1
Swen de Wit (S2198002) Master Thesis
MSc BA Strategic Innovation Management MSc International Business & Management
University of Groningen
The influence of stakeholder pressures on the green innovation performance of a company and the difference between the Netherlands and China
Supervisor: Dr. H.J (Rian) Drogendijk Co-Assessor: Dr. P.M.M. de Faria
Word count: 12413
1. Abstract
Nowadays, companies are being pressured to comply with the increasing need for green innovations.
In order to comply with this increasing need for green innovations, companies have to take into
consideration the factors and stakeholder groups which drive green innovation (Weng, Chen and Chen,
2015). Previous studies have shown that stakeholders can influence and foster the growth of green
innovations by companies (Weng et al., 2015). This study proposes to conduct a study building upon
the stakeholder management theory that customer and governmental stakeholder groups influence a
company’s green innovation performance. Furthermore, this paper suggests that there is a difference
between the Netherlands and China in the relationship between customer pressures and
governmental pressures on a company’s green innovation performance. To identify if there is a
difference both the cultural dimensions model and the world governance indicators will be explained
and applied to both China and the Netherlands. After data from the asset4 database has been collected
for 41 Dutch companies and 60 Chinese companies the hypotheses have been tested using a linear
regression analysis and comparative analysis. The results however could not confirm the hypotheses,
but a t-test has confirmed that there is in fact a significant difference between the means of customer
pressures and governmental pressures of China and the Netherlands.
2
2. Introduction
The use of natural resources combined with the rapid economic growth has harmed the environment and it has brought many environmental concerns to light (Weng, et al., 2015). In order to reduce the global carbon emissions and environmental pollution in general, many governments have developed and established environmental regulations, with the sustainable development announcements of the Johannesburg world summit as one of the most prominent examples (Weng et al., 2015). These regulations have not only increased the awareness of environmental management, they even have had a large impact on the way companies conduct their management practices and how these companies compete with one another (Weng et al., 2015). Companies seek to eliminate the problems of environmental pollution by incorporating environmental management practices in their operations.
Practices like green production and green innovation are pursued by companies in increasing numbers (Cheng, 2008). In other words, environmental protection is an important issue for companies that also influences their long-term development of business (Madsen, 2009). Nowadays, in order to conform to the new environmental regulations, firms are engaging in practices like cleaner production and developing ecological friendly product designs in increasing numbers (Wong, 2013). Furthermore, companies also have to increase the branding and environmental images they have if they want to have a change in improving and sustaining their competitive advantages and performances (Weng et al., 2015). This process can also be referred to as “going green” (Weng et al., 2015). In order to meet the increasing need of green innovations companies have to keep in mind the important factors driving green innovation and the stakeholders that can influence this business (Weng et al., 2015). Previous studies have already determined groups of stakeholders that can influence the businesses practices of companies. These groups include governmental regulations, the capabilities of suppliers, customer concerns and even the preferences of the owners of a business (Weng et al., 2015). The same stakeholder groups have also been recognized by other studies as stakeholders that can influence the decision of a firm to adopt more green innovations (Guoyou, Saixing, Chiming, Haitao & Hailiang, 2011).
Thus, previous studies have proven that stakeholders can influence and foster the growth of green
innovations by companies. According to Chen, Shyh-Boa and Chao-Tung (2006), the rise of
international environmental regulations and the increasing popularity of environmental consciousness
of customers have significant impacts on companies. The study conducted by Weng et al. (2015) has
also found that greater pressure from the government contributes significantly towards increasing the
effectiveness of green innovation practices. For this reason customer pressures and governmental
pressures should be actively managed by companies, because involving customer and governmental
stakeholder groups can increase a company’s green innovation performance (Guoyou et al., 2011).
3 This complies with the stakeholder theory, which implies that the success of a company depends on how well the company manages the relationships with key stakeholder groups that might be able to affect the success of the firm (Freeman and Phillips, 2002). Therefore, it is the job of the management of a company to gain the support of these stakeholders, by taking their interests into account, while trying to manage the firms in the most appropriate way to be able to maximize the interests of the relevant stakeholder over time (Freeman and Phillips, 2002). Many studies concerning stakeholder pressures only study and measure the direct relationship of stakeholder pressures on green innovation (Guoyou et al., 2011; Weng et al., 2015). However, Eiadat, Kelly, Roche and Eyadat, (2008) argue that implementations of several independent strategies or practices concerning the environment are associated with managerial interpretations. Thus, the main argument made by Eiadat et al. (2008) is that the same stakeholder pressures can be observed and interpreted in different ways by managers, which in turn will lead to different strategies or practices concerning green innovation.
Furthermore, several studies have only conducted their research concerning the drivers of green innovation in a single country. Thus, the international context is missing and it is difficult to determine whether the results found in these studies are generalizable. The study by Gouyou et al. (2011) only conducts their research based on data from Chinese firms and the study by Chen (2008) only involves data from Taiwanese companies. According to the institutional theory however, the legal environment in which companies operate has a significant influence on a company’s behaviour and structure (DiMaggio & Powell, 1983). DiMaggio and Powell (1983) argue that a rationalized system of contract law requires companies to exercise controls to fulfil legal commitments. Furthermore, DiMaggio and Powell (1983) state that legal commitments like annual reports and financial reporting which ensure eligibility for federal contracts also shape organizations in similar ways. Furthermore, Hofstede and de Mooij (2010) state that the culture of countries can be distinguished based on a model that includes five dimensions. As mentioned earlier governmental and customer pressures are known to influence green innovation outcomes for companies (Weng et al., 2015). Because the institutional environment of companies may influence the way managers of companies interpret stakeholder pressures it is interesting to investigate whether different institutional and cultural environments, thus different governmental and customer pressures, have different outcomes on the performance of companies concerning green innovation. Because this might help companies and future research in determining and understanding drivers of green innovation. This study will focus on the Netherlands and China, because these countries exhibit large differences in institutions and culture between each other.
Therefore, this study will investigate whether a significant difference in outcomes can be found
between the Netherlands and China.
