Network Configuration and Innovation Success - An Empirical Analysis in German High-Tech Industries

Abstract

Assuming that intensity and structure are the most important dimensions of a firm's

technological network the authors identify seven different real types of technological

interweavement. Drawing upon a database of 321 high-tech companies they can

show that innovation success is significantly determinated by a firm's network

position, different innovation targets demanding for different types of

interweavement.

478


Table of contents

1 Network configurations and innovation success

1.1 Theoretical frame of reference

1.2 Real type network configurations

1.3 Hypotheses on the impact of network configurations on innovation

success

2 Empirical findings

3 Discussion and Outlook

List of References

479


1 Network configuration and innovation success

1.1 Theoretical frame of reference

"No business is an island" (Hakansson and Snehota 1989). Co-operation with

external partners will provide helpful if not necessary know-how and resources into

a company's innovation processes. Figure 1 illustrates potential innovation partners

and the functions they can fulfil.

Figure 1:

Innovation partners and their resources

(Source: Gemunden, Heydebreck and Herden 1992, p. 360)

Empirical research on the impact of collaboration with external partners on a firm's

product and process innovation success has mainly been carried out in the form of

case studies. Specific relationships between specific partners and their

connectedness have been studied in depth (see particularly the IMP work, cf. e. g.

Axelsson 1986; Hakansson 1987; Hammarkvist, Hakansson and Mattsson 1982).

Whenever large scale studies have been carried out, the level of abstraction was

changed from analysing the relationships between the focal company and specific

partners (e. g. supplier E, customer B, university G) to analysing the relationships

between a focal company and a specific set of partners (e. g. customers in general

or suppliers in general) (cf. e. g. Gemunden,Heydebreck, and Herden 1992; Hahn

et al. 1995). In these studies the central idea of the a network approach - namely the

interconnectedness of the relationships - has been neglected.-Thus, there is a high

demand for large scaled empirical studies analysing the strategic importance of a

network configuration matching a companies innovation aims. This paper is '

intended to tackel the challenging task of identifying real types of network

configurations and their adaquacy for persureing different innovation aims.

480

The configuration of a network is defined by two dimensions: the intensity (degree of

interaction with external partners regardless of the type of partners) and the pattern

(relative importance of collaboration for all types of partners in relation to the

collaboration with all other partners) of technological interweavement.

The authors assume that different innovation tasks require different network

configurations. In this paper, the suitibility of different network configurations for

different innovation aims is analysed.

Figure 2 illustrates the theoretical framework of this paper.

Figure 2:

Theoretical frame of reference

Innovation success in turn is an important determinant of a company's overall

economic success. The network configuration is determined by a large variety of

internal and external context factors, most of them can be grouped under the

headings of motivation and capability of networking. It is not the aim of this paper,

though, to test the possible influence of a firm's position in the value chain, its age,

size, and industry, the legal framework or the intensity of competition on the intensity

and pattern of technological interweavement. This paper focuses on efficiency

analyses, i. e.: What are the impacts of different network configurations on success

of product and process innovations? In particular, we are interested in the following

issues: Which network configurations are required for successful innovations? Do

product and process innovations require different configurations? Do minor

innovations require different configurations from major innovations?

The authors test their theoretical frame of reference drawing upon a database of

321 high-tech companies operating in the fields of microelectronics, edp, sensor

technology, biotechnology, and medical equipment. For a description of the

database see e. g. Gemunden and Heydebreck 1995; Heydebreck 1995; Ritter

1995.

481

1.2 Real type network configurations

In order to analyse the intensity and pattern of a firm's technological

interweavement a vast range of indicators of network dimensions have been

collected. An exploratory factor analysis resulted in four network dimensions

explaining 66% of the variance. Each factor describes collaboration with a specific

type of external partner:

factor 1 is called supplier-interaction factor.

factor 2 is called customer-interaction factor.

factor 3 is called university-interaction factor.

factor 4 is called consultant-interaction factor.

Allthough the factor analysis provides a very clear structure the factors are impure,

meaning they load on indicators not used for their interpretation. Therefore, the

authors performed four unifactorate analyses including only indicators with factor

loading higher than 0.50. Table 1 illustrates the four dimensions of interweavement.

