University of Groningen
Faculty of Economics & Business Strategic and Innovation management
What is the effect of company
age on the rate of green
innovation within a company?
Researching the moderating influence of collaboration and
size.
Arjan Kloosterman S2066386
a.kloosterman.2@student.rug.nl /arjan92@live.nl Supervisor: Dries Faems
Second supervisor: Pedro de Faria Groningen, March 2018
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ABSTRACT
This paper analyses the effect which age has on the rate of green innovation. The last decades the importance of green innovation is growing through the rapid changes which occur in society. In this paper, it will be argued that the time of starting up a company is fundamental for the position it takes regarding being green and producing green innovations. It is argued that older companies are less likely to produce green innovations because they are more stuck in doing things the old way and are less able to cope with societal changes. There are two moderators expected to influence the relationship between age and the rate of green
innovation, the diversity of collaboration within the last years and the size of a company. The method used in this research is a hierarchical linear regression analysis including two
interaction terms. The main effect has been found statistically significant. However, an opposite result has been found which implies that older companies are more likely to produce green innovations. Collaboration diversity is found to have a positive effect on the rate of green innovation for younger companies but not for older companies. Size has a positive effect on the positive relationship between age and green innovation for older companies, but not for younger companies.
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1.
Introduction
"Sustainable development is the pathway to the future we want for all. It offers a framework to generate economic growth, achieve social justice, exercise environmental stewardship and strengthen governance."
Ban-Ki Moon is secretary general at the United Nations. Here he talks often about the importance of sustainable development and green innovation. In these times of an increasing role of technology, many leaders like him are trying to stimulate the rate of green or
sustainable innovation. Governments like to see the companies of their country to be on top of green or sustainable innovation.
The last decade more attention in the innovation management literature goes to green innovation. There are different names used for green innovation, like eco-innovation, sustainable innovation and environmentally friendly innovations or developments. The European Commission (2007) describes green innovation as a form of innovation which is aiming to progress towards the goal of sustainable development, which happens through reducing the impacts made on the environment contributing to more efficient use of natural resources. There are different dimensions described to the concept of green innovation, the main dimensions of green innovation according to Dangelico & Puraji (2010) are energy minimization, material reduction and pollution prevention.
In this study, it will be argued that in a time of accelerating societal changes, the moment of starting a company plays a big role in their type of behavior. There is much research
regarding green innovation, and what the drivers of it are. Often it looks like researchers take the concept of green innovation easily for granted, and that they do not stand still by the fact that green innovation may exist out of two different concepts: being green and being
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realization of the culture, values, and norms of a company by society (Inzerille & Rosen, 1983; Meek, 1988).
It will be argued that younger companies are more orientated at green innovation and that this is the case because younger companies are more socialized in the time and therefore feel more the need to conform to societal standards. Also, younger companies lack a specific setup of behavioral patterns which can block older companies to think in the appropriate way according to the changing times.
The effect of socialization is expected to differ in different times because societal
expectations change together with the times. The way of socialization depends on the specific moment of time in which a company was founded due to a life course dimension and a historical dimension in time (Riley, 1971). Age is not just a number; it tells something about the societal context in which a business was founded and has been growing and gained experience and build an identity through which it has gained legitimacy (Pettigrew, 1985). These aspects influence the way managers make decisions and how they deal with change (Lawler & Worley, 2006; Ackerman, 2000; Gioia & Thomas, 1996). By researching the effect age has on green innovation, this study aims to contribute to the understanding of how societal influences through socialization play a role in the rate of green innovations of companies. When a difference is found between old and young companies, it could be concluded that the socialization of the time of founding influences the way how companies look at societal expectations and demands.
The companies in this research are companies from three northern provinces of The
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technological innovation and organisation innovations leads to maximum results in terms of innovation; 3) entrepreneurs state that financial resources are one of the biggest struggles to innovate and entrepreneurs often don´t know about the support measures available to them; The research question in this study is: how does company age influences the rate of green innovation in companies?
The method of analysis will be a hierarchical linear regression with two moderating effects on it. It is expected that when companies engage in collaboration with other companies, there can occur a socialization effect which dampens the negative effect age has on the rate of green innovation. The more a company has been in collaboration the past years with other types of organizations, the more it is expected that this socialization effect occurs which dampens the negative effect age has on the rate of green innovation. Also, it is expected that the size of the company positively influences the negative effect age has on the rate of green innovation. Larger companies are expected to be more visible in society and a greater organizational visibility is linked to a higher social responsiveness (Brammer & Millington, 2005; Bowen, 2002) which is expected to lessen the negative effect age has on the rate of green innovation.
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2.
