How R&D investments are affected by national culture and to what extent is that relationship moderated by innovation?

How are R&D investments affected by national culture and to what extent is that relationship moderated by innovation?

Bachelor’s Thesis

Faculty of Economics and Business BSc Business Administration

Finance specialization

Author: Karl Martin Tamm Student ID:11621729

Supervisor: Dr. Evgenia Zhivotova Coordinator: Dr P.J.P.M. Versijp

Statement of Originality

This document is written by Karl Martin Tamm who declares to take full responsibility for the content of this document.

I declare that the text and the work presented in this document are 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

Abstract

The goal of this study was to explain how national culture may affect the research and development investments that corporations make, and how the direction of the effect is moderated by the levels of innovation in the society of the company’s country. The

hypothesis of this study was based on the assumption that the relationship between culture and corporate investments is to an extent moderated by innovation which the cultural frameworks do not measure. Likewise, the aim in this study was to test the efficiency of different prominent cultural models, such as Hofstede’s Cultural Values and GLOBE’s culture dimensions. This was done by combining 20 years of public companies’ financial data from Compustat. To analyse this, a combination of the Global Innovation Index, Hofstede’s Cultural Values frameworks and the GLOBE’s Cultural Dimensions model were used. Robust linear analysis was used to analyse the data from 42 countries and a significant effect of culture on R&D investments which was moderated by innovation in both culture models were found.

Table of Contents

1. Introduction ... 1

2. Literature Review... 4

2.1 R&D investments and firm value ... 4

2.2 Culture ... 4

2.3 Culture – GLOBE... 6

2.4 Innovation... 6

3. Data description & Methodology... 8

3.1 Variables... 9

3.2 Descriptive Statistics ... 10

3.3 Methodology ... 12

4. Results and Analysis ... 14

4.1 Hypothesis 1 ... 14

4.2 Hypothesis 2 ... 15

5. Conclusion and discussion ... 18

1. Introduction

Investing into research and development (R&D) is an important part in many companies. Researchers have noted a significant correlation between the right investments into R&D and its positive effects on profitability, product quality, sales and on the returns of other investments (Merrifield, 1989). Studies also have shown the importance of R&D investments for economic development (Guellec & Potterie, 2001). Likewise, Griliches (1992) reported his results on a broad span of social returns that come from investments into R&D. The latter described R&D as a substantial creator of growth, stating that it is

responsible for at least half of all increases in per capita output. Many corporations know this and thus place extensive emphasis on innovation. They are constantly looking for a

competitive advantage to gain an edge over their competitors. The right course of action can have large rewards, and this is especially true in industries where firms compete mainly on the basis of innovation. At the same time, investments in R&D are unpredictable, often long-term and their outcome can be hard to project (Zedtwitz, Gassmann, & Boutellier, 2004). R&D projects can be very costly and they can bring numerous problems as well. Firms usually go through great lengths to carefully plan out and finance their endeavours

considering the risk at stake. Even with great planning, human judgment is required as the uncertainty and complexity of the process can be approached in several ways. This leads companies to make different choices and the bias in these choices is currently an actively studied area.

Regarding research into international business and international management, culture has been one of the most long-lasting components (Caprar, Devinney, Kirkman & Caligiuri, 2015). This is because of its unique impact on a person. Even as a child, culture moulds and

guides the way people perceive value (Shao, Kwok, & Zhang, 2013). Culture is a major determinant in a person’s personality and contributes to their decision-making abilities.

In this paper, historical data of R&D investments made by public companies around the world are taken into consideration with an aim to explore how national culture affects their investment decisions. This topic is valuable as past literature has noted the direct associations with a company’s value and economic growth (Shao, Kwok, & Zhang, 2013). Naturally, large businesses around the globe are seeking to improve their R&D investments and processes given the value it can create. The reason R&D investments were chosen is due to their unpredictable nature which makes them difficult to systematically assess. This

requires management teams in those companies to make decisions which have been shown to be often contain a level of inherent bias (Zedtwitz, Gassmann, & Boutellier, 2004). By researching this bias and regressing it against the existing cultural differences, the effect of national culture on R&D investments can be examined in a systematic and rigorous fashion.

