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Passenger Level of Service Estimation Model for Queuing Systems at the Airport

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Passenger Level of Service Estimation Model for Queuing Systems at the Airport ARCHIVES OF TRANSPORT ISSN (print): 0866-9546 Volume 47, Issue 3, 2018 e-ISSN (online): 2300-8830 DOI: 10.5604/01.3001.0012.6505 PASSENGER LEVEL OF SERVICE ESTIMATION MODEL FOR QUEUING SYSTEMS AT THE AIRPORT Artur KIERZKOWSKI1, Tomasz KISIEL2, Maria PAWLAK3 1, 2, 3 Wroclaw University of Science and Technology, Faculty of Mechanical Engineering, Wroclaw, Poland Contact: 2) [email protected] (corresponding author) Abstract: This paper presents a model for the management of passenger service operations at airports by the estimation of a global index of the level of service. This paper presents a new approach to the scheduling of resources required to perform passenger service operations at airports. The approach takes into account the index of level of service as a quantitative indicator that can be associated with airport revenues. Taking this index into account makes it possible to create an operating schedule of desks, adapted to the intensity of checking-in passengers, and, as such, to apply dynamic process management. This offers positive aspects, particularly the possibility of improvement of service quality that directly translates into profits generated by the non-aeronautical activity of airports. When talking about level of service, there can be distinguish other important indicators that are considered very often (eg maximum queuing time, space in square meters). In this model, however, they are considered as secondary. Of course, space in square meters is important when designing a system. Here this system is already built and functioning. The concept of the model is the use of a hybrid method: computer simulation (Monte Carlo simulation) with multiple regression. This paper focuses on the presentation of a mathematical model used to determine the level of service index that provides new functionality in the current simulation model, as presented in the authors’ previous scientific publications. The mathematical model is based on a multiple regression function, taking into account the significance of individual elementary operations of passenger service at an air terminal. Key words: level of service, queuing system, airport, passenger service To cite this article: Kierzkowski, A., Kisiel, T., Pawlak, M., 2018. Passenger level of service estimation model for queuing systems at the airport. Archives of Transport, 47(3), 29-38. DOI: https://doi.org/10.5604/01.3001.0012.6505 Article is available in open access and licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) 30 Kierzkowski, A., Kisiel, T., Pawlak, M., Archives of Transport, 47(3), 29-38, 2018 1. Introduction vital from the process manager’s perspective. Creat- Airports are now expected to provide a high level of ing the right number of stations and counters to be service (LoS) to various customers. From the pas- used to perform individual passenger service opera- senger’s perspective, the most important aspect is tions makes it possible to have a considerable influ- not only the provision of a service to reach the des- ence on passengers’ waiting time in queuing sys- tination, but also the level of service. With this in tems. The aim of the paper was to develop a concept mind, improvement of the level of service at the air- model that would be suitable for analysing the influ- port has become a priority. However, the multiplic- ence of the operating schedule planning of service ity of airport services is the reason why the attain- desks in queuing systems on LoS index changes. ment of efficiency of measurements and analyses of The study involved computer simulations combined passenger perception is not easy. There are methods with a mathematical model based on a linear regres- that facilitate optimisation of the level of service. In sion and multiple regression models and using the practice, however, it is difficult to predict precisely least square method. So far, the research has been passengers’ responses. In order to avoid misinterpre- focused on the evaluation of the current condition of tation of a passenger’s impressions, Bezerra et al. service systems, whereas this paper is oriented to- (2016) proposed two solutions. The first one related wards predicting forthcoming operations in the as- to the adaptation of the measurement model for the pect of decisions to be made in the process of sched- perception of the level of quality based on a typical uling of resources. service provided in air transport. The other solution Addressing this subject is essential in the air was supposed to test the equivalence of the model transport process. The airport service evaluation re- between different passenger groups. In order to ver- port (CAPSE, 2016) concerning Asian airports un- ify correctness of the assumptions, example data ob- ambiguously shows that the level of passengers’ sat- tained a survey conducted in real-system circum- isfaction has been clearly decreasing for the last five stances. The results confirm the soundness of