‘The effect of market dynamism, cooperation and firm
age on R&D investments of family firms: an empirical
analysis’
By: Laura Kursten
University of Groningen Faculty of Economics and Business
MSc BA Strategic Innovation Management
20 June 2017
Supervisor: Prof. Dr. Faems
Co-assessor: Dr. de Faria
S2102978
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Abstract
Family firms are an important form of ownership in today’s world. As family firms make
decisions not only based on firm goals but also based on feelings, the characteristics of family
firms are different from non-family firms. However, family firms cannot be seen as a
homogenous form of ownership. This paper focused on the differences in their risk-averse
behaviour and their long-term orientation to maintain their business. I researched the relation
of market dynamism, cooperation and firm age on the R&D investments of family firms. This
paper found a significant effect between firm age and family firms’ R&D investments. Furthermore, market dynamism influences the relation between cooperation and family firms’
R&D investments. This paper provides evidence that there are differences in the field of family
firms and provides ideas for further research in this field.
Keywords: Family firms; innovation; R&D investments; cooperation; firm age;
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Introduction
It is acknowledged that family firms play an important role in the world's leading economies
(Miller & Le Breton-Miller, 2005; Zahra, 2003). Characteristically in family owned SMEs is
that family members play the role of both manager and owner (Munari, Oriani, & Sobrero,
2010). A family firm is defined by: ‘A family’s involvement in ownership and governance and a vision for how the firm will benefit the family, potentially over generations.’ (Chrisman &
Patel, 2012, p. 976) Family firms not only make decisions based on their economic goals but
typical for family firms is that they also make a lot of decisions based on their noneconomic
goals (Chrisman & Patel, 2012). Growth and survival are essential goals for family firms
because they enable family firms to be passed on to later generations (Kellermanns et al., 2008).
An important factor for firms and their ability to grow and survive is innovation (Damanpour
& Evan, 1984). According to De Massis, Frattini & Lichtenthaler (2013), there is a growth in
that family firms use technological innovation to nurture their competitive advantage and to
overcome economic and financial downturns.
Empirical research about innovation in family firms is scarce (Llach & Nordqvist, 2010). And
even though scholars have long realized that family firms are not homogenous, current literature
is mostly focused on the differences between family firms and non-family firms (Sharma,
Chrisman & Chua., 1997). Instead of focusing on the heterogeneity of family firms, literature
focused on the attributes shared by family firms to compare family firms with non-family firms
(Sharma et al., 1997). This paper will focus on the saying by Chua et al. (2012), that a theory
of the family firm must not only be able to distinguish between family and non-family firms
but must also be able to explain the differences and variations among family firms. Family firms
entail both strengths and weaknesses and the article of Cassia, De Mizzo & Pizzurno (2012)
considers that further empirical investigation is an important issue to better understand family
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(Llach & Nordqvist, 2010). This contradictory findings may be caused by the conflicting
relationship between family firms and innovation. This is caused by the commixture of a family firm’s long-term orientation and their conservative nature (Zahra, Hayton & Salvato, 2004).
Their long-term orientation allows them to dedicate resources to innovation and risk-taking.
Whereas their conservative nature may hold them from innovation because they are afraid of
destroying their family wealth (Zahra et al., 2004). Because of this conflicting relationship of
being long-term oriented on the one hand but also risk-averse towards innovation on the other
hand (Zahra et al., 2004), this paper assumes that there will be differences in the field of family
firms.
This paper will focus on the variables market dynamism, cooperation, and firm age. In dynamic
markets, it is more important to stay progressive and dynamic instead of cautious and stable
(Cassia, De Massis & Pizzurno, 2011). That is why this paper will study if there is a difference
in R&D investment behaviour when a family firm is in a dynamic market. This paper will look
into the relation between cooperation and family firms’ R&D investments because cooperation
networks are a way of speeding up innovation (Fukugawa, 2006). Finally, I will focus on firm
age because founders of family firms, who desire to build a lasting legacy, may become more
conservative in their decisions because of the high risk of failure of entrepreneurial ventures
(Morris, 1998). Younger generation family firms adopt a more professional style and try to
reinvent themselves (McConaughy & Phillips (1999); Dyer (1988); Jaffe & Lane, 2004). In this
paper, I will answer the following question: To what extent does cooperation, market dynamism
and firm age has an effect on the R&D investments of family firms?
The first variable that will be discussed in this paper is market dynamism. In dynamic markets
the competitive landscape shifts quickly and change must be promoted to survive (Eisenhardt
& Martin, 2000). If a firm is rather conservative and risk averse, this will make them inflexible,
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2010). Flexibility is important in a dynamic market in order to adapt to changing circumstances
and face continuous innovation (Zahra et al., 2004). That is why I will assume that in a dynamic
environment, family firms will invest more in R&D to keep up with the continuous innovation.
This paper will assume that family firms that cooperate more with external partners will invest
more in R&D. Because of external cooperation, a family firm can get access to external
resources and knowledge. Therefore family firms can build an innovation network, where the
firm is able to exchange knowledge, skills and resources that the firm cannot develop on their
own (Bullinger, Auernhammer & Gomeringer, 2004). Hereby, they may can spread the risk that
R&D investments entail.
