identified and analyzed. This systematic review helps identify the major knowledge gaps in the literature. The results of this study demonstrate that there is generally a lack of academic research works concerning long-term transit service disruptions and transitional periods. In fact, travelers’ perceptions, travel behaviors and changing needs during these disruptive periods were minimally addressed or analyzed. Key conclusions and recommendations are discussed below.

Given the range of different types of long-term transit system disruptions (e.g., construction, labor disputes and service failures); various disruption time frames (from a few days to several years); varying spatial coverage (from one line to system level); and different disrupted modes (e.g., bus, metro and tram), much more work can be done to explore the effects of such disruptions on people’s travel behavior and perceptions.

The possible impact of long-term disruptions on travelers in terms of changing modes, routes, trip departure times, frequency of trips, destinations, and work and home locations in addition to increasing telecommuting and trip sharing are widely recognized in the literature. However, studies rarely explored explicitly the factors affecting changes in travel behavior like shifting to different routes or changing the frequency of trips or the factors influencing relocation for transit and non-transit users using statistical models. This can be an important area for future work.

The relative importance and impact of disruption mitigation measures, while understanding how these measures could work together, within the context of long-term disruptions are rarely investigated in the literature. In fact, the current academic literature provides transit agencies with very limited information to assist them. Such knowledge can inform the processes of planning for long-term disruptions to implement more efficient and effective strategies.

Most of the studies were quantitative in nature and provided some relevant findings; however, qualitative studies can provide in-depth insights into the intersection between how, why, who, and what questions that are related to different types of disruptions. For example, it can help in understanding the importance of using different mitigation strategies for different groups of the population and their relation to different types of disruptions. Therefore, future research can focus on using qualitative approaches to elicit information not only from transit and non-transit users, but also from transit agencies and operators to understand their perspectives.

The reviewed literature generally used data from two main sources: from traveler surveys and from passive data sources that are obtained from air quality monitoring stations, bike-share systems, and highway loop detectors. Therefore, using emerging data sources such as cellular phone data and mobile app data can be explored for future studies to give a better understanding of the different long-term disruptions’ impacts. Social media data, farebox system data, and web surveys can be also incorporated in these studies.

Several studies used summary statistics, difference-in-difference approaches, or a dummy variable to isolate the impacts of long-term disruptions on different aspects (e.g., air quality, traffic conditions, and bike-share usage). However, these studies ignore that a long-term disruption entails an extended period of time, which can see different movement patterns within this period as indicated by Chandler and Shymko [ 34 ]. They stated that relying only on short-term results to draw conclusions regarding long-term impacts of long-term disruptions can lead to an overestimation of the negative effects. Therefore, future research could look into different patterns within such time frames.

Similarly, temporal changes in travel behavior after long-term disruptions or transitional periods end are rarely explored in the literature, particularly for longer disruptions that last for more than a few weeks. Some authors indicated that transit ridership can take several weeks to reach pre-disruption levels [ 37 ]. Therefore, exploring changes occurring over time to travelers and, more specifically, transit users’ travel behavior could be a viable future research endeavor.

Previous studies explored the impacts of long-term disruptions and transitional periods on bike-share usage; however, the academic literature is lacking in studies that investigate their impacts on using other active transportation modes, such as walking and cycling. Since these trips, particularly walking trips, are usually underreported in travel surveys, using sensors data from mobile phone apps can be beneficial to understand changes before, during, and after long-term disruptions for different groups of travelers.

It was found that very few articles explored changes in travelers’ perceptions, satisfaction, and needs due to transitional periods in comparison with long-term transit system disruptions triggered by other causes. Transitional periods, which usually lead to different outcomes in terms of improved service quality after ending compared to other long-term disruption periods, were not explicitly explored in the literature. Transitional periods’ ultimate positive outcomes on users’ perceptions and travel behaviors could be a viable focal point for future research efforts.

