Innovation

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“Technological Interweavement: A
Means of Achieving Innovation
Success
ARTICLE in R&AMP D MANAGEMENT · MAY 2007
Impact Factor: 2.51 · DOI: 10.1111/j.1467-9310.1992.tb01206.x
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Technological interweavement: a means of achieving
innovation success
H. G. Gemunden, P. Heydebreck and R. Herden
Institute for Applied Management Science and Corporate Strategy, University
of Karlsruhe, Germany
Abstract
In this paper, results are presented of an
empirical study of the Lake Constance
region covering a sample of 848 manufacturing companies. Based upon multivariate
analyses, the paper documents that the
mobilization of external resources and
know-how is a critical factor for a firm’s
technological innovation success which in
turn is the main determinant of commercial
innovation success. The findings show that
there are three kinds of technology-oriented
external relationships, which prove t o be of
special importance: close contacts with
customers, linkages t o universities and
research institutes and R&D-cooperations
with other companies.
THE FlRM AND ITS PARTNERS
INNOVATlON PROCESS
IN
THE
‘No business is an island.’ (HBkansson and
Snehota 1989). Companies cannot acquire
all resources which are needed in the process
of production of goods and services exclusively through hierarchical relations, but are
dependent on external resources.
Apart from market and hierarchy there is
a third mode of obtaining resources: the
relationship. Relationships are seen as
‘longterm interorganisational interaction
processes and bonds with economic targets,
directed to a sequence of exchanges’
(Gemunden (1990), p. 34). They are of a
multiplex3 nature. In this article the focus is
on the technological dimension.
Technology-oriented external relationships are a strategic instrument beyond dayto-day business to exploit external resources
and know-how; they can enable the
company to meet the challenge of increased
R&D Management 22, 4, 1992
innovation-pressure and raising expenditures for R&D accompanied by shortening
product-life-cycles
and
time
based
competition.
Especially in regard to innovation,
relationships have potentials shown neither
by market nor by h i e r a r ~ h y : ~
0
Synergy effects of value: The combination of internal and external
resources can result in a multicompetence-effect, which facilitates the
development of products of superior
quality. Furthermore, relationships
constitute an instrument to reduce
redundancies (e.g. parallel research
activities) and accelerate innovation
processes.
‘Many authors (e.g. Dirrheimer and Hubner (1983),
Kumpe and Bolwijn (1988)) find decreasing rates of
vertical integration. Miles and Snow (1986) foresee
even more disintegration. Based on the transactioncost paradigm, Picot (1991) discusses how to determine the optimal degree of vertical integration.
’The idea of relationships as a third mode of
obtaining resources constitutes the key element of
the interaction approaches. These approaches
emerged in the sixties (cf. e.g. Johanson (1966)). An
extensive overview of existing literature is given by
Schrader (1991). The interaction approaches form
the basis for the more complex network approaches
which d o not focus on a dyadic relationship but on
the interdependencies between different relationships (cf. e.g. Axelsson and Easton (1992);
Hikansson (1987); Hagg and Johanson (1982);
Johanson and Mattsson (1985)). Based upon Coase
(1937, 1972) Williamson has developed an analytical
framework to study transaction cost economics (cf.
e.g. Williamson (1985)).
’The term ‘multiplex’ has been introduced by
Boissevain (1974), p. 30. It describes the multidimensionality of relationships (e.g. social, financial
or legal dimension, cf. Hammarkvist and
Hikansson and Mattsson (1982) or Paliwoda and
Thomson (1986)).
4 C f . Gemunden (1990), p. 27ff.
359
360
f
H . G. GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
Administration
3
Suppliers,
producers of mean
of production
0 Subsidy
0
Political support
Mediatims, transfer
0 New technologies of
f Research and trainin
institutes
Research
0 Training
0
components and systems
Complementary
Innovative concepts
Structuring of processes
0 Financial, legal and
insurance services
0 Joint basic research
0 Establishing standards
0 Getting subsidies
0
Figure I
Defining new requirements
0
Changing and weighting
The company in the innovation network
Depending on the companies’ objectives,
different partners will be favoured for interaction. Figure 1 illustrates which types of
resources and services supporting innovations are offered by different actors.
Several empirical studies (cf. e.g. Becher
et al. (1989), Hikansson (1989), Hagedoorn
(1990), Rotering (1990), Urban and
Vendemini (1986 and 1988)) show that
companies acquire external resources for
their innovation processes in many different
ways from a variety of actors. For instance
they may buy licenses or assign contract
research to engineer’s offices, universities
or research institutes or they may receive
information through informal discussions
with their vertical and horizontal market
partners and have R&D cooperations.
Schrader (1990) shows the high importance of interorganizational information
exchange.
Though it is often stated that the exploitation of synergy potentials through
cooperation becomes increasingly important
(cf. e.g. Benedetti (1987), pp. 68 and 70,
Zimmermann (1986)), there is a need for
empirical research testing the influence of a
’Though readiness for trust is generally higher in
relationships than in pure market interactions, trust
cannot be considered to be self-evident, Cf. e.g.
Hallen et al. (1989), Sabel (1990), Sandstrom (1990).
‘In this paper the ‘Fachhochschulen’ (similar to
colleges) are referred to as universities.
0
0
Synergy effects of cost: The partners
tend to develop mutual trust5 in longterm
relationships
resulting
in
decreasing transaction-costs, as the
expenditures for the search of new
interaction partners, contracting and
controlling can be cut down. Joint use
of resources can result in a decrease of
fixed costs, and effects of learning
curves too.
Network potentials: Partners can be
mediators or serve as references. Sales
opportunities will improve, if an
opinion leader becomes a buyer. Also
additional relations and resources can
be explored with the partners’ help.
R b D Management 22, 4, 1992
Technological interweavement
36 1
company’s technological interweavement on
its innovation success. 7
RELATIONSHIPS: AN INSTRUMENT TO
ENLARGE THE INTERNAL KNOW-HOW
POTENTIAL
Theoretical framework
The main purpose of this paper is to analyse
how a firm’s innovation success is determined by its technological interweavement .
But apart from the usage of external technological resources, there are a lot of other
factors which could have an impact on innovation success. Thus context variables (e.g.
firm strategy, R&D-intensity, industry,
location, size) could directly influence inno-
vation success or at least show an indirect
effect
by
influencing
technological
interweavement .
Innovation success is analysed both on a
technological and on a commercial level. It
is assumed that technological innovation
success (though not being a precondition’)
has a strong positive effect on commercial
innovation success.