4 Therefore, I propose to investigate in this study whether governmental pressures and customer pressures influence a company’s green innovation performance. And in more detail I propose to investigate if differences in the institutional and cultural environment of companies, thus differences in governmental and customer pressures, lead to a different outcome on a company’s green innovation performance. In order to be able to draw a conclusion concerning the difference in influences of stakeholders in different cultures and institutional environments, this study will focus on the Netherlands and China. The reason for the choosing the Netherlands and China is that these countries exhibit large institutional and cultural differences among each other. Therefore, the question asked in this study is:
Do stakeholder pressures (customer and governmental) influence a company’s green innovation performance and is there a significant difference between the Netherlands and China in the influence of stakeholder pressures on green innovation?
This question is particularly relevant in this age, because green innovations are becoming more and more important. Because, of the severe environmental deterioration green innovation has received more attention than before and scholars now see it as a critical way for firms to obtain environmental sustainability (Guoyou et al., 2001). Besides this several studies (Guoyou et al., 2011; Weng et al., 2015) have identified that stakeholder pressures have a positive influence on the green innovation performance of companies, however these studies have only conducted their research in a single country context. Therefore, it is not clear whether these results are generalizable and if there are differences between countries and cultures. For this reason, it is relevant and interesting to investigate whether similar results can be found in different countries and if differences can be identified between countries/cultures. Furthermore, this study also holds relevant information for managers. Because this study will broaden the field of knowledge concerning stakeholder pressures by including the influences of culture and governance.
This paper will continue as follows. First, the theoretical framework will be presented. Discussing the stakeholder theory, green innovation, the institutional theory and informal and formal institutions.
Following from this review, hypotheses will be created and the conceptual framework will be drawn.
After this the methodology used in this paper will be presented, which will be followed by the results
that are found after the data analysis. Finally, the results including managerial implications and
suggestions for future research will be discussed after which a conclusion will be presented.
5
3. Literature review
3.1 Stakeholder theory
In this section a brief summary of the most important aspects of the stakeholder theory will be provided. The stakeholder theory consists out of four central theses (Donaldson and Preston, 1995).
The first theses states that the stakeholder theory presents a model, which describes the nature of a corporation. According to Donaldson and Preston (1995) this theses describes a corporation as a combination of competitive and cooperative interests. The second theses states that the stakeholder theory is instrumental. Which means that the stakeholder theory is a framework, which can be used to examine the connections between the stakeholder management of a company and the achievement of several corporate goals or performance goals (Donaldson and Preston, 1995). The third theses argues that the stakeholder theory is normative in nature and includes the acceptance of two ideas.
The first idea suggests that stakeholders are groups which have legitimate interests in a company and that stakeholders should be identified by the interest they have in a company and not by the interest a company has in the stakeholder groups (Donaldson and Preston, 1995). The second idea suggests that all stakeholder groups should be taken into consideration whether or not they can improve the interests of other groups such as shareholders. The final theses states that stakeholder management requires the inclusion of all legitimate interests of all appropriate stakeholders, this includes not only managers or others influencing corporate policies but also shareowners, the government, customers and other stakeholder groups (Donaldson and Preston, 1995).
Thus, the main idea of the stakeholder theory is that there are multiple groups that have a stake in a
company, such as governments, employees, customers, investors and financial companies (Lloret,
2015). These stakeholders can create pressures on a company with the intention to make the company
act more according to the stakeholders’ interest (Lloret, 2015). Furthermore, stakeholders can provide
a company with resources such as labour, supplies, information. And finally, stakeholders can impose
costs on a company through direct or indirect pressure from non-governmental organizations, media
and neighbours (Lloret, 2015). Thus, the success of a company depends on how well the company
manages the relationships with key stakeholder groups that might be able to affect the success of the
firm (Freeman and Phillips, 2002). Stakeholder management involves taking deliberate actions to
manage stakeholder concerns. While at the same time trying to pursue company objectives and those
of employees, because sustainable competitive operations require human resources to conform to the
company’s strategy (Lloret, 2015). All in all, the stakeholder management approach needs direct and
indirect relations between stakeholder groups and companies to find non-market strategies to
generate value (Lloret, 2015).
6
3.2 Green Innovation
Thus, stakeholder groups can pressure companies to make the company act more according to the interests of the stakeholder. And as stated earlier green innovation is becoming more and more important nowadays. Because of the severe environmental deterioration this green innovation is receiving more attention than before and it is seen by scholars as a critical way for firms to obtain environmental sustainability (Qi et al., 2010). For this reason, stakeholder pressures concerning green innovations will become increasingly relevant for companies nowadays. This relevance has already been identified by previous research, which have found multiple drivers of green innovation, with stakeholders being one of them. However, the stakeholders’ pressures will all have a different influence on the decision of a firm to pursue a green innovation strategy (Guoyou et al., 2011).
According to Guoyou et al. (2011) these stakeholders include regulation stakeholders, customers, investors and many more and they all have in common that the pressure they have on firms has been found to be a key driver for green innovation decisions of companies. Thus, companies which cooperate more intensive with their stakeholders can improve their green innovative outcomes (Guoyou et al., 2011). Companies can achieve these improved green innovative outcomes on two types of green innovation.
Green innovation exists of both green product innovation and green process innovation, these two relate to changes in social, organizational, technological or institutional changes that contribute to a reduction of negative influences of production processes and products on the environment (Guoyou et al., 2011). Green product innovation is mostly determined by eco-labelling, because there are a lot of terms that can define green products, which might work confusing (Guoyou et al., 2011). Green process innovation on the other hand is an instrument that can be used to improve the environmental management processes of firms (Chen et al., 2006). This allows firms to improve their environmental sustainability vision and by doing that they increase the potential of improving ecological efficiencies (Guoyou, 2011).
3.3 Institutional Theory
However, companies and their green innovation performance are not influenced by stakeholders
alone. The institutional theory argues that the legal environment of companies influences the
behaviour and structure of a company (DiMaggio and Powell, 1983). Furthermore, DiMaggio and
Powell (1983) state that there is a rationalized system of contract and law that requires companies to
create controls to fulfil legal commitments. According to Aldrich (1979) the most important factors in
the institutional environment are that companies must take into account other companies or
organisations. Furthermore, Aldrich (1979) states that companies compete for resources, customers,
political power and institutional legitimacy. Because of this companies become homogenous over time
7 (DiMaggio and Powell, 1983). This process is named isomorphism, which is a process that forces companies or organizations in a population to resemble other companies and organizations that have to cope with the same environmental conditions (Hawley, 1968). Based upon the process of isomorphism DiMaggio and Powell (1983) developed the concept called institutional isomorphism, which is a useful process that aids in understanding which politics companies have to undergo in modern organizational life. DiMaggio and Powell (1983) identified three mechanisms through which institutional isomorphic change occurs, namely coercive isomorphism, mimetic isomorphism and normative isomorphism.
