Article Sidebar

Submitted
January 25, 2025
Accepted
April 23, 2025
Published
August 11, 2025
Download
Full text PDF
Statistic
Read Counter : 103 Download : 116

Downloads

Download data is not yet available.

Main Article Content

Abstract

This study addresses the critical gap in understanding High-Speed Rail (HSR) marketing strategies in emerging Southeast Asian markets, such as Indonesia, where unique cultural, economic, and infrastruc­tural factors require tailored approaches. Employing bibliometric analysis, the present study delves deeper into the evolution of HSR marketing from 2014 to 2023, analyzing 138 Scopus-indexed articles through R Studio (bibliometrix) and VOSviewer. The study identifies key trends, including the emphasis on pricing strategies, consumer behavior, and sustainability. An increase in publications, especially from emerging markets, indicates a growing interest in the marketing dynamics of HSR. Co-authorship networks and citation analysis high­light prominent authors and institutions, while keyword clustering reveals a shift toward customer satisfaction and environmental concerns. A significant gap in research emerges pertinent to HSR marketing strategies in Southeast Asia, pointing toward the need for region-specific approaches. The findings reveal a research gap in emerging markets like Indonesia, where themes such as “willingness to pay” and “tourism development” remain underexplored. As indicated by the low keyword density and thematic map results, future studies should focus more on consumer behavior and localized marketing strategies to support HSR adoption in diverse socio-economic contexts.

Keywords

High-speed rail (HSR) marketing Bibliometric analysis Emerging southeast asian markets Consumer behavior Tailored marketing strategies

Article Details

License

Copyright (c) 2025 Cep Abdul Baasith Wahpiyudin, Ujang Sumarwan, Megawati Simanjuntak, Irvan Nani

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
How to Cite
Wahpiyudin, C. A. B., Sumarwan, U., Simanjuntak, M., & Nani, I. (2025). Unpacking the tracks: Diving into high-speed rail marketing research trends (2014–2024) and shaping the future of the field. Asian Management and Business Review, 5(2), 328–348. https://doi.org/10.20885/AMBR.vol5.iss2.art6
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Albalate, D., Bel, G., & Fageda, X. (2015). Competition and cooperation between high-speed rail and air transportation services in Europe. Journal of Transport Geography, 42, 166–174. https://doi.org/10.1016/j.jtrangeo.2014.07.003
  2. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
  3. Arumdani, I., Budihardjo, M., & Syafrudin, S. (2023). Landfill liner composite materials: Bibliometric and content analysis. Polish Journal of Environmental Studies, 32(3), 2473–2483. https://doi.org/10.15244/pjoes/161327
  4. Beanland, V., Salmon, P. M., Filtness, A. J., Lenné, M. G., & Stanton, N. A. (2017). To stop or not to stop: Contrasting compliant and non-compliant driver behaviour at rural rail level crossings. Accident Analysis & Prevention, 108, 209–219. https://doi.org/10.1016/j.aap.2017.09.004
  5. Bhattacharya, D. (2018). Empirical welfare analysis for discrete choice: Some general results. Quantitative Economics, 9(2), 571–615. https://doi.org/10.3982/qe931
  6. Brika, S. (2022). A bibliometric analysis of fintech trends and digital finance. Frontiers in Environmental Science, 9, 796495. https://doi.org/10.3389/fenvs.2021.796495
  7. Brika, S., Chergui, K., Algamdi, A., Musa, A., & Zouaghi, R. (2022). E-learning research trends in higher education in light of COVID-19: A bibliometric analysis. Frontiers in Psychology, 12, 762819. https://doi.org/10.3389/fpsyg.2021.762819
  8. Briones-Bitar, J., Carrión-Mero, P., Montalván-Burbano, N., & Morante-Carballo, F. (2020). Rockfall research: A bibliometric analysis and future trends. Geosciences, 10(10), 403. https://doi.org/10.3390/geosciences10100403
  9. Chen, F. (2024). Can the opening of high-speed rail reduce environmental pollution? An empirical research based on difference-in-differences model. Clean Technologies and Environmental Policy, 26(7), 2309–2321. https://doi.org/10.1007/s10098-023-02719-5
  10. Chen, Y. (2019). High-speed railway and regional economic growth: A case of Beijing-Shanghai high-speed railway. Holistica – Journal of Business and Public Administration, 10(2), 95–104. https://doi.org/10.2478/hjbpa-2019-0018
  11. Chen, Y., Chen, W., & Chen, S. (2022). The mediating role of entrepreneurship in the link between high-speed rail and carbon emissions reduction. Frontiers in Environmental Science, 10, 1013060. https://doi.org/10.3389/fenvs.2022.1013060
  12. Chen, Z., & Wang, Y. (2019). Impacts of severe weather events on high-speed rail and aviation delays. Transportation Research Part D: Transport and Environment, 69, 168–183. https://doi.org/10.1016/j.trd.2019.01.030
  13. Chi, J., & Lei, Y. (2023). High-speed rail and China’s economic growth. Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China. https://doi.org/10.4108/eai.18-11-2022.2326760
  14. Chou, C., Shen, C., Gao, D., Gao, Y., Wang, K., & Tsai, S. (2018). Modelling the dynamic impacts of high-speed rail operation on regional public transport—from the perspective of energy economy. Energies, 11(5), 1151. https://doi.org/10.3390/en11051151
  15. Connolly, D., Kouroussis, G., Woodward, P., Costa, P., Verlinden, O., & Forde, M. (2014). Field testing and analysis of high-speed rail vibrations. Soil Dynamics and Earthquake Engineering, 67, 102–118. https://doi.org/10.1016/j.soildyn.2014.08.013
  16. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
  17. D’Alfonso, T., Jiang, C., & Bracaglia, V. (2015). Would competition between air transport and high-speed rail benefit environment and social welfare? Transportation Research Part B: Methodological, 74, 118–137. https://doi.org/10.1016/j.trb.2015.01.007
