Market Orientation within University Schools of Business: Can a Dynamical Systems Viewpoint Applied to a Non-Temporal Data Set Yield Valuable Insights for University Managers?

Autor/inn/en	Cox, John C.; Webster, Robert L.; Hammond, Kevin L.
Titel	Market Orientation within University Schools of Business: Can a Dynamical Systems Viewpoint Applied to a Non-Temporal Data Set Yield Valuable Insights for University Managers?
Quelle	In: American Journal of Business Education, 2 (2009) 7, S.73-82 (11 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1942-2504
Schlagwörter	Business Administration Education; Educational Theories; Problem Sets; Problem Solving; Longitudinal Studies; Systems Analysis; Organizational Theories; Marketing; School Surveys; Data Analysis; Organizational Effectiveness; Participant Satisfaction; Educational Practices; Educational Strategies; Teaching Methods; Operations Research; Higher Education; Factor Analysis + Suchen Sie Ihr Suchwort? Educational theory; Theory of education; Bildungstheorie; Problemstellung; Problemlösen; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; System analysis; Systemanalyse; Organisationstheorie; Auswertung; Unternehmenserfolg; Bildungspraxis; Lehrstrategie; Teaching method; Lehrmethode; Unterrichtsmethode; Hochschulbildung; Hochschulsystem; Hochschulwesen; Faktorenanalyse
Abstract	This study investigates the use of using complexity theory--the study of nonlinear dynamical systems of which chaos and catastrophe theory are subsets--in the analysis of a non temporal data set to derive valuable insights into the functioning of university schools of business. The approach is unusual in that studies of nonlinearity in complex dynamical systems typically involve longitudinal data. Challenges associated with such studies usually involve establishing nonlinearity, obtaining a data set with a sufficient number of entries, and robust mathematical and computational requirements for effective analysis. The format of the paper is as follows: 1) a general description of complex systems is presented which identifies a number of generally accepted characteristics of complex systems, 2) a description of the data set and the research technique utilized, 3) a presentation of the data set as an "attractor" landscape as typically defined in complex systems analysis, 4) potential insights that may be derived from the analysis; and 5) conclusions and recommendations for further study. The value of the study is to demonstrate that within the framework of complexity theory, non longitudinal data may be used to derive valuable managerial insights into the functioning of organizations such as university schools of business. (As Provided).
Anmerkungen	Clute Institute. 6901 South Pierce Street Suite 239, Littleton, CO 80128. Tel: 303-904-4750; Fax: 303-978-0413; e-mail: Staff@CluteInstitute.com; Web site: http://www.cluteinstitute.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01