Route-based data envelopment analysis models

This paper proposes two novel route-based data envelopment analysis (DEA) models that jointly measure the route-level and company-level efficiencies amongst transport carriers. The core logics comprise a three-stage procedure that determines company efficiency, route efficiency and optimal allocation ratios for the common inputs. We prove that the ranking order of company performance determined by the route-based DEA model is identical to that determined by the company-based DEA model. An empirical case demonstrates the superiority of the proposed models in identifying the less efficient routs/companies as well as in reducing the input slacks without subjective conjectures.     

How does demand uncertainty affect food and beverage capacity in the hotel industry?

This study investigates the effect of demand uncertainty on hotels’ food and beverage (F&B) capacity using the operation data of international tourist hotels in Taiwan. The empirical results of this study show that demand uncertainty leads to an increase in F&B capacity. Moreover, the magnitude of this effect increasingly strengthens for hotels with larger F&B scales. Our results together with other studies on room capacity collectively indicate that hotels’ overcapacity problem resulting from demand uncertainty considerably varies with hotel scales and between different hotel sectors.     

The effects of corporate governance on airline performance: Production and marketing efficiency perspectives

This study explores the relationship between operating performance and corporate governance in 30 airline companies operating in the US. First, this study applies a two-stage Data Envelopment Analysis (DEA) to evaluate the production efficiency and marketing efficiency of the airlines. Our findings indicate that, in general, there is not as much dispersion in the relative productive efficiencies of the airlines as there is in their marketing efficiencies. The low-cost airlines, on average, are more efficient carriers than the full-service ones, but less efficient marketers. Secondly, truncated regression is used to explore whether the characteristics of corporate governance affect airline performance. The results demonstrate that corporate governance influences firm performance significantly. Finally, we address the managerial decision-making matrix and make suggestions to help airline managers improve performance.     

Impact of all-inclusive packages on hotel efficiency

In the last decade, all-inclusive packages have had an extraordinary boom in one of the most popular sun and beach tourism destinations in Europe, the Canary Islands. This fact reinvigorated the debate on potential benefits and negative effects on the local economy. However, there is no empirical evidence of the impact that all-inclusive packages may have on the efficiency in the hotel industry. This study assessed the effects of all-inclusive packages on cost and profit efficiency using the stochastic frontier approach and the model proposed by Battese and Coelli [(1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325–332] in a sample composed of 102 hotels of the Canary Islands from 2008 to 2014. The empirical results revealed that the hotels that offered all-inclusive packages exhibited lower efficiency levels than those hotels that did not provide this service. These results have important implications for both public policies and hotel management.     

The impact of sharing accommodation on the hotel occupancy rate in the kingdom of Swaziland

This paper examines the relationship and impact of sharing accommodation on the hotel occupancy rate (HOR) from a developing country perspective. Using panel data on the monthly HOR and the number of Airbnb room occupancy rate for the periods 2012–2016 and 2015–2016, respectively, the study applies a hierarchical regression model to respond to the research questions. The Pearson correlation test reveals a positive relationship between the HOR and Airbnb room occupancy rate, thus indicating that an increase in the hotel room occupancy rate moves in tandem with a rise in the Airbnb room occupancy rate. Further test revealed that increase in the Airbnb room occupancy rate coincided with an increase in the hotel room occupancy rate. In addition, the Airbnb platform was found to appeals to a different tourist market profile than does that of hotels, and that, therefore, the two products may be viewed as non-competitors. Furthermore, inconsistencies in regulatory provisions, in terms of which hotels are required to undergo various legal procedures as opposed to such platforms, are evident. The study recommends that the Swaziland Government should undertake stakeholder consultations aimed at developing regulations to manage and monitor sharing accommodation platform participants that will incorporate its innovative and diverse dimensions. The study is important as it provides insights into tourism destination managers on the impact of the sharing economy from a developing country perspective where empirically based research that could be useful in policy formulation is scant.     

An analysis of demand uncertainty in the hotel market

This study proposes a two-step approach to investigate the impact of certain environmental variables on demand uncertainty within the hotel sector. Adopting a simultaneous-equation model and using the operation data of international tourist hotels in Taiwan, this study shows that chained hotels face less demand uncertainty than independent hotels. Additionally, hotels that are more distant from the airport or located in metropolitan areas face a significantly higher degree of demand uncertainty.     

Estimating efficiency and its determinants in the hotel sector using a profit function

Inefficiency in the hotel sector is normally estimated through cost and scale efficiencies. This paper estimates hotel profit efficiency and its determinants employing a stochastic frontier profit function and the inefficiency effects function. The key advantage of this methodology is its ability to estimate efficiency for each hotel and the factors that explain differences in efficiency in a single-stage sampling procedure. The sample consists of 231 hotels in Spain in the period 2008–2012. Empirical evidence shows that the average level of profit efficiency is 45.85% and that age, labour productivity and location are determinants of this efficiency. Policy implications for the improvement of less efficient hotels are noted.     

