A Learning Based Vertical Integration Decision Model

Menekşe Gizem Görgün*, Seçkin Polat, Umut Asan

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Özet

Vertical integration decisions, also referred to as make or buy decisions, affect firm activity areas that determine boundaries that play a strategic role in the success of firms. The decisions may result in form of spot market usage, long-term contracts, joint ventures, and in-house productions. This study first reviews the decision modeling approaches suggested in the literature for vertical integration. The review shows that for decision making, most of the approaches are qualitative in nature and but there are also optimization models and expert based models. Thus, a new learning based probabilistic classification approach is proposed to model the vertical integration decision problem. This data-driven quantitative approach using Naïve Bayes is able to represent the uncertainty inherent in the decision problem. The applicability and effectiveness of the developed learning based vertical integration decision model is demonstrated by an example that covers real software make or buy cases in a retail company. 85% of the decisions were correctly classified by the developed data-driven model.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
EditörlerCengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar131-137
Sayfa sayısı7
ISBN (Basılı)9783030855765
DOI'lar
Yayın durumuYayınlandı - 2022
EtkinlikInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Turkey
Süre: 24 Ağu 202126 Ağu 2021

Yayın serisi

AdıLecture Notes in Networks and Systems
Hacim308
ISSN (Basılı)2367-3370
ISSN (Elektronik)2367-3389

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???event.eventtypes.event.conference???International Conference on Intelligent and Fuzzy Systems, INFUS 2021
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot24/08/2126/08/21

Bibliyografik not

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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