Table 1:

The dimensions of technological interweavement

For a description of this analysis in more detail see Gemunden and Heydebreck

1995; Heydebreck 1995; Ritter 1995.

Intensity of technological interweavement

The authors operationalise the intensity of technological interweavement as the

average factor score of the four interaction factors. This measure represents the

degree of a company's network activity independent of the type of its partners. For

further analyses the authors only differenciate between four levels of intensity: very

low, low, high, and very high intensity, each group containing 25% of the

companies.

Patterns of technological interweavement

In order to identify real type patterns, the authors clustered the cases according to

their factor scores on the four network dimensions. As the focus lies on patterns a

similarity measures was used for the cluster analysis (cosine) together with

baverage as aglomeration (using SPSS procedure). With regard to the contens the

authors have chosen to interpret the five cluster solution, which was supported by

the elbow-criteria.

Figure 3 shows the real type patterns of technological interweavement. The radar

charts illustrate differences in the relative importance of the four types of external

partner. The grey square represents equal importance of all external partners.

Figure 3:

Radar charts of network patterns

As figure 3 shows, there are substantially different patterns of interweavement.

Network configuration: Combination of intensity and patterns

The following crosstable illustrates real combinations intensity and patterns of

technological interweavement.

Table 2:

Intensity and pattern of technological interweavement

Table 2 shows that intensity and structure do not seem to be fully independent of

each other. Whereas network pattern 3 highly correlates to a low intensity of

interweavement, patterns 4 and 5 correspond to a high intensity of technological

481

interweavement. The situation is less clearcut concerning patterns 1 and 2.

Therefore, the authors have chosen to interpret two network configurations for

pattern 1 as well as for patterns 2 (one with low and one with high level of intensity).

The following seven network configurations exist (names will be used in a further

documentation of analyses):

1. The island (intensity low or very low and pattern 3): Compared with all other

groups this cluster has the lowest intensity of interweavement. The strikingly

low importance of customer interaction is due to operationalisation, because

the importance is not measured in absolute terms but in relation to the

relative importance of customer interaction of all other network configurations.

In contrast to all other groups which regard the customer as their definetely

most important external partner, the island regards its customers only as

equally important as other partners.

2. The manufacturer (intensity low or very low and pattern 2): This type of

company interacts with suppliers and customers much more intensively than

with universities and consultants. Manufacturer are heavily production

orientated. The total degree of interaction with external partners is low.

3. The toddler (intensity low or very low and pattern 1): The toddler shows a low

intensity of technological interaction with its environment as well. But in

contrast to the manufacturer the toddler lays relatively more emphasis on

collaboration with universities than on supplier interaction.

4. The highway (intensity high or very high and pattern 2): The highway shows a

very similar pattern of interweavement to the manufacturer. The degree of

interaction is much higher, though. The shape of the network configuration

indicates a rapid flow of information and know-how from supplier to focal

company to customer and vice versa.

5. The visionary (intensity high or very high and pattern 1): The visionary

interacts with universities on a high level and regards his customers as even

relatively more important than its suppliers and consultants.

484

6. The apart the market (intensity low, high, or very high and pattern 5): This

type of company is the only group regarding utilisation of innovation

orientated consultancy services as important for their innovation success.

Apart from the island the apart the market shows the lowest intensity of

collaboration with suppliers out of all types. The interaction with customers

and universities is at an average level.

7. The spider (intensity high or very high and pattern 4): The spider interacts

with all network partners at a very high level. (The two cases with intensity 2

and pattern 4 were rejected because low intensity seems not to be typically

for this group.)

In the following, the authors discuss the impact of these network configurations on

innovation success.

1.3 Hypotheses on the impact of network configurations on success

There is no overall successful type of interweavement. That means that network

intensity and network patterns have to suit specific innovative targets of a company.

Customer interaction is necessary but not sufficient to achieve product innovation

success (cf. e. g. Biemans 1992; Gemunden, Heydebreck, and Herden 1992;

Herstatt 1991; Shaw 1985). Additional partners are needed to bring forward new

ideas (in high-tech industries especially universities and research institutes) or to

offer new production facilities or technically improved or new product components to

realize new ideas (for example suppliers). Different combinations support different

innovations steps, for example the highway is more likely to support improvements

of existing products whereas the visionary promotes greater product innovation

steps. In addition, the authors assume that the highly interwoven spider is

particularly capable of achieving all kinds of product innovation success.