Evaluating the multi-period operating efficiency of international airports using data envelopment analysis and the Malmquist productivity index

For the most part, airports are publicly or semi-publicly owned and operated with fixed assets. As such, airports have been often considered little more than infrastructure providers for airlines. However, as airports have begun to offer a variety of ancillary services including passenger transfers, re-fueling, parking, and shopping, they no longer play second fiddle to airlines. To come into their own, a growing number of airports realized their need to develop competitive strategies that can attract more air traffic and generate greater revenue. Such strategies start with the assessment of their competitiveness in terms of operating efficiencies relative to others. To help airport authorities identify major drivers for enhancing the airport operational efficiency and the subsequent competitiveness, this paper evaluates the comparative efficiencies of international airports for a multi-year period (2006–2011) using data envelopment analysis intended for dynamic benchmarking and Malmquist productivity index built on time-series analysis. Our study indicates that the productivity of an airport was influenced by exogenous factors such as shifts in government policies and technological advances rather than endogenous factors driven by improvements in managerial practices.     

Multivariate models of hotel occupancy performance and their implications for hotel marketing

Multivariate models are developed to explain the differential occupancy performance of a sample of 279 English hotels. Following a procedure established in an earlier paper, hotels are first differentiated on the basis of their overall occupancy performance, seasonality, long‐term trend and length of season. Regression models are specified and calibrated to relate each of these dimensions of occupancy performance to the location and other characteristics of the hotels. The four models produce the expected positions of hotels in ‘occupancy performance space’, against which their observed positions can be compared. The application of the models in hotel marketing is discussed and demonstrated. Copyright © 2001 John Wiley & Sons, Ltd.     

US airport financial reform and its implications for airport efficiency: An exploratory investigation

This study investigates the effect on airport productive efficiency of two major funding sources used by US airports, namely the Airport Improvement Program (AIP) grants and the Passenger Facility Charges (PFC). A two-stage Data Envelopment Analysis (DEA) modeling approach is employed for this purpose. In the first stage, we estimate airport productive efficiency using a variable returns-to-scale DEA model with both desirable and undesirable outputs. In the second stage, random effects regression models are estimated with airport efficiency scores from the first stage as the dependent variable and PFC and a proxy for AIP grants as two of the explanatory variables. By applying the two-stage DEA model to 42 primary US airports, it is found that PFC use has a positive impact on airport productive efficiency, whereas the impact of AIP grants is negative. Multiple counterfactual scenarios are examined by altering the mix of the two types of funding sources. The results show that simultaneously raising the PFC ceiling and decreasing AIP grants could lead to greater airport productive efficiency. The US federal aviation authority would also benefit from realizing these scenarios, especially given the budgetary constraints it faces.     

Passenger facility charge vs. airport improvement program funds: A dynamic network DEA analysis for U.S. airport financing

Passenger Facility Charge (PFC) and the Airport Improvement Program (AIP) are two major sources to finance U.S. airports. This paper develops a novel dynamic network DEA framework to investigate the substitutability between PFC and AIP funds. We find that the studied U.S. airports can substitute PFC for 8–35% of the current AIP funds and contribute significantly to the proposed plan of the US congress to cut AIP funding. In addition, the amount of PFC-for-AIP funds substitution negatively correlates with the productive efficiency of airports. The findings send an important message for future policy reforms on U.S. airport financing.     

Monitoring hotel performance using occupancy time‐series analysis: the concept of occupancy performance space

Time series factor analysis is used to identify four temporal dimensions of occupancy performance in 279 English hotels over the period January 1992 to December 1994. These dimensions referred to as reference curves differentiate hotels on the basis of overall occupancy level (RC1), seasonality (RC2), long‐term trend (RC3) and length of season (RC4). The reference curves are used to define the dimensions of occupancy performance space in which the 279 hotels are positioned, with the hotels differentiated by hotel situation type. It is shown that the positioning of a hotel in occupancy performance space can provide a precise and effective basis for hotel marketing.     

CNG2020 strategy and airline efficiency: A Network Epsilon-Based Measure with managerial disposability

In this paper, we analyze the impacts of CNG2020 strategy on the efficiency of 29 international airlines during 2021–2023. Predictions are made through neural networks based on the empirical data from 2008 to 2015. Following the principle of CNG2020 strategy, we calculate the emission limit for each airline. Then we propose a new model, Network Epsilon-Based Measure with managerial disposability, to discuss the difference in efficiency of the airlines when the CNG2020 strategy is considered. The main findings are: (1) For most of these 29 airlines, the CNG2020 strategy has little influence on their efficiency. (2) The efficiency has little variation under the following conditions: when the carbon price is 8 $/ton CO₂-eq, when the price is 14 $/ton CO₂-eq, and when the price is 20 $/ton CO₂-eq. (3) Scandinavian is identified as the benchmarking airline.     

