THE IMPACT OF CULTURE ON GREEN INNOVATION STRATEGIES

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THE IMPACT OF CULTURE ON GREEN INNOVATION STRATEGIES

University: Amsterdam Business School Department: Economics and Business

Master: MSc BA – International Management Track Thesis Supervisor: Federica Nieri

Second Reader:

Author: Peter Molnar

Student Number: 11757442 EBEC Number: 20210117080109 Date: 28th January 2021

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Statement of originality

This document is written by Peter Molnar 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

Political institutions and companies have set ambitious goals to transition our economy into a more sustainable one. Initiatives such as the United Nations Sustainable Development Goals aim to prioritize long term and ecological sustainability as a key driver for societies and businesses moving forwards. To understand how we can transition into a more sustainable society, scholarshave researched into how companies implement Green Innovation Strategies (GIS). The implementation of GIS enables the company to reduce their footprint by improving their efficiency in their production, sourcing and allocating their resources. Different drivers of green activities and initiatives are quickly becoming an important piece of the puzzle to understand, what determines the rate of green innovation in companies. In a study of 1368 companies over the time period of 2010-2016, country Culture as an antecedent to the rate of implementing GIS has been analysed.

Power Distance and Uncertainty Avoidance have been identified as key independent variables based on the available research. This study investigates the relationship between these cultural dimensions, presented by Hofstede (1978) and the moderation by Female Prevalence, Firm Age, and Management Experience. The findings show links with a positive impact of Uncertainty Avoidanceon GIS. This relationship is positively moderatedby Female Prevalence and negatively moderated by Firm Age. However, Power Distance does not show any significant impact on GIS. This research contributes to theoretical literature with newly supported findings as well as some direct managerial implications that can be utilized in a business environment. Lastly, improvements as well as theoretical direction are presented to provide additional insights into this topic.

Keywords: Green Patents, Non-green Patent, Power Distance, Uncertainty Avoidance, Female Prevalence, Firm Age, Management Experience, Firm Behaviour

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Table of Contents

Statement of originality ... 2

Abstract... 3

Index of Tables and Figures ... 6

1. Introduction ... 7

2. Literature Review ... 13

2.1Green Innovation Strategy (GIS) ... 13

2.2Culture ... 15

2.3 Impact of Culture on Green Innovation Strategies (GIS) ... 18

2.4 Gender diversity, Firm Age, Management Experience, and Firm Behaviour ... 21

3. Theoretical Framework ... 24

3.1Impact of Culture on Green Innovation Strategies (GIS) ... 24

3.2.1Moderating Impact of Female Prevalence ... 27

3.2.2Moderating Impact of Firm Age ... 28

3.2.3Moderating Impact of Management Experience ... 30

3.3Conceptual Framework ... 32

4 Method ... 33

4.1Data Sampling and Collection ... 33

4.2 Variables... 34

4.2.1 Dependent Variable: Green Patents ... 34

4.2.2 Independent Variable: Power Distance and Uncertainty Avoidance ... 35

4.2.3 Moderating variables – Gender Diversity, Firm Age and Management Experience ... 36

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4.3 Econometric Analysis ... 38

5 Results ... 41

5.1Descriptive statistics ... 41

5.2 Correlation Matrix ... 43

5.2Multicollinearity ... 46

5.3Poisson Regression Analysis ... 46

5.3.1 Poisson Regression Analysis Model 1-3 – Direct effects ... 47

5.3.2 Poisson Regression Analysis Model 4: Female Prevalence ... 49

5.3.3 Poisson Regression Analysis Model 5: Firm Age ... 50

5.3.4 Poisson Regression Analysis Model 6: Management Experience ... 50

6. Discussion ... 54

6.1 Main Findings ... 54

6.2.1Theoretical implications... 56

6.2.2Managerial implications ... 57

6.3 Limitations and directions of the research... 58

7. Conclusion ... 60

8. Bibliography ... 62

9. Appendices ... 68

Appendix 1 – Robustness check: Net_Income ... 68

Appendix 2 – Robustness check: Net_Income ... 69

Appendix 3 – Robustness check: Employees ... 70

Appendix 4 – Robustness check: Employees ... 71

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Index of Tables and Figures

Table 1: Descriptive statistics per variable 42

Table 2: Correlation Matrix 46

Table 3: Poisson regression results: Model 1-3 48

Table 4: Poisson regression results: Model 4-6 51

Figure 1: Conceptual Framework 32

Figure 2: Moderating Effect: Female Prevalence 52

Figure 3: Moderating Effect: Firm Age 53

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1. Introduction

Sustainability and global warming have become two widely discussed topics that are closely intertwined. The 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries - developed and developing - in a global partnership (Sustainable Development, 2020). Moreover, the European Union published their initiative, Green Deal, as of December 2019 declaring that climate change and environmental degradation are existential threats to Europe and the world aiming to become climate neutral by 2050 (European Commission, 2020).

To overcome climate challenges, there is a need of new growth strategy that transforms the Union into a modern, resource-efficient and a globally competitive economy (European Commission, 2020). This strategy will involve governments, firms and all individuals in their policies to make this ambitious goal a realistic one. Green innovation strategies (GIS) have emerged as an initiative to do business in a sustainable way, both for the business and the planet, innovating products and services in a green way, reducing pollution and optimizing resource allocation (Eiadat , Roche, & Eyaday, 2008). GIS are technological innovations that help companies reduce their ecological footprint.

These innovations often include the innovation in technologies that are involved in energy-saving, pollution-prevention, waste recycling, or green product designs (Leal-Millan, Leal-Rodriguez, & Albort-Morant, 2017). In the recent years, firms and scholars study GIS and the impact of implementing sustainable solutions on business behavior and performance (Millan, 2017). Green innovations and the impact on businesses has become an increasingly

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important topic. As GIS is a relatively new topic researched by scholars and businesses, findings on its antecedents and what affects the rate of GIS is limited.