485

Hypothesis 1:

For technological product innovation success a high overall intensity of a network

and a prominent position of the customer is necessary.

In order to rapidly and efficiently improve existing products collaboration with the

suppliers is of critical importance. Therefore, the authors believe that the highway

and the spider have higher innovation s.upcess in regard of product improvements

compared with all other types of companies, (hypothesis 1 a)

In order to establish new technology platforms outstanding technological resources

and know-how from different disciplines are needed. Universities and research

institutes are particularly apt as external partners in bregk-throuqh product

innovation processes. Both suppliers apd consultants are of secondary importance

only. Therefore, visionaries and spiders are believed to realise a product innovation

success fin regard to radically new products) much higher than all other cornpany

types, (hypothesis j I?)

A lot of partners can provide valuable know how in order to stimulate process

innovation. Consultants have theoretical knowledge of best practice and are able to

assist during the implementation phase of new processes. In addition, customers

can show a company's weaknesses in processes too. Therefore, consultants and

customers can near to force companies to realise process innovations.

As suppliers promote new product ideas they also could have a positive effect in

providing new equipment to reduce production costs or decrease processing time.

Empirical studies have also shown the positive impact of universitiy interaction on

process innovations. The authors assume that suppliers and universities help a

company to overcome technical barriers to process innovations.

For these reasons, all network configurations interacting at a high or very high

degree are appropriate to support process innovations. But as developed above,

the highway and the visionary are strongly focused on product innovations and

therefore the authors expect the apart the market and the spider as best network

configurations for process innovations.

486

Hypothesis 2:

For technical process innovation success high intensity and a network patterns with

stress on customer or consultant and in addition on supplier or university is needed

(the apart the market and the soiderl

The authors assume that companies striving for process innovations will use

consultancy agencies for analysing processes and recommending partners for

problem solution. On the other hand, if process innovation is a main part of a

firm'scorporate strategy a company does not need consultants, because these

companies are very conscious about process innovations. They interact with

partners providing direct help for realising process innovations.

Hypothesis 3:

Consultant orientated networks or generally highly interwoven companies (the apart

the market and the spider} are particularly successful in realising economic profit

from rationalising their processes.

2 Empirical Findings

Table 3 provides an overview of the indicators used for measuring innovation

success.

Table 3:

Operationalisation of innovation success indicators

In the following, the authors test the hypotheses on the impact of a firm's network

configuration on innovation success. Regression analyses with configuration coded

as dummy-variables were carried out in order to test the influence of network

configuration on success. In all regression analyses the island was taken as the

reference group. In these analyses the variable 'industry 1 was included in order to

simultaniously control external effects. The results of these analyses are reported in

table A-1.

Figure 4 shows the average score for each network configuration regarding

technological product innovation success.

Figure 4:

Network configurations and product innovation

Network configuration influences technological product innovation success (p =

0.01 and p = 0.02). Furthermore, the island has significantly lower percentages of

economic successful developments. In harmony with hypothesis 1, the highway has

the highest percentage of successful improvements of products. The results of the

toddler are better than assumed. University interaction - even at a low degree of

total interweavement - is helpful to achieve product innovation success. For larger

innovation steps the visionary has high percentages of successful developments.

This result supports the assumption that university interaction leads to high

innovative products. As documented in figure 4 the spider realises high

percentages of economically successful product innovations regardless the degree

of step of innovation. This result confirms that the spider is a 'real 1 networker.

The authors analysed process innovation as well. The results of these analyses are

documented in figure 5.

Figure 5:

Network configuration and process innovation

The construct 'network configuration' is significantly influencing process innovation

success. Regarding technical process innovation success and the economic

relevance of process innovations hypothesis 2 and 3 are completely supported by

the empirical findings.

