1,721,014 research outputs found
DEA methodologies for assessing the efficiency profiles of commercial banks under heterogeneity conditions
Get PDFSince the publication of the seminal paper by Charnes, Cooper and Rhodes in
1978, where the conventional CCR model of Data Envelopment Analysis
(DEA) has been proposed, DEA as a field has substantially evolved both
methodologically and in terms of applications. So far, efficiency and
productivity studies in the banking sector proved to be amongst the most
popular application areas. The popularity of DEA in this field, amongst others,
is due to its unique features such as its non-parametric nature, it benchmarks
against the best practice performers rather than the average performers. It
allows one to identify targets for improvement; it does not need any functional
specification of the relationship between inputs and outputs, and provides a
variety of efficiency measures most suitable for a variety of applications.
Moreover, it provides a wide range of models to perform analyses at the
aggregate level and the detailed level. In addition, DEA models allow one to
perform both Static and Dynamic analyses.
In this thesis, DEA is used to assess the efficiency profiles of commercial
banks under heterogeneity conditions. First, a new DEA-based analysis
framework with a regression-based feedback mechanism is proposed to deal
with the particular features of the UK banking sector, where regression
analysis provides DEA with feedback that informs about the relevance of the
inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA
models used within the proposed framework could use both inputs and
outputs, only inputs, or only outputs, which proved necessary with UK data.
Second, to the best of our knowledge, no attempt has been made to investigate
the relative efficiency of operating environments of banks. This thesis aims at
filling this gap by analysing the efficiency of HSBC in different operating
environments or countries over time. The choice of a single bank; namely,
HSBC, is motivated by isolating the operating environment effect on efficiency
and thus avoiding any bias that would result from the relative efficiency of
different banks within the same operating environment. From a methodological
perspective, this analysis is performed using a variety of framework; namely,
A four-stage analysis is performed with Static black box SBM, Dynamic SBM,
Network SBM, and Dynamic-Network SBM DEA frameworks. Overall, this
thesis contributes to both the DEA field, through its methodological
contributions, and the banking sector, through its application of the
methodological contributions in assessing banks’ efficiency profiles
The potential short-term impact of a hyperloop service between San Francisco and Los Angeles on airport competition in California
Get PDFThe Hyperloop is a proposed new mode of transport in which passengers or freight would travel in pods through a vacuum tube at very high speeds, enough to cover a hypothetical route between San Francisco and Los Angeles’ metropolitan areas in just 35 minutes. Whereas the “time-space compression” brought by this new technology can have significant impacts in residents’ travel behaviour and household mobility, similar to those documented for high-speed rail, this paper investigates how the proposed California Hyperloop could expand airline passengers’ choice of airports for long-distance domestic trips. Using an established method to determine airport catchment areas based on flight frequencies, access times, and travel costs, we provide an exploratory analysis of how airport competition could change if a Hyperloop service was introduced. Our results clearly show that the California airport network will move towards a single airport system, with significant short-term leakage effects between major airports. These effects should be taken into consideration in the economic assessment of potential Hyperloop routes connecting major cities
Estimating the implicit value of a short-term rental license:A case study of Airbnb survivals in New York city
Get PDFFollowing New York City’s recent regulations requiring hosts of short-term accommodations to obtain licenses, most hosts either exited the market or switched to monthly rentals. This raises the question of the implicit value of a short-term rental license—a topic that has not received much attention in the literature. To address this gap, we estimated several fixed-effect negative-binomial regressions using data on New York’s extant Airbnb listings from February 2023 to March 2024. We found that short-term licensed listings earn, on average, between 5.2 and 7.2 thousand dollars more per year than unlicensed ones.</p
Price competition among short-term Airbnb listings in New York City following Local Law 18
Get PDFIn September 2023, New York City began requiring short-term rental properties to be licensed, wiping off many listings from platforms like Airbnb. The increase in short-term rental rates observed soon after illustrates price rivalry under an exogenous shock to market structure. To quantify that effect, we use data on New York’s Airbnb listings from July 2023 to January 2024 to carry out several fixed-effect regressions. We found that the intensity of price competition is hindered by the presence of multi-listing hosts. Hence, if Airbnb wishes to reclaim its ‘cheaper than hotels’ value proposition, they should tackle excessive market concentration
Technical efficiency of car manufacturers under environmental and sustainability pressures:A Data Envelopment Analysis approach
Get PDFManagers in the competitive automotive sector face growing pressures in terms of sustainability and environmental performance. While most efficiency studies focus on traditional financial and operating indicators, this study broadens the scope of analysis to include Environmental, Social, and Governance (ESG) activities. The well-known Data Envelopment Analysis (DEA) method is employed to estimate the technical efficiency of 33 global automakers from 2014 to 2017, including their ESG scores as outputs in the model. Our findings show that ESG-adjusted efficiencies tend to be higher than the traditional ones, with the Governance adjusted model achieving the highest efficiency scores, followed by the Environmental and the Social models.The results of a second-stage bootstrapped truncated regression reveal the significant impact of the automakers’size, degree of innovation and geographical region on the ESG-adjusted efficiencies. Finally, this study has implications for managers in the industry, as well as investors interested in creating sustainable portfolios