As a part of globalization, companies began to expand internationally and are often scattered over several countries and continents (You Matter, 2020). Even though green innovations are company-level decisions, businesses are becoming more and more global and have to adhere to local laws and regulations. Currently, there is a research gap between the relationship of country Culture and GIS. The mechanism between the two has not been analyzed and little is known about how Culture can impact the rate of green activities within companies. The current research streams identify the impact of Culture on firm’s performance, firm behavior as well as CSR engagement or CSR assurance (Mihet, 2012). However, when it comes to implementing GIS little research has been made to understand its antecedents in the context of culture and firm behavior.

Literature on county culture mostly relies on Hofstede (1973) and the 6 cultural dimensions. This model serves for cross-cultural communication such as Power Distance individualism, masculinity, Uncertainty Avoidance, long-term orientation and indulgence, added later, which is still used to this date to compare cultures in countries. According to Oracle, a world leading software as a sales (SaaS) company, cross-cultural core competence is at the crux of today’s sustainable competitive advantage in the market (Hummel, 2012).

Overall, sustainability and green innovation are important for political institutions and are becoming a priority for long term prosperity. The cultural dimensions have been gathered to investigate how certain aspects of culture may influence a firm’s behavior to implement GIS.

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White (2019) found that high collectivism relates positively to the rate of CSR activities in the African region. Karaibrahimoglu, et al. (2016) found that companies in countries representing lower Power Distance, lower Uncertainty Avoidance and higher collectivism focus more on reporting standards of ethical behaviours and CSR activities. Decision making is done by the more powerful members of the society as they have an unequally distributed power over other members of the society (Mihet, 2012). Furthermore, the idea of growth has an inherent risk component to it. As business ventures to pursue economic development risk are naturally part of the process. Lower Uncertainty Avoidance leads to higher R&D efforts and higher economic performance. Decisions that are made will in this case have an impact on the rate of green innovations (Mihet, 2012). The authors cited above find several relationships on how low Uncertainty Avoidance are a key part of how companies behave, whether it is engaging in CSR activities or adhering to local rules and regulations. Due to the dominance of these 2 dimensions, Power Distance and Uncertainty Avoidance have been selected as the key cultural dimensions to be analysed with regards to green innovations. Therefore, this research aims to answer the main research question:

“How does country’s Culture impact the rate of GIS? Will Power Distance and Uncertainty Avoidance positively impact the rate of green innovations?”

When it comes to companies, apart from country Culture it is important to take a look at characteristics on a firm-level that may influence decision making. Corporate governance is a term that signifies the set of rules, practices and processes within a firm (Chen, Corporate Governance, 2020). This term defines how decision making is managed and implemented in companies. Certain firm level characteristics such as Female Prevalence, Firm Age, Management Experience, and other factors may have an influence on how decisions are made within a company. Female Prevalence, Firm Age, and Management Experience will be

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analyzed to see whether they moderate the effect of cultural dimensions of Power Distance and Uncertainty Avoidance on GIS. Seierstad et al. (2017) indicate that gender diversity and quotas are becoming heavily enforced by governments and companies in Europe as there are numerous studies showing that having a gender balanced management board or parliament has an impact on performance, behavior and adhering to rules. Liao, et. al (2018) conclude that firms with a larger board size, more female directors, and separation of CEO and chairman positions are more likely to engage in CSR assurance. This is also consistent with the influence of gender diverse boards understanding CSR activities. Saona et al. (2019) find that gender diversity confirms the benefits of having a balanced board in terms of gender diversity in financial performance.

An equilibrated board tends to mitigate earnings management practices, reinforcing the value of the laws passed in recent decades (Liao, Lin, & Zhang , 2018). The current research would suggest that that companies with a balanced gender diversity will be more likely to engage in green innovations. Therefore, the research will aim to answer the following questions:

“Does gender diversity in the management board positively moderate the effect of Culture on Green Patents?

Firm Age will indicate whether companies that have been around for a longer time will pursue sustainable practices more or less than younger companies. Coad (2007) finds that companies are less capable to innovate and change firm’s behavior as they growth with assets, people, machinery and other factors that slow down processes internally. This could potentially show that other aspects within firm level characteristics have a stronger impact on the rate of implementing green innovations. Kakanda et al. (2017) find that more experienced companies

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are more likely to stick to its values and traditions and to innovate less. Therefore, the research will aim to answer the following questions:

“Does Firm Age negatively moderate the effect of Culture on Green Patents?

Furthermore, Management Experience will aid in helping to understand whether less or more experienced directors and board members will be more likely to implement GIS.

Dahlmann et al. (2020) conclude that both younger and older management boards respond to environmental performance by engaging in CSR activities, but for different reasons. Younger management boards follow social trends of being more sustainable and competitive as a business, on the other hand, more experienced management boards want to leave behind a legacy and return something back to the society. Furthermore, there is limited research on how Management Experience influence the rate of CSR activities or GIS. Political pressures, rules and regulations as well as social trends could have an important impact on how different management boards respond to green activities and green innovations (Kumar, 2020).

Therefore, another important question to be answered is:

“Does Management Experience negatively moderate the effect of Culture on Green Patents?

Overall, there is limited research into what are the antecedents of GIS, that focus on implementing sustainable solutions within a business. This research aims to identify whether country Culture and firm level characteristics have an impact on firm’s decision to implement GIS. As implementing green innovations is a firm’s behavior to change the processes internally, literature on firm’s behavior and decision will help to bring additional insights into what are the possible factors impacting green activities and green innovation.

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The next chapter, literature review will present the findings of currently literature on constructs of GIS, Culture, firm level characteristics and the relationship amongst all of them in relation to the available research and findings. Moreover, the literature review will help build arguments based on mechanisms found in prior academic research, and hypothesis that will be indicated in the 3rd chapter of theoretical framework. After defining dependent, independent, moderating and control variables in chapter 4, the results of the hypothesis testing and several models will shed light into how the previously mentioned constructs relate to each other.

Finally, discussion and conclusion will provide a general overview of all the findings followed by limitations of the current research and academic as well as managerial implications for scholars and businesses.