Coercive isomorphism results from formal and informal pressures which are exerted on organizations by other organizations upon which they are dependent. Coercive isomorphism also results from cultural expectations which are held by the society in which an organization operates (DiMaggio and Powell, 1983). These pressures can be experienced by companies or organizations as force or persuasion and in certain situations pressures leading towards organizational change can be the result of government mandates (DiMaggio and Powell, 1983). These government mandates can have a strong influence on the green innovative performance of companies, because government mandates can include new environmental regulations and the need for new pollution control technologies (DiMaggio and Powell, 1983). These mandates can in turn influence the decision companies make regarding the green innovations they pursue.
The second from of isomorphism, mimetic pressures, are the result of uncertainty in the environment of an organization, which in turn encourages organizations to imitate other organizations (DiMaggio and Powell, 1983). According to DiMaggio and Powell (1983) organizations structure and model themselves based on other organizations. Organizations have the tendency to do so when organizations’ technologies are not understood, when the environment creates uncertainty or when the goals of the organization are ambiguous (DiMaggio and Powell, 1983). This process may yield organizations with a cheap and viable solution when they face problems with unclear solutions or ambiguous causes (DiMaggio and Powell, 1983). The argument that can be derived from this information is that when several companies in a business environment are improving their green innovation performance, other companies will follow and mimic their competitors’ business plans (DiMaggio and Powell, 1983).
The final form of isomorphism is normative pressure. Normative pressure is the result of
professionalization, which is the struggle of the members of an organization in describing the
conditions and methods they need to create and uphold a visible base and legitimation for their own
individual work-related autonomy (DiMaggio and Powell, 1983). Examples of normative pressures for
8 green innovation could be the education of employees on the topic of green innovation and the development of professional rules and ethics concerning green innovation.
Building upon the three forms of isomorphism North (1990) developed a second prominent theoretical view on institutional change. North (1990) does not describe the coercive, mimetic and normative pressures as DiMaggio and Powell (1983) did, but he has made a distinction between formal and informal institutions. North (1990) defines institutions as constraints on a company’s behaviour.
Furthermore, North (1990) argues that formal rules are created and upheld by the policy makers and informal constraints are based upon the cultural heritance of a country or society. Because of this informal rules or constraints will not adapt immediately in reaction to changes in the formal rules (North, 1990). And for this reason similar policies in different countries will develop in different ways, because of the informal rules that constrain a certain country or society (North, 1990). This process has also been described as the path-dependence process by North (1997). Because of this process many different ways of development will arise, which depend largely on the cultural heritage and the individual historical experiences of countries (North, 1997). In other words, government mandates concerning the environment have a different influence based on the cultural heritage of a country (North, 1997). This means that informal rules affect the development of formal rules. Thus, it could be possible that governmental stakeholders have different pressures on companies in China and in the Netherlands. Furthermore, using the classification of North (1990) it is possible to argue that the formal environment includes governmental stakeholders, which can be seen as the representatives of lawmakers. And the informal environment includes customer stakeholder groups, which can be seen as the representatives of culture.
All in all, the institutional theory argues that organizations within the same organisational field tend to become homogenous over time because they experience similar pressures. This is the result of government mandates, the need for legitimacy and the increasing level of professionalization (DiMaggio and Powell, 1983). However, governmental regulations will develop and evolve differently in different countries because of the informal constraints in individual countries (North, 1990). For this reason, it is possible to argue that similar formal regulations in different countries develop differently over time because of cultural difference between countries. Therefore, it is possible that regulations concerning green innovation can develop in different directions and can have different outcomes in the Netherlands and China.
3.3.1 Informal regulations
As mentioned earlier the stakeholders which have been identified in this study as relevant for a
company’s green innovation performance are the customer and governmental stakeholders. Also
these stakeholders can have different pressures on companies in different countries, due to
9 differences in the institutional environment which develop because of differences in culture between countries (North, 1990). In order to be able to determine differences in culture between the Netherlands and China this study will build upon the theory provided by Hofstede (2001) and Hofstede
& de mooij (2010).
Hofstede (2001) distinguish cultures based on five dimension, which are power distance, individualism versus collectivism, masculinity versus femininity, uncertainty avoidance and long term versus short term orientation. The model created by Hofstede (2001) provides a scale from 0 to 100 for 76 countries for each individual dimension. Each country will have a position on all of the five scales or indexes relative to other countries (Hofstede, 2001). Before delving deeper it is necessary to explain each scale/index in more detail.
The first measurement scale, the power distance dimension, simply explains how power is distributed in a society (Hofstede, 2001). Thus, the question that is asked to measure this scale is to what extent members with less power in a society accept that the power is distributed unequally among the members (Hofstede and de Mooij, 2010). In cultures/societies with a large degree of power distance, like India for example, all members have a rightful place in the hierarchy of the society (Hofstede and de Mooij, 2010).
The second measurement scale is individualism versus collectivism. This scale measures whether members of a society look after themselves and their family only or if a person is loyal towards a group he or she belongs to (Hofstede, 2001). In individualistic cultures people identify with their own person.
Some traits of this type of culture are that people are self-conscious and strive for self-actualisation.
Also people in this type of culture assume that their values should be leading for the entire world (Hofstede and de Mooij, 2010). In collectivistic cultures however, people tend to identify with the group they are loyal to, people are we-conscious and are afraid to suffer a loss of face (Hofstede and de Mooij, 2010).
The third dimension is the masculinity versus femininity dimension, this dimension can be defined by several values which differ between masculine and feminine societies (Hofstede, 2001). In most feminine societies the dominant values that can be observed are caring for other and improving quality of life. While masculine societies highly value performance and achievement, with the emphasis on showing off fulfilled achievements with status brands or products (Hofstede and de Mooij, 2010).
Hofstede and de Mooij (2010) argue that the most important aspect in this dimension is role differentiation, this differentiation is small in feminine societies and large in masculine societies.
