Managers’ Corporate Entrepreneurial Actions and Job Satisfaction

Through the development and extension of theories and scholars’ subsequent empirical analyses of significant, theoretically grounded research questions, the knowledge about corporate entrepreneurship (CE) and its successful use continues to advance. Moreover, the literature suggests important relationships between the corporate environment, managers’ entrepreneurial behavior and successful implementation of corporate entrepreneurship actions. In an attempt to test some of those relationships, we describe an empirical study of 523 managers that examines the relationships among the antecedents to managers’ entrepreneurial behavior, a decision to implement entrepreneurial actions, and resulting job satisfaction and reinforcement practices.     

Structuring Corporate Headquarters: An Investigation of Franchising

This article focuses on the structuring of the corporate headquarters in a franchise organization. Four essential issues that are related to franchisors organizational structure are discussed—homogeneity and heterogeneity of franchisors structure, company-owned and franchise arrangement, the dynamics between strategy and structure, and performing innovative and administrative functions simultaneously in the headquarters. Propositions are given for each issue. The results of qualitative analysis associated with each issue are discussed.     

University Students’ Attitudes Towards Entrepreneurship: A Two Countries Comparison

There is general agreement that attitudes towards the entrepreneur, entrepreneurial activity, and its social function are determinant factors for university students to decide an entrepreneurial career.This empirical study aims at assessing and comparing the attitudes of university students towards entrepreneurship and enterprise formation in Catalonia and Puerto Rico, using a sample of 837 and 435 students, respectively.Results reveal a positive entrepreneur’s image. Both samples have a favorable perception of desirability of new venture creation, although the perception of feasibility is by far not so positive and only a small percentage has the firm intention to create a new company.     

Taking the “Q” Out of Research: Teaching Research Methodology Courses Without the Divide Between Quantitative and Qualitative Paradigms

The purpose of this paper is to provide evidence that the debate between quantitative and qualitative is divisive and, hence, counterproductive for advancing the social and behavioral science field. We advocate that all graduate students learn to utilize and to appreciate both quantitative and qualitative research methodologies. As such, students will develop into pragmatist researchers who are able to utilize both quantitative and qualitative techniques when conducting research. We contend that the best way to accomplish this is by eliminating quantitative research methodology and qualitative research methodology courses from curricula and replacing these with research methodology courses at different levels that simultaneously teach both quantitative and qualitative techniques within a mixed methodological framework.An earlier version of this article received the 2003 Southwest Educational Research Association (SERA) Outstanding Paper Award.     

Probability theory in fuzzy sample spaces

This paper tries to develop a neat and comprehensive probability theory for sample spaces where the events are fuzzy subsets of The investigations are focussed on the discussion how to equip those sample spaces with suitable -algebras and metrics. In the end we can point out a unified concept of random elements in the sample spaces under consideration which is linked with compatible metrics to express random errors. The result is supported by presenting a strong law of large numbers, a central limit theorem and a Glivenko-Cantelli theorem for these kinds of random elements, formulated simultaneously w.r.t. the selected metrics. As a by-product the line of reasoning, which is followed within the paper, enables us to generalize as well as to bring together already known results and concepts from literature.Acknowledgement. The author would like to thank the participants of the 23rd Linz Seminar on Fuzzy Set Theory for the intensive discussion of the paper. Especially he is indebted to Professors Diamond and Höhle whose remarks have helped to get deeper insights into the subject. Additionally, the author is grateful to one anonymous referee for careful reading and valuable proposals which have led to an improvement of the first draft.This paper was presented at the 23rd Linz Seminar on Fuzzy Set Theory, Linz, Austria, February 5–9, 2002.     

Measuring Hospital Performance in the Presence of Quasi-Fixed Inputs: An Analysis of Québec Hospitals

This research proposes an approach to measure hospital performance based on a generalization of Banker and Morey (1986) and Førsund (1996). This approach considers quasi-fixed inputs explicitly, calculates their implicit cost, and quantifies returns to scale. The performance measure is decomposed into allocative and technical inefficiencies. Based on a very complete data set of Québec hospitals, we find that significant inefficiencies of up to 17% ($700 CAN million) could have been saved through improved performance. Postestimation analyses that include qualitative measures of care suggest that differences in performance are attributable to differences in management or unobservable quality of care rather than patient case mix.     

On estimating the mean of the selected normal population under the LINEX loss function

Following Parsian and Farsipour (1999), we consider the problem of estimating the mean of the selected normal population, from two normal populations with unknown means and common known variance, under the LINEX loss function. Some admissibility results for a subclass of equivariant estimators are derived and a sufficient condition for the inadmissibility of an arbitrary equivariant estimator is provided. As a consequence, several of the estimators proposed by Parsian and Farsipour (1999) are shown to be inadmissible and better estimators are obtained. Received January 2001/Revised May 2002     

Pitfalls of Normal-Gamma Stochastic Frontier Models

Although conceptually pleasing, normal-gamma frontier models lead to difficult estimation problems. It is shown here that unless the sample size reaches several thousands of observations the shape parameter of the gamma density is hard to estimate, and that this carries over to estimates of the stochastic frontier, the individual inefficiencies, and the allocation of the overall variance to the stochastic frontier and to the inefficiencies.