Testing competing HRM-performance linkage models:evidence from the Greek manufacturing sector

This paper proposes an integrative framework for the conduct of a more thorough and robust analysis regarding the linkage between Human Resource Management (HRM) and business performance. In order to provide the required basis for the proposed framework, initially, the core aspects of the main HRM models predicting business performance are analysed. The framework proposes both the principle of mediation (i.e. HRM outcomes mediate the relationship between organisational strategies and business performance) and the perspective of simultaneity of decision-making by firms with regard to the consideration of business strategies and HRM policies. In order to empirically test this framework the methodological approach of 'structural equation models' is employed. The empirical research is based on a sample of 178 organisations operating in the Greek manufacturing sector. The paper concludes that both the mediation principle and the simultaneity perspective are supported, emphasising further the positive role of HRM outcomes towards organisational performance.

Density forecasts of crude-oil prices using option-implied and ARCH-type models

The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994–2006 period. Moving beyond standard ARCH type models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:727–754, 2011

Mathematical modelling of patient risks in a hospital environment, using multiple regression analysis

The aim of this research work was primarily to examine the relevance of patient parameters, ward structures, procedures and practices, in respect of the potential hazards of wound cross-infection and nasal colonisation with multiple resistant strains of Staphylococcus aureus, which it is thought might provide a useful indication of a patient's general susceptibility to wound infection. Information from a large cross-sectional survey involving 12,000 patients from some 41 hospitals and 375 wards was collected over a five-year period from 1967-72, and its validity checked before any subsequent analysis was carried out. Many environmental factors and procedures which had previously been thought (but never conclusively proved) to have an influence on wound infection or nasal colonisation rates, were assessed, and subsequently dismissed as not being significant, provided that the standard of the current range of practices and procedures is maintained and not allowed to deteriorate. Retrospective analysis revealed that the probability of wound infection was influenced by the patient's age, duration of pre-operative hospitalisation, sex, type of wound, presence and type of drain, number of patients in ward, and other special risk factors, whilst nasal colonisation was found to be influenced by the patient's age, total duration of hospitalisation, sex, antibiotics, proportion of occupied beds in the ward, average distance between bed centres and special risk factors. A multi-variate regression analysis technique was used to develop statistical models, consisting of variable patient and environmental factors which were found to have a significant influence on the risks pertaining to wound infection and nasal colonisation. A relationship between wound infection and nasal colonisation was then established and this led to the development of a more advanced model for predicting wound infections, taking advantage of the additional knowledge of the patient's state of nasal colonisation prior to operation.

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.

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.