  18. Fang, M. (2024). Can the opening of high-speed rail promote green innovation behavior of enterprises: Evidence from China. Frontiers in Business Economics and Management, 13(1), 109–115. https://doi.org/10.54097/s851gn68
  19. Farliana, N., Hardianto, H., & Oktarina, N. (2023). Hybrid learning trends in higher education post-pandemic COVID-19: Scientometric mapping. World Journal of Advanced Research and Reviews, 17(1), 716–727. https://doi.org/10.30574/wjarr.2023.17.1.0039
  20. Fingleton, B., & Szumilo, N. (2019). Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach. Regional Science and Urban Economics, 75, 148–164. https://doi.org/10.1016/j.regsciurbeco.2018.12.004
  21. Gao, Y., Zhou, J., Fang, Y., & Smith, R. (2016). Analysis of the energy use of various high-speed trains and comparison with other modes of transport. 2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER), Monte Carlo, Monaco, 1–7. https://doi.org/10.1109/EVER.2016.7476385
  22. Ge, J. (2021). Research on the impact of high-speed railway on the industrial structure change and carbon emission of Chengdu-Chongqing urban agglomeration. E3S Web of Conferences, 275, 02001. https://doi.org/10.1051/e3sconf/202127502001
  23. Gera, B. (2024). Searching for optimal routes for mixed road-rail freight transportation. Matec Web of Conferences, 390, 03004. https://doi.org/10.1051/matecconf/202439003004
  24. Hallinger, P. (2023). Bibliometric review methodology and state of the science: Bibliometric review of research on problem-based learning, 2017–2021. Interdisciplinary Journal of Problem-Based Learning, 17(2). https://doi.org/10.14434/ijpbl.v17i2.35761
  25. He, Y. (2023). Analysis of the relationship between railway passenger traffic and turnover in China based on XGBoost algorithm. Journal of Applied Mathematics and Computation, 7(3), 381–386. https://doi.org/10.26855/jamc.2023.09.008
  26. Huang, C. (2024). Transportation infrastructure and economic growth: Evidence from “new nighttime light data” in the Yangtze River Delta. PLOS ONE, 19(8), e0306477. https://doi.org/10.1371/journal.pone.0306477
  27. Hu, S., Alimire, A., Lai, Y., Hu, H., Chen, Z., & Li, Y. (2021). Trends and frontiers of research on cancer gene therapy from 2016 to 2020: A bibliometric analysis. Frontiers in Medicine, 8, 740710. https://doi.org/10.3389/fmed.2021.740710
  28. Jin, X. (2014). Key problems faced in high-speed train operation. Journal of Zhejiang University Science A, 15, 936–945. https://doi.org/10.1631/jzus.a1400338
  29. Kang, D., Zhai, X., Chen, F., Wang, W., & Jia, L. (2022). How to promote the development of a green economy: Talent or technology? Evidence from China’s high-speed rail. Frontiers in Psychology, 13, 953506. https://doi.org/10.3389/fpsyg.2022.953506
  30. Kamga, C. (2015). Emerging travel trends, high-speed rail, and the public reinvention of U.S. transportation. Transport Policy, 37, 111–120. https://doi.org/10.1016/j.tranpol.2014.10.012
  31. Kong, J., Jeong, S., Yun, J., Chung, J., & Kim, J. (2022). Heterogeneity in personal attitudes and preferences for high-speed metropolitan railway service by travel contexts in South Korea: A hybrid choice modeling approach. Transportation Research Record Journal of the Transportation Research Board, 2676(6), 797–809. https://doi.org/10.1177/03611981221076428
  32. Kraus, S., Breier, M., Lim, W. M., Dabić, M., Kumar, S., Kanbach, D., ... & Ferreira, J. J. (2022). Literature reviews as independent studies: guidelines for academic practice. Review of Managerial Science, 16(8), 2577-2595. https://doi.org/10.1007/s11846-022-00588-8
  33. Lal, P. (2023). Exploring potato seed research: A bibliometric approach towards sustainable food security. Frontiers in Sustainable Food Systems, 7, 1229272. https://doi.org/10.3389/fsufs.2023.1229272
