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An important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Annual capacity is used for long-term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes, so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. This study aims to provide an empirical analysis of airport capacity and demand, specifically focusing on insights related to air traffic design hours and the relationship between capacity and delay.

By reviewing the empirical relationships between hourly and annual air traffic volumes and between practical capacity and delay at 50 European airports during the period 2004–2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. The authors use information from several data sources, including EUROCONTROL, ACI and OAG. This study provides functional links between design hours and annual volumes for different airport clusters. Additionally, the authors appraise different daily traffic distribution patterns and their variation by hour of the day.

The clustering of airports with respect to their capacity, operational and traffic characteristics allows us to discover functional relationships between annual traffic and the percentage of traffic in the design hour. These relationships help the authors to propose empirical methods to derive expected traffic in design hours from annual volumes. The main conclusion is that the percentage of total annual traffic that is concentrated at the design hour maintains a predictable behavior through a “potential” adjustment with respect to the volume of annual traffic. Moreover, the authors provide an experimental link between capacity and delay so that peak hour figures can be related to factors that describe the quality of traffic operations.

The functional relationships between hourly and annual air traffic volumes and between capacity and delay, can be used to properly assess airport expansion projects or to optimize resource allocation tasks. This study offers new evidence on the nature of airport capacity and the dynamics of air traffic design hours and delay.

The purpose of this study was to design a renovation plan for a university campus building (Department of Electrical and Computer Engineering) with the aim to achieve nearly zero energy performance, ensuring a low specific demand (lower than 44 kWh/m²) and a high level of on-site renewable generation (equivalent to more than 20 per cent of the energy demand).

The baseline demand was characterized based on energy audits, on smart metering data and on the existing building management system data, showing a recent reduction of the electricity demand owing to some implemented measures. The renovation plan was then designed with two main measures, the total replacement of the actual lighting by LEDs and the installation of a photovoltaic system (PV) with 78.8 kWp coupled with an energy storage system with 100 kWh of lithium-ion batteries.

The designed renovation achieved energy savings of 20 per cent, with 27.5 per cent of the consumed energy supplied by the PV system. This will ensure a reduction of the specific energy of the building to only 30 kWh/m², with 42.4 per cent savings on the net-energy demand.

The designed renovation proves that it is possible to achieve nearly zero energy goals with cost-effective solutions, presenting the lighting renovation and the solar PV generation system a payback of 2.3 and 6.9 years, respectively.

This study innovated by defining ambitious goals to achieve nearly zero energy levels and presenting a design based on a comprehensive lighting retrofit and PV generation, whereas other studies are mostly based on envelope refurbishment and behaviour changes.

Ethiopia’s energy sector faces critical challenges to meeting steadily increasing energy demand given limited infrastructure, heavy reliance on hydroelectric power and underdevelopment of alternative energy resources. The purpose of this paper was to identify optimal least cost investment decisions for integrated energy source diversification. The authors seek to contribute to the relevant literature by paying particular attention to the role of public policy for promoting renewable energy investment and to better understand future energy security implications of various sources of uncertainty.

The authors created a dynamic linear programming model using General Algebraic Modelling System software to explore the national energy security implications of uncertainties associated with increasing technological advances and efficiency, and climate change scenarios.

To cope with the impacts of drought expected from future climate change on hydroelectric power production, Ethiopia would need to invest in the development of alternative energy resources. Such investment would not only enhance the sustainability and reliability of energy production but also increase costs. Greater rates of technological and efficiency innovations, however, were found to improve electricity diversification and reduce production costs and shadow prices or resource scarcity, and are thus key for enhancing energy security and reducing the risks posed by drought.

The dynamic linear programming model by the authors represents a flexible sector modelling tool for exploring the sustainability and efficiency of energy resource development pathways and evaluating the effects of different sources of uncertainty on the energy sector.

Examines two leading cases of Austrian organisations providing employee self‐rostering for work‐family balance, a little‐reported area of employment relations innovation. These cases highlight that such schemes can be successful for managements and employees even in highly routine, mechanised production environments. Asks what sorts of factors encourage management to adopt such schemes and whether different factors encourage their retention over time. In both cases, external environmental factors, internal environmental adaptation and management's embrace of high commitment strategies all influenced managerial decision making. However, these three sets of factors operated in different degrees and in different sequences between the two cases. In neither case was the institutional environment of any real importance.

Study conditions of empirical publications on time series modeling and forecasting of electricity prices vary widely, making it difficult to generalize results. The key purpose of the present study is to offer a comparison of different model types and modeling conditions regarding their forecasting performance.

