Overview of the Influence of Level of Service on the Airport Passenger Terminal Capacity

Jelena Pivac; Igor Štimac; Andrija Vidović; Karmela Boc

doi:10.7307/ptt.v34i6.4203

Authors

Jelena Pivac University of Zagreb, Faculty of Transport and Traffic Sciences
Igor Štimac University of Zagreb, Faculty of Transport and Traffic Sciences
Andrija Vidović University of Zagreb, Faculty of Transport and Traffic Sciences
Karmela Boc Rudolf Perešin Aviation Technical School

DOI:

https://doi.org/10.7307/ptt.v34i6.4203

Keywords:

airport, airport passenger terminal, level of service (LoS), airport passenger terminal capacity, airport terminal facilities, optimisation

Abstract

Establishing the desired quality of service (QoS) of the airport passenger terminal in order to improve operational performance is a challenge for every airport. Recent international research indicates a gradual recovery in air transport and, accordingly, the need to develop additional transport infrastructure. If the passenger terminal design in terms of infrastructure and operational capacity is not approached correctly, the level of service provided to passengers may decline. This research will focus on how the IATA Level of Service (LoS), which is provided to airport users can contribute to the optimisation of the level of service of the passenger terminal. Additionally, the impact of level of service on passenger terminal capacity assessment in relation to the diversity of air carrier business model will be analysed. Since there is no common link to uniformly describe and solve this problem, this paper will review the relevant literature in the field of passenger terminal capacity research and will analyse different approaches to solving this problem with the aim to develop a new unified concept in observing and optimising the capacity of the airport passenger terminal taking into account the types of air carrier business models.

References

Belobaba PP, Odoni AR, Barnhart C. The Global Airline Industry. John Wiley & Sons Ltd., Chichester, United Kingdom, 2009.

International Air Transport Association (IATA). https://www.iata.org/en/publications/store/20-year-passenger-forecast/ [Accessed 11th Apr. 2022].

International Air Transport Association (IATA). Airport Development Reference Manual (ADRM). 9th edition. Montréal, Canada; 2004.

International Air Transport Association (IATA). Airport Development Reference Manual (ADRM). 10th edition. Montréal, Canada; 2014.

International Air Transport Association (IATA): Airport Development Reference Manual (ADRM). 11th edition. Montréal, Canada; 2019.

Baker DM. Service quality and customer satisfaction in the airline industry: A comparison between legacy airlines and low-cost airlines. American Journal of Tourism Research. 2013;2(1): 67–77. doi: 10.11634/216837861302317.

Ostrowski PL, O’Brien TV, Gordon GL. Service quality and customer loyalty in the commercial airline industry. Journal of Travel Research. 1994;32(2): 16–24. doi: 10.1177/004728759303200203.

Tse DK, Wilton PC. Models of consumer satisfaction formation: An extension. Journal of Marketing Research. 1988;25(2): 204–212. doi: 10.2307/3172652.

Albacete Saez CA, et al. Service quality measurement in rural accommodation. Annals of Tourism Research. 2007;34(1): 45–65. doi: 10.1016/j.annals.2006.06.010.

Pivac J, Vince D, Štimac I, Boc K. Analiza kvalitete usluge u putničkom terminalu zračne luke s aspekta putnika. Zbornik radova 20. međunarodnog simpozija o kvaliteti Kvaliteta – jučer, danas, sutra. 2021. p. 157–174. doi: 10.52730/LLGN5445.

National Academies of Sciences, Engineering and Medicine. Improving the airport customer experience. Washington, DC: The National Academies Press; 2016.

Livingstone A, Popovic V, Kraal BJ, Kirk PJ. Understanding the airport passenger landside retail experience. In: Israsena P, Tangsantikul J, Durling D. (Eds.) Research: Uncertainty Contradiction Value - DRS International Conference 2012, 1-4 July, Bangkok, Thailand. 2012. p. 1–18. https://dl.designresearchsociety.org/drs-conference-papers/drs2012/researchpapers/78.

Mudambi SM, Schuff D. What makes a helpful review? A study of customer reviews on Amazon. Com. MIS Quarterly. 2010;34(1): 185–200. doi: https://doi.org/10.2307/20721420.

Haddad RE. Exploring service quality of low cost airlines. Services Marketing Quarterly. 2019;40(4): 301–315. doi: 10.1080/15332969.2019.1665901.

Ahn TH, Lee TJ. Service quality in the airline industry: Comparison between traditional and low-cost airlines. Tourism Analysis. 2011;16(5): 535–542. doi: 10.3727/108354211X13202764960582.

