Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework

Suryani, Erma; Chou, Shuo‐Yan; Chen, Chih-Hsien

doi:10.1016/j.eswa.2009.07.041

Cited by 169 publications

(90 citation statements)

References 13 publications

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“…Furthermore, an airport can change the amount of subsidies monthly or quarterly. To integrate these different decision time scales, this paper introduced a stock and flow modeling of SD (which represents physical and information flows), based on information feedback controls that are continuously converted into decisions and actions (Suryani et al, 2010). It is assumed that the demand control decisions are made by both parties monthly and the results are accumulated in a stock for deciding the following year's target load factor.…”

Section: Methodsmentioning

confidence: 99%

Dynamically interdependent business model for airline–airport coexistence

Minato

Morimoto

2017

Journal of Air Transport Management

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Governments provide various forms of financial support for sustaining unprofitable regional airways, especially when such airways are essential to local livelihoods and economies. However, inefficient provision of subsidies has been subject to worldwide criticism. Therefore, this study examines the load factor guarantee, a dynamically interdependent business model for airline-airport coexistence where an airline and an airport agree on the load factor of a flight, after which either party compensates for any discrepancies between the actual and agreed-upon load factor. The model is calibrated by using 2003-2014 data regarding Noto Airport and All Nippon Airways, and system dynamics are employed to model the dynamic interactions between the two parties. The findings show that successful coexistence between an airline and an airport hinges on the integral management of annual negotiations regarding the target load factor and the monthly demand adjustment of subsidies. In addition, although a subsidy represents a temporary financial loss for an airport, it is an effective way of maintaining long-term, airline-airport coexistence. This model is applicable to unprofitable airways worldwide, and it contributes to their sustainable management.

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Section: Methodsmentioning

confidence: 99%

Dynamically interdependent business model for airline–airport coexistence

Minato

Morimoto

2017

Journal of Air Transport Management

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“…Vensim [8,9] is utilized to build and simulate the system dynamics evaluation model in this paper. By change parameters, Vensim can give comparison simulation results easily.…”

Section: Simulationsmentioning

confidence: 99%

A System Dynamics Evaluation Model of Avionic Fuel Control System

Zhao¹,

Sun²,

Zhou³

et al. 2014

Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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Abstract-Avionics fuel control system, which is applied for delivering fuel to an engine in modern aircraft system, is difficult to study, design, and implement due to the highsecurity measures and the need for standard certification.To evaluate the complex dynamics involved in implementing fuel regulating for aircraft fuel system, a quantifiable evaluation model for avionics fuel control system based on system dynamics theory is developed in this paper. Firstly, the speed and flow regulation process is briefly introduced in an avionics fuel control system. Then, based on these operation principles, the analytic relations among the system state variables are provided, which come into being the system dynamics evaluation model. According to these analytic relations, the evalutation model is realized and simulated using Vensim tool. The simulation result shows that this model can be used efficiently in modeling and evaluating of avionic fuel control system for its clear causality, suitable complexity, and exact describe characteristics.

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“…Tako and Robinson [35] state that there is a widely-held belief that SD is used mostly to model problems at a strategic level. Suryani et al [32,33] argue that the main characteristics of SD are the existence of a complex system, the change of system behaviour from time to time, and the existence of the closed feedback loop.…”

Section: Introductionmentioning

confidence: 99%

“…SD is used as a modelling tool because of its rigorous approach in capturing inter-relationships among variables, and in handling dynamic aspects of the system's behaviour [29]. Suryani et al [32,33] mention that SD is used to model and to generate scenarios for forecasting demand and evaluating policy scenarios, enabling us to understand the nonlinear dynamics of behaviour under uncertain conditions. SD, initially developed by Forrester [15], is a method for qualitatively describing and analysing complex systems, and quantitatively simulating system behaviour.…”

Section: Introductionmentioning

confidence: 99%

“…Lyneis [26] developed an SD model to forecast the demand of commercial jets in the aircraft industry. Suryani et al [32] developed an SD model to analyse and forecast future air passenger demand, based on the capacity of runways and passenger terminals, in order to support long-term growth. While the demand for air travel is difficult to forecast, it is important to use SD [26].…”

Section: Introductionmentioning

confidence: 99%

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Application of a System Dynamics Model to Improve the Performance of Make-to-Order Production

Ho¹

2015

sajie

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This study provides a system dynamics (SD) model of make-to-order (MTO) production and discusses the key factors of production improvement. The proposed system can be divided into three subsystems: income/cost, order/production, and human resources (HR). The time delay between customer demand, production demand, order quantity, material demand, and inventory is considered in a practical application. In addition, this paper considers how the cycle time is affected by the total input of HR; how unit transportation cost is influenced by the delivery quantity; and how unit penalty (shortage) cost is affected by the amount of shortage. The production capacity, yield, and holding cost needed to satisfy practical demands are all considered. A simulation approach to MTO production for meeting contract requests is presented in this study. Simulation results reveal that the amount of shortage will be the most important factor affecting the policy for the replenishment of material. Although the rise in production capacity leads to a reduced amount of shortage, it does not play a significant role. A sensitivity analysis of the replenishment of material policy is conducted to find out the best suggested policy. The SD model is also shown to quickly simulate changes in system behaviour, which allows an organisation enough time to respond to and conquer any unpredictable situation that might occur. OPSOMMING'n Stelseldinamika model van 'n vervaardig-op-bestelling proses word gestel en die sleutelfaktore vir proses verbetering word bespreek. Die voorgestelde sisteem kan in drie subsisteme verdeel word, naamlik inkomste/koste, bestelling/produksie en menslike hulpbronne. Die tydsverloop tussen die kliëntevereiste, produksievereiste, bestelling hoeveelheid, materiaalvereiste en voorraad word in 'n praktiese toepassing oorweeg. Verder word daar gekyk na hoe die siklustyd affekteer word deur die menslike hulpbron insette, hoe eenheidsvervoerkoste deur afleweringshoeveelheid beïnvloed word en hoe eenheidstekortkoste deur die hoeveelheid stoorspasie beïnvloed word. Die produksiekapasiteit, -opbrengs en bergkoste benodig om praktiese vereistes te bevredig word oorweeg. A simulasie gebaseerde benadering tot vervaardig-op-bestelling produksie word voorgehou. Die simulasie resultate toon dat die tekort die belangrikste faktor is wat die materiaalvervangingsbeleid beïnvloed. Alhoewel verhoogde produksiekapasiteit tot 'n verminderde tekort lei, speel dit nie 'n beduidende rol nie. 'n Sensitiwiteitsanalise van die materiaalvervangingsbeleid is gedoen om die beste beleid voor te stel. Die stelseldinamika model word ook gebruik om vinnig veranderinge in die stelselgedrag te simuleer -dit gee 'n organisasie genoeg tyd om op onvoorspelde situasies wat hulself voor doen te reageer en te oorkom.

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Air passenger demand forecasting and passenger terminal capacity expansion: A system dynamics framework

Cited by 169 publications

References 13 publications

Dynamically interdependent business model for airline–airport coexistence

Dynamically interdependent business model for airline–airport coexistence

A System Dynamics Evaluation Model of Avionic Fuel Control System

Application of a System Dynamics Model to Improve the Performance of Make-to-Order Production

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