Choosing the Production Function Model for an Optimal Measurement of the Restructuring Efficiency of the Polish Metallurgical Sector in Years 2000–2015.

Gajdzik, Bożena and Gawlik, Remigiusz (2018): Choosing the Production Function Model for an Optimal Measurement of the Restructuring Efficiency of the Polish Metallurgical Sector in Years 2000–2015. Published in: Metals , Vol. 8, No. 1 (24 January 2018): p. 23.

Abstract

Between 2000 and 2015, the Polish metallurgical sector was subject to serious restructuring. Presented research aimed at providing a framework for possibly most accurate measurement of efficiency of this process. The study employed: (I) Quantitative research for elaboration of production function models: power regression Cobb-Douglas function with its developments; (II) Qualitative research: Analytic Hierarchy Process for assessment of relevance of efficiency evaluation criteria in reference to various production function models in metallurgy sector: (i) sectoral added value (net production); (ii) production sold; and, (iii) steel production volume. Criteria relevance has been assessed by scientists and practitioners with specialization in metallurgy. As a result the sectoral added value function has been chosen as the one that optimally reflects sector’s restructuring efficiency. This, in turn, constitutes a qualitative confirmation of previous research result, which has been verified with a quantitative method. Practical outcome is a more precise modelling of efficiency of restructuring processes in the metallurgical sector, both for scientific and business needs. The main research limitations originate from the sector itself—in order to make our tool more universal, further research should be led in parallel branches of industry.

• Item Type: MPRA Paper
• Language: English
• Keywords: production function; metallurgical sector; restructuring; multicriteria decision-making; Analytic Hierarchy Process
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; L - Industrial Organization > L6 - Industry Studies: Manufacturing > L61 - Metals and Metal Products ; Cement ; Glass ; Ceramics; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O32 - Management of Technological Innovation and R&D

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