Researchers have expressed concern that over time, some family firms become resistant to
change and follow conservative strategies that limit their future growth and profitability (Dunn,
1996; Lee, 2006; Schulze et al., 2001). This would mean that older family firms are more risk
averse than younger family firms. As they are more risk averse, they are more focused on
stability and survival (Lee; 2006, Schulze et al., 2001) The risk-taking preferences can shift
through different generations (Zahra, 2004). Little is known about the different stages of the
life cycle of family firms. Litz & Kleysen (2001) state that innovation in family-owned
companies is a responsibility for the younger generations. And that to pursue this objective, the
younger generations need to be properly trained and left free to innovate (Litz & Kleysen, 2001). This consequently has a positive effect on the family firm’s innovation (Beck et al.,
2011). I will assume that older firms will invest less in R&D investment because of their risk
aversion and conservative nature. Young firms will be more long-term oriented and will,
therefore, invest more in R&D.
This study attempts to expand our understanding of family involvement in firms. To answer my
research question, I will use the Innovation Benchmark North-Netherlands 2017, a survey that
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Innovation Survey. The survey was sent to 5447 SMEs located in the North-Netherlands and
624 firms filled in the survey. To test the conceptual model, 3 hypotheses were developed. The
hypotheses will be tested using the negative binomial regression.
Findings indicate that firm age has a negative effect on family firms’ R&D investments. No
significant effect was found between market dynamism and family firms’ R&D investments and between cooperation and family firms’ R&D investments. Furthermore, this paper found
that there is a significant relation between market dynamism and R&D investments of
non-family firms. The relation between cooperation and R&D investments of non-non-family firms is
significant as well. Lastly, an interaction effect was found for family firms between cooperation
and market dynamism. This research contributes to existing literature by filling the literature
gap about heterogeneity in family firms.
The structure of this paper is as follows. The next section describes the existing literature about
the field of family involvement in firms and R&D investment. In this part, the hypotheses and
the conceptual model will be presented. After that, the methodology will be explained followed
by testing the hypotheses. I will use the results of the research to write the discussion and future
research directions. Finally, the paper will end with a conclusion.
Literature review
In this part of the research, I will take a closer look at the research field of innovation in family
firms and the different variables of the conceptual model. During this literature review, the
conceptual model and a number of hypotheses will be presented.
Family firms
Family ownership is the dominant form of ownership around the world (La Porta, Lopez‐de‐
Silanes & Shleifer, 1999). Family-controlled firms represent a unique bundle of resources that
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focus on two characteristics of family firms that will be explained later on. The definition of a
family firm by most authors is based on three criteria. The first criterium is ownership, 50% of
the firm has to be owned by the family. The second criterium is governance, the family has to
control the business. And the last criterium is management, a significant proportion of the senior
management has to be from the same family (Llach & Nordqvist, 2010). Llach & Nordqvist (2010) used the definition by Chua et al. (1999) ‘who assert that it is unreasonable to use a
family firm definition that excludes a large number of respondents who consider themselves family firms’ (p. 383). This paper will also use the definition by Chua et al. (1999). This
definition is also used in the article of Chrisman & Patel (2012): ‘A family firm is defined by a family’s involvement in ownership and governance and a vision for how the firm will benefit
the family, potentially over generations.’ (p. 976)
There are main differences between the goals and values of family businesses and those of
individuals working in a firm where there is no family connection (Cassia et al, 2011). The
integration of family and business is what makes a family firm unique (Habbershon & Williams,
1999). In this manner, a firm can create impressive and uncommon characteristics. One of the
main managerial factors that differentiate family firms from non-family firms is that family
firms are more long-term orientated than non-family firms. Family firms feel less pressure for
short-term paybacks and are more focused to ensure the lastingness of their business (Cassia,
et al., 2011). Their long-term orientation can affect the strategic decisions of the firm (Sharma,
et al.). This is caused because of the strategic behaviour of family firms. Most family firms are
concentrated on incremental, regional expansion rather than rapid or wider international
expansion (Cassia et al., 2011). Nonetheless, Bergfeld & Weber (2011) state that successful
family firms use radical and progressive innovation to secure their future and long-term
orientation.
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radical and dynamic (Chrisman & Patel, 2012). This can be explained by their risk-averse
behaviour. An explanation for the risk-averse behaviour of family firms can be their
conservative behaviour (Cassia et al., 2011). The risk of losing family wealth withholds firms
from engaging in entrepreneurial activities (Sharma et al., 1997). Family firms tend to make
choices by noneconomic family goals that create socioemotional wealth for the family
(Chrisman & Patel, 2012). Some of their decision-making is based on feelings and emotions
instead of business logic (Stewart, 2003).
Family firms and R&D investment
On the one hand, innovation is an expensive, uncertain and risky business process that very
often requires several excellent capabilities and competences to be performed successfully. On
the other hand, it is the crucial base to increase competitiveness and business development
(Schumpeter, 1934). Crossan & Apaydin define innovation as ‘the production or adoption,
assimilation, and exploitation of a value-added novelty in economic and social spheres; renewal
and enlargement of products, services, and markets; development of new methods of
production; and establishment of new management systems. It is both a process and an outcome’ (p. 1155).
Innovation can have as output either new ways of doing things or new products, services, or
techniques (Porter, 1990). To develop new product innovations or service innovations, research
and development (R&D) expenditures are needed because of the high costs of implementing
new innovations (David, Hitt & Gimeno, 2001). Investments in R&D are sunk costs that have
a long payoff horizon and entail substantial risk (Chrisman & Patel, 2012). That is why, R&D
investments are focused on the long-term and they are inherently risky in nature (Chrisman &
Patel, 2012). A lot of firms don’t engage in R&D investments because they lack the financial
resources (Binz & Czarnitzki, 2008). The risk that R&D investments constitute, require trust,
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Berchicci (2013) found that firms with greater R&D capacity perform better than those with a low R&D capacity.
