10 resultados para L81 - Retail and Wholesale Trade
em University of Queensland eSpace - Australia
Resumo:
In the 1990s workers in Australia were increasingly subjected to negative work pressures. Irregular work patterns, work intensification, and the transformation of the notion of career, often in the name of ‘flexibility’, were increasingly common. This period was also characterised by scant regard for the quality of working life of young people in entry-level employment, which is often portrayed as a transition stage prior to their admission into the full-time core workforce. This paper explores the experiences of twenty-two young people at the beginning of their careers, in the hospitality and retail industries, with reference to three quality of working life (QWL) elements: hours flexibility, work-life balance and career potential. Qualitative evidence reveals a variety of experiences but, on balance, suggests a negative quality of working life and limited commitment to their current industry. In conclusion, the paper suggests that these industries must pay more attention to QWL issues in order to attract and retain quality staff.
Resumo:
This paper examines the impact of multinational trade accords on the degree of stock market linkage using NAFTA as a case study. Besides liberalizing trade among the U.S., Canada and Mexico, NAFTA has also sought to strengthen linkage among stock markets of these countries. If successful, this could lessen the appeal of asset diversification across the North American region and promote a higher degree of market efficiency. We assess the possible impact of NAFTA on market linkage using cross-correlations, multivariate price cointegrating systems, speed of convergence, and generalized variance decompositions of unexpected stock returns. The evidence proves robust and consistently indicates intensified equity market linkage since the NAFTA accord. The results also suggest that interdependent goods markets in the region are a primary reason behind the stronger equity market linkage observed in the post-NAFTA period. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.
Resumo:
The authors report the results of two studies that model the antecedents of goal congruence in retail-service settings. They draw the antecedents from extant research and propose that goal congruence is related to employees' perceptions of morale, leadership support, fairness in reward allocation, and empowerment. They hypothesize and test direct and indirect relationships between these constructs and goal congruence. Results of structural equations modeling suggest an important mediating role for morale and interesting areas of variation across retail and service settings.
Resumo:
Improvements in seasonal climate forecasts have potential economic implications for international agriculture. A stochastic, dynamic simulation model of the international wheat economy is developed to estimate the potential effects of seasonal climate forecasts for various countries' wheat production, exports and world trade. Previous studies have generally ignored the stochastic and dynamic aspects of the effects associated with the use of climate forecasts. This study shows the importance of these aspects. In particular with free trade, the use of seasonal forecasts results in increased producer surplus across all exporting countries. In fact, producers appear to capture a large share of the economic surplus created by using the forecasts. Further, the stochastic dimensions suggest that while the expected long-run benefits of seasonal forecasts are positive, considerable year-to-year variation in the distribution of benefits between producers and consumers should be expected. The possibility exists for an economic measure to increase or decrease over a 20-year horizon, depending on the particular sequence of years.
Resumo:
Objectives: This pilot study describes a modelling approach to translate group-level changes in health status into changes in preference values, by using the effect size (ES) to summarize group-level improvement. Methods: ESs are the standardized mean difference between treatment groups in standard deviation (SD) units. Vignettes depicting varying severity in SD decrements on the SF-12 mental health summary scale, with corresponding symptom severity profiles, were valued by a convenience sample of general practitioners (n = 42) using the rating scale (RS) and time trade-off methods. Translation factors between ES differences and change in preference value were developed for five mental disorders, such that ES from published meta-analyses could be transformed into predicted changes in preference values. Results: An ES difference in health status was associated with an average 0.171-0.204 difference in preference value using the RS, and 0.104-0.158 using the time trade off. Conclusions: This observed relationship may be particular to the specific versions of the measures employed in the present study. With further development using different raters and preference measures, this approach may expand the evidence base available for modelling preference change for economic analyses from existing data.
Resumo:
We consider the statistical problem of catalogue matching from a machine learning perspective with the goal of producing probabilistic outputs, and using all available information. A framework is provided that unifies two existing approaches to producing probabilistic outputs in the literature, one based on combining distribution estimates and the other based on combining probabilistic classifiers. We apply both of these to the problem of matching the HI Parkes All Sky Survey radio catalogue with large positional uncertainties to the much denser SuperCOSMOS catalogue with much smaller positional uncertainties. We demonstrate the utility of probabilistic outputs by a controllable completeness and efficiency trade-off and by identifying objects that have high probability of being rare. Finally, possible biasing effects in the output of these classifiers are also highlighted and discussed.