Theory
2.1 Green innovation
The concept of green innovation is the dependent variable in this research. Within the literature multiple names are used which all describe a similar concept: eco-innovation, sustainable innovation, environmental innovation and green innovation. In this research the term green innovation will be used. In short one can refer to this type of innovation when talking about novel technologies which improve the performance in both economic and environmental terms (Carillo-Hermosilla et al, 2009). The European Commission (2007) describes green innovation as a form of innovation which is aiming to progress towards the goal of sustainable development, which happens through reducing the impacts made on the environment and contributing to more efficient use of natural resources.
Dangelico & Puraji (2010) propose a framework in which they present three main dimensions of the concept of green innovation: energy minimization, material reduction, and pollution prevention. Energy minimization has everything to do with making products more efficient in use, making products which use renewable energy sources, to increase the efficiency in the production and the use of renewable energy sources in the production. Material reduction is about the recycling of existing products, making products and packaging which are
recyclable and making products and packaging which are biodegradable. Pollution prevention is about making products which prevent or reduce pollution and the pollution reduction or prevention within the production processes. Those three main dimensions are highlighted in terms of their impact in the physical life cycle of the products, which are the use of the product, the way of disposal and the way in which the manufacturing process takes place. Another author, Rennings (2000), also sees green innovation existing out of three
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researchers regarding the usable definition of sustainable development. It seems that
sustainable development is very hard to be defined operationally. This can also be said about green innovation, which in many ways is a very related if not the same concept. The
arguments against the operationalization are mainly based upon the idea that it is more like an idealistic heuristic idea, just like the concepts of justice and liberty (Rennings, 2000;
Norgaard, 1994; Cary, 1998). When talking about these concepts, most people will know what it is about, although these concepts are very hard or impossible to grab, measure and hold on to. These kinds of concepts may be more useful for showing a direction rather than be useful to predict any kind of results or outcomes. This is clearly a position very different from many of the existing research, and it creates the suggestion that green innovation is not a valid concept to research on its own.
In this research, the first position will be taken, and green innovation will be an existing concept which is possible to research. The definition used in this research co-aligns with the definition of the European Commission. Green innovation is therefore seen as a form of innovation which is aiming to progress towards the goal of sustainable development, which happens through reducing the impacts made on the environment and contributing for more efficient use of natural resources (European Commission, 2007). Since there can also be something said for the arguments against the use of this concept, a review of this concept will take place at the end of the research in the conclusion and discussion paragraph.
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Environmental regulations and standards by governments can force companies to engage more in green innovation (Milliman & Prince, 1989). When making green innovations, there is the possibility for a company to save costs. While of course not all green innovations are reducing costs for the company, some are. These future costs savings may also be a driver for a company to engage more in green innovation (Horbach, 2008). Rennings et al. (2006) show in their research that the existence of a specialized R&D department within a company also leads to higher environmental innovation in contrast to companies without a specialized R&D department. The development of new markets can be another argument to engage in green innovation and achieve product differentiation and enhanced competitive advantage (Pujari et al., 2003; Shrivastava, 1995).
2.2 The relationship between company age and the rate of green innovation
The time and societal context in which companies are created and grow are fundamental for the socialization and thus the behavioral patterns companies have. Original from the domain of sociology, socialization is about the process of entering a social context and attaining new knowledge, skills, and behavior to cope with and become one with this context (Brim, 1966). The idea of the socialization of a company includes the long-term internalization and
realization of the culture, values, and norms of a company by society (Inzerille & Rosen, 1983; Meek, 1988). DiMaggio and Powell (1983) argue that organizations not only compete for customers and resources but that to fit in the economic and social way they also must compete for institutional legitimacy and influence in the political arena. Effective
socialization will prepare both individuals and companies to cope with dynamic problems and to execute technical tasks necessary for an organization to relate to external constituents (Fogarty & Dirsmith, 2001). However, it is not enough that individual members of a company become socialized, the company itself also needs to adjust its structures and
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To continue about the theoretical implications of the process of socialization we look at the study of social gerontology. The concept of age is in almost all society’s fundamental for the ascription of status. Also, it can be one of the underlying dimensions through which social interaction within societies is regulated (Neugarten et al., 1965). Sociologists,
anthropologists, and social gerontologists have been long time interested in the differences which occur between the different age generations. Many years ago, Eisenstadt (1956) already stated that age and the differences in age are among the most basic and most important aspects of the course of a life and the destiny of it. Social gerontology is the specialization that is centered around the process of aging and the social aspects of the
differences in age. Riley (1971) takes much of the theory on social gerontology a step further; she claims that age is responsible for most of the stratification in society. Riley (1971)
promotes age stratification as an innovative approach within social gerontology. Riley (1971) sees the different age generations all being part as separate ingredients which form the
societal macrocosm, they are separated but interdependent with the other age strata. Therefore, she promotes for a re-examination of the ideas of aging, and the succession of birth and deaths as being integral parts of all the processes which occur within the society. The changes which occur through the births and deaths of individuals, generations, and institutions constitute pressures and strains which lead to innovation (Riley, 1971). What Riley (1971) was wondering about, how does it come that individuals located in different age strata can differ that much from each other? To put it simpler: why do older generations differ that much from the middle and younger? Riley (1971) attempts to answer this by including two dimensions of time: a life course dimension and a historical dimension. Using these two distinct types of dimensions of time, Riley (1971) claims it is possible to use them as some sort of coordinates for locating an individual in the age structure of society. In the article Riley (1971) mostly talks about generations. However, the same concepts can also be applied to organizations, businesses and institutions, since they also are bound by the life course dimension and the historical dimension and are part of a generation of businesses. For this research it is relevant to apply those two dimensions on the founding and growing process of a company.
