Gravitational force exerted by Brazilian tourist destinations on foreign air travelers

This article analyses the context of international tourist flows by air and tourism in Brazil, by applying the principles of the gravity model. The study includes 13 Brazilian international airports that served 108 origin-destination pairs, which accounted for 80.14% of the total tourist flows by air in 2012. In the statistical analysis applied, the dependent variable Ft is the tourist flow between the country of origin and the Brazilian state of destination. To approximate an explanatory equation, we formulated a linear function that was able to support, in 31.7% of the cases, the dependence of the international tourist flows with the variables considered in the linear regression performed. The conclusion is that the assumptions considered in this study only partially explain the gravitational force exerted by Brazilian tourist destinations, so there is a need to refine the model by including other variables that can influence the flows by air of international tourists.     

Airport classification based on cargo characteristics

Air cargo has received little attention in airport research. In this paper, 114 airports are grouped according to their cargo business characteristics. Applying a hierarchical cluster analysis, the paper uses absolute (cargo tonnage) and relative measures (share of cargo work load units, of freighter movements and of international cargo) to establish the reliance of different airport types and groupings on air cargo. Eight distinct clusters are identified which show clear differences in the characteristics of the sample with regard to cargo activities. Geographic patterns of these airports are also revealed. For example, North American and European airports are characterised by features unique to these regions. Airports that are highly dependent on air cargo tend to benefit from a central location within networks of cargo airlines, while other airports with high cargo volumes generate these as a result of significant belly-capacity of passenger operations. Understanding the heterogeneity of cargo airports is important for future benchmarking studies in this field.     

International air network structures and air traffic density of world cities

This paper examines international air passenger and cargo flows within and among Asia, Europe, and America, and the degree of air traffic density for major cities worldwide, using a basic gravity model composed of GDP, population, distance, and several dummy variables. The results reveal that many cities are strengthening their position as international air transportation hubs, especially: Tokyo, Hong Kong, Singapore, London, Paris, Frankfurt, Amsterdam, New York, and Miami. Finally, the results show that the air traffic density of three cities, Seoul, Hong Kong, and Amsterdam, is growing at an extraordinary rate.     

The impact of national macro-environment exogenous variables on airport efficiency

Our paper tests the extent to which airport efficiency is affected by national macro-environmental factors. The literature on airport performance measurement is extensive but has tended to focus mainly on estimating the effects on efficiency from what are mostly endogenous variables. We undertake a two-stage analysis of 59 international airports observations in the Europe and Asia-Pacific regions. The first stage involves the use of Data Envelopment Analysis (DEA) to measure the efficiency of these airports. This is followed by a second stage, where we use a Truncated Regression model that incorporates the Simar and Wilson bootstrapping technique to test the extent to which a set of macro-environmental factors affect airport efficiency. Results reveal that a state's air transport sector output, institutional quality and robustness, the macro-economic environment, safety and security, and human development, all have a significant influence on the performance of airports. The result of this study fills the gap in the literature related to the non-discretionary variables affecting the performance of airports. It also suggests that policymakers and airport managers consider the identified factors when benchmarking airports.     

Responses of air cargo carriers to industrial changes

This study examines how product characteristics, values, inventory cost, shipping charges, shipping distance, and time affect an international firm's choice of air carrier. An individual choice model is constructed by assuming that the shipper in a specific industry chooses the optimal air cargo carrier with the minimal logistics cost. The study further aggregates air cargo demands on different routes for the carriers by considering the spatial distribution of the origin-destination pattern and any temporal changes in the industrial structure. A case study is used to illustrate the application of the proposed model using data from Taiwan Taoyuan International Airport and the industrial economics database in Taiwan. The results show that shippers with high product value and short delivery distance focus on the shipping charge and prefer choosing the air cargo carrier that offers more flights. Further a carrier may achieve a larger market share if its supply attributes match the industrial structure and the product characteristics of the market on the route. Finally, because dynamic changes in the industrial structure and product value have been captured, the results are more accurate than that from the Grey model.     