Morash EA, Ozment J. Toward management of transportation service quality. Logistics and Transportation Review. 1994; 30, 115–140.

Young C, Lawrence C, Lee M. Assessing service quality as an effective management tool: The case of the airline industry. Journal of Marketing Theory and Practice. 1994;2(2): 76–96.doi: 10.1080/10696679.1994.11501652.

Han H, Hwang J. In-flight physical surroundings: Quality, satisfaction, and traveller loyalty in the emerging low cost flight market. Current Issues in Tourism. 2017;20(13): 1336–1354. doi: https://doi.org/10.1080/13683500.2014.960371.

O’Connell JF, Williams G. Passengers’ perceptions of low cost airlines and full service carriers: A case study involving Ryanair, Aer Lingus, Air Asia and Malaysia Airlines. Journal of Air Transport Management. 2005;11(4): 259–272. doi: 10.1016/j.jairtraman.2005.01.007.

Lim J, Lee HC. Comparisons of service quality perceptions between full service carriers and low cost carriers in airline travel. Current Issues in Tourism. 2019;23: 1261-1276. doi: 10.1080/13683500.2019.1604638.

Koklic MK, Kukar-Kinney M, Vegelj S. An investigation of customer satisfaction with low-cost and full-service airline companies. Journal of Business Research. 2017;80: 188–196. doi: 10.1016/j.jbusres.2017.05.015.

Chiou YC, Chen YH. Factors influencing the intentions of passengers regarding full service and low cost carriers: A note. Journal of Air Transport Management. 2010;16(4): 226–228. doi: 10.1016/j.jairtraman.2009.11.005.

Chou CC, et al. An evaluation of airline service quality using the fuzzy weighted SERVQUAL method. Applied Soft Computing. 2011;11(2): 2117–2128. doi: 10.1016/j.asoc.2010.07.010.

Transportation Research Board. ACRP Report 25 - Airport passenger terminal planning and design, Volume 1: Guidebook, Airport Cooperative Research Program. Washington, USA; 2010.

Brunetta L, Right L, Andreatta G. An operations research model for the evaluation of an airport terminal: SLAM (Simple Landside Aggregate Model). Journal of Air Transport Management. 1999; 161–175. doi: 10.1016/S0969-6997(99)00010-1.

Štimac I. Optimiranje udjela prijevoznika u kapacitetima zračne luke, Ph.D. Thesis. Fakultet prometnih znanosti, Zagreb, 2017.

Zagrafos KG, et al. Modelling and managing airport performance. 1st edition. Chichester, UK: John Wiley and Sons Ltd; 2013.

Svrcek T. Planning level decision support for the selection of robust configurations of airport passenger buildings. MIT, Dept. of Aeronautics & Astronautics, Flight Transportation Laboratory. FTL Report No. R94-6, 1994.

Pavlin S. Aerodromi I. Zagreb: Fakultet prometnih znanosti; 2006.

Hae Choi J. Changes in airport operating procedures and implications for airport strategies post-COVID-19. Journal of Air Transport Management. 2021;94. doi: 10.1016/j.jairtraman.2021.102065.

Odoni AR, de Neufville R. Passenger terminal design. Transportation Research. 1992;26A(1): 27–35.

Kim D-U, Jie M-S, Choi W-H. Airport simulation based on queuing model using ARENA. International Journal of Advanced Science and Technology. 2018;115: 125–134. doi: 10.14257/ijast.2018.115.12.

Guizzi G, Murino T, Romano E. A discrete event simulation to model passenger flow in the airport terminal. Proceedings of the Applied Computing Conference. 2009.

Andreatta G, Brunetta L, Righi L, Jacur GR. Simulation vs. analitical models for the evaluation of an airport landside. http://www.aerohabitat.eu/uploads/media/25-01-2010_-_Simulation_vs_Analytical_models_-_Airport_side_Brunetta_Andreatta.pdf.

Adeke PT. Modelling of queuing process at airport check-in system: A case study of Manchester and Leeds-Bradford airports. Nigerian Journal of Technology (NIJOTECH). 2018;37(1). doi: 10.4314/njt.v37i1.5.

Nommik A, Antov D. Modelling regional airport terminal capacity. 16th Conference od Reliablity and Statitiscs in Transportation and Communication, RelStat 2016, 19-22 Oct. 2016, Riga, Latvia. 2016.