All in all, the results of our analyses support our hypotheses: different network

configurations exist and these configurations are strongly influencing innovation

488

10

success in different ways. Depending on the number of cases, not all of our results

are sufficient in a way that we can call them statistically confirmed. But "it may be of

interest to recall that Freud created psychoanalysis out of five cases and that

Hippocrates laid the foundation for medicine from seven cases" (Gummesson

1995).

3 Discussion and Outlook

Our findings are promising. They show that for a description of innovation networks

intensity and patterns are decisive. Like 'industry' there are a lot of additional

variables influencing network activities or the success of network activities. In further

research, the authors will, therefore, analyse these influences. Particularly, a firm's

corporate strategy should be included (cf. Gemunden and Heydebreck 1994).

Networks are dynamic. The authors assume that a company can develop the

network in a way that the network is changing from one configuration to another.

This process will be influenced by a lot of external variables as well. Thus, it will be

interesting to have a look on the developing process of a company's network

configuration.

489

11

Appendix

Table A-1:

Network configurations and innovation success

(results of the regression analyses)

490

12

Factor

Indicator

importance of suppliers

importance of suppliers by developing

new product ideas

importance of suppliers by product

conception

importance of suppliers developing new

products

importance of suppliers by testing new

products

importance of customers

importance of customers by developing

new product ideas

importance of customers by product

conception

importance of customers developing new

products

importance of customers by testing new

products

importance ol universities

importance of (Fach-) Hochschulen and

research institutes

importance of consultants

importance of engineering offices

explained variance [%]

Cronbachs alpha

F1

(n=294)

0.68

0.79

0.86

0.87

0.82

-

-

-

-

-

-

-

-

-

65.1

0.86

F2

(n-297)

-

-

-

_

_

0.71

0.76

0.77

0.68

0.71

_

-

-

-

52.7

0.77

F3

(n=307)

-

-

-

_

-

-

-

-

-

-

0.93

0.93

-

-

85.7

0.83

F4

(n=305)

-

-

-

-

-

-

-

-

-

-

-

-

0.88

0.88

' 77.7

0.71

Table 1:

The dimensions of technological interweavement

491

13

pattern

intensity

very low

low

high

very high

1

13

40

15

2

29

35

11

8

3

24

2

4

2

26

52

5

6

12

7

Table 2:

Intensity and pattern

492

14

indicator

percentage of economic successful

developments

• improvement ot products

• new product development

technical process innovation success

economic relevance of process

innovations

operationalisation

tour categories to choose:

0 = no product innovations

1 = 'less than 25%'

2 a 'between 25 and 50%'

3 » 'between 50 and 75%'

4 =. 'more than 75%'

(actor built up with the following

indicators:

• savings in working time

• increase of maschine productivity

• reduction of process time

• savings in material and energy

factor built up with the following

indicators regarding the relevance of

process innovations for:

• survival of the company

• profit or productivity

• growth of the company

mean in sample

44%

35%

0.00

(factor score)

0.00

(factor score)

Table 3: Operationalisation of innovation success indicators

493

15

network

configuration

The manufacturer

The toddler

The highway

The visionary

The apart the market

The spider

improvement of

products

impact of industry: n. s.

impact of network configuration:

p - 0.02

beta

0.11

0.26

0.22

0.13

0.03

0.24

level of sign.

0.34

0.01

0.01

0.09

0.72

0.03

new product

development

impact of industry: n. s.


p - 0.01

beta

0.20

0.36

0.17

0.22

0.18

0.38

level of sign.

0.07

0.00

0.05

0.01

0.04

0.00

technical process innovation success

impact of industry: p - 0.00


p - 0.06

beta

0.32

0.21

0.19

0.04

0.13

0.34

level of sign.

0.01

0.04

0.03

0.58

0.13

0.00

economic

relevance of

process innovations

impact of industry: p - 0.08


p - 0.04

beta

0.11

0.11

0.06

0.08

0.23

0.30

level of sign.