Measuring connectivity in the air freight industry

In this paper, we present an air transport connectivity model for air freight. For the purposes of this paper, connectivity is defined as all possible direct and indirect connections to or from an airport operated by wide-body aircraft, weighted for the quality of the connection in terms of transhipment and in-flight times. Using this model, we analyse the networks of seven European airports. Europe’s largest hub airports carry most air freight thanks to their extensive intercontinental passenger networks, while smaller airports with a strong focus on air freight carry large amounts of cargo on dedicated freighter aircraft. For air freight operations, the catchment area of an airport is much larger than it is for passenger services, as shipments are being trucked to their departure airport throughout all of mainland Europe. Since there are many airports sharing the same catchment area, potential competition for air freight is fierce. We found that well located regions between the four large European airports have access to large air freight networks, whilst regional air freight connectivity in northern and southern parts of Europe is substantially lower.     

Efficiencies and scope economies of Chinese airports in moving passengers and cargo

The paper looks at the technical efficiency of Chinese airports using multi-output stochastic input distance function analysis. This method provides a statistical test of scope economies to investigate the contribution of air cargo transport to airport efficiency. Our findings confirm the presence of scope economies in air passenger and air cargo transport among airports in China. We compare and contrast these results with results obtained from single-output stochastic production frontier analysis in which the effect of scope economies is not included. Our results indicate that the presence of scope economies significantly affects the estimation of technical efficiency, thus implying different efficiency rankings among airports in China.     

Determinants of Brazilian international flights: The role of hub-and-spoke and infrastructure variables

The objective of this study is to evaluate the determining factors influencing airline companies to operate international origin-destination (O-D) routes from different Brazilian airports. The results are based on a panel data model and support the assumption that statistically significant explanatory variables stem from gravity factors (GDP and an airport competition measure weighted by distance), hub-and-spoke variables and capacity inputs. We find that a composite variable made up by the airport capacity variables – given by the size of the terminal building and the length of runways – and its domestic connections have a positive effect on airport competitiveness. In conclusion, we find that not only well-known demand-side factors, but also supply-side variables – strategic decisions taken by airport management – matter in attracting international flights.     

A time–space network model for unit load device stock planning in international airline services

Unit load devices (pallets, containers, etc.) are used to move luggage and air cargo on wide-bodied aircraft. This paper examines a case study of the number of devices needed by an airline for international scheduled services. Unit load device movements between airports require planes to load and deliver. The stock of the unit load devices is thus influenced by the airline’s scheduled services. Based on a recurring weekly schedule, this study develops a time–space network to formulate mathematical programming models for minimizing device quantities. This model is applied to assess the preparation level of unit load devices for the various service networks for a Taiwanese airline.     

The opening of direct flights across the Taiwan Strait: the impact on the global role of Taiwan’s international airport

Scheduled direct flights between Taiwan and Mainland China were halted for six decades and restarted in December 2008. The Taiwan’s government has a policy of developing Taoyuan International Airport (TPE), the major international airport in Taiwan, as one of main hubs in East Asia, based on the airport’s access to Mainland China. To assess whether the airport is progressing toward meeting the set expectation, this study evaluates the changes in airline networks of the TPE after the opening of direct flights across the Taiwan Strait. The time-dependent earliest arrival time algorithm is applied to global flights in 2004, 2008, and 2012. Empirical evidence demonstrates that providing direct flights across the Taiwan Strait has significantly increased accessibility from TPE to airports in China, but did not improve the centrality of TPE. Additionally, the transfer dependency of TPE on other airports is increasing significantly. This result was based on two major reasons: the first involves the Chinese government’s refusal to allow Chinese citizens to use airports in Taiwan as transfer points to and from other countries and the second reflects the competitiveness among airports and airlines in the region. The key finding is that political exclusion of airline use by external governments via travel regulations adversely influences the development of an airport as a global hub.     

