Was wollen jüngere und ältere Erwerbstätige erreichen? Altersbezogene Unterschiede in den Inhalten und Merkmalen beruflicher Ziele [What do younger and older workers want to accomplish? Age-related differences in content and characteristics of occupational goals ]

Demographic changes necessitate that companies commit younger workers and motivate older workers through work design. Age-related differences in occupational goals should be taken into account when accomplishing these challenges. In this study, we investigated goal contents and goal characteristics of employees from different age groups. We surveyed 150 employees working in the service sector (average age = 44 years, age range 19 to 60 years) on their most important occupational goals. Employees who stated goals from the area of organizational citizenship were significantly older than employees with other goals. Employees who stated goals from the areas of training and pay/career were significantly younger than employees with other goals. After controlling for gender, education, and work characteristics, no age-related differences were found in the goal areas teamwork, job security, working time, well-being, and new challenges. In addition, no relationships were found between age and the goal characteristics specificity, planning intensity, as well as positive and negative goal emotions. We recommend that companies provide older workers with more opportunities for organizational citizenship and commit younger workers by providing development opportunities and adequate pay

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.