The role of culture and cultural instability in innovation at the national level : insight and implications for innovation management

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The Role of Culture and Cultural Instability in Innovation at the National Level Insight and Implications for Innovation Management

By Danny Groskamp

Master Thesis Business Administration Entrepreneurship & Innovation Track University of Amsterdam

Student number: 10002925

Supervisor: Dr. W. (Wietze) van der Aa Second reader: Mr B. (Balazs) Szatmari MSc Date: 23-6-2017

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Statement of Originality

This document is written by Student Danny Groskamp, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

This study examines the relationship between culture and innovation on a national level. We study whether particular dimensions relate to levels of innovation, by comparing cultural dimension scores of Hofstede’s cultural model to innovation scores determined by the Global Innovation Index. Furthermore, we examine whether cultures are changing within countries over time, and whether these changes in culture also relate to changes in levels of innovation, by comparing data from the World Values Survey with IP statistics. Findings indicate that individualism, long-term orientation and indulgence relate positively to innovation, that power distance and uncertainty avoidance relate negatively to innovation, and that masculinity does not relate to innovation. Additionally, we found that cultures are indeed changing over time, and that change on some of the cultural dimensions relate to changes in innovation, although these results are limited. These findings highlight the idea that national cultures are an important determinant of innovative success, and provide insight into the stimulation of innovation in organizations to increase their performance.

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Introduction

The topic of innovation is becoming more and more recognized in modern business, as company environments are considered to be changing increasingly faster due to globalization, advances in information technology and managerial innovation (Cummings, & Worley, 2005). Adapting innovatively to contemporary business environments is considered imperative to organizational success by science (Tushman, 1997; Nonaka, 1991; Henderson, & Clark, 1990; Schumpeter, 1934) as well as practice (Pohle, & Chapman, 2006). As such, examining how innovation can be enhanced in organizations in order to increase performance is very relevant for management practice. One factor that has been shown to exert considerable influence on innovation is national culture (Shane, 1993; Nakata, & Sivakumar, 1996; Steensma, Marino, Weaver, & Dickson, 2000).

National culture is becoming more and more relevant to management practice as increasing globalization is opening up international business opportunities. Multinational corporations, for instance, have the freedom to locate business units almost anywhere in the world. Deploying certain business activity that benefits from innovation supporting environments, like an R&D department, in countries that are able to provide such environments could prove beneficial to companies’ innovative endeavours (Jones, & Davis, 2000), enabling them to gain a competitive advantage (Barney, 1986) and generate higher profits (Gunday, Ulusoy, Kilic, & Alpkan, 2011).

Another business opportunity created by globalization is the possibility to hire the best personnel for any position without being limited by geographical boundaries. It is becoming increasingly easier for foreign professionals to migrate to countries where there is a high demand for their labour, for companies to recruit foreign personnel and facilitate their migration to the host country, and for cross-national teams to be formed that operate through telecommunication methods, enabling members to collaborate without being present in the same physical location. As such, national cultural traits can be imported/acquired and used as a resource for firms to increase their levels of innovation. Firms may be able to increase their level of innovation, for instance, through the recruitment of personnel from individualist countries, as these countries have been found to have higher levels of innovation (Rinne, Steel, & Fairweather, 2012). Additionally, employing foreign personnel increases cultural diversity within the firm, leading to creativity gains (Stahl, Maznevski, Voigt, & Jonsen, 2010), an essential factor in the process of innovation. However, although these studies indicate a prominent role of national culture in determining innovation, research on this topic has been quite limited. Some prior research on the link between national culture and innovation has been conducted (Shane, 1993; Rinne et al., 2012; Kaasa, 2013), showing that values focussing on individual performance, small differences in power between leaders and followers, and a future orientation relate to higher

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levels of innovation. However, to the best of our knowledge, not all aspects of culture have yet been examined regarding innovation. Additionally, research indicates that national culture is changing over time (Beugelsdijk, Maseland, & Hoorn, 2015; Inglehart, & Baker, 2000), but the effect of cultural change on innovation has not been tested yet. Therefore, the current study will examine the

relationship between national culture and innovation more in-depth, addressing these research gaps. We do so by asking how national cultural traits relate to innovation, how national cultures change over time, and whether national cultural change within countries relates to different levels of innovation. In the first section of this introduction, we will elaborate on the construct of national culture, after which we will shorty discuss the concept of innovation. Then, we will explain the link between the two constructs.

National Culture

The concept of culture defines itself as a set of shared values, beliefs and expected behaviours among groups (Hayton, George, & Zahra, 2002). The concept of national culture, as such, is described as a set of shared values, beliefs and expected behaviours that are generally accepted by citizens of a certain nation. Countries often differ in regard to their cultural characteristics. For instance, citizens from the western world, like Americans, generally value the concept of choosing one’s own spouse, believing that love is a necessary condition for marriage, and will act accordingly by dating different people and selecting a spouse on their own (Levine, Sato, Hashimoto, & Verma, 1995). However, in other parts of the world, like India, people generally value the concept of arranged marriage, believing that parents are the best possible people to select a spouse, and will act accordingly by taking a step back and having the parents take care of the spouse selection process. Such differences in culture seem to influence a range of different outcomes on the individual, organizational and national level (Kirkman, Lowe, & Gibson, 2006; Chow, Shields, & Chan, 1991). Schuler and Rogovsky (1998), for instance, show that companies in individualist countries tend to use revenue-models based on pay-for-performance and maintain a focus on individual pay-for-performance, while Moorman and Blakely (1995) found that people in collectivist countries are more likely to exhibit organizational citizenship behaviour, putting in extra effort in addition to their formal tasks. To be able to study such effects of national culture, it is imperative that a valid cultural model is used, to enable the classification and categorization of national cultures across the globe.

There have been many attempts at unravelling the different dimensions of national culture (Fink, Neyer, & Kölling, 2006). Kluckhohn and Strodtbeck (1961) were the first to take on this challenge, and came up with five factors: human nature orientation, man-nature orientation, time orientation, activity orientation and relational orientation. With their research, they set the standard for all future

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followed, for example, by Trompenaars (1993), who identified seven factors, among which individualism and universalism. Schwartz (1992), in contrast, came up with as many as eleven different factors, ranging from self-direction to spirituality. The cultural model that has been used most extensively in the literature, however, is the model of Hofstede (Bond, 2002).

