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Using analytic network process to predict the performance of international construction joint ventures
Date
2007-07-01
Author
Ozorhon, Beliz
Dikmen Toker, İrem
Birgönül, Mustafa Talat
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Strategic collaborations such as joint ventures (JVs) have become an important way of exploiting business opportunities for construction companies. However, such entities are difficult to manage due to their composite structures, which entail diverse organizational cultures, styles, and objectives. Therefore, measurement of JV performance has been an interesting research topic although there is no consensus on the definition, measures, and variables of performance yet. Considering the inherent complexities of the construction projects, only an adequate combination of criteria allows assessing the international construction joint venture (ICJV) performance. Within this study, an analytic network process model is developed to examine the links between the determinants of performance and to observe the influences of these factors on the ICJV performance. As a result, interpartner relations, structural factors and interpartner fit are found to be the most important determinants of ICJV success. Effectiveness of conflict resolution and control mechanisms contribute significantly to ICJV performance. Cultural fit is the most important fit that should be attained between the partners. The performance of the model is tested on eight real construction projects and satisfactory results are obtained.
Subject Keywords
Management Science and Operations Research
,
General Engineering
,
Strategy and Management
,
Industrial relations
URI
https://hdl.handle.net/11511/38852
Journal
JOURNAL OF MANAGEMENT IN ENGINEERING
DOI
https://doi.org/10.1061/(asce)0742-597x(2007)23:3(156)
Collections
Department of Civil Engineering, Article
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B. Ozorhon, İ. Dikmen Toker, and M. T. Birgönül, “Using analytic network process to predict the performance of international construction joint ventures,”
JOURNAL OF MANAGEMENT IN ENGINEERING
, pp. 156–163, 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38852.