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2. Literature Review

The following part of literature review will describe and identify the constructs relevant for this research. It is important to shed light on how exactly these constructs have been framed by academics and authors to get a better understanding on what are the current literature streams and findings relevant for each of the sub sections. The enhanced literature review aims to highlight the available research, findings, relationships and relevance towards this topic. The reader should have a clear understanding of what has been found and concluded from numerous sources. The information will further be developed to create a theoretical foundation which will create a conceptual framework on how these constructs are related and what are the mechanisms amongst one another.

2.1 Green Innovation Strategy

(G

IS)

The currently available literature runs into different research streams. “Green innovation refers to an innovation that puts emphasis on the reduction of waste, pollution prevention and environmental management system implementation” (Eiadat et al, 2008, pp.

131). Moreover, Reuvers (2015) contributes to this definition, stating that green innovations have an impact on production, assimilation or exploitation of a product, production process, service or management or business method that is novel to the organization and which results, throughout its life cycle, in a reduction of environmental risk, pollution and other negative impacts of resources use, including energy use, compared to relevant alternatives. These are the sustainable pproducts (for example: solar energy)and services that are implemented in the firm. This can be in the form of transitioning the energy usage for a product or service or using pollution-control technology to reduce the footprint of the company.

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There is considerate amount of information available on GIS with regards to companies, organizations and government, specifically focusing on how we can use these innovations for long term sustainability and growth in the society (Steger, 2005). More research is made into what are current practices of organizations and governments in the field of CSR and environmental management, the specific actions that have been implemented to become more sustainable, or greener. Further research streams, such as Song (2018), look closer into how GIS can become the identity of a company, specifically how companies develop a sustainable brand image due to their contributions to green growth.

Millan (2017) states that, GIS comprises all type of innovations that contribute to the creation of key products, services, or processes to reduce the harm, impact, and deterioration of the environment at the same time that optimizes the use of natural resources. Such type of innovation develops a critical role these days because it channels an appropriate use of the natural resources to improve the human well-being in modern society. Moreover, the creation and incorporation of changes in products and production processes could contribute to sustainable development. Leal-Millan, et. al (2018) states that GIS should be comprehended as strategic choices of companies towards a sustainable future.

The majority of the research done into GIS is labelling and defining this as a relatively new term, how it is relevant towards the sustainability goals as well as what are the implications of GIS on the business in terms of return on investment and profit, as well as indicating that GIS is a consequence of a firm’s behavior to implementing green strategies. Overall, GIS refers to activities that reduce the ecological footprint of a company by means of pollution reduction, resource allocation, technology advancements and other forms of transforming value chain within a business.

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2.2 Culture

National culture is defined by Hofstede (2001) as “the collective programming of the mind which distinguishes the members of one group or category of people from another”.

Hofstede has further defined 6 elements of national culture; Power Distance Index (PDI), Individualism versus Collectivism (IDV), Masculinity versus Feminity (MAS), Uncertainty Avoidance (UAI), Long Term Orientation versus Short Term Orientation (LTO) and Indulgence versus Restraint (IVR) (Hofstede, Compare Countries, 1973). These terms have been used by Hofstede to compare different cultural dimension amongst countries to get a better understanding of cultural differences in the business world and will be briefly identified below.

Power Distance indicates the degree to which the less powerful members of a society accept and expect that power is distributed unequally. People in societies exhibiting a large degree of Power Distance accept a hierarchical order in which everybody has a place, and which needs no further justification. In societies with low Power Distance, people strive to equalize the distribution of power and demand justification for inequalities of power (Hofstede, Compare Countries, 1973).

Individualism can be defined as a preference for a loosely knit social framework in which individuals are expected to take care of only themselves and their immediate families.

On the other hand, collectivism, represents 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, Compare Countries, 1973).

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Masculinity indicates a preference in society for achievement, heroism, assertiveness, and material rewards for success and competitiveness. Meanwhile femininity, stands for a preference for cooperation, modesty, caring for the weak and quality of life. Society at large is more consensus oriented (Hofstede, Compare Countries, 1973).

Uncertainty Avoidance indicates how members of the society are uncomfortable with uncertainty and ambiguity and how they deal with the fact that the future is unknown (Hofstede, Compare Countries, 1973).

When it comes to long term orientation and short-term orientation society has to maintain some links with its own past while dealing with the challenges of the present and the future. Societies prioritize these two existential goals differently. Societies who score low on this dimension, for example, prefer to maintain time-honored traditions and norms while viewing societal change with suspicion. Those with a culture which scores high, on the other hand, take a more pragmatic approach: they encourage thrift and efforts in modern education as a way to prepare for the future (Hofstede, Compare Countries, 1973).

Indulgence stands for a society that allows relatively free gratification of basic and natural human drives related to enjoying life and having fun. Restraint stands for a society that suppresses gratification of needs and regulates it by means of strict social norms (Hofstede, Compare Countries, 1973).

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Contributing to Hofstede’s definition, is the norms, behaviors, beliefs, customs, and values shared by the population of a sovereign nation. Specific characteristics such as language, religion, ethnic and racial identity, cultural history and traditions (IGI Global, 2020). According to Oliver (2011), any exploration of national culture has to be approached with caution. It is only too easy to fall into the trap of identifying stereotypes or caricatures. It is a set of factors such as politics, people, traditions and others that build up national culture. Furthermore, regardless of how culture is defined; organizations today are likely to conduct business internationally and multinational enterprises may face unexpected challenges in managing information (Oliver, 2011).

Management literature has identified Power Distance and Uncertainty Avoidance as main cultural dimensions that dominate research streams with regards to CSR engagement, firm behavior and firm performance and their relationship with GIS. As seen in the research of (Azmat & Zutshi, 2012), (Cetenak & Cingoz, 2017), (Li & Karakowsky , 2005), and other authors who have identified who have found that both Power Distance and Uncertainty Avoidance have an impact on the rate of innovation, engaging in green activities as well as rate of innovation, these two cultural dimensions have been selected as key constructs and will be further researched with relationship to other constructs in the following subchapters.