A practical approach to determining critical macroeconomic factors in air-traffic volume based on K-means clustering and decision-tree classification

A given region's volume of air passengers and cargo is frequently taken to represent its economic development. This research proposes a practical methodology for investigating the inherent patterns of the relationships between air-traffic volume and macroeconomic development, utilizing data-mining techniques, including K-means clustering and Decision Tree C5.0 classification. Using the case of Taiwan from 2001 to 2014, 32 potential macroeconomic factors ascertained from a literature review were combined with air-traffic volume data to establish a 168-month dataset. After this dataset was grouped into five clusters, decision trees were implemented to determine its critical macroeconomic characteristics. The resulting four critical factors and their thresholds were the Information and Electronics Industrial Production Index (IE Index), at 83.22; National Income Per Capita, at US$3,222; Employed Population, at 10.134 million; and the Japanese Nikkei 225 Stock Average, at 10564.44. Among these, the IE Index was found to be the first critical factor relating to air-traffic volume as well as the only characteristic to distinguish Cluster V – 58 consecutive months from March 2010 to December 2014 inclusive – among others, and the reasonableness of this finding was confirmed via examination of detailed air-traffic statistics. Besides, the effectiveness of the four identified critical factors as predictive variables were validated by comparing forecasted results with actual air traffic volume from 2015 to 2016. Understanding these four critical factors and their relative importance is of great value to policymakers seeking to allocate limited resources optimally and objectively. Therefore, as an effective and efficient means of capturing significant and explainable macroeconomic factors influencing air-traffic volume, the proposed methodology can be applied to strategy formulation, operations management, and investment planning by governments, airports, airlines, and related entities.     

The determinants of air passenger traffic at Turkish airports

Investigating the determinants of air passenger traffic has become commonplace. In contrast with most previous publications, this paper investigates these determinants in an emerging country, Turkey, at the provincial level between 2004 and 2014. We find that GDP/capita, population, distance to alternative airports, tourism, leading cities, and international migrations all support more air traffic. Furthermore, market concentration is associated with less traffic, and the presence of academics with more traffic. Mapping models' residuals suggest catchment areas, surface transport options, domestic migrations and (geo)politics could also matter. Accordingly, it appears the determinants of Turkey's air passenger traffic do not differ from those of developed economies. The results also suggest new airports should be built based on the aforementioned factors.     

The underlying drivers and future development of air cargo

Air cargo plays a crucial role in the air transport chain and in the globalized economy. As for other modes of transport, the demand for air cargo is a derived demand. Previous studies showed that the main determinants of air cargo demand are merchandise trade and the share of manufactures in merchandise trade. This paper aims to fill a gap in the existing literature by additionally taking the influence of air freight yields and oil prices into account when modelling the global air cargo development. Furthermore, it provides an insight into the future development of air cargo. Forecasts until 2023 are made based on a number of scenarios for the main determinants of air cargo demand. Moreover, an insight is provided into the current air cargo market, including traffic levels and different types of actors and traffic flows. The results are useful not only for academics but also for industry stakeholders for which air cargo is an important contributor to profit and/or cash levels.     

Air cargo expansion and economic growth: Finding the empirical link

This paper applies Granger causality tests to examine the causal relationship between air cargo expansion and economic growth in Taiwan for the period 1974–2006. The results of cointegration tests show a long-run equilibrium and bi-directional relationship between air cargo expansion and economic growth in the case of Taiwan.     

Investigating factors that influence passengers' shopping intentions at airports – Evidence from Taiwan

This study examines the influence of passengers' socio-demographic characteristics, trip characteristics and perceptions of airport shopping on their shopping intentions at airports. We collected a sample of passenger survey data at two major international airports in Taiwan. Two primary shopping intentions, namely pre-planned shopping and impulse shopping, are identified based on the results of factor analysis. A seemingly unrelated regressions (SUR) model is then adopted to measure the relationships between the two buying tendencies and potential determinants. Passengers' perceptions of airport shopping show positive impacts on their shopping intentions. The SUR results also reveal significant differences among the personal profiles of passengers in determining various shopping tendencies.     

Determinants of airport cost flexibility in a context of economic recession

The recent economic downturn led to a significant contraction in the global demand for air travel and cargo. In spite of that, airports’ operating costs did not mirror the traffic trends and kept increasing during the same period, showing evident signs of lack of flexibility. With this background, this paper aims at identifying the drivers of airport cost flexibility in a context of economic recession. This is done by estimating a short-run stochastic cost frontier over a balanced pool database of 194 airports worldwide between 2007 and 2009. Using the total change in cost efficiency during the sample period as a proxy for cost flexibility, the impact of variables such as ownership, outsourcing, airline dominance, low-cost traffic, and revenue diversification is tested in a second-stage regression. Contrary to the existing literature, a higher level of outsourcing is shown to reduce cost flexibility. Results also indicate that low-cost traffic, diversification, and corporatization increase the airports’ ability to control costs. The negative impact of airline dominance suggests the need for more stringent regulations on slot allocation at congested airports in order to ensure optimal infrastructure usage.     

