Site-specific and geographical segmental social, environmental and ethical disclosures by the Ghanaian mining sector

Purpose: This paper explores the extent of site-specific and geographic segmental social, environmental and ethical reporting by mining companies operating in Ghana. We aim to: (i) establish a picture of corporate transparency relating to geographic segmentation of social, environmental and ethical reporting which is specific to operating sites and country of operation, and; (ii) gauge the impact of the introduction of integrated reporting on site-specific social, environmental and ethical reporting. Methodology/Approach: We conducted an interpretive content analysis of the annual/integrated reports of mining companies for the years 2009, 2010 and 2011 in order to extract site-specific social, environmental and ethical information relating to the companies’ mining operations in Ghana. Findings and Implications: We found that site-specific social, environmental and ethical reporting is extremely patchy and inconsistent between the companies’ reports studied. We also found that there was no information relating to certain sites, which were in operation, according to the Ghana Minerals Commission. This could simply be because operations were not in progress. Alternatively it could be that decisions are made concerning which site-specific information is reported according to a certain benchmark. One policy implication arising from this research is that IFRS should require geographic segmental reporting of material social, environmental and ethical information in order to bring IFRS into line with global developments in integrated reporting. Originality: Although there is a wealth of sustainability reporting research and an emergent literature on integrated reporting, there is currently no academic research exploring site-specific social, environmental and ethical reporting

The sustainable value approach: a clarifying and constructive comment

Recently, the original benchmarking methodology of the Sustainable Value approach became subjected to serious debate. While Kuosmanen and Kuosmanen (2009b) critically question its validity introducing productive efficiency theory, Figge and Hahn (2009) put forward that the implementation of productive efficiency theory severely conflicts with the original financial economics perspective of the Sustainable Value approach. We argue that the debate is very confusing because the original Sustainable Value approach presents two largely incompatible objectives. Nevertheless, we maintain that both ways of benchmarking could provide useful and moreover complementary insights. If one intends to present the overall resource efficiency of the firm from the investor's viewpoint, we recommend the original benchmarking methodology. If one on the other hand aspires to create a prescriptive tool setting up some sort of reallocation scheme, we advocate implementation of the productive efficiency theory. Although the discussion on benchmark application is certainly substantial, we should avoid the debate to become accordingly narrowed. Next to the benchmark concern, we see several other challenges considering the development of the Sustainable Value approach: (1) a more systematic resource selection, (2) the inclusion of the value chain and (3) additional analyses related to policy in order to increase interpretative power.

Intercomparison of shortwave radiative transfer schemes in global aerosol modeling: results from the AeroCom Radiative Transfer Experiment

In this study we examine the performance of 31 global model radiative transfer schemes in cloud-free conditions with prescribed gaseous absorbers and no aerosols (Rayleigh atmosphere), with prescribed scattering-only aerosols, and with more absorbing aerosols. Results are compared to benchmark results from high-resolution, multi-angular line-by-line radiation models. For purely scattering aerosols, model bias relative to the line-by-line models in the top-of-the atmosphere aerosol radiative forcing ranges from roughly −10 to 20%, with over- and underestimates of radiative cooling at lower and higher solar zenith angle, respectively. Inter-model diversity (relative standard deviation) increases from ~10 to 15% as solar zenith angle decreases. Inter-model diversity in atmospheric and surface forcing decreases with increased aerosol absorption, indicating that the treatment of multiple-scattering is more variable than aerosol absorption in the models considered. Aerosol radiative forcing results from multi-stream models are generally in better agreement with the line-by-line results than the simpler two-stream schemes. Considering radiative fluxes, model performance is generally the same or slightly better than results from previous radiation scheme intercomparisons. However, the inter-model diversity in aerosol radiative forcing remains large, primarily as a result of the treatment of multiple-scattering. Results indicate that global models that estimate aerosol radiative forcing with two-stream radiation schemes may be subject to persistent biases introduced by these schemes, particularly for regional aerosol forcing.