Evaluating the efficiency of a small hotel chain with a Malmquist productivity index

By applying data envelopment analysis (DEA) a two‐stage procedure is followed to evaluate the determinants of efficiency of a Portuguese public‐owned hotel chain, Enatur for the period 1999 to 2001. In the first stage the paper estimates the Malmquist index and breaks it down into technical efficiency and technological change. In the second stage, a Tobit econometric model, designed to relate efficiency scores, along with other managerial and contextual variables, is used to identify the efficiency drivers. The implications of this study for managerial purposes are then discussed. Copyright © 2005 John Wiley & Sons, Ltd.     

Performance evaluation of China's air routes based on network data envelopment analysis approach

Air routes are among the most important elements of civil aviation transport. Airlines' operations are mainly dependent on the structure and layout of air routes. This paper first divides the production process of air routes into two stages, allocation and transport, based on air route operational characteristics. Then, two network data envelopment analysis (DEA) models are proposed to analyze the efficiency of the system, allocation, passenger transport, and freight transport of 477 air routes. The research result demonstrates that the different constraints on intermediate measure in the network DEA models do affect the air routes’ efficiency significantly; Most air routes have high allocation efficiency and passenger transport efficiency, while they have low freight transport efficiency. Furthermore, the efficiencies of 82 airports are also analyzed after aggregating the efficiencies of the air routes.     

Evaluating energy efficiency for airlines: An application of VFB-DEA

In this paper, the energy efficiency of airlines has been studied with number of employees, capital stock and tons of aviation kerosene as the inputs and Revenue Ton Kilometers, Revenue Passenger Kilometers, total business income and CO₂ emissions decrease index as the outputs. A new model, Virtual Frontier Benevolent DEA Cross Efficiency model (VFB-DEA), is proposed to calculate the energy efficiencies of 11 airlines from 2008 to 2012. Spearman correlation coefficient is applied to validate the applicability of the new model. The results indicate that capital efficiency is an important factor in driving energy efficiency, and the American financial crisis had a significant influence on the change in energy efficiency during this period.     

Operational efficiency of Asia–Pacific airports

Airports are important drivers of economic development and thus under tremendous pressure from emerging competitors. However, few studies have analysed the operational efficiency of Asia–Pacific airports. This study therefore evaluated the operational efficiency of 21 Asia–Pacific airports between 2002 and 2011. A two-stage method was used: Data Envelopment Analysis (DEA) to assess airport efficiency, followed by the second-stage regression analysis to identify the key determinants of airport efficiency. The first-stage DEA results indicated that Adelaide, Beijing, Brisbane, Hong Kong, Melbourne, and Shenzhen are the efficient airports. The second-stage regression analysis suggested that percentage of international passengers handled by an airport, airport hinterland population size, dominant airline(s) of an airport when entering global airline strategic alliance, and an increase in GDP per capita are significant in explaining variations in airport efficiency.     

Dynamic DEA models with network structure: An application for Iranian airlines

Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span.     

A fully fuzzy network DEA-Range Adjusted Measure model for evaluating airlines efficiency: A case of Iran

Due to the competition among companies, evaluating the performance is one of the most important issues for managers. Data Envelopment Analysis (DEA) - Range Adjusted Measure model (RAM) is one of the non-radial models to evaluate the performance of companies. This paper presents a fully fuzzy network DEA-RAM model for evaluating airlines and extends the network DEA-RAM model in the fully fuzzy framework. First, a network structure is designed for airlines and then, a DEA-RAM model is presented for calculating efficiency scores. To handle uncertainty in data, fully fuzzy approach is considered and finally, a multi-objective network model is proposed to calculate airlines’ efficiencies. To solve the proposed fully fuzzy DEA-RAM model, the lexicographic approach is used and the efficiency scores are reported as interval numbers. To illustrate the capability of the proposed fully fuzzy DEA-RAM model, the actual data of 14 Iranian airlines are gathered and the interval efficiencies of airlines are evaluated.     

An integration of the multi-component DEA and GAR models to the measurement of hotel performance

The aim of this paper is to identify how well each hotel performs in each of its room and food and beverage divisions. To this end, this paper develops a multi-component data envelopment analysis/global assurance region (MDEA/GAR) model to fully gauge hotel performance where each hotel has its specific inputs and outputs for both divisions as well as shared inputs and common outputs between the two divisions. The application shows how the MDEA/GAR model can incorporate preferable hotels among the efficient ones with higher profit earning ratios when evaluating hotel performance. The results show that members of international chain-managed hotels perform significantly better than local chain-managed and independently managed hotels.