Abstract
This paper examines the effect of culture on national innovation and prosperity. Because culture shapes the way people think about and behave in regard to risk, opportunities, and rewards, it should influence the nature of entrepreneurial activity and, by extension, economic outcomes. Using structural equation modeling on a sample of 63 countries, we propose and test a comprehensive explanation of how culture as an umbrella construct (as opposed to an analysis of its constituent parts) affects innovation and national prosperity. We propose a two-stage model of innovation, and find support for our hypothesized relationship that “economic creativity” influences “innovation implementation.” At the national level, we find that culture does indeed influence economic creativity. We also find that innovation implementation explained some of the variation in prosperity across countries. By establishing that “big picture” culture matters to innovation, the door has opened for researchers to evaluate this relationship using data from any one of a number of rival culture frameworks. Moreover, these empirical finding buttress the theoretical arguments that culture powerfully shapes the character of national innovation.
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The power of culture to shape national innovation systems notwithstanding, within-country variations in regional innovation systems are inevitable. Saxenian's (1994) landmark study comparing the two dominant innovation regions in the United States in the 1980s and 1990s—California's Silicon Valley and Route 128 in Massachusetts—demonstrated that widely divergent regional innovation systems can and do emerge within the same national institutional framework. During the 1980s and 1990s Silicon Valley outperformed Route 128 on a number of important metrics. Best (2001) documents the subsequent transformation of the Massachusetts innovation system during the 1990s toward a style that more closely resembled that of the economically more successful Silicon Valley model. Over time, it seems regional innovation systems within the same national innovation system will vary within a much narrower range than was previously thought (Asheim and Gertler 2005).
Kluckhohn and Strodtbeck of the Harvard “Values Project” (1961) described, in their seminal research, culture as variations in value orientations, which could be analyzed both among societies and within a given society. They theorized that cultures are unique in the way their members prefer to respond to a set of common problems or questions: (1) What is the character of human nature—are people basically good, evil, or both?; (2) What is the relation of humans to nature—should humans subjugate themselves to, live in harmony with, or attempt to master nature?; (3) What is the temporal focus of human life—past, present, or future?; (4) What is the preferred mode of activity—being, becoming, or doing?; (5) How should humans relate to others—as individualists or collectivists? Unfortunately, data to support the model are not available on more than a few societies, which limits the way in which the model could be used in comparative research.
Hofstede (1980) conducted a landmark international study, and concluded that national cultures vary on four dimensions: Individualism/collectivism, power distance, uncertainty avoidance, and masculinity/femininity. (Some years later, Hofstede and Michael Bond of the University of Hong Kong added a fifth dimension, “Confucian dynamism,” which intended to capture unique cultural characteristics of Asian societies and differentiate them from Western cultures.) We are aware of at least two major studies reviewing empirical research carried out with Hofstede's variables, Kirkman et al. (2006) reviewed 180 published studies and Sondergaard (1994) reviewed 61 empirical studies. Both found overwhelmingly confirmation of Hofstede's variables. Sondegaard concluded that “By and large, Hofstede’s findings were confirmed in the reviewed replication studies once some modifications with respect to perception of the environment at the time of the research and known sample characteristics had been made” (1994, p. 452).
Following Hofstede, Trompenaars (1994) proposed seven variables to differentiate cultures, several of which overlap with Kluckhohn and Strodtbeck, and Hofstede: (1) Universalism versus particularism (the relative preference for general rules or context-and relationship-specific guidelines when making decisions in ambiguous situations); (2) individualism versus collectivism; (3) neutral or affective display of emotion; (4) specific versus diffuse assignment of responsibility; (5) achievement versus ascription (how status is attributed to members of a culture); (6) sequential versus synchronic preference for processing of activities; (7) free will versus determinism (The shared belief that outcomes in life are a function of either factors internal to the person, or instead from the environment or other external factors). While Trompenaars’ added variables have enriched our understanding of culture and cultural differences between nations and groups of people, additional studies are needed to provide evidence of the reliability and validity of the seven proposed variables. Researchers have begun to incorporate some of Trompensaars’ concepts in their models (e.g., McGuire et al. 2006), however, significant country-level data with evidence of reliability and validity are yet unavailable in published reports.
The GLOBE research consortium model (Javidan and House 2001) measured both values and cultural practices in numerous countries, initially with the objective to study differences in leadership styles and effectiveness in different cultures. GLOBE identified nine variables: uncertainty avoidance, future orientation, power distance, institutional collectivism, humane orientation, performance orientation, in-group collectivism, gender egalitarianism, and assertiveness. The GLOBE model and dataset offer much promise to researchers, although criticisms have been leveled at both the model (e.g., possible conceptual overlap of variables) and the secretiveness of the research consortium (Hofstede 2006).
McGuire et al. (2006) presented a promising model that built on and extended the previous research, with nine dimensions, namely: doing versus being orientation, individualism versus collectivism (from Kluckhohn and Strodtbeck); uncertainty avoidance, power distance, and long-term versus short-term orientation (adapted from Hofstede); universalism versus particularism, determinism versus free will, (from Trompenaars), plus heterogeneity versus homogeneity, and facework. While evidence of the reliability and validity of some of the dimensions has been provided (e.g., McGuire et al. 2008), data for a large sample of countries are unavailable.
There are caveats to individualism when discussing innovation implementation. At an extreme, individualism might impair the ability to reach consensus and take collective action necessary for implementation of new ideas (Morris et al. 1993). The preponderance of evidence from the research, nonetheless, suggests a strong positive influence of individualism on both creativity and innovation.
In general, Earley (2006) objects to the aggregation of cultural values for analysis at any level below the societal-level.
A latent variable is a hypothesized and unobserved concept that can only be approximated by observable or measurable variables (Hair et al. 1998, p. 585).
Kurtosis scores may differ depending on the statistical software package used. The origin in computing Kurtosis is 3 (±3 implying normality). STATA, used here, returns Pearson Kurtosis, which for a normally distributed variable is centered on 3. SAS and SPSS, for example, produce what is know as Kurtosis-3 or Fisher Kurtosis, which for a normally distributed variable is centered on zero.
When working with archival data one is often constrained by the choices other researchers make. In our case, we were constrained by Hofstede's sample. We did not attempt to select countries that might provide specific sources of evidence, which would have resulted in sample selection bias. And we are confident that our data, which include industrialized, developing, and transition economies, provide ample representativeness. Nevertheless, given the size of our sample, when judging the generalizability of our results, a narrower interpretation is recommended.
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Williams, L.K., McGuire, S.J. Economic creativity and innovation implementation: the entrepreneurial drivers of growth? Evidence from 63 countries. Small Bus Econ 34, 391–412 (2010). https://doi.org/10.1007/s11187-008-9145-7
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DOI: https://doi.org/10.1007/s11187-008-9145-7