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A Cross Sectional Study of the Ten Longest Ultra-Long-Range Air Routes
(Sciendo, 2019-04-01) Glenn Baxter; Panarat Srisaeng; Graham Wild
In recent times, several airlines have commenced the operation of ultra-long-range (ULR) services. Using a mixed methods research approach, this paper examines the aircraft deployment, the target passenger market segments, the aircraft cabin configurations, the flight stage lengths and the available seat kilometres (ASKs) produced on the world's ten longest air routes. The study found that some airlines are operating ultra-long-range services on a hub-to-hub basis, whilst other airlines are operating these services to open new spoke city markets. The case airlines are targeting the premium and leisure travel market segments. The Boeing 787-9 is the most popular aircraft type for these services followed by the Airbus A380-800 and the Boeing B777-200LR aircraft. Qatar Airways Doha to Auckland service has the longest flight stage length (14,535 kilometres). The other 9 air routes all exceed 13,400 kilometres in length. The greatest number of annual ASKs are produced on the Emirates Dubai to Auckland services (5.09 billion ASKs) and the smallest number of annual ASKs are on the Qantas Airways Perth to London services (2.49 billion ASKs). © 2019 Transport and Telecommunication Institute, published by Sciendo.
A qualitative assessment of a full-service network airline sustainable energy management: The case of finnair plc
(World Scientific and Engineering Academy and Society, 2021) Panarat Srisaeng; Glenn Baxter; Graham Wild
-Airlines are extremely energy intensive. Around the world airlines are increasingly focusing on the environmentally sustainable energy management. Using a qualitative longitudinal case study research approach, this study examines Finnair’s sustainable energy management over the period 2010 to 2019. The airline’s major energy source is jet fuel used for the operation of the airline’s aircraft fleet and the electricity which is used to power its facilities located at Helsinki Airport. The study found that Finnair’s annual jet fuel consumption has grown throughout the study due to the airline’s route network and aircraft fleet expansion. The fuel required for ground vehicles has risen reflecting greater operational requirements due to the company’s expansion. The annual consumption of electricity and electricity for heating has displayed a general downward trend during the study period. The annual electricity per passenger has also decreased despite the large growth in passenger numbers. Finnair has increased its use of renewable energy sources for its flight and ground operations. A key energy saving strategy has been the acquisition and operation of a modern state-of-the-art, fuel efficient aircraft fleet. © 2021, World Scientific and Engineering Academy and Society. All rights reserved.
A Study of government owned airport’s service quality: The case of Hua Hin Airport
(โรงเรียนการท่องเที่ยวและการบริการ มหาวิทยาลัยสวนดุสิต, 2019-06-30) Parleda Sampaothong; Neeyakarn Limaroon; Kwanrat Jansirinara
The purposes of this study was to study the satisfaction level of passengers towards the service quality of Hua Hin Airport by using SERVQUAL instrument to analyse the GAP of passenger expectation and perception. The researchers aim to use the outcome of this study for further preparation for the readiness of Hua Hin Airport in the direction of service quality. This study was quantitative research with survey by distributing “Satisfaction Survey” Questionnaire to 180-sample population. The questionnaire focuses on the analysis of SERVQUAL with 5 dimensions of Tangibility, Reliability, Responsiveness, Assurance and Empathy. The results of study were as follows; (1) There were no significant differences between passenger expectation and perception toward Hua Hun Airport service quality. (2) Tangibility is the most sensitive factor toward passenger expectation. (3) Empathy is the number one satisfaction that passengers considered on Hua Hin Airport service quality. (4) Shopping & dinning area, Ground transportation options and Flight Information screens around terminal areas were indicated as the most urgent issues for improvement from the Gap Analysis. (5) There were some parts of SERVQUAL and Gap Analysis demonstrated that Hua Hin Airport performance obtained perception over expectation. Those areas were on some parts of Tangibility, Responsiveness, Assurance and all part of Empathy
A Study of Thai Massage Service Quality Effect on International Tourist Confidence
(University of Primorska, 2023-12-27) Napaporn Janchai; Glenn Baxter; Panarat Srisaeng
