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Business concentration as Polish enterprises’ path towards development and competitiveness improvement

Andruszkiewicz Krzysztof, Kasprowicz Magdalena

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

2023

z. 173

25--36

Objective: To present, based on subject literature, such important issues as the concept and types of business concentration, as well as the motives and barriers to this phenomenon. The article also aims to show the 2018-2021 scale and course of enterprise mergers and acquisitions in Poland. Project/methodology/approach: The empirical material was drawn from the Navigator Capital and FORDATA annual reports presenting details and analyses of the most important mergers and acquisitions in Poland. Results: As a result of the analyses carried out, the 2018-2021 scale of mergers and acquisitions in Poland was identified in quantitative and value terms.

A stacked generalization framework for the prediction of corporate acquisitions

Tartari E., Doumpos M., Baourakis G., Zopounidis C.

Foundations of Computing and Decision Sciences

2003

Vol. 28, No. 1

41-61

Over the past decade the number of corporate acquisitions has increased rapidly worldwide. This has been mainly due to strategic reasons, since acquisitions play a prominent role in corporate growth. The prediction of acquisitions is of major interest to stockholders, investors, creditors and generally to anyone who has established a relationship with the acquired and non-acquired firm. Most of the previous studies on the prediction of corporate acquisitions have focused on the selection of an appropriate methodology to develop a predictive model and the comparison with other techniques to investigate the relative efficiency of the methods. On the contrary, this study proposes the combination of different methods in a stacked generalization context. Stacked generalization is a general framework for combining different classification models into an aggregate estimation which is expected to perform better than the individual models. This approach is employed to combine models for predicting corporate acquisitions which are developed through different methods into a combined model. Four methods are considered, namely linear discriminant analysis, probabilistic neural networks, rough set theory and the UTADIS multicriteria decision aid method. An application of the proposed stacked generalization approach is presented involving a sample of 96 UK firms.