Figure 2 illustrates the theoretical framework of the study.
Herden and Heydebreck (1991) give a
description of the relevance of different
types of technological interweavement and
test the influence of context variables on
technological interweavement.
This paper deals exclusively with the
Commercial
Innovation
Success
*
4
Technological Resources
Figure 2
Theoretical framework
’The influence of non-technological cooperations
on corporate growth has been investigated in several
studies (cf. e.g. Diller and Gaitanides (1989)) but the
impact of technological interweavement on success
has been largely neglected in empirical research. The
study of Hagedoorn and Schakenraad (1992) analysing the effects of strategic partnerships on success
is one of the few exceptions.
R&D Management 22, 4, 1992
I-
‘Even new products that d o not contain a better
technology than their predecessors might turn out to
result in a commercial innovation success (e.g.
fashion).
Vice versa the commercial innovation success
might influence the technological innovation success
by generating an innovative atmosphere and last but
not least the necessary financial resources but this
possibility is not analysed in this paper.
362
H. G. GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
explanation of innovation success. Only the
direct effects of context variables on innovation success have been taken into account,
for a presentation of the indirect effects
of context variables via technological
interweavement on innovation success, cf.
Herden (1991).
Hypotheses of the study
Product innovations can be flops mainly
because of two reasons. Either the technical
aims are not achieved or, what happens far
more often, the results of the development
process are satisfying in technical terms but
market receptivity is low because the
product doesn’t meet the targeted customers’ needs or because it is perceived as a
me-too product. Contacts with customers,
especially with lead user”, can help to
reduce both types of risk.
Lead users represent an important source
of technological know-how. They can do
R&D on their own and let their suppliers
participate in the knowledge, test prototypes
(cf. e.g. Biemans (1989, 1990)) or initiate
innovation processes of their suppliers by
defining new requirements or by suggesting
improvements of products already existing
(cf. Foxall (1984, 1986), Foxall and Tierney
(1984), Gemiinden (1990), pp 4ff, Herden
(1990), pp 75ff, Herstatt (1991), von Hippel
(1978a, 1978b, 1988), Parkinson (1982,
1985), Rothwell et al. (1974), Urban and
von Hippel (1988)). Cultivating the customers’ resources leads to a decrease of the
risk of technical failure.
The commercial risk is reduced as the supplier gains knowledge about his customers’
needs during his interaction with them, he
learns to estimate the market potential of
product ideas.
We therefore infer the following
assumption.
Hypothesis 1: Companies which regard and
use their customers as important sources of
innovation have higher technological and
commercial innovation success than other
companies .
“Lead users face needs that will be general in a
marketplace, but d o so months or years before the
greater part of that marketplace encounters them
(Hippel (1986)). In fact they not only recognise
future trends, but take part in forming them.
Cooperations between companies and
research institutes or universities usually
concentrate on the development of new products or processes, the implementation of
new technologies or the use of new
materials. More seldom the purpose of these
cooperations is improvement of products or
processes already existing. l 1 According to
the companies, cooperation with research
institutes and universities will still gain in
importance for the companies due to the
growing complexity of innovation processes
and the resulting need of complementary
external know-how. l 2
Research institutes and universities try to
expand the extent of their cooperations with
industry, too. l 3 The reasons for this trend
are the following:
Research institutes and universities feel
the necessity to acquire resources from
industry because of the growing budgetshortages.
Secondly, financial incentives for professors and researchers foster closer
contacts between research institutes,
universities, and industry. In BadenWurttemberg the Steinbeis-Stiftung
supports and mediates many R&Dcooperations between professors (especially from Fachhochschulen) and
firms. l 4
Cooperations with research institutes and
(technical) universities are usually developed
and maintained in order to solve technical
problems, and to secure the access to the
bottleneck-resource for many innovation
processes: highly qualified personnel. We
therefore assume that technological innovation success is strongly and directly influenced by cooperation activities with research
institutions whereas we d o not assume a
direct positive influence on commercial
“These are findings of an additional survey of 492
firms to be published later.
I’ Amendments of the ‘Hochschulrahmengesetz’
have opened new forms of cooperations with universities in Germany.
l 3 Cf. Allesch and Preifl-Allesch and Spengler
(1988).
l4 The Steinbeis-Stiftung is starting activities in
former East Germany, especially in Saxony.
R&D Management 22, 4, 1992
Technological interweavement
innovation success. This leads us to the following hypothesis:
Hypothesis 2: Companies which cooperate
with research institutes and universities have
higher technological innovation success than
those which don't cooperate.
In addition to customers, universities and
research institutes, other innovation partners such as suppliers, co-suppliers or competitors may constitute important sources of
innovative know-how. In this paper these
actors will only be considered, if the focal
company has some measure of (formal or
informal 15) R&D-cooperations with them. l6
For companies with compatible goals
and complementary
resources R&Dcooperations appear to be an appropriate
means to cultivate synergy potentials in
innovation processes because of the following reasons:
Innovation processes often require
interdisciplinary
know-how, which
seldom exists inside one single
company. The integration of new
technologies, e.g. microelectronics,
modern information and communication technologies or laser and sensor
technology, demands the creation of
knowledge and competence, which
often lie in a totally different field compared to their previous R&Dactivities.
The development of
internal competence on totally new
fields of technology is very often protracted and combined with high costs.
Therefore companies tend to acquire
such competence from external partners, whenever they don't consider the
363
new
knowledge
to
be
keytechnologies.
0
Innovations require investment, which
is often combined with considerable
uncertainty. In case the investors are
risk-averse, safe investments with low
net present value will be preferred to
investments in innovations even though
the latter might have a considerably
higher net present value. Cooperation is
not only a means of reducing the
absolute risk of failure by exploiting
synergy potentials and thus realising a
multi-competence-effect, but also splits
the risk on the partners, too. Through
this division of risk and costs the partners gain the opportunity to diversify
their innovation activities, in effect
they can put their eggs in more than one
basket.
In addition, it is assumed that R&Dcooperation has a direct effect on commercial innovation success. Cooperation
enlarges the possible fields of application,
thus increasing the possibilities to exploit the
new product or process (economies of
scope). R&D-cooperation with specific partners can foster commercial innovation
success in different ways:
'*
0
0
R&D-cooperation with co-suppliers can
be used as a starting point for coordinated marketing activities, based on
the joint goal of selling the complex
system.