Effects of cargo types and load efficiency on airline cargo revenues

Numerous factors affect air cargo revenue management. Air cargo companies base their cargo charges on whichever is the greater of gross weight or volumetric weight. We developed a cargo consolidation model based on air cargo characteristics, and investigated the effect of cargo density, the Density Ratio of Heavy cargo to Light cargo (DRHL), and the percentage of small cargo on the chargeable weights and revenues of airlines. The empirical results show that a higher DRHL indicates greater chargeable weight, and that as the DRHL climbs to a certain level, the extent of chargeable cargo weights tends to stabilize gradually. The closer the cargo density approaches the most suitable loading density for a flight, the greater the chargeable weight is. A higher proportion of small cargo loaded on an aircraft means higher airline revenue. Our results can effectively combine types of air cargo to increase loading rates and revenues for airlines.     

The growth of Arabian airlines from a German perspective – A study of the impacts of new air services to Asia

Airlines from Bahrain, Kuwait, Qatar, the United Arab Emirates and Oman have gained significant market shares in international air transport. Traditionally travellers have chosen hubs like Amsterdam, Frankfurt, London or Paris as transfer points for trips to Asia. With the inauguration of non-stop services to places like Abu Dhabi, Doha or Dubai, new choices for air travellers have emerged. We analyse data derived from German air transport statistics on the effects of passenger flows between the airports of Düsseldorf and Hamburg to Asian destinations. They suggest that services introduced by Emirates stimulated passenger demand for Asian destinations, while incumbent hubs do not lose transfer passengers. Regarding travel times and connection quality of routings between secondary airports in Germany and Asian destinations, comparing routings of Emirates Airlines and Lufthansa suggests that due to geographic and scheduling constraints, services via Arabia do not constitute a perfect substitute for time-sensitive passengers.     

Gravity models for airline passenger volume estimation

This paper presents two gravity models for the estimation of air passenger volume between city-pairs. The models include variables describing the general economic activity and geographical characteristics of city-pairs instead of variables describing air service characteristics. Thus, both models can be applied to city-pairs where currently no air service is established, historical data is not available, or for which factors describing the current service level of air transportation are not accessible or accurately predictable. One model is limited to city-pairs with airports not subject to competition from airports in the vicinity, while the other model includes all city-pairs. Booking data of flights between Germany and 28 European countries is used for calibration. Both models show a good fit to the observed data and are statistically tested and validated.     

Statistical modelling of runway incursion occurences in the United States

Runway incursions are an important aviation safety concern; between 2002 and 2015 there were 16,785 runway incursions at United States airports ranging in size from small general aviation (GA) to large commercial airline hubs. When examining airports with the 50 highest incursion count over the past 5 years, the predominant categories were large hubs, which accounted for 21 airports and general aviation (GA) airports which accounted for 16 airports. In June 2015, the Federal Aviation Administration (FAA) announced the Runway Incursion Mitigation (RIM) program to identify airport risk factors that might contribute to a runway incursion and develop strategies to help airport stakeholders mitigate those risks. Different size airports serve different aircraft fleets, serve different operating volumes, and have different resources available (both funds and technologies) for incursion mitigation. Therefore, it is valuable to determine the correlating factors that affect incursions at different size airports. This paper uses econometrics based modelling techniques to identify statistically significant factors in data provided by the (FAA) public web sites on runway incursions. The model identified statistically significant variables that correlate with incursions, based on severity, for airports categories defined by the National Plan of Integrated Airport Systems (NPIAS).The model results indicate that operational incidents (OI) are more likely at large hub airports. In contrast, at GA/non-hub airports, pilot deviations (PD) were significant for less severe incursions (severity C and D). Only one variable, “number of years since 2002”, was found to be significant for all the three airport categories; this variable was correlated with severity A incursions and indicated a statistically significant reduction in severity A incursions, despite an overall 80% increase in incursions between 2002 and 2015.