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Venekamp, Jari S4065239
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The Influence of Culture on a Country’s Sustainability Competitiveness
Research Paper for Pre-Msc
Groningen, 06-02-2020
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THE INFLUENCE OF CULTURE ON A COUNTRY’S
SUSTAINABILITY COMPETITIVENESS
ABSTRACT
This article is about the influence of culture on the sustainability competitiveness of a country. Culture is described by the six dimensions of Hofstede. The sustainability competitiveness of a country is determined by different quantitative indicators, divided into
five categories. Based on prior research, the Hofstede dimensions are linked to these categories. This is followed by a regression analysis to determine relations. Culture has a
large influence on the sustainability competitiveness of a country. Not all categories are equally influenced by culture, this is dependent on the amount of human interference.
Categories with indicators such as pollution and therefore a higher degree of human interference tend to be influenced by culture to a stronger extent.
Jari Venekamp University of Groningen
Faculty of economics and business
06-02-2020
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INTRODUCTION
The importance of Corporate Social Responsibility (CSR) has seen a rise in recent years. A 2015 study found that 91% of global consumers expect businesses to operate in a responsible manner. In addition, 84% of global consumers specifically search for responsible products (highspeedtraining, 2018).
The above studies indicate that consumers are increasingly more aware of the importance of social responsibility. A company engaging in CSR shows that it does not only care about profit, but also takes an interest in wider social issues. This aligns with increasing customer demands for social responsibility and can therefore attract customers who also share these values (highspeedtraining, 2018).
In addition to attracting customers, CSR has many other benefits. For example, operating sustainably and ethically can lead to an improved public image. This is crucial as customers take public image into consideration when deciding whether they are willing to buy products.
In addition, CSR can lead to an advantage over competitors by standing out from an ethical and responsible perspective (highspeedtraining, 2018).
Although most of the world has seen an increase in demand for social responsibility from the consumers perspective, the engagement in CSR by companies around the world varies significantly. There are multiple sources for these differences such as the influence of legislation. Recent studies linked another source, however. This source is culture. A 2017 study by Gallén & Peraita found that different aspects of culture, as described by Hofstede’s six cultural dimensions, affects CSR disclosure. Another study in 2010 by Vachon linked the cultural dimensions to green corporatism and environmental innovation.
A reason for this difference in CSR measures is that companies are from countries with different sustainability competitiveness ratings. This score indicates the ability of a country to generate and sustain inclusive wealth and a dignified standard life. Studies have shown that companies from countries with a higher sustainability competitiveness are more likely to engage in CSR to a certain degree. As prior studies showed that culture influences
sustainability, it is expected that a connection is also found between culture and sustainability competitiveness.
There are models to describe culture and models to describe sustainability competitiveness.
Based on prior research, hypotheses will be drafted that state which aspect of culture
influences which aspect of sustainability competitiveness. This paper will research to verify
whether proven relationships between culture and sustainability also hold between culture
and sustainability competitiveness and identify relationships that have not been previously
researched.
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THEORETICAL FRAMEWORK
Culture
Culture is a difficult concept and cannot be described by just one definition. A broad
definition of culture is: “Culture is an umbrella term which encompasses the social behavior and norms found in human societies” (Nat.museum, 2019). Another definition describes different aspects of culture: “Culture encompasses religion, food, what we wear, how we wear it, our language, marriage, music, what we believe is right or wrong, how we sit at the table, how we greet visitors, how we behave with loved ones, and a million other things” (De Rossi, 2017). Hofstede describes culture as: “The programming of the human mind by which one group of people distinguishes itself from another group” (Hofstede’s Insights, 2019).
Given the complexity of the term “culture”, it is hard to apply a method to accurately
measure culture in a country. A question that comes to mind is: “How can a concept so broad and intangible be described quantitatively?’’. This is what Geert Hofstede did by applying the six dimensions of culture. Each dimension represents independent preferences for a certain state of affairs over a different state of affairs that distinguishes countries from each other (Hofstede’s Insights, 2020). It should be noted that a specific score on a dimension does not hold much meaning by itself. The scores of a country become relevant in comparison to another country.