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2.3 Impact of Culture on Green Innovation Strategies (GIS)

Culture is an important term for research into how businesses operate and make decisions (Muthusamy & Che Adnan, 2020).With increased level of globalization of firms internationally, decision making can become strongly undermined by differences in culture. To get a better understanding of how national culture contributes to GIS and implementation of sustainable products into a firm it is crucial to look into past and recent research in this topic.

There is extensive research done into how culture contributes to firm behaviour and firm performance. GIS is the implementation of sustainable patents within goods and services of a company. Therefore, we can consider GIS as a firm behaviour, which is a topic that has been researched by scholars over the past decades. For instance, Li et al. (2005) found that in the context of government policy, companies in certain East Asian countries adhere to regulations by adjusting their behaviour. These countries scored higher on Power Distance and lower on Uncertainty Avoidance. Li et al. (2005) define Power Distance as the extent to which the members of a society accept that power in institutions and organizations is distributed unequally. Uncertainty Avoidance can be defined as a measure of the degree to which the members of a society feel uncomfortable with uncertainty and maintain institutions protecting conformity. Low Power Distance and Uncertainty Avoidance are consistent with higher level of risk taking, flexibility, and aggressively searching for new ventures, markets and opportunities. Mihet (2012) further contribute to the literature of Power Distance and Uncertainty Avoidance, stating that Power Distance represents the degree on how power is distributed amongst the society. Power Distance is a key dimension as power is important in making decisions in a country or a company. It indicates the extent to which less powerful members of a society accept and expect power distributed unequally. High Power Distance

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systems are typically characterized by authoritarian political systems, governed by elites. These systems tend to innovate less and the growth in the long run is smaller. Mihet (2012) from the International Monetary Fund concluded that in a data set of 50,000 companies across 51 countries showed a relationship between risk-taking firm behaviour in countries with low uncertainty aversion, low tolerance for hierarchical relationships, and high individualism.

Additionally, (Karaibrahimoglu & Cangarli, 2016) find that low Power Distance and higher collectivism contribute to higher reporting standards of ethical behaviour and CSR activities.

In societies with lower Power Distance, people are more sensitive to ethical issues due to a strong belief in the protection of the rights of all people. On the other hand, high Power Distance, contributes to inequality in distribution of resources and can be characterized by a relatively low regard for ethics and engagement in CSR activities. (Karaibrahimoglu &

Cangarli, 2016). Cetenak et. al (2017) find that in 20 countries, low Power Distance and lower Uncertainty Avoidance have a significant impact on financial decision making such as research and development, cutting costs or expanding as a business.

Currently, the research streams on GIS are rather focused on how GIS may help in a sustainable development of our society to address to global climate risk (United Nations, 2020).There is limited research on how national culture acts as an antecedent to GIS. However, CSR as a construct that has been researched earlier than GIS, there are some insights that previous literature can contribute towards the framework of how culture impacts rate of implementing GIS. White et al. (2019) analyzes how culture and infrastructure influences CSR in Kuwait. Kuwaiti cultural values as well as country’s infrastructure positively relate to CSR activities in the region due collectivism this is due to the fact that Kuwait being a collectivistic country, communities want to do social deeds for one another and grow a community that is more sustainable and promotes social causes. In this research we can look at collectivism as a cultural dimension that serves as a mechanism to implementing CSR activities. More precisely,

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the findings here can indicate that societies with higher level of collectivism are a source or way of getting towards CSR practices. Furthermore, since companies in the country are proud to do business in the country (due to collectivism), social norms require enterprises to give back to a social cause (White & Alkandari, 2019). Azmat & Zutshi (2012) analyze the impact of home country culture on CSR of entrepreneurs from Sri Lanka in Australia.

The practical implications showed that country culture has an effect on the perception of CSR. The entrepreneurs had strong bonds to norms from Sri Lanka but have adjusted themselves to the cultural values in Australia. The entrepreneurs have shown a strong resemblance to home-country norms and trends as a higher level of collectivism. In this instance we can observe that collectivism and the doing good for community can become a mechanism on culture impacts behavior of individuals and organizations. While neither of the articles show how a clear conclusion to how culture impacts sustainability and CSR, research suggests that culture may have an impact on how people view sustainability and GIS. Other studies that have also researched topic of GIS found unclear relations between culture and how it may impact sustainability and GIS.

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2.4 Gender diversity, Firm Age, Management Experience, and Firm Behaviour

Specific firm characteristics may have an impact on how business innovate and engage in GIS. Research from Liao et al. (2018), Saona et al. (2018), Adusei et al. (2017) and others find that gender diversity, as well as financial performance or characteristics of the job board may have an impact on CSR engagement and adhering to sustainable norms and trends. This information can be source of information on how firm level characteristics can impact the implementation of GIS. For instance, Liao, et. al (2018) conclude that firms with a larger board size, more female directors, and separation of CEO and chairman positions are more likely to engage in CSR assurance. Evidence shows that a more gender balanced board is more likely to identify benefits of CSR and engaging in CSR activities. Females represented in the board are more likely to prioritize strategy over competitiveness in the market. This is also consistent with the influence of gender diverse boards understanding CSR activities.

Gender diversity also influences the CSR assurance provider choice. Saona et al.

(2018) find that gender diversity in confirm the benefits of having a balanced board in terms of gender diversity. An equilibrated board tends to mitigate earnings management practices, reinforcing the value of the laws passed in recent decades in Europe. More balanced management boards are more likely to present CSR initiatives as strategically important rather than male dominated boards. Interestingly, Adusei et al. (2017) find that gender diversity positively relates to firm performance up to the threshold of 50% gender diversity in the management board and above 50% and more dominated by female management boards, companies show a decrease in financial performance. Moreover, Moreno-Gomez et al. (2018) find that in 54 companies in Colombia there is a positive relationship between gender diversity

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and business performance. Yu et al. (2016) conclude that, male leaders in the management board positively relate firm competitiveness aggressiveness in the market and female leaders focus on long term growth and strategy.

