Equity Valuation Using Multiples: An Empirical Investigation (Schriften zum europäischen Management)

Learn more about Amazon Prime. Get fast, free shipping with Amazon Prime. Get to Know Us. English Choose a language for shopping. Explore the Home Gift Guide. Amazon Music Stream millions of songs. Amazon Advertising Find, attract, and engage customers. Amazon Drive Cloud storage from Amazon. Alexa Actionable Analytics for the Web.

AmazonGlobal Ship Orders Internationally. Amazon Inspire Digital Educational Resources. Amazon Rapids Fun stories for kids on the go. Amazon Restaurants Food delivery from local restaurants. ComiXology Thousands of Digital Comics. East Dane Designer Men's Fashion. Shopbop Designer Fashion Brands. Withoutabox Submit to Film Festivals. Amazon Renewed Refurbished products with a warranty.

Amazon Second Chance Pass it on, trade it in, give it a second life. Alternatively, we computed DI iw with a local overall mortality rate weighted by different impact scores adapted from Fock, a.

Personalized Telehealth in the Future: A Global Research Agenda

We compiled for each grid cell the respective measures of recovery, mortality, and benthic disturbance in ArcGIS Thus, DI and DI w describe spatially disaggregated alternative assumptions of the relative state of benthic disturbance, based on the average bottom trawling effort from to This final step corresponds to the evaluation of the risk of worsening the current state of benthic disturbance due to future MSP measures in the German EEZ. Our scenario applies to planned OWD sites, where, in case of their realization, extensive areas would be closed for fishery.

Effects on the fleets using otter boards are negligible. Thus, we defined the following spatial management scenario: We combined a BN with GIS to predict changing likelihoods of benthic disturbance states due to different trawling effort patterns. We used the Netica software system www. The BN model contains the deterministic relationships described above and reflects the causal links of all parameters required to calculate the unweighted and weighted disturbance indicator Figure 3.

Benthic communities and the fishing frequencies of the six fleets are parent nodes and are considered to be independent from each other. Each parent node has discrete states e. Fleet-specific mortality rates are represented as functions of the respective fishing frequencies and the estimated decline rates for each benthic community. The overall mortality rate and weighted mortality rate are child nodes of the fleet-specific mortality rates and are defined by their deterministic relationships with their parent nodes.

Recover frequency, recovery time, and abundance decline are child nodes of the benthic communities. The likelihoods of the states of the disturbance indicator nodes are predicted as a function of the likelihood of the overall relative mortality rates unweighted and weighted and the predicted recovery by the benthic community. We also assessed the sensitivity of the disturbance indictor node DI to the influence of the parent nodes by calculating the variance reduction.

1. !
2. .
3. Polonaise No. 4 in C Minor, Op. 40, No. 2.

The latter describes how well the predictions of the BN match the actual cases and is defined as the mean probability value of a given state averaged over all cases. Assuming that the fishing effort will relocate in areas with already high fishing intensity, the probability of a unit area experiencing the highest level of fishing pressures or being in state 3 must increase.

We inferred subsequently the changes of the probability distributions of the DI and DI w nodes. It is worth mentioning that the here defined spatial shift in fishing effort reflects one out of many possible changes to the prior distributions of the parent nodes reflecting the fishing frequencies of the six fleets.

The results of the structured literature review of 32 papers are summarized in Table 3. Most studies focused on one or two stressors with a clear emphasis on fisheries; other activities included aggregate mining and marine traffic. Cumulative pressures were analysed in a quarter of all examined studies, mostly assuming additive effects. We observed that the measure of sensitivity of ecosystem components or indicators was mostly related to a metric derived from a model output which based either on empirical data or expert knowledge.

In contrast, a quarter of the reviewed studies were based on expert knowledge and three studies being based exclusively on empirical data. Another important result was that the terminology of risk, vulnerability, and impact varied greatly across the studies and has been used synonymously. Despite this variation in terminology, the components to calculate a measure of vulnerability or impact have been similar across all cases. All studies defined vulnerability or impact as a function of a measure of ecosystem sensitivity and the occurrence probability and magnitude of a stressor or pressure.

However, the concepts of resistance and resilience of ecosystem components were only considered in a few studies. More than half of the reviewed studies carried out a risk evaluation and tested a broad range of scenarios including simulated pressure—effect scenarios, mostly related to the future license areas of wind farms or fisheries management measures.

Cumulative effect scenarios have been tested by weighting for instance the relationship between indicators and pressures. It is relevant to allude to the fact that about one-third of the studies did not account for uncertainty. Some studies assessed uncertainty quantitatively based on model uncertainty. List of 32 recent empirical studies of semi- quantitative ERAs in the context of the development, implementation or evaluation of marine spatial management.

Studies were reviewed according to the spatial scale and the methods used with regard to the three steps of a risk assessment: The mean overall local mortality rate assuming an equal impact of all fishing fleets is displayed in Figure 5 top , where high values can be found in the North—East of the study area and along a coastal strip. The relative combined recovery rates of the benthic communities are fishery independent and therefore patterns resembled the benthic communities Figure 5 , bottom. Spatial predictions of DI revealed that 5. High values of the unweighted and weighted disturbance indicator were found in different places Figure 6.

For each BN node that represents a continuous variable the weighed mean the mean value weighted by the probability of occurrence with its Gaussian standard deviation is shown on the bottom of each node Figure 3. For instance, the weighted mean state value for large beam trawl frequencies is 0. An alternative interpretation of the probabilities associated with the respective node states is that there is a The baseline BN showed further that there is a 4. In contrast, there is only a 1. The classification success rate spherical payoff which ranges from 0 to 1, with 1 being the best model performance, indicated a relative accuracy of the BN model for predicting the disturbance indicator DI with a value of 0.

Estimated values of the disturbance indicator DI based on an overall local mortality rate with equal weight for the impact scores of the six fishing fleets; right: In contrast, using the same scenario the average likely value of DI w increased from 0. However, this increase was not significant due to the great variance in estimates. The additional modification of the prior distribution of the Beamsml node and the predicted probabilities of benthic disturbance states are displayed in Figure 7 b.

The model predicted an average likely value of 0. However, for this case study, where the BN is populated with spatial data, the likely values of the disturbance indicator averaged over the entire study area of minor importance as indicated by the high standard error.

Equity Valuation Using Multiples: An Empirical Investigation - Andreas Schreiner - Google Книги

Here, the predicted likelihood of an area proportion having a certain value is much more relevant to evaluate trade-offs of spatial management scenarios. Whereas the assumed redistribution scenario of both fleets showed no significant effect on the four DI states, overall changes were predicted in relation to the probability distributions of DI w.

This means that 1. More relevant changes to the predicted probabilities were observed for the DI w States 1 and 2. We used the steps of a risk assessment framework described by Cormier et al.

1. Mutande di ghisa: Dalla banca al supermecato: come evitare i pessimi consigli per gli acquisti del nostro cervello (Italian Edition)?
2. Editorial Reviews.
3. Personalized Telehealth in the Future: A Global Research Agenda;
4. Special offers and product promotions.
5. .
6. ?
7. Introduction?

There are, of course, other established risk assessment frameworks such as a productivity—susceptibility analysis PSA a semi-quantitative ERA methodology Waugh et al. Further bow tie diagrams describe and analyse risk events by visualizing relevant pathways from causes to consequences Ferdous et al. The bow tie diagram focuses on so-called barriers representing existing control or mitigation measures that are placed between the causes and the risk, and the risk and consequences.

Recently, BNs have been used in combination with bow tie diagrams to overcome their purely depictive capabilities by adding probabilities and conditional dependencies between components Badreddine and Amor, ; Khakzad et al. The here identified methodological shortcomings were based on a structured, but not exhaustive selection of studies.

Nevertheless, this selection was a result of a literature database search Scopus using defined keywords, context, and expected type of output. Review results showed that independently from the investigated ecosystem components, computing quantitative measures of sensitivity is still challenging and could hardly be derived from empirical data alone.

Often a combination of model outputs and expert knowledge seemed to deliver the preferred metric e. Thus, our findings emphasized the lack of empirical studies to support extrapolation of measures of sensitivity to system scale questions see discussion in Crain et al. Another identified weakness was the lack of an explicit assessment of uncertainty, especially in cases where expert judgements were used.

Uncertainty cannot be eliminated from any integrated assessment or model-based decision support; however, it should be recognized and constructively handled Rotmans and van Asselt, ; Astles et al. Thus, the assessment of uncertainty is an important prerequisite of the herein described steps of risk analysis and subsequent risk evaluation.

For instance, fuzzy sets and advice theory allow for characterization of uncertainty associated with expert knowledge Ferdous et al. Despite the great variation of terminology across studies the minimum measure of vulnerability involved always was a combination of a measure of sensitivity of an ecosystem component and the probability and magnitude of a stressor occurring. However, only a few studies computed vulnerability according to the best practices defined in De Lange et al.

This depicts a future need to root spatially explicit quantitative ERAs more in ecological theory with regard to system function and processes e. Scenario evaluation is deemed as an important step in the risk assessment framework and which has been carried out in roughly half of the reviewed studies. Those who did simulate management scenarios generally used spatially explicit tools and approaches such as Ecospace Fouzai et al. Surprisingly, only one of the studies, included in this review, exploited a process-based numerical model to predict ecosystem responses to natural or human pressures Vanhatalo et al.

Routinely used for reconstructions of past conditions or to forecast possible future trends, such models are useful in the context of risk assessments Weisse et al. Building on hydrodynamic drift simulations, Chrastansky and Callies have demonstrated how such model data can be turned into spatially explicit information on the risk posed by hypothetical oil spills in the North Sea.

Their approach based on a BN, which makes the essential information of the model available without the need to access the memory-intensive, original datasets. In that way, detailed information on key natural drivers and their causal relationships with existing pressures can easily be considered in a wider GIS-coupled risk assessment framework. Until now, this is rarely the case in ERAs making it difficult if not impossible to separate the effects of natural disturbance, for example by waves, from that caused by human activities such as bottom trawling Diesing et al.

According to ecological theory Pickett and White, , disturbance regime is, however, an important spatial process which should be accounted for when assessing the risks of spatial management scenarios. The aim of the case study was to address some of the methodological shortcomings identified in the current literature on spatially explicit and quantitative ERAs and to provide some perspectives for assessing the trade-offs of on MSP measures in the German EEZ of the North Sea.

We built on a study by Fock a for calculating measures of fishing frequency, mortality rates and the disturbance indicators. The overall measures of recovery and mortality have been computed for 10 benthic communities Pesch et al. For this, we converted existing model outputs on recovery and mortality rates by sediment type to respective rates by benthic community. This has been done by weighting sediment-specific parameters with likely species habitat preferences given in Rachor and Nehmer As a consequence, those benthic community-specific estimates on mortality and recovery rates reflect rather rough estimates of those parameters.

A promising alternative source for recovery rates days by phyla and habitat type provides a meta-analysis of trawl impact studies carried out by Kaiser et al. In future studies, those results could be used to redefine for instance fleet-specific impact scores is fleet of the weighted mortality rates. Further, benthic disturbance was only calculated for infaunal benthic communities, while epifaunal species may be more vulnerable to fishing disturbance Piet et al.

Account Options

As a result, future steps to improve mortality and recovery rates of benthic communities would embrace the combination of infaunal and epifaunal recovery and decline rates. In our case study, we did not explicitly map or consider a measure of natural disturbance; however, we can assume that natural disturbance, for example, by tidal and wave stress as well as daily and seasonal temperature variability, is highest in shallow coastal areas Becker et al.

Here, benthic communities will show greater resilience to fishing disturbance than in zones with larger water depths e. Thus, taking interactions between fishing and natural disturbances into account would very likely result in different patterns of the disturbance indicator. Nevertheless, Fock et al. Addressing a similar topic Diesing et al. They defined trawling impact as significant when it exceeds natural disturbance by waves and tides. The observed differences in spatial pattern of the two disturbance indicators were clearly a result of the weighting of the impact of the different fishing fleets.

In this sense, it reflects a transparent assessment of uncertainty. To enable a dynamic link of risk analysis and risk evaluation, hence scenario evaluation, we combined GIS with a BN model to conduct a quantitative spatially explicit risk assessment. BNs indeed are advantageous, especially when considering the input from various data types Aguilera et al. BNs represent multidimensional distributions and can conveniently be applied for updating probability distributions of all variables given observations for just a subset of them.