0.32

0.26

0.45

0.28

0.01

0.01

Table A-1 :Network configurations and innovation success

(results of the regression analyses)

494

16

Administration> Subsidy• Political support• Mediations, transfer > Laws, (de-) regulations

Co-supptiers• Complementary know-how

• Solving interlace problems

Consultants> Innovative Concepts• Structuring of processes• Financial, legal and insurance services

Suppliers,producers of means

of productionNew technologies ol components and systems

BuyersDefining new requirements] Solving problems of im plementation and market acceptance

^Reference function

Focal CompanyOwn authority

Research and training Institutes

• Research• Training

Qualified personnel

CompetitorsJoint basic research Establishing standards Getting subsidies

J1

Distributors> Changing and weightingof demands

• Gathering informationabout developments ofcompetitors

Figure 1:Innovation partners and their resources

(Source: Gemunden, Heydebreck and Herden 1992, p. 360)

495

17

overall success

growth productivity

il

innovation success

product innovation success

process innovation success

j , 1 1

llflllp:^^

: ill.i.;:'intenshyy.;11lll;-xlt - ;: -^--- -C :;¥.-• :.^-: ::f;|i|;#:

Figure 2: Theoretical frame of reference

496

18

pattern 1(68 cases)

pattern 3(26 cases)

suppliers

universities

pattern 2(83 cases)

suppliers

pattern 4(80 cases)

suppliers

suppliers

Figure 3:

Radar charts of network patterns

497

50%

25%

•oJCO CO

TD

E0)

19

.c o>

<D

improvements of products (percentage of economic successful innovations)

'5. CO0)

50%

25%

2 ns3

QJ£-c? h-E

0>-0 TJ

<p -c H-

« • S —« ®

O> T3 'CL

CO O

new product development (percentage of economic successful innovations)

Figure 4: Network configuration and product innovation

498

20

0.20

0.00-

-0.20

TJ

CO5

Qj =0

raJZ O)IcCD

The visionary apart et

technical process innovation success (average factor sores)

0.20

o.ocr

-0.20

Q)x:

§1S

economic relevance of process innovations _____(average factor scores)_____

Figure 5:

Network configurations and process innovation

4-99

21

List of References

Axelsson, B. (1986), "Fran Fluga till Spindel", unpublished working paper.

Biemans, W. G. (1992), Managing innovations within networks. London and New

York

Gemunden, H. G. and P. Heydebreck (1994), "Matching business strategy and technological network activities - The impact on success", in Meeting the challenges

of new frontiers. Proceedings of the 10th annual conference. W. G. Biemans and P.

Ghauri, eds. Groningen.

— and -— (1995), "Innovationskooperation und Innovationserfolg. Eine empirische

Analyse kleiner und mittlerer Unternehmen in Spitzentechnologiebranchen", final

research report for the Ministry of Research and Technology.

— ; — and R. Herden (1992), "Technological interweavement: A means of achieving innovation success", R&D Management. Vol. 22 (4), 359-76.

Gummesson, E.; I. Thoresson-Hallgren and E. Bylund (1995), "Service productivity

and IT, in People, technology and productivity. Proceedings of the ninth world

productivity congress. Istanbul.

Hahn, R.; A. Gaiser; J.-A. Heraud and E. Muller (1995), "Innovationstatigkeit und Unternehmensnetzwerke", Zeitschrift fur Betriebswirtschaft. Vol. 65 (3), 247-65

Hakansson, H. (1987), Industrial technological Development. A network approach. Worcester.

— and I. Snehota (1989), "No business is an island. The network concept of

business strategy", Scandinavian Journal of Management Studies. Vol. 45, 187-

200.

SOD

22

Hammarkvist, K.-O.; H. Hakansson and L-G. Mattsson (1982), "Markets as networks

- An approach to the analysis of specific marketing situations", paper presented at

the 1982 Annual Meeting of the European Academy for Advanced Research in

Marketing, Antwerpen.

Herstatt. C. (1991), "Anwender als Quelle fur die Produktinnovation", doctorial

dissertation, University of Zurich.

Heydebreck, P. (1995), "Technologische Verflechtung: ein Instrument zum

Erreichen von Produkt- und ProzeBinnovationserfolg", doctorial dissertation,

University of Karlsruhe.

Ritter, T. (1995), "Strukturen technologischer Verflechtung. Eine empirische Studie in Spitzentechnologiebranchen", diploma thesis, University of Karlsruhe.

Shaw, B. (1985), "The role of the Interaction between the user and the manufacturer in medical equipment innovation", R&D Management. Vol. 15 (4), 283-92.

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