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Int. J. Entrepreneurship and Innovation Management, Vol. 10, Nos. 3/4, 2009 353
Copyright © 2009 Inderscience Enterprises Ltd.
A meta-analysis on the influence of national culture on innovation capability
Hongyi Sun Dept. of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 8 Tat Chee Av., Kowloon, Hong Kong, China E-mail: [email protected]
Abstract: This paper records the study on the influence of national cultures on innovation capability. It is a meta-analysis of previous studies. Innovation capability is measured according to the research by Porter and Stern (2001). The national culture is measured according to the study by Hofstede (1991). Hofstede’s (1991) national culture model covers dimensions such as power distance, individualism, masculinity and uncertainty avoidance. Four hypotheses were formulated accordingly to test the relationship between national culture and national innovation capability. It is found out that individualism, power distance and uncertainty avoidance are correlated with national innovation capability. An innovative culture index (ICI) is formulated for benchmarking.
Keywords: national culture; individualism; power distance; uncertainty avoidance; innovation capability.
Reference to this paper should be made as follows: Sun, H. (2009) ‘A meta-analysis on the influence of national culture on innovation capability’, Int. J. Entrepreneurship and Innovation Management, Vol. 10, Nos. 3/4, pp.353–360.
Biographical notes: Hongyi Sun is an Associate Professor at the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong. He is the Director of the famous Engineering Doctorate programme in Engineering Management (EngD-EM). His teaching and research areas include management of technological innovation, quality management, and manufacturing/operations strategy. He is the winner of Teaching Excellence Awards at City University of Hong Kong due to his significant contribution to the teaching and training of management of technological innovation.
1 Introduction
Michael Porter’s model of the national diamond is used to explain the role of the national environment in the competitive position of industries and firms. It is argued that the influence of national culture on the competitive advantage of nations is given too little attention in this model (van den Bosch and van Prooijen, 1992). Porter agrees that van den Bosch and van Prooijen (1992) rightly raise the importance of cultural factors in setting the context for national competitive advantage. Porter and Stern (2001) further
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pointed out that innovation has become the defining challenge for global competitiveness. National culture has attracted the interests of researchers when investigating the driving forces of national innovation capability. There have been a few studies on the impact of national culture on the national innovation capability (Shane, 1993; Steensma et al., 2001; Van Everdingen and Waarts, 2003; Lynn and Gelb, 1996). These studies are mostly base on Hofstede model on national culture. However, the measure of innovation dimensions varies. For example, Shane (1993) uses the rate of trade mark, Van Everdingen and Waarts (2003) uses the adoption rate of enterprises resources planning (ERP), while Steensma et al. (2001) investigate the technological alliances. In this study, the Hofstede’s national culture will also be used to measure national culture. The innovation capability will be based on the national innovation capability index proposed by Porter and Stern (2001). Porter and Stern (2001) provided a systematic measure of the national innovation. The model was used later in the global competitive report. Based on the result on the relationship between national culture and national innovation capability, an innovative culture index (ICI) is proposed and a percent rank is formulated for benchmarking.
2 Hypothesis formulation
Hofstede’s national culture model covers five dimensions (Hofstede, 1991; van den Bosch and van Prooijen, 1992). Their basic definitions and relationship with innovation capability are discussed below.
Power distance index (PDI) focuses on the degree of equality, or inequality, between people in the country’s society. A high power distance ranking indicates that inequalities of power and wealth have been allowed to grow within the society. These societies are more likely to follow a caste system that does not allow significant upward mobility of its citizens. A low power distance ranking indicates the society de-emphasising the differences between citizen’s power and wealth. In these societies, equality and opportunity for everyone is stressed. PDI represents five beliefs that discourage innovation. They are hierarchy, vertical communication, centralisation of power, tight control over employees and resistance to changes in power distribution. Therefore, the first hypothesis is formulated as following:
Hypothesis 1 Societies with longer power distance will be less innovative than societies with shorter power distance.