Similarly, this study also explores the moderating effect of innovation on the relationship between country culture and corporate R&D investment levels. Many articles have previously reported a significant correlation between cultural frameworks and

innovation. By observing the interaction of innovation, we can investigate if the combined model improved, and in which way, if any, does innovation influence the relationship of the outcome variable (OV) and the independent variable (IV).

Previous studies have mostly used financial data from OECD countries and mainly focused on the cultural differences between Western and East-Asian countries applied dynamic GMM methods (Lee, 2015). The results of his article indicated R&D investments are sensitive to a firm’s internal funds and in East-Asian countries this sensitivity was

and upon previous studies by including a wider range of countries from with developed and developing nations being included.

While many studies conducted on the effect of culture on business behaviours only used one cultural model, this research wishes to improve upon this and includes additional factors in the regression.

To sum up, this study seeks to investigate the following research question: How are R&D investments affected by national culture and to what extent is that relationship

2. Literature Review

To discover and understand why and how culture plays a role in how companies not only invest in R&D but also mitigate its potential risks, several key topics come into play. How R&D investments are linked to firm value, how and where culture comes into play, how the GLOBE project tries to explain these cultural dimension differences, and innovation lie at its core.

2.1 R&D investments and firm value

The literature has proven that investments in R&D produce value for a business as differentiation leads to a more unique and better product which in turn gives the company a competitive advantage over others (Ehie & Olibe, 2010). Even with major global disruptions, studies have shown that R&D investments positively affect manufacturing and service

companies. This is one of the reasons why the yearly amount of money invested into R&D has been growing consistently and reached a record of $1.7 trillion in 2019 ("How much does your country invest in R&D?", 2020). Nevertheless, R&D can also present significant

difficulties for many companies (Lee et al., 1996). Firstly, R&D is not easy to generalize as research is completely different from development. At the same time, R&D problems are not clearly structured, so executives are forced to make choices between trade-offs (Zedtwitz et al., 2004).

2.2 Culture

Systematically studying culture has proven to be extremely difficult as scholars have struggled to produce a framework which can accurately capture and explain all the complex characteristics of culture (Caprar, Devinney, Kirkman & Caligiuri, 2015). Despite it, many attempts have been made and one of the most well-known papers in this area was Hofstede's

“Culture's Consequences”. There he defined culture as "the collective programming of the mind that distinguishes the members of one group or category of people from others" (Hofstede, 2001, p. 9).His work on cultural values has been the most influential in its field and it has been cited over 54,000 times (Tung & Verbeke, 2010). The first model only distinguished between four cultural dimensions: Power Distance, Uncertainty Avoidance, Individualism and Masculinity (Hofstede, 1980). With data from 40 countries, Hofstede claimed that his framework was able to explain 50% of the business-wide variation between nations. In 2010, two variables called “Long Term versus Short Term Orientation” and “Indulgence versus Restraint” were added to the framework. Furthermore, decades of studies using other models have supported Hofstede’s work and shown the existence of a correlation between cultural values and employment behaviours (Kirkman, Lowe, & Gibson, 2006). Some researchers have pointed out that two dimensions were added 30 years later while the initial surveys did not try to measure them (Oyserman, Coon, & Kemmelmeier, 2002). Moreover, Hofstede himself has pointed out the limitations of his framework. Hofstede explained that due to the changing nature of culture, his rankings are not constant over time and need to be adjusted periodically (Hofstede, 1985).

Moreover, culture is enduring as Hofstede said in his work that “Among the

components of national cultures are the prevalent value systems that parents within a culture transfer to their children, and so on” (Hofstede, 1985, p. 347). Because of its influence on business decisions, culture has been used in previous research as a moderator and mediator of strategic planning, expansion patterns, cross-national information transfer, venture capital performance, entrepreneurship, leadership style and a multitude of other individual results (Kirkman, Lowe, & Gibson, 2006; Taras, Kirkman, & Steel, 2010). With this in mind, culture is a prominent factor in strategic planning and even though it is an intangible concept in itself, it can directly influence a firm’s value. For example, it is claimed that East Asian

nations such as Hong Kong and Japan share similar cultural views which originated from Confucian traditions and that this has given them a competitive advantage for economic development (Kahn, 1979).