The six culture dimensions of Hofstede Power Distance (PDI)
Power distance can be described as “the extent to which the less powerful members of organizations and institutions accept and expect that power is distributed unequally”
(Hofstede, 2011). Typical for this dimension is the fact that unequal distribution of power is not only enforced from above, but also expected from below. Followers endorse this
inequality as much as the leaders. An example of power distance in societies is the respect and fear for older people in societies with a high power distance, versus no respect and no fear for older people in societies with a low power distance. Another example is the
expectation of power use. Hofstede states that in countries with a low power distance: “Use of power should be legitimate and is subject to criteria of good and evil” (Hofstede, 2011). In countries with a high power distance, Hofstede states: “Power is a basic fact of society antedating good or evil: its legitimacy is irrelevant” (Hofstede, 2011).
Individualism versus collectivism (IDV)
Individualism can be described as: “a preference for a loosely-knit social framework in which individuals are expected to take care of only themselves and their immediate families.”
(Hofstede, 2011). Collectivism can be described as: “a preference for a tightly-knit framework in society in which individuals can expect their relatives or members of a particular ingroup to look after them in exchange for unquestioning loyalty” (Hofstede, 2011). A short description would be that this dimension either shows a preference for the ‘I’
or the ‘we’. For example, a country with a high IDV score puts more emphasis on the
development of the individual, whereas a country with a lower score puts more emphasis on
what is important for the group. The individual should do whatever provides the greatest use
for the group the individual is a part of.
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Masculinity versus femininity (MAS)
Masculinity represents a preference in society for materialism, achievement and heroism.
Femininity represents a preference for cooperation, modesty and quality of life. Masculine societies therefore tend to be more competitive whereas femininity is more consensus
oriented (Hofstede, 2011). Countries with a high MAS score also express somewhat of a ‘live to work’ society whereas countries with a low MAS score express more of a ‘work to live’
society. For example, in masculine societies life goals should be expressed in materials, a high job function including income and assertiveness. Whereas in feminine societies, long term happiness is more important (Hofstede, 2011).
Uncertainty avoidance (UAI)
Uncertainty avoidance indicates the discomfort of a society with uncertainty and ambiguity.
It expresses the degree to which a country tries to control the unknown future or lets it be. It is commonly mistaken for risk avoidance or following rules. But actually, it describes anxiety and distrust when confronted with unfamiliar situations. This is paired with the preferences for rules and habits (Hofstede, 2011).
Long term orientation versus short term orientation (LTO)
The long-term orientation has everything to do with change. It describes the degree to which societies maintain links with its past whilst dealing with present and future challenges.
Countries with a low score on LTO have a preference for maintaining traditions and express suspicion when it comes to change. Countries with a higher LTO score prefer to be more pragmatic. Societies express thrift and adjust modern education to prepare themselves for future challenges (Hofstede, 2011).
Indulgence versus restraint (IVR)
This dimension describes the degree to which gratification in relation to enjoying life and having fun is allowed. Indulgent societies tend to not suppress gratification, whereas more restraint societies do. This is often reinforced by strict social norms (Hofstede, 2011).
Schwartz’s Culture Model
In addition to Hofstede, an Israeli sociologist named Shalom Schwartz, divides culture into seven different clusters. Each cluster is linked to another cluster, its direct opposite.
Schwartz’ theory differs from Hofstede by stating that when a country expresses preference for a certain cluster, it will show aversion to its linked opposite. Similar to Hofstede, culture on each cluster is quantified by a score (US DK Expats, 2020).
Embeddedness versus autonomy
Embeddedness can be described by the degree to which individual inclinations are avoided that otherwise could disturb the traditional order. Its paired opposite, autonomy, describes the control an individual has over choices as opposed to having consider others and shared rules (US DK Expats, 2020).
Mastery versus harmony
In a culture with a preference for mastery, individuals are looking for success through
personal action. People tend to continuously look for self-improvement, sometimes at the cost
of others. Its paired opposite, harmony, states that people are happy to accept their place in
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the world. Harmony puts greater emphasis on the group, rather than the individual (Changing Minds, 2020).
Hierarchy versus egalitarianism
In a culture with a hierarchical preference, the social order is clear. People accept either the superior or inferior position that they have and are expected to be modest and self-controlled.
Its paired opposite, egalitarianism, states that everyone is equal and is expected to express concern for others (Changing Minds, 2020).
Hofstede versus Schwartz
Both models describe and quantify culture. However, Hofstede’s six dimensions are described more extensively. In addition to this, Hofstede provides more data. The theory allows for better country-to-country comparison which is essential for this research.
Therefore, Hofstede will be the literature used to describe culture in this research.
Sustainability competitiveness
Sustainability competitiveness is described as: “The ability to generate and sustain inclusive wealth and dignifying standard of life for all citizens in a globalized world of competing economies” (Solability, 2020). Solability ranked most countries in the world with a score, indicating the country’s competitiveness in comparison to others. To do this, competitiveness is divided into 5 different ‘layers’. Together, these layers form the sustainability pyramid, as illustrated below.