the years. At the same time, there are no analogous re- six-factor structure. The presented model is recog- ports relating to European airports. The significance nised as an alternative to the multidimensional ap- of passenger satisfaction resulting in profits gener- proach in the context of measuring the performance ated by non-aeronautical activity of an airport was of an airport with reference to the level of service. described in DKMA (2014). It was showed that an This is a very significant approach that justifies the evaluation increase by 0.1 on a five-point scale re- analysis of how a passenger terminal functions sults in an increase in the profits generated by non- within the LoS aspect. aviation activity by USD 0.8 per served passenger. For Correia et al. (Correia and Wirasinghe, 2007; The importance of cost management in air transport Correia et al., 2008), a general level of service con- has already been written (Jafernik and Sklorz, 2015; cerning passenger terminals is based on the proce- Jacyna-Gołda, 2015; Żak, 2004, Koucky, 2007; dure that consists in the observation of passengers Vintr, 2007) and acquisition of information that may affect pas- Subsequent passenger service operations performed sengers’ evaluation of the airport. This approach is in series are dependent processes (Kierzkowski and used to obtain quantitative evaluations based on the Kisiel, 2017, 2018). Thus, an appropriate model can survey data, whereas an analysis provides a relation- be used to develop an operating schedule so that the ship of quantitative evaluations and global indices. global index of passenger evaluation at the airport Correia et al. (Correia and Wirasinghe, 2007; Cor- assumes the highest value possible. reia et al., 2008) also determine the level of service at terminals based on users’ opinions. As a ground 2. Queuing systems at the airport for this concept, quantitative values are assigned to By adapting the notation applied in Malarski (2006), individual services with reference to tests conducted the passenger service operation can be expressed as at airports. An analysis showed that the most note- a graph adjusted for use in computer simulation worthy influence on the level of service is exerted modelling. The graph consists of elementary sub- by the following factors: queuing time, service time graphs that take into account an additional variable, and space availability. These are the factors that are on the basis of which it will be possible to determine a passenger’s waiting time in the queue. Hence, each Kierzkowski, A., Kisiel, T., Pawlak, M., 31 Archives of Transport, 47(3),29-38, 2018 elementary graph relates to a subsequent passenger γwe – variable describing random conditions of the service operation, taking into account these varia- duration of operation when the passenger enters the bles: terminal – the variable must assume (here determin- - ψ: variable describing random conditions of the istically) a value equal to 0 (Gwe –graph of an artifi- instant when the passenger appears for a ser- cial operation); vice operation; ξwe – variable describing the consequent of the oper- - γ: variable describing random conditions of the ation, where: time between the operation is started and the 0 - consequent Gwiz tasks included in the operation are finished; ξwe= {1 - consequent Gc-in - ξ: variable describing the consequent of the op- 2 - consequent Gkb eration. The passenger service operation may be completed we at the airport in different configurations. It depends G represents the operation of a passenger entering on the arrangement of individual zones in the air ter- the terminal – this is not a queuing system. However, a comprehensive approach to passenger service op- minal. Particular relevance is given to operations of we passport control (ID control) and safety control. For eration G was implemented demonstratively as an instance, safety control may be performed in a cen- artificial passenger service operation. tralised system. If this is the case, the safety control In the PO check-in process, there are different zone is located at the transition between the gener- check-in methods. However, one may generalise by ally-accessible zone and the departure lounge. At assuming that this is a binary operation. The passen- some airports, safety control takes place directly at ger checks in at the airport (independently of the the entrance to the gate or just in front of the gate. method: service station or counter, self-service ki- At most regional airports, there is a service operation osk, etc.) or the passenger has already completed together with a centralised system as well as pass- check-in before arriving at the passenger terminal. port control that takes place in the departure lounge. For passengers checking in, the operation can be ex- In such a case, the departure lounge is divided into pressed as the following elementary graph: the Schengen zone and a non-Schengen zone. Inde- c-in c-in c-in c-in pendently of the arrangement of individual elements G =(ψ ,γ ,ξ ) (2) of the passenger service system, the service opera- tions can be expressed in the form of basic elemen- where: tary graphs.
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