2.3 Culture – GLOBE

The GLOBE (Global Leadership and Organizational Behaviour Effectiveness) project is a multi-phase, multi-method and multi-sample research project intended to investigate the interrelationships between societal culture, societal effectiveness and organizational

leadership. In comparison, Hofstede’s framework consists of six dimensions while the GLOBE framework makes use of 18 dimensions to distinguish between societal values and practices on an individual and in-group level. While both models report variables on a national level, their distinction arises from the GLOBE’s framework being based on

substantial empirical and theoretical research (Venaik & Brewer, 2016). Other authors used statistical analysis to illustrate how Uncertainty Avoidance (UA) dimensions in both models convey distinct parts of the same feature. Hofstede’s UA dimension was found to present societal stress while the GLOBE’s dimension conveys how to rule-oriented society is.

2.4 Innovation

Innovation has been researched by academics for several decades and still researchers have trouble accurately pinpointing its causes and its effect on organisations, policies and behaviours (Damanpour & Gopalakrishnan, 2001). Scholars are exploring how to solve the problem of how to create models that could cover the complexity of the real world. Naturally, the latter is not only complicated but difficult to encapsulate given the thousands of variables which come into play. Due to this, academics have to narrow their frameworks and focus on a specific innovation topic such as organizational innovation, the stages of innovation, and how countries’ view on R&D plays a role on innovation. This has made it difficult to unify the

findings as they were observed unrelated attitudes. In actuality, the different types of innovation overlap with each other.

An exhaustive project to measure innovation is The Global Innovation Index (GII). It is co-published annually by Cornell University, INSEAD and the World Intellectual Property Organization to capture the multi-dimensional aspects of innovation. The GII collects data on 129 countries and through 7 variables compiles a weighted global average score for each country. The GII elements are Institutions, Human capital and Research, Infrastructure, Market sophistication and Business sophistication Knowledge and Technology outputs and Creative outputs. By design, the GII takes into account the differences because of the

differing economic and political environments in each country. This makes the GII suitable as a measure of a nation’s overall level of innovation.

3. Data description & Methodology

The financial data in this study was gathered from the WRDS Wharton database, more specifically Compustat – Capital IQ (Global). This data consisted of 252,666

observations on 27,901 public companies from 1999 to 2020. The data on Hofstede’s cultural values was acquired from Hofstede’s cultural values website and it consisted of 110 countries and their scores on six cultural dimensions. The dimensions that were measure were: Power Distance, Uncertainty Avoidance, Individualism, Masculinity, Long Term versus Short Term Orientation and Indulgence versus Restraint. They are used to measure and compare cultural differences across country averages (Hofstede, 1985) on a 0 to 100 scale.

The Data from GLOBE’s 2004 project was required through their website and it included the information of 62 countries and their ranking based on 18 cultural dimensions. The GLOBE dimensions are as follows: Uncertainty Avoidance Societal Practices, Future Orientation Societal Practices, Power Distance Societal Practices, Collectivism I Societal Practices (Institutional Collectivism), Humane Orientation Societal Practices, Performance Orientation Societal Practices, Collectivism II Societal Practices (In-group Collectivism), Gender Egalitarianism Societal Practices, Assertiveness Societal Practices, Uncertainty Avoidance Societal Values, Future Orientation Societal Values, Power Distance Societal Values, Collectivism I Societal Values (Institutional Collectivism), Human Orientation Societal Values, Performance Orientation Societal Values, Collectivism II Societal Values (In-group Collectivism), Gender Egalitarianism Societal Values, Assertiveness Societal Values. They are used to measure a culture’s societal values and practices individually and, in a group, setting on a 0 to 10 scale. To be better compare the scores of both frameworks, all the values in the GLOBE framework were multiplied by ten to also have it on a 0 to 100 scale.

