John P. Angelidis

The corporate social responsiveness orientation of board members: Are there differences between inside and outside directors?

Differences and similarities between inside and outside board members with regard to their attitudes toward corporate social responsibility are examined. The results indicate that outside directors exhibit greater concern about the discretionary component of corporate responsibility and a weaker orientation toward economic performance. No significant differences between the two groups were observed with respect to the legal and ethical dimensions of corporate social responsibility. Some explanations as well as limited generalizations and implications are developed.

Board members in the service industry: An empirical examination of the relationship between corporate social responsibility orientation and directorial type

One area of business performance of particular interest to both scholars and practitioners is corporate social responsibility. The notion that organizations should be attentive to the needs of constituents other than shareholders has been investigated and vigorously debated for over two decades. This has provoked an especially rich and diverse literature investigating the relationship between business and society. As a result, researchers have urged the study of the profiles and backgrounds of corporate upper echelons in order to better understand this relationship.There is ample evidence that corporations have in recent years increased the proportion of outside directors on their boards. This has been partly in reaction to increased interest in the corporate social responsiveness of business organizations and suggestions that the board of directors could play a unique role in this area. The expectation on the part of practitioners, researchers, and governmental regulators is that outside directors will advocate greater corporate responsiveness to societys needs by playing a more active role in overseeing managerial decisions.The purpose of this study is to partially fill a void in the literature by determining whether or not these expectations are justified, particularly in the service industry. Data were collected as part of a larger cross-national study of corporate social responsibility. A multivariate analysis of variance (MANOVA) of the results of a survey of 307 board members (198 outside and 109 inside directors) indicates that outside directors exhibit greater concern about the discretionary component of corporate responsibility and a weaker orientation toward economic performance. No significant differences between the two groups were observed with respect to the legal and ethical dimensions of corporate social responsibility. Some explanations as well as limited generalizations and implications are developed.

The corporate social responsiveness orientation of hospital directors: does occupational background make a difference?

The results of a survey of 184 directors from 15 hospitals are analyzed to determine their corporate social responsiveness orientation. They indicate that board members whose occupational background is not in health care exhibit greater concern for economic performance and the legal component of corporate responsibility than their counterparts whose occupational background is in health care. No significant differences between the two groups were observed with respect to the ethical and discretionary dimensions of corporate social responsibility. Some explanations as well as limited generalizations and implications are developed.

A Decision Tree Approach to the Interpretation of Multivariate Statistical Techniques.

Abstract Multivariate statistical techniques have become increasingly popular over the last decade in many fields, especially management. However, management researchers, faculty, and students often do not have sufficient statistical training to appreciate the practical application of multivariate techniques. This article discusses the nature, power, and limitations of four of the most widely used multivariate techniques: factor analysis, MANOVA, multiple regression, and multiple discriminant analysis. Decision trees serve as road maps to guide users through the techniques and assist them in interpreting the results.