Airport planning: approaches to determining the planning horizon
Abstract
Airport planning is a challenging task that requires knowledge of many standards and recommended practices, bylaws and procedures. Besides, it is possible that politicians would try to intervene in the planning process, which always exceeds the election period of one government. Therefore, the article provides in-depth theoretical analysis of the problem and summarizes the results of research that focused on comparing the approach to the airport planning issues in the Slovakia and Croatia. The primary goal was to develop a methodology for determining the airport planning horizon, to assess the significance of individual planning phases and to evaluate results. The research was carried out using a combination of several methods. The main challenge was to determine the length of the planning horizon. In 2 panels, 32 experts from Slovakia and Croatia were interviewed and 224 different responses were received and processed by the fuzzy Delphi method. The advantage of this approach relies on combination of well – developed theory and practical solutions in cooperation with experts from the industry. Despite the different legal frameworks and similar standards for airport planning in both countries, the results of the research proved that the values of the optimal planning horizons are comparable. As a result, the methodology can therefore be used in other countries with similar conditions. However, planning procedures and practices depend on the specifics of states or even regions. Eventually, the experience from the research provides relevant and robust material to support teaching. Besides, it is transferable to other fields of transport infrastructure planning. Additionally, the research results were provided to the state planning authorities.
Keyword : airport planning, land use plans, long-term plans, planning methodology, fuzzy Delphi method, expert panels
How to Cite
Kazda, A., Novák Sedláčková, A., & Bračić, M. (2023). Airport planning: approaches to determining the planning horizon. Transport, 38(3), 139–151. https://doi.org/10.3846/transport.2023.19797
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Kazda, A. 2017. Airport planning and design – legal and professional competence requirements, Civil and Environmental Engineering 13(2): 143–148. https://doi.org/10.1515/cee-2017-0019
Kazda, A. 1985. Obchodná prevádzková činnosť: vybrané state. Bratislava: Alfa. 175 s. (in Slovak).
Kazda, A.; Caves, R. E. 2015. Airport Design and Operation. Emerald. 569 p. https://doi.org/10.1108/9781784418694
Kazda, A.; Novák Sedláčková, A.; Bračić, M. 2020. Expropriation and airport development, Civil and Environmental Engineering 16(2): 282–288. https://doi.org/10.2478/cee-2020-0028
Ke, L.; Bin, S. 2020. Research on planning and design of airport airfield area, IOP Conference Series: Materials Science and Engineering 792: 012016. https://doi.org/10.1088/1757-899X/792/1/012016
Kuo, Y.-F.; Chen, P.-C. 2008. Constructing performance appraisal indicators for mobility of the service industries using fuzzy Delphi method, Expert Systems with Applications 35(4): 1930–1939. https://doi.org/10.1016/j.eswa.2007.08.068
Kwakkel, J. H.; Walker, W. E.; Marchau, V. A. W. J. 2010. Adaptive airport strategic planning, European Journal of Transport and Infrastructure Research 10(3): 249–273. https://doi.org/10.18757/ejtir.2010.10.3.2891
Mohamad, S.; Embi, M.; Nordin, N. 2015. Determining e-portfolio elements in learning process using fuzzy Delphi analysis, International Education Studies 8(9): 171–176. https://doi.org/10.5539/ies.v8n9p171
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Pachauri, B.; Kumar, A.; Dhar, J. 2013. Modeling optimal release policy under fuzzy paradigm in imperfect debugging environment, Information and Software Technology 55(11): 1974–1980. https://doi.org/10.1016/j.infsof.2013.06.001
Pandey, M. M. 2020. Evaluating the strategic design parameters of airports in Thailand to meet service expectations of low-cost airlines using the fuzzy-based QFD method, Journal of Air Transport Management 82: 101738. https://doi.org/10.1016/j.jairtraman.2019.101738