Figure 1 (Sustainability pyramid)
Each layer describes a different aspect of sustainability competitiveness, and countries are
given a score on each layer. Certain indicators for each layer determine the score of each
country. The scores on each layer determine the overall sustainability competitiveness rating
of a country (Solability, 2020).
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Natural capital
The first layer of the pyramid, natural capital, is defined by the natural physical environment.
Scores are based on the availability of recourses such as available land, forests and energy.
Countries with high scores on this layer typically have a high availability of land, rich biodiversity, and abundant natural resources (Solability, 2020).
Resource management
The second layer of the pyramid, resource management or resource efficiency, is described as the extent to which a country is able to manage available resources such as natural capital, human capital and financial capital efficiently. It is measured by indicators such as the amount of fossil fuels burnt, electricity usage, water per capita and resource balance. Most of the high scoring countries are developing countries, due to low resource consumption. The first developed economy in the ranking list is Sweden at place 21 (Solability, 2020).
Social capital
The third layer of the pyramid, social capital, is described as the sum of the country’s social stability and the general well-being of the population. It is measured by indicators such as health care availability, equality, crime rates and general freedom. European countries, especially West-European and Scandinavian countries, have the highest scores. This is followed by oceanic countries such as Australia and New-Zealand. Despite economic and cultural similarities between these countries and the United States, The US is ranked 40
th(Solability, 2020).
Intellectual capital
The fourth layer of the pyramid, intellectual capital, is described as “the basis for innovation capability and sustainable economic competitiveness” (Solability, 2020). It is measured by indicators such as school enrollment, school performance, research & development budgets and the amount of new business registrations. Countries with a high score on this layer are more likely to develop or sustain successful economies by research and high value adding, knowledge driven industries. At the top of the ranking list are mostly countries with well developed economies. South-Korea takes the number one spot, by a considerable margin, followed by Sweden (Solability, 2020).
Governance capital
The fifth layer of the pyramid, governance capital, is described as everything that is unrelated
to natural capital and shaped by legal and regulatory frameworks. It describes how society is
developed and maintained by authorities and institutions. This is most often in the form of
government bodies. It is measured by indicators such as the availability of public services,
country infrastructure, business environment, corruption, and financial stability. Developed
economies tend to score higher on this dimension than developing economies. Ireland is
ranked first, followed by the Czech Republic (Solability, 2020).
8 Other literature
In addition to Solability, there is not much literature that is able to describe and quantify sustainability competitiveness as extensively as Solability. One publication of ‘Our Common Future’ in 1987 defined sustainability competitiveness as: ‘’the development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (World Economic Forum, 2014). Similar to Solability, it describes sustainability competitiveness by dividing sustainability into different categories such as efficient use of natural resources and carbon reduction. However, this study is not as extensive as Solability and fails to quantify competitiveness comparably to Solability.
Linking the sustainability layers to the Hofstede dimensions
As defined in the literature section, each dimension of the cultural dimensions by Hofstede describes a certain aspect of national culture. In the same way, each layer of the sustainability pyramid describes a certain aspect of sustainable competitiveness. In the following section, the cultural dimensions of Hofstede will be linked to the sustainability layers. These
connections will solely be based on previous research. Each sustainability layer has certain criteria that influence the score on that dimension. For instance, the social capital layer has indicators such as: health care availability, equality and crime rates (Solability, 2020). Past research on relationships between the Hofstede dimensions and these indicators will determine which Hofstede dimensions will be linked to which sustainability layers. The sustainability layers determine the sustainability competitiveness of a country. Therefore, measuring the influence of culture on these layers measures the influence on sustainability competitiveness.
The first layer of the pyramid, natural capital, is defined as: “The natural physical
environment” (Solability, 2020). This involves the presence of agriculture, biodiversity, water and natural resources. Because resources are a thing nature gives, a country either has them or it does not, it is expected that culture does not influence this layer whatsoever. Presence of rivers or oil for example is given and uninfluenced by humanity and can therefore not be related to culture.
Hypothesis 1: There is no relationship between any of the Hofstede dimensions and the natural capital layer of the sustainability pyramid.
The second layer of the pyramid, resource efficiency, is described as “the ability to manage available resources efficiently” (Solability, 2020). The first indicator for this layer is energy.