Data on innovation levels in different countries came from the Global Innovation Index website and consisted of an index ranking for 129 countries. All four datasets had to be combined to generate the final dataset. After removing missing values and computing new variables, the sample decreased to 177,439 observations of 23,536 companies from 42 different countries. The top three countries with the most observation arethe United States of America with 42,201 samples, Japan with 37,241 samples and China with 25,712 samples. Together they represent 59.26% of all observations and individually portray 23,78%, 20.99% and 14.49% of the data.

3.1 Variables

The majority of variables came directly from the original datasets and other variables were constructed using them. The GVKEY identifier, year, R&D expenditures, total assets, total liabilities, total equity, company name, ISO country code, innovation index, Hofstede’s 6 cultural values and GLOBE’s 18 cultural values are from their original datasets. Eleven other variables are computed.

This study chooses to use R&D ratio to show a company’s commitment into R&D. The variable was computed by dividing R&D expenditures by total assets. Research has shown a noteworthy relationship between a firm’s size and the amount it invests. This is also evident from the dataset as R&D expenditures and total assets have a correlation of 0.8043. In the light of that, R&D expenditure is not suitable for the test and it is preferred to use a company’s relative R&D expenditures to company size. When total R&D expenditures was divided by total assets and then it was multiplied by 100 to simplify the results. After it the correlation between company size and the outcome variable decreased by 0.8116 and turned negative from 0.8043 to -0.0073. The correlation table can be seen in table 1.

Table 1. Correlation between the outcome variable and firm size

TOTAL ASSETS R&D EXPENSES R&D RATIO TOTAL ASSETS 1.0000

R&D EXPENSES 0.8043 1.0000

R&D RATIO -0.0073 -0.0019 1.0000

Six additional variables are created for every country by multiplying their Hofstede’s scores with the relative GII value. On top of that, the last two constructed variables are computed per country by multiplying their average Hofstede and the average GLOBE values by their Innovation Index value.

Two variables, average Hofstede and average GLOBE are created per country and are the arithmetic average country scores in both cultural frameworks. As explained before, both frameworks average their results to get a country’s rating in each dimension. Therefore, an arithmetic average full score can be computed for each country in both culture models. Two more variables are created from them by multiplying a nation’s full score with its GII value.

3.2 Descriptive Statistics

In table 3 the mean and standard deviation of total assets, R&D expenditures, Hofstede’s average score, GLOBE’s average score, GII index score and the R&D ratio are given. On top of that, the smallest and largest recorded value is shown for each variable. As can be seen from the table, the largest variable is total assets which has the largest mean value of 735768.4 and has a standard deviation of 58,000,000. In total assets, the lowest value recorded was 0.03 and the highest was 14,500,000,000. It indicates that the size of the firms varies to a large extent and needs to be accounted for as to not influence the results. The last variable in Table 3, R&D ratio of total assets shows that on average, companies invest

variability and brings the standard deviation down to 6.1884, which can be seen in table 2. This allows for the observations to be compared on an equal basis and is in line with my assumption that the variable is more suited for the study than total assets.

Table 2. Descriptive Statistics

Variable Obs. Mean Std. Dev. Min Max

Power distance 177,439 55.3415 17.7571 11 104 Individuality 177,439 56.53 27.8872 13 91 Masculinity 177,439 64.8812 19.2694 5 95 Uncertainty Avoidance 177,439 56.3919 24.7857 8 112 Long-Term vs Short-Term 177,439 60.0068 27.3623 9 100 Indulgence 177,439 47.8334 18.8694 16.9643 97.3214 Innovation 177,439 54.9184 7.516 23.93 67.24 Assets 177,439 735768.4 5.8 0.03 1.45 R&D 177,439 6093.837 303426.3 0.001 6.12

In the table the mean and standard deviation of Hofstede’s cultural dimensions are presented along with the GII. The means of the variables show that on average nations’ cultural values lie near the centre. On the other hand, the standard deviation of each variable indicates that the countries in the study inhibit substantial variation in their national culture. It is especially prevalent in the values for individuality and long-term thinking with a standard deviation of 27.8872 and 27.3623 respectively. These results are in line with the assumption

that a country’s level of individuality and long-term thinking may have the most significant effect on the outcome.