Individualism (IDV) focuses on the degree the society reinforces individual or collective achievement and interpersonal relationships. A high IDV ranking indicates that individuality and individual rights are paramount within the society. Individuals in these societies may tend to form a larger number of looser relationships. A low IDV ranking typifies societies of a more collectivist nature with close ties between individuals. These cultures reinforce extended families and collectives where everyone takes responsibility for fellow members of their group. Three beliefs in this index encourage innovation (Shane, 1993). These are freedom, an outward orientation and contact with senior managers. These beliefs lead to the second hypothesis:
Hypothesis 2 Individualistic societies will be more innovative than collectivistic ones.
A meta-analysis on the influence of national culture on innovation capability 355
Masculinity (MAS) focuses on the degree the society reinforces or does not reinforce, the traditional masculine work role model of male achievement, control and power. A high MAS ranking indicates that the country experiences a high degree of gender differentiation. In these cultures, males dominate a significant portion of the society and power structure, with females being controlled by male domination. A low MAS ranking indicates that the country has a low level of differentiation and discrimination between genders. In these cultures, females are treated equally to males in all aspects of the society. This index is related to innovative organisations in terms of rewards and recognition for performance and motivation and achievement, training and skills development (Shane, 1993). These characters leader to the third hypothesis:
Hypothesis 3 The societies with higher MAS score will be more innovative.
Uncertainty avoidance index (UAI) focuses on the level of tolerance for uncertainty and ambiguity within the society – i.e., unstructured situations. A high uncertainty avoidance ranking indicates that the country has a low tolerance for uncertainty and ambiguity. This creates a rule-oriented society that institutes laws, rules, regulations and controls in order to reduce the amount of uncertainty. A low uncertainty avoidance ranking indicates the country has less concern about ambiguity and uncertainty and has more tolerance for a variety of opinions. This is reflected in a society that is less rule-oriented, more readily accepts change and takes more and greater risks. Organisations in countries with a high UAI generally show characteristics such as resistance to innovations, highly formalised management and the constraining of innovations by rules (Hofstede, 2001). In high UAI cultures, risk-averse attitudes imply that companies will not take unnecessary risks and only adopt innovations if their value has already been proven in the market. These arguments lead to the fourth hypothesis:
Hypothesis 4 Societies with higher UAI score will be less innovative.
Long-term orientation (LTO) was developed later. Data are very limited. So it is ignored in this research. Previous research did not find any empirical relationship between this index and innovation.
3 Methodology and empirical data
For a long time, the results of previous research were integrated only into what we call narrative review; that is, the reviewer reads and thinks about a collection of relevant studies and then writes some narrative account of whether the hypothesis under consideration seems to be supported by the evidence. Due to traditional research results accumulation, it becomes increasingly difficult to understand what they tell us. It may not be systematically to accumulate the results of research, so it becomes increasingly difficult to find the knowledge in this flood of information. Until the mid ‘70s, Glass et al. (1981) proposed a method to integrate and summarise the findings from body of research. The method was called meta-analysis. Glass introduced the term ‘meta-analysis’ to stand for statistical combination of results of independent studies or is the statistical analysis of a collection of individual studies. Therefore, more and more in recent years, the results of previous research are being integrated into what we call meta-analysis or statistical integration of the results of independent studies.
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Meta-analysis is ‘the analysis of analyses’. It refers to the analysis of the results of several independent studies. That is, the units of analysis are the results of independent studies rather than the responses of individual subjects. It is the rubric used to describe quantitative methods for combining evidence across studies. Because meta-analysis usually relies on data in the form of summary statistics derived from the primary analyses of studies, it is truly an analysis of the results of statistical analyses. Besides, the application of statistical procedures of meta-analysis examines tests of a common hypothesis from more than one study.
This study is a meta-analysis. It is based on two previous studies that have been published. They are the research on national culture by Hofstede (1991, 2001) and the study on national innovation capability by Porter and Stern (2001). The data are all available from publications and website. The data about national culture is also available on the internet. The data on national innovation for 2002 is from the annual report of world economic forum chaired by Porter and is available on the website. The variable is shortened as IN02. It covers number of US patent per million population, rate of higher education and survey of technological innovation in companies.