This is measured by the amount of fossil fuels burnt, electricity usage and the number of renewables. The second indicator is water. This is measured by the amount of water per capita, water withdrawals rate and water productivity. The third indicator is the availability of raw materials.
A study by Husted in 2005 found a significant influence of certain cultural dimensions by Hofstede on environmental sustainability. The study found that the IDV-dimension positively influences environmental sustainability. It also found a negative relationship between the PDI-dimension and environmental sustainability (Husted, 2005). Environmental
sustainability is closely linked to the energy and water indicators. Therefore, based on the
research by Hudson, it is expected that IDV and PDI influence the scores on the resource
efficiency layer of the pyramid.
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Hypothesis 2A: The resource efficiency layer of the sustainability pyramid is influenced by culture.
Hypothesis 2B: The resource efficiency layer of the sustainability pyramid is positively influenced by the IDV-dimension.
Hypothesis 2C: The resource efficiency layer of the sustainability pyramid is negatively influenced by the PDI-dimension.
The third layer of the pyramid, social capital, is defined as: “the sum of a nation’s political stability and well-being of the entire population” (Solability, 2020). The first indicator for this layer is health. This is measured by health care availability, child mortality and family planning. The second indicator is equality. This is measured by income equality, resource equality and gender equality. The third indicator is crime. This is measured by theft ratings, violent crime ratings and the prison population. The fourth indicator is freedom. This is measured by the amount of press freedom and human rights ratings. The fifth indicator is satisfaction. This is measured by individual happiness ratings, suicide rates and public service satisfaction ratings.
A study by Alas in 2006 found that power distance has a positive relationship with ethical values such as standard of living and social equality. The concepts of standard of living and social equality are measurements of the equality and satisfaction indicators. Therefore, it is expected that power distance positively influences social capital (Alas, 2006). Another study, by Vernaik et al. in 2013 titled: ‘’Looking into the future: Hofstede long term orientation versus globe future orientation”, found a positive relationship between the LTO-dimension and human desire for more equality (Vernaik, Zhu, & Brewer, 2013). As equality is an indicator for the social capital layer, it is expected that LTO influences social capital positively.
Hypothesis 3A: The social capital layer of the sustainability pyramid is influenced by culture.
Hypothesis 3B: The social capital layer of the sustainability pyramid is positively influenced by the PDI-dimension.
Hypothesis 3C: The social capital layer of the sustainability pyramid is positively influenced by the LTO-dimension.
The fourth layer of the pyramid, intellectual capital, is defined as: “the value of a company or organization’s employee knowledge, skills, business training or any proprietary information that may provide the company with a competitive advantage’’ (investopia, 2019). The first indicator of this layer is education. This is measured by the amount of school enrollments, the average school performance and school infrastructure. The second indicator is research and development. This is measured by capital allocation and tertiary education. The third indicator is new business. This is measured by the amount of new business registrations, high-tech manufacturing businesses and trademarks (Solability, 2020).
A study by Figlio et al in 2019 titled: ‘’Long-Term Orientation and Educational
Performance” found a positive relationship between LTO and educational performance. As
educational performance is a measurement of the education indicator, it is expected that LTO
positively influences the intellectual capital layer.
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Hypothesis 4A: The intellectual capital layer of the sustainability pyramid is influenced by culture.
Hypothesis 4B: The intellectual capital layer of the sustainability pyramid is positively influenced by the LTO-dimension.
The fifth layer of the pyramid is governance capital. This concerns everything related to society and economy which is shaped by legal regulatory and a framework. This framework is developed, maintained and updated by institutions and authorities. Most often this is in the form of government bodies (Solability, 2020). The first indicator for this layer is government cohesion. This is measured by the availability of public services, the educational budged and the military spending. The second indicator is infrastructure. This is measured by the amount of infrastructure investments and the number of roads and rail. The third indicator is business environment. This is measured by the ease-of-doing-business rating, business registration and sector developments. The fourth indicator is corruption. This is measured by the corruption index rating and bribery prevalence. The fifth indicator is financial stability. This is measured by the expose to certain financial shocks and financial regulation.
A study by Sanyal and Samanta in 2000 found that power distance and masculinity positively affect corruption. As corruption is an indicator for governance capital, it is expected that the PDI-dimension influences the governance capital layer (Sanyal & Samanta, 2002). This is because a higher corruption level will lead to a lower governance capital score (Solability, 2020).
Hypothesis 5A: The governance capital layer of the sustainability pyramid is influenced by culture.
Hypothesis 5B: The governance capital layer of the sustainability pyramid is negatively influenced by the PDI-dimension.