Hofstede (1980) conducted a remarkable study, in which he collected over 100,000 surveys filled in by IBM personnel in 50 countries. He asked participants to answer questions about personal value orientations, and reduced these orientations with factor analysis to four dimensions: individualism versus collectivism, low versus high power distance, masculinity versus femininity, and low versus high uncertainty avoidance. Ten years later he added another factor based on additional research, which was called Confucian dynamism, or long-term orientation (Hofstede, 1991), and only recently a sixth dimension was added, called indulgence (Hofstede, Hofstede, & Minkov, 2010). The six factors of Hofstede’s model of cultural dimensions are described as follows (Hofstede, 2011):

1. Individualism / collectivism: collectivism is the extent to which people are highly integrated into strong, cohesive in-groups, whereas individualistic cultures have loose ties between individuals, expecting one to take care of themselves rather than relying on external support. Citizens of collectivist cultures provide protection of in-group members in return for unquestionable loyalty. These cultures can be characterized by classifying people by group and a stress on belonging, as opposed to a classification of people as individuals and the right to privacy in individualistic cultures.

2. Low / high power distance: power distance is the extent to which members of less influential organizations / institutions accept and expect an unequal distribution of power, leading to inequality. This inequality is endorsed by society leaders (high power) as well as followers (low power). A low power distance society can be characterized by a relatively even income

distribution and followers that expect to be consulted, as opposed to a relatively uneven income distribution and followers expecting to be told what to do in high power distance societies. 3. Masculinity / femininity: refers to the value distribution between genders. Masculine societies are

generally assertive and competitive, whereas feminine societies are more modest and caring. Masculine cultures can be characterized by an admiration of strong people and high emotional and social role differentiation between genders, whereas feminine cultures can be characterized by a sympathy for the weak and minimal emotional and social role differentiation between genders.

4. Low / high uncertainty avoidance: represents a society’s (in-)tolerance for ambiguity, or extend to feel (un-)comfortable in unstructured situations. Societies high in uncertainty avoidance focus on minimizing the emergence of such ambiguous situations, by applying strict behavioural codes, rules and laws. Citizens of high uncertainty avoidance societies generally disapprove of deviant opinions and belief in an absolute truth. These societies can be characterized by an emotional

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need of rules and lower scores on subjective well-being, as opposed to a disliking of rules and higher scores on subjective well-being in low uncertainty avoidance societies.

5. Long / short-term orientation: refers to the Chinese concept of Confucian dynamism. Cultures with a long-term orientation tend to value perseverance and a sense of shame, while short term oriented cultures tend to value social obligations and respect for tradition. Long term oriented cultures can be characterized by, for instance, openness to learn from other countries and the attribution of success and failure to effort, whereas short term oriented cultures are generally associated to feelings of pride towards one’s own nation and an attribution of success and failure to luck.

6. Indulgence / restraint: refers to the extend societies allow free gratification of human desires related to the enjoyment of life. Indulgent societies are relatively high in the allowing of human desire gratification, while restraint societies are more prone to controlling these gratifications, regulating them with strict social norms. Indulgent societies can be characterized by a perception of personal control over life and a high rate of sports activity, whereas restraint societies generally have a perception of helplessness and a low sports activity rate.

Although the Hofstede model has been used extensively in the literature, it has not come without critique.

Critique on Hofstede’s model

Jones (2007) has reviewed the literature in this regard and found eight arguments against Hofstede’s model. First of all, scholars like Schwartz (1999) argue that surveys are not an appropriate measuring instrument when assessing values that are sensitive and subjective. Participants might provide socially desirable responses instead of answering truthfully. Second, it is argued that Hofstede assumes homogeneity of national cultures, whereas national cultures actually consist of different groups of ethnic units (Nasif, Al-Daeaj, Ebrahimi, & Thibodeaux, 1991). Ignoring national variation in cultural values would therefore not be appropriate. However, when comparing nations, we would say it is inevitable that these variations are aggregated, as this is level of analysis we want to compare. Even when looking into the ethnic subgroups of a nation, there will be a division into other subgroups that value things differently, in which there will be smaller groups that also deviate from the norm. For this reason, a line must be drawn at the national level. The point here is to get an average score for the level of analysis. Adding to the second argument, the third argument states that nations are not the correct unit of analysis when measuring culture, as culture is not bounded by borders (McSweeney, 2002). However, Hofstede (1998) argues that these are the only means we currently have in

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The fourth argument mentions political influences as a confounding factor in analysing cultures. During the time of measurement by Hofstede, political instabilities like the cold war caused data from socialist and third world countries to be missing. However, missing data is a sophist argument, as not measuring certain cases does not implicate an inappropriate method of measurement. The fifth reason states that the one company approach by Hofstede cannot possibly provide sufficient information on national cultures (Søndergaard, 1994). However, Hofstede (1998) argues that he was not trying to make absolute measures, but only tried to gauge differences between cultures. In this reasoning, it would even be more appropriate use a one company approach, as survey responses would not be confounded by variation in factors like corporate policy and management practices.

Furthermore, the sixth argument is challenging Hofstede’s outdated measures, as these may not be as representative anymore in current rapidly changing global environments. Hofstede (1998) counters this by arguing that national cultures are very stable and will not change that quickly. Scholars do not quite agree on this point however, as we will discuss more in depth in a later section of this paper. Argument seven argues that Hofstede considers cultures to consist of too few dimensions. Hofstede (1998) agrees with this point, and is continuing his research into further division of the concept of national culture. In fact, after publication of Jones’ article (2007), Hofstede (2010) added the sixth dimension of indulgence to his cultural model. Lastly, the eighth argument states that some statistical integrity issues were found (Dorfman, & Howell, 1988). Some country scores were based on too few cases to be valid measures.

Although critics do seem to have some valid arguments against the model of Hofstede, it is still the most researched, most cited, well replicated model of the multi-dimensional construct of national culture, which has been constructed by a combination of rigorous design, systematic data collection and coherent theory (Jones, 2007). Although the model might not be perfect, it is still the best means of assessing the culture of nations, and as such will be used in the current study. To gain a better understanding of what this division in cultural dimensions adds to organizational literature, we will discuss the effects of Hofstede’s dimensions on organizational outcomes in the next section of this paper.

National culture and organizational outcomes

In regard to individualism / collectivism, Wagner (1995) showed that individualist people are less likely to engage in cooperative behaviour, due to their personal independent nature. As individualist people generally value self-reliance, they are more likely to engage in tasks by themselves instead of tackling them as a group. Collectivist people, in contrast, are more open for collaboration as they feel more interdependent and reliant on groups. This finding is highlighted by Moorman et al. (1995), who

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found that people of a collectivist nature are more likely to engage in organizational citizenship behaviour, putting in extra work in addition to their formal task-description. This is typical for collectivist people, as they are more focused on attaining group-goals (as opposed to personal needs), and will exert extra effort in obtaining these. Individualist people, in contrast, are generally less concerned with group-goals, and will allow themselves to put in less effort engaging in organizational citizenship behaviour, prioritizing their own personal needs.