Incorporating social issues, such as equity concerns, and seeking to derive lessons to help understand the equity impacts of long-term disruptions and transitional periods on different groups of populations are yet to be accomplished. These groups can include Indigenous populations, visible minorities, and people with systemic barriers to using other transportation modes. Additionally, there is a lack of research to both understand and address the sociopolitical, institutional and community capacity dimensions, which is an important aspect during such periods.

Finally, this study aimed to derive lessons from the current academic literature on the effects of transit systems’ long-term disruptions and transitional periods. Exploration of this rather diverse research area will not only inform professionals but will also highlight important gaps in the current literature for researchers. Future research can expand the presented efforts and focus on reviewing transit agency reports and studies and conducting surveys and interviews with transit planners to record their experience and to better understand their perspective of the effects of transit systems’ long-term disruptions and transitional periods. This is to help cities and transit agencies to better anticipate and manage “change”. This will, in turn, help to facilitate and secure the development of their public transport networks while planning and being better prepared for long-term transit system disruptions, thereby aiding them in achieving their overarching sustainability goals.

Data availability

No datasets were generated or analysed during the current study.

CUTA, Transit vision 2040 . 2015.

OECD/ITF, ITF transport outlook 2017 . 2017.

Miller E. et al., Canadian transit ridership trends study: Final report. University of Toronto Transportation Research Institute. 2018 p. 140.

Aston L, et al. Exploring built environment impacts on transit use—an updated meta-analysis. Transp Rev. 2021;41(1):73–96.

Article   Google Scholar  

Ye L, Mokhtarian P, Circella G. Commuter impacts and behavior changes during a temporary freeway closure: The ‘Fix I-5’ project in Sacramento. Calif Trans Plan Technol. 2012;35(3):341–71.

Zhu S, Levinson DM. A review of research on planned and unplanned disruptions to transportation networks, in transportation research board 89th annual meeting. Washington DC: United States; 2010.

Google Scholar  

Danczyk A, et al. Unexpected versus expected network disruption: effects on travel behavior. Transp Policy. 2017;57:68–78.

Kattan L, de Barros A, Saleemi H. Travel behavior changes and responses to advanced traveler information in prolonged and large-scale network disruptions: a case study of west LRT line construction in the City of Calgary. Transport Res F: Traffic Psychol Behav. 2013;21:90–102.

Schimohr K, Scheiner J. Spatial and temporal analysis of bike-sharing use in cologne taking into account a public transit disruption. J Transp Geogr. 2021;92: 103017.

Zhu S, Levinson D. Disruptions to transportation networks: a review. In: Levinson D, Liu H, Bell M, editors. Network reliability in practice. New York: Springer, New York; 2012. p. 5–20.

Chapter   Google Scholar  

Currie G, Muir C. Understanding passenger perceptions and behaviors during unplanned rail disruptions. Trans Res Proc. 2017;25:4392–402.

Saxena N, Hossein Rashidi T, Auld J. Studying the tastes effecting mode choice behavior of travelers under transit service disruptions. Travel Behavi Soc. 2019;17:86–95.

Zhu S, et al. Travel behavior reactions to transit service disruptions: study of metro safe track projects in Washington, D.C. Trans Res Record. 2017;2649(1):79–88.

Shiqi H, et al. Performance evaluation of bus routing scheme during subway construction using fuzzy aggregation. Open Civil Eng J. 2016;10:826–35.

Giuliano G, Golob J. Impacts of the Northridge earthquake on transit and highway use. J Transp Stat. 1998;1(2):1–20.

van Exel NJA, Rietveld P. When strike comes to town…anticipated and actual behavioural reactions to a one-day, pre-announced, complete rail strike in the Netherlands. Trans Res Part A Policy Prac. 2009;43(5):526–35.

Pnevmatikou A, Karlaftis M, Kepaptsoglou K. Metro service disruptions: how do people choose to travel? Transportation. 2015;42(6):933–49.

Shalaby A, Li L, Diab E. Chapter 14: rail transit disruption management: a comprehensive review of strategies and approaches. In: Currie G, editor. Handbook of Public Transport Research (HOPTR). Cheltenham, United Kingdom: Edward Elgar Publishing; 2021. p. 280–313.

