The performances of international construction projects are quite vulnerable to the conditions of the host country. Because going overseas requires a substantial amount of resources, the process of country evaluation and selection is important in a firm's decision making. Despite an emerging interest and need for the systematic evaluation of countries, existing studies remain limited to case studies for one or a few countries because of the lack of multiple country databases. To overcome this limitation, this paper performs a quantitative analysis to classify countries in the construction industry. Based on international marketing theory and a literature review, the authors not only identify country classification variables but also suggest an analytical approach for diagnosing multidimensional aspects of countries in terms of country attractiveness and past project performance. To evaluate 32 countries, this study uses international institutional (construction industry-specific and country-specific) data and project-level data for Korean firms over the 25-year period from 1990 to 2014. Using a factor analysis and cluster analysis, this study classifies 32 countries according to four different factors (business environment, market opportunity, the possibility of project success, and market experience) and explains each country's current status. Compared with existing country risk indices, which provide only one deterministic value, the proposed approach has the potential to capture construction industry-specific trends and actual project performance, enabling firms to not only evaluate and classify candidate countries in a timely manner but also to make better decisions when addressing country-related problems in the construction industry.
|Journal||Journal of Management in Engineering|
|Publication status||Published - 2017 Jul 1|
Bibliographical noteFunding Information:
This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korean government (MOST) (NRF-2015R1A2A1A09007327).
All Science Journal Classification (ASJC) codes
- Industrial relations
- Strategy and Management
- Management Science and Operations Research