CHAIR PROFESSORSHIPS IN BUSINESS IN THE UNITED STATES
This paper provides a profile of the 1,454 business chair professorships in the United States in 1997. The five disciplines covered are accounting, economics, finance, management, and marketing. The University of Pennsylvania had the largest number of chairholders in business in 1997. Three other schools that had more than 40 chairholders each were Harvard, Northwestern and Massachusetts Institute of Technology (MIT). Harvard produced the highest number of graduates serving as chairholders followed by Chicago, MIT, Texas at Austin, Illinois, and Stanford. Most of the schools that produced large numbers of chairholders are listed among the best business schools in the United States.
The selection of a dean in an academic environment: are we getting what we deserve?
Purpose – The purpose of the development of the paper was due to the seemingly endless searching for deans to replace the former dean of three to four years.Design/methodology/approach – The paper was developed around the present relevant secondary data.Findings – The key findings of the paper were that deans were being replaced due to the difference in expectation of the various constituents (e.g. students, faculty, administration, parents) in the performance of the SBA.Research limitations/implications – Limitations of the study were not providing primary data to support the theory based hypotheses of the study.Practical implications – Deans need to recognize that there will be conflicting expectations relative to the performance of the dean and that deans have a very short time to effectuate change in academic organizations.Social implications – Not having such high turnover in dean's positions should provide the stability of management to bring about change need in institutions of higher education.Ori...
Rapid Spatially Coupled AVO Inversion
The Bayesian methodology yields a natural framework for many geophysical inverse problem, see e.g. (Tarantola and Valette, 1982; Tarantola, 1987; Duijndam, 1988a; Duijndam, 1988b). The solution of a Bayesian inverse problem is represented by the posterior distribution. From the posterior distribution the best estimate and the corresponding uncertainty can be extracted and a set of plausible solutions can be drawn.