Based on the findings of these studies, one might argue that companies are better off hiring personnel of a collectivistic nature, as cooperative and organizational citizenship behaviour are generally perceived as positive for organizations. However, a collectivist nature does not always yield positive results. Goncalo and Staw (2006), for instance, found that individualist people are generally more creative than collectivist people. When asked to come up with creative solutions for a certain task, individualist people showed to be superior in both generating creative ideas as well as selecting creative ideas. One reasonable explanation for this effect is that individualist people are less likely to inhibit themselves in fear of not conforming to the group, and as such are able to come up with and select more creative solutions. Based on these findings, we cannot conclude that a collectivist culture is better for organizations than an individualist culture, or vice versa, as both ends of the dimension show both positive as well as negative effects on different organizational outcomes.

Additionally, previous research shows that other dimensions of culture also exert an effect on organizations. Brockner, Ackerman, Greenberg, Gelfan, Francesco, Chen et al. (2001), for instance, show that people react more negatively to low voicing employees in countries that are low in power distance, compared to countries that are high in power distance. This is explained by high power distance cultures legitimizing an unequal distribution in decision making power, thereby expecting that low power followers will not show voicing behaviour as they do not have the power to make any decisions. This can have a negative effect on the organization as the voicing employees may have great ideas for the company, which will never be communicated, let alone be implemented, because the national culture is highly power distant.

In regard to uncertainty avoidance, some research on organizational outcomes has also been

conducted. Hwang (2005) has shown that uncertainty avoidance aids in the adoption of new enterprise resource planning (ERP) systems by increasing its ease of use in employees. The author argues that ERP systems can be used as a tool to reduce uncertainty with structured business process and operations, and as such would be more readily adopted in cultures high in uncertainty avoidance. Furthermore, Shenkar and Zeira (1992) showed that uncertainty avoidance plays a role in mitigating

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decision making. As such, CEO’s of joint ventures will have a clearer view of their role and are able to execute their function more effectively.

Although the findings in these studies show interesting effects of national culture on organizational outcomes, Newman and Nollen (1996) argue that for firms to maximize performance, their

management practices must fit well with the national culture of its host country no matter how they score on each dimension. Management practices that are inconsistent with the deeply help values of the national culture, cause employees to feel dissatisfied, uncomfortable and uncommitted. As such, they may be less able and willing to perform, causing firm performance to decline. This indicates that managers should closely examine whether their management practices are in line with the national culture of their host country, as well-being of their employees and the performance of their firm depends on it.

Another interesting claim that Newman et al. (1996) make is that national culture is impervious to change. Whether this is true would be very important for management practices, as management might need to take adaptive measures to keep its fit with national culture, and might need to monitor cultural change in other countries, in order to import the right cultural traits and make sure these traits have not adapted. As such, it is important to assess whether cultures indeed do change, or whether they might be more flexible than Newman et al. suggest.

The stability of national culture

Although Newman et al. (1996) suggest that national culture is impervious to change, they do not provide any reference or explanation supporting this claim. This merely implies that the stability of national culture is a deeply seated assumption, not to be questioned quickly. Indeed, Hofstede (2001) argues that national cultures are extremely stable over time, only significantly changing over the course of generations due to a self-reinforcing system. He proposes that the structure and functioning of a society’s institutions reinforce the cultural patterns of society, which are themselves a product of these cultural patterns (Kwok, & Tadesse, 2006). Additionally, Thurow (1999) argues that national cultures are inherently stable due to the significant presence of forces resisting change. However, recently scholars have been questioning the assumption that national cultures are inherently stable. Inglehart et al. (2000), for instance, argue that economic development brings about social change, in accordance with modernization theory. They claim that “industrialization produces pervasive social and cultural consequences, from rising educational levels to changing gender roles” (p. 20) and found evidence for massive cultural change. In this study, authors used data from the World Values Survey, and examined whether national cultures are changing in regard to two dimensions: traditional

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versus secular-rational and survival versus self-expression. They found that many countries showed substantial changes in cultural values. Both West and East Germany, for instance, show their values changing from traditional to secular-rational, with West Germany additionally showing a change of values from survival to self-expression. Other countries, like Belarus and Russia, show a different pattern, with values changing towards values concerning tradition and survival. This evidence shows that cultures are not only changing in absolute terms, but also relatively to each other.

Additionally, evidence for modernization theory comes from Zhang and Shavitt (2003), who show that values of Modernity and Individualism are becoming more and more pronounced in Chinese culture, which has traditionally always been a collectivist society. Furthermore, Taras, Steel, & Kirkman (2006) have shown that Hofstede’s dimensions of cultural values are indeed changing over time, by conducting a meta-analysis of over 500 studies that used Hofstede’s model in different countries, in different time-periods. However, the strength and direction of cultural change differs from country to country. Their results show that the biggest changes in culture have been noted in countries that have changed their political and economic system. In accordance with modernization theory, these cultures are generally changing towards typical western values like a decrease in power distance and uncertainty avoidance, and an increase in individualism. Western countries, in contrast, show relatively stable scores in regard to the cultural dimensions, or even slightly change towards non-western values like collectivism and high power distance. Former Soviet countries, however, show a major shift towards individualism, while the United States are slowly shifting towards collectivism.

Additionally, Beugelsdijk et al. (2015) provide evidence for cultural change by extracting the dimensions of Hofstede from the World Values Survey (WVS). The WVS is a survey containing a wide range of items about values, that has been conducted throughout the world from 1981 to 2014 by a global network of social scientists, and contains over 300,000 documented cases. Beugelsdijk et al. used the database of the WVS to extract the dimensions of Hofstede through WVS-items, and examined whether countries differed in score over time. They too found that cultural dimensions are changing over time, although their results indicate that national cultures change in an absolute rather than a relative manner. Nations are generally shifting more towards individualist and indulgent values, and are decreasing in power distance, but the relative difference on cultural dimensions between countries are found to be remarkably stable, in contrast to the findings of Inglehart et al. (2000) and Taras et al. (2006).

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The notion that cultures are changing over time is important for managers around the world, as they might have to adjust their practice to accommodate these changes. Maintaining a good cultural fit (Newman et al., 1996) between the management practices in an organization and the national culture of its host country is an important predictor of firm performance.

Innovation

Before examining the link between national culture and innovation, this section of the paper will elaborate on the construct of innovation. Innovation is a seemingly difficult construct to define, as many attempts have been made (Baregheh, Rowley, & Sambrook, 2009). Thompson (1965, p. 2), for instance, focusses its definition on the different types of innovation, stating that “Innovation is the generation, acceptance and implementation of new ideas, processes products or services”, whereas Kimberly (1981, p. 108) is more concerned with the multiple stages of innovation, stating “There are three stages of innovation: innovation as a process, innovation as a discrete item including, products, programs or services; and innovation as an attribute of organizations.” After conducting a careful review on the definitions of innovation, Baregheh et al. conclude that the construct of innovation should be primarily defined as (1) a multi-stage process, (2) transforming ideas into new/improved (3) products, services or processes.