Adacher L, Flamini M, Guaita M, Romano E. A model to optimize the airport terminal departure operations. 20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 Sep. 2017, Budapest, Hungary. 2017. doi: 10.1016/j.proeng.2017.01.083.

Pivac J, Štimac I, Bračić M, Steiner S. Utjecaj razine kvalitete usluge na dimenzioniranje putničkog terminala zračne luke. Zbornik radova Kvaliteta – jučer, danas, sutra. 2020. p. 323–345. doi: 10.30657/hdmk.2020.20.

International Civil Aviation Organization (ICAO). Economic development. https://www.icao.int/sustainability/pages/low-cost-carriers.aspx [Accessed 5th May 2022].

Pandey MM. Evaluating the strategic design parameters of airports in Thailand to meet service expectations of low-cost airlines using the fuzzy-based QFD. Journal od Air Transport Management. 2020. doi: 10.1016/j.jairtraman.2019.101738.

Lawton T, Solomko, S. When being the lowest cost is not enough: Building a successful low fare airline business model in Asia. J. Air Transp. Manag. 2005;11: 355–362. doi: 10.1016/j.jairtraman.2005.03.001.

De Neufville R. Low-cost airports for low-cost airlines: Flexible design to manage the risks. Transp. Plan. Technol. 2008. doi: 10.1080/03081060701835688.

Wong JT, Liu TC. Development and application of an airport terminal simulation model. A case study of CSK Airport. Transportation Planning and Technology. 1998;22: 73–86. doi: 10.1080/03081069808717620.

Ballis A, Stathopoulos E, Sfakianaki E. Sizing of processing and holding air terminal facilities for charter passengers using simulation tools. International Journal of Transport Management. 2002.

Sabar R, Anuar NK, Abdullah R. Preferences of low-cost passengers, low cost airlines and airport management on Low Cost Terminal (LCT) facilities development model. International Journal of Supply Chain Management. 2018;7(6): 150–157.

Barrett SD. How do the demands for airport services differ between full-service carriers and low-cost carriers? Journal of Air Transport Management. 2004;10(1): 33–39. doi: 10.1016/j.jairtraman.2003.10.006.

Jain JL, Mohanty SG, Bohm W. A course on queuing models. New York: Chapman & Hall/CRC; 2007. doi: https://doi.org/10.1201/b15892.

Pavlin S. Aerodromi II - Planiranje aerodroma. Zagreb: Fakultet prometnih znanosti, Sveučilište u Zagrebu; 2014.

Brunetta L, Romanin-Jacur G. A flexible model for the evaluation of an airport terminal. Department of Pure and Applied Mathematics, University of Padova; 2001.

Caot Y, Nsakanda LA, Pressman I. A simulation study of the passenger check-in system at the Ottawa International Airport. SCSC; 2003.

Bulut E, Duru O, Huang ST. A multidimensional QFD design for the service quality assessment of Kansai International Airport, Japan. Total Qual. Manag. Bus. Excel. 2016;29(1–2): 202–224. doi: 10.1080/14783363.2016.1174058.

Pandey M, Singh D, Jayraj R, Damodaran K. Evaluating the success factors for development and sustenance of low-cost regional airports in India using fuzzy multi-criteria decision making method. Journal of Applied Economic Sciences. 2018;13(1): 89–100.

Sivrikaya O, Tunç E. Demand forecasting for domestic air transportation in Turkey. Open Transp. J. 2013;7: 20–26. doi: 10.2174/1874447820130508001.

Priyadarshana M, Fernando AS. Modeling air passenger demand in Bandaranaike international airport Sri Lanka. J. Bus. Econ. Policy. 2015;2(4): 146–151.

Alsumairi M, Tsui KWH. A case study: The impact of low-cost carriers on inbound tourism of Saudi Arabia. J. Air Transp. Manag. 2017;62: 129–145. doi: 10.1016/j.jairtraman.2017.04.001.

Srisaeng P, Baxter GS, Wild G. Forecasting demand for low cost carriers in Australia using an artificial neural network approach. Aviation. 2015;19(2): 90–103. doi: 10.3846/16487788.2015.1054157.

Srisaeng P, Baxter G, Richardson S, Wild G. A forecasting tool for predicting Australia’s domestic airline passenger demand using a genetic algorithm. J. Aerosp. Technol. Manag. 2015;7(4): 476–489. doi: 10.5028/jatm.v7i4/475.

El-Din MM, Farag M, Abouzeid A. Airline passenger forecasting in Egypt (domestic and international). Int. J. Comput. Appl. 2017;165(6): 1-5. doi: 10.5120/ijca2017913113.