3.3 Methodology

The aim of this study was to explore the effect of a nations culture on a company’s R&D expenditure and to see if this relationship is moderated by innovation. Secondly, this study wished to compare a different prominent culture model to see if it will perform better. The study first used linear regression, where Hofstede’s cultural model and its interaction effect with the GII were used as the independent variable. It was assumed that his cultural framework is able to explain some of the differences at a significant level, granted that previous research has supported Hofstede’s findings and that initially he proclaimed to be able explain 50% of the cross-country variance in business (Hofstede, 1985).

Nevertheless, research has shown a linkage in a country’s culture and on the level of innovative output it produces (Didero, Gareis, Marques & Ratzke, 2008). In his research Hofstede did not measure innovation in societies, although he suspected that part of it would be reflected in his Long Term versus Short Term Orientation dimension. The issue with including innovation in cultural frameworks has been that a nation’s innovative output is largely dependent on the economic and political factors inside the country (GII). OECD reports that 80% of all R&D expenditures are generated by ten of the of the most developed countries in the world. The Global Innovation Index uses a rigours method to measure the level of innovation in a society on a scale that is comparable with each other and tries to minimize bias of external factors to show the inherit levels of innovation in a country. As both are commonly used in studies, they are usually taken as independent measures and so the following hypothesis is proposed:

Hypothesis 1: Innovation has a significant moderating effect between cultural values and R&D investments.

In the light of the difficulties recorded by scholars in measuring culture, Hofstede’s model, while the most used one, is criticised by others. A substantial number of scholars have used his scores on country-level individualism as proxies for individualism. Many others have noted that Hofstede’s work found a discrepancy between two countries (Oyserman, Coon & Kemmelmeier, 2002). The GLOBE project attempts to improve upon these limitations and researches its measurement on an individual and group level. Additionally, the GLOBE project extends the list of dimensions from 6 to 18 variables and its framework is based on strong empirical research. Because the GLOBE project covers a larger are of

factors, it can be assumed that its model captures a bigger part of Innovation in its

measurements, than Hofstede’s. This was supported by looking at the correlation of models to the GII. Hofstede’s model has a correlation of -0.3315 to innovation while the GLOBE model has a -0.5272. Thus, the second hypothesis is:

Hypothesis 2: The GLOBE model describes more of the variation than the Hofstede model but is less moderated by innovation

4. Results and Analysis

In order to regress and further analyze the dataset, assumptions for regression had to be met and tested. Firstly, the scores from the GLOBE framework had to be multiplied by ten so that all the variable in the study are consistently measured. Tests for normality were used on the all the variables to observe their distribution. Due to the large number of observations, the Shapiro Wilk test for normality could not be used and thus tests for kurtosis and skewness were used instead. The tests showed a lack of both kurtosis and skewness which was

supported by examining the scatterplot. On top of that, both regressions use robust standard errors adjusted for heteroskedasticity to limit heteroskedasticity.

4.1 Hypothesis 1

In order to investigate this study first hypotheses that innovation has a positive moderating effect on the relationship between the Hofstede’s cultural values and R&D investments at the 95% confidence interval. All the assumption for the analysis were met. After conducting the analysis, it was found that the regression model explains 21% of the total variance of the outcome variable with a R² value 0.2101. This is in line with our

assumptions and previous research that culture influences the decision-making of companies. Interestingly, almost all variable in Hofstede’s framework were significant except for

Indulgence versus Restraint, which had a p-value 0.59>0.05. Firstly, the main effects of the cultural values of Hofstede were examined and from them Power-Distance and masculinity were the strongest predictors of the outcome variable which supports the findings of (Zhang, Zhang & Zhang, 2015). Except for Long-Term Orientation, all of the other dimensions were found to have a negative relationship with the outcome variable. With R&D projects, time is an important factor and the result of this regression are in line with the limitations explained in (Zedtwitz, Gassmann & Boutellier, 2004). With this in mind, innovation showed the

largest negative influence on the outcome. Innovation’s regression coefficient was almost double the coefficient of Power-Distance.