Parenté, F. J.; Anderson, J. K.; Myers, P.; O’Brien, T. 1984. An examination of factors contributing to Delphi accuracy, Journal of Forecasting 3(2): 173–182. https://doi.org/10.1002/for.3980030205
Petrović, M.; Mlinarić, T. J.; Šemanjski, I. 2019. Location planning approach for intermodal terminals in urban and suburban rail transport, Promet – Traffic & Transportation 31(1): 101–111. https://doi.org/10.7307/ptt.v31i1.3034
Rawson, R.; Hooper, P. D. 2012. The importance of stakeholder participation to sustainable airport master planning in the UK, Environmental Development 2: 36–47. https://doi.org/10.1016/j.envdev.2012.03.013
Ray, P. K.; Sahu, S. 1990. Productivity management in India: a Delphi study, International Journal of Operations & Production Management 10(5): 25–51. https://doi.org/10.1108/01443579010005245
Rowe, G.; Wright, G. 2001. Expert opinions in forecasting: the role of the Delphi technique, International Series in Operations Research & Management Science 30: 125–144. https://doi.org/10.1007/978-0-306-47630-3_7
Rowe, G.; Wright, G.; Bolger, F. 1991. Delphi: a reevaluation of research and theory, Technological Forecasting and Social Change 39(3): 235–251. https://doi.org/10.1016/0040-1625(91)90039-I
Saldıraner, Y. 2013. Airport master planning in Turkey; planning and development problems and proposals, Journal of Air Transport Management 32: 71–77. https://doi.org/10.1016/j.jairtraman.2013.07.003
Sismanidou, A.; Tarradellas, J. 2017. Traffic demand forecasting and flexible planning in airport capacity expansions: lessons from the Madrid-Barajas new terminal area master plan, Case Studies on Transport Policy 5(2): 188–199. https://doi.org/10.1016/j.cstp.2016.08.003
Soiferman, L. K. 2010. Compare and Contrast Inductive and Deductive Research Approaches. University of Manitoba, Winnipeg, Manitoba, Canada. 23 p. Available from Internet: https://eric.ed.gov/?id=ED542066
Suh, D.; Ryerson, M. S. 2017. Frameworks for adaptive airport planning and techniques for a new era of planning, Transportation Research Record: Journal of the Transportation Research Board 2603: 65–77. https://doi.org/10.3141/2603-07
Tisdall, L.; Zhang, Y.; Zhang, A. 2020. Development challenges facing general aviation airports: a case study of Archerfield airport, Queensland, Australia, Case Studies on Transport Policy 8(4): 1458–1467. https://doi.org/10.1016/j.cstp.2020.10.010
Tsai, H.-C.; Lee, A.-S.; Lee, H.-N.; Chen, C.-N.; Liu, Y.-C. 2020. An application of the fuzzy Delphi method and fuzzy AHP on the discussion of training indicators for the regional competition, Taiwan National skills competition, in the trade of joinery, Sustainability 12(10): 4290. https://doi.org/10.3390/su12104290
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Zarnowitz, V.; Lambros, L. A. 1987. Consensus and uncertainty in economic prediction, Journal of Political Economy 95(3): 591–621. https://doi.org/10.1086/261473
Ahmad, Z.; Wasli, M. M. P.; Fauzi, M. S. H. M.; Jamil, M. R. M.; Siraj, S. 2014. Fuzzy Delphi analysis for future environmental education using interactive animation, in 2nd International Seminar Teaching Excellence and Innovation, 25 February 2014, Kuala Lumpur, Malaya, 1–8. Available from: https://snazlan.files.wordpress.com/2015/11/3-fuzzy-delphi-analysis-for-future-environmental-education-using-interactive-animation.pdf
Airport Technology. 2020. Charles de Gaulle Airport (CDG/LFPG). Available from Internet: https://www.airport-technology.com/projects/degaulle/
Barofsky, I. 2012. Can quality or quality-of-life be defined?, Quality of Life Research 21(4): 625–631. https://doi.org/10.1007/s11136-011-9961-0
Brown, G.; Raymond, C. M. 2014. Methods for identifying land use conflict potential using participatory mapping, Landscape and Urban Planning 122: 196–208. https://doi.org/10.1016/j.landurbplan.2013.11.007
Caves, R. E.; Gosling, G. D. 1999. Strategic Airport Planning. Pergamon. 468 p.