The high costs and risk of R&D investments can be seen as a disadvantage by family firms because of their risk-averse behaviour of family firms. The outcomes of investing in R&D are not shown immediate and therefore, it is a risk-taking activity (Chen & Hsu, 2009). Nevertheless, risk taking is correlated to innovative and proactive behaviour (Naldi et al., 2009). On the other hand, the ability to innovate is important for family firms to enhance their
profitability and growth (Zahra, 2004). Innovation is a driver to create wealth and ensure firm’s
long-term survival (Acs & Armington 2004; Bruyat & Julien, 2000). Consequently, when
family firms focus on the long-term existence of their firms, innovation can be an important
mechanism for family firms as they may turn into a competitive advantage that is associated
with long-run success (Chen & Hsu, 2009). When the importance of long-term goals increases
in family firms, they are more willing to invest in their long-term wealth, even though the
short-term goals may be at risk (Chrisman & Patel, 2012).
The paper of Chen and Hsu (2009) investigated R&D investments in family firms and found a
negative relationship between family ownership and R&D investment. This suggests that either
family ownership discourages risky long-term R&D investment. It can also suggest that firms
with family ownership use their R&D investments more efficiently and that is why they need
fewer R&D investments (Chen & Hsu, 2009). When the latter one is true, that will be positive
for the innovation performance of the family firm. In the article of Chrisman & Patel (2012), they found that the variability of family firms’ R&D investments is greater than that of
non-family firms, this depends on the goal-setting of the firm. When performance is at or above the
desired level, family firms are expected to invest less in R&D than non-family firms (Chrisman
& Patel, 2012).
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Nonetheless, literature tends to focus on the homogeneity of family firms, whereas there are
many differences between family firms (Melin & Nordqvist, 2007). Family firms are
heterogeneous as they differ in terms of the extent and mode of family involvement in
ownership and management (Melin & Nordqvist, 2007). I assume that this heterogeneity of
family firms will affect their behaviour towards innovation and in particular R&D investments.
Therefore this paper developed the following conceptual model. Below, this paper will explain
the different variables that are part of the conceptual model.
Market dynamism
Nowadays, the competitive world firms operate in is highly dynamic and uncertain. Therefore
Hamel, 2000, claims that innovation is required to survive as a firm. Dynamic markets are
markets in which the competitive landscape shifts quickly and change must be promoted to
survive (Eisenhardt & Martin, 2000). For family firms, it is important to have an
entrepreneurial mindset in order to determine and exploit opportunities present in an uncertain
environment (Shane & Venkataraman, 2002).
According to Dunn, 1996, family firms are more inwardly directed. Nevertheless, in dynamic
and competitive environments, companies need a high level of strategic flexibility in order to
secure their assets and resources and to take advantage of emerging opportunities (Zahra, et al.,
11 and growth (Eisenhardt & Martin, 2000).
Strategic flexibility is important to all firms, but as family firms often been described as
conservative and slow to recognize and respond to changes in their environment, strategic
flexibility may be particularly interesting for family firms (Zahra et al., 2008). A family firm's
personal ties and strong commitment can enable them to react to environmental shifts (Zahra et
al., 2008). Staying intensely involved in the market is a manner that reduces the tendency of
family firms to stay passive and risk averse (Eddleston, Kellermanns & Sarathy, 2008). As
follows they can respond to the strategic contingencies.
Changes in the competitive, technological and global landscapes have challenged family firms
to look out for new systems and strategies to innovate and keep their market positions (Zahra
et al., 2008). This way a firm has the capacity to adapt to changing circumstances by for
instance, adopting emerging technologies (Volberda, 1996). Especially in a dynamic
environment, if family firms stay involved and active in the market, firms can stay alert and
face continuous innovation (Zahra et al., 2008).
That is why I expect that family firms in a dynamic environment will invest more in R&D to
stay innovative and adapt to the circumstances of the changing environment in order to survive
in the long-run. This will help them in their long-term orientation because growth and survival
are essential goals for family firms to maintain their business (Kellermans et al., 2008).
That is why I propose the following hypothesis:
Hypothesis 1: Market dynamism has a positive effect on family firms’ R&D investment. Cooperation
Participating in external cooperation networks is gaining huge popularity among firms of all
sizes (Hagedoorn, 2002). That is because there are multiple advantages why family firms should
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networking can be needed for a firm to achieve economies of scale or to integrate diverse skills,
technologies and competencies (Mancinelli & Mazzanti, 2008).
Another reason for family firms to develop external relationships in order to network is to
secure needed resources that the family firm does not own and are difficult to develop within
the family firm (Nordqvist & Goel, 2008).
Lastly, through growing interaction in a network, SMEs can tackle the insecurity they are
experiencing from development and use of technologies (Bullinger et al., 2004). By creating a
link between different companies, research facilities, suppliers and customers SMEs can create
a solid innovation network where they can share knowledge and profit from complementary
resources (Bullinger et al., 2004). The resources and knowledge that SMEs could gain from
external innovation partnerships might contribute to the stimulus and capacity firms need to
innovate (Hewitt-Dundas, 2006).