R&D-cooperation with competitors or
the sale of licences are a way to establish new norms and standards and
thereby facilitate market penetration. l 9
We derive
Hypothesis 3: Companies which have established arrangements for R&D-cooperation
I5HBkansson (1989) studies more than 100 small
and medium sized Swedish companies, finding that
80% of the cooperations were informal. Large
companies tend to formalize their cooperations to a
much higher degree.
I6For an analysis of other innovation partners see
e.g. Herden and Heydebreck (1991), Herden (1991)
or Rotering (1990).
"The study of Pavitt et al. (1989) documents that
firms often d o research on different fields compared
to their production and selling activities. See also
Archibugi (1988).
R&D Management 22, 4, 1992
"Cf. Hausler (1990), who studies inter-industry
relationships between companies of the machinery
and the electronics industry.
l 9 That these forms of technology-oriented external
relationships are a very powerful means t o achieve
market success can be seen on the video market. By
selling licences at low prices to competitors JVC
managed to drive out other competitors offering
products of superior quality.
364
H. G. GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
with other Companies have higher technological and commercial innovation success
than companies which do not cooperate.
Though this paper concentrates on the
connection between technological interweavement and innovation success and corporate growth the following hypotheses on
the influence of internal and external context
variables on innovation success are also
tested in order to get an impression of the
relative importance
of technological
interweavement compared to context
variables.
Hypothesis 4: R&D-intensive companies
show higher technological and commercial
innovation success than other companies.
Though the cultivation of external technological resources is assumed to be vital for a
firm’s innovation success, internal R&Dactivities seem indispensable:
(1) The company does not only have to be
able to understand external input but
also to develop it further and adjust it
to its own needs.
(2) In order to be attractive a company
must have its own (preferably unique)
technological competence, which it can
offer its potential partners. Thus
companies with a strong internal competence get easier access to external
know-how.
Internal R&D-activities can be regarded as a
necessary but not as a sufficient precondition
for successful product innovations.
Hypothesis 5: Large companies show both
higher technological and commercial innovation success than small companies.
Large companies have advantages in
exploiting external resources because they
are more powerful than small companies.
For instance they may tie their suppliers to
them without being dependent on them and
force their partners to hand over their knowhow to them or even to put it at the disposal
of other suppliers, which often means providing competitors with know-how. ‘If that
doesn’t work, we have got the means to put
pressure on them.’20
Hypothesis 6: Innovation success is
industry-spec$c.
Companies from different industries are
influenced by very different surroundings.
For instance public schemes to promote
innovation are often orientated on single
industries or on fields of technology relevant
only for some industries. In addition the
necessity of innovation varies from industry
to industry. One reason for the differences
again is to be seen in governmental interventions (e.g. in the form of new laws in the
field of conservation) another by the varying
intensity of competition.
TEST DESIGN AND DATABASE
The steps of the analysis
A large database is a precondition for a multivariate quantitative test of the hypotheses
given above. Therefore a total survey of
all 4564 companies in the manufacturing
industry of the Lake Constance region*l has
been carried out, though neglecting
companies with less than five employees. 22
Eighteen per cent of the questionnaires
were returned. There are no substantial
systematic biases regarding the context variables ‘location’ and ‘industry’, but there is a
bias in regard to firm size. Large companies
show a higher willingness to reply than small
companies. If we assume that the 86% of
”This quotation from the Head of a Development
Division of a large manufacturing company makes
clear that even close relationships can be
characterised by exploitation rather than harmony.
On the German side, the population contains the
rural district of Constance, the chamber of commerce divisions Bodensee-Oberschwaben and
Lindau as well as the Bavarian Allgau. The population
furthermore
covers
the
principality of Liechtenstein, the Swiss cantons
Appenzell-Ausserrhoden, Appenzell-Innerrhoden,
Graubiinden, St. Gallen and Thurgau and
Vorarlberg in Austria.
”Companies with fewer than five employees have
been omitted mainly due to pragmatic reasons.
There is a lack of information on context variables
concerning these very small companies, so that no
tests on representativity of the returned questionnaires could have been made, which would have
been problematic because of the very low rate of
return such companies generally show. Furthermore, most of these companies don’t show great
interest in innovation.
‘’
R&D Management 22, 4, 1992
Technological interweavement
the returned questionnaires which contain
information about the number of employees
are representative for all returned questionnaires, the rates of return per group are as
follows:
up to 19 employees:
20-99 employees:
100-499 employees:
500 and more
employees:
9% rate of return
25% rate of return
38% rate of return
47% rate of return
By using a multivariate method of analysis
(logistic regression) it is possible to control
the influences of the variable ‘size of firm’,
so that the response-bias will not lead to
misinterpretations.
In addition to the mailed questionnaire,
interviews with both replying and nonreplying companies in the studied region
have been performed in order to get an
insight into the causal mechanisms behind
the correlations found in the quantitative
analyses. These interviews give the impression that there is no bias in the sample in
regard to technological interweavement and
innovation success. Besides, interviews with
suppliers of innovation-oriented services
have been carried out (e.g. with chambers of
commerce, universities, and research
institutes).
Operationalisation of variables23
Context. Indicators for the size of the frrm
are the number of employees and the sales
volume in 1989. As these indicators point
into the same direction in all analyses made,
in the following ‘firm size’ is exclusively
operationalized as ‘number of employees’.
This indicator has far less missing values
than ‘sales volume’ has. Four categories
have been formed (up to 19 employees,
20-99 employees, 100-499 employees, 500
and more employees).
In order to operationalise industry, four
categories have been formed: primary
industry, producers of industrial goods, producers of consumer goods and food and
beverage industry.
The indicators for the intensity of R&D
are the share of R&D employees of the
2 3 The operationalization is only given for those
variables included in the final model.
R&D Management 22, 4, 1992
365
whole staff and the R&D expenses in percent
of sales in 1989. As both indicators point in
the same direction throughout the analyses,
only the latter is presented in this paper.
Again the companies are divided into four
groups.
Group 1: R&D expenses in VO of sales: < 1%
Group 2: R&D expenses in Vo of sales:
1-3%
Group 3: R&D expenses in 070 of sales:
3-5%
Group 4: R&D expenses in 070 of sales: > 5%
Technological interweavernent. Three types
of technological interweavement have been
investigated more detail. The intensity of
cooperation between jirms and research
institutes and universities has been measured
by counting how many of the following
types of contacts existed between the
company and at least one research institute
or university:
demand for consultancy services on
marketing of new products,
demand for consultancy services on
technological problems,
0 participation in post-qualification seminars, workshops etc.
taking out of licences,
using laboratories jointly,
joint R&D-proj ects,
award of contracts on R&D,
acquisition of R&D-personnel,
acquisition of personnel (apart from
R&D),
temporary transfer of personnel to the
research institute or university.
