An exploratory analysis of the effects of ownership change on airport competition

Common or group ownership of airports poses a particular challenge for policy-makers, in that consumers (airlines and passengers) may not have access to benefits that stem from a more competitive system (e.g. lower prices, higher quality of service). However, whilst the arguments for and against group versus individual operations are well known, there are only limited practical cases when a change from common to individual ownership has occurred. One such case is in Scotland where the ownership of Edinburgh and Glasgow airports was separated in 2012. Therefore, the aim of this paper is to undertake a comparative assessment of the impact of this ownership change on the nature of competition between the two airports for the period 2006-2017. Catchment areas overlap, so it was hypothesised that separate ownership would lead to a more intense competitive rivalry with consequent effects on route development, traffic growth, the level/structure of aeronautical charges, financial performance, capital investment and quality of service. A number of key performance indicators covering these areas have been analysed, both before and after 2012 to assess whether there is evidence of a more competitive environment. The main findings are (i) traffic and routes have increased at both airports, although their relative roles appear to have changed; (ii) published charge levels have increased (iii) aeronautical yield has increased at Edinburgh but declined at Glasgow; (iv) prices have diverged reflecting differences in core market price elasticities; strategies have also been driven by a broader financial imperative around maximising EBITDA given declining unit costs and stagnation in non-aeronautical yields; (vi) certain performance indicators suggest that efficiency and service quality have improved. The implications for policy-makers are that airport market re-structuring and ownership change will most likely lead to divergence in pricing and route development strategies

Airport Competition with the Scottish Lowlands Region

The aim of this paper is to undertake an assessment of airport competition within the Scottish Lowlands region, which has experienced significant variations in economic development, and to examine whether competitive forces have been strengthening or weakening in recent years. This region covers the airports of Edinburgh, Glasgow and Prestwick in the last twelve years they have all experienced changes in ownership. BAA which had, for many years, operated both Edinburgh and Glasgow airports, sold the former to GIP in 2012 whilst in 2013 the Scottish Government purchased the privately-owned Prestwick. During this period there were also significant changes in airline network strategies. In order to assess the competitive pressures facing these airports, three key areas are considered, namely: aeronautical charging policy, the service quality provided and traffic development. The analysis shows that since ownership separation, competition has intensified between Edinburgh and Glasgow, whilst Prestwick airport, which benefitted from Ryanair expansion in the 1990s, is now a significantly diminished competitive proposition in the Scottish Lowland market. This has implications not only for airport policy and economic regulation but also for broader economic well-being in this region

Do managed clinical networks improve quality of diabetes care? : Evidence from a retrospective mixed methods evaluation

Peer reviewedPostprin

A Fundamental Comparison of International Real Estate Returns

This study analyzes commercial real estate returns in Australia, Canada, the United Kingdom, and the United States over the period 1985-95, from the perspective of a U.S. investor. Because national indices can consist of differing property mixes, this study separately analyzes the office, retail, and warehouse sectors. Moreover, these analyses also convert total returns into their fundamental components: initial yield, growth in income, and shifts in capitalization rates. The paths of currency-adjusted income and asset values and, therefore, capitalization rates are also presented. Generally speaking, the fundamental components of retail returns across the four countries exhibit greater divergence than the office and warehouse sectors. It is interesting that the U.S. property sectors showed the worst performance, while the Australian retail and the British office and warehouse sectors were the best performers (both before and after currency adjustments). Additionally, the currency-adjusted Australian returns were adversely effected by exchange rate movements, while the British returns were positively effected. Lastly, the correlation of the quarterly percentage change in income was generally lower and less statistically significant that the correlation patterns observed among the other components of return. This might suggest that more idiosyncratic risk can be found in the real estate space markets (as proxied by income changes) than in the real estate capital markets (as proxied by the pricing of the income--that is, capitalization rates), which appear to be more globally influenced.

Design and development of a peristaltic pump for constant flow applications

In wide-ranging areas, including hydraulics, biomedical, automotive, and aerospace, there is often a need to move a fluid with a constant flow rate. This is difficult to achieve with any type of pump and usually other elements are inserted to regularize the output. This study focused on the peristaltic pump because there are few studies on it and it has some interesting features, such as extreme simplicity, a small number of components, and the extreme compactness of the whole system. The first part of this study is focused on analyzing the classical geometry of the peristaltic pump to understand the origin of the discontinuity in the flow rate; the second part proposes a new geometry that mitigates the flow irregularity by more than 200%. In this way, it is possible to use it in all the sectors where a constant flow rate is required but where insulation between the fluid and the machine is required. Together with the flow study, an analysis of how the main geometric parameters affect the operation of the pump is provided, complete with explanatory graphs and tables. A prototype made through additive manufacturing technologies is also proposed