Then, the interaction effects between Hofstede’s cultural values and Innovation on R&D investments were examined. All of them were statistically significant and more interestingly, when innovation was added to the regression, the direction of Hofstede’s cultural dimension on the OV was reversed. Long-Term Orientation*Innovation had a negative coefficient of -.0020878 and Hofstede’s other variables were positively related to the OV. Based on this, the null hypothesis can be rejected the hypothesis is accepted as innovation exhibits a moderating effect on the interaction of Hofstede’s cultural framework and R&D expenditures.

Table 3. The results of the regression to test the hypothesis 1 and examine the effects of Hofstede’s variables, innovation and their interaction effects on R&D.

Effect Estimate t 95% CI LL UL Constant 27.3211 15.35*** 23.8316 30.8106 Power distance -0.2987 -23.51*** -0.3236 -0.2738 Individuality -0.0496 -5.39*** -0.0677 -0.0316 Masculinity -0.1568 -13.30*** -0.1799 -0.1337 Uncertainty Avoidance -0.0918 -20.57*** −0.1005 -0.083 Long-Term vs Short-Term 0.082 9.25*** 0.0646 0.0993 Indulgence -0.0215 -1.89 -0.0438 0.0008 Innovation -0.4560 -13.12*** -0.5241 -0.3879

Note: *** significant at 1% level, ** significant at 5% level, * significant at 10% level

4.2 Hypothesis 2

The second hypothesis was stated to examine whether the GLOBE model or the Hofstede’s framework is more effective in explaining the variance in R&D investments when the moderator Innovation is taken into consideration. Thus, two separate regression analyses were conducted. The first analysis used the weighted average score of Hofstede’s cultural values, Innovation and their interaction effect on R&D investments. The second analysis used the weighted average score of GLOBE cultural values, Innovation and their interaction effect on R&D investments.

The first regression analysis which examined Hofstede’s framework showed that the regression had a R² 0.1154, meaning that 11.5% of the total variance of the outcome variable is explained by the model. All variables were found to be significant and similar to the tests in the first hypothesis, innovation had a moderating effect on and reversed the direction of the framework’s effect.

The second regression looked at the GLOBE cultural model and it was able to increase R² by 0.0126% from 0.1154 to 0.1280 which is in line with our second hypothesis. Power Distance * Innovation 0.0062 23.53*** 0.0057 0.0067 Individuality * Innovation 0.0016 8.64*** 0.0012 0.0019 Masculinity *Innovation 0.0023 10.73*** 0.0019 0.0027 Uncertainty Avoidance * innovation 0.0017 19.53*** 0.0015 0.0019

Long vs Short Term * Innovation

-0.0021 -12.80*** -0.0024 -0.0018

As previously, all of the variables in the regression had a significant effect. Conversely to the second hypothesis, the moderating effect of innovation is bigger when the GLOBE model is used. The coefficients in the Hofstede model changed from -0.7151 to 0.0114 after adding innovation but the GLOBE model coefficients changed from 4.1852 to -0.0969. Thus the null-hypothesis is rejected.

Table 4. The results of the regression to test the hypothesis 2 and examine the effects of the Hofstede’s framework, innovation and their interaction effects on R&D.

R&D ratio Coefficient Standard error t 95% CI LL 95% CI UL Constant 27.527 1.1616 23.7*** 25.2503 29.8038 Hofs -0.7152 0.0227 -31.55*** -0.7595 -0.6707 Innovation -0.3333 0.02173 -15.34*** -0.3759 -0.2908 Hofs * Innovation 0.0114 0.0004 27.16*** 0.0106 0.012272

Note: *** significant at 1% level, ** significant at 5% level, * significant at 10% level

Table 5. The results of the regression to test the hypothesis 2 and examine the effects of GLOBE framework, innovation and their interaction effects on R&D.