In the multivariate analyses it is just
differentiated between companies maintaining contacts with research institutes or
universities and companies without such
contacts, whilst in the bivariate contingency
analyses, companies with zero, one, two,
and three different types of contacts each
form a separate category, while companies
with four or more contacts are combined in
one group.
Approximately one third of all companies
are already maintaining cooperations with
research institutes and universities, an
additional 9% are planning to establish such
cooperation.
366
H. G. GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
Concerning R&D-cooperations with other
companies we have simply scaled whether
firms cooperate in the field of R&D or not.
21% of the firms have reported such
cooperations. 24
A rating scale has been used to measure
the importance of customers as a source of
know-how for the development or utilisation of technologically improved or new
products or p r o c e ~ s e s . ~In~ the logistic
regression the variable is dichotomous, one
group is formed by the companies regarding
their customers at least as ‘helpful’ the other
group is formed by the companies which do
not regard their customers at least as
‘helpful’ for their innovation processes.
Efficiency. Technological innovation success
has been operationalised as to what extent
companies have taken up technologically
improved or new products (e.g. new
materials, new output functions) during the
last five years. Marginal improvements were
explicitly excluded. Three categories were
given: ‘no extent’ ‘limited extent’ and ‘considerable extent’. In the logistic regression
we only differentiate between companies
which have taken up new products to a considerable extent (about one third of the
companies) and those which have not.
In order to measure commercial innovation success the companies have been
asked what share of their sales volume they
realised through products introduced into
the market during the last five years.26 This
percentage has been directly taken as an
indicator for commercial innovation success
and has not been set in relation to the
average of a certain group of companies
(e.g. companies of one industry), because
this would imply that all groups (e.g. industries) show equal commercial innovation
success: the most innovative company in a
stable industry would be judged as innovative as the most innovative company in a
very fast changing industry. Instead of
eliminating the differences between e.g. the
24There is a bias in the sample towards large
companies. As larger companies cooperate more
often than small companies the percentage of
cooperating companies is overestimated.
25 The two extremes of the scale are ‘of no import’
and ‘necessary’.
industries’ level of innovativeness we therefore include ‘industry’ as an explaining variable for commercial innovation success in
our multivariate analyses.
In the logistic regression, commercial
innovation success is assumed for companies
who make at least 30% of their sales with
new products. This applies to about half of
the companies.
Because of the difficulties in obtaining
profitability ratios in written surveys we
have ascertained data on the corporate
growth. Companies showing at least 20%
growth of sales volume in the period 1986 to
1989 (half of the companies do so), and
respectively at least 25% growth of number
of employees (about 25% of the companies
do so) during the same time period are
referred to as growing. One has to be careful
when interpreting this indicator as it can
mean different things under different circumstances. Thus, it makes a difference
whether a company with two employees
grows 50% or whether a company with
2,000 employees grows 50%; the same holds
true for variables like, e.g. industry. We preferred not to include these variables in our
indicators but chose to look at them as
determinants of corporate growth instead.
The investigation shows an unexpectedly
high correlation between technological and
commercial innovation success (Kendall’s
tau-c = 0.425;
level
of
significance
CY < 0.005).
New products generally have higher
growth potentials than older products.
*’
*‘For industries with short product-life-cycles the
five-year period might be too long. In fact, two generations of the same product may be reported. A
shorter period would certainly make it easier for the
respondents to answer the question. Despite the
mentioned weaknesses of the quite long time period
we preferred it to the three-year period because we
have not focused on innovative industries but have
looked at the whole manufacturing industry. If we
used a time period considerably shorter than the
typical product-life-cycle a company’s percentage of
sales due to new products would be significantly
determined by the point of measuring. Furthermore,
the five-year period has been used more frequently
than the three-year period which opens more possibilities of comparing the results to the findings of
other studies.
27 Non-linear interaction effects have not been
tested.
R&D Management 22, 4, 1992
Technological interweavement
367
share of sales
made by new products
share of companies
with high growtl
D <lo%
a
10%-30%
30%-50%
250%
no
limited
considerable
extent of
technological innovation success
Figure 3
Innovation wccess and growth of sale?
Therefore it seems plausible to assume faster
growth for firms which make a large share
of their sales with new products than for
those firms which make nearly all their sales
with old products. However, do firms with a
high innovation success really show higher
company success in terms of growth of sales
volume and number of employees? Are our
measures of innovation success valid predictors of company success? Figure 3 illustrates
the empirical findings.
Neither technological nor commercial
innovation success alone is a guarantee for
overall success. It takes both technological
and commercial innovation success to grow.
These findings lead to the conclusion that
companies which attain a high percentage of
their sales by products that have only been
slightly improved, just try to defend their
market position, while realising a considerable share of sales by essentially improved
or totally new products turns out to be an
The influence of technological
interweave-interweavement and context
variables on innovation success
The relevance of customers for innovation
success. Seventy-five per cent of the
companies in the sample believe that dialogues with their customers had been at least
helpful for the development of technically
improved or new products or production
processes. Nearly 50% stated that the contacts with the customers had been a precondition for innovation success. 29 But do the
companies for which the information
exchange with their customers is of high
28 The correlation between innovation success and
growth of number of employees is not that clear but
tends into the same direction.
29 Missing values have been interpreted as ‘of no
relevance’, so that the importance of a close contact
with customers is probably underestimated.
R&D Management 22, 4, 1992
instrument for expansion into new markets
and therewith a means to stimulate growth.
DETERMINANTS OF INNOVATION SUCCESS
368
H. G. GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
60
50
extent of
technological
innovation success
40
share of companies [ % ]
0 none
30
limited
considerable
2c
10
0
very little
medium
high
stated relevance of information from
customers for the innovation
Figure 4
60
Technological innovatiin success and relevance of customers
'
50.
40
-
extent of
technological
innovation success
share of companies [ % I '
0 none
30.
limited
mconsiderable
20'
10'
0No
Yes
R&D cooperations
Figure 5
Technological innovation success and R&D cooperation with other firms
R&D Management 22, 4, 1992
369
Technological interweavernent
importance show a higher innovation
success?
The findings support hypothesis 1 .