Keeping in mind the risk-averse behaviour of family firms, this paper assumes that cooperating
with different partners can reduce the risk of investing on your own in the needed resources.
Therefore this paper assumes that because of the new knowledge and expertise gained from the
cooperation with external partners, family firms that participate in cooperation will be more
willing to invest in R&D, whereas firms that do not cooperate a lot will be more hesitant to
invest in R&D.
That is why I propose the following hypothesis:
Hypothesis 2: Cooperation has a positive effect on family firms’ R&D investments Firm age
When looking at academic literature of family firms, noticeable is that different generational
stages in a family differ in their innovation-oriented culture (Zahra, 2005). When later
innovation-13
oriented culture in the firm (Zahra, 2005). First-generation family firms show more risk-averse
behaviour in comparison with later-generation family firms. This is because of their desire to
keep the business within the family and maintain family wealth. Family firms have less pressure
for short term paybacks and more attention to ensure the longevity of the business (Cassia et
al., 2011). Consequently, founders might shy away from investing in new business development
(Zahra, 2005). This risk-averse behaviour and resistance to change might affect their innovative
behaviour and consequently R&D investments. They want to protect their legacy for future
generations. Founders of family firms favour their own children and family members over
competent employees (Chrisman & Patel, 2012).
Younger generation family firms feel the need to push for new ways to do things more than
older generation family firms (Kepner, 1991). The younger generation is more
innovation-oriented because they are more left free to innovate and long-term innovation-oriented (Litz & Kleysen,
2001). Young and relatively small start-ups engage intensively in R&D activities (Shefer &
Frenkel, 2005).
R&D investments are consequently a long-term investment (Chrisman & Patel, 2012). This
may yield competitive advantages associated with long-run success. Managers of family firms
may opt for this approach despite the associated risks (Chen & Hsu, 2009). Because of the
long-term orientation of younger generations, the family firm will become more innovation oriented.
That is why I propose the following hypothesis:
Hypothesis 3: Firm age has a negative effect on family firms’ R&D investment.
Methodology
As mentioned by Van Aken, Berends & Van der Bij (2012), a theory testing approach should
be used if the literature streams are already elaborated and not scattered, but there is still a
literature gap in the theoretical explanations. In the following section the measurement of the
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Data collection
In order to test the hypotheses mentioned in the literature review, an already available survey
is used. At the beginning of 2017 (February) an email was send to a sample of SMEs located
in the North of the Netherlands with an invitation to participate in the ‘Benchmarking innovation in the North of the Netherlands project’. Most of the questions in the survey are
based on the Community Innovation Survey (CIS). The CIS is a survey of innovation activity
in enterprises.
In 2017, the survey was send to 5447 SMEs and substantially completed by 624 companies.
This means that there is a response rate of 11,45%. Two students tried to increase the response
rate by calling the non-respondent firms in the beginning of March. The results presented in
this paper will be based on the responses of the participating companies. 49,7% of these
companies are family firms. 50,3% of the companies are non-family firms.
Variables
Dependent variable family firms’ R&D investments R&D investments will be
measured by asking firms (1) what percentage of the revenue was spend on internal R&D
activities, (2) what percentage of the revenue was spend on external R&D activities. For this
dependent variable the final questionnaire ‘Innovation benchmark North-Netherlands’ is used.
To measure the R&D investments, I will use the sum of these two questions to measure the total
percentage of R&D investments. I exclude 9 faulty responses who indicated spending more
than 100% of their revenue on R&D activities.
Independent variable market dynamism When measuring market dynamism, a set of
five statements is used. The statements are rated on a 5-point Likert scale ranging from very
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market there are continuous changes.’ ‘Not a lot changes in our market during the year.’ ‘In our
market, volumes and delivery rates of products and services change quickly and regularly.’ These statements are derived from the final questionnaire ‘Innovation Benchmark North
Netherlands’.
Independent variable cooperation Cooperation is measured by asking firms if they
cooperated with different types of partners in the period 2014-2016. This question is derived
from the Communication Innovation Survey (CIS) and used in the final questionnaire ‘Innovation Benchmark North Netherlands’. The type of partners are (1) customers (2)
consultancy firms (3) suppliers (4) direct and indirect competitors (5) universities (6) companies
in another sector. Firms are asked whether they cooperated with the partners on a binary yes/no
scale.
If the firm cooperated with a partner, the variable measure reads a ‘1’. If the firm did not
cooperate with a partners, the variable measure reads a ‘0’. In order to use the variable in the
analysis, the paper created a count variable by summing up all the different partners. So the
count data can vary from 0 to 6 as 6 partners are identified in the questionnaire.
Independent variable firm age For this independent variable I use the final
questionnaire ‘Innovation Benchmark North Netherlands’. I asked firms to fill in the year of
establishment of their firm. To use this data, this paper adjusted the data for the measured year
by subtracting the year of establishment of the year this paper is written, 2017.
Control variables In this paper I will control for a number of variables that possibly
can influence R&D investments. The variables this paper is controlling for are introduction of
new product innovation, introduction of new process innovation, education level and firm size.