According to Hansen and Birkinshaw (2007), innovation can be divided into three stages: the idea generation stage, the idea conversion phase and the idea diffusion stage. In the idea generation stage, innovative ideas are created in- or outside the company trough methods like brainstorming or tapping external partners. The second stage of the innovation process is the idea conversion stage, in which ideas are selected and developed. Thirdly, idea diffusion concern itself with spreading innovation throughout the organization.

Additionally, important findings regarding the innovation literature comes from Crossan and Apaydin (2010), who distinct between innovation input and innovation output. Innovation input refer to factors like R&D investment, and for instance the initiation of a brainstorm session to come up with

innovative ideas. However, exerting effort in providing innovative input does not necessarily mean that it results in innovative output, or tangible innovative products, services or processes. This all depends on how well the innovative process performs. In our study, we will be primarily concerned with innovation output, as we are most interested in the final results, rather than the effort that was put in. However, we will incorporate both dimensions to different extends.

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National Culture and Innovation

Shane (1993) was one of the first to conduct a study on the effect of national culture on innovation output at the national level. He compared Hofstede’s first four dimensions (1980) to trademark statistics. The results of Shane’s study indicate that national culture indeed affects innovative output. Low uncertainty avoidance appears to be the strongest indicator of high levels of innovation, relating to both trademark outputs in 1975 and 1980. The author argues that this is because innovation implies uncertainty. By definition, innovative ideas are novel and have not yet been tested. As such, the effects of implementing innovative ideas is always more uncertain than maintaining the status quo, how promising these innovative ideas may seem. Indeed, Mueller, Melwani and Goncalo (2012) argue that although people generally desire new innovative ideas, they implicitly reject them because of their uncertain effects. People from countries that are more accepting towards uncertainty, as such, would be more open to innovative ideas. Therefore, cultures that are low in uncertainty avoidance will show higher levels of innovation. Shane’s findings support prior research by Philips and Wright (1977), who found that Southeast Asians are more acceptant towards uncertainty than Britons, and as such show more appreciation towards new ideas. This appreciation of new ideas can be valuable for all stages in the innovation process. Novel ideas may be generated more easily as the tolerance for uncertainty makes these ideas come to mind more easily, and a favour of innovative ideas will improve their chance of being selected and adopted throughout the company.

Additionally, Shane (1993) found that high innovation levels could be predicted by high levels of individualism and low levels of power distance. As the author argues, individualism primarily aids innovation through granting managers the freedom to act on innovative opportunities, whereas managers in collectivist countries do not enjoy this level of freedom, and as such will limit the implementation of innovative ideas. Such limited freedom will also inhibit the generation of innovative ideas, as employees are discouraged to come up with innovative ideas as these will probably not be adopted anyway. Additionally, individualism relates to an outward orientation, causing employees to have more contact with outsiders, and as such generate more innovative ideas by combining multi-disciplinary knowledge in new ways. In regard to power distance, innovation is aided through a minimum of organizational hierarchy and free communication across the levels of hierarchy. As such, innovative ideas reach top levels more easily, and a decision to move an idea to the next stage is more likely to be made. Furthermore, low power distance relates to more trust in subordinates. When managers enjoy higher levels of trust in subordinates, they will more quickly be convinced of innovative ideas generated by these subordinates, and as such will be more likely to act upon them.

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Lastly, Shane (1993) predicted that masculinity would also be related to innovation through a greater emphasis on personal achievement and training, but did find not a significant relationship. This finding is explained by Menzel, Krauss, Ulijn and Weggeman, (2008), who argue that both sides of the masculinity spectrum can be associated with high levels of innovation. Masculine traits like purposefulness and clear goal setting are helpful in stimulating innovation by increasing the need for new innovative solutions towards achieving these goals. On the other hand, feminine traits like a playful atmosphere, a supportive environment and an emphasis on cooperation also aid innovation. Indeed, opposite findings are shown by Kaasa (2013), who shows high levels of innovation to be related to low levels of masculinity.

Menzel et al. (2008) also address the relationship between long-term orientation and innovation. Long-term orientation emphasises a dynamic, future oriented mind-set that is open to the exploration of new possibilities. In contrast, a short-term orientation emphasizes a focus on the past and present, maintaining the status quo by exploiting the well-known. As such, values of long-term orientation would be related to higher levels of innovation, whereas a short-term focus relates to lower levels of innovation. This is supported by Herbig and Dunphy (1998), who argue that innovation adoption depends on cultural values related to long-term orientation. They describe, for instance, the reaction of the Chinese when introduced to power machinery in the previous century. At the time, power machinery was a very innovative concept, and able to greatly improve the efficiency of tasks that were previously performed by manual labour. However, adopting such machinery meant a change of working routine and the re-evaluation of manual labour. Long-term oriented cultures would probably adopt such an innovation without much resistance, but as the Chinese maintained a short-term orientation at that time, they initially refused to adopt power machinery, even though this would have been very beneficial in optimizing business processes.

Other research regarding national culture and innovation adoption comes from Steenkamp, Hofstede and Wedel (1999), who studied the effect of national culture on consumer innovativeness, or their propensity to adopt new and different products. An increased demand of innovative products would require organizations to become more innovative and create such products. The authors found that high levels of individualism, high levels of masculinity and low levels of uncertainty avoidance related to high levels of consumer innovativeness. Consumer innovativeness involves the initiation of new behaviour independent of others (Midgley, & Dowling, 1978), explaining its relationship with individualism. Additionally, uncertainty avoidance relates to a resistance to change from usual patterns, reducing risk by choosing for the well-known. As innovation implies uncertainty, an acceptance of uncertainty would therefore allow consumers to choose for innovative products more easily.

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Furthermore, the relationship between masculinity and consumer innovativeness is explained through the purchase of new items as a way to assert one’s interest and show off wealth and success (Rogers, 1983), traits that are highly masculine. This is supported by Nakata and Sivakumar (1996), who argue that masculine traits are especially important in the adoption/implementation stage of innovation. Conversely, the authors state that femininity is more beneficial for the first stage of innovation, where new ideas are being generated. This supports the theory of Menzel et al. (2008), who state that both ends of the masculinity/femininity dimension aid innovation in different ways. Nakata et al. (1996) go further than that however, and argue that the effects of other cultural dimensions are also

dependent on the stage of the innovation process. They propose that the idea generation stage would benefit from individualism, low power distance, femininity, low uncertainty avoidance and a long-term orientation. Conversely, they argue that the implementation stage of innovation benefits from collectivism, high power distance, masculinity, high uncertainty avoidance and a short-term orientation. These propositions, however, have not been tested.