The fourth dimension is uncertainty avoidance and this dimension measures the level in which
members of a society feel endangered by ambiguity and uncertainty and the extent to which they try
10 to avoid these situations (Hofstede, 2001). A society with high uncertainty avoidance is featured by low acceptance rates towards change and innovations, while societies with low uncertainty avoidance have a better attitude towards change and innovations (Hofstede and de Mooij, 2010). Thus, this dimension can explain why certain innovations could be adopted in certain societies and if innovations will be discarded in other societies (Hofstede and de Mooij, 2010).
Finally, the fifth dimension is long-term versus short-term orientation, this dimension explains whether a society is future orientated or relies on the past and thus has a short-term orientation (Hofstede, 2001).
In conclusion, it could prove useful to measure the culture of a country or society because customers from different cultures could pressure companies in different and specific ways, which requires a company to act accordingly. This argument is also applicable to green innovations. Take for example, the difference between a masculine and a feminine society. In a feminine society people focus on improving the quality of living and people tend to care for each other (Hofstede and de Mooij, 2010).
In this type of society one would expect green innovations to be more important, because they increase the quality of life (Hofstede and de Mooij, 2010). In a masculine society however, people tend to be more focused on performance and achievement (Hofstede and de Mooij, 2010). In this society, making profits and having access to luxury products will be more important (Hofstede and de Mooij, 2010). This suggests that it is likely that different cultural values in China and in the Netherlands may lead to different customer pressures with regard to green innovations.
3.3.2 Formal regulations
In the previous section informal institutions have been discussed in the form of cultural differences between countries. In order to complete the theory provided by North (1990) formal institutions also have to be discussed. Which will be done by determining whether there are differences in governance between the Netherlands and China using the worldwide governance indicators. Previous studies have already shown that the worldwide governance indicators are a reliable and valid source to proxy the quality of regulatory institutions of countries (He and Qui, 2012).
The worldwide governance indicators have been developed to determine cross-country indicators of
governance (Kaufmann, Kraay and Mastruzzi, 2010). The WGI includes six broad indicators of
governance, which cover more than 200 countries. The six indicators the WGI consists of are voice and
accountability, political stability and absence of violence/terrorism, government effectiveness,
regulatory quality, rule of law and control of corruption (Kaufmann et al., 2010). The indicators have
been developed by using several hundred variables that capture the governance perceptions that have
11 been reported by commercial business information providers, survey respondents, non-governmental organizations and public sector organizations from all over the world (Kaufmann et al., 2010).
According to the WGI, governance includes the traditions and institutions by which authority in a country is exercised (Kaufmann et al., 2010). According to Kaufmann et al. (2010) governance includes three processes, which can be measured by the six governance indicators. The first process is the process by which governments are selected, monitored and replaced. This process is measured by the voice and accountability and the political stability and absence of violence/terrorism indicators. Voice and accountability measures whether a countries citizens have freedom of expression, freedom of association, free media and the ability to participate in the selection process of their government (Kaufman et al., 2010). Political stability and absence of violence/terrorism catches the perceptions of the change that the government of a country will be destabilized or overthrown by unconstitutional or aggressive means. This includes terrorism, politically-motivated violence and it measures if the government can effectively create and implement policies (Kaufmann et al., 2010).
The second process measures the capacity of the government to effectively formulate and implement their policies, which is measured by the government effectiveness and regulatory quality indicators (Kaufmann et al., 2010). Government effectiveness measures perceptions concerning the quality of public services, the quality of civil services and the degree to which these civil services are independent from political pressures, the quality of policy formulation and implementation and finally it measures a governments credibility concerning commitment to such policies (Kaufmann et al., 2010). Regulatory quality measures the perceptions of the ability of the government to formulate and implement their policies and regulations that allow private sector development (Kaufmann et al., 2010).
The final process that governance includes is the level of respect of citizens and the state for the
institutions that govern economic and social interactions among them (Kaufmann et al., 2010). This
process can be measured by the rule of law and control of corruption indicators. Rule of law measures
perceptions which include the extent to which agents follow the rules of society and have confidence
in the rules of society (Kaufmann et al., 2010). Besides this, rule of law also measures perceptions
concerning the quality of contract enforcement, the police, the courts, the change of crime and
violence and most importantly the quality of contract enforcement (Kaufmann et al., 2010). The final
index, control of corruption measures the perceptions of the level to which public power is used for
private gain. This index covers corruption on both large and small scale (Kaufmann et al., 2010).
12
3.4 Hypotheses
3.4.1 Customers
Previous research has discussed the impact of customer pressure on the decision of a company concerning environmental practices. According to several studies, customer expectations are one of the most important factors that influence a companies’ environmental practices nowadays (Weng et al., 2015). Increasing numbers of customers have concerns about the environmental and therefore buy products which are environmentally friendly (Weng et al., 2015). This works also the other way around, increasing numbers of customers nowadays refuse to buy products which harm or might harm the environment. Thus, pressure from customers is an important factor that stimulates companies into adopting green innovation strategies (Guoyou et al., 2001). Companies can also benefit from these pressures for they can differentiate their products, which could lead to a competitive advantage (Guoyou et al., 2001). Finally, companies can also benefit from customers word-of-mouth of the companies branding and image by successfully responding to these pressures (Weng et al., 2015). This leads to hypothesis 1:
H1: Customer pressures have a positive influence on a company’s green innovation performance in the Netherlands and in China
However, according to Hofstede’s cultural dimensions model (2001; 2005), customers behave differently in different countries due to the differences in the cultural dimensions that can be perceived between countries. Therefore, there is a reason to believe that customer pressures have a different impact on a company’s green innovation performance in China than in the Netherlands. Furthermore, the customer pressures a company has to cope with in the Netherlands could be completely irrelevant for companies in China. In order to investigate whether a difference can be perceived between the Netherlands and China I considered to include the data provided in Hofstede’s cultural dimension model. The ratio score for each individual dimension for both China and the Netherlands can be seen in table1 below.
The Netherlands China
Power Distance 38 80
Individualism/Collectivism 80 20
Masculinity/Femininity 14 66
Uncertainty Avoidance 53 30
Long/Short term orientation 67 87
(Table1: ratios for each individual dimension for China and the Netherlands, source geert-hofstede.com)
13 The numbers provided in table1 support the argument that a difference in customer pressures can be perceived between the Netherlands and China.