  34. Larue, G. S., Filtness, A. J., Wood, J. M., Demmel, S., Watling, C. N., Naweed, A., & Rakotonirainy, A. (2018). Is it safe to cross? Identification of trains and their approach speed at level crossings. Safety Science, 103, 33-42. https://doi.org/10.1016/j.ssci.2017.11.009
  35. Li, X., Tang, J., Hu, X., & Wang, W. (2020). Assessing intercity multimodal choice behavior in a touristy city: a factor analysis. Journal of Transport Geography, 86, 102776. https://doi.org/10.1016/j.jtrangeo.2020.102776
  36. Liu, L., & Chen, L. (2021). Research on the impact of Chengdu-Chongqing high-speed railway on tourism economic connection of cities along the line. In Proceedings of the 6th International Conference on Economics, Management, Law and Education (EMLE 2020) (pp. 123–129). Atlantis Press. https://doi.org/10.2991/aebmr.k.210210.019
  37. Liu, Y., & Shi, J. (2019). How inter-city high-speed rail influences tourism arrivals: Evidence from social media check-in data. Current Issues in Tourism, 22(9), 1025–1042. https://doi.org/10.1080/13683500.2017.1349080
  38. Lim, L. Y., Bong, C., Ho, W. S., Lim, J. S., Van Fan, Y., Ong, P. Y., ... & Lee, C. T. (2022). Research update on food waste composting: A bibliometric analysis and way forward. Chemical Engineering Transactions, 97, 523-528. https://doi.org/10.3303/CET2297088
  39. Lim, W. M., & Kumar, S. (2024). Guidelines for interpreting the results of bibliometric analysis: A sensemaking approach. Global Business and Organizational Excellence, 43(2), 17–26. https://doi.org/10.1002/joe.22229
  40. Lim, W. M., Kumar, S., & Donthu, N. (2024). How to combine and clean bibliometric data and use bibliometric tools synergistically: Guidelines using metaverse research. Journal of Business Research, 182, 114760. https://doi.org/10.1016/j.jbusres.2024.114760
  41. Lu, Y., Yang, S., & Jian, L. (2022). The influence of high-speed rails on urban innovation and the underlying mechanism. PLOS One, 17(3), e0264779. https://doi.org/10.1371/journal.pone.0264779
  42. Lubis, H., Pantas, V., & Farda, M. (2019). Demand forecast of Jakarta-Surabaya high-speed rail based on stated preference method. International Journal of Technology, 10(2), 405. https://doi.org/10.14716/ijtech.v10i2.2442
  43. Malabanan, I., Satirasetthavee, D., Kitthamkasorn, S., & Panpaksorn, J. (2023). Returning to public transportation in transitioning out of COVID-19: Effects of passenger satisfaction on frequency of use of rail transport. Transactions on Transport Sciences, 14(2), 54–67. https://doi.org/10.5507/tots.2023.005
  44. Mendes, J., Bueno, L., Oliveira, A., & Gerólamo, M. (2022). Agriculture startups (AgTechs): A bibliometric study. International Journal of Professional Business Review, 7(2), e0312. https://doi.org/10.26668/businessreview/2022.v7i2.312
  45. Mensah, M., & Jumah, A. (2021). Electronic money and consumer spending behaviour: Evidence from Ghana. Advances in Management and Applied Economics, 11(6), 105–121. https://doi.org/10.47260/amae/1136
  46. Morley, K. (2024). Wellbeing impact study of high-speed 2 (WISH2): Protocol for a mixed-methods examination of the impact of major transport infrastructure development on mental health and wellbeing. PLOS One, 19(2), e0298701. https://doi.org/10.1371/journal.pone.0298701
  47. Mou, Z., Yan, K., Li, K., Shen, D., Li, X., Han-bing, W., & Chen, Y. (2021). Dynamic evolution game of travelers’ air-to-HSR choice under the scenario of HSR speed-up. Mathematical Problems in Engineering, 2021, 1–12. https://doi.org/10.1155/2021/9650907
  48. Muchiri, M., Késmárki-Gally, S., Fekete-Farkas, M., & Lakner, Z. (2022). Bibliometric analysis of green finance and climate change in the post-Paris Agreement era. Journal of Risk and Financial Management, 15(12), 561. https://doi.org/10.3390/jrfm15120561
  49. Mukherjee, D., Lim, W. M., Kumar, S., & Donthu, N. (2022). Guidelines for advancing theory and practice through bibliometric research. Journal of Business Research, 148, 101–115. https://doi.org/10.1016/j.jbusres.2022.04.042