Another research suggests that board size, board composition, and risk management disclosure have a significant positive effect on the performance, board experience has negative relationship on firm’s performance (Kakanda, Salim, & Chandren, 2017). Practically speaking, a management board of directors that are more experienced and older have a negative impact on the business performance, as they are less likely to innovate and to remain competitive in the market. Dahlmann et al. (2020) conclude that both younger and older management boards respond to environmental performance, however older management boards react as physical and regulatory climate risk, such as fines and regulations and younger management boards engage more towards sustainability as they see opportunities that that arise connected to climate risks.

While factors such as gender, board size and management structure have been studied, there is still limited available research on how Firm Age and Management Experience contributes to the rate of green innovation, GIS. The potential findings can become an important theoretical addition to this research as it may shed more light into how firm level characteristics may influence GIS.

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Management literature provides consistent findings on how gender diversity positively contributes to firm’s performance and engagement in CSR activities. Literature into Firm Age, and Management Experience are rather limited, authors state that both less and more experienced companies and management boards are likely to engage in green innovation but due to different reasons, whether it is leaving a legacy behind or keeping up with the latest norms and trends. Noordin (2014) finds that there are mixed results between firm’s experience and firms’ performance as it is very difficult to generalize across all companies and industries.

Companies tend to have more capital as they are more experienced but at the same time they have difficulties to innovate as they get bigger and it becomes more difficult to grow and make decisions quickly. Coad (2007) also find that companies are less capable to innovate and change firm’s behavior as they growth with assets, people, machinery and other factors that slow down processes internally.

In conclusion, we see that certain aspects of a management board have an influence on firm’s behavior and firm’s performance. As previously mentioned, GIS can be interpreted as a firm’s behavior during which a company decides to implement new ways of conducting business. Companies have to adapt to stay competitive and at the moment it seems that sustainability and CSR practices are becoming increasingly important and demanded by organizations, governments and the society.

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3. Theoretical Framework

This section will look deeper into how the current literature can assist with building arguments on how Culture has an impact on companies implementing GIS. Firstly, Arguments will be presented on how Power Distance and Uncertainty Avoidance impacts the rate of GIS.

Secondly, arguments will look into how Female Prevalence, Firm Age, and Management Experience moderate the relationship between Power Distance & Uncertainty Avoidance and GIS. The following chapter will present arguments based on the chapter of literature review, identify hypothesis as well as the overall theoretical model that will be further tested in the following chapters.

3.1 Impact of Culture on Green Innovation Strategies (GIS)

The literature on how culture can impact firm behaviour demonstrates how culture can impact decision making in a company (Li & Karakowsky , 2005). GIS is a firm’s behaviour that results in the company implementing sustainable solutions to its products or services.

Power Distance relates to the distribution of power and decision making. High Power Distance indicates that there is a great respect for the superior in a business environment, and that the decision making is done at the top. On the contrary, low Uncertainty Avoidance indicates that in the society, members feel comfortable with an unstructured situations and interchangeable environments. Decisions are made freely and without any constraints with respect to the futuree (Li & Karakowsky , 2005). Low Power Distance and low Uncertainty Avoidance are linked to higher risk taking, flexibility, innovation and searching for new opportunities (Li &

Karakowsky , 2005). Contributing to that, Mihet (2012) concludes that societies with low Power Distance are more innovative and show a greater growth in the long run. On the other hand, high Power Distance is typically characterized by authoritarian systems where only elites

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make the decision making, they innovate less and stagnate. Naturally, with growth and venturing to new markets, risk is bound to come along the way. Li et al. (2005) and Mihet (2012) find that as companies experiences uncertainty and risk in the long run, they are more likely to continue innovating and become more comfortable with the uncertainty of the near future, representing a low Uncertainty Avoidance. Karaibranhimoglu et al. (2016) found a relationship between low Power Distance positively contributing to ethical reporting and engaging in CSR activities, the authors find a strong relationship where collectivism and Power Distance contributes to CSR engagement.

Boubakri et al. (2017) find lower Power Distance and lower Uncertainty Avoidance to impact firm’s behaviour and performance. The mechanism shows that decisions are made throughout the whole organization and that lower Uncertainty Avoidance is also positively contributing to affecting firm behaviour. As companies aim to venture further in their business, they experience risk and uncertainty. Furthermore, there is extensive research in organizational culture on how companies with low hierarchy and Power Distance positively impact the rate of firms behaviour, such findings were present in the research of Ngo (2008), Uzkurt et al.

(2013) and O’Reilly et al. (2014). While this research implies results from organizational culture rather than national culture, these papers suggest that lower hierarchy (Power Distance) have the strongest impact on firm’s decision making and firm’s behaviour.

Stemming from the research of (Mihet, 2012), (Li & Karakowsky , 2005), (Karaibrahimoglu & Cangarli, 2016), and others low Power Distance and low Uncertainty Avoidance contributes to ethical reporting, engagement in CSR activities, firm’s innovation and being more active in green innovations. The mechanism of the authors shows that low Power Distance correlates to ethical behaviour, reporting standards and adhering to laws and

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regulations as well as higher rate of innovation and long-term growth. Furthermore, low Uncertainty Avoidance indicates that as companies venture to new markets and products and seek growth opportunities risk and uncertainty of the foreseeable future are a natural part of the process. Companies as well as members of the society become more comfortable with situations where there is less clarity, scoring lower on Uncertainty Avoidance.

Hence, Power Distance and Uncertainty Avoidance will negatively impact the rate of GIS as the rate of these dimensions will increase. As companies score higher on these independent variables, they will negatively impact the rate of the dependent variable. Based, on the argument above proposed hypotheses below are:

H1 a): (High) Power Distance will negatively impact Green Patents (GIS)

H1 b): (High) Uncertainty Avoidance will negatively impact Green Patents (GIS)

Stemming from the above-mentioned theory lower Power Distance and lower Uncertainty Avoidance are more likely to result in companies engaging in CSR activities, innovation, risk taking and changing firm behaviour. Societies that score lower on Power Distance tend to innovate and risk more as decisions are made by the masse and not by the elites or an autocratic system (Cetenak & Cingoz, 2017). Naturally, with higher rate of innovation, as societies venture for new opportunities risk is part of the growth. With experience, the society becomes more comfortable with risk taking and uncertainty of the future. Therefore, low Power Distance and Uncertainty avoidance predict a higher rate of GIS, as a part of innovation and firm behaviour consistent with current literature. As the dimensions of Power Distance and Uncertainty rise, companies will innovate and implement less GIS.