Additionally, Tugmaner (2014) conducted a study investigating the effects of the first five of Hofstede’s dimensions on national innovation output. As an indicator of innovation at the national level, scores from the Global Innovation Index were used. Analysis showed that low power distance, individualism and long-term orientation related positively to innovation output, as opposed to

masculinity and uncertainty avoidance, which showed no relationship. This is largely in support of the literature. A non-significant result for uncertainty avoidance, however, is surprising, as previous research consistently shows that the level of uncertainty avoidance is one of the most important predictors of innovation.

Lastly, Kaasa (2013) conducted a study on the relationship between Hofstede’s first four cultural dimensions and innovation input and output. The author found that all dimensions of culture were related to both innovation input and output. Individualism related positively with innovation input and output, although it relates stronger to innovation output. Additionally, power distance related

negatively with innovation input and output, although it related stronger to innovation input. Masculinity and uncertainty avoidance both related equally strong to both measures of innovation. The result of studies discussed in this section of the paper are summarized in table 1. Findings for individualism, power distance and uncertainty avoidance are very consistent. Masculinity, in contrast, shows very inconsistent results, whereas indulgence has not been researched at all. Additionally, findings for long-term orientation are consistent, but only rely on two prior studies.

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Table 1

Findings of prior research regarding the relationships between the cultural dimensions and innovation

Study IC PD MAS UA LTO ID

Shane (1996) + - 0 - n/a n/a

Menzel et al. (2008) + - 0 - + n/a

Steenkamp et al. (1999) + n/a + - n/a n/a

Rinne et al. (2012) + - n/a 0 n/a n/a

Kaasa (2013) + - - - n/a n/a

Tugmaner (2014) + - 0 0 + n/a

Note. IC = individualism; PD = power distance; MAS = Masculinity; UA = uncertainty avoidance; LTO = long-term orientation; IR = indulgence. + indicates a positive relationship with innovation; - indicates a negative relationship with innovation; 0 indicates no relationship with innovation.

These findings indicate that organizational levels of innovation might benefit from deploying innovative business activity, like developing new technology, in countries that are high in individualism, low in power distance, low in uncertainty avoidance and/or high in long-term orientation. Additionally, hiring personnel from such countries may also aid innovation, as people form these countries hold values that are positively associated with innovative behaviour.

Furthermore, managers might use these findings to copy cultural characteristics that are associated with innovation into their own organizational culture. Individualism, for instance, might be increased to aid levels of innovation by developing individual targets and personal goals for each employee within the organization. As such, employees might experience higher feelings of individualism, causing them to generate and communicate more innovative ideas to impress others. However, national cultural characteristics might prove to exert different effects within organizations than on nations as a whole, making it a complex endeavour to generate advice for individual organizations based on a national level study. Furthermore, tweaking with organizational cultural values to the point that they deviate too much from the national culture can have adverse effects on organizational performance (Newman et al., 1996).

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Current Study

Based on the literature discussed in the introduction, we conclude that the dimensions of national culture are able to predict levels of innovation. Specifically, individualism and long-term orientation relate positively to innovation, whereas power distance and uncertainty avoidance relate negatively to innovation. The relationship between the masculinity/femininity dimension is more complicated, as both ends of the dimension aid innovation in different ways, although the literature balances the scales towards high levels of masculinity being related to high levels of innovation.

Additionally, research on the sixth dimensions, indulgence/restraint, is limited because it has only been introduced recently. However, we expect indulgence to be positively related to innovation, as we think that the free gratification of human desires translates to higher levels of innovation through allowing oneself to engage in new, innovative behaviour as a way to enjoy life. Therefore, the current study will test the relationships between the different cultural dimensions, as done prior by Tugmaner (2014). Additionally, the dimension of indulgence will be added, and the latest Global Innovation Index data will be used. As such, main hypothesis 1 that will be tested is “National culture relates to innovation.”. This hypothesis consists of the following six sub-hypotheses:

H1a: “Individualism relates positively to innovation.” H1b: “Power distance relates negatively to innovation.” H1c: “Masculinity relates positively to innovation.”

H1d: “Uncertainty avoidance relates negatively to innovation.” H1e: “Long-term orientation relates positively to innovation.” H1f: “Indulgence relates positively to innovation.”

Furthermore, the literature in the introduction leads us to conclude that cultural dimensions are not inherently stable, but are able to change over time. This causes us to ask whether changes in culture are also able to change levels of innovation. For instance, do countries that are becoming more individualistic also become more innovative? Therefore, main hypothesis 2 that will be tested is: “Cultural change relates to innovation growth.”. This hypothesis consists of the following six sub-hypotheses:

H2a: “Cultural change towards individualism is positively related to innovation growth.” H2b: “Cultural change towards power distance is negatively related to innovation growth.” H2c: “Cultural change towards masculinity is positively related to innovation growth.”

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H2e: “Cultural change towards long-term orientation is positively related to innovation growth.”

H2f: “Cultural change towards indulgence is positively related to innovation growth.” The process model of the current study is schematically represented in figure 1.

Figure 1

Process model of the current study

National culture Innovation

Innovation growth Cultural change

H1 H2

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Method

Hypothesis 1: National Culture and Innovation

For the first hypothesis, the study of Tugmaner (2014) will be replicated with the latest data available. For the measure of cultural dimensions, the latest version of Hofstede’s cultural dimensions, which is publicly available on his personal website, will be used (Hofstede, 2015). This dataset consists of the original four cultural dimensions of Hofstede generated with the data of his global IBM study (Hofstede, 1980), and the more recently added dimensions of long-term orientation (Hofstede, 1991) and indulgence (Hofstede, 2010), which are based on data from the World Values Survey.

For the innovation output measure, the latest version of the Global Innovation Index (GII; 2016) will be used (WIPO, 2016a). The GII is a combined initiative of Cornell University, the European Institution of Business Administration (INSEAD) and the World Intellectual Property Organization (WIPO). Its aim is to capture the multidimensional construct of innovation (WIPO, 2017), and in doing so they generate innovation data on a national level, providing country scores for every

dimension of innovation. The framework (figure 2) of the GII splits the dimensions of innovation into inputs and outputs, similar to Crossan et al. (2010). The input dimension consists of five

sub-dimensions: (1) institutions, (2) human capital & research, (3) infrastructure, (4) market

sophistication, and (5) business sophistication. The output dimension consists of two sub-dimensions: (6) knowledge & technology output, and (7) creative output. These dimensions are shortly explained as follows:

1. Institutions enable innovation by attracting business activity and fostering growth. The GII determines scores for this dimension by assessing the political, regulatory and business environment.

2. Human capital & research refers to the ability of residents to engage in innovative behaviour, by assessing the level and standard of education and research activity. 3. The third pillar weighs the degree to which innovation is supported by infrastructure, by

assessing the ICT-technology used, general infrastructure metrics like kWh per capita, and the level of ecological sustainability.