Companies which stated that they get essential information for the development of new
products from their clients show an innovation success very significantly above
average. 30 Figure 4 shows that the relevance
of customers is very strongly correlated
with technological success (Kendall’s
level
of
significance
tau-c = 0.261,
a < 0.005). The correlation with commercial
innovation success is weaker (Kendall’s
level
of
significance
tau-c = 0.187,
a < 0.005).
R&D cooperations-a means of increasing
innovation success. Figure 5 documents that
hypothesis 2 is confirmed. Companies which
cooperate in the field of R&D have higher
technological success than those companies
not cooperating (Kendall’s tau-c = 0.241,
level of significance CY < 0.005). The same
holds true in regard to commercial innovation success, but the correlation is not that
strong (Kendall’s tau-c = 0.183, level of
significance CY < 0.005).
According to the companies studied R&D
cooperation will gain further in importance
as a means of increasing a firm’s
innovativeness. Though cooperation can be
a valuable means to complement a firm’s
internal resources it has to be taken into
account that problems can also arise. Ten
per cent of the cooperating companies mentioned that in at least one of their cooperative arrangements their partners put the
cooperation at risk through unfair conduct,
an additional 9% saw their cooperation
spoiled for this reason. Other problems
mentioned were: the partner’s lower technical competence and disagreements on the
exploitation of the outcome.
The study shows that large companies in
contrast to small companies mostly have
written contracts with respect to cooperation. An explanation for this observation
might be that large companies transfer their
30 Other bivariate analyses indicate the relevance of
using for instance suppliers or competitors as
sources of information. However, in multivariate
analyses these variables turn out to be insignificant.
R&D Mariageirienr 2 2 , 4. I992
high intraorganisational degree of formalisation3’ to their external relationships.
Contacts with research institutes and universities as a determinant of innovation success.
Hypothesis 3 is confirmed: with an
increasing number of different types of contacts to universities and research institutes
the companies show a higher technological
innovation success (Kendall’s tau-c = 0.260,
level of significance CY < 0.005). This finding
is illustrated by figure 6 .
The correlation between number of linkages to research institutes and universities,
and commercial innovation success is also
positive and significant. Our hypothesis was
more conservative.
Nearly all companies regard the benefit of
their cooperation with research institutes or
universities as ‘high’ or ‘very high’.32 Only
10% mention problems occurring during the
cooperation, mostly regarding the poor performance of universities in keeping
deadlines. 3 3
The injluence of context variables on
innovation success
R&D intensity. Hypothesis 4 is fully
confirmed by the empirical findings. R&Dintensive companies show higher commercial innovation success than firms with low
R&D-expenses in 070 of sales (Kendall’s tauc = 0.340, level of significance a < 0.005). 34
The question arises whether the maintenance of technology-oriented
external
relationships really influences innovation
success or whether the R&D intensity is
’’
Cf. Child (1975).
’*The synergy potentials of cooperations between
companies and universities have been illustrated in
e.g. Boyle (1986) and Cyert (1985).
”For an elaboration on problems of R&D cooperations between industry and universities cf. Geschka
and Alter and Schwerdtner (1975). It seems as if the
there mentioned problems (e.g. lack of confidential
or communication difficulties) have become less
important.
34 The correlation between R&D intensity and technological innovation success looks rather similar
(Kendall’s tau-c = 0.325; level of significance
a < 0.005).
370
H. G . GEMUNDEN, P. HEYDEBRECK AND R. HERDEN
6C
extent of
technological
innovation success
share of companies [ % ]
a
40
none
limited
considerable
20
0
none
one
two
three
four and more
number of different types of contacts
with universities and research institutes
Figure 6
Number of different types of contacts and technological innovation success
100
80
60
no R&D cooperation
share of companies [ % ]
with technological
innovation success
R&D cooperation
40
20
0
<1%
1%-<3%
3%-<5%
2 5%
R&D expenses in % of sales
Figure 7
R&D intensity and cooperation as determinants of technological innovation success
R&D Management 22, 4, 1992
37 1
Technological inter weavemen 1
decisive for innovation success and just ‘by
chance’ R&D intensive companies cultivate
external resources to a larger extent. In the
following this question will be analysed with
a multivariate design.
At this point a trivariate finding is presented indicating that cooperation as an
activity shows a significant influence on
innovation success even if R&D intensity is
simultaneously controlled. Figure 7 shows
that R&D cooperation can be a very
valuable means to extend the internal
resource potential especially for companies
with low R&D intensity.
Size of t h e j r m . Hypothesis 5 is confirmed
by the bivariate findings: Large companies
show higher technological innovation
success (Kendall’s tau-c = 0.218, level of
significance CY < 0.005). They even realise
higher commercial innovation success,
though the correlation is not as strong as
expected (Kendall’s tau-c = 0.092, level of
significance CY < 0.005).
Industry. Producers of industrial goods
develop new products and improve existing
ones more often than other manufacturing
companies. They even have higher commercial innovation success. Companies in the
food industry have astonishingly little innovation success. These findings are illustrated
in figure 8.
Multivariate analyses
Logistic regression. In order to decide which
of the analysed variables really have a specific influence on innovation success a multivariate approach has to be used. The
authors do not believe that innovation
success is a linear function of context variables or technological interweavement.
Integrating external technological knowhow in one way or another certainly
lengthens a company’s innovation potential
and it stimulates innovation success but on
the other hand it is assumed that there is a
limit to positive effects of cooperation. The
marginal utilities of increasing cooperation
are positive but decreasing. (It seems rather
implausible that companies cooperate that
much that the marginal utilities become
40
501
share of sales
made by new products
share of companies [ % I
0 <lo%
30
10%-30%
30Yo- 50 Yo
20
>50%
10
n
primary industry
industrial goods
consumer goods
food industry
industry
Figure 6
R&D Management 22, 4, 1992
Indusrr! and commercial innobation success
372
H. G . GEMUNDEN. P. HEYDEBRECK AND R. HERDEN
negative.) Therefore we decided to use a
non-linear model.
In this case the logistic regression35
appears to be appropriate. We use the
Exp(B)-values which indicate a change of the
ratio of successful to non-successful firms, if
a category is changed (in case of a dichotomous or polytomous independent variable)
or if a variable is increased by one unit (in
case of a metric independent variable).