Zhang S, et al. Metro system disruption management and substitute bus service: a systematic review and future directions. Transp Rev. 2021;41(2):230–51.

Page MJ, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372: n71.

TRID. Home - Transport Research International Documentation - TRID. 2021 https://trid.trb.org/ . Accessed on 20 July 2021

Ouzzani M, et al. Rayyan—a web and mobile app for systematic reviews. Syst Rev. 2016;5(1):210.

Arslan Asim M, et al. Transit users’ mode choice behavior during light rail transit short-term planned service disruption. Transp Res Rec. 2021;2675(10):711–22.

Diab EI, Badami MG, El-Geneidy AM. Bus transit service reliability and improvement strategies: integrating the perspectives of passengers and transit agencies in North America. Transp Rev. 2015;35(3):292–328.

Ravensbergen L, et al. Accessibility by public transport for older adults: a systematic review. J Transp Geogr. 2022;103: 103408.

Ravensbergen L, et al. Associations between light rail transit and physical activity: a systematic review. Transp Rev. 2023;43(2):234–63.

Nguyen-Phuoc D, et al. How do public transport users adjust their travel behaviour if public transport ceases? a qualitative study. Transport Res F: Traffic Psychol Behav. 2018;54:1–14.

Yap M, Nijënstein S, van Oort N. Improving predictions of public transport usage during disturbances based on smart card data. Transp Policy. 2018;61:84–95.

Sun C, et al. The improvement and substitution effect of transportation infrastructure on air quality: an empirical evidence from China’s rail transit construction. Energy Policy. 2019;129:949–57.

Article   CAS   Google Scholar  

Younes H, et al. How transit service closures influence bikesharing demand; lessons learned from SafeTrack project in Washington, D.C. metropolitan area. J Trans Geogr. 2019;76:83–92.

Kaviti S, et al. Impact of pricing and transit disruptions on bikeshare ridership and revenue. Transportation. 2020;47(2):641–62.

Pereira B, et al. Biomonitoring air quality during and after a public transportation strike in the center of Uberlândia, Minas Gerais, Brazil by Tradescantia micronucleus bioassay. Environ Sci Pollut Res. 2014;21(5):3680–5.

Ding L, et al. Characterization of chemical composition and concentration of fine particulate matter during a transit strike in Ottawa. Can Atmos Environ. 2014;89:433–42.

Chandler V, Shymko N. Environmental impact of public transit: evidence from a long strike in Ottawa. Can Public Policy—Analyse de Politiques. 2020;46(1):59–72.

Rivers N, Saberian S, Schaufele B. Public transit and air pollution: evidence from Canadian transit strikes. Can J Econ. 2020;53(2):496–525.

Spyropoulou I. Impact of public transport strikes on the road network: the case of Athens. Trans Res Part A:Policy Pract. 2020;132:651–65.

Anderson ML. Subways, strikes, and slowdowns: the impacts of public transit on traffic congestion. Am Econ Rev. 2014;104(9):2763–96.

Moylan E, Foti F, Skabardonis A. Observed and simulated traffic impacts from the 2013 bay area rapid transit strike. Transp Plan Technol. 2016;39(2):162–79.

Fuller D, et al. Impact of a public transit strike on public bicycle share use: an interrupted time series natural experiment study. J Trans Health. 2019;13:137–42.

Stanley K, et al. Opportunistic natural experiments using digital telemetry: a transit disruption case study. Int J Geogr Inf Sci. 2016;30(9):1853–72.

Government of Canada. Largest public transit investment in GTA history will create jobs and kickstart the economy. 2021 https://www.canada.ca/en/office-infrastructure/news/2021/05/largest-public-transit-investment-in-gta-history-will-create-jobs-and-kickstart-the-economy.html . Accessed on 20 July 2021

Infrastructure Canada, Permanent, integrated, and locally responsive: New foundations for public transit funding in Canada. 2023, Infrastructure Canada: Infrastructure Canada.