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(Riley, 1971). When being founded in a specific time, there tends to be a commonality in the roles for generations to be experienced through the expectations of society which differ from the roles and expectations in other generations (Riley 1971). The life course dimension as stated by Riley (1971) includes social, psychological and institutional expectations which influence the role played by the generations. Companies founded at the same time are therefore expected to have much in common with each other. Those common aspects are shaped by those expectations which belong to a specific time of society. This is in line with the idea of socialization, whereas a company internalizes and realizes the culture, values and norms of society (Inzerille & Rosen, 1983; Meek, 1988). Since now there is a lot more focus on producing green products then a couple of decades years ago, and the expectations of society about corporate social responsibility are a lot more in the picture, it can be expected that younger companies are more committed to producing green innovations since they all grew up in the same societal context which demands more from the companies than a couple of decades years ago. This is also in line with theory about socialization stating that there is a bidirectional interactive process regarding early age generations (Kuczynski & Parkin, 2007). This means that in the first-place, society influences the young generations, who through their new interpretation of the social experiences construct new meanings and views (Kuczynski & Parkin (2007). These new meaning and views could result in more green innovations for young companies, since they are influenced by social experiences of a time wherein the importance of being green is a lot higher than in the time of earlier generations.
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security and confidence when staying in their own way of doing business, based on their experience. Through their history and experience companies have created their own business identity and culture. The experience and identity of a company influences the way they make strategies (Lawler & Worley, 2006; Ackerman, 2000; Gioia & Thomas, 1996) and it also influences the way they manage change (Lawler & Worley, 2006; Ackerman, 2000).
Managers of older companies may be more likely to create strategies which are based on their own experience, history, identity and business culture. Aspects of business culture and
identity have created legitimacy for the company in the past (Pettigrew, 1985). Therefore, it is very likely that managers want to hold onto this. So, because of the difference in
socialization effect, caused by these two dimensions of time, it can be expected that
companies with a different age act different upon societal, social and institutional events and expectations. Companies of old age are expected to be more committed to the expectations regarding the dimensions of time in which they were founded and have been growing in which less importance was placed on producing green innovations. With this comes their unique experience and by gaining experience a unique business identity and culture has been formed, which managers may prefer to base their decisions on since it has given legitimacy in the past for the business (Pettigrew, 1985). While younger companies are expected to be more committed to the expectations which society ask in their time, in which being green and sustainable is more important.
This leads to hypothesis 1: Age has a negative effect on the rate of green innovation
2.3 The effect of age on the rate of green innovation, moderated by collaboration It may be that collaboration can socialize older companies to become more in line with societal demands of the time. As stated in the previous paragraph, it is expected that older companies due to their different coordination in time dimensions are less socialized in the demands of society and therefore are less likely to produce green innovations. It is expected that through collaboration a socialization effect can occur by the organizational learning processes active in a collaboration which make that older companies get more on track with the societal demands of the time and therefore through the socialization effect of
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Much previous research has addressed the positive effects collaboration has on innovation performance (Baum, Calabrese & Silverman, 2000; Ahuja, 2000; Ahuja & Katila, 2001). Through the process of knowledge sharing companies can obtain and learn competitive social resources from their partners that otherwise may take a very long time to obtain through experience (Teece, 1986).Dingler & Enkel (2016) researched the collaboration across industry boundaries. In their research, they state that collaboration increases the
understanding of each other’s values and background (Dingler & Enkel, 2016). Therefore, when an older company, which is expected to be less engaged in green innovation,
collaborates with companies with other values and background, the understanding can increase of why it is important to be engaged in green innovation. Swanson & Holton (2001) have stated that the organization's learning capability is one of the most important aspects that enable a company to stay on track with the societal changes and demands. Through the sharing of knowledge organizations can become more familiar with changing demands in or outside the industry (Roberts & Berry, 1985) which can impact the way how older companies look at green innovation. Through the socialization active in the transfer of knowledge, companies can acquire and install new practices and routines (Dingler & Enkel, 2016). These new practices and routines can imply that older companies change their practises and routines towards more green innovation. Organizational learning contains a couple of essential
