- Author
- Malara Maciej (Wrocław University of Technology), Mazurkiewicz Mariusz (Wrocław University of Technology)
- Title
- Modelling the Determinants of Winning in Public Tendering Procedures Based on the Activity of a Selected Company
- Source
- Operations Research and Decisions, 2012, vol. 22, no. 1, s. 51-62, rys., tab., bibliogr. 14 poz.
- Keyword
- Analiza dyskryminacyjna, Analiza skupień, Prawo zamówień publicznych
Discriminant analysis, Cluster analysis, Public procurement law - Note
- summ.
- Abstract
- The purpose of this article is to identify the factors influencing the probability of winning in public procurement procedures and to assess the strength of their impact from the perspective of both: the bidder and procurer. The research was conducted with the use of series of quantitative methods: binary logistic regression, discriminant analysis and cluster analysis. It was based on a sample consisting of public tenders, in which the examined company performed the role of a bidder. Thus, the research process was aimed at both identifying the factors of success and estimating the probability of achieving it, where it was possible to obtain probabilities. The main idea of this research is to answer questions about the utility of various methods of quantitative analysis in the case of analyzing determinants of success. Results of the research are presented in the following sequence of sections: characteristics of the examined material, the process of modelling the probability of winning, evaluation of the quality of the results obtained. (original abstract)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of Poznań University of Economics and Business
The Main Library of the Wroclaw University of Economics - Full text
- Show
- Bibliography
-
- ACZEL A.D., Complete Business Statistics, Richard D. Irwin, Inc., Sydney 1993.
- AGRESTI A., Categorical Data Analysis, Wiley, New York 2002.
- AMEMIYA T., Advanced Econometrics, Harvard University Press, 1985.
- Documentation of the SPSS 17.0 statistical package.
- EVERITT B.S., LANDAU S., LEESE M., Cluster analysis, Oxford University Press, London 2001.
- GUTIERREZ P.A., SALCEDO-SANZ S., SEGOVIA-VARGAS M.J., SANCHIS A., PORTILLA-FIGUERAS J.A., et al., Generalized Logistic Regression Models Using Neural Network Basis Functions Applied to the Detection of Banking Crises, Lecture Notes in Computer Science, Trends in Applied Intelligent Systems, 2010, 6098, 1-10.
- HOSMER D.W., LAMESHOW S., Applied Logistic Regression, 2nd Ed., Wiley, Chichester 2000.
- JAIN A.K., MURTY M.N., FLYNN P.J., Data Clustering: A Review, ACM Computing Surveys, 31, 3, 1999, 264-323.
- MADDALA G.S., Introduction to Econometrics, 3rd Ed., Wiley, Chichester 2001.
- MALARA Z., Przedsiębiorstwo w globalnej gospodarce, PWN, Warszawa 2006.
- MALAWSKI M., O rozwiązaniu średnich wypłat zagadnienia przetargowego Nasha, Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk, 2001 (935), 1-10.
- MINASOWICZ A., KOSTRZEWA M., Analiza wielokryterialnego wyboru najkorzystniejszej oferty w postępowaniach przetargowych z wykorzystaniem systemu eksperckiego opartego na przesłankach rozmytych, http://suw.biblos.pk.edu.pl/downloadResource&mId=154505 state on: 25.02.2012.
- PRAHALAD C.K., HAMEL G., Competing for the future, Harvard Business Press, 1994.
- Public Procurement Law, Act of 29 January 2004 (together with subsequent amendments).
- Cited by
- ISSN
- 2081-8858
- Language
- eng
- URI / DOI
- http://dx.doi.org/10.5277/ord120103
