Making international expansion decision for construction enterprises with multiple criteria: a literature review approach

References

• Aghaei-Chadegani A, Salehi H, Yunus MM, Farhadi H, Fooladi M, Farhadi M, Ale Ebrahim N. 2013. A comparison between two main academic literature collections: web of science and scopus databases. Asian Soc Sci. 9:18–26.
   Google Scholar
• Al-Tabtabai H, Alex AP 2000. Modeling the cost of political risk in international construction projects. Project Manag J. 31:4–13.
   Google Scholar
• Bu-Qammaz AS, Dikmen I, Birgonul MT. 2009. Risk assessment of international construction projects using the analytic network process. Can J Civ Eng. 36:1170–1181.
   Web of Science ®Google Scholar
• Chan EH, Suen HC, Chan CK. 2006. MAUT-based dispute resolution selection model prototype for international construction projects. J Constr Eng Manag. 132:444–451.
   Web of Science ®Google Scholar
• Chau KW. 1997. The ranking of construction management journals. Constr Manag Econ. 15:387–398.
   Google Scholar
• Chen C, Messner JI. 2010. Permanent versus mobile entry decisions in international construction markets: influence of home country–and firm-related factors. J Manag Eng. 27:2–12.
   Web of Science ®Google Scholar
• Chen SM, Tan JM. 1994. Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets Syst. 67:163–172.
   Web of Science ®Google Scholar
• Cheng MY, Tsai HC, Chuang KH. 2011. Supporting international entry decisions for construction firms using fuzzy preference relations and cumulative prospect theory. Expert Syst Appl. 38:15151–15158.
   Web of Science ®Google Scholar
• Dikmen I, Birgonul MT. 2004. Neural network model to support international market entry decisions. J Constr Eng Manag. 130:59–66.
   Web of Science ®Google Scholar
• Dikmen I, Birgonul MT, Gur AK. 2007. A case-based decision support tool for bid mark-up estimation of international construction projects. Autom Constr. 17:30–44.
   Web of Science ®Google Scholar
• Dikmen I, Birgonul MT, Han S. 2007. Using fuzzy risk assessment to rate cost overrun risk in international construction projects. Int J Project Manag. 25:494–505.
   Google Scholar
• Downe‐Wamboldt B. 1992. Content analysis: method, applications, and issues. Health Care Women Int. 13:313–321.
   PubMedGoogle Scholar
• Elo S, Kyngäs H. 2008. The qualitative content analysis process. J Adv Nurs. 62:107–115.
   PubMed Web of Science ®Google Scholar
• Fellows RF, Liu AM. 2008. Research methods for construction. 3rd ed. Sussex: John Wiley & Sons.
   Google Scholar
• Gad GM, Kalidindi SN, Shane J, Strong K. 2011. Analytical framework for the choice of dispute resolution methods in international construction projects based on risk factors. J Legal Affairs Dispute Resol Eng Const. 3:79–85.
   Google Scholar
• Gunhan S, Arditi D. 2005a. Factors affecting international construction. J Constr Eng Manag. 131:273–282.
   Web of Science ®Google Scholar
• Gunhan S, Arditi D. 2005b. International expansion decision for construction companies. J Constr Eng Manag. 131:928–937.
   Web of Science ®Google Scholar
• Guz AN, Rushchitsky JJ. 2009. Scopus: a system for the evaluation of scientific journals. Int Appl Mech. 45:351–362.
   Google Scholar
• Han SH, Diekmann JE 2001a. Approaches for making risk-based go/no-go decision for international projects. J Constr Eng Manag. 127:300–308.
   Web of Science ®Google Scholar
• Han SH, Diekmann JE. 2001b. Making a risk-based bid decision for overseas construction projects. Constr Manag Econ. 19:765–776.
   Google Scholar
• Han SH, Diekmann JE, Lee Y, Ock JH. 2004. Multicriteria financial portfolio risk management for international projects. J Constr Eng Manag. 130:346–356.
   Web of Science ®Google Scholar
• Han SH, Kim DY, Kim H. 2007. Predicting profit performance for selecting candidate international construction projects. J Constr Eng Manag. 133:425–436.
   Web of Science ®Google Scholar
• Han SH, Kim DY, Kim H, Jang WS. 2008. A web-based integrated system for international project risk management. Autom Constr. 17:342–356.
   Web of Science ®Google Scholar
• Hastak M, Shaked A. 2000. ICRAM-1: model for international construction risk assessment. J Manag Eng. 16:59–69.
   Web of Science ®Google Scholar
• Hawk D. 2006. Conditions of success: a platform for international construction development. Constr Manag Econ. 24:735–742.
   Google Scholar
• Jato-Espino D, Castillo-Lopez E, Rodriguez-Hernandez J, Canteras-Jordana JC. 2014. A review of application of multi-criteria decision making methods in construction. Autom Constr. 45:151–162.
   Web of Science ®Google Scholar
• Kabir G, Sadiq R, Tesfamariam S. 2014. A review of multi-criteria decision making methods for infrastructure management. Struct Infrastruct Eng. 10:1176–1210.