Towards a framework for managing IT-enabled change, sourcing and governance

In the resource-based view, organisations are represented by the sum of their physical, human and organisational assets, resources and capabilities. Operational capabilities maintain the status quo and allow an organisation to execute their existing business. Dynamic capabilities, otherwise, allow an organisation to change this status quo including a change of the operational ones. Competitive advantage, in this context, is an effect of continuously developing and reconfiguring these firm-specific assets through dynamic capabilities. Deciding where and how to source the core operational capabilities is a key success factor. Furthermore, developing its dynamic capabilities allows an organisation to effectively manage change its operational capabilities. Many organisations are asserted to have a high dependency on - as well as a high benefit from - the use of information technology (IT), making it a crucial and overarching resource. Furthermore, the IT function is assigned the role as a change enabler and so IT sourcing affects the capability of managing business change. IT sourcing means that organisations need to decide how to source their IT capabilities. Outsourcing of parts of the IT function will also outsource some of the IT capabilities and therefore some of the business capabilities. As a result, IT sourcing has an impact on the organisation's capabilities and consequently on the business success. And finally, a turbulent and fast moving business environment challenges organisations to effectively and efficiently managing business change. Our research builds on the existing theory of dynamic and operational capabilities by considering the interdependencies between the dynamic capabilities of business change and IT sourcing. Further it examines the decision-making oversight of these areas as implemented through IT governance. We introduce a new conceptual framework derived from the existing theory and extended through an illustrative case study conducted in a German bank. Under a philosophical paradigm of constructivism, we collected data from eight semi-structured interviews and used additional sources of evidence in form of annual accounts, strategy papers and IT benchmark reports. We applied an Interpretative Phenomenological Analysis (IPA), which emerged the superordinate themes for our tentative capabilities framework. An understanding of these interdependencies enables scholars and professionals to improve business success through effectively managing business change and evaluating the impact of IT sourcing decisions on the organisation's operational and dynamic capabilities.

An aggregate resource efficiency perspective on sustainability: a Sustainable Value application to the EU-15 countries

The Sustainable Value approach integrates the efficiency with regard to environmental, social and economic resources into a monetary indicator. It gained significant popularity as evidenced by diverse applications at the corporate level. However, its introduction as a measure adhering to the strong sustainability paradigm sparked an ardent debate. This study explores its validity as a macroeconomic strong sustainability measure by applying the Sustainable Value approach to the EU-15 countries. Concretely, we assessed environmental, social and economic resources in combination with the GDP for all EU-15 countries from 1995 to 2006 for three benchmark alternatives. The results show that several countries manage to adequately delink resource use from GDP growth. Furthermore, the remarkable difference in outcome between the national and EU-15 benchmark indicates a possible inefficiency of the current allocation of national resource ceilings imposed by the European institutions. Additionally, by using an effects model we argue that the service degree of the economy and governmental expenditures on social protection and research and development are important determinants of overall resource efficiency. Finally, we sketch out three necessary conditions to link the Sustainable Value approach to the strong sustainability paradigm.

How do I know if my forecasts are better? Using benchmarks in Hydrological ensemble prediction

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are ‘toughest to beat’ and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better.

Implication of methodological uncertainties for mid-Holocene sea surface temperature reconstructions

We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations. Further evaluations of potential subsurface and/or seasonal artifacts that may contribute to obscure the MH SST reconstructions are urgently needed to provide reliable benchmarks for model evaluations.

