Effect of low-cost airlines on tourism in Spain. A dynamic panel data model

This article estimates the impact of low-cost airlines on Spanish tourism during the first decade of the 21st century looking tourist traffic from the principal EU-15 member states using a dynamic panel data. The expansion in low-cost airline activity has had significant, positive direct and indirect effects on the Spanish economy. The study also looks at some of the key elasticities of demand that have influenced this.     

Improving service quality using quality function deployment: The air cargo sector of China airlines

Recent-rising crude oil prices have impacted on the development of the air-freight industry making improved service quality and competitiveness— pressing issues for management. To examine the performance of China Airlines this paper employs quality function deployment to integrate inside quality technology and the voice of outside consumers, and using “House of Quality” charts, illustrates the company's performance in terms of service and offer suggestions for improvement. The conclusion shows, in terms of outside consumer voice, the three main factors demanding improvement and the three in greatest need of improvement regarding quality technology.     

Some potential issues of service quality reporting for airlines

Prior studies have examined the value relevance of operating measures in the airline industry. These indicators, however, have been evaluated in isolation. This study adds to the extant literature by investigating the interactive effects of service quality (e.g., on-time arrivals, flight delays, mishandled baggage, and complaints) and aircraft productivity on the firm's future performance as measured by one-quarter-ahead Return on Assets or Return on Sales. Overall, results show that negative factors such as more complaints and more mishandled baggage interact with aircraft productivity to further reduce one-quarter ahead Return on Assets or Return on Sales, with the results of complaints being more pronounced. On the other hand, there is no support for the interaction between on-time arrivals and aircraft productivity.     

Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis: A comment

This paper provides critical remarks and remedies to a recent article published in [Chiou, Y.-C., Chen, Y.-H., 2006. Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis. Transportation Research Part E 42, (2) 116–127]. In their article, the authors adopted data envelopment analysis (DEA) to measure the route-based performance of Taiwanese domestic airlines. The present paper points out the faults or errors found in their article, in terms of variable selection, model selection, scale efficiency and scale economy, slack analysis, Tobit regression, and terminologies used. It is hoped to make more appropriate and much clearer the DEA applications to airline’s performance evaluation.     

Seasonality and price behaviour of airlines in the Alicante-London market

This article focuses on airline prices in the Alicante-London market. It analyzes price evolution over short periods to observe the incidence of seasonality, the types of firms involved, timetabling, types of airport, competitiveness, and variables such as the price of jet fuel and the rate of exchange used by airlines to establish prices. The paper shows the relative incidence of these variables and stresses the relevance of seasonality and competitiveness in the price strategies followed by the different types of company.     

Cross-cultural perspectives regarding service quality and satisfaction in Chinese cross-strait airlines

Although the same culture and language pertains in Taiwan and the Chinese mainland, perceptions of service quality vary. Here notions of air service quality is examined in terms of passengers’ backgrounds, and especially of those from cross-strait areas based on the perception data of Taiwan travelers and Mainland China travelers. Significant differences are found between cross-strait airlines and Taiwan and Mainland China travelers regarding service attributes.     

A modified VIKOR multiple-criteria decision method for improving domestic airlines service quality

This study applies a modified VIKOR method to improve service quality among domestic airlines in Taiwan. Our model allows decision-makers to understand the gaps between alternatives and aspired-levels in practice. A large sample is used to establish a complete service quality evaluation framework for reducing the gaps to achieve the aspired-level. We then applied the modified VIKOR method to establish the gaps in priorities between alternatives and aspired-levels. Finally, based on these gaps in priorities, we provide managerial implications to improve different carriers for satisfying the customers’ needs to achieve the aspired-level.     

An analytic hierarchy process for ranking operating costs of low cost and full service airlines

This paper develops an application of the analytic hierarchy process to rank the operating cost components of full service and low cost airlines. It takes into account the financial balance sheets and answers to a questionnaire submitted to the managers of selected airlines. The results suggest that the analytic hierarchy process can be appropriately used to obtain the ranking of the costs taking into account different views: financial, management and operative. Rental, office equipment and other supplies costs show the highest importance in the cost ranking, both for full services and low cost airlines. The robustness of the results is tested by Monte Carlo analysis.     

A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines

This paper presents an effective approach based on combining VIKOR, GRA, and interval-valued fuzzy sets to evaluate service quality of Chinese cross-strait passenger airlines via customer surveys. The proposed approach can enable decision-makers to understand the gaps between alternatives and aspired levels. An empirical study is used to establish a complete service quality evaluation framework for reducing the gaps to achieve the aspired level. Based on the gaps in priorities, it can help an airline to identify its own strengths and weaknesses in specific areas of passenger service to further improve service quality.     