These hypotheses help answer the following central research question.
Central research question: what is the impact of culture on the sustainability competitiveness
of countries?
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METHODOLOGY
Two methods have been used to describe culture. Although other theories exist in literature, not all of them can be backed up with quantitative data. As this research requires culture to be quantified, only cultural theories using quantitative data have been elaborated in the
theoretical framework section. Of the two, Hofstede described culture more extensively. In addition to this, there is also a higher availability of data. Therefore, it was decided to link the cultural dimension of Hofstede to the sustainability layers instead of Schwartz’ clusters.
Solability was used to describe and quantify sustainability competitiveness. Although there is literature to describe sustainability competitiveness, there is no literature that quantifies it.
Therefore, the sustainability layers of Solability are used.
To find literature on both topics, search terms such as: “culture” and “sustainability competitiveness” were used to search for articles on Smartcat and Google Scholar. It was then decided that the research would only be included in the research if it was able to quantify either culture or sustainability competitiveness.
The sustainability competitiveness score consists of multiple layers and most countries have an individual score on each layer. This data is public and can be found on the website of Solability. On the website of Hofstede, a data file containing all the Hofstede scores is
available for download. Firstly, both datasets are edited and organized. Concerning Hofstede, some countries missed data on either all or specific dimensions. These countries have been excluded from the research. The Solability database has been filtered in the same way. Lastly, any countries that were only present in one database and absent in the other, have also been deleted. Some countries were missing in the Hofstede database, these have been manually added by looking up the scores in the country comparison section of Hofstede’s website. The dataset concerning Hofstede’s cultural dimensions was made public in 2015. The
sustainability dataset was made public in 2019. The total amount of countries with valid scores in both datasets is 60.
To check whether the hypotheses are correct, a statistical analysis will be computed. Both datasets contain interval data on a scale between zero and one hundred. Given the hypotheses and the datatype, the statistical test will be a regression analysis between the dependent and independent variables as stated previously. A separate analysis for each dependent variable will be computed. All dimensions from Hofstede will be added as independent variables for every test. In addition to the significance levels of the individual variables, the regression analysis will also provide a ‘Prob > F’ value. This indicates the significance of the whole model and will test all hypotheses stating a general relationship between culture and the respective sustainability layer.
For all ‘A’ hypotheses, the null hypothesis is that R
2= 0. Where R
2represents the explanatory value. This explains the percentage of variation of the dependent variable that is caused by variations of the independent variables.
For all ‘A’ hypotheses, the alternative hypothesis is that R
2≠ 0. The ‘Prob > F’ value indicates the probability of making a type I error.
For all other hypotheses, the null hypothesis is β
k= 0. Where β
krepresents the regression
coefficient of all independent variables.
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Table 2 (Regression Results)
For all other hypotheses, the alternative hypothesis is that at least one β
i≠ 0. Where β
irepresents the regression coefficient of any independent variable.
RESULTS
The summary statistics of all variables is stated below. The names of the Hofstede dimensions are in the first six rows and are abbreviated. These represent the independent variables. This is followed by the dependent variables, the sustainability layers.
Summary statistics
N Mean Median St.Dev min max
pdi 60 58.333 60.5 20.661 11 100
idv 60 46.583 46 23.618 12 91
mas 60 48.883 49.5 20.126 5 100
uai 60 67.283 70 22.543 8 100
lto 60 48.82 48.11 22.511 13 100
ivr 60 48.025 46.875 22.342 1 100
naturalcapital 60 45.246 44.305 10.372 24.92 63.74
socialcapital 60 47.12 48.395 7.315 33.12 58.78
intellectualcapital 60 47.648 47.5 11.455 18.47 72.93
governancecapital 60 55.232 54.845 5.557 41.18 66.46
resourceintensity 60 49.396 49.615 6.977 36.37 63.79
Table 1 (summary statistics)
The results of all regression analysis are in the table below. The models have been combined using outreg2 in STATA. The significance of the regression coefficients is represented by the
*’s. The ‘constant’ is the y-intercept. The standard errors are represented in parentheses below each coefficient. For all models, the adjusted R
2value is used instead of the regular R
