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标题：Multivariate analysis of attitudes on financial and other aspects of business ethics of future managers
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作者：Knežević, Blaženka ; Kurnoga, Nataša ; Šimurina, Nika 等
期刊名称：Croatian Operational Research Review
印刷版ISSN：1848-0225
出版年度：2017
卷号：8
期号：1
页码：93-105
DOI：10.17535/crorr.2017.0006
语种：English
出版社：Croatian Operational Research Society
摘要：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.
关键词：business ethics; ATBEQ; factor analysis; cluster analysis