Twelfth Annual Concerto Competition, November 18, 2002

Concert program for Twelfth Annual Concerto Competition, November 18, 2002

Old conflicts, new rivals? Airline competition in the European market

Christoph Franz of Lufthansa recently identified Ryanair, easyJet, Air Berlin and Emirates as the company’s main competitors – gone are the days when it could benchmark itself against BA or Air France-KLM! This paper probes behind the headlines to assess the extent to which different airlines are in competition, using evidence from the UK and mainland European markets. The issue of route versus network competition is addressed. Many regulators have put an emphasis on the former whereas the latter, although less obvious, can be more relevant. For example, BA and American will cease to compete between London and Dallas Fort Worth if their alliance obtains anti-trust immunity but 80% of the passengers on this route are connecting at one or both ends and hence arguably belong to different markets (e.g. London-San Francisco, Zurich-Dallas, Edinburgh-New Orleans) which may be highly contested. The remaining 20% of local traffic is actually insufficient to support a single point to point service in its own right. Estimates are made of the seat capacity major airlines are offering to the local market as distinct from feeding other routes. On a sector such as Manchester–Amsterdam, 60% of KLM’s passengers are transferring at Schiphol as against only 1% of bmibaby’s. Thus although KLM operates 5 flights and 630 seats per day against bmibaby’s 2 flights and 298 seats, in the point to point market bmibaby offers more seats than KLM. The growth of the Low Cost Carriers (LCCs) means that competition increasingly needs to be viewed on city pair markets (e.g. London-Rome) rather than airport pair markets (e.g. Heathrow-Fiumicino). As the stronger LCCs drive out weaker rivals and mainline carriers retrench to their major hubs, some markets now have fewer direct options than existed prior to the low cost boom. Timings and frequencies are considered, in particular the extent to which services are a true alternative especially for business travellers. LCCs typically offer lower frequencies and more unsociable timings (e.g. late evening arrivals at remote airports) as they are more focused on providing the cheapest service rather than the most convenient schedule. Interesting findings on ‘monopoly’ services are presented (including alliances) - certain airlines have many more of these than others. Lufthansa has a significant number of sectors to itself whereas at the other extreme British Airways has direct competition on almost every route in its network. Ryanair and flybe have a higher proportion of monopoly routes than easyJet or Air Berlin. In the domestic US market it has become apparent since deregulation that better financial returns can come from dominating a large number of smaller markets rather than being heavily exposed in the major markets - which are hotly fought over. Regional niches that appear too thin for Ryanair to serve (with its all 189 seat 737-800 fleet) are identified. Fare comparisons in contrasting markets provide some insights to marketing and pricing strategies. Data sources used include OAG (schedules and capacity), AEA (traditional European airlines traffic by region), the UK CAA (airport, airline and route traffic plus survey information of passenger types) and ICAO (international route traffic and capacity by carrier). It is concluded that airlines often have different competitors depending on the context but in surprisingly many cases there are actually few or no direct substitutes. The competitive process set in train by deregulation of European air services in the 1990s is leading back to one of natural monopolies and oblique alternatives. It is the names of the main participants that have changed however!

Strings Concerto Competition, November 17, 2015

Concert Program

Concerto Competition Winners Showcase February 1, 2001

Concert Program for Concerto Competition Winners Showcase February 1, 2001

Resource security impacts men’s female breast size preferences

It has been suggested human female breast size may act as signal of fat reserves, which in turn indicates access to resources. Based on this perspective, two studies were conducted to test the hypothesis that men experiencing relative resource insecurity should perceive larger breast size as more physically attractive than men experiencing resource security. In Study 1, 266 men from three sites in Malaysia varying in relative socioeconomic status (high to low) rated a series of animated figures varying in breast size for physical attractiveness. Results showed that men from the low socioeconomic context rated larger breasts as more attractive than did men from the medium socioeconomic context, who in turn perceived larger breasts as attractive than men from a high socioeconomic context. Study 2 compared the breast size judgements of 66 hungry versus 58 satiated men within the same environmental context in Britain. Results showed that hungry men rated larger breasts as significantly more attractive than satiated men. Taken together, these studies provide evidence that resource security impacts upon men’s attractiveness ratings based on women’s breast size.

Do human resource practices enhance organizational commitment in SMEs with low employee satisfaction?

This paper considers a large matched employee–employer data set to estimate a model of organizational commitment. In particular, it focuses on the role of firm size and management formality to explain organizational commitment in British small and medium-sized enterprises (SMEs) with high and low levels of employee satisfaction. It is shown that size ‘in itself’ can explain differences in organizational commitment, and that organizational commitment tends to be higher in organizations with high employee satisfaction compared with organizations of similar size with low employee satisfaction. Crucially, the results suggest that formal human resource (HR) practices can be used as important tools to increase commitment and thus, potentially, effort and performance within underperforming SMEs with low employee satisfaction. However, formal HR practices commonly used by large firms may be unnecessary in SMEs which benefit from high employee satisfaction and positive employment relations within a context of informality.

The significance of Marx's value for strategy theory: competitive advantage and the issue of tautology within the resource-based view of the firm

Marxian thinking following the TSSI (Temporal Single System Interpretation) of Marx is applied to refute the allegation of a tautology in the resource-based view of the firm--paired with providing an explanation of how and why resources create value--, where resources are synonymous with Marx's categories of constant and variable capital. Refuting the allegation naturally leads to the holy grail of resource-based thinking, i.e. the question of what, conceptually, constitutes a firm's competitive advantage within the industry context. The article achieves its objectives by tying the resource-based view into Marx's theory value.

Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Intelligent electric vehicle heuristic for energy resource management using simulated annealing

The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .