Outsourcing:assessing the risks and benefits for organisations, sectors and nations

Purpose - This research aims to assess the risks and benefits of outsourcing for organisations, sectors and nations. The literature on outsourcing contains little evidence of research on holistic issues of its impact at systems levels beyond the firm, notably sectors and nations. Design/methodology/approach - A Delphi study with senior strategists from private and public sectors captured perspectives and specific observations on benefits and risks of outsourcing. Emergent issues on outsourcing policy, strategy and decision-making processes were synthesised into a framework for analysing factors associated with outsourcing. Findings - The findings suggest that a more holistic view of outsourcing is needed, linking local, organisational issues with sector and national level actions and outcomes. In this way, aggregate risks and benefits can be assessed at different systems levels. Research limitations/implications - Future research might address the motivations for outsourcing; currently there is little research evidence to assess whether outsourcing is a mechanism for failing to solve internal problems, and moving responsibility and risk out of the firm. Additionally most outsourcing research to date has concentrated on an activity either being "in" or "out"; there is little research exploring the circumstances in which mixed models might be appropriate. Practical implications - The framework provides an aid to research and an aide memoire for managers considering outsourcing. Originality/value - This paper contributes to knowledge on understanding of outsourcing at different systems levels, particularly highlighting the implications of outsourcing for sectors and nations. Previously most research has focused at the level of the firm or dyadic relationship. © Emerald Group Publishing Limited.

Wealth shocks, credit-supply shocks, and asset allocation:evidence from household and firm portfolios

We use a unique dataset with bank clients’ security holdings for all German banks to examine how macroeconomic shocks affect asset allocation preferences of households and non-financial firms. Our analysis focuses on two alternative mechanisms which can influence portfolio choice: wealth shocks, which are represented by the sovereign debt crisis in the Euro area, and credit-supply shocks which arise from reductions in borrowing abilities during bank distress. While households with large holdings of securities from stressed Euro area countries (Greece, Ireland, Italy, Portugal, and Spain) de-crease the degree of concentration in their security portfolio as a result of the Euro area crisis, non-financial firms with similar levels of holdings from stressed Euro area countries do not. Credit-supply shocks at the bank level result in lower concentration, for both households and non-financial corporations. Only shocks to corporate credit bear ramifications on bank clients’ portfolio concentration. Our results are robust to falsification tests, and instrumental variables estimation.

Self-affinity in financial asset returns

We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns. © 2012 Elsevier Inc. All rights reserved.

Analysing the European Union's responses to organized crime through different securitization lenses

In the past 30 years, organized crime (OC) has shifted from being an issue of little, or no concern, to being considered one of the key security threats facing the European Union (EU), the economic and political fabric of its society and its citizens. The purpose of this article is to understand how OC has come to be understood as one of the major security threats in the EU, by applying different lenses of Securitization Theory (ST). More specifically, the research question guiding this article is whether applying different ST approaches can lead us to draw differing conclusions as to whether OC has been successfully securitized in the EU. Building on the recent literature that argues that this theoretical framework has branched out into different approaches, this article wishes to contrast two alternative views of how a security problem comes into being, in order to verify whether different approaches can lead to diverging conclusions regarding the same phenomenon. The purpose of this exercise is to contribute to the further development of ST by pointing out that the choice in approach bears direct consequences on reaching a conclusion regarding the successful character of a securitization process. Starting from a reflection on ST, the article proceeds with applying a “linguistic approach” to the case study, which it then contrasts with a “sociological approach”. The article proposes that although the application of a “linguistic approach” seems to indicate that OC has become securitized in the EU, it also overlooks a number of elements, which the “sociological approach” renders visible and which lead us to refute the initial conclusion.

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

Wealth shocks, credit-supply shocks, and asset allocation:evidence from household and firm portfolios

We use a unique dataset with bank clients’ security holdings for all German banks to examine how macroeconomic shocks affect asset allocation preferences of households and non-financial firms. Our analysis focuses on two alternative mechanisms which can influence portfolio choice: wealth shocks, which are represented by the sovereign debt crisis in the Eurozone, and credit-supply shocks which arise from reductions in borrowing abilities during bank distress. We document het- erogeneous responses to these two types of shocks. While households with large holdings of secu- rities from stressed Eurozone countries (Greece, Ireland, Italy, Portugal, and Spain) decrease the degree of concentration in their security portfolio as a result of the Eurozone crisis, non-financial firms with similar levels of holdings from stressed Eurozone countries do not. Credit-supply shocks at the bank level (caused by bank distress) result in lower concentration, for both households and non-financial corporations. We also show that only shocks to corporate credit bear ramifications on bank clients’ portfolio concentration, while shocks in retail credit are inconsequential. Our results are robust to falsification tests, propensity score matching techniques, and instrumental variables estimation.

Predicting practical benefits of dynamic asset ratings of 33kv distribution transformers

This paper reports potential benefits around dynamic thermal rating prediction of primary transformers within Western Power Distribution (WPD) managed Project FALCON (Flexible Approaches to Low Carbon Optimised Networks). Details of the thermal modelling, parameter optimisation and results validation are presented with asset and environmental data (measured and day/week-ahead forecast) which are used for determining dynamic ampacity. Detailed analysis of ratings and benefits and confidence in ability to accurately predict dynamic ratings are presented. Investigating the effect of sustained ONAN rating compared to a dynamic rating shows that there is scope to increase sustained ratings under ONAN operating conditions by up to 10% higher between December and March with a high degree of confidence. However, under high ambient temperature conditions this dynamic rating may also reduce in the summer months.

Weather forecasting to predict practical dynamic asset rating of overhead lines

This paper describes the potential of pre-setting 11kV overhead line ratings over a time period of sufficient length to be useful to the real-time management of overhead lines. This forecast is based on short and long term freely available weather forecasts and is used to help investigate the potential for realising dynamic rating benefits on the electricity network. A comparison between the realisable benefits in ratings using this forecast data, over the period of a year has been undertaken.

Social media in emergency management:Twitter as a tool for communicating risks to the public

One of the main challenges of emergency management lies in communicating risks to the public. On some occasions, risk communicators might seek to increase awareness over emerging risks, while on others the aim might be to avoid escalation of public reactions. Social media accounts offer an opportunity to rapidly distribute critical information and in doing so to mitigate the impact of emergencies by influencing public reactions. This article draws on theories of risk and emergency communication in order to consider the impact of Twitter as a tool for communicating risks to the public. We analyse 10,020 Twitter messages posted by the official accounts of UK local government authorities (councils) in the context of two major emergencies: the heavy snow of December 2010 and the riots of August 2011. Twitter was used in a variety of ways to communicate and manage associated risks including messages to provide official updates, encourage protective behaviour, increase awareness and guide public attention to mitigating actions. We discuss the importance of social media as means of increasing confidence in emergency management institutions.