Similarity assessment of countries to facilitate learning from international construction projects


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2018

Öğrenci: BESTE ÖZYURT

Eş Danışman: İREM DİKMEN TOKER, MUSTAFA TALAT BİRGÖNÜL

Özet:

Knowledge is a major source of competitive advantage in the global construction industry. Companies learn from previous experiences and if they can find an effective way to transfer their previous experiences to forthcoming projects, they can increase their competitiveness. The aim of this thesis is to demonstrate how similar countries can be grouped so that contractors can utilise lessons learned in similar markets to improve project performance in forthcoming projects. For this purpose, at the initial stage of this study, host country factors affecting the success of international construction projects are identified through literature review. An evaluation form is designed and validated by experts to collect country-specific data. After the collection of country data using available resources as well as expert opinion, cluster analysis is performed to group countries where Turkish contractors frequently execute their projects. In this thesis, 39 countries are clustered by using cluster analysis with SPSS 23.0. As a result, three clusters are obtained and further validated by statistical methods as well as by expert opinion. Finally, how identification of similarities and transferring lessons learned between countries may facilitate learning from international construction projects are discussed. It is clear that the clusters identified are not static and may change in time. Also, the country clusters are not generic as they only reflect the Turkish contractors’ perspective and experience in global construction industry. However, research findings provide some evidence that firms may learn from experiences in similar countries and cluster analysis can be utilised to identify similar country clusters.