E-learning in traditional industries: balancing the preferences of an ageing workforce with the expectations of a technoloigy-savvy generation

There is widespread argument that traditional organisations and industries with a predominantly older workforce who are not using computers as an integral part of their work, are unlikely to embrace the opportunities afforded by e-learning. However, the challenge remains to engage a younger generation of learners who seem comfortable learning with technology, whilst not alienating those older learners who may prefer to learn in more traditional ways. This paper analyses data from five case organisations within the Australian rail industry to identify how the potential of e-learning can be realised whilst acknowledging the technological divide between younger and older workers.

Attraction and retention in rural and remote communities

Attracting and retaining a skilled labour force is a critical yet complex issue for rural and remote communities. This article reports the findings of a study investigating the current approaches to recruitment and retention in two separate Australian regions. Building on previously developed models, the research analyses the roles employers and the wider communities are playing, or potentially could play, in addressing issues that influence labour shortages. The findings of the research highlight the complexities of employee attraction and retention and emphasise the need for communities and businesses to work together to overcome labour shortages in rural and remote locations.

E-learning : aging workforce versus technology-savvy generation

Purpose – The purpose of this paper is to provide description and analysis of how a traditional industry is currently using e-learning, and to identify how the potential of e-learning can be realised whilst acknowledging the technological divide between younger and older workers. Design/methodology/approach – An exploratory qualitative methodology was employed to analyse three key questions: How is the Australian rail industry currently using e-learning? Are there age-related issues with the current use of e-learning in the rail industry? How could e-learning be used in future to engage different generations of learners in the rail industry? Data were collected in five case organisations from across the Australian rail industry. Findings – Of the rail organisations interviewed, none believed they were using e-learning to its full potential. The younger, more technologically literate employees are not having their expectations met and therefore retention of younger workers has become an issue. The challenge for learning and development practitioners is balancing the preferences of an aging workforce with these younger, more “technology-savvy”, learners and the findings highlight some potential ways to begin addressing this balance. Practical implications – The findings identified the potential for organisations (even those in a traditional industry such as rail) to better utilise e-learning to attract and retain younger workers but also warns against making assumptions about technological competency based on age. Originality/value – Data were gathered across an industry, and thus this paper takes an industry approach to considering the potential age-related issues with e-learning and the ways it may be used to meet the needs of different generations in the workplace.

Semi-parametric forecasting of realized volatility

Forecasts generated by time series models traditionally place greater weight on more recent observations. This paper develops an alternative semi-parametric method for forecasting that does not rely on this convention and applies it to the problem of forecasting asset return volatility. In this approach, a forecast is a weighted average of historical volatility, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in volatility across time (as a measure of market conditions) by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are significantly more accurate than a number of competing approaches at both short and long forecast horizons.

Enabling innovation and facilitating learning in kifs: the role of HRM practices

The aim of this paper is to contribute to our understanding of the link between HR practices, learning orientation and types of innovation in knowledge-intensive firms (KIFs). To this end, we first compiled a comprehensive overview of the existing literature on HR practices aimed at supporting innovation. On the basis of this literature, we then collected and analyzed data from a qualitative study of 19 Danish KIFs recognized for their innovation performance, focusing on links between the HR practices they use to support exploratory and exploitive learning behaviors to enhance incremental and/or radical innovation. The findings from this study demonstrate that KIFs utilize a range of HR practices that enable different learning orientations, based on the type of innovation compatible with their organizational goals.

HRM in professional service firms : engendering commitment to what or whom?

Professional service firms (PSFs) present HR professionals with a number of unique challenges, as they share characteristics of both service and knowledge intensive organizations. While many of these firms are relying on High Commitment Work Practices (HCWPs) to enhance critical employee behaviors such as service quality and turnover, the analysis presented in this paper raises questions about traditional understandings of commitment in professional service environments. In particular, data from three Danish financial investment PSFs suggest that employees are more committed to developing and promoting their own professions than to the organization itself, which has important implications for the way in which HCWPs are designed and utilized. In addition, the focus of HCWP research has favored the use of social exchange theory as an underpinning framework for considering the impact of HR practices on employee commitment. In the context of PSFs, we question the applicability of social exchange theory and instead draw upon the Ability-Motivation-Opportunity (AMO) framework (1982) to analyze how specific HRM practices contribute to the development of commitment, and to successful organizational outcomes in PSFs.

On the efficacy of techniques for evaluating multivariate volatility forecasts

The performance of techniques for evaluating multivariate volatility forecasts are not yet as well understood as their univariate counterparts. This paper aims to evaluate the efficacy of a range of traditional statistical-based methods for multivariate forecast evaluation together with methods based on underlying considerations of economic theory. It is found that a statistical-based method based on likelihood theory and an economic loss function based on portfolio variance are the most effective means of identifying optimal forecasts of conditional covariance matrices.