  50. Najmaei, A., & Sadeghinejad, Z. (2022). Green and sustainable business models: Historical roots, growth trajectory, conceptual architecture, and an agenda for future research—A bibliometric review of green and sustainable business models. Scientometrics, 128(2), 957–999. https://doi.org/10.1007/s11192-022-04577-2
  51. Nobanee, H., Alqubaisi, G., Alhameli, A., Alqubaisi, H., Alhammadi, N., Almasahli, S., … & Wazir, N. (2021). Green and sustainable life insurance: A bibliometric review. Journal of Risk and Financial Management, 14(11), 563. https://doi.org/10.3390/jrfm14110563
  52. Noviarti, D. (2023). Systematic literature review: Financing system in railway transportation. E3S Web of Conferences, 429, 03008. https://doi.org/10.1051/e3sconf/202342903008
  53. Pan, L. (2024). Effects of train speed on dynamic performance of shoe-rail interaction system. Advances in Mechanical Engineering, 16(4). https://doi.org/10.1177/16878132241239799
  54. Qi, Y. (2023). Effect of rail profile wear on vehicle operation performance in high-speed line. Industrial Lubrication and Tribology, 75(10), 1188–1198. https://doi.org/10.1108/ilt-08-2023-0270
  55. Qiu, H. (2023). Analysis of consumer behavior in bigdata insights. In Proceedings of the 2023 International Conference on Big Data and Analytics (pp. 429–438). Atlantis Press. https://doi.org/10.2991/978-94-6463-298-9_47
  56. Ren, X., Wang, F., Wang, C., Du, Z., Chen, Z., Wang, J., & Dan, T. (2019). Impact of high-speed rail on intercity travel behavior change. Journal of Transport and Land Use, 12(1), 265–285. https://www.jstor.org/stable/26911268
  57. Sallan, J. (2023). Recent trends in air transport research: A bibliometric analysis. Future Transportation, 3(3), 1046–1067. https://doi.org/10.3390/futuretransp3030058
  58. Santosa, F. (2023). Prior steps into knowledge mapping: Text mining application and comparison. Issues in Science and Technology Librarianship, 102. https://doi.org/10.29173/istl2736
  59. Schouten, A., Wachs, M., Blumenberg, E. A., & King, H. R. (2022). Cohort analysis of driving cessation and limitation among older adults. Transportation, 49(3), 841–865. https://doi.org/10.1007/s11116-021-10196-2
  60. Šimeček, M. (2019). Discrete choice analysis of travel behaviour. Transactions on Transport Sciences, 10(1), 5–9. https://doi.org/10.5507/tots.2019.001
  61. Straulino, D., Froy, F., Schwanen, T., & Neave, G. (2023). Connecting up embedded knowledge across northern powerhouse cities. Environment and Planning A: Economy and Space, 55(7), 1690–1713. https://doi.org/10.1177/0308518x231159108
  62. Tang, J., Zhen, F., Cao, J., & Mokhtarian, P. L. (2018). How do passengers use travel time? A case study of Shanghai–Nanjing high-speed rail. Transportation, 45, 451–477. https://doi.org/10.1007/s11116-017-9824-9
  63. Tang, M. (2024). Can the opening of high-speed rail boost corporate ESG? Empirical evidence from China. Advances in Economics, Management, and Political Sciences, 75(1), 37–43. https://doi.org/10.54254/2754-1169/75/20241788
  64. Tang, Z., Bi, H., Sun, J., Xu, Y., & Wang, Z. (2023). Research on the coopetition relationship and the development of city-industry integration of urban agglomeration under the effect of HSR. Frontiers in Environmental Science, 11. https://doi.org/10.3389/fenvs.2023.1082664
  65. Tian, B., Bian, Y., Bian, D., Gao, Y., Zhang, X., Zhou, S., … & Wang, L. (2022). Knowledge mapping of alternative splicing of cancer from 2012 to 2021: A bibliometric analysis. Frontiers in Oncology, 12, 1068805. https://doi.org/10.3389/fonc.2022.1068805
  66. Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
  67. Wang, J., Jiao, J., Du, C., & Hu, H. (2015). Competition of spatial service hinterlands between high-speed rail and air transport in China: Present and future trends. Journal of Geographical Sciences, 25(9), 1137–1152. https://doi.org/10.1007/s11442-015-1224-5
  68. Wang, S., Zhou, H., & Ge, H. (2020). Is the high-speed rail opening environmentally friendly? Taking the difference-in-differences test in Jiangsu, China. Complexity, 2020, 1–11. https://doi.org/10.1155/2020/7154076