The first dimension, the power distance dimension, measures the distribution of power in a country (Hofstede, 2001). When consulting the data provided it becomes clear that the Netherlands scores low on the power distance dimension while China scores high. The conclusion that can be drawn from this, is that China is characterised by a culture with a large power distance. Which means that people with a higher social status are more important and have more power than people with a low social status in China, inequalities amongst people are perceived as acceptable (Hofstede and de Mooij, 2010). In the Netherlands people tend to be more equal and power is thus distributed more evenly among all members in the society regardless of their social status (Hofstede, 2001). The assumption that can be drawn from this dimension is that in China powerful individuals will more likely apply pressure on companies than in the Netherlands.
The second dimension, the individualism/collectivism dimension, shows that the Netherlands (80) has an individualistic culture, while China (20) has a collectivistic culture. In other words, people in the Netherlands tend to take care of only themselves and their direct family. In China people do the opposite, people in China act in the interest of the social group they belong to instead of acting according to their own preferences (Hofstede, 2001). The assumption that can be drawn from this dimension is that social groups are more likely to apply pressure on companies in China and individuals are more likely to apply pressure on companies in the Netherlands.
According to the third dimension, the masculinity/femininity index, China (66) scores significantly higher than the Netherlands (14). A low score on this index is associated with a feminine society and a high score with a masculine society (Hofstede, 2001). Therefore, the Netherlands can be defined as a feminine society and China as a masculine society. This suggests that values like caring for others and improving the quality of life are important in the Netherlands, while the most important value in China will be the drive and orientation towards success. For this reason I assume that customers in the Netherlands will apply more pressure on companies to improve their green innovation practices than customers in China will do. Because caring for each other and improving the quality of life, which are important in a feminine society and thus the Netherlands, can be associated with creating a more environmentally friendly business.
The fourth dimension measures whether societies tend to make plans in order to control the future or
if a society waits to see what the future brings (Hofstede, 2001). Taking the scores of this index into
consideration it is possible to argue that the Netherlands (53) has a slight preference for avoiding
uncertainty (Hofstede, 2001). China (30) on the other hand has a very low preference for avoiding
14 uncertainty (Hofstede, 2001). This could mean that customers in the Netherlands will tend to have a higher preference for green innovation. For example, investing in green energy can be seen as uncertainty avoidance because the price of fossil fuels fluctuate over time and fossil fuels will eventually be depleted. This argument can also be used for China, because the Chinese people tend to have a low preference for avoiding uncertainty it is possible that the Chinese people will be less inclined to invest in renewable energy. And when the time comes the Chinese people are willing to invest in renewable energy, fossil fuels might have already been depleted.
The final dimension, the long- versus short term orientation, explains whether a society is future orientated or relies on the past (Hofstede and de Mooij, 2010). The numbers provided in table 1 indicate that both the Netherlands (67) and China (87) have a pragmatic nature. Thus, the fifth dimension does not suggest that there are differences in customer pressures between China and the Netherlands.
When taking the results on these five dimension into consideration it becomes clear that there are indeed cultural differences between the Netherlands and China. Only the fifth dimension suggests that China and the Netherlands are culturally similar concerning their short versus long term orientation.
The other four dimensions suggest that there are cultural differences between China and the Netherlands. These cultural differences in turn influence how people and therefore customers behave.
Thus, this suggests that it is possible that there are differences in the types of pressures customers apply on companies in the Netherlands and in China. However, it is not yet clear which cultural differences, and therefore which cultural dimensions, lead to stronger customer pressures. This leads to the following hypothesis.
H2: Customer pressures have a different effect on a company’s green innovation performance in China than in the Netherlands
3.4.2 Government
Previous research has studied the relation between governmental regulations and environmental practices and have found that governmental pressure is one of the most important external stakeholders of a company (Weng et al., 2015). Governments change and enforce laws concerning the actions of companies towards environmental management and operating in a sustainable way (Weng et al., 2015). The degree to which governments enforce the rules and regulation will in turn determine the total impact of them on a company’s environmental policies (Weng et al., 2015). This leads to hypothesis 3:
H3: Governmental pressures have a positive influence on a company’s green innovation
performance in the Netherlands and in China
15 However, in this study I also aim to investigate if a there is a difference in governmental pressures between the Netherlands and China and if these different governmental pressures have a different influence on a company’s green innovation performance in these countries. Therefore, I suggest to investigate whether there is a difference in governance between China and the Netherlands. This can be done by consulting the WGI and comparing the scores the Netherlands and China receive on the six indicators provided in the WGI.
The Netherlands China
Voice and accountability 98 5
Political stability and absence of violence/terrorism
79 27
Government effectiveness 97 68
Regulatory quality 96 44
Rule of law 97 44
Control of corruption 95 50
(Table2: scores for each individual indicator included in the WGI for China and the Netherlands, source: www.info.worldbank.org)
In table two the scores of both the Netherlands and China on each of the six indicators provided in the WGI can be seen. It is clear that the Netherlands scores better on the WGI indexes than China does.
This suggests that there are in fact differences in governance between the Netherlands and China.
As can be seen in table two the Netherlands scores significantly higher on the voice and accountability index than China does. This means that people living in the Netherlands have more freedom of expression, association, and free media and have a higher level of democracy in their country (Kaufman et al., 2010). Also on the political stability indicator the Netherlands has a higher score than China, which means that the Dutch government has a low change to be overthrown by unconstitutional or aggressive means than China’s government. On the rule of law indicator the Netherlands also scores higher than China, which means that the people in the Netherlands perceive agents to follow the rules of society better and have confidence in the rules of society more than people in China do (Kaufman et al., 2010). Also on the control of corruption indicator the Netherlands scores higher than China, which means that the level to which public power is used for private gain is lower in the Netherlands than in China. Or in other words, corruption is more likely to take place in China than it is to take place in the Netherlands (Kaufman et al., 2010).
As stated earlier the impact of governmental pressures on a company’s environmental policies
depends on the degree to which a government enforces the rules and regulations they have
implemented (Weng et al., 2015). Because of this only the second process described in the WGI will be
16 discussed and analysed in more detail in this section. As mentioned earlier Kaufman et al. (2010) argue that governance includes three processes which each can be measured by two of the six indicators provided in the WGI. The second process Kaufman et al. (2010) describe is the capacity of the government to effectively formulate and implement their policies, which is measured by the government effectiveness and regulatory quality indicators. For this reason, the government effectiveness and regulatory quality indicators will be discussed in more detail.