Tax evasion, inequality, and progressive taxes : a political economy perspective

The standard approach to tax compliance applies the economics-of-crime methodology pioneered by Becker (1968): in its first application, due to Allingham and Sandmo (1972) it models the behaviour of agents as a decision involving a choice of the extent of their income to report to tax authorities, given a certain institutional environment, represented by parameters such as the probability of detection and penalties in the event the agent is caught. While this basic framework yields important insights on tax compliance behavior, it has some critical limitations. Specifically, it indicates a level of compliance that is significantly below what is observed in the data. This thesis revisits the original framework with a view towards addressing this issue, and examining the political economy implications of tax evasion for progressivity in the tax structure. The approach followed involves building a macroeconomic, dynamic equilibrium model for the purpose of examining these issues, by using a step-wise model building procedure starting with some very simple variations of the basic Allingham and Sandmo construct, which are eventually integrated to a dynamic general equilibrium overlapping generations framework with heterogeneous agents. One of the variations involves incorporating the Allingham and Sandmo construct into a two-period model of a small open economy of the type originally attributed to Fisher (1930). A further variation of this simple construct involves allowing agents to initially decide whether to evade taxes or not. In the event they decide to evade, the agents then have to decide the extent of income or wealth they wish to under-report. We find that the ‘evade or not’ assumption has strikingly different and more realistic implications for the extent of evasion, and demonstrate that it is a more appropriate modeling strategy in the context of macroeconomic models, which are essentially dynamic in nature, and involve consumption smoothing across time and across various states of nature. Specifically, since deciding to undertake tax evasion impacts on the consumption smoothing ability of the agent by creating two states of nature in which the agent is ‘caught’ or ‘not caught’, there is a possibility that their utility under certainty, when they choose not to evade, is higher than the expected utility obtained when they choose to evade. Furthermore, the simple two-period model incorporating an ‘evade or not’ choice can be used to demonstrate some strikingly different political economy implications relative to its Allingham and Sandmo counterpart. In variations of the two models that allow for voting on the tax parameter, we find that agents typically choose to vote for a high degree of progressivity by choosing the highest available tax rate from the menu of choices available to them. There is, however, a small range of inequality levels for which agents in the ‘evade or not’ model vote for a relatively low value of the tax rate. The final steps in the model building procedure involve grafting the two-period models with a political economy choice into a dynamic overlapping generations setting with more general, non-linear tax schedules and a ‘cost-of evasion’ function that is increasing in the extent of evasion. Results based on numerical simulations of these models show further improvement in the model’s ability to match empirically plausible levels of tax evasion. In addition, the differences between the political economy implications of the ‘evade or not’ version of the model and its Allingham and Sandmo counterpart are now very striking; there is now a large range of values of the inequality parameter for which agents in the ‘evade or not’ model vote for a low degree of progressivity. This is because, in the ‘evade or not’ version of the model, low values of the tax rate encourages a large number of agents to choose the ‘not-evade’ option, so that the redistributive mechanism is more ‘efficient’ relative to the situations in which tax rates are high. Some further implications of the models of this thesis relate to whether variations in the level of inequality, and parameters such as the probability of detection and penalties for tax evasion matter for the political economy results. We find that (i) the political economy outcomes for the tax rate are quite insensitive to changes in inequality, and (ii) the voting outcomes change in non-monotonic ways in response to changes in the probability of detection and penalty rates. Specifically, the model suggests that changes in inequality should not matter, although the political outcome for the tax rate for a given level of inequality is conditional on whether there is a large or small or large extent of evasion in the economy. We conclude that further theoretical research into macroeconomic models of tax evasion is required to identify the structural relationships underpinning the link between inequality and redistribution in the presence of tax evasion. The models of this thesis provide a necessary first step in that direction.

An extension to the rank constraint for improving the reliability of stereo matching algorithms using the rank transform

The rank transform is one non-parametric transform which has been applied to the stereo matching problem The advantages of this transform include its invariance to radio metric distortion and its amenability to hardware implementation. This paper describes the derivation of the rank constraint for matching using the rank transform Previous work has shown that this constraint was capable of resolving ambiguous matches thereby improving match reliability A new matching algorithm incorporating this constraint was also proposed. This paper extends on this previous work by proposing a matching algorithm which uses a dimensional match surface in which the match score is computed for every possible template and match window combination. The principal advantage of this algorithm is that the use of the match surface enforces the left�right consistency and uniqueness constraints thus improving the algorithms ability to remove invalid matches Experimental results for a number of test stereo pairs show that the new algorithm is capable of identifying and removing a large number of in incorrect matches particularly in the case of occlusions

An accurate and reliable stereo matching algorithm incorporating the rank constraint

A fundamental problem faced by stereo vision algorithms is that of determining correspondences between two images which comprise a stereo pair. This paper presents work towards the development of a new matching algorithm, based on the rank transform. This algorithm makes use of both area-based and edge-based information, and is therefore referred to as a hybrid algorithm. In addition, this algorithm uses a number of matching constraints,including the novel rank constraint. Results obtained using a number of test pairs show that the matching algorithm is capable of removing a significant proportion of invalid matches. The accuracy of matching in the vicinity of edges is also improved.