  69. Widaryanti, P. (2024). Discovering thematic change and evolution of political connections research. Future Business Journal, 10(1), 59. https://doi.org/10.1186/s43093-024-00356-y
  70. Wong, M. (2021). Generative modelling and machine learning methods for travel behaviour analysis (Doctoral dissertation, Toronto Metropolitan University). https://doi.org/10.32920/ryerson.14664273
  71. Xiao, Z., Zhao, Z., Wang, H., Sun, P., & Feng, X. (2020). Speed trajectory optimization for a high-speed train. WIT Transactions on The Built Environment, 199, 261-272. https://doi.org/10.2495/cr200241
  72. Xuesong, J. (2022). Research progress of high-speed wheel–rail relationship. Lubricants, 10(10), 248. https://doi.org/10.3390/lubricants10100248
  73. Xu, G., Yang, H., Liu, W., & Shi, F. (2018). Itinerary choice and advance ticket booking for high-speed railway network services. Transportation Research Part C: Emerging Technologies, 95, 82–104. https://doi.org/10.1016/j.trc.2018.07.010
  74. Xu, L., & Shen, X. (2021). Research on consumer behavior based on the perspective of behavioral economics. https://doi.org/10.2991/assehr.k.211209.054
  75. Xu, X. (2024). A study of the impact of the use of real-time crowding information on the perceived service quality of high-speed rail by passengers with unfixed-seat tickets. Applied Sciences, 14(2), 535. https://doi.org/10.3390/app14020535
  76. Xu, Y., & Zhu, S. (2023). Transport infrastructure, intra-regional inequality, and urban-rural divide: Evidence from China’s high-speed rail construction. International Regional Science Review, 47(3), 378–406. https://doi.org/10.1177/01600176231177672
  77. Yang, W., Chen, Q., & Yang, J. (2022). Factors affecting travel mode choice between high-speed railway and road passenger transport—Evidence from China. Sustainability, 14(23), 15745. https://doi.org/10.3390/su142315745
  78. Yang, Z., Li, C., Jiao, J., Liu, W., & Zhang, F. (2020). On the joint impact of high-speed rail and megalopolis policy on regional economic growth in China. Transport Policy, 99, 20–30. https://doi.org/10.1016/j.tranpol.2020.08.007
  79. Yu, S. (2024). Research status and development trends of active control technology for pantograph in high-speed railways, 1-8. https://doi.org/10.20944/preprints202403.1137.v1
  80. Yuan, X., Guo, L., & Ye, K. (2016). A study on small-world characteristics of China’s high-speed railway networks. Modular and Offsite Construction (Moc) Summit Proceedings. https://doi.org/10.29173/mocs29
  81. Yuan-yuan, C. (2021). Research on the impact of high-speed railway opening on regional economy and environment - Evidence based on Henan Province. E3S Web of Conferences, 275, 01003. https://doi.org/10.1051/e3sconf/202127501003
  82. Yue, T. (2023). Influence of “double cross” shaped high-speed rail line on industrial development of cities along Henan. https://doi.org/10.4108/eai.2-12-2022.2328674
  83. Zeng, Z., & Xiao-jun, W. (2023). Will world cultural heritage sites boost economic growth? Evidence from Chinese cities. Sustainability, 15(10), 8375. https://doi.org/10.3390/su15108375
  84. Zhang, P., Ding, R., Zhao, W., Zhang, L., & Sun, H. (2022). Passenger travel path selection based on the characteristic value of transport services. Sustainability, 15(1), 636. https://doi.org/10.3390/su15010636
  85. Zhen, F., Cao, X., & Tang, J. (2019). The role of access and egress in passenger overall satisfaction with high speed rail. Transportation, 46, 2137–2150. https://doi.org/10.1007/s11116-018-9918-z
  86. Zhou, J. (2023). The impact of high-speed railway on the accessibility pattern of triangle of central China. https://doi.org/10.4108/eai.2-12-2022.2328711
  87. Zgonc, B., Tekavčič, M., & Jakšič, M. (2019). The impact of distance on mode choice in freight transport. European Transport Research Review, 11(1), 1-18. https://doi.org/10.1186/s12544-019-0346-8