CSR and the "underserving":a role for the state, civil society and business?

Purpose – The purpose of this paper is to demonstrate how the conceptual lens of corporate social responsibility (CSR), business and civil society can be used to explore “less popular causes” (in this case, a community-based public sector empirical study of initiatives with offenders) and, in particular, respond to the question used by Walzer “In which society can lives be best led?” Design/methodology/approach – This is a formative and summative evaluation study of a National Offender Management “community payback” offender scheme based in the UK using a mixed method, predominantly qualitative approach that integrates theory and practice. Findings – The paper finds that citizenship actions of front-line public sector employees, working in partnership with other agencies in the community, embody the essence of Walzer's notion of CSR and civil society by going beyond the call of duty to provide additional training and moral support for the community offenders. Originality/value – The paper contributes towards an understanding of how CSR and civil society debates can inform wider aspects of public policy and business through its application to areas of society that are perceived to be “challenging” and “undeserving”.

The mediating role of discrete emotions in the relationship between injustice and counterproductive work behaviors:a study in Pakistan

Purpose: Our study explores the mediating role of discrete emotions in the relationships between employee perceptions of distributive and procedural injustice, regarding an annual salary raise, and counterproductive work behaviors (CWBs). Design/Methodology/Approach: Survey data were provided by 508 individuals from telecom and IT companies in Pakistan. Confirmatory factor analysis, structural equation modeling, and bootstrapping were used to test our hypothesized model. Findings: We found a good fit between the data and our tested model. As predicted, anger (and not sadness) was positively related to aggressive CWBs (abuse against others and production deviance) and fully mediated the relationship between perceived distributive injustice and these CWBs. Against predictions, however, neither sadness nor anger was significantly related to employee withdrawal. Implications: Our findings provide organizations with an insight into the emotional consequences of unfair HR policies, and the potential implications for CWBs. Such knowledge may help employers to develop training and counseling interventions that support the effective management of emotions at work. Our findings are particularly salient for national and multinational organizations in Pakistan. Originality/Value: This is one of the first studies to provide empirical support for the relationships between in/justice, discrete emotions and CWBs in a non-Western (Pakistani) context. Our study also provides new evidence for the differential effects of outward/inward emotions on aggressive/passive CWBs. © 2012 Springer Science+Business Media, LLC.

Data envelopment analysis model for the appraisal and relative performance evaluation of nurses at an intensive care unit

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

Service employee clusters in banking:exploring Ind's typology considering behaviour, commitment and attitude about leadership

Purpose: Ind suggests front line employees can be segmented according to their level of brand-supporting performance. His employee typology has not been empirically tested. The paper aims to explore front line employee performance in retail banking, and profile employee types. Design/methodology/approach: Attitudinal and demographic data from a sample of 404 front line service employees in a leading Irish bank informs a typology of service employees. Findings: Champions, Outsiders and Disruptors exist within retail banking. The authors provide an employee profile for each employee type. They found Champions amongst males, and older employees. The highest proportion of female employees surveyed were Outsiders. Disruptors were more likely to complain, and rated their performance lower than any other employee type. Contrary to extant literature, Disruptors were more likely to hold a permanent contract than other employee types. Originality/value: The authors augment the literature by providing insights about the profile of three employee types: Brand Champions, Outsiders and Disruptors. Moreover, the authors postulate the influence of leadership and commitment on each employee type. The cluster profiles raise important questions for hiring, training and rewarding front line banking employees. The authors also provide guidelines for managers to encourage Champions, and curtail Disruptors. © Emerald Group Publishing Limited.