components which contribute to knowledge production processes. This includes the search for information, the assimilation of information and the developing and creation of new knowledge regarding products, processes and services (Verdonschot, 2005). Organizational learning has also been linked to achieving strategic renewal within organizations (Crossan & Berdrow, 2003). So, when socialization through organizational learning occurs, older
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This leads to hypothesis 2: The negative relationship between company age and the rate of green innovation is positively moderated by collaboration diversity
2.4 Moderating effect of size on the relationship between age and the rate of green innovation
When a company is larger it is more visible and vulnerable to the influences from outside (Brammer & Millington, 2005; Bowen, 2002). Also, a company often implies it has
accumulated more knowledge (Coad et al, 2013). Larger firms are therefore expected to be less affected by the negative effect age has on the rate of green innovation. As explained in the section about hypothesis 1, older companies are expected to be less socialized in the demands of society nowadays. Smaller firms are usually more influenced by their local networks in the part of the value chain in which they are active themselves (Arbuthnot, 1997; Tilley, 2000), while larger companies are more active in a larger part of society through having more stakeholders and a larger network. Larger firms are because of this more visible in society, and a greater organizational visibility is linked to a higher social responsiveness (Brammer & Millington, 2005; Bowen, 2002). It has been found in earlier research that larger firms show higher activity levels in environmental and external social issues (Observatory of European SMEs, 2002). Also, a larger sized firm often implies that a firm has been more able to accumulate a stock of resources and knowledge (Coad et al, 2013). Older companies which are large, are expected to have accumulated a larger stock of resources and knowledge and this knowledge can have the required socialisation effect which gets the company more in track with societal demands, values and norms. Because of the positive influence size seems to have on CSR and the engagement in environmental and social issues, it is expected that the negative effect age has on green innovation is less strong for larger companies
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3.
Conceptual model
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4.
Methods
4.1 Sample and data collection
All the data in this research are obtained through the Noord-Nederlandse Innovatiemotor. This is a project which is initiated by the expertise center VinCi, which is part of the Rijksuniversiteit Groningen (RUG) and the Samenwerkingsverband Noord-Nederland (SNN). Other strategic partners which are involved are the TCNN, NOM; PNO Consultants and the patent center Nederland. The aim of this project is to research the innovation
activities, investments, and performance of companies in the North of the Netherlands and compare these activities with other companies. The 2017 wave is the second time this research is performed. This year 5447 companies from the North of the Netherlands are approached and requested to participate in this research. All the companies are small and medium sized businesses. From these 5447 companies there was a response of 624 companies who answered the request and filled in the survey. This is a response rate of 11,45%. The survey was not always completed by all respondents. From those companies 129 also filled in the 2016 version of the survey. All the questions in the survey have been put in Dutch.
4.2 Variable measurements
This section will provide the measurements used to measure the dependent, independent, moderating and control variables. The questions all originate within the research of the Noord-Nederlandse innovatiemotor and have been validated as being usable measurements by the researchers of the University of Groningen.
Independent variable company age
16 Dependent variable rate of green innovation
This dependent variable tells if the company in the period of 2014-2016 has produced a green innovation. A green innovation according to The European Commission (2007) is a form of innovation aimed at achieving the goal of sustainable development, which happens through reducing the impacts made on the environment and to contribute to a more efficient use of natural resources. The construction of the variable exists out of six sub questions, which are all answered by filling in yes or no. In every case of the sub-questions, yes means that there was a green aspect in one of their innovations in the period of 2014-2016, and no means there was no green aspect in the innovations produced in the period of 2014-2016. The end variable constructed is a sum of all these sub questions. The more a company has answered yes, the higher the rate of green innovation is. The original question is: A green innovation is the introduction of a product, process or organization innovation which in comparison with alternatives ads positive value to the environment. Did your company create in the period 2014-2016 a product, process, or organization innovation which resulted in one of the following green environment advantages? 1) Lower material uses per unit output 2) Lower energy use per unit output 3) Smaller CO-2-print of your company 4) Replacement of material by less polluting or less dangerous substitute 5) Less polluting of ground, water, air or less sound hassle 6) Recycling of garbage, water or material. Yes = 1, No = 2. The variable has been coded in a way that no gets a score of 0, and a yes gets a score of 1. This means that the higher the company scores on this variable, the higher the rate of green innovation of the company is.