Performance assessment of airlines using range-adjusted measure,strong complementary slackness condition,and discriminant analysis

This study integrates RAM (range-adjusted measure), SCSC (strong complementary slackness condition), and DEA–DA (data envelopment analysis–discriminant analysis) to rank airlines. As conventional DEA models do not fully use all inputs and outputs, they result zero in many multipliers. These sorts of DEA models may yield many efficient decision-making units (DMUs). This decreases the discrimination power of DEA. To overcome this limitation, this study proposes a novel application of RAM–DEA/SCSC along with DA. A case study demonstrates the applicability of our proposed approach.     

Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment

The purpose of this study is to evaluate the performance of the European airlines, using a balanced scorecard perspective. Within this scope, a hybrid multi-criteria approach was used by combining the Fuzzy DEMATEL, Fuzzy ANP, and MOORA methods. The results demonstrate that customer dimensions and profit per customer are the most significant key factors in the balanced scorecard perspective. Additionally, the airline companies with the largest profit (per employee) and highest number of passengers and flights (per employee) had the best scores in the multidimensional performance results. Furthermore, the airline companies with the highest profitability and efficiency are more successful than other companies. Therefore, we recommend European airlines to focus on these aspects in order to improve their performance. This study makes an important contribution to literature by helping to solve a significant problem in the market with the proposed methodology.     

An investigation of service quality,customer satisfaction and loyalty in China's airline market

Customer loyalty is a source of competitive advantage and an important intangible asset to any organisations, but empirical evidence from China's airline market regarding the determinants of passenger satisfaction and loyalty is lacking. This paper investigates the service quality of four major airlines in China's domestic market and explores the links between their service quality and customer satisfaction, as well as the conditions under which airlines can retain existing passengers. In line with previous studies, service quality variables are significant factors influencing customer satisfaction levels. However, satisfactory service was not found to result in higher customer loyalty among business travellers. In comparison to Hainan Airlines, passengers who travelled with Air China, China Southern and China Eastern were more likely to switch to an alternate carrier, indicating lower levels of brand loyalty. In addition, the frequent flyer programs (FFPs) have been largely a failure for the four major airlines in terms of increasing customer loyalty, as revealed in this study. It is necessary to draw distinctions between business and leisure travellers when studying the determinants of customer satisfaction and customer loyalty. Ticket pricing had a positive and significant effect on passengers' overall satisfaction and in turn strengthened customer loyalty among leisure travellers, but achieved no impact on the satisfaction and loyalty of business passengers. Some demographic variables such as gender, income and education are statistically significant for one group of passengers but not for another in the probit models estimated. It is suggested that different marketing strategies may be used to target different market segments to improve customer loyalty.     

Mapping ridership using crowdsourced cycling data

Cycling volumes are necessary to understand what influences ridership and are essential for safety studies. Traditional methods of data collection are expensive, time consuming, and lack spatial and temporal detail. New sources have emerged as a result of crowdsourced data from fitness apps, allowing cyclists to track routes using GPS enabled cell phones. Our goal is to determine if crowdsourced data from fitness apps data can be used to quantify and map the spatial and temporal variation of ridership. Using data provided by Strava.com, we quantify how well crowdsourced fitness app data represent ridership through comparison with manual cycling counts in Victoria, British Columbia. Comparisons are made for hourly, AM and PM peak, and peak period totals that are separated by season. Using Geographic Information Systems (GIS) and a Generalized Linear Model we modelled the relationships between crowdsourced data from Strava and manual counts and predicted categories of ridership into low, medium, and high for all roadways in Victoria. Our results indicate a linear association (r² 0.40 to 0.58) between crowdsourced data volumes and manual counts, with one crowdsourced data cyclist representing 51 riders. Categorical cycling volumes were predicted and mapped using data on slope, traffic speeds, on street parking, time of year, and crowdsourced ridership with a predictive accuracy of 62%. Crowdsourced fitness data are a biased sample of ridership, however, in urban areas the high temporal and spatial resolution of data can predict categories of ridership and map spatial variation. Crowdsourced fitness apps offer a new source of data for transportation planning and can increase the spatial and temporal resolution of official count programs.     

Modeling electric taxis' charging behavior using real-world data

Charging behavior is critical to the development and deployment of electric vehicle (EV) systems, given its impacts in EV adoption, the energy and environmental performance of EVs, potential load change to the electric grid, etc. However, the general characteristics of practical charging behavior have not been well studied. Existing studies are mostly based on travel data from conventional internal combustion engine vehicles, modeled with assumed and simplified charging scenarios. The use of public charging infrastructure is often neglected. Few studies evaluate real-world charging behaviors of EVs currently in operation using public charging stations. To address this gap, this study analyzes the data of 39,372 charging events from 129 unique electric taxis in Shenzhen, China to study the distributions of daily charging frequency, charging start time, and charging duration. The insights we learned from this study are: 1) the daily frequency for a vehicle to visit charging stations is unlikely to exceed five times; 2) the distribution of charging start time have multiple peaks and can be fitted with Gaussian Mixture Models; 3) charging duration is influenced by charging start time; and 4) charging dynamics can be modeled using the distributions of daily charging frequency, charging start time, and charging duration. Results from this study can inform charging behavior modeling for EVs and charging infrastructure development.     

