A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England

The UK Government's Department for Energy and Climate Change has been investigating the feasibility of developing a national energy efficiency data framework covering both domestic and non-domestic buildings. Working closely with the Energy Saving Trust and energy suppliers, the aim is to develop a data framework to monitor changes in energy efficiency, develop and evaluate programmes and improve information available to consumers. Key applications of the framework are to understand trends in built stock energy use, identify drivers and evaluate the success of different policies. For energy suppliers, it could identify what energy uses are growing, in which sectors and why. This would help with market segmentation and the design of products. For building professionals, it could supplement energy audits and modelling of end-use consumption with real data and support the generation of accurate and comprehensive benchmarks. This paper critically examines the results of the first phase of work to construct a national energy efficiency data-framework for the domestic sector focusing on two specific issues: (a) drivers of domestic energy consumption in terms of the physical nature of the dwellings and socio-economic characteristics of occupants and (b) the impact of energy efficiency measures on energy consumption.

Scale sensitivity of drivers of environmental change across Europe

The development of effective environmental management plans and policies requires a sound understanding of the driving forces involved in shaping and altering the structure and function of ecosystems. However, driving forces, especially anthropogenic ones, are defined and operate at multiple administrative levels, which do not always match ecological scales. This paper presents an innovative methodology of analysing drivers of change by developing a typology of scale sensitivity of drivers that classifies and describes the way they operate across multiple administrative levels. Scale sensitivity varies considerably among drivers, which can be classified into five broad categories depending on the response of ‘evenness’ and ‘intensity change’ when moving across administrative levels. Indirect drivers tend to show low scale sensitivity, whereas direct drivers show high scale sensitivity, as they operate in a non-linear way across the administrative scale. Thus policies addressing direct drivers of change, in particular, need to take scale into consideration during their formulation. Moreover, such policies must have a strong spatial focus, which can be achieved either by encouraging local–regional policy making or by introducing high flexibility in (inter)national policies to accommodate increased differentiation at lower administrative levels. High quality data is available for several drivers, however, the availability of consistent data at all levels for non-anthropogenic drivers is a major constraint to mapping and assessing their scale sensitivity. This lack of data may hinder effective policy making for environmental management, since it restricts the ability to fully account for scale sensitivity of natural drivers in policy design.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

The role of horizontal resolution in simulating drivers of the global hydrological cycle

The role of atmospheric general circulation model (AGCM) horizontal resolution in representing the global energy budget and hydrological cycle is assessed, with the aim of improving the understanding of model uncertainties in simulating the hydrological cycle. We use two AGCMs from the UK Met Office Hadley Centre: HadGEM1-A at resolutions ranging from 270 to 60 km, and HadGEM3-A ranging from 135 to 25 km. The models exhibit a stable hydrological cycle, although too intense compared to reanalyses and observations. This over-intensity is explained by excess surface shortwave radiation, a common error in general circulation models (GCMs). This result is insensitive to resolution. However, as resolution is increased, precipitation decreases over the ocean and increases over the land. This is associated with an increase in atmospheric moisture transport from ocean to land, which changes the partitioning of moisture fluxes that contribute to precipitation over land from less local to more non-local moisture sources. The results start to converge at 60-km resolution, which underlines the excessive reliance of the mean hydrological cycle on physical parametrization (local unresolved processes) versus model dynamics (large-scale resolved processes) in coarser HadGEM1 and HadGEM3 GCMs. This finding may be valid for other GCMs, showing the necessity to analyze other chains of GCMs that may become available in the future with such a range of horizontal resolutions. Our finding supports the hypothesis that heterogeneity in model parametrization is one of the underlying causes of model disagreement in the Coupled Model Intercomparison Project (CMIP) exercises.

The drivers of multinational enterprise subsidiary entrepreneurship in China: a new resource-based view perspective

This paper extends the resource-based view (RBV) of the firm, as applied to multinational enterprises (MNEs), by distinguishing between two critical resource dimensions, namely relative resource superiority (capabilities) and slack. Both dimensions, in concert with specific environmental conditions, are required to increase entrepreneurial activities. We propose distinct configurations (three-way moderation effects) of capabilities, slack, and environmental factors (i.e. dynamism and hostility) to explain entrepreneurship. Using survey data from 66 Canadian subsidiaries operating in China, we find that higher subsidiary entrepreneurship requires both HR slack and strong downstream capabilities in subsidiaries, subject to the industry environment being dynamic and benign. However, high HR slack alone, in a dynamic and benign environment, but without the presence of strong capabilities, actually triggers the fewest initiatives, with HR slack redirected from entrepreneurial experimentation towards complacency and inefficiency. This paper has major implications for MNEs seeking to increase subsidiary entrepreneurship in fast growing emerging markets.