Chang, P.-L.; Hsu, C.-W.; Chang, P.-C. 2011. Fuzzy Delphi method for evaluating hydrogen production technologies, International Journal of Hydrogen Energy 36(21): 14172–14179. https://doi.org/10.1016/j.ijhydene.2011.05.045
Chen, C.-T. 2000. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems 114(1): 1–9. https://doi.org/10.1016/S0165-0114(97)00377-1
Cheng, C.-H.; Lin, Y. 2002. Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation, European Journal of Operational Research 142(1): 174–186. https://doi.org/10.1016/S0377-2217(01)00280-6
Creswell, J. W.; Clark, V. L. P. 2017. Designing and Conducting Mixed Methods Research. SAGE Publications. 520 p.
Dawood, K. A.; Sharif, K. Y.; Ghani, A. A.; Zulzalil, H.; Zaidan, A. A.; Zaidan, B. B. 2021. Towards a unified criteria model for usability evaluation in the context of open source software based on a fuzzy Delphi method, Information and Software Technology 130: 106453. https://doi.org/10.1016/j.infsof.2020.106453
De Neufville, R.; Odoni, A. 2003. Airport Systems: Planning, Design, and Management. McGraw-Hill Professional. 883 p.
Duru, O.; Bulut, E.; Yoshida, S. 2012. A fuzzy extended DELPHI method for adjustment of statistical time series prediction: An empirical study on dry bulk freight market case, Expert Systems with Applications 39(1): 840–848. https://doi.org/10.1016/j.eswa.2011.07.082
EIU. 2021. Democracy Index 2021: the China Challenge. Economist Intelligence Unit (EIU.) Available from Internet: https://www.eiu.com/n/campaigns/democracy-index-2021/
FAA. 2005. FAA AC 150/5070-6B: Airport Master Plans. Federal Aviation Administration (FAA).
FAA. 2023. National Plan of Integrated Airport Systems (NPIAS). Federal Aviation Administration (FAA). Available from Internet: https://www.faa.gov/airports/planning_capacity/npias
Ferrulli, P. 2016. Green Airport Design Evaluation (GrADE) – methods and tools improving infrastructure planning, Transportation Research Procedia 14: 3781–3790. https://doi.org/10.1016/j.trpro.2016.05.463
Fewings, R. 2001. Wayfinding and airport terminal design, The Journal of Navigation 54(2): 177–184. https://doi.org/10.1017/S0373463301001369
Freestone, R.; Baker, D. 2010. Challenges in land use planning around Australian airports, Journal of Air Transport Management 16(5): 264–271. https://doi.org/10.1016/j.jairtraman.2010.03.001
Freestone, R.; Baker, D. 2011. Spatial planning models of airport-driven urban development, Journal of Planning Literature 26(3): 263–279. https://doi.org/10.1177/0885412211401341
Gupta, U. G.; Clarke, R. E. 1996. Theory and applications of the Delphi technique: a bibliography (1975–1994), Technological Forecasting and Social Change 53(2): 185–211. https://doi.org/10.1016/S0040-1625(96)00094-7
Gutierrez, O. 1989. Experimental techniques for information requirements analysis, Information & Management 16(1): 31–43. https://doi.org/10.1016/0378-7206(89)90025-6
Hakfoort, J.; Poot, T.; Rietveld, P. 2001. The regional economic impact of an airport: the case of Amsterdam Schiphol airport, Regional Studies 35(7): 595–604. https://doi.org/10.1080/00343400120075867
Horonjeff, R.; McKelvey, F.; Sproule, W.; Young, S. 2010. Planning and Design of Airports. 5th edition. McGraw Hill. 688 p.