Introduction of new product innovation is measured by asking firms if they introduced any new
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innovation is measured by asking firms if they introduced any new or strongly improved
services during the period 2014-2016. These questions are derived from the Communication
Innovation Survey (CIS). Whether a firm introduced a new innovation or not can influence the
R&D investments of that firm. For the control variable education level, this paper looked at the percentage of FTE’s in the firm that had a high level education (HBO/WO). Education level
can control for R&D investments because a high level education can foster innovation (Stam &
Wennberg, 2009). Firm size is measured in number of employees in full time employments (FTE’s). This variable has a range from 0 to 250 FTE’s. The range of 0-250 FTE’s is the most
common used range to define an SME (Ayyagari, Beck & Demirguc-Kunt, 2007). Firm size
can influence family firms’ R&D investments because large firms are more likely to secure the
funding that is needed to improve R&D (Ettlie & Rubenstein, 1987).
Method selection
For this paper, a theory-testing approach is followed as the literature field is already elaborated,
not scattered as mentioned before. For the conceptual model, the most appropriate method to
use is the Poisson regression or the Negative Binomial regression. These tests are used to
measure a dependent variable which consists of count data with a high number of zero’s. R&D
investments is positively skewed with a skewness of 2,35.
If you want to use the Poisson regression, the mean and the variance of the dependent variable
have to be similar. The difference between the Poisson regression and the Negative Binomial
regression is that the Negative Binomial has a dispersion parameter. This dispersion parameter
adjusts the variance independently of the mean, hereby overdispersion is taken into account
(Gardner, Mulvey & Shaw, 1995; Lawless, 1987). Our dependent variable family firms’ R&D
investments has a mean of 13,56 and a variance of 21,47. So in this case the Negative Binomial
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In order to use the Negative Binomial Regression, a few assumptions have to be met. First, as
mentioned before, the dependent variable has to exist of count data with a high number of zero’s. R&D investments. From the 483 firms that filled in the questions about R&D
investments, 173 firms answered that they don’t spend any revenue on R&D investments. So
there are 173 zero’s in the variable. Count data is data, you can count instead of rank, also count
data can’t have measurements below 0. As we measure R&D investments in percentage of
revenue, we can state that this is count data. Lastly, independence of observations is required
when applying the Negative Binomial regression. As all the firms independently filled in the
questionnaire, this paper can state that there indeed is an independence of observations.
Results
Before starting to analyse the data, this paper first recoded the variable market dynamism. A
set of five statements is used as a measurement for market dynamism. Factor analysis showed
that the five statements are indeed part of the same factor. The Cronbach Alpha of all the five
items is 0,779, this means is it allowed to combine the statements. Therefore by using factor
analysis a new variable is made to combine the statements.
Descriptive statistics and correlations
As seen in table 1 below, the mean of the dependent variable R&D investments is 13,56. This
implies that family firms on average spend 13,56% of their revenue on internal and external
R&D activities. A standard deviation of 21,47 implies that the variation of R&D investments is
high. 173 family firms answered that they do not spend any revenue on R&D investments. As
reported in the table, the mean of firm size 19.82. This implies that family firms on average have 19,82 FTE’s with a standard deviation of 33.46.
Also remarkable is the high variation of high educated FTE’s in family firms. 36,83% of FTE’s
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mean of 29,98 with a standard deviation of 36,23. Firm size has a mean of 19,82 with a standard
deviation of 33,46. When looking at cooperation, the table shows that the mean is 2,14 and the
standard deviation is 1,79. the count data of cooperation can vary from 0 to 6. So a mean of
2,14 is quite low and means that most firms do not cooperate with a lot of partners.
By looking at the correlation analysis, a first indication of interaction between variables is
provided. As shown in the table, almost all variables correlate with the dependent variable R&D
investments. Market dynamism is the only variable that does not correlate with R&D
investments. Also the correlation between firm size and firm age (0,389**) is quite high. In the
table below, you can find the means, variances and correlations of all the variables used in this
paper.
Table 1. descriptive statistics and correlation analysis
Variable Mean S 1 2 3 Correlations 4 5 6 7 8 1 R&D investments 13,56 21,47 1,000 2 Firm age 29,98 36,23 -,243** 1,000 3 Market dynamism -0,25 1,02 ,016 ,030 1,000 4 Cooperation 2,14 1,79 ,146* ,005 -,037 1,000 5 Introduction of product innovation 1,46 0,50 -,303** -,037 -,033 -,267** 1,000 6 Introduction of process innovation 1,50 0,50 -,154* ,116 -,205** -,142* ,195** 1,000 7 Education level 36,83 33,77 ,340** -,295** -,045 ,094 ,054 -,159* 1,000 8 Firm size 19,82 33,46 -,149* ,389** ,074 ,035 -,155** -,045 -,263** 1,000
* Correlation is significant at the 0,05 level ** Correlation is significant at the 0,01 level
Hypotheses testing
Table 2 presents a summary of the results of the Negative Binomial Regression. The omnibus
test shows that the overall model is significant and therefore a good fit. Model 1 only includes
our control variables. All the control variables correlate significantly and positively with R&D
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positive significant relation between introduction of a process innovation and family firms’
R&D investments disappears.
In model 2, the independent variables are added to the model. Hypothesis 1 presents the
relationship between market dynamism and family firms’ R&D investments, comparing the
ordinal data from market dynamism with the count data from R&D investments. In model 2 it
is clear that there is no significant relation between cooperation and family firms’ R&D
investment. So, hypothesis 1 will be rejected.
Hypothesis 2 presents the relationship between cooperation and family firms’ R&D investment.
In model 2 there is no significant relation between cooperation and R&D investments. This
means that hypothesis 2 will be rejected.
Hypothesis 3 presents the relationship between firm age and family firms’ R&D investments.