4. Market sophistication refers to the extend markets are supporting innovation through availability of credit and capital, an assessment of the competitive environment and access to international markets.

5. The last input sub-dimension of business sophistication is concerned with the degree to which companies are conducive to innovative activity.

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I. Knowledge creation in the form of patent applications, utility model applications and the publishing of scientific and technical articles in peer-reviewed journals. II. Knowledge impact includes statistics on the impact of innovative activity like

entry of new firms and high-tech industrial output.

III. Knowledge diffusion refers to the extend innovation is distributed, by looking at royalty and license fees, high-tech exports, ICT exports and net outflow of foreign direct investment.

7. Lastly, creative output is a more modern approach to measuring innovation output. It also includes three sub-pillars:

I. Intangible assets in the form of trademark applications, industrial design

applications, use of ICT in business and organizational models, and areas that are linked to process innovation.

II. Creative goods and services are concerned with audio-visual exports, global entertainment and media output, printing and publishing output, and creative goods export.

III. Lastly, online creativity refers to the statistics on generic and country-code top level domains, edits to Wikipedia, and video uploads on YouTube.

In addition to generating scores for each sub-dimension per country, the GII determines an innovation input and an innovation output sub-score by taking the average of all sub-dimensions. Lastly, the average of the input and output sub-score is used as the final innovation score per country, which will be used as the dependent variable for the first hypothesis. In addition to the testing of the hypothesis, exploratory analysis will be conducted to check for relationships between the cultural dimensions and sub-scores of the GII. This analysis will include GII input and output scores, and the sub-scores for innovation output: knowledge & technology output and creative output. This paper focuses on innovative output rather than input, as we are most interested in results rather than effort. Figure 2

Schematic representation of the GII’s framework of innovation

Global Innovation Index (total score)

Innovation input sub-index Innovation output

sub-index Institutions Human capital & research Infrastructure Market sophistication Business sophistication Knowledge & technology output Creative output

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Hypothesis 2: National Cultural Change and Innovation Growth

For the second hypothesis, it is necessary to measure cultural change as the independent variable. Unfortunately, Hofstede (2001) has always argued that cultures are very slow to change, and as such has never considered measuring cultural dimensions changing over time. However, the World Values Survey (WVS; World Values Survey, 2015) obtained national cultural data continuously from 1981 up until 2014. Although the WVS does not include variables that explicitly state scores regarding Hofstede’s cultural dimensions, sub-sets of items can be extracted that represent the dimensions of Hofstede. Through this method, Hofstede himself extracted the latest two cultural dimensions of long-term orientation (Minkov, & Hofstede, 2012) and indulgence (Hofstede et al., 2010). The authors manually selected WVS-variables that could be related to a long-term orientation, like valuing service to others, economical thrift and determination. After identifying these variables, reliability- and factor analysis were used to weed out irrelevant items, and to construct a reliable scale for each dimension. Furthermore, Beugelsdijk et al. (2015) also attempted to do this for the first four

Hofstede-dimensions. This study will use a similar strategy in constructing scales for Hofstede’s cultural dimensions from WVS-items.

For the dependent variable, the Global Innovation Index is unfortunately less well suited than for the previous hypothesis, as this index has only been published since 2007. However, patent, trademark, and industrial design statistics, as used in Shane (1993), have been measured since 1980 by the World Intellectual Property Organization (WIPO, 2016b). These measures have also been used by the GII to determine innovative output in the form of knowledge & technology and creativity output. Therefore, we will use these factors to operationalize the dependent variable for hypothesis 2.

Since we are determining cultural change in testing hypothesis 2, we will exploratively examine in which direction cultures are changing, and specifically analyse which world regions are changing in which direction.

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Results

Hypothesis 1: National Culture and Innovation

First, dependent, independent, and exploratory variables were checked for outliers (+3SD). None were found. Analysing kurtosis and skewness statistics showed all variables to be normally distributed.

Correlation matrix

To enable easy comparison between variables, a correlation matrix was constructed.

Correlation analysis was conducted between the dependent, independent, and exploratory variables. The correlation matrix is presented in table 2.

Table 2

Correlations between cultural dimensions, and Global Innovation Index scores

Note. GII KTO = GII Knowledge & Technology Output; GII CO = GII Creative Output. * indicates a significant correlation at the .05 level; ** indicates a significant correlation at the .01 level. Factor 1 to 6 originate from a dataset published in 2015, whereas factor 7-11 originate from a dataset published in 2016.

The correlation matrix shows that some cultural dimensions correlate with one another. Individualism relates negatively with power distance, whereas indulgence relates negatively with both power distance and long-term orientation. This might indicate some overlap between the cultural dimensions. Factor 1 2 3 4 5 6 7 8 9 10 11 1. Individualism - -.60** .05 -.17 .08 .16 .69** .66** .69** .62** .70** 2. Power distance - .15 .23 .05 -.30* -.60** -.57** -.59** -.50** -.62** 3. Masculinity - .05 .03 .07 -.05 -.05 -.05 .02 -.12 4. Uncertainty avoidance - -.04 -.07 -.31* -.32** -.29* -.35** -.20 5. Long-term orientation - -.45** .39** .36** .40** .45** .32** 6. Indulgence - .23* .24* .21 .13 .26* 7. GII total - .97** .97** .92** .93** 8. GII input - .88** .83** .85** 9. GII output - .95** .96** 10. GII KTO - .81** 11. GII CO -

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Furthermore, the correlation matrix shows that individualism, long-term orientation and indulgence relate positively to GII total scores, whereas power distance and uncertainty avoidance relate negatively to GII total scores. These results are in line with our hypothesis. Masculinity, however, does not significantly correlate with GII total scores, which is in contrast with our hypothesis.

Hypothesis testing

Hypothesis 1 predicted that individualism, masculinity, long-term orientation and indulgence are positively related to the Global Innovation Index 2016 score, whereas power distance and uncertainty avoidance are negatively related to the Global Innovation Index 2016 score. Although the results in the correlational matrix already indicate that findings are largely in favour of our hypothesis (table 2), we also see some overlap between the different cultural dimensions. To test whether cultural

dimensions independently relate to total GII scores, a multiple regression analysis was conducted to predict total GII scores based on individualism, power distance, masculinity, uncertainty avoidance, long-term orientation and indulgence. Using the enter method, it was found that all cultural

dimensions combined explain a significant amount of variance in total GII scores (F(6, 53) = 22.80, p < .001, R2_{= .71, R}2

adjusted = .68). It was found that individualism, power distance, uncertainty avoidance, long-term orientation and indulgence significantly predict total GII scores (table 3). Table 3

Coefficients of multiple regression analysis: GII total scores predicted by cultural dimensions

Cultural dimension Standardized β t p

Individualism .36 3.45 .001 Power distance -.24 -2.20 .032 Masculinity -.06 -0.72 .474 Uncertainty avoidance -.20 -2.61 .012 Long-term orientation .50 5.69 < .001 Indulgence .29 3.18 .002

From these results, we conclude that individualism, long-term orientation and indulgence are significantly positively related to GII total scores (confirming H1a, H1e, and H1F), that power distance and uncertainty avoidance are significantly negatively related to GII total scores (confirming H1b, and H1d), and that masculinity is not significantly related to GII total scores (rejecting H1c).