Wellness tourism is one of the world’s fastest growing industries (Global Wellness Institute, 2018). Wellness tourism has developed into a very important tourism market segment around the world over the past two decades or so. This is especially so for Thailand, where wellness tourism has become one of country’s most important tourism markets. In addition to attracting high-end tourists from developed and developing countries, wellness tourism also increases the economy of small or developing countries (Jagyasi, 2022). Thai massage has a strong link to wellness tourism as it is a key service for wellness tourism. In terms of the massage business, tourist confidence is the perception of service quality that influences a purchase decision. Service quality and tourist confidence are intertwined, which then leads to income and economic development. Therefore, examining service quality within Thai massage in relation to tourist confidence is important for exploring the crucial factors influencing international tourist confidence in Thai massage. The results of this research may lead to service quality development to encourage confidence among international tourists who are a significant source of foreign revenue. This research aims to examine the effect of Thai massage service quality on international tourist confidence. A survey of 400 international tourists was conducted in Bangkok, Thailand between March and May 2019, using a structured research questionnaire to collect all necessary data, which was then used to test the research hypotheses using multiple regression analysis. The study concluded that three out of five elements of service quality affect international tourist confidence. These elements include ‘Empathy,’ ‘Tangibility,’ and ‘Responsiveness,’ while ‘Assurance’ and ‘Reliability’ did not have a significant effect on tourist confidence. The findings of this research establish an empirical relationship between empathy, tangibility and responsiveness of Thai massage businesses and international tourists’ confidence. This insight of the study may help the massage business to have a better understanding about the elements of service quality that influence international tourist confidence. © 2023 University of Primorska. All rights reserved.
Airport Related Emissions and their Impact on Air Quality at a Major Japanese Airport: The Case of Kansai International Airport
(Sciendo, 2020-04-01) Glenn Baxter; Panarat Srisaeng; Graham Wild
The objective of this study was to investigate the carbon dioxide (CO2) emissions of an airport, to determine if strategies are helping to achieve sustainability targets. Kansai International Airport was selected as the case study, and it is Japan's third largest airport and there was readily available comprehensive data to enable a study to be undertaken. The airport has a dedicated environmental division and has implemented various initiatives over the past decade or so to reduce the airport's impact on the surrounding environment, especially since it is in Osaka Bay. The research used an exploratory design, with an initial qualitative case study, followed by a quantitative longitudinal study, utilizing correlation to assess trends over time. Results showed statistically significant reductions in carbon dioxide (CO2) emission from the three facets of airport operations, both in terms of the number of passengers and number of aircraft serviced by the airport. As a result, the initiatives undertaken at Kansai International Airport could be adapted and used by other airports to help reduce their carbon dioxide emissions. © 2020 Glenn Baxter et al., published by Sciendo.
An adaptive neuro-fuzzy inference system for forecasting Australia's domestic low cost carrier passenger demand
(Taylor and Francis Ltd., 2015-07-03) Panarat Srisaeng; Glenn Baxter; Graham Wild
This study has proposed and empirically tested two Adaptive Neuro-Fuzzy Inference System (ANFIS) models for the first time for predicting Australia's domestic low cost carriers demand, as measured by enplaned passengers (PAX Model) and revenue passenger kilometres performed (RPKs Model). In the ANFIS, both the learning capabilities of an artificial neural network (ANN) and the reasoning capabilities of fuzzy logic are combined to provide enhanced prediction capabilities, as compared to using a single methodology. Sugeno fuzzy rules were used in the ANFIS structure and the Gaussian membership function and linear membership functions were also developed. The hybrid learning algorithm and the subtractive clustering partition method were used to generate the optimum ANFIS models. Data was normalized in order to increase the model's training performance. The results found that the mean absolute percentage error (MAPE) for the overall data set of the PAX and RPKs models was 1.52% and 1.17%, respectively. The highest R2-value for the PAX model was 0.9949 and 0.9953 for the RPKs model, demonstrating that the models have high predictive capabilities. © 2015 Vilnius Gediminas Technical University (VGTU) Press.