In model 2, there is a negative significant relation between firm age and family firms’ R&D
investments (p<0,05). This indicates that older firms invest less in R&D (β =-0,008).
Hypothesis 3 is therefore supported
Table 2. Negative Binomial Regression for Family firms
Variables Model 1 Model 2
β SE β SE Control variables Introduction of product innovation 1,099** 0,193 1,114** 0,202 Introduction of process innovation 0,499** 0,195 0,314 0,217 Education level 0,012** 0,002 0,911** 0,003 Firm size -0,003 0,003 0,000 0,003 Independent variables Market dynamism 0,130 0,099 Cooperation 0,020 0,052 Firm age -0,008** 0,003 N 145 145 Wald chi-square 124,72 100,13 Log-likelihood -501,977 -496,836
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In table 3, another Negative Binomial Regression is performed. In this table the results are
shown for non-family firms. When analysing this table, noticeable is that there are differences
and similarities between family firms and non-family firms.
When looking at the control variables the significant effects of introduction of product
innovation, introduction of process innovation and education level are the same in table 2 in
comparison with table. However as shown in model 2 of table 3, there is a negative significant
effect between firm size and R&D investments. In table 2, this effect is nonsignificant.
When looking at the independent variables, the differences between family firms and
non-family firms are noticeable. The significant effect between firm age and non-family firms’ R&D
investments as shown in table 2, is non-existent in table 3. There is no significant effect between
firm age and the R&D investments of non-family firms. However, there is a positive significant
effect between market dynamism and R&D investments of non-family firms (β=0,234).
Furthermore, there is a positive significant effect between cooperation and R&D investments
of non-family firms as shown in model 2 of table 3 (β=0,275). When looking at table 2, there
is no significant effect between market dynamism and family firms’ R&D investments or
between cooperation and family firms’ R&D investments. This means that when non-family
firms operate in a dynamic market, they will invest more in R&D. Also, when non-family firms
cooperate with a lot of partners, the R&D investments will go up. For family firms, this effect
21
Table 3. Negative Binomial Regression for non-family firms
Variables Model 1 Model 2
β SE β SE Control variables Introduction of product innovation 0,579** 0,188 0,401* 0,194 Introduction of process innovation 0,090 0,192 -0,220 0,205 Education level 0,017** 0,003 0,014** 0,003 Firm size -0,008** 0,002 -0,006** 0,003 Independent variables Market dynamism 0,234* 0,101 Cooperation 0,275** 0,056 Firm age -0,005 0,005 N 133 133 Wald chi-square 79,34 36,30 Log-likelihood -501,977 -490,917
* Correlation is significant at the 0,05 level ** Correlation is significant at the 0,01 level
Post hoc analyses
Additionally, I researched if there is an interaction effect between the different independent
variables. The interaction effect is shown in table 4 and table 5. I tested the interaction effect
for all the three independent variables. As shown in the tables the interaction effect is tested for
family firms and non-family firms. In model 3, the interaction effect between market dynamism
and cooperation is tested. In model 4, the interaction effect between market dynamism and firm
age is tested. Lastly, in model 5, I tested the interaction effect between cooperation and firm
age.
As shown in table 4, the interaction effect between market dynamism and cooperation is
significant (p<0,01) in model 3. The interaction effect in model 3 is a negative interaction effect
(β=-0,142). Below, the interaction effect is shown in a figure in order to interpret the effect.
Furthermore there is no interaction effect found between market dynamism and firm age. In
22
Table 4. Negative Binomial regression: Interaction effects for family firms
variables Model 1 Model 2 Model 3 Model 4 Model 5
β SE β SE β SE β SE β SE Control variables Introduction of product innovation 1,099** 0,193 1,114** 0,202 1,020** 0,204 1,086** 0,202 1,113** 0,201 Introduction of process innovation 0,499** 0,195 0,314 0,217 0,148 0,223 0,325 0,217 0,306 0,219 Education level 0,012** 0,002 0,911** 0,003 0,013** 0,003 0,011** 0,003 0,011** 0,003 Firm size -0,003 0,003 0,000 0,003 -0,001 0,003 0,000 0,003 0,000 0,003 Independent variables Market dynamism 0,020 0,052 0,486** 0,158 0,020 0,133 0,134 0,099 Cooperation 0,130 0,099 0,061 0,053 0,024 0,052 0,005 0,066 Firm age -0,008** 0,003 -0,008** 0,003 -0,009** 0,003 -0,009* 0,004 Interaction effect Market dynamism X Cooperation -0,142** 0,051 Market dynamism X Firm age 0,003 0,002 Cooperation X Firm age 0,001 0,002 N 145 145 145 145 145 Wald chi-square 124,72 100,13 84,03 97,51 81,72 Log-likelihood -501,977 -496,836 -492,837 -496,046 -496,768
* Correlation is significant at the 0,05 level ** Correlation is significant at the 0,01 level
The interpretation of the interaction effect can be found in figure 1. Because the interaction
effect between market dynamism and cooperation is significant, a graph was made in order to
interpret the effect. When looking at the figure, it shows that when market dynamism is low,
R&D investments will go up when the level of cooperation increases. On the other hand, when
there is a high level of market dynamism, R&D investments go down when the level of
23
Figure 1. Interaction effect
As shown in table 5, there are no significant interaction effects between market dynamism and
cooperation or between market dynamism and firm age. This is different from table 4 where a
significant negative interaction effect between market dynamism and cooperation on R&D
investments for family firms was found. The interaction effect between market dynamism and
firm age is not significant as well. This result is in line with the result for family firms in table
4. In model 5 is shown that the interaction effect between cooperation and firm age is not
24
Table 5. Negative Binomial regression: Interaction effects for non-family firms
Variables Model 1 Model 2 Model 3 Model 4 Model 5