2. This value corrects the increase of the R
2that is caused by an increase in the number of variables.(1) (2) (3) (4) (5)
Variables natural capital resource efficiency social capital intellectual capital governance capital
pdi -0.0437 -0.0556 -0.0898* -0.0494 -0.0617
(0.0893) (0.0551) (0.0474) (0.0761) (0.0435)
idv 0.0568 0.126*** 0.0800* 0.103 0.0418
(0.0753) (0.0464) (0.0400) (0.0642) (0.0367)
mas -0.148** -0.0244 -0.0449 -0.0882 0.00791
(0.0666) (0.0411) (0.0354) (0.0568) (0.0325)
uai 0.0595 0.0402 -0.00564 -0.0433 -0.00405
(0.0589) (0.0363) (0.0312) (0.0502) (0.0287)
lto -0.0757 0.0187 0.177*** 0.340*** 0.0730**
(0.0698) (0.0430) (0.0370) (0.0595) (0.0340)
ivr 0.0570 0.0305 0.0353 0.179*** -0.0617*
(0.0733) (0.0452) (0.0389) (0.0625) (0.0357)
Constant 49.35*** 42.89*** 40.89*** 27.73*** 56.17***
(10.76) (6.635) (5.712) (9.177) (5.244)
Prob > F 0.0721* 0.0017*** 0.0000*** 0.0000*** 0.0012***
Adjusted R2 0.0983 0.2427 0.4893 0.4624 0.2539
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
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The first model, natural capital, is significant at a 90% confidence level. This is not in
compliance with hypothesis 1. The explanatory value is just 0.0983. This means that 9,83%
of the variation of the natural capital score can be explained by a variation of the cultural dimension scores, which is low in comparison to other explanatory values. Considering significance at a confidence level of 90%, the only significant regression coefficient is the masculinity dimension.
The second model, resource efficiency, is significant. This means the null hypothesis of R
2= 0 can be rejected and the alternative hypothesis accepted. This is in compliance with
hypothesis 2A. The explanatory value is 0.2427. This means that 24,3% of the score variation of resource efficiency can be explained by a score variation of the Hofstede dimensions. The only significant regression coefficient is the individuality dimension. This means that country culture, as described by Hofstede’s IDV-dimension, positively influences the score on
resource efficiency. This is in compliance with hypothesis 2B. Hypothesis 2C states a negative influence from the PDI-dimension on resource efficiency. Although the regression coefficient is negative, the result is not significant and the hypothesis therefore unproven.
The third model, social capital, is highly significant as the ‘Prob > F’ value is nearly zero.
This is in compliance with hypothesis 3A, meaning the null hypothesis is rejected and it is accepted that R
2≠ 0. The explanatory value is 0.4893. This means 48,9% of the score variation of social capital can be explained by a score variation of the Hofstede dimensions.
This indicates a strong connection between culture and the social capital layer. The PDI- dimension regression coefficient is significant at p<0.1. However, this is not in compliance with hypothesis 3B, as the regression coefficient is negative. The hypothesis expected a positive relation between the PDI-dimension and social capital. Therefore, the hypothesis is disproven. The LTO-dimension regression coefficient is significant at a 99% confidence level. This is in compliance with hypothesis 3C.
The fourth model, intellectual capital, is highly significant as the ‘Prob > F’ value is nearly zero. This is in compliance with hypothesis 4A, meaning the null hypothesis is rejected and it can be concluded that culture influences the intellectual capital layer. The explanatory value is 0.4624. This means that 46,2% of the score variation on intellectual capital can be
explained by a score variation on the Hofstede dimensions. This, just like social capital, indicates a strong connection between culture and sustainability competitiveness. The regression coefficient of the LTO and IVR dimensions are significant at p<0.01. This is in compliance with hypothesis 4B. However, the significance of the IVR-dimension was unexpected. This means that there is some connection between the dimension and the indicators of the layer. One reason could be that such a link has not been researched yet.
Another reason could be that an unidentified variable influences a country score on the
intellectual capital layer.
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The fifth model, governance capital, is significant as the ‘Prob > F’ value is below 0.01. This means the alternative hypothesis is accepted and it is concluded that culture influences country scores on governance capital. This is stated in hypothesis 5A. The explanatory value is 0.2539. This means that 25,4% of the score variation on governance capital can be
explained by a variation of Hofstede’s cultural dimension scores. Hypothesis 5B is unproven.
Although the regression coefficient is negative, it is insignificant and can therefore not prove the hypothesis. Regression coefficients of the LTO and IVR-dimensions are significant, however. This was not expected as there was no evidence of relationships between these dimensions and indicators of governance capital.