An assessment of airport sustainability, part 1-waste management at Copenhagen Airport
(MDPI AG, 2018-03-01) Glenn Baxter; Panarat Srisaeng; Graham Wild
Airports play a vital role in the air transport industry value chain, acting as the interface point between the air and surface transport modes. However, substantial volumes of waste are produced as a by-product of the actors' operations. Waste management is therefore becoming especially important to airports. Using a qualitative and quantitative case study research approach, this paper has examined the waste management strategies and systems at Copenhagen Airport, Scandinavia's major air traffic hub, from 1999 to 2016. The two major sources of waste at Copenhagen Airport are the waste generated from aircraft serving the airport and the waste arising from ground activities undertaken in the land and airside precincts. The growth in passengers and aircraft movements has had a concomitant impact on the volume of waste generated. Swept waste and sludge are processed by an external provider. Waste generated in the passenger terminals and the airport operator's facilities is handled at a central container station, where it is sorted for incineration, recycling or for landfill. The environmental impact of the waste produced at the airport is mitigated through the recycling of waste wherever possible. © 2018 by the authors.
An Assessment of Airport Sustainability, Part 2—Energy Management at Copenhagen Airport
(MDPI AG, 2018-06-01) Glenn Baxter; Panarat Srisaeng; Graham Wild
Airports play a critical role in the air transport value chain. Each air transport value chain stakeholder requires energy to conduct their operations. Airports are extremely energy intensive. Greenhouse gases are a by-product from energy generation and usage. Consequently, airports are increasingly trying to sustainably manage their energy requirements as part of their environmental policies and strategies. This study used an exploratory qualitative and quantitative case study research approach to empirically examine Copenhagen Airport, Scandinavia's major air traffic hub, sustainable airport energy management practices and energy-saving initiatives. For Copenhagen Airport, the most significant environmental impact factors occurring from energy usage are the CO2 emissions arising from both the air side and land side operations. Considering this, the airport has identified many ways to manage and mitigate the environmental impact from energy consumption on both the air and land side operations. Importantly, the application of technological solutions, systems and process enhancements and collaboration with key stakeholders has contributed to the airport's success in mitigating the environmental impact from energy usage at the airport whilst at the same time achieving energy savings. © 2018 by the authors.
An assessment of airport sustainability: Part 3-water management at Copenhagen Airport
(MDPI AG, 2019-09-01) Glenn Baxter; Panarat Srisaeng; Graham Wild
Sustainable water management is critical for airports as they consume substantial volumes of water to maintain their infrastructure and operations. Airports also generate large volumes of surface and waste waters. The aim of this study was to examine Copenhagen Airport's sustainable water management strategies and systems from 2006 to 2016. The study used a longitudinal qualitative research design. The annual water consumption at Copenhagen Airport has risen from 2006 to 2016 in line with the increased passenger volumes and aircraft movements. Drinking water is sourced from the Taarnby and Dragør municipal water works. Non-potable water is used wherever possible and is sourced from a local remedial drilling. Copenhagen Airport uses two separate sewer systems for handling surface and wastewater. These waters are not discharged to same system due to their different nature. To mitigate environmental risks and impacts on soil, water, and local communities; the quality of drinking, ground, and surface water are regularly monitored. The airport has implemented various water saving initiatives, such as, an aquifer thermal energy system, to reduce water consumption. The strategies, systems, and the water-saving initiatives have successfully underpinned Copenhagen Airport's sustainable water management. © 2019 by the authors.