The authors analyze the forecasting performance of AR (autoregressive), MA (moving average), ARMA (autoregressive moving average) and GARCH (generalized autoregressive moving average) models with and without the explanatory variables, that is, power consumption and power generation from wind and solar. Additionally, the authors vary the detailed model specifications (choice of lag-terms) and transformations (using differenced time series or log-prices) of data and, thereby, obtain individual results from various perspectives. All analyses are conducted on rolling calibrating and testing time horizons between 2010 and 2014 on the German/Austrian electricity spot market.

The main result is that the best forecasts are generated by ARMAX models after spike preprocessing and differencing the data.

The present study extends the existing literature on electricity price forecasting by conducting a comprehensive analysis of the forecasting performance of different time series models under varying market conditions. The results of this study, in general, support the decision-making of electricity spot price modelers or forecasting tools regarding the choice of data transformation, segmentation and the specific model selection.

The paper aims to clarify the relationship between energy flexibility and building components and technologies. It determines the energy flexibility potential of buildings in relation to their physical characteristics and heat supply systems with respect to external boundary conditions.

The emphasis of the evaluation is based on the timing and the amount of shiftable and storable thermal loads in buildings under defined indoor thermal comfort conditions. Dynamic building simulation is used to evaluate the potential of selected building characteristics to shift heating loads away from peak demand periods. Insights on the energy flexibility potential of individual technologies are gained by examining the thermal behaviour of single-zone simulation models as different input parameters are varied. For this purpose, parameters such as envelope qualities, construction materials, control systems for heating are modified.

The paper provides a comprehensive understanding of the influence of the different building parameters and their variations on their energy shifting potential under “laboratory conditions” with steady boundaries. It suggests that the investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the heating load of a building, also influence the resulting potential for energy flexibility. The findings show that the combination of a slowly reacting heat transfer system, such as concrete core activation and a readily available storage mass in the room, and a high insulation standard proved to have a high potential to shift heating loads.

In this paper, energy-flexible components were evaluated in a steady-state simulation approach. Outside temperature, solar irradiation and internal loads over the simulation duration were set constant over time to provide laboratory conditions for the potential analysis. On the basis of both duration and performance of the load shifting or storage event, the components were then quantified in a parametric simulation. The determined energy flexibility is directly related to the power of the heating, cooling, hot water and ventilation system, which can be switched on or off. In general, it can be seen that high power (high loads) demand usually can be switched on and off for a short duration, and low power demand usually for a longer duration. The investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the load of a building, also influence the resulting potential for energy flexibility. Higher insulation standards, for example, lead to lower loads that can be switched on or off, but increase the duration of the event (flexibility time). So that, in particular, the shiftable load potential is low but results in a long switch-off duration. Furthermore, passive storage potential in buildings like the storage mass inside the room and the type of heat/cooling transfer system can affect the flexibility potential by more than three times. Especially the combination of a high storage mass and a concrete core heat transfer system can significantly increase the flexibility.

We introduce and analyze an innovative transportation system called flexible mobility on demand (FMOD). FMOD provides a menu of optimized travel options in real-time. Practical considerations related to the business model for FMOD are taken into account as a pre-study for the pilot that will be conducted in Japan.

A modeling framework of FMOD is developed that integrates scheduling, routing, assortment optimization, and choice modeling methodologies. An assortment optimization model is developed with an objective function to maximize operator profit and consumer surplus.

The FMOD system is analyzed through simulation experiments in a Japanese case study. Simulations are presented for Hino city in Tokyo with different numbers of vehicles in the fleet. This analysis provides insights about the fleet size necessary to maintain reasonable levels of operator profit and consumer surplus.

We consider a business model for FMOD that offers flexibility to the operator in terms of who provides resources. The resources are managed with dedicated and non-dedicated services. The experiment indicates that operators can determine the size of the dedicated fleet based on an objective function that maximizes operator profit and passenger satisfaction.

Investigates the increased waiting time costs imposed on society due to inappropriate use of the emergency department by patients seeking non‐emergency or primary care. Proposes a simple economic model to illustrate the effect of this misuse at a public or not‐for‐profit hospital. Provides evidence that non‐emergency patients contribute to lengthy delays in the ER for all classes of patients. Proposes a priority queuing model to reduce average waiting times.

Operations management involves utilizing given resources as efficiently as possible to deliver services to customers and meet business goals. Developing efficient business operations requires a hospitality organization to design efficient service environments, as part of its mission. This chapter articulates the key design and planning strategies for the development of a successful hospitality organization. The first section covers the process of location selection, as the most important factor leading to the success of a hospitality organization. The second section discusses strategies for estimating the number of users (service employees and customers) during peak and idle times to justify a costly financial investment. The third section concerns the readers with the topic of layout planning, with the goal of service optimization for a targeted number of customers. The fourth section deliberates workflow conditions, and finally, the last section addresses the ambience and design of the physical hospitality environment, which is crucial for customer evaluation of a hospitality organization as it creates a first impression.