4 Results
Data analysis is based on correlation and structural equation modelling (SEM). First, simple correlation is calculated as shown in Table 1. According to Table 1, IDV and power distance are significantly correlated with innovation capability. The multiple correlations also supports that IDV and power distance are significantly correlated with innovation index, as shown in Table 2. UAI is not significantly correlated with innovation. Table 1 Simple correlation
INO2 PDI IDV MAS
PDI –.603** IDV .604** –.686** MAS –.083 .102 .077 UAI –.175 .186 –.248* .020
Notes: **Correlation is significant at the 0.01 level. *Correlation is significant at the 0.05 level.
Table 2 Multiple correlation among national culture and innovation capability
Unstandardised coefficients Standardised coefficients
B Std. error Beta t Sig.
(Constant) 3.810 .832 4.576 .000 PDI –1.745E-02 .008 –.333 –2.155 .037 IDV 1.778E-02 .007 .382 2.436 .019 MAS –5.826E-03 .007 –.090 –.790 .434 UAI –1.184E-03 .006 –.024 –.212 .833
Notes: F = 9; p < 0.001; n = 45
A meta-analysis on the influence of national culture on innovation capability 357
Although UAI is not directly correlated with innovation capacity, it is correlated with IDV. This is explainable since if people have pressure and feel uncertain, they will depend more on other people to release the pressure and concern and as a result, have to be more collectivism. Additionally, power distance is also negatively correlated with IDV. Based on this result, it is proposed that there may be a network relationship among the national culture dimensions and the innovation capability. A model is proposed as shown in Figure 1. Fitness results show that the model fit very well with chi-square/df = 1.338, CFI = 0.98.8 and RMSEA = 0.062. So, it can be concluded that Hypotheses 1 and 2 are accepted. Hypothesis 3 is rejected. Hypothesis 4 is accepted as well. Figure 1 The relationship among national culture and innovation capability
According to the multiple correlation and SEM testing, it can be concluded that three dimensions of the national culture influence national innovation capability. The three do not influence innovation alone, but also interrelated among themselves. So, a comprehensive ICI is proposed. It is formulated by factor analysis of the three dimensions. The three dimensions turn out to be one coherent factor. The testing result is shown in Table 3. Table 3 Innovative culture index
Component
IDV –.864 PDI .838 UAI .465 Initial eigenvalues 1.73 % of variance 60
Based on the ICI, the participating countries/regions are ranked as shown in Table 4. Cluster analysis based on ICI identified three groups. Group 1 has less innovative
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national culture (INC). Group 3 has more innovative culture. Group 2 is in the middle. The ICI, as well as the three corresponding dimensions, have also been transformed into percent rank. The ranking provides a practical benchmarking for any society to compare it with other. For example, Hong Kong falls into Group 2. It is in the top 51% by ICI, namely in the middle. Coming into the individual dimensions, Hong Kong’s IDV and power distance are in top 30% and 29%. However, its UAI is in top 95% (or bottom 5%), which means its population are experiencing high pressure and high uncertainty. The member of this society would like to follow rules and are unwilling to make changes. Therefore, the implication for Hong Kong companies is to provide a more stable and less pressure job environment. The government and companies should also think about how to motivate and encourage its citizens to be braver and to embrace new things. Its company culture and education system should all aim to encourage people to accept changes. Table 4 The percent ranks of INC index
Country ICI Clusters PDI IDV UAI