An assessment of sustainable airport water management: The case of Osaka’s Kansai international airport
(MDPI Multidisciplinary Digital Publishing Institute, 2018) Glenn Baxter; Panarat Srisaeng; Graham Wild
Airports are an essential infrastructure to facilitate aviation. The substantial growth of aviation has led to a significant increase in water usage by airports. Airports also generate large volumes of wastewater that may include contaminants. Hence, understanding sustainable water management practices is essential in the aviation industry. In this study, an exploratory research design was utilized in the examination of the sustainable water management strategies and systems at Kansai International Airport from 2002 to 2016. The qualitative data were examined using document analysis as part of a case study. The quantitative data were analyzed using regression analysis as part of a longitudinal study. The airport has been able to reduce the total water consumption, water consumption per passenger, and water consumption per aircraft movement, even with increased traffic in recent years. The airport sources water from the municipal authorities and reclaims water for non-potable water uses. The airport conducts regular water quality tests which measure the Chemical oxygen demand, total nitrogen, and total phosphates. The airport’s onsite wastewater processing centre processes all wastewaters, which discharges non-reclaimed water into Osaka Bay. With a decrease in water consumption, there has similarly been a decrease in the need to treat wastewater, while the reclaimed water ratio has increased over the period of the study. © 2018 by the authors.
Cooperating to compete in the global air cargo industry: The case of the DHL Express and Lufthansa cargo A.G. Joint venture airline ‘Aerologic’
(MDPI Multidisciplinary Digital Publishing Institute, 2018-03-16) Glenn Baxter; Panarat Srisaeng
This paper presents a case study of the DHL Express and Lufthansa Cargo strategic joint venture cargo airline ‘AeroLogic’, the global air cargo industry’s largest operative joint venture between an airline and a leading international express and logistics provider. The study used a qualitative research approach. The data gathered for the study was examined by document analysis. The strategic analysis of the AeroLogic joint venture was based on the use of Porter’s Five Forces framework. The study found that the AeroLogic joint venture airline has provided synergistic benefits to both partners and has allowed the partners to access new markets and to participate in the evolution of the air cargo industry. The new venture has also enabled both joint venture partners to enhance their competitive position in the global air cargo industry through strengthened service offerings and has provided the partners with increased cargo capacities, a larger route network, and greater frequencies within their own route networks. The study also found that the AeroLogic business model is unique in the air cargo industry. A limitation of the study was that AeroLogic’s annual revenue or freight traffic data was not available. It was, therefore, not possible to analyse the business performance of the joint venture. © 2018 by the authors
Environmentally Sustainable Airline Waste Management: The Case of Finnair PLC
(Kauno Technologijos Universitetas, 2021-12-09) Glenn Baxter; Panarat Srisaeng; Graham Wild
Airlines around the world are increasingly focusing on the environmentally sustainable management of wastes produced as a by-product of their operations. The objective of this work was to analyze Finnair’s non-hazardous waste (NHW) types and quantities, their NHW management strategies, and the methods used to mitigate the environmental impact of their NHW, over the period 2008 to 2019. To achieve these objectives, the study was underpinned by an in-depth mixed methods research design; this incorporated a quantitative longitudinal study and a qualitative document analysis. The results revealed that despite significant growth of their operations, Finnair’s annual NHWs have declined over the study period. Finnair’s annual NHWs decreased from 5,710 tonnes in 2008 to 4,212.01 tonnes in 2019. The primary waste disposal methods used by the airline are waste-to-energy recovery and waste recycling, both in-house and by external third-party service providers. Smaller quantities of wastes are composted. Since 2015, the company has had a policy of not disposing wastes to landfill. © 2021, Kauno Technologijos Universitetas. All rights reserved.
Estimating a Regional Airport Air Passenger Demand Using an Artificial Neural Network Approach: The Case of Huahin Airport, Thailand
(LAMBERT Academic Pubishing, 2022-03-20) Panarat Srisaeng; Glenn Baxter; Parleda Sampaothong
Abstract: Artificial neural networks (ANNs) are a promising modelling approach for predicting an airport’s air passenger demand. The study proposed and empirically tested an artificial neural network model to predict the annual passenger demand for Huahin Airport, a regional and tourist focused airport located in Thailand. The ANN input variables included Thailand’s population size, Thailand’s real GDP, world jet fuel prices, Thailand total passengers carried, Thailand’s tourist numbers and Thailand’s unemployment rates. The data were trained using the Levenberg-Marquandt back-propagation algorithm. The ANN comprises eight neurons in the hidden layer and one neuron in the output layer. 80 per cent of the data was used in the training phase with the remaining data divided into validation (10 per cent) and testing (10 per cent) phases. The proposed ANN provided very accurate prediction values. The coefficient of determination R value of model was around 0.995, and the mean absolute percentage error (MAPE) of the final ANN model was 13.27%. The study found that the four key determinants of Huahin Airport annual air passenger demand were Thailand population size, the commencement of AirAsia services at Huahin Airport, Thailand’s tourist numbers, and Thailand’s real GDP.
Forecasting demand for low cost carriers in Australia using an artificial neural network approach
(Taylor and Francis Ltd., 2015-03-23) Panarat Srisaeng; Glenn S. Baxter; Graham Wide
This study focuses on predicting Australia’s low cost carrier passenger demand and revenue passenger kilometres performed (RPKs) using traditional econometric and artificial neural network (ANN) modelling methods. For model development, Australia’s real GDP, real GDP per capita, air fares, Australia’s population and unemployment, tourism (bed spaces) and 4 dummy variables, utilizing quarterly data obtained between 2002 and 2012, were selected as model parameters. The neural network used multi-layer perceptron (MLP) architecture that compromised a mul ti-layer feed-forward network and the sigmoid and linear functions were used as activation functions with the feed forward‐back propagation algorithm. The ANN was applied during training, testing and validation and had 11 inputs, 9 neurons in the hidden layers and 1 neuron in the output layer. When comparing the predictive accuracy of the two techniques, the ANNs provided the best prediction and showed that the performance of the ANN model was better than that of the traditional multiple linear regression (MLR) approach. The highest R-value for the enplaned passengers ANN was around 0.996 and for the RPKs ANN was round 0.998, respectively. Keywords: air transport, artificial neural network (ann), Australia, forecasting methods, low-cost carrier.
Machine Learning for Air Transport Planning and Management
(American Institute of Aeronautics and Astronautics Inc, AIAA, 2022) Graham Wild; Glenn Baxter; Panarat Srisaeng; Steven Richardson
In this work we compare the performance of several machine learning algorithms applied to the problem of modelling air transport demand. Forecasting in the air transport industry is an essential part of planning and managing because of the economic and financial aspects of the industry. The traditional approach used in airline operations as specified by the International Civil Aviation Organization is the use of a multiple linear regression (MLR) model, utilizing cost variables and economic factors. Here, the performance of models utilizing an artificial neural network (ANN), an adaptive neuro-fuzzy inference system (ANFIS), a genetic algorithm, a support vector machine, and a regression tree are compared to MLR. The ANN and ANFIS had the best performance in terms of the lowest mean squared error. © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
Predicting Australia’s Domestic Airline Passenger Demand using an Anfis Approach
(Sciendo, 2022-04-30) Panarat Srisaeng; Glenn Baxter
The forecasting of future airline passenger demand is critical task for airline management. The objective of the present study was to develop an adaptive neuro-fuzzy inference system (ANFIS) for predicting Australia's domestic airline passenger demand. The ANFIS model was trained, tested, and validated in the study. Sugeno fuzzy rules were used in the ANFIS structure and Gaussian membership function, and linear membership functions were also developed. The hybrid learning algorithm and the subtractive clustering partition method were used to generate the optimum ANFIS models. The results found that the mean absolute percentage error (MAPE) for the overall data set of the ANFIS model was 3.25% demonstrating that the ANFIS model has high predictive capabilities. The ANFIS model could be used in other domestic air travel markets. © 2022 Panarat Srisaeng et al., published by Sciendo.