Moderator collaboration diversity
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Moderator size
This question asks about the size of the company, which is about the number of employees a company has. It has been logarithmic transformed to produce a less skewed variable. The literal question is: What is the total amount of employees within you’re company in 2016 (in FTE: Full Time Equivalents). It has been logarithmic transformed to produce a less skewed variable. It is expected that company size has a positive influence on the rate of green
innovation. It is expected that size will have a positive influence on the negative effect of age on the rate of green innovation. This is because a larger sized firm often implies that a firm has been more able to accumulate a stock of resources and knowledge (Coad et al., 2013). And that through their higher visibility the social responsiveness of larger company is expected to be higher (Brammer & Millington, 2005; Bowen, 2002).
Government rules
This is the first control variable. It asks in which amount the company is obstructed by government rules to innovate. The question can be answered by four options: 1) big 2) average 3) a bit 4) not at all. Companies can state to be obstructed by the government to innovate. Previous literature from the management literature suggests that pressure from society for environmentally friendly products, processes and policy’s may not always lead to an increase in green innovation and that it can even limit it by initiating a minimum
investment in green innovation to signal that the company has committed to ‘green policy’ (Darnall, 2006; Bansal & Hunter, 2003; Suchman, 1995). Many small companies state that they are not always able to obey the governmental laws regarding social responsible and green behaviour (Petts et al, 1999; Tilley, 1999). It is therefore expected that when
companies experience obstruction through government rules the score on green innovation will be lower.
Patents or design patent
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the following protection methods for innovations which have been introduced in the period 2014-2016? 1) Patent; 2) Registration of design patterns/Design Patents/Model rights. 1=yes 2=no. This has been coded in a way that 2=0, which implies that a higher score on this variable means that a company used more protection methods.
Internal % of investment in R&D
This control variable asks what the % is of the turnover which the company uses for R&D purposes. It is expected that the higher the % is of R&D investment, the higher the rate of green innovation is. The percentage of investment in research and development can reflect the amount of firm-specific technological knowledge (Hashai & Almor, 2008), which can provide the basis for developing and sustaining a competitive advantage what can be an important source for the generation of technological innovation (Le et al., 2006; Roper et al., 2004). The literal question is: Which % of the turnover is being used for internal research and development activities in 2016?
Market change
This control variable asks if the market the company is active in experiences rapid changes. It is expected the more the market changes the company is active in, the higher the rate of green innovation is. It exists out of two variables. The literal question is: For our organisation we agree with the following statement: 1) Changes in our market are intense; 2) In our market there is continuously change. The answers given range from 1 to 5, where 1 completely disagrees and 5 is completely agrees. The higher the score, the more intense the market is where the company is active in. Within fast changing markets companies must be flexible and adaptive with the changes which occur in the market and within society to stay in
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5.
Results
The results section contains three parts. In the first part in Table 1, an overview will be given of the descriptive statistics of the variables used in this analysis. The descriptive statistics given are the number of observations, the minimum and the maximum score, the mean score of the variable and the standard deviation. In the second part of Table 2, the correlations between the used variables are shown, and an interpretation will be given about the most striking correlations and their implications. In the second part of Table 3, the main part of this research is shown. This is the hierarchical regression analysis where models are created to test the hypothesis about the main effect and the moderating effects. It consists out of five different models. The control variables, the independent variable, and the moderator variables are standardized to get a better interpretation of the interaction effects. The first model
includes only the control variables. In the second model the variable of age is added to test hypothesis 1. The third model adds the moderator variable collaboration diversity and the interaction term AgexCollaboration diversity to test if collaboration diversity moderates the relationship between company age and the rate of green innovation. The fourth model adds the moderator variable size and the interaction term AgexSize to test if company size
moderates the relationship between company age and the rate of green innovation. In the fifth model both moderating and interacting variables are included to test the overall model.
5.1 Descriptive statistics
Table 1 Descriptive statistics
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In table 1 can be found the descriptive statistics of the variables used in the regression analysis before the log transformation and the standardization. In this it is a bit easier to interpret the descriptive, and what the most important scores are. What can be seen is that the number of patents or design patents is low, a mean score of .2495 on this variable tells that only 12.47% of the companies has requested a patent in the last years. The companies in the dataset experience on average a high rate of changes in their market. The mean score of market change is 3.2746, where the maximum score is 5.00. The average percentage of the turnover invested in research and development is 15%. The average amount of employees is 19, and the average age of the companies in this dataset is about 25 years old.
Table 2 Correlations
Patents Market change
Age Size Collaborat ion diversity Governme nt rules Internal % investment Rate Green Innovation Patents 1 -.061 -.096* -.030 .125* -.073 .297** .146** Market change -.061 1 -.046 .025 -.020 -.077 .035 .187** Age -.096* -.046 1 .507** -.094 .063 -.376** .151** Size -.030 .025 .507** 1 .044 .003 -.245** .177* Collaborati on diversity .125* -.020 -.044 .044 1 -.161** .270** .091 Governmen t rules -.073 -.077 .063 .003 -.161** 1 -.090 -.279** Internal % investment .297** .035 -.376** .245** .270** -.090 1 .023 Rate Green Innovation .146** .187** .151** .177** .091 -.279** .023 1
*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).