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3.2.1 Moderating Impact of Female Prevalence

We can get a better understanding of how decisions are made by looking into firm level characteristics. Female Prevalence positively impacts firm’s behavior in identifying benefits of CSR practices and engaging in CSR activities (Liao, Lin, & Zhang , 2018). Positive relationship between gender diversity and firm’s behavior to adhere to local laws has been identified by Saona et al. (2019). Further positive benefits have been found by Adusei et al.

(2017) in the financial performance of companies that are gender diverse in their management board. The authors find that while male leaders in the board are focusing on aggressive competitiveness in the market (Adusei, Akomea, Poku, & McMillan, 2017), female leaders are more likely to engage in long term growth, strategy and internal initiatives. Furthermore, more gender balanced boards prioritize (Liao, Lin, & Zhang , 2018) CSR activities and ethical reporting, female representatives focus more on long term prosperity and sustainable way of leading a business rather than short term financial benefits and competitive position in the market.

Based on the information above and the positive relationship between gender diversity in the management board and several impacts in firm’s behavior, engaging in CSR activities as well as financial performance, the argument proposed is that companies with diverse gender representation will show positive moderating impact on how culture impacts rate of GIS. More specifically, the relationship in the framework of culture and GIS will be strengthened in companies that that show a higher gender diversity. This is consistent in line with the mechanism of (Adusei, Akomea, Poku, & McMillan, 2017), (Liao, Lin, & Zhang , 2018), and other authors who have suggested that having female leaders in the management board leads to more engagement in CSR activities as they prioritize long term growth and sustainability.

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The available research suggests that having a gender balanced board with female leaders being represented has positive impacts on firm behavior, firm performance, CSR engagement, CSR assurance and ethical reporting (Saona, Muro, San Martin, & Baier-Fuentes, 2019). Therefore, as more female will be represented in the companies, the relationship between Power Distance and Uncertainty Avoidance will be positively moderated and will increase the rate of GIS. Hence, the proposed hypothesis is:

H2 a): Female Prevalence will positively moderate Power Distance’s effect on GIS

H2 b): Female Prevalence will positively moderate Uncertainty Avoidance’s effect on GIS

Having a gender balanced management board has significant benefits on firm’s financial performance as well as CSR engagement (Liao, Lin, & Zhang , 2018). Above mentioned researchers find positive relationship with female executives being represented in the management board. This is due to different motives of female leaders. While male leaders tend to focus on short term profit and competitiveness in the market, female leaders tend to focus on long term growth and strategy (Liao, Lin, & Zhang , 2018). Therefore, companies with more female leaders represented in the management board will be more likely in positively moderating and strengthening the relationship between the key independent variables of Culture and GIS.

3.2.2 Moderating Impact of Firm Age

Firm Age is the second firm level characteristic. How long a business has been operating can potentially determine the experience, capital and resources that are available for companies to dedicate to implement green innovations by innovating their line of products and

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services. Noordin (2014) concludes that there are rather mixed findings when it comes to the importance of firm’s experience, especially several challenges with generalizing implications across different companies and industries. Large companies that have capital, resources and experience in the industry are restrained by their size in making decisions quicker, becoming innovative and performing well in the long run. Coad et al. (2007) states that companies have several challenges and are less capable to innovate due to the sheer amount of capital and resources available, decision making takes longer due to internal communication and processes, this often creates inefficiencies and lagging performance. (Coad, Segarra, & Teurel, 2016) later finds that Firm Age negatively impacts the rate of innovation. This is due to the fact that older companies are more likely to stick to its original values and will not innovate. On the other hand, less experienced companies that are younger are more likely to undertake riskier innovation and are more oriented towards employee growth as well as business growth. Hence, the hypotheses are as followed:

H3 a): Firm’s age will negative moderate Power Distances’ effect on GIS

H3 b): Firm’s age will negative moderate Uncertainty Avoidance’s effect on GIS

Firms that have been around for a longer period of time are less likely to innovate and to stick to their traditions and ways of doing business (Coad, Segarra, & Teruel, 2007). As per available research, companies that have been around for a longer time will be negatively moderate the relationship between Culture and GIS.

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3.2.3 Moderating Impact of Management Experience

Management Experience, in the form of average age represented in the board, may also influence the mechanism between Power Distance and Uncertainty Avoidance and their relationship with GIS. Kakanda et al. (2017) found that board experience has negative relationship with firm’s performance and decision making. Companies that had a higher average age in the management board shown had a negative impact on the financial performance and changing firm behavior. In practice, management boards that are more experienced and are represented with higher age average show a resilience to changing behavior and rather sticking with established norms, rules and traditions within the company.

Dahlmann et al. (2020) show that both younger and older management board conclude a positive impact on environmental issues, older management boards are motivated to avoid regulations and fines and younger management boards look for potential opportunities. In this instance, older management boards are more likely to engage in environmental issues.

Contributing to that, there was a positive relationship between management boards experience and environmental activities, the mechanism shows that more experienced management boards and executives want to leave a legacy behind (Kumar, 2020). Furthermore, Aziz (2018) found that younger directors are more likely to implement quicker decisions and solutions as well as responding to social issues. Companies are hiring less experienced directors in their management board to bring a fresh perspective, to help understand younger customers and bring a newly found connection.

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Stemming from the available literature, the argument proposes that it is more likely that younger management boards are more likely to innovate and implement green innovations.

This is due to the fact that younger management boards are more likely to innovate quicker, respond to trends and norms as well as have an interest climate risks. Hence, more experienced and older management boards will have a negative moderating impact between Culture on GIS.