Self-Drive Tourism: Unlocking the Potential of the Thailand Riviera
(2024-11-25) Parleda Sampaothong; Narin Sungraksa; Kwanrat Jansirinara; Thapana Tangjui; Panarat Srisaeng; Neeyakarn Limaroon
The Thailand Riviera is a key element in the government's strategic plan to boost the nation's economy through targeted tourism development initiatives. Despite its natural beauty and numerous attractions, awareness of the region remains limited, suggesting the need for enhanced promotional efforts. This study aims to develop a proactive marketing and public relations model to promote tourism in the Thailand Riviera, with a focus on self-drive tourism as a case study. A mixedmethods approach was employed, including a survey of 400 tourists to examine their behaviors and perceptions of the Thailand Riviera, as well as in-depth interviews with 24 key informants, including tourists,government officials, and tourism professionals. The EDFR research method was applied to establish a proactive marketing and public relations model, incorporating the insights of 17 experts. A qualitative approach was used to test and verify the proposed self-drive tourism model. The findings suggest that the marketing and tourism promotion strategy for the Thailand Riviera should emphasize self-drive tourism and highlight a distinctive regional identity in alignment with provincial tourism policies under the Thailand Riviera brand. To build brand awareness, mascot marketing should be implemented, positioning the mascot as a tourism ambassador. The proposed self-drive tourism model includes the Thailand Riviera Self-Drive Salt Route in Phetchaburi, connected to the Thailand Riviera Self-Drive Coastal Route in Prachuap Khiri Khan, with community-based tourism activities along the scenic routes. This form of tourism has the potential to reach remote areas, promoting income distribution within local communities and contributing to national economic growth. Overall, this study provides valuable insights into the potential of self-drive tourism as a key driver for promoting tourism in the Thailand Riviera.
Sport Day "Flight Fest 2025 : Reunion on the Runway
(มหาวิทยาลัยสวนดุสิต ศูนย์การศึกษา หัวหิน, 2025-03-30) มหาวิทยาลัยสวนดุสิต ศูนย์การศึกษา หัวหิน
Sustainable airport waste management: The case of Kansai international airport
(MDPI AG, 2018) Glenn Baxter; Panarat Srisaeng; Graham Wild
The global air transport industry is predicted to continue its rapid growth. A by-product of air transport operations, however, is the substantial volumes of waste generated at airports. To mitigate the environmental impact of waste and to comply with regulatory requirements, airports are increasingly implementing sustainable waste management policies and systems. Using an in-depth case study research design, this study has examined waste management at Kansai International Airport from 2002 to 2015. Throughout its history the airport has implemented world best practices to achieve its goal of being an eco-friendly airport. The qualitative data gathered for the study were analysed using document analysis. The quantitative data were analysed using t-tests. Statistically significant results were found in the reduction in waste per passenger and aircraft movement (for total waste, incinerated waste, and landfill waste). In addition, a statistically significant increase in the proportion of waste recycled, and a decrease in the proportion of waste sent to landfill was observed. As such, quantitatively speaking, Kansai International Airport has shown significant waste management improvements. The study concludes that Kansai Airport’s waste management approaches and policies can be transferred to other airport facilities. This would greatly improve sustainability across airports, globally. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
The air cargo carrying potential of the Airbus A350-900xWB and Boeing 787-9 aircraft on their ultra-long-haul flights: A case study for flights from San Francisco to Singapore
(Sciendo, 2018) Glenn Baxter; Panarat Srisaeng; Graham Wild
The introduction of the Airbus A350-900 (A359) and the Boeing B787-9 (B789) have enabled airlines to operate ultra-long-range services. Using a mixed methods research design, this study has examined the air cargo-carrying potential of Singapore Airlines Airbus A350-900XWB (A359) and United Airlines Boeing B787-9 (789) aircraft on their ultra-long-haul San Francisco to Singapore and the Singapore to San Francisco air routes. The qualitative data was analysed using document analysis, and the air cargo payload was modelled by simulation. The air cargo-carrying potential of the two aircraft types was significantly influenced by enroute weather. In the event of eastbound winds, the Singapore Airlines Airbus A350-900XWB air cargo payload was 16.9 tonnes and the United Airlines Boeing 787-9 was 11.5 tonnes, when these flights had a full passenger payload. In the case of westbound winds with a full passenger payload, the Singapore Airlines Airbus A350-900XWB air cargo payload was 13.1 tonnes and the United Airlines Boeing 787-9 was 7.9 tonnes. When there were no winds on the air routes, the Singapore Airlines Airbus A350-900XWB offered 15.0 tonnes and the United Airline Boeing 787-9 offered 9.7 tonnes of air cargo payload, respectively. © 2018 Sciendo. All Rights Reserved.

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