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internal % of the investment. It has a high correlation with the number of patents (.297), age (-.376), size (-.245) and collaboration diversity (.270). One other correlation which may be a bit striking is the one between the government rules and the rate of green innovation (-.279). This implies that the companies who claim to be hindered by government rules indeed score lower on the rate of green innovation. Also, the rate of changing markets seems to influence the rate of green innovation, with a correlation of (.187) companies which are active in fast-changing markets seem to score higher on the rate of green innovation. Size and age are also very high significant correlated (.507; p<0.01), which could imply a high multicollinearity. However, they have been standardized and a ViF score is calculated, which did not indicate any problems with the multicollinearity.
Table 3 Hierarchical regression analysis
Model 1 Model 2 Model 3 Model 4 Model 5 (Constant) 2.154*** 2.143*** 2.133*** 2.002*** 1.990*** Government rules -.538*** -.546*** -.506*** -.542*** -.503*** Market change .326*** .343*** .360*** .351*** .368*** Patents .246** .247*** .240** .246*** .242** Internal % Investment -.278*** -.140 -.234** -.173 -.266** logAge .344*** .340*** .338*** .339*** Collaboration Diversity .210** .189* logAgexCollaboration diversity -.210** -.226** logSize -.048 -.055 logAgexlogSize .251** .251** R2 .128 .152 .169 .167 .184 Adj. R2 .118 .140 .153 .150 .163 F-Test 12.776*** 12.463*** 10.088*** 9.879*** 8.622*** N 354 354 354 354 354
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In table 3 there can be found the results of the hierarchical linear regression analysis. It exists out of five models. The test tells us that all models seem to be significant, regarding the F-test there does not seem to be a problem with the models. Also, the ViF scores of all
variables have been checked and there seem to be no problems with the multicollinearity. All ViF scores appear to be between 1-2, while there only appear to be problems when the ViF score exceeds 10. The amount of usable observations is 354, which is enough to use it for the analysis.
5.2 Control variables
In the first model the control variables are placed in the model. All control variables in the first model are found to be significant with a p-value lower than 0.005. The variance
23 5.3 Age and the rate of green innovation
In model 2 the variable company age is added to check for the effect company age has on the rate of green innovation. In contrast to the theory, there is found a significant positive effect from company age on the rate of green innovation (B= .340; p= .001). This implies that the older a company is, the more likely it is to produce green innovations. Therefore hypothesis 1 is not supported. However, there is found a positive significant effect of age on the rate of green innovation.
5.4 Collaboration diversity moderator
Next, we look at model 3, here both collaboration diversity (.210; p<.05) and the interaction term AgeXCollaboration (-.210; p<.05) diversity are found to be significant. The model is significant and adding the interaction and moderation term increases the R^2 by .017, indicating collaboration diversity and the interaction term contribute to the explained variance in the model. Company age in combination with collaboration diversity is found to have a negative impact on the rate of green innovation. To interpret the interaction effect, a plot has been made. It was theorized in hypothesis 2 that a higher score on collaboration diversity would positively influence the negative effect of age on green innovation. So, older companies with a higher level of collaboration diversity were expected to score higher on the rate of green innovation than older companies with a low level of collaboration diversity. As can be seen in the plot, this is not the case. An increase in age does not lead to higher green innovation for companies with a high level of collaboration diversity. What can be seen is that with a low level of collaboration diversity, an increase in age does lead to a higher rate of green innovation. Also, for young companies which have a high score on collaboration diversity, a significant higher rate of green innovation has been found than for young companies with a low score on collaboration diversity.
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5.5 Size moderator
In model 4 the effect of size is looked upon. Size has a small but not significant negative effect on the rate of green innovation (-.048). The interaction term AgeXSize has a significant positive effect on the rate of green innovation (.251; p< .05). In figure 3 a plot has been made which contains the interaction effect of AgeXSize to explain how size influences the
relationship between age and the rate of green innovation.
It was theorized in hypothesis 3 that a higher score of firm size would positively influence the negative effect of age on the rate of green innovation. So, larger sized firms were expected to be less influenced by the negative effect of age on the rate of green innovation.
What can be seen from figure 3 is that having a large size positively influences the positive effect of age on the rate of green innovation. So, with an increasing age there is indeed a higher rate of green innovation for larger sized companies. Having a small size does not influence the relationship between age and green innovation. Also, for young companies with a small size a higher rate of green innovation has been found then for young companies with a large size.