The government effectiveness indicator measures the quality of public services, the quality of civil services and the quality of policy formulation and implementation (Kaufman et al., 2010). Besides this the government effectiveness indicator also measures the degree to which civil- and public services are influenced by political pressures and the credibility of the government concerning their commitment to their introduced policies (Kaufman et al., 2010). As can be seen in table 2 the Netherlands has a score of 97 and China has a score of 68 on this indicator. What can be derived from these numbers is that the Netherlands has a higher level of government effectiveness than China has.
This suggests that the quality of the Dutch government’s policy formulation and implementation processes are better than the quality of the Chinese government’s policy formulation and implementation processes (Kaufman et al., 2010). Furthermore, the Dutch government’s credibility to concerning commitment to their policies is also higher than China’s government’s credibility.
The regulatory quality indicator measures the extent to which the government is able to formulate and implement policies and regulations which allow for private sector development (Kaufman et al., 2010).
Consulting table 2 shows that the Netherlands score 96 on this indicator and China scores 44 on this indicator. Thus, the Netherlands has a higher regulatory quality than China has. This means that the Dutch government is more able to formulate and implement their policies and regulations in such a way that it allows for private sector development than the Chinese government’s formulation and implementation of policies allows (Kaufman et al., 2010).
All in all, the Netherlands has a better regulatory quality and government effectiveness than that China has. This also means that the Dutch government is able to develop and implement their environmental policies better than that the Chinese government is able to. Thus, there is a difference in governance between the Netherlands and China. This suggests that Dutch governmental pressures have a stronger influence on a company’s green innovation performance than the Chinese governmental pressures have on the green innovation performance of companies. This leads to hypothesis 4:
H4: Governmental pressures have a stronger effect on a company’s green innovation performance
in the Netherlands than in China
17 3.4.3 Conceptual model
All hypotheses combined result in the conceptual framework which can be seen below in figure 1. The first relationship in the model represents hypothesis 1, as can be seen in the conceptual framework I suspect that there is a positive relationship between customer pressures and the green innovation performance of a company in the Netherlands and China. The second relationship represent hypothesis 2, which suggests that there is a difference in the effect of customer pressures on the green innovation performance of companies between the Netherlands and China. The third relation in the model represents hypothesis 3, as can be seen in the conceptual framework I suspect that a positive relationship exists between governmental pressures and a company’s green innovation performance in the Netherlands and China. The fourth and final relation in the model suggests that there is a stronger effect of governmental pressures on a company’s green innovation performance in the Netherlands than in China. Finally, in order to test hypotheses 2 and 4 a comparative analysis using split sample analysis will be conducted.
Figure 1 (Conceptual model)
4. Methodology
This study will make use of the theory testing approach, which is deductive in nature. In other words,
this study aims to empirically test the generated hypotheses by conducting statistical analyses. After
having conducted these empirical tests, the results will be examined and interpreted. The reason this
study will make use of the theory testing method is because the used variables are well known,
because the relationships between the variables used in this study have been tested before. However,
this study will examine the relationships between these variables in a specific matter, namely the effect
18 of customer and governmental pressures on green innovation performance. Furthermore, I propose in this study that this relationship is influenced by the country of origin of the companies included in the analysis. This relationship could influence the way governmental and customer pressures are exercised in a country and therefore the green innovation performance outcome could differ as well.
This country effect has been tested conducting a comparative analysis, which involves a split sample analysis.
4.1 Data Collection
This study obtained the necessary data from databases the University of Groningen had available. The database that has provided the necessary data is called DataStream, which also holds asset4 data.
DataStream is a ThomsonReuters business and it is a reliable source for economic and financial data, it holds information about companies from over 175 countries worldwide and it also includes over 63 currencies (Summers, 2003). Furthermore, the database holds information up to twenty-five years old (Summers, 2003). The asset4 database can be accessed in a similar way to DataStream and this database holds data on corporate social responsibility. It includes environmental data, social data and governance data (ESG data) on a company level on 3400 public companies from all over the world.
Some examples of the data available in asset4 are emission reduction, resource reduction, product innovation and client loyalty. In order to extract data from asset4 one has to select a constituent list, which includes companies from a selected country. This study used the Shanghai A-share Index to extract data for Chinese companies and the AEX all share Index to extract data for Dutch companies.
The sample in this study consists out of 101 companies out of which 41 companies are from the Netherlands and 60 companies are from China, these are all the companies that were available in the database for ESG data for these countries.
4.2 Measurement scales
The asset4 ESG framework rates and compares companies against about 700 individual data points,
which are combined into approximately 250 key performance indicators. The average of these key
performance indicators are taken into a framework of eighteen categories, which are divided over four
pillars. These pillars in turn, integrate all the included categories into a single overall score. All pillars
and categories included in asset4 can be seen in appendix 1. The scores for all indicators, categories,
pillars and overall scores in the asset4 database are calculated in a similar way. All underlying data
points for each pillar or category are equally weighted and z-scored and finally compared against all
included companies in the asset4 database. This results in a standardized and normalized scored
percentage that takes a value between 0% and 100%. For this study data will be extracted from several
categories and two pillars included in asset4. These pillars are environmental and social. The categories
included are resource reduction, customer/product responsibility, society/community and product
19 innovation (ThomsonReuters, 2017). Besides asset4, two general variables have been extracted from DataStream namely, market value and net sales or revenues.
4.2.1 Dependent variable: green innovation performance
The green innovation performance of a company has been measured based on the product innovation pillar included in asset4. The product innovation pillar measures a company’s management commitment and effectiveness towards supporting the research and development of eco-efficient products or services. The product innovation pillar uses a ratio scale on which a company can score between 0-100. Some items included in this pillar are renewable/clean energy products, environmental research and development expenditures and energy footprint reduction (ThomsonReuters, 2017).
4.2.2 Independent variable: customer pressure
The customer pressure has been measured based on the customer/product responsibility pillar which is also included in asset4. This pillar measures a company’s management’s commitment and effectiveness towards creating value-added products and services, while upholding the customer’s security. Furthermore, this pillar also reflects on a company’s ability to produce quality goods and services, while taking aspects like the customer’s health, safety, integrity, privacy and other concerns customers may have into account. This pillar includes items such as: controversies towards health and safety, product labelling and product and service quality. Besides this, the pillar also includes aspects as whether the company has an ISO 9000 certificate and if the company communicates their operations clear and straightforward towards their customers. This pillar also measures a company’s performance on a 0-100 ratio scale (ThomsonReuters, 2017).
