

Author: Troutt M.D. Zhang A. Tadisina S.K. Rai A.
Publisher: Springer Publishing Company
ISSN: 0254-5330
Source: Annals of Operations Research, Vol.74, Iss.1, 1997-01, pp. : 289-304
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
This paper discusses a class of modeling alternatives to regression or canonical corre-lation when dependent variables can be logically considered as outputs to be maximized. Likewise independent variables should be considered as constraints on resources which establish limits to the output levels. A total factor productivityyefficiency ratio of non-negatively weighted outputs divided by similarly weighted inputs is to be fitted to the data by the Maximum Decisional Efficiency Principle. It is assumed that such data, when obtained from experienced managers or viable organizations, should tend to exhibit purposeful rather than random behavior under appropriate parameter value choices and density assumptions. Some model quality improvement issues, analogous to those in regression theory, are also proposed (e.g. criterion choice, residual analysis, and outliers). Potential advantages of the approach are discussed for empirical studies in Information Technology and Productiony Operations Management settings.
Related content


By Song Ma-Lin Guan Youyi Song Feng
Kybernetes: The International Journal of Systems & Cybernetics, Vol. 42, Iss. 6, 2013-06 ,pp. :


By Keramati Abbas Albadvi Amir
International Journal of Information Technology and Management, Vol. 8, Iss. 4, 2009-05 ,pp. :

