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A stacked generalization framework for the prediction of corporate acquisitions

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

Foundations of Computing and Decision Sciences

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2003

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Vol. 28, No. 1

41-61

EN

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.

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Data analysis for the identification of Greek distribution channels: the case of organic olive oil

Baourakis G., Drakos P., Spyridakis D.

Foundations of Computing and Decision Sciences

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2001

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Vol. 26, No. 4

239-254

EN

This study offers an assessment of the distribution channels for olive oil in Greece. Greek and international olive oil markets are examined. An insight into the manufacturing, wholesale and retail sectors of major companies along with their corresponding market shares is also presented. A market survey was conducted by questionnaire in Athens, Thessaloniki and Crete in order to record quantitative data, preferences, purchasing criteria, buying procedures and the attitudes of firms towards both conventionally and organically produced olive oil. Personal interviews with executives from major olive oil companies were carried out. Data analysis using descriptive, univariate and bivariate statistics and correspondence analysis was applied.

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A statistical assessment of consumers' criteria regarding organic agricultural products: the case of organic olive oil

Baourakis G., Apostolakis I.

Foundations of Computing and Decision Sciences

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1999

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Vol. 24, No. 1

21-31

EN

The socio-economic parameters of organic farn1ing in the restructuring of small to medium agricultural economies, such as that of Greece, are of significant importance. In these cases organic farn1ing seems to offer a promising alternative and profitable agricultural practice, particularly where organic olive oil is concerned. The paper aims to find, with a statistical assessment, the criteria that the consumers use in order to choose organic products and their willingness to pay in order to buy them. An overview of the Greek organic farming structure is presented and the subjects of the supply of, and demand for, organic olive oil are discussed. A market survey2 was conducted in several areas of Greece in order to record quantitative data, preferences, purchasing criteria, buying procedures and attitudes towards organic olive oil.