Multivariate $findings. Concerning the influence of technological interweavement on
innovation success, the multivariate analyses
confirm the bivariate results: close contacts
with lead users, cooperations with universities and research institutes as well as R&D
cooperations with other companies all show
a highly significant influence on technological innovation success. 36 Thus they
indirectly lead to commercial innovation
success. A direct influence of exploiting
external resources on commercial innovation
success could only be found for the variable
'contacts to customers' but it only reached a
level of significance of CY =0.078. It will
therefore not be included in the empirical
framework. 37
Apart from these variables of technological interweavement, only R&D intensity
is significantly influencing the technological
innovation success: the more R&D intensive
a company is the more likely is it to show
technological innovation success.
In addition, R&D intensity has a direct
positive influence on commercial innovation
success. The multivariate analyses show that
industry, too, has a direct effect on commercial innovation success, 38 though the main
determinant is the technological innovation
success. Thus, technological interweavement, without having any direct influence,
indirectly strongly affects commercial innovation success.
Other context variables, e.g. size or
location, show neither a direct influence on
t
Growth of sales
Figure 9 Empirical framework"
3 5 F ~ ra detailed description of the logistic
regression see e.g. Hosmer and Lemeshow (1989).
36 Hagedoorn and Schakenraad (1992) found that
companies which maintain R&D-cooperation are
more likely to show a high share of net income in
total sales than companies without R&Dcooperation but they did not find a positive influence of cooperation on innovativeness. As their
indicators for innovativeness are input (R&Dintensity) as well as output oriented (number of
assigned patents) the construct innovativeness must
not be compared to our construct innovation success
which is a pure output indicator.
"The levels of significance for the direct influence
on commercial innovation success are as follows:
cooperations with universities and research institutes
a = 0.681, R&D-cooperations with other companies
a = 0.662.
38 Companies in the consumer goods industry realize
the highest percentage of their sales through new
products, followed by primary industry and the
industrial goods industry. In the food and beverage
industry the percentage of sales with new products is
very low, cf. appendix.
R&D Management 22, 4, 1992
Technological interweavement
technological nor on commercial innovation
success, but multivariate contingency analyses show that they strongly influence the
structure and intensity of a firm’s technological network, 39 which in turn influences
innovation success.
The commercial innovation success shows
significant influence only on growth of sales
not on growth of number of employees.
Growth of sales is probably the better indicator for overall success as efforts to reduce
costs can lead to a decrease of the number of
employees.
DISCUSSION AND OUTLOOK
Based upon multivariate analyses the study
documents that the mobilisation of external
resources is a critical factor of performance
for innovation processes. The findings are
based upon logistic regression, also taking
into account relevant context variables. A
follow-up study with 492 companies in the
chamber
of
commerce district
of
Schwarzwald-Baar-Heuberg supports the
relevance of technology oriented external
relationships for a firm’s innovativeness. 4 1
Firms which do not supplement their
internal resources and competence with
complementary external resources and
knowledge show a lower capability for realising innovations. Apart from a few exceptions
this
results
in
decreased
competitiveness against those companies
interwoven in technological networks. 42
There are indications that this is especially
valid for small and medium sized
companies, which have far greater problems
than large companies in acquiring qualified
personnel to develop and maintain internal
competence.
39Cf.Herden (1991) and Herden and Heydebreck
( 1991).
‘O For more detailed information see the appendix.
41
These results will be published in a future paper.
Under specific circumstances innovations need not
be necessary. Thus a distiller of whisky promotes his
products with the slogan: ‘We promise no( to
improve it’. The same holds true with respect to
process innovations. Another brand of whisky is
promoted with the slogan: ‘We devote the same time
to distil our whisky as we did a 100 years ago.’
R&D Management 22, 4. 1992
373
The findings raise questions of two kinds
which necessitate further research:
1.
What are the conclusions f o r public
policy?
How efficient can public fostering of
technological interweavement be? The
following measures could be analysed:
-founding of incubators,
-subsidizing institutions which stimulate and mediate technology transfer,
-giving grants t o cooperation projects,
-strengthening disadvantaged firms to
become
attractive
cooperationpartners (e.g. small and medium-sized
companies).
2. What are the conclusions for the
companies in accordance with:
-systematic search for partners,
-analyses of potentials and risks of
cooperation,
-treating of problems occurring in
cooperations,
-implementation and coordination of
relationships?
It is astonishing how strong the observed
correlations are in spite of the quite rough
operationalisation of innovation success.
Nevertheless future studies should try to
apply finer indicators, particularly for technological innovation success.
Our study has shown that technological
interweavement has an indirect influence on
commercial
innovation
success
and
company success via technological innovation success. However, we were not able
to quantify the strength of this effect, since
we applied a non-linear-model, i.e. logistic
regression. By using LISREL or other linear
structural models, one could estimate direct,
indirect and total effects. Besides, one could
differentiate between constructs and indicators, thus providing better controls for
measurement errors.
Another interesting subject is the analysis
of process innovations which have been
largely neglected in this study. Technological interweavement may have an even
stronger influence on innovation success as
our study has shown, because it can also
foster process innovations. On the other
hand, it might very well be that other types
of networks are required to develop or
374
H. G. GEMUNDEN, P . HEYDEBRECK AND R. HERDEN
improve processes compared to products.
For instance cooperation with suppliers and
co-suppliers might be of a higher importance
for process innovations than for product
innovations.
The study indicates that relationships
must not be regarded in isolation, but that it
is necessary to coordinate the relationships
through network management (e.g. a lead
customer might demand improvements of
the durability of a product which forces the
manufacturer to use new materials leading
to a change of the production process. A
cooperation with suppliers could help to
speed up the innovation process and to
reduce costs.). It would be interesting
to analyse whether there exist different types
of firms (e.g. ones that cooperate with customers and research institutes and ones that
cooperate with suppliers and competitors)
and find out under which circumstances
different types prove to be efficient.
APPENDIX
logistic regression commercial innovation success
with TECHSUCC (technological innovation success)
R&DINT (R&D-intensity)
SIZE (size of firm)
REGION (location)
IND (industry)
CUST (importance of customers)
COR&DUNI (cooperation with research institutes and universities)
R&DCOOP (R&D-cooperations with other companies)
/categorical R&DINT SIZE REGION IND
/method = fstep.
Variable
TECHSUCC
R&DINT
R&DINT 11I
R&DINT (2)
R&DINT (3)
IND
IND (1)
IND (2)
IND (3)
Constant
8
1.9040
- 0.3842
- 1.0078
- 0.0938
0.3352
0.2784
1.0241
-0.9148
Variables in the Equation
S.E.