IATA. 2022. Airport Development Reference Manual (ADRM). International Air Transport Association (IATA). Available from Internet: https://store.iata.org/IEC_ProductDetails?id=9346-12
ICAO. 2023. Airport Planning Manual – Part I – Master Planning (Doc 9184 – Part 1). International Civil Aviation Organization (ICAO). Available from Internet: https://store.icao.int/en/airport-planning-manual-master-planning-doc-9184-part-1
IEP. 2021. Global Peace Index 2021: Measuring Peace in a Complex World. Institute for Economics & Peace (IEP), Sydney, Australia. 97 p. Available from Internet: https://www.visionofhumanity.org/wp-content/uploads/2021/06/GPI-2021-web-1.pdf
Ishikawa, A.; Amagasa, M.; Shiga, T.; Tomizawa, G.; Tatsuta, R.; Mieno, H. 1993. The max-min Delphi method and fuzzy Delphi method via fuzzy integration, Fuzzy Sets and Systems 55(3): 241–253. https://doi.org/10.1016/0165-0114(93)90251-C
ITF. 2016. Airport Demand Forecasting for Long-Term Planning. ITF Round Tables 159. International Transport Forum (ITF). 100 p. https://doi.org/10.1787/9789282108024-en
Kazda, A. 2012. Airport access infrastructure critical issue of the intermodal chain, in CETRA 2012: 2nd International Conference Road and Rail Infrastructure, 7–9 May 2012, Dubrovnik, Croatia, 595–600.
Kazda, A. 2017. Airport planning and design – legal and professional competence requirements, Civil and Environmental Engineering 13(2): 143–148. https://doi.org/10.1515/cee-2017-0019
Kazda, A. 1985. Obchodná prevádzková činnosť: vybrané state. Bratislava: Alfa. 175 s. (in Slovak).
Kazda, A.; Caves, R. E. 2015. Airport Design and Operation. Emerald. 569 p. https://doi.org/10.1108/9781784418694
Kazda, A.; Novák Sedláčková, A.; Bračić, M. 2020. Expropriation and airport development, Civil and Environmental Engineering 16(2): 282–288. https://doi.org/10.2478/cee-2020-0028
Ke, L.; Bin, S. 2020. Research on planning and design of airport airfield area, IOP Conference Series: Materials Science and Engineering 792: 012016. https://doi.org/10.1088/1757-899X/792/1/012016
Kuo, Y.-F.; Chen, P.-C. 2008. Constructing performance appraisal indicators for mobility of the service industries using fuzzy Delphi method, Expert Systems with Applications 35(4): 1930–1939. https://doi.org/10.1016/j.eswa.2007.08.068
Kwakkel, J. H.; Walker, W. E.; Marchau, V. A. W. J. 2010. Adaptive airport strategic planning, European Journal of Transport and Infrastructure Research 10(3): 249–273. https://doi.org/10.18757/ejtir.2010.10.3.2891
Mohamad, S.; Embi, M.; Nordin, N. 2015. Determining e-portfolio elements in learning process using fuzzy Delphi analysis, International Education Studies 8(9): 171–176. https://doi.org/10.5539/ies.v8n9p171
Murray, T. J.; Pipino, L. L.; Van Gigch, J. P. 1985. A pilot study of fuzzy set modification of Delphi, Human Systems Management 5(1): 76–80. https://doi.org/10.3233/HSM-1985-5111
Musani, S.; Jemain, A. A. 2013. A fuzzy MCDM approach for evaluating school performance based on linguistic information, AIP Conference Proceedings 1571: 1006–1012. https://doi.org/10.1063/1.4858785
Pachauri, B.; Kumar, A.; Dhar, J. 2013. Modeling optimal release policy under fuzzy paradigm in imperfect debugging environment, Information and Software Technology 55(11): 1974–1980. https://doi.org/10.1016/j.infsof.2013.06.001
Pandey, M. M. 2020. Evaluating the strategic design parameters of airports in Thailand to meet service expectations of low-cost airlines using the fuzzy-based QFD method, Journal of Air Transport Management 82: 101738. https://doi.org/10.1016/j.jairtraman.2019.101738
