BARRIER FACTORS AFFECTING DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEM PROJECTS
Abstract
This paper identifies potential barrier factors affecting effectiveness and development (ED) of ITS projects as well as criteria for measuring ED of ITS projects in Ho Chi Minh City, Vietnam. The study discovers the barrier constructs, and analyzes data using the Partial Least Squares Structural Equation Modeling method (PLS-SEM). The results provides a general and comprehensive overview of the main issues of ITS, and identifies 28 barrier factors with five main constructs affecting ED of ITS projects, namely the lack of undivided attention from the government (AG), financial constraints for ITS (FC), inadequate transport infrastructure (ITI), the over-development of urbanization (ODU), and the readiness and integration for ITS (RI). This paper fill the knowledge gap by discovering the causal relationships between barrier constructs and ED of ITS projects in Vietnam. Also it proposes several solutions for these issues, which are also a useful measurement tool for government agencies, planners, and traffic system designers to help them self-assess and make action plans now or in the near future.
References
Alam, M., Ferreira, J., & Fonseca, J. (2016). Introduction to intelligent transportation systems. In Intelligent transportation systems (pp. 1-17). Springer, Cham. doi:https://doi.org/10.1007/978-3-319-28183-4_1.
Barclay, D., Thompson, R., & Higgins, C. (1995). The Partial Least Squares Approach To Causal Modeling: Personal Computer Adoption And Use As Illustration. Technology Studies, 2, 285–309.
Booysen, M. J., Andersen, S. J., & Zeeman, A. S. (2013, October). Informal public transport in Sub-Saharan Africa as a vessel for novel intelligent transport systems. In 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013) (pp. 767-772). IEEE. doi:https://doi.org/10.1109/ITSC.2013.6728324.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates.
Dapice, D., Gomez-Ibanez, J. A., & Thanh, N. X. (2010). Ho Chi Minh City: Challenges for Growth. Retrieved from United Nations Development Programme: http://www.undp.org/content/dam/vietnam/docs/Publications/26503_HCM_Challenges_of_growth-VN.pdf (07.05.2021).
Dassani, N., Nirwan, D., & Hariharan, G. (2015). Dubai - A New Paradigm For Smart Cities. Retrieved from KPMG: https://assets.kpmg/content/dam/kpmg/pdf/2016/04/Dubai-a-new-paradigm-for-smart-cities-uae.pdf (12.09.021).
Dubow, J. (2014). Big Data And Urban Mobility. Retrieved from The World Bank: https://www.worldbank.org/content/dam/Worldbank/Feature%20Story/mena/Egypt/Egypt-Doc/Big-Data-and-Urban-Mobility-v2.pdf (12.05.2021).
El Husseiny, H. M., El Meligy, B., & Hassan, M. (2017). The opportunities and challenges of applying intelligent transport systems (ITSS) on road transport in egypt: a case study on Cairo/Alexandria desert road. The Business & Management Review, 8(5), 100-110.
Far, B., Chavoshy, A., rad, A. L., & Mozaffari, G. (2013). Challenges Of Implementation Of Intelligent Transportation Systems In Developing Countries: Case Study – Tehran. WIT Press, 2(VIII), 977-987. doi:http://doi.org/10.2495/SC130832.
Finck, M., Lamping, M., Moscon, V., & Richter, H. (2020). Smart Urban Mobility as a Regulatory Challenge. In Smart Urban Mobility (pp. 1-17). Springer, Berlin, Heidelberg. doi:https://doi.org/10.1007/978-3-662-61920-9_1.
Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382-388. doi:10.1177/002224378101800313.
Foster, J. (2021). ITS World Congress Preview. Retrieved from (10.11.2021).
Geisser, S. (1974). A Predictive Approach to the Random Effect Model. Biometrika, 61(1), 101-107. doi:10.2307/2334290.
Grant-Muller, S., & Usher, M. (2014). Intelligent Transport Systems: The propensity for environmental and economic benefits. Technological Forecasting and Social Change, 82, 149-166. doi:10.1016/j.techfore.2013.06.010.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. doi:10.1108/EBR-11-2018-0203.
Hair, J. J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis.
