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

On Setting Apartment Rental Rates: A Regression-Based Approach

This study presents a regression-based analysis of apartment rents for a cross-section of properties located in an "edge city" submarket. It attempts to provide a solution for owners and managers of apartments to the thorny problem of setting a property's rental rate. The approach used in this analysis differs from previous studies in at least three important respects: (1) vacancy is treated as part of the dependent variable, (2) the property-specific rental rate generated by the regression analysis is compared to the property's actual effective rent, and (3) each property in the submarket is ranked by the difference between its actual effective rent and its characteristic-adjusted effective rent. This is then followed by several observations concerning the advantages and disadvantages of such an analysis in a practical setting.

A Fundamental Examination of Securitized and Unsecuritized Real Estate

Most studies (including this one) have found a weak statistical relationship between total returns for securitized and unsecuritized real estate equities. Some studies argue that REIT shares behave more like the stock market, than real estate. In an attempt to focus this discussion, this study examines the fundamental underlying return-generating components: dividends, investment values, and dividend yields using NAREIT and NCREIF data from 1978 through 1994. While dividends have been part of the REIT pricing calculus for some time, relatively few studies have focused upon the "dividends" paid by NCREIF properties. The short-run relationships between these fundamental components are weak and many of their distributions display significant non-normal tendencies. Even when quarterly lags of up to two years are examined, these distributions also tend to be weakly correlated with one another. Of the three fundamental components, the long-run path of prices exhibited the strongest relationship. Interestingly, the volatility of the NCREIF dividend series is approximately 150% of the NAREIT volatility, while the volatility of the NCREIF asset values is roughly 25% of the NAREIT volatility. This is contradictory: in a simplified setting, greater dividend volatility should be accompanied by greater price volatility, not less, as observed here. Nevertheless, such comparisons suffer due to the incompatibility of the data sources and, accordingly, this study should be viewed as a preliminary examination of securitized and unsecuritized real estate returns.

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.

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

The role of information technology in the airport business : a retail-weighted resource management approach for capacity-constrained airports

Much research has been undertaken to gain insight into business alignment of IT. This alignment basically aims to improve a firm’s performance by an improved harmonization of the business function and the IT function within a firm. The thesis discusses previous approaches and constructs an overall framework, which a potential approach needs to fit in. Being in a highly regulated industry, for airports there is little space left to increase revenues. However, the retailing business has proven to be an area that may contribute towards higher income for airport operators. Consequently, airport management should focus on supporting this business segment. Nevertheless, it needs to be taken into account that smooth airport operations are a precondition for successful retailing business at an airport. Applying the concept of information intensity, the processes of gate allocation and airport retailing have been determined to appraise the potential that may be realized upon (improved) synchronization of the two. It has been found that the lever is largest in the planning phase (i.e. prior to operations), and thus support by means of information technology (for information distribution and improved planning) may help to enable an improved overall retail performance. In order to determine potential variables, which might influence the output, a process decomposition has been conducted along with the development of an appropriate information model. The derived research model has been tested in different scenarios. For this purpose an adequate gate allocation algorithm has been developed and implemented in a purposewritten piece of software. To calibrate the model, actual data (several hundred thousand data items from Frankfurt Airport) from two flight plan seasons has been used. Key findings: The results show that under the conditions described it seems feasible to increase retail sales in the magnitude of 9% to 21%. The most influential factors (besides the constraining rule set and a retail area’s specific performance) proved to be a flight’s minimum and maximum time at a gate as well as its buffer time at gate. However, as some of the preconditions may not be accepted by airport management or national regulators, the results may be taken as an indication for cost incurred, in case the suggested approach is not considered. The transferability to other airport business models and limitations of the research approach are discussed at the end along with suggestions for future areas of research.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Using STEM Camps to Improve Female Interest in Technology Careers

Science, technology, engineering, and math (STEM) fields have been traditionally entered by men, often establishing women as underrepresented in many of these fields. This research study focuses on participants at a STEM camp for middle- and high-school girls designed to introduce them to technology. The camp was held 4 times over 3 years, with many of the participants from rural areas, underrepresented by race and economic status. Sixty camp attendees completed pre- and post-camp surveys and are referred to as the intervention group. A control group of 200 middle- and high-school girls who did not attend the camp also took the survey. This paper focuses on a subset of the survey results that sought to determine the impact on camp participants in the areas of technology self-efficacy and technology career interest as it related to management information systems (MIS). Analysis of the data collected found a significant difference in MIS self-efficacy between the intervention group and control group but no significant difference in choices of MIS-related careers. Results also include recommended improvements to STEM camp design

C-NMT: A Collaborative Inference Framework for Neural Machine Translation

Collaborative Inference (CI) optimizes the latency and energy consumption of deep learning inference through the inter-operation of edge and cloud devices. Albeit beneficial for other tasks, CI has never been applied to the sequence-to-sequence mapping problem at the heart of Neural Machine Translation (NMT). In this work, we address the specific issues of collaborative NMT, such as estimating the latency required to generate the (unknown) output sequence, and show how existing CI methods can be adapted to these applications. Our experiments show that CI can reduce the latency of NMT by up to 44% compared to a non-collaborative approach

Multiscale three-dimensional scaffolds for soft tissue engineering via multimodal electrospinning

A novel (scalable) electrospinning process was developed to fabricate bio-inspired multiscale three-dimensional scaffolds endowed with a controlled multimodal distribution of fiber diameters and geared towards soft tissue engineering. The resulting materials finely mingle nano- and microscale fibers together, rather than simply juxtaposing them, as is commonly found in the literature. A detailed proof of concept study was conducted on a simpler bimodal poly(ε-caprolactone) (PCL) scaffold with modes of fiber distribution at 600 nm and 3.3 μm. Three conventional unimodal scaffolds with mean diameters of 300 nm and 2.6 and 5.2 μm, respectively, were used as controls to evaluate the new materials. Characterization of the microstructure (i.e. porosity, fiber distribution and pore structure) and mechanical properties (i.e. stiffness, strength and failure mode) indicated that the multimodal scaffold had superior mechanical properties (Young's modulus ∼40 MPa and strength ∼1 MPa) in comparison with the controls, despite the large porosity (∼90% on average). A biological assessment was conducted with bone marrow stromal cell type (mesenchymal stem cells, mTERT-MSCs). While the new material compared favorably with the controls with respect to cell viability (on the outer surface), it outperformed them in terms of cell colonization within the scaffold. The latter result, which could neither be practically achieved in the controls nor expected based on current models of pore size distribution, demonstrated the greater openness of the pore structure of the bimodal material, which remarkably did not come at the expense of its mechanical properties. Furthermore, nanofibers were seen to form a nanoweb bridging across neighboring microfibers, which boosted cell motility and survival. Lastly, standard adipogenic and osteogenic differentiation tests served to demonstrate that the new scaffold did not hinder the multilineage potential of stem cells. © 2009 Acta Materialia Inc