4.2.3 Independent variable: governmental pressure
Governmental pressure has been measured using the society/community pillar from asset4. This pillar measures a company’s management commitment and effectiveness towards maintaining the company’s reputation within the general community on local, national and global level. This includes abiding by the law. Examples of this are protecting public health, complying with emission rights and respecting business ethics, like not engaging in bribery. This pillar includes items which measure whether or not companies engage in bribery, lobbying, compliance with local regulations and whether or not a company follows OECD guidelines. This pillar also uses a 0-100 ratio scale as measurement scale (ThomsonReuters, 2017).
4.2.4 Control variables
In this study several control variables have also been included, namely resource reduction, emission
reduction, product responsibility, shareholder loyalty, vision/strategy, revenue/client loyalty, market
value and net sales or revenues. The reason these variables have been included as control variables is
20 that they offer alternative explanations for the dependent variable. Therefore it is possible that the control variables could have more explanatory potential than the only the two independent variables have. The variable resource reduction, which is also included in asset4, measures a company’s management commitment and effectiveness towards achieving efficient use of natural resources in the production process. This variable could prove to give valuable insights on whether reducing the use of natural resources also improves a company’s green innovation performance (ThomsonReuters, 2017). The emission reduction variable measures a company’s management commitment and effectiveness towards the reduction of environmental emission of waste, greenhouse gases and so on in the production and operational processes (ThomsonReuters, 2017). The product responsibility variable measures whether a company is committed and effective towards creating value added products and services upholding the customer’s security (ThomsonReuters, 2017). The shareholder loyalty variable measures a company’s commitment and effectiveness in generating a return on investments (ThomsonReuters, 2017). The vision and strategy variable measures the effectiveness of a company in creating an overarching vision and strategy for their company (ThomsonReuters, 2017).
The revenue/client loyalty variable measures whether a company is able to grow while maintaining a loyal client base through satisfactions programs etcetera (ThomsonReuters, 2017). The final control variables included are market value and net sales or revenues, which are included because these are a reliable way of measuring a company’s general performance. Therefore, they could also explain a company’s green innovation performance.
4.3 Data analysis
The data obtained from asset4 and DataStream has been transferred into IBM SPSS Statistics (SPSS),
which is a statistical program which is able to run statistical analyses on large datasets. After this SPSS
has been used to calculate the descriptive statistics for each variable included in the analysis. The
descriptive statistics include the number of observations, minimum value, maximum value, mean and
standard deviation. After having calculated the descriptive statistics a factor analysis has been
conducted including the control variables, because some control variables might measure the same
and besides this the control variables could correlate high among each other. Finally, the developed
hypotheses in this study will be tested by conducting a linear regression analysis. This regression
analysis will be conducted following the methodology provided by Berman, Wicks, Kotha and Jones
(1999). This methodology requires this study to estimate two different regression models. First the
direct effects model and second the comparative model. Hypothesis 1 and 3, the direct effect model,
will be tested by conducting a normal regression analysis concerning the independent variables
governmental- and customer pressures and the dependent variable green innovation performance to
test whether both independent variables are significantly related to green innovation. Hypothesis 2
21 and 4, the comparative analysis, requires the inclusion of the interactions between the governmental pressures and customer pressures and the country of origin (China or the Netherlands) of the companies included in the regression equation. In the next section the results of the conducted analyses will be given after which a discussion of the results and the final conclusion will follow.
5. Results
5.1 Descriptive statistics
The descriptive statistics can be found in table 3. It is important to note that four companies lacked observations for some variables. This problem has been solved by computing the average value for each included company in the database for each variable and adding the average as new value. This was necessary because otherwise there would have been fewer than 100 observations, which would be too little to properly conduct the necessary analyses. Out of the 101 observations 41 companies are based in the Netherlands and 60 are based in China.
N Minimum Maximum Mean Std. Deviation
Green Innovation 101 15,63 97.00 54,52 30,67
Customer Pressures
101 7,06 97.25 49,33 28,62
Governmental Pressures
101 5.36 96.51 53.55 31.37
Resource Reduction
101 8.92 93.58 54.68 30.89
Emission Reduction
101 11.72 95.39 51.98 29.89
Product Responsibility
101 7.05 97.25 49.46 28.49
Shareholder Loyalty
101 1.91 95,08 50.53 30.38
Vision Strategy 101 10.28 94.31 57.42 31.13
Revenue, Client Loyalty
101 3.16 97.78 55.82 32.32
Market Value 2015
100 1244.81 1352048.00 116031.82 230229.87
Market Value 2016
100 1193.27 1287279.00 109552.08 218135.13
Net Sales 2014 99 153818.00 2803727000 158099561.70 392085065.30
Net Sales 2015 99 196158.00 2018877000 149806526.20 322205972.20
Net Sales 2016 98 207886.00 1602431000 130288914.80 252592487.30
Valid N (Listwise) 97 Table 3 (Descriptive Statistics)
N Minimum Maximum Mean Std. Deviation
Green Innovation 60 15.63 96.15 45.27 27.99
Customer Pressure
60 7.06 92.98 41.66 28.76
Governmental Pressures
60 5.36 94.64 42.95 30.68
Valid N (Listwise) 60
Table 4 (Descriptive Statistics China)
22
N Minimum Maximum Mean Std. Deviation
Green Innovation 41 15.72 97.00 68.07 29.66
Customer Pressures
41 10.78 97.25 60.58 24.69
Governmental Pressures
41 12.76 96.51 69.05 25.65
Valid N (Listwise) 41
Table 5 (Descriptive Statistics the Netherlands)
In table 4 above the descriptive statistics for the independent variables and the dependent variable can be seen for the Chinese observations only. In table 5 above the descriptive statistics for the independent variables and dependent variable can be seen for the Dutch observations only. As can be observed from the tables the Chinese mean for both the independent and dependent variables is around twenty points lower than the Dutch mean for the independent and dependent variables.
Because of this an independent samples t-test has been conducted in SPSS to identify whether or not the Chinese and Dutch means on the variables green innovation, customer pressures and governmental pressures differ significantly from each other. The results of this analysis can be seen in table 6 down below.