CONCLUSION
To answer the central research question: ‘’what is the impact of culture on the sustainability competitiveness of countries?’’, it can be said that there is a strong link between culture and sustainability competitiveness. The research showed that culture influences every layer of the sustainability, even the natural capital layer which was expected to be insignificant. Different aspects of culture determine the score of a country on each layer, meaning that culture as a whole does not necessarily influence the score, but rather certain aspects of it. For each layer of sustainability, different cultural aspects are important. It seems that categories
experiencing a higher degree of human interference, are more influenced by culture.
An overview of the results is stated below.
Hypotheses Accepted or rejected Reason
1: There is no relationship between any of the Hofstede dimensions and the natural capital layer of the sustainability pyramid.
Rejected Significant at p<0.1
2A: The resource efficiency layer of the sustainability pyramid is influenced by culture.
Accepted Significant at p<0.01
2B: The resource efficiency layer of the sustainability pyramid is positively influenced by the IDV-dimension.
Accepted Significant at p<0.01
2C: The resource efficiency layer of the sustainability pyramid is negatively influenced by the PDI-dimension.
Rejected Insignificant
3A: The social capital layer of the sustainability pyramid is influenced by culture
.
Accepted Significant at p<0.01
3B: The social capital layer of the sustainability pyramid is positively influenced by the PDI-dimension.
Rejected Negative regression coefficient
instead of positive
15 3C: The social capital layer of
the sustainability pyramid is positively influenced by the LTO-dimension.
Accepted Significant at p<0.01
4A: The intellectual capital layer of the sustainability pyramid is influenced by culture.
Accepted Significant at p<0.01
4B: The intellectual capital layer of the sustainability pyramid is positively influenced by the LTO-dimension.
Accepted Significant at p<0.01
5A: The governance capital layer of the sustainability pyramid is influenced by culture.
Accepted Significant at p<0.01
5B: The governance capital layer of the sustainability pyramid is negatively influenced by the PDI-dimension.
Rejected Insignificant
Figure 3 (summary of results)
The first hypothesis is significant at p<0.1. This is interesting as no aspect of natural capital should be influenceable by culture. Nevertheless, there is a significant relationship between masculinity and natural capital. This means that some unidentified aspect of natural capital is influenced by culture. This unidentified aspect is not mentioned by Solability.
Hypotheses 2 and 2A are significant, this means the resource efficiency layer is influenced by culture in general, as well as specifically positively by the IDV dimension. The proven
relationship by Husted between IDV and environmental sustainability also holds for the resource efficiency layer.
Hypotheses 2C, a negative relationship between PDI and resource efficiency, is insignificant.
Even though the study by Husted proved a relationship between PDI and environmental sustainability. It turns out that even though resource efficiency and environmental
sustainability are closely related, the relationship does not hold for the resource efficiency layer.
Hypotheses 3A and 3C, stating a relationship between culture and social capital in general as well as a positive relationship between LTO and social capital, are accepted. It was
hypothesized that LTO influenced this layer as equality is an indicator for the social capital layer, this turned out to be the case. Hypothesis 3B, a positive relationship between PDI and social capital, is insignificant. Even though Alas found a relationship between culture and social equality, which is an important indicator for the social capital layer, a relationship is unproven.
Hypotheses 4A and 4B, a general relationship between culture and intellectual capital as well as a positive relationship between LTO and intellectual capital, are accepted. Figlio proved a relationship between LTO and education. The relationship also holds for intellectual capital, likely because education is an important indicator for this layer.
Hypothesis 5A, stating a relationship between governance capital and culture in general, is
proven. However, the layer is affected by aspects of culture that were not hypothesized as
hypothesis 5B, stating a negative relationship between PDI and governance capital, is
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disproven. Sanyal and Samata proved a relationship between PDI and corruption. Even though corruption is an indicator for governance capital, the relationship is unproven.
The significance levels of this analysis do not only prove a relationship, but it also tells something about how closely the two subjects are related. Most models were significant above the 99% confidence level. For some, the p-value was near zero. As culture is
intertwined with sustainability competitiveness, and equally intertwined with being hard to change, it provides an argument why countries experiencing low sustainability
competitiveness seem to be stuck with that score. Although culture is not the only factor influencing competitiveness, as is obvious by the explanatory values of each model, it most certainly plays an important role. In the case of social capital, culture explains social capital score variation for nearly 50%. Sometimes, however hard a country might try to improve sustainability competitiveness, it is battling against its own difficult-to-change culture.