Wald
df
0.2963
41.2990
1
26.8706
3
0.2340
2.6964
1
1
0.2453
16.8747
0.2372
0.1772
1
14.5402
3
0.2897
1.3387
1
0.2510
1.2300
1
0.281 5
13.2331
1
0.2553
12.8366
1
Sig
0.0000
0.0000
0.1006
0.0000
0.6738
0.0023
0.2473
0.2674
0.0003
0.0003
R
0.2971
0.2165
- 0.0396
-0.1828
Exp(8)
6.7130
0.0000
0.6810
0.3650
0.9050
0.1385
0.0000
0.0000
0.1 589
1.3982
1.3210
2.7847
R&DINT (1) is formed by the companies which spend < 1 % of their sales on R&D.
R&DINT (2) is formed by the companies which spend 1 %-3% of their sales on R&D.
R&DINT (3) is formed by the companies which spend 3%-5% of their sales on R%D.
R&DINT (4) is formed by the companies which spend > 5% of their sales on R&D, the Exp(B)-value is 4.41 85
(worked out as the residual effect, not calculated by the programme).
IND (1) is formed by the companies of the primary industry.
IND (2) is formed by the companies which produce industrial goods.
IND (3) is formed by the companies which produce consumer goods.
IND (4) is formed by the companies of the food and beverage industry, Exp(B) = 0.1944.
logistic regression technological success
with R&DINT (R&D-intensity)
SIZE (size of firm)
REGION (location)
IND (industry)
CUST (importance of customers)
COR&DUNI (cooperations with research institutes and universities)
R&DCOOP (R&D-cooperations with other companies)
/categorical R&DINT SIZE REGION IND
/method = fstep.
R&D Management 22, 4, 1992
375
Technological interweavernent
B
Variables in the Equation
Wald
df
S.E.
Sig
R
22.8072
3
0.0000
0.1921
-0.6790
0.2182
9.6802
1
0.0019
- 0.1298
1
0.01 61
-0.091 2
5.7924
-0.5231
0.2174
3.9406
1
0.0471
0.0653
0.4270
0.2151
.0020
0.1 285
1
9.5270
1.319 7
0.4276
0.1694
15.0730
1
0.0001
1.0218
0.2632
1
0.0048
0.1 1 4 4
7.9606
0.7813
0.2768
Constant
-1.8913
0.4327
19.1026
1
0.0000
R&DINT (1) is f o r m e d by t h e companies w h i c h s p e n d < 1% o f t h e i r sales on R&D.
R&DINT ( 2 ) is f o r m e d by t h e companies w h i c h s p e n d 1 %-3% of t h e i r sales on R&D.
R&DINT (3) is f o r m e d b y t h e cornanies w h i c h s p e n d 3%-5% o f t h e i r sales on R%D.
R&DINT ( 4 ) is f o r m e d b y t h e companies w h i c h s p e n d > 5 % of t h e i r sales on R&D, Exp(B) = 2.1708
Variable
R&DINT
R&DINT ( 1
R&DINT 12)
R&DINT ( 3 )
CUST
COR&DUNI
R&DCOOP
REFERENCES
Allesch. J . , PreiR-Allesch, D. and Spengler, U. (1988).
‘Technologie-Transfer-Hochschule und Wirschaft’, Bestandsaufnahme und Modelle der Zusammenarbeit, Koln.
Archibugi. D. (1988), ‘The inter-industry distribution of technological capabilities. A case study in the application of the Italian
patenting in the USA’, Technovation, Vol. 7, pp. 259-274.
Axelsson, B. and Easton, G. (1992), (eds) Industrial Networks. A
New’ View of Reality, London, New York: Routledge.
Becher, G . et al. (1989), ‘FuE-Personalkostenzuschusse:Strukturentwicklung, Beschaftigungswirkungen und Konsequenzen fur
die Innovationspolitik’, FhG-IS1 (ed.), Karlsruhe, Berlin.
Benedetti, C . de (1987), ‘Europe’s new role in a global market’, in
A. J . Pierre (ed.), A High Technology Gap? Europe, America
and Japan, New York: Council and Foreign Relations, pp. 67-87.
Biemanr, W. G . (1989), ‘Developing innovarions within networks-with
a n application to the Dutch medical equipment
industry’, Dissertation.
Biemans, W. G. (1990), ‘Manufacturer-user relationships in testing
newly developed prototypes’, paper presented at the 6th I.M.P.
Conference in Milano.
Boissevain, J . (1974). Friends of Friends: Networks, Manipulators,
and Coalitions, New York.
Boyle, K. A. (19861, ‘Technology transfer between universities and
the UK offshore industry’, IEEE Transactions on Engineering
Management, Vol. EM-33, pp. 33-42.
Child, J . (1975), ’Prognose und Erklarung von Organisationsstruktur’, in E. Grochla (ed.). Organisationstheorie, I , Teilband,
Stuttgart.
Coase, R. H . (1937), ‘The nature of the firm’, Economics. Vol. 4,
pp. 386-405.
Coase, R. H . (1972), ‘Industrial organization: a proposal for
research’, in v. R. Fuchs (ed.), Policy Issues and Research Opportunities in Industrial Organizations, New York.
Cyert, R. M. (1985) ‘Establishing university-industry joint ventures’, Research Management, Vol. 28, pp. 27-28.
Diller, H . and Gaitanides, M. (1989), ‘Vertriebsorganisation und
handelsorientiertes Marketing. Lohnt sich kooperatives Verhalten
gegenuber dem Handel?’, Zeitschrift fur Betriebswirtschaft, Vol.
6, pp. 589-608.
Dirrheimer, M. and Hubner, T. (1983), ‘Vertical integration and
performance in the automative industry’, paper presented at the
‘Future of Automobile Forum’, MIT, Boston.
Foxall. G . R. (1984), Corporate Innovation: Marketing and
Strategy, New York: St Martin’s Press.
Foxall, G. R. (1986), ‘A conceptual extension o f the customer-active
paradigm’, Technovation, Vol. 4, pp. 17-27.
Foxall, G. R. and Tierney, J. (1986). ‘From CAP1 to CAP2: userinitiated innovation from the user’s point of view’, Management
Decision, Vol. 22, pp. 3-15.
Gemunden, H. G . (1990), ‘Innovationen in Geschaftsbeziehungen
und Netzwerken’, working paper, Karlsruhe.
Geschka, H., Alter, U. and Schwerdtner, H.-E. (1975), ‘Effiziente
Urnsetrung wissenschaftlicher Erkenntnisse in die industrielle
Nutzung’, Berlin et al.