Arab World 0.71 2 0.13 0.47 0.51 Argentina 0.40 2 0.65 0.54 0.26 Australia 0.05 3 0.75 0.98 0.70 Austria 0.18 3 0.99 0.63 0.48 Belgium 0.36 2 0.36 0.85 0.10 Brazil 0.58 2 0.24 0.47 0.40 Canada 0.13 3 0.72 0.90 0.79 Chile 0.75 1 0.45 0.29 0.26 China 0.65 2 0.13 0.21 0.91 Colombia 0.87 1 0.31 0.07 0.37 Costa Rica 0.55 2 0.83 0.12 0.26 Czech 0.35 3 0.83 0.65 0.44 Denmark 0.00 3 0.95 0.83 0.97 E. Africa 0.56 2 0.42 0.34 0.68 Ecuador 0.95 1 0.17 0.01 0.53 El Salvador 0.91 1 0.34 0.20 0.10 Finland 0.24 3 0.86 0.69 0.60 France 0.38 2 0.29 0.80 0.26 Germany 0.25 3 0.83 0.72 0.55 Greece 0.73 1 0.50 0.41 0.00 Guatemala 1.00 1 0.04 0.00 0.04 HK 0.51 2 0.29 0.30 0.95 Hungary 0.27 3 0.67 0.90 0.33 India 0.45 2 0.20 0.58 0.84 Indonesia 0.82 1 0.17 0.09 0.79 Iran 0.42 2 0.54 0.52 0.60 Ireland 0.11 3 0.92 0.78 0.90 Israel 0.22 3 0.97 0.61 0.35
A meta-analysis on the influence of national culture on innovation capability 359
Table 4 The percent ranks of INC index (continued)
Country ICI Clusters PDI IDV UAI
Italy 0.33 3 0.61 0.87 0.42 Jamaica 0.31 3 0.68 0.50 0.99 Japan 0.47 2 0.59 0.54 0.13 Malaysia 0.93 1 0.00 0.32 0.86 Mexico 0.89 1 0.09 0.38 0.33 Netherlands 0.15 3 0.74 0.90 0.66 New Z 0.04 3 0.93 0.89 0.75 Norway 0.16 3 0.90 0.76 0.71 Pakistan 0.64 2 0.58 0.09 0.48 Panama 0.98 1 0.04 0.03 0.26 Peru 0.85 1 0.42 0.14 0.15 Philippines 0.80 1 0.06 0.40 0.82 Poland 0.49 2 0.29 0.67 0.11 Portugal 0.84 1 0.45 0.34 0.02 S. Africa 0.29 3 0.65 0.70 0.75 S. Korea 0.76 1 0.50 0.18 0.30 Singapore 0.53 2 0.22 0.21 1.00 Spain 0.44 2 0.56 0.60 0.26 Sweden 0.09 3 0.90 0.80 0.95 Switzerland 0.20 3 0.84 0.74 0.62 Taiwan 0.62 2 0.54 0.16 0.50 Thailand 0.67 2 0.42 0.21 0.57 Turkey 0.60 2 0.34 0.45 0.30 UK 0.02 3 0.83 0.96 0.90 Uruguay 0.69 2 0.47 0.43 0.06 USA 0.07 3 0.70 1.00 0.80 Venezuela 0.96 1 0.09 0.05 0.40 W. Africa 0.78 1 0.20 0.21 0.64
5 Discussions and conclusions
This research investigates the influence of national culture on national innovation capability. It is based on previous researches on national culture and national innovation capability. The research reveals that national culture does influence the national innovation capability. The influencing cultural elements include powder distance (negative influence), IDV (positive influence) and uncertainty avoidance (indirectly negative influence). The three elements are integrated together to formulate an ICI. The ICI can be used to benchmark a national culture in terms of supporting innovation.
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National culture will definitely influence the individual personality of a population. Therefore, the ranking of national cultures in terms of innovativeness will bear implications for international companies to locate their R&D countries. If a county has a more innovative culture, it is more likely to be invested as R&D centres. Future research should be conducted to see how the national culture influences the creative personality.
National culture will also influence the corporate culture. Future research should also be conducted to investigate how the national culture influences the corporate culture, especially the multinational corporate culture.
Hofstede’s model is not the only one on national culture. There are other models such as the one by Hall (1976) model on culture context and chronicity. Future research should also include other national culture dimensions into consideration. Finally, national culture should not be treated as the only factor that explains the differences in national innovation capability. Other factors such as the level of economic development, social systems, political systems and education systems also have influence on national innovation capability. All these need future research in the future, especially via more macro meta-analyses.
Acknowledgements
The research reported in this paper is fully supported by a Strategic Research Grand (SRG 70001715) from the City University of Hong Kong, Hong Kong, P.R. China.
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