Energy-efficient and Privacy-aware Social Distance Monitoring with Low-resolution Infrared Sensors and Adaptive Inference

Low-resolution infrared (IR) Sensors combined with machine learning (ML) can be leveraged to implement privacy-preserving social distance monitoring solutions in indoor spaces. However, the need of executing these applications on Internet of Things (IoT) edge nodes makes energy consumption critical. In this work, we propose an energy-efficient adaptive inference solution consisting of the cascade of a simple wake-up trigger and a 8-bit quantized Convolutional Neural Network (CNN), which is only invoked for difficult-to-classify frames. Deploying such adaptive system on a IoT Microcontroller, we show that, when processing the output of a 8×8 low-resolution IR sensor, we are able to reduce the energy consumption by 37-57% with respect to a static CNN-based approach, with an accuracy drop of less than 2% (83% balanced accuracy)

Bilevel Training Schemes in Imaging for Total Variation--Type Functionals with Convex Integrands

In the context of image processing, given a $k$-th order, homogeneous and linear differential operator with constant coefficients, we study a class of variational problems whose regularizing terms depend on the operator. Precisely, the regularizers are integrals of spatially inhomogeneous integrands with convex dependence on the differential operator applied to the image function. The setting is made rigorous by means of the theory of Radon measures and of suitable function spaces modeled on $BV$. We prove the lower semicontinuity of the functionals at stake and existence of minimizers for the corresponding variational problems. Then, we embed the latter into a bilevel scheme in order to automatically compute the space-dependent regularization parameters, thus allowing for good flexibility and preservation of details in the reconstructed image. We establish existence of optima for the scheme and we finally substantiate its feasibility by numerical examples in image denoising. The cases that we treat are Huber versions of the first and second order total variation with both the Huber and the regularization parameter being spatially dependent. Notably the spatially dependent version of second order total variation produces high quality reconstructions when compared to regularizations of similar type, and the introduction of the spatially dependent Huber parameter leads to a further enhancement of the image details.Comment: 27 pages, 6 figure

The ethics of people analytics: risks, opportunities and recommendations

Purpose: This research analyzed the existing academic and grey literature concerning the technologies and practices of people analytics (PA), to understand how ethical considerations are being discussed by researchers, industry experts and practitioners, and to identify gaps, priorities and recommendations for ethical practice. Design/methodology/approach: An iterative “scoping review” method was used to capture and synthesize relevant academic and grey literature. This is suited to emerging areas of innovation where formal research lags behind evidence from professional or technical sources. Findings: Although the grey literature contains a growing stream of publications aimed at helping PA practitioners to “be ethical,” overall, research on ethical issues in PA is still at an early stage. Optimistic and technocentric perspectives dominate the PA discourse, although key themes seen in the wider literature on digital/data ethics are also evident. Risks and recommendations for PA projects concerned transparency and diverse stakeholder inclusion, respecting privacy rights, fair and proportionate use of data, fostering a systemic culture of ethical practice, delivering benefits for employees, including ethical outcomes in business models, ensuring legal compliance and using ethical charters. Research limitations/implications: This research adds to current debates over the future of work and employment in a digitized, algorithm-driven society. Practical implications: The research provides an accessible summary of the risks, opportunities, trade-offs and regulatory issues for PA, as well as a framework for integrating ethical strategies and practices. Originality/value: By using a scoping methodology to surface and analyze diverse literatures, this study fills a gap in existing knowledge on ethical aspects of PA. The findings can inform future academic research, organizations using or considering PA products, professional associations developing relevant guidelines and policymakers adapting regulations. It is also timely, given the increase in digital monitoring of employees working from home during the Covid-19 pandemic

Customer Lifetime Value Prediction Using Embeddings

We describe the Customer LifeTime Value (CLTV) prediction system deployed at ASOS.com, a global online fashion retailer. CLTV prediction is an important problem in e-commerce where an accurate estimate of future value allows retailers to effectively allocate marketing spend, identify and nurture high value customers and mitigate exposure to losses. The system at ASOS provides daily estimates of the future value of every customer and is one of the cornerstones of the personalised shopping experience. The state of the art in this domain uses large numbers of handcrafted features and ensemble regressors to forecast value, predict churn and evaluate customer loyalty. Recently, domains including language, vision and speech have shown dramatic advances by replacing handcrafted features with features that are learned automatically from data. We detail the system deployed at ASOS and show that learning feature representations is a promising extension to the state of the art in CLTV modelling. We propose a novel way to generate embeddings of customers, which addresses the issue of the ever changing product catalogue and obtain a significant improvement over an exhaustive set of handcrafted features