The influence of race performance on re-participation behaviour of trail runners in the Transgrancanaria event
Get PDFResearch question: This paper aims to determine whether race performance has an impact on re-participation behaviour in trail running events. Own performance is a key driver of satisfaction in sport events, but this variable has received less attention than others in the empirical literature about re-participation intentions, even less so for trail running. Research methods: This paper employed time-series data to analyse re-participation behaviour of trail runners: our dataset includes all participants in the multi-race Transgrancanaria event (Canary Islands, Spain) between 2008 and 2018. A logistic regression (n=10,170) aims to establish a link between race performance and the propensity to return to the event.Results and findings: Results show that improving own ranking within the same race has positive impacts on re-participation behaviour for both locals and visiting participants. Progressing to a longer race over time boosts loyalty for locals, while finishing in the top ten for a given category also motivates further participation, but only for non-locals.Implications: These findings have implications for the race organiser as they shed light on some key drivers of re-participation that can justify the introduction of measures to incentivise loyalty by taking advantage of the broad choice of events on offer. This can be achieved by offering discounts and other benefits linked to performance or race progression.<br/
A frontier-based hierarchical clustering for airport efficiency benchmarking
No full textPurpose: When large samples are used to estimate airport efficiency, clustering is a necessary step before carrying out any benchmarking analysis. However, the existing literature has paid little attention to developing a robust methodology for airport classification, instead relying on ad hoc techniques. In order to address this issue, this paper aims to develop a new airport clustering procedure. Design/methodology/approach: A frontier-based hierarchical clustering procedure is developed. An application to cost-efficiency benchmarking is presented using the cost function parameters available in the literature. A cross-section of worldwide airports is clustered according to the relevant outputs and input prices, with cost elasticities and factor shares serving as optimal variable weights. Findings: The authors found 17 distinct airport clusters without any ad hoc input. Factors like the use of larger aircraft or the dominance of low-cost carriers are shown to improve cost performance in the airport industry. Practical implications: The proposed method allows for a more precise identification of the efficiency benchmarks, which are characterized by a set of cophenetic distances to their "peers". Furthermore, the resulting classification can also be used to benchmark other indicators linked to airport costs, such as aeronautical charges or service quality. Originality/value: This paper contributed to airport clustering by providing the first discussion and application of optimal variable weighting. In regard to efficiency benchmarking, the paper aims to overcome the limitations of previous papers by defining a method that is not dependent on performance, but on technology, and that can be easily adapted to large airport datasets.5084860,576Q1ESC
The income elasticity gap and its implications for economic growth and tourism development: the Balearic vs the Canary Islands
Get PDFThe Balearic and the Canary Islands are two well-known tourism-led economies. They both experienced a tourism boom during the same decades, and, hence, they developed a similar productive-mix. Nevertheless, there are strong economic differences between the two regions. While the Balearic Islands enjoy a high GDP per capita, the Canary Islands show a more modest performance. The results of a panel data regression confirm our hypothesis that they differ substantially in terms of income elasticity of tourism. It is two times higher in the Balearic Islands than in the Canaries, which indicates the first is perceived as a more luxurious destination. Furthermore, the results of a dynamic computable general equilibrium model show that the Canaries would converge in GDP per capita with the Balearic Islands if they attracted tourists with a similar profile as the latte
Drivers of Airbnb prices according to property/room type, season and location:A regression approach
Get PDFWhile past studies on Airbnb pricing highlight the importance of room features, host characteristics and location factors, little has been investigated about whether these factors are the same across different property/room types, locations and seasons. To fill that gap, this paper presents a study about the drivers of Airbnb prices in Bristol using ordinary least squares (OLS) and geographically-weighted regression (GWR) methods. The estimated models exhibit sharply different levels of goodness-of-fit, suggesting that the prices of different room types might not be explained by the same set of price factors. The results also uncover statistically significant differences between the price determinants of apartments and house listings and reveal spatial patterns in the price effects. These findings have implications for price setting and the assessment of competition. Future studies should account for potential differences across property/room types, as well as consider the spatial variability of the estimated coefficients
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