26. Conceptualizing and Measuring Distance in International Business Research: Recurring Questions and Best Practice Guidelines

In one of the earlier explanations of this notion, Goodnow and Hansz (1972) state that, as firms enter markets further away from the United States, “government becomes less stable, the markets become poorer, the economy becomes less stable, cultural homogeneity declines, legal and geographical barriers go up and cultures become different” (Goodnow and Hansz 1972: 37). Johanson and Vahlne (1977) generalize this argument by stating that the further from the home country, the more uncertainty and the higher the costs of acquiring information.

It is interesting to note that trade, the dependent variable in gravity models, is one of the explanatory variables in the Uppsala model.

There is no grand theory in the sense of a single framework with a set of assumptions, mechanisms, and boundary conditions. That does not mean that there is no theory of national cultural differences (Adler 1983).

Theoretically, such discrete changes can also be found at other levels. For example, Ronen and Shenkar (2013) have shown that countries can be grouped into a limited number of culturally homogeneous supra-national zones.

In light of the popularity of their distance measure, it is interesting to point out that Kogut and Singh’s (1988) findings regarding the effect of uncertainty avoidance on entry mode were stronger than the cultural distance effect (see Kogut and Singh 1988: 424).

Occasionally, this is referred to as Cartesian distance (e.g., Buchner et al. 2017).

In addition to the Kogut and Singh index and the Euclidean index, some researchers have used a mix of the two. For example, Barkema and Vermeulen (1997) use a Euclidean distance index but correct for differences in the variances of each of Hofstede’s cultural dimension by multiplying the individual dimension distances by 1/v_i where v_i is the variance of each cultural dimension. The Kogut and Singh index adapts the scales in a similar way (see Eq. 26.1), but does not take the square root. In this case, the difference between the Kogut and Singh index and this third approach is the aggregation procedure (square root vs. dividing by the number of dimensions). Although this is not the same type of transformation, they are effectively highly correlated.

In the case of South Africa, the WVS-EVS data provide a score for the fifth and sixth dimensions of Hofstede’s framework. The four original Hofstede dimensions refer to Caucasian South Africans only. We have decided not to mix both samples, and hence exclude South Africa from the analysis.

Inglehart (1997) used the WVS-EVS data to develop two dimensions of differences in national cultural values related to degree of materialism. However, his framework is rarely used in management (it is mostly used in sociology and political science). One reason for the limited use of the WVS-EVS data in management is the fact that, despite the use of stratified nationally representative samples and the richness of the WVS-EVS data (they contain more than 200 value-related questions), the user-friendliness of the database is limited. Note also that in its fifth and sixth rounds, the WVS has included a condensed ten-item version of the Schwartz values.

These correlations do not depend on the choice of home country. Drogendijk & Slangen (2006, 372) report a correlation of.97 between the Euclidean and Kogut and Singh versions of the four-dimensional Hofstede index when using the Netherlands as a home country. For the most used home country in cultural distance research, the United States, this correlation is also. 97.

We use data for 2013, but as the QoG index is highly correlated over time (0.99 between t and t + 1), the selected year does not affect the outcome.

The Mahalanobis institutional distance based on six dimensions correlates 0.96 with the five dimensional Mahalanobis institutional distance index (using QoG data).

As the European manager of personnel research at IBM, Geert Hofstede had privileged access to the confidential IBM employee data used to develop his cross-cultural framework. The original data stayed at IBM after Geert Hofstede left IBM in 1973 (based on personal communication from Geert Hofstede).

See Ralston et al. (1997) and Ralston (2008) for an alternative view.

Although both Berry and Beugelsdijk use WVS-EVS to develop Hofstede-inspired cultural dimensions, there is only limited overlap in the WVS-EVS questions used by Berry et al. (2010) and Beugelsdijk et al. (2015). Both studies use the question on trust (WVS code a165). The correlations between the original Hofstede dimensions, and the ones developed by Berry et al. (2010) and Beugelsdijk et al. (2015) differ. Berry et al.’s (2010) individualism correlates 0.24 with Hofstede’s original individualism, Berry et al’s power distance correlates 0.25 with Hofstede’s, uncertainty avoidance correlates 0.52 with Hofstede’s and Berry et al’s masculinity correlates 0.16 with Hofstede’s. For Beugelsdijk et al. (2015), these correlations with the original Hofstede dimensions are: 0.77 for individualism, 0.74 for uncertainty avoidance, 0.72 for power distance, and 0.92 for indulgence versus restraint.

Note that the correlations shown in Table 26.3 are country-specific, because each cultural distance is calculated relative to a different home country. Hence, the correlation between two distance indices can vary depending on home country. A similar country specificity holds for the correlation between the ICRG- and EFI-based institutional distance indices. We have calculated all the cultural distance correlations shown in Table 26.3 as well as the correlation between the ICRG- and EFI-based institutional distance indices for each home country. Calculating the country-specific correlations does not change our overall conclusion.

Schwartz has described the difference between his approach and those of others (i.e., Hofstede) in the following way: “(a) It [the approach] derived the cultural orientations from a priori theorizing rather than post hoc examination of data. (b) It designated a priori the value items that serve as markers for each orientation. (c) It used as measures only items tested for cross-cultural equivalence of meaning. (d) It included a set of items demonstrated to cover the range of values recognized cross-culturally, a step toward ensuring relative comprehensiveness of cultural value dimensions. (e) It specified how the cultural orientations are organized into a coherent system of related dimensions and verified this organization, rather than assuming that orthogonal dimensions best capture cultural reality. (f) It brought empirical evidence that the order of national cultures on each of the orientations is robust across different types of samples from each of a large number of nations around the world [and using different instruments]. These distinctive features increase the promise of this approach for future research.” (Schwartz 2004: 73, and reprinted in Schwartz 2006: 179).

A similar relationship exists between institutional distance and economic distance, because high-quality institutions are generally associated with high levels of economic development (Acemoglu et al. 2005).