Decision support systems for human resource training and development

Human resource training and development methods and techniques have different qualitative characteristics that require a multicriteria and multiscenario framework for their assessment. This study incorporates the AHP to assess the nine most important human resource training and development methods and techniques, under five criteria and six scenarios. The methods considered are ‘on-the-job training’, ‘mentorship’, ‘apprenticeship’, ‘vestibule training/simulators’, ‘web-based learning’, ‘instructor-led classroom training’, ‘programmed self-instruction’, ‘case studies/role playing’ and ‘systematic job rotations and transfers’. ‘Vestibule training/simulators’ and ‘mentorship’ have the average best scores, and they should be among the first priorities especially when efficiency, the motivation of employees and minimization of the duration of training time are the most important factors. ‘Web-based learning’ is ideal for minimizing training costs or when ease of application is the first priority. ‘On-the-job training’ is a very good alternative when the cost of training should be reduced while the motivation of employees should be increased.     

Government spending and revenues in the Greek economy: evidence from nonlinear cointegration

This paper attempts to re-evaluate the long-run macroeconomic relationship between government revenues and expenditures of the Greek economy over the period 1999–2010. The empirical analysis applies the newly developed asymmetric ARDL cointegration methodology of Shin et al. (2011) which permits more flexibility in the dynamic adjustment process towards equilibrium, than in the classical case of a linear model. Our findings point towards the fiscal synchronization hypothesis, supporting evidence of asymmetric interactions between the two fiscal components in both the long- and the short-run time horizon. More particularly, in the long-run, the negative changes of expenditures dominate the response of revenues, while the opposite applies in the response of expenditures.     

Improvement of a Bio-Economic Mathematical Programming Model in the Case of On-Farm Source Inputs and Outputs

We present a two-step process for solving nonlinear farm activity models inside a linear framework under the assumption that market prices approximate the shadow prices of the model’s constraints. In the event of market imperfections or missing prices (for example non-marketed outputs), the previous assumption is not justified and the derived solution is not optimal. To circumvent this problem and to avoid nonlinear algorithms that may prove unwieldy for large models, we propose an iterative computation method, based on the re-estimation of shadow prices in each step until a converging solution is found. The method is applied to the bio-economic model AROPAj, which consists of a number of linear programming (LP) farm sub-models representing different farming systems across the European Union. For most of LPs producing non-marketed outputs a converging solution is obtained in two iterations, while the remaining LPs lead to periodic solutions of very low amplitude.

     

Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are trained (estimated) using the same input variables as those used in the logistic. The objective is to demonstrate the use of networks in forecasting mortgage default and to compare their performance with that of the logistic benchmark in terms of prediction accuracy. Neural networks are shown to be superior to the logistic in terms of discriminating between good and bad loans. The study performs sensitivity analysis on the average loan and offers suggestions on further improving prediction of defaulting loans.     

Fiscal policy and financial market movements

This paper estimates fiscal policy reaction function in order to investigate the links between financial market movements and fiscal policy outcomes. An increase in asset prices affects in a positive and significant manner primary balances, with the response reflecting both an increase in government revenues and a fall in government spending. The most important impact on fiscal balances is due to changes in residential property prices. Changes in equity and commercial property prices are also important determinants of fiscal balances. Our findings suggest that the steepening of the slope of the yield curve contributes to expenditure based fiscal discipline.     

Managing Large-scale IT Projects: The Case of National Air Traffic Services' New En Route Centre at Swanwick

UK experience with implementation of high-profile IT projects has been rather unhappy, with projects tending to be severely delayed, to operate poorly and to be prone to escalating costs. There is therefore a need to understand better and to improve the management of such investments. This paper adopts a synthetic approach to analysing large-scale IT projects, drawing upon research on managing inflexible technology, project management and information technology implementation. The paper combines findings from these literatures to produce a detailed set of factors that are known to adversely affect ambitious software and other large-scale development projects. It employs a case study of software development at National Air Traffic Services' NERC project at Swanwick potentially to illustrate these. The paper finds that experience at Swanwick does indeed mirror many of the pitfalls predicted but also that the synthesis of approaches attempted enhances our understanding of the difficulties involved in managing large-scale IT projects perhaps rather better than univocal approaches.     

Value creation around merger waves: The role of managerial compensation

This paper examines the relation between executive compensation and value creation in merger waves. The sensitivity of CEO wealth to firm risk increases the likelihood of out-of-wave merger transactions but has no influence on in-wave merger frequency. CEOs with compensation linked to firm risk have better out-of-wave merger performance in comparison to in-wave mergers. We also present evidence that cross-sectional acquirer return dispersion is greater for in-wave acquisitions. Our results suggest that the underperformance of acquiring firms during merger waves can be attributed in part to ineffective compensation incentives, and appropriate managerial incentives can create value, particularly in non-wave periods.     

Chi-square Distribution as a Research Tool,and Some of Its Most Important Parametric and Non-parametric Applications

When researchers are testing the validity of claims during their research, they may use either parametric methods （if they exist） or non-parametric methods if appropriate parametric methods do not exist. The Chi-square （x2） distribution plays an important role in both parametric and non-parametric methods and many of its most important applications are explored in this paper. This paper provides an excellent summation of the properties and capabilities of the very versatile x2 distribution, and many specific applications and suggestions for additional future applications.     

Bank capital regulation in a barrier option framework

The barrier options theory of corporate security valuation is applied to the contingent claims of a regulated bank. The regulator/insurer of a bank owns a down-and-in call option on the bank assets which can be balanced against the expected coverage cost. Raising the regulatory barrier (critical asset level triggering bank closure) leads to a transfer of wealth from stockholders to the insurer and reduces stockholder incentives to increase asset risk. Empirical tests on a sample of 152 one-bank holding companies show that regulatory barriers are priced in the stock market and are inversely related to Tier 1 leverage ratios.