R&D ratio Coefficient Standard error t 95% CI LL 95% CI UL Constant -196.5461 3.1027 -63.35*** -202.6273 -190.4649 GLOBE 4.1852 0.0676 61.93*** 4.0528 4.3177 Innovation 4.585 0.0619 74.12*** 4.4538 4.7063 GLOBE * Innovation -0.097 0.0014 -71.59*** -0.0996 -0.0943 Note: *** significant at 1% level, ** significant at 5% level, * significant at 10% level

5. Conclusion and discussion

Nowadays culture plays an increasingly important role not just in our society, but also in our business world. There are so many factors that are influenced by culture (Shao, Kwok, & Zhang, 2013). This research was conducted to answer the research question: How R&D investments are affected by national culture and to what extent is that relationship moderated by innovation? Based on the literature, it was hypothesized that innovation has a significant moderating effect on the relationship between the outcome variable and the independent variable. Identically, a similar analysis was conducted with a different cultural framework to see if it improves the regression results. To research this, financial data of public companies in 20 years was combined with the Global Innovation Index data, Hofstede’s cultural values frameworks and with the GLOBE culture model.

From the results, it can be stated that Hofstede’s cultural values, such as Power Distance, Individuality, Masculinity and Uncertainty Avoidance had a statistically significant negative effect on the levels of R&D investments. On the other hand, Long Term versus Short term Orientation had a statistically positive effect on R&D investments. There was no significant effect found for the cultural value Indulgence versus Restraint. I can assume that one of the reasons for the insignificant results of Indulgences vs Restraint is caused because the dimension focuses on very short-term characteristics similar to instinct. Since R&D projects and investments can have very long time-spans, it is almost a complete opposite to the dimension itself and thus will not have any significant effect on it.

Innovation was found to have a significant negative effect on R&D investments when other variables were controlled. This was an interesting result as one would expect them to be positively related but the outcome can have implications for future research. One idea for this result can be that the countries that have high inherent innovation levels need to divert fewer

resources to R&D development to achieve their goals. The interaction effect of Power

Distance and Innovation, the interaction effect of Individuality and Innovation, the interaction effect of Masculinity and Innovation, the interaction effect of Uncertainty Avoidance and Innovation, the interaction effect of Long Term versus Short term Orientation and Innovation, and the interaction effect of Indulgence versus Restraint and Innovation were found to have significant negative effects on R&D investments which are in line with the hypothesis of the study and show the moderating effect of innovation. One explanation for this effect can be that Hofstede’s dimensions do not incorporate innovation in its measurements. This is also suggested by the low correlation between them and it can imply that the when innovation is included in this framework, it can improve explanatory power but it can also reduce it.

When testing and comparing the efficiencies of GLOBE model versus Hofstede's framework while innovation is taken into consideration, it was found that the GLOBE model explained a higher percentage of the total variance of the outcome variable, such as R&D investments but innovation moderated the relationship. The last finding was not in line with the second hypotheses and the reasons for such a result would be interesting for furthers research. All in all, the study was able to answer the research question it set out to answer.

This research has many implications. This study is highly important for finance professionals because it compares two culture models and gives more details on their efficiency nowadays as innovation is taken into consideration. Also, it is important for

companies as they are going to have a better understanding of their investments and effects of culture as well as the innovations. Lastly, this research could be interesting for other

researchers as it looks like the practical issues such as R&D investments from the cultural perspective. It can be inspirational for other researchers and provide them with a theoretical framework in case they would want to work on this topic as well.

This study had several limitations which could have affected the results. Firstly, the database used for this research had a lot of missing financial data, which had to be removed, and data entry mistake. Initially, the dataset included 110 countries, but after cleaning it, the data from 42 countries were used in the study. It makes the research less generalizable and reliable. This could affect the findings and decrease the internal validity of the study. Besides, two models examined in this research included had scores for different lists of countries; therefore, it was difficult to conclude their efficiencies and influence on R&D investments.

Lastly, the concept of culture is not stable and changing over time. In the finance world, it is important to provide precise information to give efficient advice to companies around the world based on the findings. However, it is difficult to combine these financial and cultural concepts. Thus, the suggestion for the further research would be to focus on developing a more reliable way to measure the concepts to minimize bias from external factors when investigating the relationships between variables and increase validity.

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