Parenté, F. J.; Anderson, J. K.; Myers, P.; O’Brien, T. 1984. An examination of factors contributing to Delphi accuracy, Journal of Forecasting 3(2): 173–182. https://doi.org/10.1002/for.3980030205
Petrović, M.; Mlinarić, T. J.; Šemanjski, I. 2019. Location planning approach for intermodal terminals in urban and suburban rail transport, Promet – Traffic & Transportation 31(1): 101–111. https://doi.org/10.7307/ptt.v31i1.3034
Rawson, R.; Hooper, P. D. 2012. The importance of stakeholder participation to sustainable airport master planning in the UK, Environmental Development 2: 36–47. https://doi.org/10.1016/j.envdev.2012.03.013
Ray, P. K.; Sahu, S. 1990. Productivity management in India: a Delphi study, International Journal of Operations & Production Management 10(5): 25–51. https://doi.org/10.1108/01443579010005245
Rowe, G.; Wright, G. 2001. Expert opinions in forecasting: the role of the Delphi technique, International Series in Operations Research & Management Science 30: 125–144. https://doi.org/10.1007/978-0-306-47630-3_7
Rowe, G.; Wright, G.; Bolger, F. 1991. Delphi: a reevaluation of research and theory, Technological Forecasting and Social Change 39(3): 235–251. https://doi.org/10.1016/0040-1625(91)90039-I
Saldıraner, Y. 2013. Airport master planning in Turkey; planning and development problems and proposals, Journal of Air Transport Management 32: 71–77. https://doi.org/10.1016/j.jairtraman.2013.07.003
Sismanidou, A.; Tarradellas, J. 2017. Traffic demand forecasting and flexible planning in airport capacity expansions: lessons from the Madrid-Barajas new terminal area master plan, Case Studies on Transport Policy 5(2): 188–199. https://doi.org/10.1016/j.cstp.2016.08.003
Soiferman, L. K. 2010. Compare and Contrast Inductive and Deductive Research Approaches. University of Manitoba, Winnipeg, Manitoba, Canada. 23 p. Available from Internet: https://eric.ed.gov/?id=ED542066
Suh, D.; Ryerson, M. S. 2017. Frameworks for adaptive airport planning and techniques for a new era of planning, Transportation Research Record: Journal of the Transportation Research Board 2603: 65–77. https://doi.org/10.3141/2603-07
Tisdall, L.; Zhang, Y.; Zhang, A. 2020. Development challenges facing general aviation airports: a case study of Archerfield airport, Queensland, Australia, Case Studies on Transport Policy 8(4): 1458–1467. https://doi.org/10.1016/j.cstp.2020.10.010
Tsai, H.-C.; Lee, A.-S.; Lee, H.-N.; Chen, C.-N.; Liu, Y.-C. 2020. An application of the fuzzy Delphi method and fuzzy AHP on the discussion of training indicators for the regional competition, Taiwan National skills competition, in the trade of joinery, Sustainability 12(10): 4290. https://doi.org/10.3390/su12104290
UNDP. 2022. Human Development Report 2021-22: Uncertain Times, Unsettled Lives: Shaping our Future in a Transforming World. United Nations Development Programme (UNDP). Available from Internet: https://hdr.undp.org/content/human-development-report-2021-22
WB. 2023. Worldwide Governance Indicators. The World Bank Group (WB). Available from Internet: https://databank.worldbank.org/source/worldwide-governance-indicators
Zadeh, L. A. 1965. Fuzzy sets, Information and Control 8(3): 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zarnowitz, V.; Lambros, L. A. 1987. Consensus and uncertainty in economic prediction, Journal of Political Economy 95(3): 591–621. https://doi.org/10.1086/261473