Ranking and Clustering Australian University Research Performance, 1998-2002

This paper clusters and ranks the research performance of thirty-seven Australian universities over the period 1998-2002. Research performance is measured according to audited numbers of PhD completions, publications and grants (in accordance with rules established by the Department of Education, Science and Training) and analysed in both total and per academic staff terms. Hierarchical cluster analysis supports a binary division between fifteen higher and twenty-two lower-performing universities, with the specification in per academic staff terms identifying the self-designated research intensive "Group of Eight" (Go8) universities, plus several others in the better-performing group. Factor analysis indicates that the top-three research performers are the Universities of Melbourne, Sydney and Queensland in terms of total research performance and the Universities of Melbourne, Adelaide and Western Australia in per academic staff terms.Higher education, hierarchical cluster analysis, research performance, factor analysis

Tanzania: A Hierarchical Cluster Analysis Approach

It is common for researchers and rural development policy stakeholders to describe smallholder farmers as a homogeneous group in terms of their demand for farm credit and farm investment behaviour. Given the diversity of factors such as farm credit products (input credit in cash, input credit in kind), farming systems (extensive Vs intensive farming, food crop Vs traditional cash crop production, crop production Vs livestock keeping), asset endowment, income sources and experience in farm credit borrowing, it is obvious that the demand for farm credit and use with which it is put are also diverse among farmers. Using survey data from Kibondo district, west Tanzania, we use hierarchical cluster analysis to classify borrower farmers according to their borrowing behaviour into four distinctive clusters. The appreciation of the existence of heterogeneous farmer clusters is vital in forging credit delivery policies that are not only appropriate for particular categories of farmers but also that do provide potential for reducing supply side transaction risks and costs.Key words: Smallholder farmers, hierarchical cluster analysis, farm credit supply

Commonalities and Disparities among the EU Candidate

One of the important challenges of the European Union (EU) at the beginning of the 21st century is its enlargement. After the integration of the 12 countries in 2005 and 2007, the EU continues its strategy for stability, security and prosperity in Europe. The new candidate countries, at different levels of development, are Western Balkan countries and Turkey. The objective of the paper is to investigate the differences among the EU candidate countries according to the current measures of welfare/sustainability and to find their similarities and differences. This analysis of the differences and the similitude between candidate countries is done by using multidimensional scaling method (MDS) and hierarchical cluster analysis of sustainability, which takes into account, at the same time, economic, health, standard of living, people and environmental variables, as part of the multivariate statistical analysis technique - one of the basic methods of multidimensional scaling. Furthermore, MDS method allows a standardized (transformed) analysis of the data collected in different scales. This study is based on the data standardized by means of Z score transformation. The main conclusions of the analysis light up the differences between candidate countries and could be an important tool for the policy makers to focus their efforts on the difficult goal to join the European Union.multidimensional scaling, hierarchical cluster analysis, statistical analysis

Multivariate analysis of attitudes on financial and other aspects of business ethics of future managers

Business ethics is a set of rules by which individuals and institutions behave and conduct business in a responsible manner. It involves appropriate constraints on the pursuit of self-interest and profits, particularly when actions affect other stakeholders. Research on financial and other aspects of business ethics includes an examination of personal attitudes which give insight into ways in which people tend to behave as employees, managers, taxpayers and consumers. In this research, the standard ATBEQ questionnaire was extended with five variables covering corporate social responsibility and applied to a sample of business administration students in Croatia. The aim of the research was to identify groups of future managers based on an evaluation of their attitudes on business ethics and corporate social responsibility. The analysis was divided into two parts. In the first part, factor analysis was performed on 35 variables (attitudes) relating to business ethics and corporate social responsibility. Six factors were extracted and factor scores were calculated. In the second part, hierarchical and non-hierarchical cluster analyses were conducted. Factor scores were used as input data for the cluster analysis. Firstly, the hierarchical cluster analysis was run on the calculated factor scores. According to the dendrogram, a three-cluster solution was chosen. The non-hierarchical cluster analysis was then used to improve the results of the hierarchical cluster solution. Finally, these clusters (groups) of future managers were characterised according to their attitudes on financial and other aspects of business ethics and corporate social responsibility