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Exploratory analysis

In addition to the testing of hypothesis 1, we conducted exploratory analysis to check for relationships between cultural dimensions and sub-scores of the GII. Specifically, GII input and output sub-scores were included, as were the sub-scores for the GII output dimension, knowledge & technology output and creativity output. The correlation matrix in table 2 shows that all GII measures correlate highly. Countries that are high in innovation input, for instance, are also high in innovative output.

Furthermore, we see that individualism, power distance and long-term orientation significantly relate to all dimensions of innovation. Uncertainty avoidance, however, does not significantly relate to creative output. Additionally, indulgence does not relate significantly to innovation output, while relating significantly to innovation input. Indulgence does, however significantly relate to creative output, as opposed to knowledge and technology output.

Hypothesis 2: National Cultural Change and Innovation Growth Extraction of cultural dimensions from the WVS

Beugelsdijk et al. (2015) previously extracted the cultural dimensions of Hofstede from the WVS. However, these authors only used data from the first half of WVS cases, and were not able to extract a scale for masculinity. We are convinced that more reliable scales may be extracted from the WVS when using all data available. Additionally, this might lead to the extraction of the masculinity dimension.

To determine which WVS-variables represent a cultural dimension of Hofstede, the author manually selected variables from the WVS-database that correspond to one of Hofstede’s dimensions

(Appendix 1). Then, for each one of the first four dimensions, corresponding WVS-items were coded dichotomously as either in line with the dimension (1) or in contrast with the dimension (0). Then, for every item, the percentage of participants that responded in line with the dimension was determined for each country. Then, reliability analysis was conducted across the selected WVS-items for all dimensions. Items that conflicted with the others were discarded. For the remaining items, factor-analysis was performed to determine whether all items load onto the same factor. Again, conflicting items were discarded. The remaining WVS-items were then selected to represent Hofstede’s

dimensions in further analysis. Reliability for each scale is presented in table 4. These results indicate that the scales extracted from the WVS for individualism, masculinity and uncertainty avoidance are all high, and for power distance reliability is low.

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Table 4

Reliability (Cronbach’s α) of cultural dimension scales based on WVS-items

Dimension Number of WVS-items N Reliability

Individualism 5 94 α = .90

Power distance 4 82 α = .43

Masculinity 6 37 α = .88

Uncertainty avoidance 4 66 α = .80

To check whether the newly created scales indeed relate to Hofstede’s original scores, correlation analysis was conducted between the original Hofstede scores and the common factor scores of the newly created scales based on the WVS-items. Original Hofstede scores for individualism (r = .71, p < .001), power distance (r = .55, p < .001) and uncertainty avoidance (r = .73, p < .001) show to significantly relate positively to their WVS counterpart. The original Hofstede score for masculinity (r = .31, p = .155), however, shows no significant relation to its WVS-counterpart.

Determining cultural dimension scores over time

After selecting and analysing WVS-items corresponding to the cultural dimensions of Hofstede, we determined cultural dimension scores over time. For this, the first and the last three WVS waves were grouped together to represent either time-period 1 (1981-1998) or time-period 2 (1999-2014). Again, country scores for each WVS-item were determined similarly as above, but now separate per time-period. For each time-period, the average of WVS-items was used as the score for the cultural dimension. This means that, for every country with available data, a score of every one of Hofstede’s dimensions was determined per time-period. Then, for each dimension, the difference in each cultural dimension between time-period 1 and time-period 2 was calculated to determine cultural change (see Appendix 2 for cultural change scores per country). Upon examination of the cultural change

variables, we discovered an outlier (+3 SD) in the data. The power distance cultural change score for Pakistan was extreme (around -90%). Upon inspection, the score proved to depend on only one variable of the scale, as the others were missing values. Therefore, we excluded this value in further analysis.

To explore whether cultures are changing over time, a repeated measures ANOVA was conducted between time-period 1 and time-period 2 to analyse whether cultural dimensions, on average, are changing over time (table 5). Results indicate that, on average, cultures are significantly becoming

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significantly becoming more long term oriented, but do not seem to change significantly regarding uncertainty avoidance.

Table 5

Repeated measures ANOVA between time-period 1(T1) and 2(T2) for every cultural dimension

Dimension Mean T1 Mean T2 F p

Individualism 33.387 30.544 7.573 .009 Power distance 71.532 58.624 39.172 < .001 Masculinity 40.735 36.225 8.745 .005 Uncertainty avoidance 65.528 66.745 0.888 .351 Long-term orientation 35.743 49.123 199.817 < .001 Indulgence 73.250 63.668 39.036 < .001

Determining innovation scores

In order to compare changes in innovation over time between countries, we extracted patent,

trademark and industrial design registrations per country from 1981 until 2014 from the website of the WIPO (2016b). For all three operationalisations, data was again grouped in either time-period 1 (1981-1998) or period 2 (1999-2014). Based on the total registrations in period 1 and time-period 2, the growth of registrations between the two time-time-periods was determined for each country, and for each of the three types of registration. Then, we checked all types of registration for outliers (+3SD), as these could heavily influence the results of our analysis. We found some extreme values for all registration variables. Upon closer inspection, Albania showed an extreme design registration growth rate of 30333%, as only 6 registrations were granted in time-period one. For this reason, this value was excluded from further analysis. Other countries that showed extreme growth rates showed no such error in the form of very low values for time-period 1, so these values were not excluded in further analysis.

Furthermore, upon examining the distribution of the dependent variables, kurtosis and skewness statistics showed all variables to be non-normally distributed. Transforming the variables as ln(x), however, resulted in a normal distribution. As such, we used this transformed variable in further analysis. Then, we checked whether the dependent variables correlated with one another. All variables significantly positively correlated with one another (see correlation matrix in table x). Then, factor analysis was used (eigenwaarde > 1) to examine whether the dependent variables all load one factor.

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This was indeed the case. Additionally, a common factor score was determined which was used as the dependent variable in the testing of hypothesis 2.

Correlation matrix

To enable easy comparison between variables, a correlation matrix was constructed.

Correlation analysis was conducted between the independent and dependent variables. The correlation matrix is presented in table 6.

Table 6

Correlations between cultural change dimensions, patent registration growth, trademark registration growth, industrial design registration growth, and the common dependent factor

Note. * indicates a significant correlation at the .05 level; ** indicates a significant correlation at the .01 level.