Drivers of in-group and out-of-group electronic word-of-mouth (eWOM)

Purpose – The purpose of this study is to address a recent call for additional research on electronic word-of-mouth (eWOM). In response to this call, this study draws on the social network paradigm and the uses and gratification theory (UGT) to propose and empirically test a conceptual framework of key drivers of two types of eWOM, namely in-group and out-of-group. Design/methodology/approach – The proposed model, which examines the impact of usage motivations on eWOM in-group and eWOM out-of-group, is tested in a sample of 302 internet users in Portugal. Findings – Results from the survey show that the different drivers (i.e. mood-enhancement, escapism, experiential learning and social interaction) vary in terms of their impact on the two different types of eWOM. Surprisingly, while results show a positive relationship between experiential learning and eWOM out-of-group, no relationship is found between experiential learning and eWOM in-group. Research limitations/implications – This is the first study investigating the drivers of both eWOM in-group and eWOM out-of-group. Additional research in this area will contribute to the development of a general theory of eWOM. Practical implications – By understanding the drivers of different eWOM types, this study provides guidance to marketing managers on how to allocate resources more efficiently in order to achieve the company's strategic objectives. Originality/value – No published study has investigated the determinants of these two types of eWOM. This is the first study offering empirical considerations of how the various drivers differentially impact eWOM in-group and eWOM out-of-group.

Key drivers of frontline employee generation of ideas for customer service improvement

Anchored in the service-dominant logic and service innovation literature, this study investigates the drivers of employee generation of ideas for service improvement (GISI). Employee GISI focuses on customer needs and providing the exact service wanted by customers. GISI should enhance competitive advantage and organizational success (cf. Berry et al. 2006; Wang and Netemeyer 2004). Despite its importance, there is little research on the idea generation stage of the service development process (Chai, Zhang, and Tan 2005). This study contributes to the service field by providing the first empirical evaluation of the drivers of GISI. It also investigates a new explanatory determinant of reading of customer needs, namely, perceived organizational support (POS), and an outcome of POS, in the form of emotional exhaustion. Results show that the major driver of GISI is reading of customer needs by employees followed by affective organizational commitment and job satisfaction. This research provides several new and important insights for service management practice by suggesting that special care should be put into selecting and recruiting employees who have the ability to read customer needs. Additionally, organizations should invest in creating work environments that encourage and reward the flow of ideas for service improvement

Individual assets, market structure and the drivers of return

Much UK research and market practice on portfolio strategy and performance benchmarking relies on a sector‐geography subdivision of properties. Prior tests of the appropriateness of such divisions have generally relied on aggregated or hypothetical return data. However, the results found in aggregate may not hold when individual buildings are considered. This paper makes use of a dataset of individual UK property returns. A series of multivariate exploratory statistical techniques are utilised to test whether the return behaviour of individual properties conforms to their a priori grouping. The results suggest strongly that neither standard sector nor regional classifications provide a clear demarcation of individual building performance. This has important implications for both portfolio strategy and performance measurement and benchmarking. However, there do appear to be size and yield effects that help explain return behaviour at the property level.

Extreme rainfall variability in Australia: Patterns, drivers and predictability

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an Empirical Orthogonal Teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. We illustrate that, as with mean rainfall, the El Niño-Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool-season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean Dipole and Southern Annular Mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter than average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with mid-latitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anti-cyclone. Tropical cyclone activity is observed to have significant relationships with some warm season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.

The drivers of projected North Atlantic sea level change

Sea level change predicted by the CMIP5 atmosphere–ocean general circulation models (AOGCMs) is not spatially homogeneous. In particular, the sea level change in the North Atlantic is usually characterised by a meridional dipole pattern with higher sea level rise north of 40°N and lower to the south. The spread among models is also high in that region. Here we evaluate the role of surface buoyancy fluxes by carrying out simulations with the FAMOUS low-resolution AOGCM forced by surface freshwater and heat flux changes from CO2-forced climate change experiments with CMIP5 AOGCMs, and by a standard idealised surface freshwater flux applied in the North Atlantic. Both kinds of buoyancy flux change lead to the formation of the sea level dipole pattern, although the effect of the heat flux has a greater magnitude, and is the main cause of the spread of results among the CMIP5 models. By using passive tracers in FAMOUS to distinguish between additional and redistributed buoyancy, we show that the enhanced sea level rise north of 40°N is mainly due to the direct steric effect (the reduction of sea water density) caused by adding heat or freshwater locally. The surface buoyancy forcing also causes a weakening of the Atlantic meridional overturning circulation, and the consequent reduction of the northward ocean heat transport imposes a negative tendency on sea level rise, producing the reduced rise south of 40°N. However, unlike previous authors, we find that this indirect effect of buoyancy forcing is generally less important than the direct one, except in a narrow band along the east coast of the US, where it plays a major role and leads to sea level rise, as found by previous authors.