   Web of Science ®Google Scholar
• Kabir G, Sadiq R, Tesfamariam S. 2014. A review of multi-criteria decision making methods for infrastructure management. Struct Infrastruct Eng. 10:1176–1210.
   Web of Science ®Google Scholar
• Kangas J, Store R, Leskinen P, Mehtätalo L. 2000. Improving the quality of landscape ecological forest planning by utilising advanced decision-support tools. Forest Ecol Manag. 132:157–171.
   Web of Science ®Google Scholar
• Khatri N, Ng HA. 2000. The role of intuition in strategic decision making. Hum Relat. 53:57–86.
   Web of Science ®Google Scholar
• Kim DY, Ashuri B, Han SH. 2012. Financial valuation of investments in international construction markets: real-options approach for market-entry decisions. J Manag Eng. 29:355–368.
   Web of Science ®Google Scholar
• Kim DY, Han SH, Kim H. 2008. Discriminant analysis for predicting ranges of cost variance in international construction projects. J Constr Eng Manag. 134:398–410.
   Web of Science ®Google Scholar
• Korhonen P, Moskowitz H, Wallenius J. 1992. Multiple criteria decision support-A review. Eur J Oper Res. 63:361–375.
   Web of Science ®Google Scholar
• Li H, Jin Z, Li V, Liu G, Skitmore RM. 2013. An entry mode decision-making model for the international expansion of construction enterprises. Eng Constr Arch Manag. 20:160–180.
   Google Scholar
• Lin KL. 2010. Human resource allocation for remote construction projects. J Manag Eng. 27:13–20.
   Web of Science ®Google Scholar
• Malhotra NK. 2009. Marketing research: an applied orientation, 6th ed. New Jersey: Pearson Education: Pearson Education.
   Google Scholar
• Mendoza GA, Martins H. 2006. Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms. Forest Ecol Manag. 230:1–22.
   Web of Science ®Google Scholar
• Moselhi O, Hegazy T, Fazio P. 1991. Neural networks as tools in construction. J Constr Eng Manag. 117:606–625.
   Web of Science ®Google Scholar
• Moselhi O, Martinelli A. 1990. Analysis of bids using multiattribute utility theory. Proceeding of the International Symposium on Building Economics and Construction Management; Sydney, Australia; p. 335–45.
   Google Scholar
• Ölçer MG, Akyol DE. 2014. A MADM based decision support system for international contractor rating. J Intell Fuzzy Syst. 27:2163–2175.
   Web of Science ®Google Scholar
• Osei-Kyei R, Chan AP. 2015. Review of studies on the critical success factors for public–private partnership (PPP) projects from 1990 to 2013. Int J Project Manag. 33:1335–46.
   Web of Science ®Google Scholar
• Ozorhon B, Dikmen I, Birgonul MT. 2006. Case-based reasoning model for international market selection. J Constr Eng Manag. 132:940–948.
   Web of Science ®Google Scholar
• Rosengren KE. 1981. Advances in Scandinavia content analysis: An introduction. In: Rosengren KE, editor. Advances in content analysis. Beverly Hills, CA: Sage; pp. 9–19.
   Google Scholar
• Shakhsi-Niaei M., Torabi SA, Iranmanesh SH. 2011. A comprehensive framework for project selection problem under uncertainty and real-world constraints. Comput Ind Eng. 61:226–237.
   Web of Science ®Google Scholar
• Singh D, Tiong RL. 2005. A fuzzy decision framework for contractor selection. J Constr Eng Manag. 131:62–70.
   Web of Science ®Google Scholar
• Sonmez R, Ergin A, Birgonul MT. 2007. Quantiative methodology for determination of cost contingency in international projects. J Manag Eng. 23:35–39.
   Web of Science ®Google Scholar
• Tam CM, Thomas KL, Zhang H. 2007. Decision making and operations research techniques for construction management. Hong Kong: City University of Hong Kong Press.
   Google Scholar
• Tang LC, Atkinson B, Zou RR. 2012. An entropy-based SWOT evaluation process of critical success factors for international market entry: a case study of a medium-sized consulting company. Constr Manag Econ. 30:821–834.
   Google Scholar
• Utama WP, Chan AP, Zahoor H, Gao R. 2016. Review of research trend in international construction projects: a bibliometric analysis. Constr Econ Build. 16:71–82.
   Web of Science ®Google Scholar
• Wanous M, Boussabaine HA, Lewis J. 2003. A neural network bid/no bid model: the case for contractors in Syria. Constr Manag Econ. 21:737–744.
   Google Scholar
• Wood VR, Goolsby JR. 1987. Foreign market information preferences of established US exporters. Int Market Rev. 4:43–52.
   Google Scholar
• Zavadskas EK, Antuchevičienė J, Kapliński O. 2015. Multi-criteria decision making in civil engineering. Part II – applications. Eng StructTechnol. 7:151–167.
   Google Scholar