Information available will propagate across the whole network regardless of the orientation of edges see, e. This analysis of joint probabilities based on incomplete observations must be distinguished, however, from predicting the results of external interventions e. For the latter purpose, a BN must be formulated in line with causal relationships see Pearl, Thus, an influence diagram represents parameters actively controlled by rational decision-makers as non-random decision nodes.

They rate system configurations that result from management decisions based on value or utility nodes Pearl, ; Bedford and Cooke, In our example, we did not construct an influence diagram with decision nodes. Further multistage decision networks allow even for considering a sequence of decisions at future points in time when certain types of information will become available. Such repeated decision-making is an essential part of an adaptive management process Vugteveen et al. A representation of such practically relevant concepts in a probabilistic framework such as the one illustrated here, however, is scientifically challenging and requires future development.

This was based on the assumption that vessels conducting demersal mixed or crustacean fishery reallocate their effort in areas of potential large catch or previous knowledge and experience Bastardie et al. Results showed that the assumed shift in fishing frequencies did not result in significant changes of the average likely value of the disturbance indicator. This information is much more meaningful when evaluating the trade-offs of spatial management options.

Once, more realistic fishing effort displacement scenarios become available, the combined GIS and BN approach can be used to predict likely local values of, for example, the disturbance indicator. For instance, individual-based models, predicting fishing fleet behaviour under changing economic or ecological conditions Bastardie et al. Currently, quantitative ERA studies in a spatial management context reflect a wide range of assessment approaches, with varying interpretations of the terms risk, vulnerability, or impact.

Especially, the different definitions of vulnerability suggest that future spatially explicit quantitative ERAs should be more rooted in ecological theory with regard to system function and processes. Spatially explicit risk assessments yet to come should also consider the inclusion of numerical models for instance describing natural disturbance, since this is an important component in ecological disturbance theory. We identified a transparent assessment of uncertainty as clear shortcoming of many current approaches and conclude that the application of BNs are a promising approach to address this.

Also future research is needed on how to build meaningful influence diagrams, with parameters actively controlled by rational decision-makers decision nodes , in the course of quantitative ERAs. Independently from the concepts and methods applied to predict a measure of risk, we strongly recommend putting caution on the type of output produced and its potential uptake in an actual spatial management process. The latter often refers to complex multiple objectives settings, where the impacts of many human activities need to be jointly assessed. In conclusion, marine spatial management or MSP processes should embed ERA frameworks which allow for the integration of multiple risk assessments and the quantification of related uncertainties at a common spatial scale.

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Close mobile search navigation Article navigation. Quantitative environmental risk assessments in the context of marine spatial management: Abstract Marine spatial planning MSP requires spatially explicit environmental risk assessment ERA frameworks with quantitative or probabilistic measures of risk, enabling an evaluation of spatial management scenarios. View large Download slide.

A novel approach to model exposure of coastal-marine ecosystems to riverine flood plumes based on remote sensing techniques. An ecological method for qualitative risk assessment and its use in the management of fisheries in New South Wales, Australia. Integrating individual trip planning in energy efficiency — Building decision tree models for Danish fisheries. The challenge of managing marine biodiversity: Which is the more dominant and practicable contributor to maritime policy in the UK? Interactions between global and local stressors of ecosystems determine management effectiveness in cumulative impact mapping.

Using a Bayesian network to summarize variability in numerical long-term simulations of a meteorological-marine system: A new tool for offshore wind energy risk assessment. Towards marine ecosystem based management in South Florida: Interactive and cumulative effects of multiple human stressors in marine systems. A proposed method for assessing the extent of the seabed significantly affected by demersal fishing in the Greater North Sea.

The importance of monitoring and evaluation in adaptive maritime spatial planning. Human activities in UK offshore waters: The estuarine quality paradox, environmental homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas. Analyzing system safety and risks under uncertainty using a bow-tie diagram: Integrating multiple pressures at different spatial and temporal scales: Linking marine fisheries to environmental objectives: Recovery of UK seabed habitats from benthic fishing and aggregate extraction-Towards a cumulative impact assessment.

Improving ocean management through the use of ecological principles and integrated ecosystem assessments.