Do construction companies need to match employees' expectations?

Commitment of employees is relatively low in construction. This problem is exasperated by companies inability to attract, motivate, and retain talent that is then often channelled into other more attractive industrial sectors where the prospects, conditions and rewards are perceived to be much higher. The purpose of this study is thus primarily to develop a generic model to maximise employees' engagement, improve their motivation and increase the retention levels. To achieve this aim, the investigation looks into how perceived employment obligations and expectations impact commitment and through that organisational performance. The study is based on the postulations of Luhmann's theory of social systems with communication viewed as a constitutive element of a social system. Consequently expectations of a particular party in an employment relationship are represented in a communicative space requiring the other party's understanding in order to align expectations of both sides in the relationship. Explicitly, alignment of by an employee perceived manager's expectations determines his/ her commitment to fulfil obligations towards the manager. The result of this first stage of research is a conceptual model developed following the substantial supporting evidence in the literature and it forms the framework for mitigation of low commitment, motivation and retention of employees. The model particularly focuses on factors affecting employees' perceived expectations like reneging, incongruence and the process of communication. In the future the model will be validated using empirical data from a combination of observational and enquiry-based research. Once completed, the model will provide a framework for informing Human Resource Management policies with the aim to improve commitment of employees, increase the levels of retention and consequently improve the performance of construction organisations.

'A load too heavy': Critical reflections on the child labor problem in Africa's small-scale mining sector

This paper provides an extended analysis of the child labor problem in the artisanal and small-scale mining (ASM) sector, focusing specifically on the situation in sub-Saharan Africa. In recent years, the issue of child labor in ASM has garnered significant attention from the International Labor Organization (ILO), which has been particularly active in raising public awareness of the problem; and, has proceeded to implement policies and collaborative project work aimed at Curtailing children's participation in ASM activities in a number of African countries. The analysis concludes with a critical appraisal of an ILO project recently launched in the Talensi-Nabdam District in the Upper East Region of Ghana, which sheds light on how the child labor problem is being tackled in practice in ASM communities in sub-Saharan Africa. (c) 2008 Elsevier Ltd. All rights reserved.

An old problem revisited - and solved: Upton and Dalton's linear production response: A note

This note presents a robust method for estimating response surfaces that consist of linear response regimes and a linear plateau. The linear response-and-plateau model has fascinated production scientists since von Liebig (1855) and, as Upton and Dalton indicated, some years ago in this Journal, the response-and-plateau model seems to fit the data in many empirical studies. The estimation algorithm evolves from Bayesian implementation of a switching-regression (finite mixtures) model and demonstrates routine application of Gibbs sampling and data augmentation-techniques that are now in widespread application in other disciplines.

The extrapolation problem and how population modeling can help

We argue that population modeling can add value to ecological risk assessment by reducing uncertainty when extrapolating from ecotoxicological observations to relevant ecological effects. We review other methods of extrapolation, ranging from application factors to species sensitivity distributions to suborganismal (biomarker and "-omics'') responses to quantitative structure activity relationships and model ecosystems, drawing attention to the limitations of each. We suggest a simple classification of population models and critically examine each model in an extrapolation context. We conclude that population models have the potential for adding value to ecological risk assessment by incorporating better understanding of the links between individual responses and population size and structure and by incorporating greater levels of ecological complexity. A number of issues, however, need to be addressed before such models are likely to become more widely used. In a science context, these involve challenges in parameterization, questions about appropriate levels of complexity, issues concerning how specific or general the models need to be, and the extent to which interactions through competition and trophic relationships can be easily incorporated.