Companies that are governed by older management boards are going weaken the relationship between Power Distance and Uncertainty Avoidance and will show negative impacts on the rate of GIS. The effect between Power Distance, Uncertainty Avoidance and GIS will therefore be strengthened as younger and less experienced management boards will engage into environmental issues more. The proposed hypotheses are:

H5 a): Management Experience will negatively moderate Power Distance’s effect on GIS H5b): Management Experience will negatively moderate Uncertainty Avoidance’s effect on GIS

Younger management boards are more likely to innovate, change firm behavior and partake in risk taking (Aziz, 2018). In the context of Power Distance and Uncertainty Avoidance, as the age average of the management board will increase, Management Experience will negatively moderate the relationship and companies will be less likely to implement GIS.

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3.3 Conceptual Framework

Figure 1 – Conceptual Framework

As mentioned above country Culture dimensions of Power Distance and Uncertainty Avoidance will be measured to identify how they impact a firm’s decision to change behavior and implement GIS. How these dimensions rank on Hofstede’s insights will be compared with the rate of Green Patents implemented of companies. The moderating variable of Female Prevalence, Firm Age, and Management Experience will be analyzed to with regards to the rate of GIS. Based on the literature review and hypothesis building, gender diversity in the form of Female Prevalence will positively moderate the impact of Power Distance and Uncertainty Avoidance. On the other hand, Firm Age and Management Experience indicates a negative moderation of cultural dimensions on the rate of GIS.

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4 Method

The methodology will shed light into the data collection and sampling of this research, informing the reader about the background of the data, the reasoning behind using this information as well as how it will be used to support the theoretical framework and conceptual model displayed in Chapter 3.

4.1 Data Sampling and Collection

The sample of this study is composed from information on Green Patents (GIS) implemented by 1368 companies (n=1368) and was collected as the core outcome of this research. The 1368 firms are represented by top s2000 R&D investors worldwide over the time period 2010-2016. The sample is a result of combining EC-JRC/OECD COR&DIP˝ databases.

The top 2000 R&D investors were listed in three surveys taken in the years of 2012, then 2014 and lastly 2016. Out of those 2000 companies there were 1368 that were present in all 3 surveys throughout the years, creating a list of most innovative companies from 2010-2016. The information on patents is gathered from the JRC Directorate B – Growth and Innovation, the OECD Directorate for Science, Technology and Innovation (STI) and the European Commission and is based on information from the US Patent and Trademark Office (USPTO), the EPO’s Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) and the European Union Intellectual Property Office (EUIPO) (Dernis, et al., 2019). The sample consists of companies based in; Asia-Pacific (34,3%), North America (32,6%), Europe (32,5%), South America (0,6%) and Africa (0,1%).

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Data collection on cultural dimensions has been carried out on Hofstede’s Insights (2020) website. This is a database that provides information on all 6 cultural dimensions identified by Hofstede per country. Moreover, databases such as Orbis (2020), Factset (2020), Compustat (2020) and NexusUni (2020) have been used to collect specific information on companies that include management board experience, in the form of average age as well as gender diversity, how many females and males are represented in the management board of the companies from the data sets.

All of these databases are provided by the University of Amsterdam as a source of information on financial performance as well as firm information that companies share. The use of multiple databases will be implemented to mitigate any issues with a certain company not being registered in a specific database. If there was not available information for a certain company, Orbis, Factset or Compustat would contain more information available.

4.2 Variables

4.2.1 Dependent Variable: Green Patents

The dependent variable for this study is Green_Patents. The rate of GIS and how companies implement green innovations is the core of this research. The purpose is to get a better understanding whether and how do other variables affect GIS in these companies. Patent information on R&D activity and Industrial Property (IP) assets in combination with bibliometric data has been collected to present an overview of the applications of the families of patents and the trademarks filed by the included firms (Dernis et al., 2019).

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The number of patents referring to R&D activities reflected the numerical output of innovation within a firm. Any form of innovation in R&D activities that would satisfy IP requirements was noted as a patent. The patents that enabled the firm to become more sustainable and greener, improving the product chain would be marked as Green_Patents. The numerical output of Green_Patents that have been implemented by the firm in a given year would indicate the amount of GIS, the amount of innovation a company has gone through to become more sustainable by reducing its resources usage. Information on patents has been collected based on EC-JRC/OECD COR&DIP˝ (Dernis, et al., 2019) databases and with the help of International Patent Classification (IPC) (WIPO, 2020) classified into two categories, number of Total_Patents and number of Green_Patents. Bearing in mind that firms have been studied over the period of 2010-2016, meaning that this is a longitudinal study, GIS in the form of Green patents refer to the numerical number corresponding to the company at a time t.

4.2.2 Independent Variable: Power Distance and Uncertainty Avoidance

The key independent variables are Power Distance (PDI) and Uncertainty Avoidance (UAI) as a part of the cultural dimensions. The variable of national culture divided into cultural dimensions have a value of 1-100 (lowest – highest) indicating the degree to which society in a specific country relate towards the dimensions of Power Distance and Uncertainty Avoidance (Hofstede, Compare Countries, 1973). The collected data has been used to indicate the effect of each key independent variable of PDI and UAI in relation with the rate of Green_Patents.

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4.2.3 Moderating variables – Gender Diversity, Firm Age and Management Experience

The variable of gender diversity has been collected by the Orbis database.

Female_Prevalence was computed as the share of females represented in the management board compared to males represented (Bureau van Dijk, 2020). The values have a minimum of 0%, for male dominated management boards, up to 100%, for female dominated management boards.

The next moderating variables in this study are Firm_Age, how long it has been operating and Management_Experience. For Firm_Age, the databases mentioned in the section of sampling and data collection have been used. Firm_Age indicates the experience the company has at a certain time period. The variable was measured by subtracting the year of foundation from the year of observation (Bureau van Dijk, 2020). Forexample, a company founded in 1980, would be noted as 30 years of age in 2010, 31 years in 2011, etc. The variable Management_Experience has been computed as the average of all representatives in the management board. Information on the age of all members of the management board has been collected. Average age was computed from the data collected to represent age average of the overall management board, noted as Management_Experience (Bureau van Dijk, 2020).