Therefore hypothesis 3 is partially supported: Since there is no negative effect of age on green innovation, there is no support for the exact hypothesis. However, there is significant
1 1,5 2 2,5 3 3,5 4 4,5 5
Low Age High Age
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interaction between size and age and a moderation effect occurs. For companies with a large size there is a positive effect of age on the rate of green innovation. For companies with a small size there is no significant impact of age on the rate of green innovation.
Figure 3
6.
Conclusion and Discussion
6.1 Theoretical implicationsAs seen in the results, the main effect of company age on the rate of green innovation is found to be significant. However, age seems to have a positive effect on the rate of green innovation. Therefore, to address this unexpected result there must be looked upon the theory again very precisely. There are two ways in which this result may be explained. It might be due to wrong theoretical issues that the results are not in line with the theory. Also, it may be the case that the concept of green innovation is not valid for research and that research about green innovation therefore can lead to conflicting results, this will be explained more in depth in the limitations part. Within the theory it is expected that the time when a company starts up influences the way how it is socialized by society. Young companies were expected to be
1 1,5 2 2,5 3 3,5 4 4,5 5
Low Age High Age
26
more in line with the demands of the current time since they are founded and raised at this time. Companies are expected to be influenced by two dimensions of time (Riley, 2016) which contribute to how they deal with strategic issues and manage change (Lawler & Worley, 2006; Ackerman, 2000; Gioia & Thomas, 1996). When combining the used theory with the results, it will be argued that older companies are more in line with the demands of society nowadays. It may be the case that the effect of socialization does not depend that much on the time of the founding. But socialization may be a constant process and older companies are socialized through all times they are doing business. When combining this with their experience, in contrast to expectations, the experience might contribute to how they must deal with the changing society. It was expected first that experience and an own way of doing business kept the older businesses in behavior patterns of their moment of founding and growing which has given them legitimacy in the past (Pettigrew, 1985). But it very well may be the case that through experience older companies know better how to deal with changes. This is in line with other research on generations, stating that the youngest
generations, often named GenX, GenMe or millennials, put less value on work and identify their role more with events regarding leisure time and individualistic traits and therefore differ from the older generations who put more value on identifying and contributing to society (Twenge, 2010).
When looking at the moderator effect of collaboration diversity, it has been found that collaboration diversity significantly moderates the relationship between age and the rate of green innovation. However, the effect is found to be negative on the positive effect age has on the rate of green innovation. The results show that collaboration diversity for younger companies has a positive influence, but for older companies, it does not have a positive influence in terms of producing more green innovations. This could be explained by the fact that younger companies still have a lot to learn and can obtain a lot of knowledge through collaboration, while older companies have already acquired a lot of knowledge through the years. This is not known since the variable of collaboration asks about the collaboration in recent years only. So, it may be the case that the socialization effect which occurs within collaboration (Dingler & Enkel, 2016) is more relevant for younger companies and that organizational learning occurs more for younger companies, which can then lead to strategic renewal towards more green innovation (Crossan & Berdrow, 2003).
The second moderator in this analysis is size. It was expected that company size had a
27
results understate the theory partly. Being a larger sized company positively influences the positive effect of age on the rate of green innovation. So according to the results, the larger older companies are, the more likely they are to produce green innovations. One explanation for this could be that larger older companies through their size and history have the most stakeholders in the larger society and are also the most active in the larger society. Because of this, their position is more visible than the position of smaller companies, which makes them more commit to the influences from society (Brammer & Millington, 2005; Bowen ,2002). A smaller size does not influence the relationship between company age and green
innovation. The results imply that for younger companies it is more beneficial for the rate of green innovation to be small. This may be because the entrepreneur, which is a specific type of the young small business owner, is often associated with personality traits which increase the likelihood of socially responsible behavior (Solymossy & Masters, 2002; Teal and Carroll, 1999).
A bit striking is a negative effect the internal percentage investment in research and
development has on the rate of green innovation. The higher the percentage of the revenue put in research and development, the lower the rate of green innovation is. This may be explained by fact that the businesses in this research are small and medium-sized companies. Smaller companies often have less financial resources; when they invest the resources they have, it may be investments in research and development related to their main business activity, instead of investments in green innovations.
6.2 Managerial implications
The results show that age has a positive influence on the rate of green innovation. For governments and policy makers, this implies that it is very important to keep the young companies on track with the societal demands. Young companies seem to be less engaged in the green innovation, and because they are the future, it is important to learn them from a young age already to be involved in green innovation. Since contrary to the theoretical expectations young companies are less involved in green innovation, governments and policy makers ae recommended to create an active policy regarding engaging young companies in green innovation. Also, since collaboration seems to have a positive effect through
28
can exchange knowledge and enhance each other’s capabilities regarding green innovation. Collaboration enables organizations to develop socialization which on its turn facilitates the transfer of knowledge through installing new practices and routines (Dingler & Enkel, 2016). One contribution to begin with, the system of schooling could be adjusted more in a way that children and students should be thought from a young age to be more engaged in being green. Since public schools and universities are important agents for the development and
transmission of broad social norms and cultural values, and function as one of the main activators of socialization within society (Johnson, 1982).