R&D Management 22, 4, 1992
ExpW
0.5071
0.5927
1.5326
3.7423
2.7782
2.1842
Hakansson, H. (1987), (ed.) Industrial Technological Developmenr:
A Network Approach, London: Croom Helm.
Hakansson. H . (1989), Corporate Technological Behaviour-Cooperarion and Networks, London: Routledge.
Hakansson, H . and Snehota, I. (1989), ‘No business is an island’,
Scandinavian Journal of Management, Vol. 5 , pp. 187-200.
Hagg. I. and Johanson, J. (1982), ‘Foretag i Natvefk-Ny Syn p i
Konkurrenskraft’. Stockholm: Liber.
Hausler, J . (1990), ‘Zur Gegenwart der Fabrik der Zukunft:
Forschungsaktivitaten im bundesdeutschen Maschinenbau’,
MPlFG discussion paper, Koln.
Hagedoorn, J. (1990), ‘Organizational modes of inter-firm cooperation and technology transfer’, Technovation, Vol. 10,
pp. 17-30.
Hagedoorn, J. and Schakenraad, J. (1992) ‘The economic effects of
strategic partnerships and technology cooperation’, Luxembourg:
Office for Official Publications of the EC (forthcoming).
Hallen, L., Johanson, J. and Seyed-Mohamed, N. (1989), ‘Relationships and exchange in international business’, Advances in International Marketing, Vol. 3 , pp. 7-23.
Harnmarkvist, K.-O., HIkansson, H . and Mattsson, L . 4 . (1982),
‘Marknadsforing for Konkurrenskraft’, Malmo: Liber.
Herden, R. and Heydebreck, P . (1991), ‘Innovation durch technologische Verflechtung’, FhG-IS1 (ed.), Karlsruhe.
Herden, R. (1990), ‘Die Bedeutung der zwischen- und uberbetrieblichen Zusammenarbeit als Voraussetzung fur das Entstehen und
die Entwicklung innovativer Produkte und Prozesse. Eine Untersuchung am Beispiel der feinmechanischen und optischen Industrie Baden-Wurttembergs’, FhG-IS1 (ed.), Karlsruhe.
Herden, R. (1991), ‘Struktur und Effizienz technologieorientierter
Aunenbeziehungen im betrieblichen lnnovationsmanagement’,
Dissertation, Karlsruhe.
Hippel, E. von (1978a) ‘A customer-active paradigm for industrial
product idea generation’, Research Policy, Vol. 7, pp. 240-266.
Hippel, E. von (1978b), ‘Successful industrial products from customer ideas’, Journal of Marketing, pp. 39-49.
Hippel, E. von (1986), ‘Lead users: a source of novel product concepts’, Management Science, Vol. 32, pp. 791-805.
Hippel, E . von (1988), The Sources of Innovation, New York,
Oxford: Oxford University Press.
Hosmer, D. W. and Lemeshow, S. (1989), Applied Logistic
Regression, New York.
Johanson, J . (1966), ’Svenskt Kvalitetsstll p i Utlandska Marknader’, Dissertation, Uppsala.
Johanson. J . and Mattsson, L . G . (1985), ‘Marketing investment
and market investments in industrial networks’, International
Journal of Research in Marketing, Vol. 2, pp. 185-195.
Kumpe. T. and Bolwijn, P. (1988), ‘Manufacturing: The New Case
for Vertical Integration’, Harvard Business Review, MarchApril, 75-81,
Miles, R. and Snow, C . (1986). ‘Organizations: new concepts for
new forms’, California Management review, Vol. XXVIII, No. 3,
pp. 62-73.
Paliwoda, S. J . and Thomson, P. (1986). ‘Industrial product class
and market behaviour: a study in the French packaging market’,
in P. W . Turnbull and S. J. Paliwoda, (eds), Research in International Marketing, London Sydney Dover: New Hampshire.
376
H. G. GEMUNDEN. P. HEYDEBRECK AND R. HERDEN
Parkinson, S. T. (19821, ‘The role of the user in successful new
product development‘, R&DManagemenr, Vol. 12, pp. 123-131.
Parkinson, S. T. (1985), ‘Factors influencing buyer-seller relationship in the market for high technology products’, Journal of Business Research, Vol. 13, pp. 49-60.
Pavitt, K . Robson, M. and Townsend, J. (1989), ‘Technological
assumulation, diversification and organisation in UK companies,
1945-1983’, Management Science, Vol. 35, pp. 81-99.
Picot, A. (1991), ‘Ein neuer Ansatz zur Gestaltung der Leistungstiefe’, Zeitschrift Fur betriebswirtschaftliche Forschung. Vol. 43,
pp. 336-357.
Rotering, C. (1990), ‘Forschungs- und Entwicklungskooperationen
zwischen Unternehmen’, Stuttgart: Poeschel.
Rothwell, R., Freeman, C., Horsley, A . , Jervis, V. T. P.,
Robertson, A. B. and Townsend, J. (1974), ‘SAPPHO
updated-Project SAPPHO Phase II’, Research Policy, Vol. 3,
pp. 258-291.
Sabel, Ch. S. (1990), ‘Studied trust: building new forms of cooperation in a volatile economy’, working paper.
Sandstrom, M . (1990), ‘Atmosphere in international business
relationships’, Licentiate Thesis at Uppsala University.
Schrader, S. (1990), ‘Zwischenbetrieblicher lnformationstransfer:
eine empirische Analyse kooperativen Verhaltens’, Berlin:
Duncker & Humblot.
Schrader, S. (1991), ‘Kooperation’, Beitrag fur die Festschrift
‘Empirische betriebswirtschaftliche Forschung’, (forthcoming).
Urban, G. L. and Hippel. E. von (1988), ‘Lead user analysis for the
development of new industrial products’, Management Science,
Vol. 34, pp. 569-582.
Urban, S. and Vendemini, S. (1986), ‘Enterprlses allemandes et
cooperation industrielles a l’echelle europeenne. Etudes et recherches du Plan’, No. 2. La Documentation Francaise, Paris.
Urban, S. and Vendemioi, S. (19881, ‘Les enterprises industrielles
italiennes et la cooperation internationale’, CESAG, Universite
Robert Schumann (ed.), Strasbourg.
Williamson, (1985), ‘The economic institutions of capitalism’, New
York: The Free Press.
Zimmermann, E . (1986), ‘Technologiekooperationene’, Zeitschrift
fur Betriebswirtschaft Erganzungsheft 1, pp. 225-233.
R&D Management 22, 4, 1992