4.2.4 Control variables – ROA, Total Assets, R&D and Industry

A control variable is any factor that is controlled or held constant during this research.

Unlike the independent and dependent variables, control variables aren’t a part of the experiment, but they are important because they could affect the outcome (Helmenstine, 2020).

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The first control variable is return on assets, otherwise known as ROA. Return on assets is a profitability ratio that provides how much profit a company is able to generate from its assets. In other words, return on assets (ROA) measures how efficient a company's management is in generating earnings from their economic resources or assets on their balance sheet (Boyte- White, 2020). This control variable takes a look at the financial performance of the company.

The second control variable is Total assets, referred to as Complete_Assets. Similarly, to ROA, total assets is a financial indicator of how big the company is. Total assets refer to the total amount of assets owned by a person or entity (Accounting Tools, 2019). This control variable indicates the firm’s size, how much is owned by the company. Large companies have a bigger capital to invest into sustainability and to innovate (Lopez-Perez, Melerio, & Javier, 2017).

The third control variable is Total_Patents, as a part of R&D. Green_Patents are a part of Total_Patents, it is important to take a look at what is the total number of innovations within a company. This serves as a tool to get information on the complete R&D and innovation activities within a company, not solely relying on the Green_Patents.

The fourth control variable is industry of the companies. ISIC is a standard classification of economic activities arranged so that entities can be classified according to the activity they carry out. The categories of ISIC at the most detailed level (classes) are delineated according to what is, in most countries, the customary combination of activities described in statistical units and considers the relative importance of the activities included in these classes (ILOSTAT, 2020). The industries have been divided into, primary, secondary and tertiary.

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There may be differences between the rate of sustainable development and Green_Patents across industries due to, government policies, social pressures and nature of the industry / sector they are working in (Botero, 2019). This variable has been coded into dummy variables of “Industry Primary”, “Industry Secondary”, and “Industry Tertiary”. When the company was labelled “0” when it was not a part of the industry and “1” when it was a part of the industry.

4.3 Econometric Analysis

For the purpose of this research, SPSS has been utilized as a software to help analyze the results of the data collected. The IBM SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications (IBM, 2020). For the purpose of this study, I use Poisson Regression analysis between the dependent variable, independent variables, moderating variables and control variables. Poisson regression is used to model response variables (Y-values) that are counts. It describes which explanatory variables have a statistically significant effect on the response variable. In other words, it tells me which X-values work on the Y-value. It’s best used for rare events, as these tend to follow a Poisson distribution (as opposed to more common events which tend to be normally distributed) (Statistics, 2020). Poisson regression will be used to identify the relationship between variables’ and their impact on Green_Patents which is a countable numeric outcome variable.

The formula for testing hypotheses between Culture, moderating variables, and GIS are following:

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H1a): Effect of Power Distance on Green_Patents

Green_Patents i,t = β0 + β1 PDI i,t + β2 Female_Prevalencei,t + β3 Firm_Age i,t + β4

Management_Experience i,t + β5 ROA i,t + β6 Complete_Assets i,t-1 + β7 Total_Patents i,t-1

+ β8 Industry dummies i,t + ɛi,t

H1b): Effect of Uncertainty Avoidance on Green_Patents

Green_Patentsi,t = β0 + β1 UAI i,t + β2 Female_Prevalencei,t + β3 Firm_Age i,t + β4

Management_Experience i,t + β5 ROA i,t + β6 Complete_Assets i,t-1 + β7 Total_Patents i,t-1 + β8 Industry dummies i,t + ɛi,t

H2a): Moderating effect of Female_Prevalence between Power Distance and Green_Patents Green_Patentsi,t = β0 + β1 PDI i,t + β2 Female_Prevalencei,t + β3 PDI i,t * Female_Prevalence

i,t4 Firm_Age i,t + β5 Management_Experience i,t + β6 ROA i,t + β7 Complete_Assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,t

H2b): Moderating effect of Female_Prevalence between Uncertainty Avoidance and Green_Patents

Green_Patentsi,t = β0 + β1 UAI i,t + β2 Female_Prevalencei,t + β3 UAI i,t * Female_Prevalence

i,t4 Firm_Age i,t + β5 Management_Experience i,t + β6 ROA i,t + β7 Complete_Assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,t

H3a): Moderating effect of Firm_Age between Power Distance and Green_Patents

Green_Patentsi,t = β0 + β1 PDIi,t + β2 Firm_Agei,t + β3 PDI i,t * Firm_Age i,t + β4

Female_Prevalence + β5 Management_Experience i,t + β6 ROA i,t + β7 complete_assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,

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H3b): Moderating effect of Firm_Age between Uncertainty Avoidance and Green_Patents Green_Patentsi,t = β0 + β1 UAIi,t + β2 Firm_Agei,t + β3 UAI i,t * Firm_Age i,t + β4

Female_Prevalence + β5 Management_Experience i,t + β6 ROA i,t + β7 Complete_Assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,

H4a): Moderating effect of Management_Experience between Power Distance and Green_Patents

Green_Patentsi,t = β0 + β1 PDIi,t + β2 management_experiencei,t + β3 PDI i,t * Management_Experience i,t + β4 Female_Prevalence + β5 Management_Experience i,t + β6

ROA i,t + β7 Complete_Assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,

H4b): Moderating effect of Management_Experience between Uncertainty Avoidance and Green_Patents

Green_Patentsi,t = β0 + β1 UAIi,t + β2 Management_Experiencei,t + β3 UAI i,t * Management_Experience i,t + β4 Female_Prevalence + β5 Management_Experience i,t + β6

ROA i,t + β7 Complete_Assets i,t-1 + β8 Total_Patents i,t-1 + β9 Industry dummies i,t + ɛi,

Figure

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References

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