Entry effect of low-cost carriers on airport-pairs demand model using market concentration approach

The trend of open sky policies and growth of low-cost airlines, the topic of airport-pairs demand is gradually being addressed in the golden aviation circle of Northeast Asia. The variety of flight services among the four major metropolises with dual-airport systems leads to a competition-cooperation relationship existing between various airports and airlines. Therefore, this study investigates the causal relationship between the route-level passenger demand and influential factors using aggregate data collected through website observations. The empirical study focuses on direct flights of airport-pair routes among Taipei, Shanghai, Seoul, and Tokyo. Results of the passenger regression model indicate that frequency, code-share, and morning flights have positive impacts on increasing passenger numbers for airlines. Further, the market concentration degree of Herfindahl-Hirschman Index and entry effect of low-cost carriers are important for the route-level passenger demand. In addition, routes with departures and arrivals in hub airports have a considerable attraction relative to other airport-pair routes. Finally, the proposed passenger model performs well in predicting market share, especially for routes with high demand.     

Calculating load factors for the transatlantic airline market using supply and demand data – A note on the identification of gaps in the available airline statistics

This paper takes a critical view of the verification of load factors for the direct transatlantic airline market by combining supply and demand-data. The supply-related data originate from the Official Airline Guide, a well-known data source that contains information on scheduled flights. The demand-related data originate from the Marketing Information Data Transfer database, a data set containing information on actual airline bookings. Combining both data sets enables us to calculate the seat occupancy of direct flights between North-West Europe and the US for 2001. Based on the results, we assess the utility of the joint use of these data sources for aviation economic research, and identify various gaps in the available airline statistics.     

Forecasting the demand for an employee Park and Ride service using commuters' stated choices

This paper uses Stated Choice (SC) data to forecast the demand for an employee Park and Ride service. Since it is well known that SC data contain sources of variation not present in Revealed Preference data we pay special attention to the scaling of the SC model. The results show that the modal shift away from parking-on site will be small unless the new service is accompanied by measures aimed at making parking on-site less attractive such as introducing parking charges.     

A comparative performance analysis of airline strategic alliances using data envelopment analysis

As “open skies” agreements became more common among different countries and thus began to open up international routes to further competition, the global airline industry has undergone accelerated structural changes for the last two decades. These changes include the consolidation and expansion of airline strategic alliances throughout different regions of the world. Though airline strategic alliances are generally perceived to be a major driver for enhancing the operating efficiency and the subsequent competitiveness of participating member airlines, the concrete evidence supporting such a perception is still lacking in the literature. This paper is one of few attempts to evaluate the comparative efficiency of the strategic alliances among global airlines and then assess the managerial impact of airline alliances on the airline's comparative performances.     

Dynamic accessibility mapping using floating car data: a network-constrained density estimation approach

The concept of accessibility has been attracting increasing attention from transportation planners and researchers. The goal of “smart growth” is to promote accessibility rather than mobility. Accessibility mapping is a highly effective tool to support smart growth planning. Studies on accessibility mapping and analysis have proliferated over the last decade as Geographic Information Systems (GIS) has been widely adopted to produce accessibility maps. Nevertheless, a major negative aspect of these efforts is the lack of dynamic access measurement. Traffic conditions change significantly over space and time, leading to non-stationary travel time estimation which is central to accessibility measurement. In this paper, we propose a dynamic accessibility measure based on real-time travel speeds that are derived from floating car data (FCD). We introduce a novel integrated access measure to compute accessibility to Points of Interest (POIs) constrained by road networks. POI accessibility measures are obtained by means of both Network Kernel Density Estimation (NKDE) and Network Linear Density Estimation (NLDE). Therefore, we are able to capture temporal dynamics by taking into account speed variability using FCD during peak and off-peak hours on weekdays and weekends. We demonstrate that the proposed approach can capture the spatio-temporal dynamics of accessibility using FCD for Wuhan city in China. Empirical studies were conducted to examine the impacts of density estimation parameters (search bandwidths) and POI weights on the integrated accessibility. We find that search bandwidth and POI weights would impose profound influence on final accessibility values. Experiments also show that NKDE and NLDE would produce significantly different estimation results.