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Simultaneous Equation Model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance
Dipartimento di Filosofia e Scienze Sociali, Università del Salento, Lecce, Italy.
Linköping University, Department of Management and Engineering, Quality Technology and Management . Linköping University, The Institute of Technology.
2009 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 36, no 7, 801-815 p.Article in journal (Refereed) Published
Abstract [en]

The aim of this paper is to study the effect of management factors on enterprise performance, considering a survey that the University Consortium in Engineering for Quality and Innovation has led. The relationships between management factors and enterprise performance are formalized by a Simultaneous Equation Model based on the generalized maximum entropy (GME) estimation method. The format of this paper is as follows. In Section 2, the data collected, the questionnaire evaluation, and the management model analytical formulation are introduced. In Section 3, the GME formulation is specified, showing the main characteristics of the estimation method. In Section 4, the results and a comparison among GME, partial least squares (PLS), and maximum likelihood estimation (MLE) is shown. In Section 5, concluding remarks are discussed.

Place, publisher, year, edition, pages
Taylor & Francis , 2009. Vol. 36, no 7, 801-815 p.
Keyword [en]
Generalized maximum entropy, human resources, leadership, maximum likelihood estimation, partial least squares, performance, Simultaneous Equation Model, strategic planning
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-19134DOI: 10.1080/02664760802510026OAI: oai:DiVA.org:liu-19134DiVA: diva2:223391
Note
This is an electronic version of an article published in: E Ciavolino and Jens Jörn Dahlgaard , Simultaneous Equation Model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance, 2009, JOURNAL OF APPLIED STATISTICS, (36), 7, 801-815. JOURNAL OF APPLIED STATISTICS is available online at informaworldTM: http://dx.doi.org/10.1080/02664760802510026 Copyright: Taylor & Francis http://www.tandf.co.uk/journals/default.aspAvailable from: 2009-07-06 Created: 2009-06-12 Last updated: 2017-12-13Bibliographically approved

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