Willingness to pay for contagious bovine pleuropneumonia vaccination in Narok South District of Kenya

Contagious bovine pleuropneumonia (CBPP) is an economically important trans-boundary cattle disease which affects food security and livelihoods. A conjoint analysis–contingent valuation was carried out on 190 households in Narok South District of Kenya to measure willingness to pay (WTP) and demand for CBPP vaccine and vaccination as well as factors affecting WTP. The mean WTP was calculated at Kenya Shillings (KSh) 212.48 (USD 3.03) for vaccination using a vaccine with the characteristics that were preferred by the farmers (preferred vaccine and vaccination) and KSh −71.45 (USD −1.02) for the currently used vaccine and vaccination. The proportion of farmers willing to pay an amount greater than zero was 66.7% and 34.4% for the preferred and current vaccine and vaccination respectively. About one third (33.3%) of farmers would need to be compensated an average amount of KSh 1162.62 (USD 13.68) per animal to allow their cattle to be vaccinated against CBPP using the preferred vaccine and vaccination. About two-thirds (65.6%) of farmers would need to be compensated an average amount of KSh 853.72 (USD 12.20) per animal to allow their cattle to be vaccinated against CBPP using the current vaccine and vaccination. The total amount of compensation would be KSh 61.39 million (USD 0.88 million) for the preferred vaccine and vaccination and KSh 90.15 million (USD 1.29 million) for the current vaccine and vaccination. Demand curves drawn from individual WTP demonstrated that only 59% and 27% of cattle owners with a WTP greater than zero were willing to pay a benchmark cost of KSh 34.60 for the preferred and current vaccine respectively. WTP was negatively influenced by the attitude about household economic situation (p = 0.0078), presence of cross breeds in the herd (p < 0.0001) and years since CBPP had been experienced in the herd (p = 0.0375). It was positively influenced by education (p = 0.0251) and the practice of treating against CBPP (p = 0.0432). The benefit cost ratio (BCR) for CBPP vaccination was 2.9–6.1 depending on the vaccination programme. In conclusion, although a proportion of farmers was willing to pay, participation levels may be lower than those required to interrupt transmission of CBPP. Households with characteristics that influence WTP negatively need persuasion to participate in CBPP vaccination. It is economically worthwhile to vaccinate against CBPP. A benefit cost analysis (BCA) using aggregated WTP as benefits can be used as an alternative method to the traditional BCA which uses avoided production losses (new revenue) and costs saved as benefits.

The DACCIWA project: dynamics-aerosol-chemistry-cloud interactions in West Africa

Massive economic and population growth, and urbanization are expected to lead to a tripling of anthropogenic emissions in southern West Africa (SWA) between 2000 and 2030. However, the impacts of this on human health, ecosystems, food security, and the regional climate are largely unknown. An integrated assessment is challenging due to (a) a superposition of regional effects with global climate change, (b) a strong dependence on the variable West African monsoon, (c) incomplete scientific understanding of interactions between emissions, clouds, radiation, precipitation, and regional circulations, and (d) a lack of observations. This article provides an overview of the DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project. DACCIWA will conduct extensive fieldwork in SWA to collect high-quality observations, spanning the entire process chain from surface-based natural and anthropogenic emissions to impacts on health, ecosystems, and climate. Combining the resulting benchmark dataset with a wide range of modeling activities will allow (a) assessment of relevant physical, chemical, and biological processes, (b) improvement of the monitoring of climate and atmospheric composition from space, and (c) development of the next generation of weather and climate models capable of representing coupled cloud-aerosol interactions. The latter will ultimately contribute to reduce uncertainties in climate predictions. DACCIWA collaborates closely with operational centers, international programs, policy-makers, and users to actively guide sustainable future planning for West Africa. It is hoped that some of DACCIWA’s scientific findings and technical developments will be applicable to other monsoon regions.