β SE β SE β SE β SE β SE Control variables Introduction of product innovation 0,579** 0,188 0,401* 0,194 0,401* 0,194 0,433* 0,195 0,403* 0,194 Introduction of process innovation 0,090 0,192 -0,220 0,205 -0,218 0,206 -0,201 0,205 -0,220 0,205 Education level 0,017** 0,003 0,014** 0,003 0,014** 0,003 0,014** 0,003 0,014** 0,003 Firm size -0,008** 0,002 -0,006** 0,003 -0,006** 0,003 -0,007** 0,003 -0,006* 0,003 Independent variables Market dynamism -,275** 0,056 0,229 0,131 0,334* 0,139 0,236* 0,103 Cooperation 0,234* 0,101 0,274** 0,058 0,280** 0,056 0,282** 0,135 Firm age -0,005 0,005 -0,005 0,005 -0,006 0,005 -0,005 0,008 Interaction effect Market dynamism X Cooperation 0,003 0,056 Market dynamism X Firm age -0,006 0,005 Cooperation X Firm age 0,000 0,003 N 133 133 133 133 133 Wald chi-square 79,34 36,30 35,51 97,51 Log-likelihood -501,977 -490,917 -490,916 -496,046
* Correlation is significant at the 0,05 level ** Correlation is significant at the 0,01 level
Robustness checks
To make sure that the results in this paper are also significant when performing the tests in a
different way, a few robustness checks are performed. First, when looking at the variable
cooperation, there is another way of measuring this using the final questionnaire ‘Innovation
Benchmark North-Netherlands’. To measure cooperation, firms were asked: ‘Has your
company collaborated with other companies or institutions for its innovation activities in the
period 2014-2016?’ Cooperation is measured on a binary yes/no scale. If the firm collaborated with other firms or institutions, the variable measure reads a ‘1’. If the firm did not collaborate
25
when applying this alternative measurement. The relation between firm age and family firms’
R&D investments is still significant and also the interaction effect between market dynamism
and cooperation on family firms’ R&D investments is still significant. All the other effects are
insignificant.
The second robustness check this paper performed was excluding the variable firm size from
the analyses. As shown in table 1, the correlation between firm size and firm age is quite high
(0,389**). By excluding firm size in the Negative Binomial regression, I will check if the
results of the analyses are robust. Looking at the results without the variable firm size, no
significant changes are spotted. This means that the results of the analyses are robust.
Discussion
For this study, different effects on family firms’ R&D investments were researched. One of the
hypotheses is supported, where as other hypotheses got rejected. First, there was no significant
relation between cooperation and family firms’ R&D investments. This is in contradiction with
the hypothesis in which this paper predicted that there would be a positive relationship between cooperation and family firms’ R&D investment. I predicted that this relationship would be
positive because the resources and knowledge gained from external cooperation can contribute
to the stimulus and capacity to innovate of a family firm (Hewitt-Dundas, 2006). When looking
further into the literature the article of Acquaah (2012), stated that that on the one hand family
firms have an actively involved management, nonetheless, they are also considered to have an
inexperienced and ineffective management. So, family firms can be involved in external
cooperation networks, nonetheless if you do not use those networks effectively they will not
have value for the firm.
Also, no significant effect was found between market dynamism and family firms’ R&D
26
R&D investments. According to literature, it is important to stay involved in a dynamic market
(Eddleston et al., 2008). By use of R&D investments, it is possible for family firms to adapt to
the changing circumstances in the market (Volberda, 1996). However this statement is not
supported in this research.
Furthermore, this paper found a negative significant effect between firm age and family firms’
R&D investments. This confirms the literature saying that there is a difference between younger
generations involved in the family firm and older generations (Zahra, 2005). By focusing on
protecting their legacy, older family firms may miss the opportunity to invest in R&D and be
more innovation-oriented (Zahra, 2005).
By analysing the results, the research question can be answered. For one part of the research
question it can be stated that there is a significant effect on family firms’ R&D investments as firm age showed a positive significant relation with family firms’ R&D investments. The
Negative Binomial regression showed a small but significant effect (β=-0,008), whereas no
significant relations were found for the other variables. Concluding, to answer the research
question, this paper states that firm age is the only variable that affects the R&D investments
of family firms.
In the results section, on top of the results between the different variables and family firms’
R&D investments, this paper looked at the results for non-family firms. A comparison is made
between family firms and non-family firms. Here we can see that there are differences between
the relationships with R&D investments between family firms and non-family firms. Family
firms and non-family firms differ a lot in how they manage their organizational structures,
entrepreneurial orientation, risk taking and innovation (Naldi et al., 2007). So, it is not that
uncommon that the results between family firms and non-family firms differ. Whereas family
short-27
term profit maximization (Acquaah, 2012). A remarkable difference was that in non-family
firms, a significant relation was found between cooperation and R&D investment, whereas in
family firms this relationship was not significant. When the level of cooperation go up the
investments in R&D for non-family firms will go up as well. Moreover, the relation between
market dynamism and R&D investments was found positively significant. So when non-family
firms operate in a highly dynamic market, there investments in R&D will go up. Lastly, no
relation was found between firm age and R&D investments. So firm age does not have an effect
on the height of R&D investments of non-family firms. Whereas this relationship had a positive
significant effect for the R&D investments of family firms. This may be caused by the
long-term orientation of family firms. The strategy of family firms is more focused on being cautious
and stable, whereas non-family firms may be more progressive and dynamic (Chrisman & Patel,
2012). Because of this strategy, non-family firms might take more risk overall, not taking in
mind the age of the firm. Because of differences in ownership structure of family firms and
non-family firms, different outcomes can occur because they make different choices (De Massis
et al., 2012). Non-family firms focus more on profit and economic measures to main the firm,
whereas goals of family firms are more focused on protecting and maintaining the family
members (Cassia et al., 2011).
