Zoekresultaten

Designing Light Electric Vehicles for urban freight transport

Dutch Sport Federations Changing into Market Oriented Organizations: The Institutional Theory Applied on Three Case Studies

In 2005 and 2006, almost sixty Dutch National Sport Federations (NSFs) participated in a special program for creating a marketing strategy for the next four years. This program was initiated and organized by NOC*NSF (the Dutch Olympic Umbrella Sports Organization). The NSFs had to joint the project to receive funds. For most of them it was the first time they seriously analyzed the market with the aim of developing new programs. The purpose of this paper is to explore to what extent Dutch NSFs are capable to change their structures to become more market oriented and more market responsive in order to write strategic plans. The changed structures are investigated using the "institutional theory" (Tolbert & Zucker, 1996) and are explained by exogenous (market context and institutional context) and endogenous (interests, values, power dependencies, and capacity for action) dynamics from the neo-institutionalist framework (Greenwood & Hinings, 1996). In 2005 NSFs were expected to be in a pre-institutionalized stage, i.e. they were supposed to develop new organizational structures in response to specific problems (Kikulis, 2000). Now, approximately 1½ years after finishing their strategies, the question arises whether they have reached the semi-institutional stage, i.e. whether the new structures or actions are diffused across organizations, yet still subject to change and whether old structures are yet eroding (Kikulis, 2000). Methods Studying the intended structural change of NSFs requires an in-depth study of their social reality and the reactions and interpretations of involved actors, including their applied meanings to certain situations. Greenwood & Hinings (1996) plead for detailed comparative case-studies when studying institutional changes. Therefore three NSFs has been selected: The Royal Dutch Korfball Federation (KorfFed); The Royal Dutch Billiards Federation (BillFed); and the Dutch Jeu de Boules Federation (JeuFed). These three federations differ on size, amount of housed sports, number of associated clubs, sorts of intermediary decision making bodies, employed FTE's, and more. Therefore it is expected that the tempo of institutionalization of the new, market oriented, structures, will differ among them. Sugden & Tomlinson (2002) developed a multi-method style of qualitative research for making sense of the deep, inside information below the surface of everyday life. They call it the "Brighton method. Applying the Brighton method for this research implies that the three cases will be studied with respect to their history, their present marketing actions, their results and the changes in their organization. In-depth interviews, document analysis (policy plans, marketing plans and more), and where possible observations and participations are used to create a critical and investigative view of the organizations in change. Results The KorfFed used the marketing program to further develop existing programs. Although the outcomes of these programs were not new, the program has opened the eyes of the president, director and staff members. They are now conscious of the urgency of a market orientation, and a marketing orientation (a marketing position has already been introduced), and they see opportunities in attracting non-competition playing korfball players. They have, however, not yet reached the phase of semi-institutionalization of the market oriented structures. This can be concluded from the following: - The organization still has an ad-hoc character; - Some board members still make decisions based on their own insights rather than on information from the professional part of the organization; - Decisions to start programs are still grounded on subsidy possibilities rather than on market possibilities. Interest dissatisfaction and power dependencies are the main dynamics that form barriers in the planned organizational change. The BillFed is a federation that covers four disciplines, i.e. pool, snooker, carom, and billiard 3 cushions. The federation used to act upon these four disciplines. The marketing program has made clear that the BillFed should act upon target groups instead of on these disciplines. Therefore, the federation created a vision to reach youth, young adults, as also elderly people. Carrying out this new vision requires a market orientated structure (focus on target groups) instead of an internal orientated structure (focus on discipline groups). This new vision is created on an upper level (general board together with professional staff) in the organization. This federation also introduced a professional marketing position. Unfortunately, the underlying layers remain slightly passive and are not willing to work along the new structures, which mean that the new structures have not been diffused across the whole organization. Interest dissatisfaction, value commitments and power dependencies are the problematic dynamics. The JeuFed used to have a strong competition and tournament (internal) orientation, while many jeu-de-boules players play the game just for fun. The marketing program has created the insight that the just-for-fun players are also an important target group. Hence, 3 projects are developed to make club membership more attractive for all jeu-de-boules players. Since the federation never worked with projects before, they just found out that implementing projects such as these requires new structures. The JeuFed has just arrived in the pre-institutionalized phase, still far away from the semi-institutionalized chapter. Power dependencies and a lack of capacity for change are influencing dynamics in this case. Discussion Although it is already 1½ years ago that Dutch NSFs finished their marketing program, in none of the described cases the new structures have reached the semi-institutional stage. These new structures or actions are not yet diffused across the organizations, and the old structures are not eroding. In all three cases another combination of endogenous dynamics are influencing the process of organizational change. Continuing research is needed to find out whether these federations will ever reach the next stage of institutionalization and which dynamics will play an important role.