The climate of Europe 6000 years ago

Palaeoclimates across Europe for 6000 y BP were estimated from pollen data using the modern pollen analogue technique constrained with lake-level data. The constraint consists of restricting the set of modern pollen samples considered as analogues of the fossil samples to those locations where the implied change in annual precipitation minus evapotranspiration (P–E) is consistent with the regional change in moisture balance as indicated by lakes. An artificial neural network was used for the spatial interpolation of lake-level changes to the pollen sites, and for mapping palaeoclimate anomalies. The climate variables reconstructed were mean temperature of the coldest month (T c ), growing degree days above 5  °C (GDD), moisture availability expressed as the ratio of actual to equilibrium evapotranspiration (α), and P–E. The constraint improved the spatial coherency of the reconstructed palaeoclimate anomalies, especially for P–E. The reconstructions indicate clear spatial and seasonal patterns of Holocene climate change, which can provide a quantitative benchmark for the evaluation of palaeoclimate model simulations. Winter temperatures (T c ) were 1–3 K greater than present in the far N and NE of Europe, but 2–4 K less than present in the Mediterranean region. Summer warmth (GDD) was greater than present in NW Europe (by 400–800 K day at the highest elevations) and in the Alps, but >400 K day less than present at lower elevations in S Europe. P–E was 50–250 mm less than present in NW Europe and the Alps, but α was 10–15% greater than present in S Europe and P–E was 50–200 mm greater than present in S and E Europe.

Towards improving the framework for probabilistic forecast evaluation

The evaluation of forecast performance plays a central role both in the interpretation and use of forecast systems and in their development. Different evaluation measures (scores) are available, often quantifying different characteristics of forecast performance. The properties of several proper scores for probabilistic forecast evaluation are contrasted and then used to interpret decadal probability hindcasts of global mean temperature. The Continuous Ranked Probability Score (CRPS), Proper Linear (PL) score, and IJ Good’s logarithmic score (also referred to as Ignorance) are compared; although information from all three may be useful, the logarithmic score has an immediate interpretation and is not insensitive to forecast busts. Neither CRPS nor PL is local; this is shown to produce counter intuitive evaluations by CRPS. Benchmark forecasts from empirical models like Dynamic Climatology place the scores in context. Comparing scores for forecast systems based on physical models (in this case HadCM3, from the CMIP5 decadal archive) against such benchmarks is more informative than internal comparison systems based on similar physical simulation models with each other. It is shown that a forecast system based on HadCM3 out performs Dynamic Climatology in decadal global mean temperature hindcasts; Dynamic Climatology previously outperformed a forecast system based upon HadGEM2 and reasons for these results are suggested. Forecasts of aggregate data (5-year means of global mean temperature) are, of course, narrower than forecasts of annual averages due to the suppression of variance; while the average “distance” between the forecasts and a target may be expected to decrease, little if any discernible improvement in probabilistic skill is achieved.

Margin squeeze: an above cost predatory pricing approach

We provide a new legal perspective for the antitrust analysis of margin squeeze conducts. Building on recent economic analysis, we explain why margin squeeze conducts should solely be evaluated under adjusted predatory pricing standards. The adjustment corresponds to an increase in the cost benchmark used in the predatory pricing test by including opportunity costs due to missed upstream sales. This can reduce both the risks of false-positives and false-negatives in margin squeeze cases. We justify this approach by explaining why classic arguments against above-cost predatory pricing typically do not hold in vertical structures where margin squeezes take place and by presenting case law evidence supporting this adjustment. Our approach can help to reconcile the divergent US and EU antitrust stances on margin squeeze.

Future changes of wind energy potentials over Europe in a large CMIP5 multi-model ensemble

A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

PETS 2014: dataset and challenge

This paper describes the dataset and vision challenges that form part of the PETS 2014 workshop. The datasets are multisensor sequences containing different activities around a parked vehicle in a parking lot. The dataset scenarios were filmed from multiple cameras mounted on the vehicle itself and involve multiple actors. In PETS2014 workshop, 22 acted scenarios are provided of abnormal behaviour around the parked vehicle. The aim in PETS 2014 is to provide a standard benchmark that indicates how detection, tracking, abnormality and behaviour analysis systems perform against a common database. The dataset specifically addresses several vision challenges corresponding to different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘simple’ event detection: the behaviour recognition of a single actor) and High-Level Video Analysis (‘complex’ event detection: the behaviour and interaction recognition of several actors).

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.