Abstract
In this era of globalization, an accurate analysis of country-specific advantages (CSAs) is imperative for multinational corporations (MNCs) to thrive in global competition. Integrating previous extensions of Porter's diamond model, this paper introduces the ‘dual double diamond’ (DDD) model as a new approach to analyze CSAs of countries with various characteristics, and empirically tests the explanatory power of each model. The results show that the generalized double diamond (GDD) and nine-factor (NF) models have better explanatory power than Porter's diamond when assessing CSAs of countries with high international connectivity and high human-factor dependency, respectively, and that the DDD model is more comprehensive than the GDD and NF models in explaining CSAs of countries with heterogeneous attributes. This paper also discusses the implications of the DDD model for MNCs investing, or planning to invest, in Asian countries.
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Notes
High correlation coefficients between land area and major natural resources show that land area can be employed as a proxy variable for factor endowments (natural resources): aluminum production: r=0.81; natural gas production: r=0.74; round wood production: r=0.72; oil production: r=0.53; coal production: r=0.51; pig iron and crude steel production: r=0.48; cement production: r=0.37 (all the correlations are significant at the 0.01 level (two-tailed)).
As the probability of committing at least one Type I error in the set of K independent comparisons is calculated as P=1−(1−α)K (Glass and Hopkins, 1996), in order to employ a significance level of 0.05 for the complete set of multiple comparisons, we adopt a significance level of 0.01 for each comparison.
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An early version of this paper was presented at the Academy of International Business 2007 annual meeting in Indianapolis, IN. We thank anonymous AIB and ABM reviewers for their valuable comments.
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Cho, DS., Moon, HC. & Kim, MY. Does one size fit all? A dual double diamond approach to country-specific advantages. Asian Bus Manage 8, 83–102 (2009). https://doi.org/10.1057/abm.2008.27
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DOI: https://doi.org/10.1057/abm.2008.27