F Sig. t
Green Innovation Equal variances assumed
0.606 0.438 3.924**
Equal variances not assumed
3.881
Customer Pressures Equal variances assumed
4.690 0.033 3.435
Equal variances not assumed
3.535*
Governmental Pressures Equal variances assumed
0.033 4.478
Equal variances not assumed
4.689 4.632**
Table 6 (Independent samples t-test) ** p < 0,001 * p < 0,05
The information that can be drawn from the analysis visible in table 6 is that equal variances are
assumed for green innovation and equal variances are not assumed for both customer pressures and
governmental pressures. Due to the significance levels however, the conclusion can be drawn that the
means of the dependent variable green innovation and the independent variables customer pressures
and governmental pressures are significantly different from each other in the Netherlands and China.
23
5.2 Factor Analysis
1 2 3 4 5 6 7 8 9 10 11
Resource Reduction 1
Emission Reduction 0.841
**
1
Product Responsibility
0.475
**
0.517
**
1
Shareholder Loyalty 0.338
**
0.271
**
0.351
**
1
Vision/Strategy 0.835
**
0.741
**
0.489
**
0.289
**
1 Revenue/Client
Loyalty
0.556
**
0.453
**
0.527
**
0.362
**
0.603
**
1
Market Value 2015 0.004 -0.058 0.049 -0.001 0.067 0.208
* 1
Market Value 2016 0.018 -.037 0.058 0.002 0.080 0.216
*
0.997
**
1
Net Sales 2014 -0.035 -0.067 -0.030 -0.121 -0.023 0.046 0.290
**
0.300
**
1 Net Sales 2015 -0.068 0.512 -0.017 -0.116 -0.048 .053 0.335
**
0.340
**
0.982
**
1 Net Sales 2016 -0.172 0.101 -0.060 -0.112 -0.152 -
0.018 0.316
**
0.301
**
0.975
**
0.9 97*
* 1
Table 7 (Correlation Table Control Variables) ** p < 0.01 * p < 0.05
Component 1 2 3
Eigenvalue 3.904 3.081 1.602
Resource Reduction 0.900 Emission Reduction 0.855 Product Responsibility 0.697 Shareholder Loyalty 0.457 Vision/Strategy 0.876 Revenue/Client Loyalty 0.727
Market Value 2015 0.978
Market Value 2016 0.978
Net Sales 2014 0.983
Net Sales 2015 0.984
Net Sales 2016 0.978
Table 8 (Rotated Component Matrix and Eigenvalues)
As mentioned before the data has been analysed in two linear regression models. First, the direct
effects model has been tested focussing on hypotheses 1 and 3. And second, the comparative analysis
has been tested in the second model focussing on hypotheses 2 and 4. It is important to note however,
that not all control variables have been included in the linear regression analysis because the
exploratory factor analysis found three underlying dimension behind the control variables. As
mentioned in the methods section of this paper the factor analysis has been conducted because some
control variables might measure similar characteristics and some control variables correlate highly
24 among each other, as can be seen in table 7. The conducted factor analysis is valid because the Kaiser- Meyer-Olkin measure of sampling adequacy had a value of 0,708, which is higher than the acceptable minimum of 0,600 and the Bartlett’s Test of Sphericity had a value of 0,00 which is in the acceptable level (Malhotra, 2013). In table 8 the three components found in the factor analysis and their eigenvalues can be seen, which are all above the acceptable level of one (Malhotra, 2013). The factor loadings of each variable are also included in table 8 and in appendix 2 the scree plot can be seen, which also suggest that there are three components. Using these three components, three new variables have been computed in SPSS and used in the linear regression analysis. The first variable (ESG variables) extracted from the factor analysis includes the control variables resource reduction, emission reduction, product responsibility, vision and strategy and revenue/client loyalty. The second variable (Net Sales Average) includes the net sales from 2014, 2015 and 2016. And the final variable (Market Value Average) extracted includes the market value of 2015 and 2016. Only the factor loading value for the control variable shareholder loyalty proved to be too low (0.457) to include it in any of the dimension found in the factor analysis, therefore this control variable has not been included in the linear regression analysis. The choice to only include the control variables in this factor analysis and to not include the independent and dependent variables has been done for theoretical reasons. Also, including them into the factor analysis could possibly load them into a single factor as well. Which would make a data analysis impossible.
5.3 Regression Analysis
Green Innovation Customer Pressure Governmental Pressure
Green Innovation 1
Customer Pressure 0.439** 1
Governmental Pressure 0.419** 0.422** 1
Table 9 (Correlation Table Independent and Dependent Variables) ** p < 0.01 * p < 0.05
In table 9 the correlation among the dependent and independent variables can be seen and in table 10 all calculated linear regression models can be seen. All models are significant on the p < 0,05 level.
Model 1 only measures the effect of customer and governmental pressures on green innovation.
Model 2 measures the same as model 1 only this model includes the control variables. Model 3
measures the relationship between customer and governmental pressures on the green innovative
performance of companies based in the Netherlands. And finally, model 4 measures the relationship
between customer and governmental pressures on the green innovative performance of companies
based in China.
25
Variable Model 1
Explanatory variables only
Model 2 Including control
variables
Model 3 Dutch sample only
Model 4 Chinese sample only
B t-value B t-value B t-value B t-value
(Constant) 22.744 3.767** 16.611 2.408* 25.577 1.717 20.446 2.545*
CustomerPressures 0.342 3.327* 0.129 0.915 0.212 0.818 0.228 1.339
GovernmentalPressures 0.279 2.973* 0.41 0.284 -0.297 -1.213 0.259 1.412
Marketvalue_average 3.590E-6 0.277 0.000 1.261 1.189E-5 0.821
Netsales_average ESG_Variable
1.364E-8 0.519
1.274 2.239*
1.092E-7 0.643
-0.604 1.552
1.709E-8 -0.014
1.599 -0.045 ANOVA F (17.179) p = 0.000 F = (7.659), p = 0.000 F = (3.094) p = 0.020 F = (3.620) p = 0.007
R² 0.260 0.296 0.307 0.266
Δ R² 0.244 0.258 0.207 0.192
Observations 101 101 41 60
Table 10 (Linear Regression models) ** p < 0,001 * p < 0,05