Interestingly, cultural change on some dimensions correlate with all types of registration growth. Change towards power distance and change towards masculinity significantly negatively relate to all types of registration growth, whereas change towards indulgence relates positively with all types of innovation growth. Change towards individualism, change towards uncertainty avoidance and change towards long-term orientation do not significantly relate to any type of innovation growth.

Additionally, we see that change towards indulgence correlates negatively with change towards power

Factor 1 2 3 4 5 6 7 8 9 10

1. Individualism change - -.14 -.03 .15 .36* -.20 -.28 -.19 -.19 -.13 2. Power distance change - .25 .06 .34* -.63** -.51** -.51** -.64** -.52*

3. Masculinity change - -.23 .08 -.13 -.39** -.43** -.43** -.56**

4. Uncertainty avoidance change - .09 -.07 .10 .04 -.04 .10

5. Long-term orientation change - -.50** -.27 -.17 -.21 -.28

6. Indulgence change - .35* .42** .59** .42**

7. Patent registration growth - .69** .71** .73**

8. Trademark registration growth - .72** .78**

9. Industrial design registration

growth - .74**

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indulgent, are also likely to become less power distant and long-term oriented. Lastly, change towards long-term orientation shows to significantly relate positively to both change towards individualism and change towards power distance. This indicates that countries that are getting more long-term oriented, are also likely to become more individualistic and power distant.

Hypothesis testing

To test whether cultural change relates to IP registration growth, a multiple regression analysis was conducted to predict the common dependent factor based on change towards individualism, change towards power distance, change towards masculinity, change towards uncertainty avoidance, change towards long-term orientation and change towards indulgence. Using the enter method, it was found that change on all cultural dimensions combined explains a significant amount of variance in the common dependent factor (F(6, 30) = 5.37, p = .001, R2_{= .52, R}2

adjusted = .42). Results indicate that change towards power distance and change towards masculinity significantly predict trademark registration growth (table 7).

Table 7

Coefficients of multiple regression analysis: common dependent factor predicted by change in cultural dimensions

Cultural change towards: Standardized β t p

Individualism -.06 -0.41 .674 Power distance -.43 -2.35 .026 Masculinity -.45 -3.22 .003 Uncertainty avoidance .08 0.61 .547 Long-term orientation -.21 -1.21 .235 Indulgence -.09 -0.43 .672

From these results, we conclude that change towards power distance and change towards masculinity significantly relate negatively to the common dependent factor, whereas change on any of the other cultural dimensions does not significantly relate to the common dependent factor. This indicates that the positive relationship between indulgence and the common dependent factor, as indicated in the correlation matrix, is in fact not a direct relationship, but is confounded by the other cultural dimensions. Based on these results, we confirm hypothesis H2b, and reject hypotheses H2a, H2c, H2d, H2e, and H2f.

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Exploratory analysis

Exploratively, we examined whether world regions differ regarding the direction of cultural change. Therefore, we grouped countries by world region and determined their average cultural change scores per dimension. These results are summarized in table 8.

Table 8

Change in cultural dimensions from time-period 1 to time-period 2 per world region

World region N IC PD MAS UA LTO IR

Asia 7 -2.01 -18.12 -14.56 +10.89 +11.57 -9.05

Europe 23 -3.95 -15.80 -3.33 +0.66 +11.62 -5.49

Middle East and North Africa 3 -10.46 -17.58 -4.62 +5.72 +14.66 -20.57

North America 3 -5.25 +3.68 -1.69 -3.90 +14.36 -20.57

Oceania 2 -3.09 +4.60 -13.54 -2.69 +24.51 -23.45

South America 7 +2.33 -7.60 +5.40 -6.46 +16.49 -17.03

Sub-Saharan Africa 2 +0.32 -17.73 -12.15 +5.51 +14.49 -12.02

Note. IC = individualism; PD = power distance; MAS = Masculinity; UA = uncertainty avoidance; LTO = long-term orientation; IR = indulgence.

These results show different changes in culture per world region. Most regions are becoming less individualistic, except for South America and Sub-Saharan Africa, which show a slight increase in individualism. The Middle East and North Africa remarkably show the most rapid decline in individualism. Furthermore, although regions show different directions in change regarding the first four cultural dimensions, all regions show a sharp increase in long term orientation and a sharp decrease in indulgence.

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Discussion & Conclusions

This study builds on previous research showing a link between national culture and innovation (Shane, 1993; Herbig & Dunphy, 1998; Nakata & Sivakumar, 1996). In particular, this study shows that certain national cultural characteristics relate to the innovation input and output of countries. In line with previous research, we found that individualism and long-term orientation relate positively to innovation, whereas power distance and uncertainty avoidance relate negatively to innovation, and masculinity does not relate to innovation at all. Additionally, we showed that the national cultural dimension of indulgence also relates positively to innovation, which has not been examined before. Regarding individualism, our results are not surprising, as previous research consistently shows a positive relationship between individualism and innovation (Shane, 1993; Menzel et al., 2008; Steenkamp et al., 1999; Rinne et al., 2012; Kaasa, 2013; Tugmaner, 2014). When comparing effect sizes of prior research with our estimation, we find that standardized β values are very similar, and indicate a small to medium effect size. Tugmaner found a standardized β value of .37, while Kaasa found a standardized β value of .35. Our study consequently found a standardized β value of .36. Rinne et al., however, estimated the partial η2_{in their study, and found a value of .23, indicating a} large effect size. Shane argues that the main reason for the relationship between individualism and innovation is that managers in individualist cultures are allowed more freedom to act upon creative ideas, whereas managers from collectivist cultures are not granted this freedom. As such, innovative ideas have a better chance to make it in individualist cultures. This argumentation is supported by findings of Kaasa, who found that individualism relates more strongly to innovation output than to innovation input. Indeed, creative ideas are more likely to result in innovative output when they are selected to be implemented. Additionally, individualism is associated with a value on individual performance, which might cause people to be more inclined towards generating and communicating innovative ideas to make an impression on others (Goncalo, & Staw, 2006).

In regard to power distance, results are also consistent with previous studies (Shane, 1993; Menzel et al., 2008; Steenkamp et al., 1999; Rinne et al., 2012; Kaasa, 2013; Tugmaner, 2014). Low power distance is associated with minimal organizational hierarchy, which might be the mechanism explaining this relationship. As organizational hierarchy is minimal in low power distance cultures, innovative ideas from employees reach top management more easily, making them more likely to be implemented. Additionally, a higher degree of trust in employees aids the implementation of

innovative ideas, as managers will expect these ideas to exert a better impact on their organization. Furthermore, our results are largely in line with prior literature regarding uncertainty avoidance (Shane, 1993; Menzel et al., 2008; Steenkamp et al., 1999; Kaasa, 2013). This is not surprising, as