DISCUSSION AND LIMITATIONS
Firstly, it should be noted that the rating system of the Hofstede dimensions is imperfect. It defines culture to be bound by borders. However, culture is extremely diverse, even within the same country. For example, the entirety of India has one specific score on each of the Hofstede dimensions. Yet, the country is diverse from a cultural, religious and ethnical perspective. India did not exist as a country before it was a part of the British empire, therefore different parts of what people call India nowadays were almost entirely different.
Yet, the entire country now has one specific score on the dimensions of Hofstede. Although Hofstede’s way of measuring culture remains one of the most thorough methods today, it is not without its flaws. The scores on the Hofstede dimensions should not indicate the way culture is in a specific country but serve as a comparison tool to make it easier to understand cultural differences between two or more countries.
It should also be noted that linking the Hofstede dimensions to the sustainability layers has solely been based on prior research. This means that there are, as proven by the results, different unexpected relationships. The results of this paper can therefore function as a basis for future research between culture and sustainability competitiveness instead of reproving relationships that have already been researched. For instance, there is a strong relationship between IVR and intellectual capital as p<0.01, but there is no research to prove a
relationship between IVR and any of the indicators.
Furthermore, the first model was significant at p<0.1. As most indicators consist of resources given by nature, it seems that culture should not have any relation to a score on this layer.
However, the website of Solability does mention ‘pollution’ in the description of this layer.
As pollution is controlled by humanity, this could be the reason for a significant result in the
regression analysis. This would explain a low explanatory value, as this indicator is just a
small part of the natural capital indicators. This is speculation, however. Further research is
required to prove this. Research in the relationship between the masculinity dimension and
pollution would also be required.
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REFERENCES
Alas, R. (2006). Ethics in countries with different cultural dimensions. Journal of business ethics.
Changing Minds. (2020). Schwartz Culture Model. Retrieved from Changing Minds:
http://changingminds.org/explanations/culture/schwartz_culture.htm
Figlio, D., Giulliano, P., Ozek, U., & Sapienza, P. (2019). Long-Term Orientation and Educational Performance. American Economic Journal, 272-309.
Gallén, M., & Peraita, C. (2017). The effects of national culture on corporate social responsibility disclosure: a cross-country comparison. Applied Economics, 2967-2979.
Herremans, I. (2007). Relationships Among Intellectual Capital,Uncertain Knowledge, and Culture.
Global Journal of Business Research, Vol. 1, 24-35.
High Speed Training. (2018, January 26). The importance of corporate social responsibility for your business. Retrieved from High Speed Training:
https://www.highspeedtraining.co.uk/hub/importance-of-corporate-social-responsibility/
Hofstede's Insights. (2019, February 27). What do we mean by culture? Retrieved from Hofstede's Insights: https://news.hofstede-insights.com/news/what-do-we-mean-by-culture
Husted, B. W. (2005). Culture and Ecology: A Cross-National Study of the Determinants of Environmental Sustainability. MIR: Management International Review, 349-371.
Investopia. (2019, April 29). Intellectual Capital. Retrieved from Investopia:
https://www.investopedia.com/terms/i/intellectual_capital.asp LiveScience. (2017, July 13). What is culture? Retrieved from LiveScience:
https://www.livescience.com/21478-what-is-culture-definition-of-culture.html Nat.museum-digital.de. (2019, October 6). Culture. Retrieved from Nat.museum-digital.de:
https://nat.museum-digital.de/index.php?t=tag&id=2745&cachesLoaded=true Sanyal, R. N., & Samanta, S. K. (2002). Corruption Across Countries: The Cultural and Economic
Factors. Business & Professional Ethics Journal, 21-46.
Solability. (2019, December 31). Global Sustainable Competitiveness Index 2019. Retrieved from Solability: http://solability.com/the-global-sustainable-competitiveness-index/downloads Solability. (2020, January 1). The Global Index. Retrieved from Solability: http://solability.com/the-
global-sustainable-competitiveness-index/the-index
Solability. (2020, January 1). The global sustainable competitiveness index. Retrieved from Solability:
http://solability.com/the-global-sustainable-competitiveness-index/methodology US DK Expats. (2020). Schwartz's Culture Model. Retrieved from US DK Expats:
https://usdkexpats.org/theory/schwartzs-culture-model
Vernaik, S., Zhu, Y., & Brewer, P. (2013). Looking into the future: Hofstede long term orientation versus GLOBE future orientation. Cross Cultural Management An International Journal, 361- 385.
18 World Economic Forum. (2014). Defining Sustainable Competitiveness. Retrieved from World
Economic Forum: https://reports.weforum.org/global-competitiveness-report-2014- 2015/defining-sustainable-competitiveness/