Infrastructure Canada. Share your views: Public engagement on permanent public transit funding in Canada . 2022 https://www.infrastructure.gc.ca/transit-transport/consultation-eng.html . Accessed on 15 August 2022

EMBARQ Network. China transportation briefing: Filling the finance gap . Smartcitiesdive 2012 https://www.smartcitiesdive.com/ex/sustainablecitiescollective/china-transportation-briefing-filling-finance-gap/41011/ . Accessed on 2 June 2024

European Commission. EU invests €6.2 billion in sustainable, safe and efficient transport infrastructure. 2023 https://ec.europa.eu/commission/presscorner/detail/en/ip_23_3436 . Accessed on 2 June 2024

Woodhouse, S. Biden Offers $9.8 Billion to Bolster Public Transit Agencies . 2024 https://www.bloomberg.com/news/articles/2024-02-29/biden-offers-9-8-billion-to-bolster-public-transit-agencies?embedded-checkout=true . Accessed on 2 June 2024

Diaz F, et al. Canadian transit agencies response to COVID-19: understanding strategies, information accessibility and the use of social media. Trans Res Int Pers. 2021;12: 100465.

Download references

We would like to thank the Social Sciences and Humanities Research Council (SSHRC) of Canada and Infrastructure Canada (INFC) for partially funding this research.

Author information

Authors and affiliations.

Department of Geography & Planning, University of Saskatchewan, 117 Science Place, Saskatoon, SK, S7N 5C8, Canada

Mohamed G. Noureldin & Ehab Diab

You can also search for this author in PubMed   Google Scholar

Contributions

The authors confirm contribution to the paper as follows: study conception and design: Noureldin & Diab; data collection: Noureldin; analysis and interpretation of results: Noureldin & Diab; draft manuscript preparation: Noureldin & Diab. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Ehab Diab .

Ethics declarations

Competing interest.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

1.1 General disruptions studies

• Rows 2 and 3 include a study that has modeled a mitigation strategy’s impact. Automated fare collection (AFC). Stated preference (SP). Revealed preference (RP). Multinomial Logit Model (MNL). Nested logit (NL). “Y” refers to the model’s dependent variable(s). “X” refers to the model’s independent variables

2.1 Construction studies

• Rows 1, 3, and 7 include a study that has modeled the impact of a mitigation strategy. Rows 4 and 6 include a study that has discussed or investigated the impact of a mitigation strategy using summary statistics. “Y” refers to the model’s dependent variable(s). “X” refers to the model’s independent variables. Stated preference (SP). Revealed preference (RP). Sulfur dioxide (SO 2 ). Nitrogen dioxide (NO 2 ). Fine particulate matter smaller than or equal to 10 µm in diameter (PM 10 ). Fine particulate matter smaller than or equal to 2.5 µm in diameter (PM 2.5 ). Gross domestic product (GDP). Analysis of variance (ANOVA). Variable message signs (VMS). Light rail transit (LRT)

3.1 Labor dispute and strike studies

• Row 9 includes a study that has modeled the impact of a mitigation strategy. Rows 5 and 6 include a study that has discussed or investigated the impact of a mitigation strategy using summary statistics. “Y” refers to the model’s dependent variable(s). “X” refers to the model’s independent variables. Fine particulate matter smaller than or equal to 10 μm in diameter (PM 10 ). Fine particulate matter smaller than or equal to 2.5 μm in diameter (PM 2.5 ). Sulphur dioxide (SO 2 ). Ozone (O 3 ). Nitrogen oxide (NO or NO X ). Carbon monoxide (CO). Condition probability function (CPF). Bay Area Rapid Transit (BART). Los Angeles County Metropolitan Transportation Authority (MTA)

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Noureldin, M.G., Diab, E. Impacts of long-term transit system disruptions and transitional periods on travelers: a systematic review. Discov Cities 1 , 15 (2024). https://doi.org/10.1007/s44327-024-00015-5

Download citation

Received : 05 March 2024

Accepted : 14 August 2024

Published : 27 August 2024

DOI : https://doi.org/10.1007/s44327-024-00015-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Long-term disruptions
• Transitional periods
• Construction
• Travel behavior
• Public transit
• Find a journal
• Publish with us
• Track your research