6.3 Limitations and future research
One of the limitations of the study may be the generalizability. The study includes companies from the provinces in the north of the Netherlands. There may be cultural differences
between the provinces, which cannot be directly seen in the data, which could somehow influence the results. Within this research, only small and medium sized enterprises are questioned. Therefore, it may be that results regarding size may differ when larger companies would be examined, and it might be the case that the moderation effect of size would have another effect when adding larger companies to the research. Another limitation may be the way questions are asked, most variables only include a yes/no option, and therefore the construction of the variables and the way the model is constructed might contribute to the results found. For example, the questions about green innovation are all answered by yes/no; this implies that within the data it cannot be found how green the products really are. Also, it cannot be found how innovative the products really are. Here we arrive at one of the greatest limitations of this research, and probably also of much other research regarding green
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Appendix
Company Age: Q5 Vraag: Jaar van oprichting van uw bedrijf? Translation: Q5 Question: Year of starting up you´re Company?
Green innovation: Q20 Een milieu-innovatie is de introductie van een productinnovatie (goed of dienst), procesinnovatie of organisatorische innovatie die een positieve bijdrage levert voor het milieu in vergelijking met de alternatieven. Deze milieubijdragen kunnen het hoofdobjectief zijn van de innovatie, maar kunnen ook het bijproduct zijn van andere objectieven. Vraag: heeft uw onderneming in de periode 2013-2015 een product (goed of dienst), proces-, of organisatorische geïntroduceerd die de volgende milieuvoordelen opleveren?
Translation: Q20 an environmental innovation is the introduction of product innovation
(good or service), process innovation or organizational innovation that makes a positive contribution to the environment compared to the alternatives. These environmental
36 Lager materiaalverbruik per
eenheid output (Q20_1) Ja (1)
Nee (2) Lager energieverbruik per
eenheid output (Q20_2) Ja (1)
Nee (2) Kleinere CO2-voetafdruk van
uw bedrijf (totale CO2-uitstoot door productie, vervoer, enz.)
(Q20_3)
Ja (1) Nee (2)
Vervanging van materialen door minder vervuilende of minder gevaarlijke substituten (Q20_4)
Ja (1) Nee (2)
Minder vervuiling van grond, water en/of lucht en/of minder
geluidshinder (Q20_5)
Ja (1) Nee (2)
Recyclage van afval, water of
materiaal (Q20_6) Ja (1)
Nee (2)
Lower material consumption
per unit of output (Q20_1) Yes (1)
No (2)
Lower energy consumption per
unit of output (Q20_2) Yes (1) No (2)
Smaller carbon footprint of your company (total CO2 emissions from production, transport, etc.)
(Q20_3)
Yes (1) No (2)
Replacement of materials by less polluting or less dangerous
substitutes (Q20_4)
Yes (1) No (2)
Less pollution of soil, water and/or air and/or less noise
(Q20_5)
Yes (1) No (2)
Recycling waste, water or
material (Q20_6)
37
Government rules Q22 In welke mate verhinderden of belemmerden elk van de volgende factoren uw innovatie-activiteiten in de periode tussen begin 2014 en eind 2016?
Translation: Q22 In which amount was your company hindered by one of the following factors regarding your innovation activities in the period between 2014 and 2016? 4) Though regulations
The question can be either answered by four options: 1) big 2) average 3) a bit 4) not at all
Size Q36 Wat was het totaal aantal werknemers van uw bedrijf in 2016 (in FTE)? ______ FTE (Full Time Equivalents) (1)
Translation What is the total amount of employees within you’re company in 2016 (in FTE: Full-Time Equivalents)
Internal % investment Q24 Welk percentage van de omzet werd uitgegeven aan interne O&O activiteiten in 2016?______ % (1)
Translation: Q24: Which % of the turnover is being used for internal research and development activities in 2016?
Market Change: Q51 Voor onze organisatie geldt...
Veranderingen in onze lokale markt zijn intens (Q69_1) In onze lokale markt vinden continu veranderingen plaats (Q69_3)
38
Patents: Q21 Heeft uw bedrijf de volgende beschermingsmethodes gebruikt voor innovaties die in de periode 2014-2016 werden geïntroduceerd?
Translation: Has your company used the following protection methods for innovations which have been introduced in the period 2014-2016? 1) Patent; 2) Registration of design patterns/Design Patents/Model rights. 1=yes 2=no.
Octrooien/Patenten (Q21_1) Ja (1) Nee (2)
Registratie van Designpatronen/Design patenten/Modelrecht (Q21_2)