This paper performed post-hoc analyses where the interaction effect between the independent
variables was tested. In table 3, an interaction effect was found between market dynamism and
cooperation. In figure 1, the interpretation of the interaction effect is shown, where we can see
that when market dynamism is low, R&D investments will go up when the level of cooperation
increases. The decision to cooperate with a diverse pallet of external partners depends on the
behaviour of main decisionmakers in a firm (Classen et al., 2012). So, the interaction effect
may be explained through the risk-taking behaviour of the family firm. In a dynamic market,
28
firm. When cooperating with external partners, there can be a risk of leaking information
(Belderbos et al., 2004).
Theoretical implications
This paper contributes to existing literature by analysing various variables that differentiate
family firms from each other. Hereby, this paper advances our understanding of family firms. I
used two mechanisms in order to develop the hypotheses, on the one hand long-term orientation
and on the other hand risk-averse behaviour. This paper provides an indication that older family
firms invest less in R&D than young family firms. Furthermore, this paper provides an
indication that market dynamism affects the relation between the level of cooperation and family firms’ R&D investments. This indicates that in a highly dynamic market, when the level
of cooperation goes up, this will result in declining R&D investments. Keeping in mind that
more research has to be done to and this research is a small contribution in the field of research
on family firms. This paper filled in the literature gap of the heterogeneity of family firms
towards their R&D investment behaviour. This paper provided evidence by looking at different
variables in the field of family firms. By looking at the heterogeneity of family firms about
R&D investments in family firms (Chrisman & Patel, 2012), this paper contributes to existing
research.
Managerial implications
Regarding this research, this paper came up with managerial implications for family firms to
look into. A key finding of this research is that older firms invest less in R&D. R&D investments
are a long-term investment that focuses on innovation within the firm. As a firm it is important
to focus on R&D investments because these investments can benefit the firm in the long-term.
A characteristic of family firms is that they are focused on growth and survival to pass on their
29
longevity of the family business. Therefore, it is important for managers of a family firms to
invest in R&D, even when the result is not immediately showable. It can eventually ensure the
longevity of the business. By better control and evaluation, family firms can calculate the
risk-taking beforehand in order to minimize the risk (Naldi et al., 2009). However, risk-risk-taking cannot
be entirely controlled by a firm, it is also about being flexible and informality, so family should
not try to control everything (Naldi et al., 2009).
Limitations and future research
Regarding to this research, a few limitations and future research subjects were found that are
discussed below. The amount firms spend every year on R&D investments can differ. The ‘Innovation Benchmark North Netherlands’ is focused on the time period 2014-2016. If a firm
spends a lot of their revenue on R&D in one year. It can happen that in another year, the firm
wants to focus on developing another department of the firm. R&D investments are a risky
long-term investment. furthermore R&D requires a large amount of sunk-cost investment (Kor,
2006). So because of the sunk-costs that are part of the R&D investments, it might happen that
the amount firms spend on R&D is really diverse every year. This can have an impact on the
results. As already argued by Chrisman & Patel (2012), R&D investments are focused on the
long-term. Looking at R&D investments in a longer period, may give more reliable results.
Due to time and available resources, this paper was limited to SMEs in the north of the
Netherlands. Future research can focus on a larger region to see if the results would also be
robust when you apply them to different regions or larger regions. By focusing on a larger
region or a different country, the research can become more diverse. In this way, the results
become more reliable.
The measurement of R&D investments can differ from other methods and may influence the
30
investments by R&D investments divided by sales and R&D investments divided by assets.
Using multiple ways to measure a variable makes a research more robust.
Lastly, when looking at the results and the comparison between family firms and non-family
firms. It is confirmed that there are differences between the two types of firms. In future
research, the different outcomes in the different tables regarding the interaction effect between
market dynamism and cooperation on R&D investments can be further explored. When
performing qualitative research and using interviews as a research method, further research can
explore how come this interaction effect exists and why it is not applicable to non-family firms.
Conclusion
This study provides an insight in the research of family firms. The purpose of the study was to
provide statistical evidence for different variables on family firms’ R&D investments. To
conclude, this papers shows that firm age has a negative effect on R&D investments of family
firms. Furthermore, different significant results were found between family firms and
non-family firms, as cooperation and market dynamism have a positive significant effect on R&D
investments for non-family firms. Lastly, significant results were found in the interaction effect
between market dynamism and cooperation. Their long-term orientation helps them to focus on
innovation, but there risk-averse behaviour can hold them back and might make the firm
inefficient. This paper contributes to the literature of family firms by looking at heterogeneity
in family firms related to R&D investments. This study provides opportunities for further
research to look into the interaction effect between market dynamism and cooperation.
31
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