Dutch Sport Federations Changing into Market Oriented Organizations: The Institutional Theory Applied on Three Case Studies

In 2005 and 2006, almost sixty Dutch National Sport Federations (NSFs) participated in a special program for creating a marketing strategy for the next four years. This program was initiated and organized by NOC*NSF (the Dutch Olympic Umbrella Sports Organization). The NSFs had to joint the project to receive funds. For most of them it was the first time they seriously analyzed the market with the aim of developing new programs. The purpose of this paper is to explore to what extent Dutch NSFs are capable to change their structures to become more market oriented and more market responsive in order to write strategic plans. The changed structures are investigated using the "institutional theory" (Tolbert & Zucker, 1996) and are explained by exogenous (market context and institutional context) and endogenous (interests, values, power dependencies, and capacity for action) dynamics from the neo-institutionalist framework (Greenwood & Hinings, 1996). In 2005 NSFs were expected to be in a pre-institutionalized stage, i.e. they were supposed to develop new organizational structures in response to specific problems (Kikulis, 2000). Now, approximately 1½ years after finishing their strategies, the question arises whether they have reached the semi-institutional stage, i.e. whether the new structures or actions are diffused across organizations, yet still subject to change and whether old structures are yet eroding (Kikulis, 2000). Methods Studying the intended structural change of NSFs requires an in-depth study of their social reality and the reactions and interpretations of involved actors, including their applied meanings to certain situations. Greenwood & Hinings (1996) plead for detailed comparative case-studies when studying institutional changes. Therefore three NSFs has been selected: The Royal Dutch Korfball Federation (KorfFed); The Royal Dutch Billiards Federation (BillFed); and the Dutch Jeu de Boules Federation (JeuFed). These three federations differ on size, amount of housed sports, number of associated clubs, sorts of intermediary decision making bodies, employed FTE's, and more. Therefore it is expected that the tempo of institutionalization of the new, market oriented, structures, will differ among them. Sugden & Tomlinson (2002) developed a multi-method style of qualitative research for making sense of the deep, inside information below the surface of everyday life. They call it the "Brighton method. Applying the Brighton method for this research implies that the three cases will be studied with respect to their history, their present marketing actions, their results and the changes in their organization. In-depth interviews, document analysis (policy plans, marketing plans and more), and where possible observations and participations are used to create a critical and investigative view of the organizations in change. Results The KorfFed used the marketing program to further develop existing programs. Although the outcomes of these programs were not new, the program has opened the eyes of the president, director and staff members. They are now conscious of the urgency of a market orientation, and a marketing orientation (a marketing position has already been introduced), and they see opportunities in attracting non-competition playing korfball players. They have, however, not yet reached the phase of semi-institutionalization of the market oriented structures. This can be concluded from the following: - The organization still has an ad-hoc character; - Some board members still make decisions based on their own insights rather than on information from the professional part of the organization; - Decisions to start programs are still grounded on subsidy possibilities rather than on market possibilities. Interest dissatisfaction and power dependencies are the main dynamics that form barriers in the planned organizational change. The BillFed is a federation that covers four disciplines, i.e. pool, snooker, carom, and billiard 3 cushions. The federation used to act upon these four disciplines. The marketing program has made clear that the BillFed should act upon target groups instead of on these disciplines. Therefore, the federation created a vision to reach youth, young adults, as also elderly people. Carrying out this new vision requires a market orientated structure (focus on target groups) instead of an internal orientated structure (focus on discipline groups). This new vision is created on an upper level (general board together with professional staff) in the organization. This federation also introduced a professional marketing position. Unfortunately, the underlying layers remain slightly passive and are not willing to work along the new structures, which mean that the new structures have not been diffused across the whole organization. Interest dissatisfaction, value commitments and power dependencies are the problematic dynamics. The JeuFed used to have a strong competition and tournament (internal) orientation, while many jeu-de-boules players play the game just for fun. The marketing program has created the insight that the just-for-fun players are also an important target group. Hence, 3 projects are developed to make club membership more attractive for all jeu-de-boules players. Since the federation never worked with projects before, they just found out that implementing projects such as these requires new structures. The JeuFed has just arrived in the pre-institutionalized phase, still far away from the semi-institutionalized chapter. Power dependencies and a lack of capacity for change are influencing dynamics in this case. Discussion Although it is already 1½ years ago that Dutch NSFs finished their marketing program, in none of the described cases the new structures have reached the semi-institutional stage. These new structures or actions are not yet diffused across the organizations, and the old structures are not eroding. In all three cases another combination of endogenous dynamics are influencing the process of organizational change. Continuing research is needed to find out whether these federations will ever reach the next stage of institutionalization and which dynamics will play an important role.

Building and building systems energy prediction models to enhance energy flexibility control

The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.

Building and building systems energy prediction models to enhance energy flexibility control

The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.

Three priorities for evidence-based governance of heatwave events in Europe

In this opinion piece, we establish some key priorities for evidence-based governance to address the increasing threat of heatwave events in Europe, particularly for human health. According to the European Environment Agency (EEA) [1], Europe is warming faster than the global average. The year 2020 was the warmest year in Europe since the instrumental records began, with the range of anomaly between 2.53˚C and 2.71˚C above the pre-industrial levels. Particularly high warming has been observed over eastern Europe, Scandinavia and the eastern part of the Iberian Peninsula. Climate change-related heatwaves are becoming a significant threat to human health and necessitate early action [2]. While financial resources and technological capacities are crucial to aid (local) governments in adapting to and proactively mitigating the threats posed by heatwaves, they are not enough [3]. Akin to flood responses, European countries must prepare for large-scale evacuations of vulnerable citizens (especially older adults living alone) from their homes. Here, we outline three priorities for Europe in the governance domain. These priorities encompass developing and rolling-out heat-health action plans, a stronger role for European Union institutions in regional heatwave governance, and creating a sense of urgency by developing innovative ways of communicating research findings to relevant policy makers and citizens.