Hair, J. J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM): SAGE.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2012). Using partial least squares path modeling in advertising research: basic concepts and recent issues. In Handbook of research on international advertising: Edward Elgar Publishing.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. doi:10.1007/s11747-014-0403-8.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing. Emerald Group Publishing Limited, 20, 277-319. doi:https://doi.org/10.1108/S1474-7979(2009)0000020014.
Hidalgo, D., & Huizenga, C. (2013). Implementation of sustainable urban transport in Latin America. Research in transportation economics, 40(1), 66-77. doi:https://doi.org/10.1016/j.retrec.2012.06.034.
Hsu, I. Y. Y., Wódczak, M., White, R. G., Zhang, T., & Hsing, T. R. (2010). Challenges, approaches, and solutions in intelligent transportation systems. In 2010 second international conference on ubiquitous and future networks (ICUFN) (pp. 366-371). IEEE. doi:https://doi.org/10.1109/ICUFN.2010.5547180.
ISO. (2019). ISO 37122:2019 Sustainable cities and communities - Indicators for smart cities. In. International Organization for Standardization.
ISO. (2020). ISO/TC 204 Intelligent Transport Systems. In: International Organization for Standardization.
John, S. K., Sivaraj, D., & Mugelan, R. K. (2019). Implementation Challenges and Opportunities of Smart City and Intelligent Transport Systems in India. In Internet of Things and Big Data Analytics for Smart Generation (pp. 213-235). Springer, Cham. doi:https://doi.org/10.1007/978-3-030-04203-5_10.
Karim, Z., & Fouad, J. (2018a). An analysis of public bus transport performance and its determinants factors: The case of major Morocco's cities. In 2018 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA) (pp. 44-50). IEEE.
Karim, Z., & Fouad, J. (2018b). Measuring urban public transport performance on route level: A literature review. In MATEC Web of Conferences (Vol. 200, p. 00021). EDP Sciences.
Khekare, G. S., & Sakhare, A. V. (2013). A smart city framework for intelligent traffic system using VANET. In 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s) (pp. 302-305). IEEE. doi:https://doi.org/10.1109/iMac4s.2013.6526427.
Khorasani, G., Tatari, A., Yadollahi, A., & Rahimi, M. (2013). Evaluation of Intelligent Transport System in Road Safety. IJCEBS, 1(1), 110-118. doi:http://doi.org/10.12691/jfe-4-5-1.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1-26.
Komninos, N. (2006). The architecture of intelligent clities: Integrating human, collective and artificial intelligence to enhance knowledge and innovation. In 2006 2nd IET International Conference on Intelligent Environments-IE 06 (Vol. 1, pp. 13-20). IET.
Latan, H., & Noonan, R. (2017). Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. Springer.
Lazaroiu, G. C., & Roscia, M. (2012). Definition Methodology For The Smart Cities Model. Energy, 47(1), 326-332. doi:http://doi.org/10.1016/j.energy.2012.09.028.
L Lin, Y., Wang, P., & Ma, M. (2017). Intelligent transportation system (ITS): Concept, challenge and opportunity. In 2017 ieee 3rd international conference on big data security on cloud (bigdatasecurity), ieee international conference on high performance and smart computing (hpsc), and ieee international conference on intelligent data and security (ids) (pp. 167-172). IEEE.
Mangiaracina, R., Perego, A., Salvadori, G., & Tumino, A. (2016). A Comprehensive View Of Intelligent Transport Systems For Urban Smart Mobility. International Journal of Logistics Research and Applications, 20(1), 39-52. doi:https://doi.org/10.1080/13675567.2016.1241220.
Mathew, E. (2019, October). Intelligent Transport Systems and Its Challenges. In International Conference on Advanced Intelligent Systems and Informatics (pp. 663-672). Springer, Cham. doi:https://doi.org/10.1007/978-3-030-31129-2_61.
Metz, B., Davidson, O., Bosch, P., Dave, R., & Meyer, L. (2007). Climate Change 2007: Mitigation of Climate Change.
Peterson, R. A., & Kim, Y. (2013). On the Relationship Between Coefficient Alpha and Composite Reliability. Journal of Applied Psychology, 98(1), 194–198. doi:http://www.doi.org/10.1037/a0030767.
Prabhu, S. B., Balakumar, N., & Antony, A. J. (2017). A research on smart transportation using sensors and embedded systems. International Journal of Innovative Research in Computer Science & Technology (IJIRCST). doi:https://doi.org/10.21276/ijircst.2017.5.1.5.
Qin, H., & Zhang, W. (2011). Charging scheduling with minimal waiting in a network of electric vehicles and charging stations. In Proceedings of the Eighth ACM international workshop on Vehicular inter-networking (pp. 51-60).
Rigdon, E. E. (2012). Rethinking partial least squares path modeling: In praise of simple methods. Long range planning, 45(5-6), 341-358. doi:https://doi.org/10.1016/j.lrp.2012.09.010.
Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3 (Version 3.3.3): Bönningstedt: SmartPLS. Retrieved from https://www.smartpls.com/ (05.05.2021).
Roselló, X., Langeland, A., & Viti, F. (2016). Public Transport in the Era of ITS: The Role of Public Transport in Sustainable Cities and Regions. In G. Gentile & K. Noekel (Eds.), Modelling Public Transport Passenger Flows in the Era of Intelligent Transport Systems: COST Action TU1004 (TransITS) (pp. 3-27). Cham: Springer International Publishing.
Russo, F., Rindone, C., & Panuccio, P. (2014). The Process Of Smart City Definition At An EU Level. WIT Press, 2. doi:http://doi.org/10.2495/SC140832.
Sampson, E. (2019). Smart Mobility, Empowering Cities. Retrieved from ITS World Congress Singapore: https://erticonetwork.com/wp-content/uploads/2020/03/ITSWC-2019-Post-Event-Report-v4-final.pdf (16.05.2021).
Sarstedt M., Ringle C.M., Hair J.F. (2021) Partial Least Squares Structural Equation Modeling. In: Homburg C., Klarmann M., Vomberg A.E. (eds) Handbook of Market Research. Springer, Cham. https://doi.org/10.1007/978-3-319-05542-8_15-2.
Schlingensiepen, J., Nemtanu, F., Mehmood, R., & McCluskey, L. (2016). Autonomic transport management systems—enabler for smart cities, personalized medicine, participation and industry grid/industry 4.0. In Intelligent transportation systems–problems and perspectives (pp. 3-35). Springer, Cham. doi:https://doi.org/10.1007/978-3-319-19150-8_1.
Sen, R., & Raman, B. (2012). Intelligent transport systems for Indian cities. In 6th USENIX/ACM Workshop on Networked Systems for Developing Regions ({NSDR} 12).
Stone, M. (1974). Cross-Validatory Choice and Assessment of Statistical Predictions. Journal of the Royal Statistical Society. Series B (Methodological), 36(2), 111-147.
Sun, J. (2011). Development and Strategies for the Intelligent Transport System in China. In ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation (pp. 1263-1267). doi:https://doi.org/10.1061/41177(415)161.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159-205. doi:https://doi.org/10.1016/j.csda.2004.03.005.
Tuominen, A., & Ahlqvist, T. (2010). Is the transport system becoming ubiquitous? Socio-technical roadmapping as a tool for integrating the development of transport policies and intelligent transport systems and services in Finland. Technological forecasting and social change, 77(1), 120-134. doi:https://doi.org/10.1016/j.techfore.2009.06.001.
Tyrinopoulos, Y., & Antoniou, C. (2013). Factors affecting modal choice in urban mobility. European Transport Research Review, 5(1), 27-39. doi:https://doi.org/10.1007/s12544-012-0088-3.
United-Nations. (2018). World Urbanization Prospects The 2018 Revision Retrieved from New York: https://population.un.org/wup/Publications/Files/WUP2018-Report.pdf (21.04.2021).
Zeng, N., Yan Liu, P. G., Hertogh, M., & König, M. (2021). Do Right PLS And Do PLS Right: A Critical Review Of The Application Of PLS-SEM In Construction Management Research. Frontiers of Engineering Management, 356-369. doi:https://doi.org/10.1007/s42524-021-0153-5.