Drivers of change in mountain farming in Slovakia: from socialist collectivisation to the Common Agricultural Policy

The transformations in Slovak agriculture from the 1950s to the present day, considering both the generic (National and EU) and site-specific (local) drivers of landscape change, were analysed in five mountain study areas in the country. An interdisciplinary approach included analysis of population trends, evaluation of land use and landscape change combined with exploration of the perceptions of local stakeholders and results of previous biodiversity studies. The generic processes active from the 1950s to 1970s were critical for all study areas with impacts lasting right up until the present day. Agricultural collectivisation, agricultural intensification and land abandonment had negative effects in all study areas. However, the precise impacts on the landscape were different in the different study areas due to site-specific attributes (e.g. population trends, geographic localisation and local attitudes and opportunities), and these played a decisive role in determining the trajectory of change. Regional contrasts in rural development between these territories have increased in the last two decades, also due to the imperfect preconditions of governmental support. The recent Common Agricultural Policy developments are focused on maintenance of intensive large-scale farming rather than direct enhancement of agro-biodiversity and rural development at the local scale. In this context, local, site-specific attributes can and must form an essential part of rural development plans, to meet the demands for management of the diversity of agricultural mountain landscapes and facilitate the multifunctional role of agriculture.

Drivers of in‐group and out‐of‐group electronic word‐of‐mouth (eWOM)

Purpose– The purpose of this study is to address a recent call for additional research on electronic word‐of‐mouth (eWOM). In response to this call, this study draws on the social network paradigm and the uses and gratification theory (UGT) to propose and empirically test a conceptual framework of key drivers of two types of eWOM, namely in‐group and out‐of‐group. Design/methodology/approach– The proposed model, which examines the impact of usage motivations on eWOM in‐group and eWOM out‐of‐group, is tested in a sample of 302 internet users in Portugal. Findings– Results from the survey show that the different drivers (i.e. mood‐enhancement, escapism, experiential learning and social interaction) vary in terms of their impact on the two different types of eWOM. Surprisingly, while results show a positive relationship between experiential learning and eWOM out‐of‐group, no relationship is found between experiential learning and eWOM in‐group. Research limitations/implications– This is the first study investigating the drivers of both eWOM in‐group and eWOM out‐of‐group. Additional research in this area will contribute to the development of a general theory of eWOM. Practical implications– By understanding the drivers of different eWOM types, this study provides guidance to marketing managers on how to allocate resources more efficiently in order to achieve the company's strategic objectives. Originality/value– No published study has investigated the determinants of these two types of eWOM. This is the first study offering empirical considerations of how the various drivers differentially impact eWOM in‐group and eWOM out‐of‐group.

The economics of enhanced landfill mining: private and societal performance drivers

This paper addresses the economics of Enhanced Landfill Mining (ELFM) both from a private point of view as well as from a society perspective. The private potential is assessed using a case study for which an investment model is developed to identify the impact of a broad range of parameters on the profitability of ELFM. We found that especially variations in Waste-to-Energy (WtE efficiency, electricity price, CO2-price, WtE investment and operational costs) and ELFM support explain the variation in economic profitability measured by the Internal Rate of Return. To overcome site-specific parameters we also evaluated the regional ELFM potential for the densely populated and industrial region of Flanders (north of Belgium). The total number of potential ELFM sites was estimated using a 5-step procedure and a simulation tool was developed to trade-off private costs and benefits. The analysis shows that there is a substantial economic potential for ELFM projects on the wider regional level. Furthermore, this paper also reviews the costs and benefits from a broader perspective. The carbon footprint of the case study was mapped in order to assess the project’s net impact in terms of greenhouse gas emissions. Also the impacts of nature restoration, soil remediation, resource scarcity and reduced import dependence were valued so that they can be used in future social cost-benefit analysis. Given the complex trade-off between economic, social and environmental issues of ELFM projects, we conclude that further refinement of the methodological framework and the development of the integrated decision tools supporting private and public actors, are necessary.