Management interventions and prosocial behaviours:understanding the mediating mechanisms

Previous research suggests that the attitudes and behaviours of front-line employees (FLEs) significantly influence customers’ evaluations of service quality and customer satisfaction. Therefore, it becomes important to identify the variables that influence FLEs job attitudes and Prosocial ServiceBehaviours (PSBs). The conceptual framework developed from extant literature is presented, which proposes that management interventions (internal communication, training and development and empowerment) have a direct effect on PSBs. In addition, these relationships are mediated by role stress and job attitudes. Implications for service management and future research directions are discussed.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Women as translators, as translation trainers, and as translation scholars

Over the centuries, women have always played a significant part in translation practice, training, and theoretical reflection. In fact, translation (and interpreting) have often been characterized as a feminine occupation. This chapter looks at these three aspects predominantly from a quantitative perspective. In terms of the profession, it investigates the distribution of male and female translators and interpreters in the United Kingdom and the subject areas they are working in. For women's contribution to the academic discipline of Translation Studies, it investigates the amount of female authors who contributed to the discipline with their publications and asks whether female scholars focus on specific topics. Finally, it investigates leadership roles of women in professional associations. The paper concludes by reflecting on the potential significance of such studies. © 2013.

Plant closures, precariousness and policy responses:revisiting MG Rover 10 years on

With automotive plants being closed in Australia and western Europe, this article reflects on the employment status of ex-MG Rover (MGR) workers following the closure of the Longbridge plant in 2005. In particular, it draws on Standing's typology of labour market insecurity and uses a mixed-methods approach including an analysis of a longitudinal survey of some 200 ex-MGR workers, and in-depth interviews with ex-workers and policy-makers. While the policy response to the closure saw significant successes in terms of the great majority of workers successfully adjusting into re-employment, and with positive findings in terms of re-training and education, the paper finds significant challenges in terms of security of employment, income, job quality and representation at work years after closure. In particular, the paper posits that the general lack of attention to employment security at the macrolevel effectively undermined elements of a positive policy response over the longer run. This in turn suggests longer-term policy measures are required to address aspects of precariousness at work.

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.

Within-role, extra-role and anti-role behaviours in retail banking

Purpose: This paper aims to explore front line employee performance in retail banking and presents distinct components of employee performance, including extra-role and sabotage behaviours. Design/methodology/approach: Data was collected from Irish bank employees. Usable responses were received from 404 respondents and subjected to exploratory factor analysis. Structural Equation Modeling (SEM) was used to undertake a confirmatory factor analysis of the emergent five-factor model. Findings: Results indicate front line employee performance is multi-faceted and comprised of civility, assurance and reliability, customer orientation, as well as extra-role behaviour and anti-role behaviour, or sabotage. Research limitations/implications: This exploratory study focuses on the Irish banking sector. To explore the generalisabilty of results, replication studies among other samples of branch banking employees in other countries are in order. Moreover, our survey is limited to the views of branch employees. We advocate research among bank managers and customers to triangulate potentially divergent views about performance. Practical implications: Findings have implications for recruitment, training and rewards. To ensure new hires are service minded, managers must consider their potential for extra-role or sabotage behaviour. Employees who demonstrate extra-role behaviours must be rewarded to encourage the adoption of such behaviours. Managers must also seek to minimise job stress in order to curtail anti-role behaviours. Originality/value: This paper offers insights into employees' views about their own performance at the front line. It extends the conceptualisation of service quality, by considering extra-role behaviour and sabotage as components of employee performance. © Emerald Group Publishing Limited.

Human capital:theoretical and empirical insights

There is nothing more difficult to plan, more Doubtful of success, nor more dangerous to manage Than the creation of a new system. For the initiator has the enmity of all who would Profit by the preservation of the old system, and Merely lukewarm defenders in those who should gain By the new one. N. Machiavelli (1513) Abstract: The purpose of this paper is twofold. First, we want to challenge the notion of "human capital" as "education, training and work experience" and suggest that it is the "quality of the workforce" that matters, here defined as the set of characteristics that allow workers to function in a specific institutional and historical context. Our main conclusion is that the quality of the workforce is affected by the institutional environment where the workers live and that therefore it can vary across countries and institutional contexts. Second, we want to show the empirical relevance of this last point by testing the extent to which the quality of institutions (here proxied by the governance indicators of Kaufmann etal. (2007)) can affect the quality of the workforce (proxied by the percentage of the working age population registered in a lifelong learning program). Our empirical analysis is conducted on a data-set of 11 European countries observed over the period 1996-2006. The results indicate that countries with better governance indicators are also endowed with a more qualified workforce. © 2011 American Journal of Economics and Sociology, Inc.