Survey of countertrade practices in Australia

This empirical exploratory study is part of a larger comprehensive study of countertrade practices in the Asia-Pacific region. A mail survey of 600 Australian international trading firms reveals that a positive attitude toward countertrade exists among both countertraders and non-countertraders in Australia. Further the study reveals the major motivating factors, the benefits derived difficulties faced and reasons for not countertrading by Australian firms. In addition, the study identifies the forms of countertrade used, the countries sewed, and the product and service categories countertraded. The results are compared to earlier studies of UK and Canadian firms, and the implications for international marketing managers are discussed. (C) Elsevier Science Inc., 1997.

Australian import managers' purchasing decision behaviour: An empirical study

Reports a pilot study of the relative importance of import decision variables as rated by Australian managers. A systematic sample qi 104 Australian managers representing different companies participated in the study. Australian importers rated product quality as the most important variable when importing products from overseas followed by long-term suppliers' dependability, product style/feature, price, and timely delivery. Australian managers who import consumer products find the domestic import duties and tariffs to be more important than did those who import industrial products. Larger volume importers regard the product brand name reputation to be more important than did those who import smaller volumes.

Australian empirical study into genetic discrimination

This paper outlines a major empirical study that is being undertaken by an interdisciplinary team into genetic discrimination in Australia. The 3-year study will examine the nature and extent of this newly emerging phenomenon across the perspectives of consumers, third parties, and the legal system and will analyze its social and legal dimensions. Although the project is confined to Australia, it is expected that the outcomes will have significance for the wider research community as this is the most substantial study of its kind to be undertaken to date into genetic discrimination.

A consumer-based method for retailer equity measurement: Results of an empirical study

This research extends the consumer-based brand equity measurement approach to the measurement of the equity associated with retailers. This paper also addresses some of the limitations associated with current retailer equity measurement such as a lack of clarity regarding its nature and dimensionality. We conceptualise retailer equity as a four-dimensional construct comprising retailer awareness, retailer associations, perceived retailer quality, and retailer loyalty. The paper reports the result of an empirical study of a convenience sample of 601 shopping mall consumers at an Australian state capital city. Following a confirmatory factor analysis using structural equation modelling to examine the dimensionality of the retailer equity construct, the proposed model is tested for two retailer categories: department stores and speciality stores. Results confirm the hypothesised four-dimensional structure.

An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification

Racing algorithms have recently been proposed as a general-purpose method for performing model selection in machine teaming algorithms. In this paper, we present an empirical study of the Hoeffding racing algorithm for selecting the k parameter in a simple k-nearest neighbor classifier. Fifteen widely-used classification datasets from UCI are used and experiments conducted across different confidence levels for racing. The results reveal a significant amount of sensitivity of the k-nn classifier to its model parameter value. The Hoeffding racing algorithm also varies widely in its performance, in terms of the computational savings gained over an exhaustive evaluation. While in some cases the savings gained are quite small, the racing algorithm proved to be highly robust to the possibility of erroneously eliminating the optimal models. All results were strongly dependent on the datasets used.