Promotors or Champions? Pros and Cons of Role Specialisation for Economic Process

Abstract

According to the Great-Man Theory, the creation of something new used to be accredited solely to one outstanding individual: the champion. This prevailing notion in Angloamerican research was first challenged by Witte (1973), who concluded that an innovation cannot be a one-man decision, since the creation of something new usually involves highly complex and multi-person decision processes. Witte’s model credits the success not to one all-around individual, but to the cooperation of several different specialized persons (so called promotors). Even though the Great-Man Theory is still leading the discussion, the idea of specialized promotors should not be underestimated. In this article we discuss the circumstances under which specialized promotors or generalized champions are better suited for economic progress. We find extensive empirical proof for both roles.

Full text

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340 SBR 59 October 2007 340363
Katja Rost/Katharina Hölzle/Hans-Georg Gemünden*
Promotors or ChamPions? Pros and Cons of role
sPeCialisation for eConomiC ProCess**
abs traC t
According to the Great-Man Theory, the creation of something new used to be accred-
ited solely to one outstanding individual: the champion. This prevailing notion in Anglo-
American research was first challenged by Witte (1973), who concluded that an inno-
vation cannot be a one-man decision, since the creation of something new usually
involves highly complex and multi-person decision processes. Witte’s model credits the
success not to one all-around individual, but to the cooperation of several different spe-
cialized persons (so called promotors). Even though the Great-Man Theory is still lead-
ing the discussion, the idea of specialized promotors should not be underestimated. In
this article we discuss the circumstances under which specialized promotors or gener-
alized champions are better suited for economic progress. We find extensive empirical
proof for both roles.
JEL-Classification: M12, O32.
Keywords: Champions; Promotors.
1 in tro d uCt i on
In the 1970’s, Eberhard Witte developed the idea of promotors. He defined promotors as
“individuals who actively and intensively support the innovation process” (Witte (1973,
15-16)). Witte started by asking how economic progress develops. Technological inven-
tions, i.e., new products, production materials, or production processes, might or might
not generate economic value (Walter (1998, 37)). Based on the question of how economic
progress develops, Witte identified barriers against innovation that hinder economic prog-
ress. ese barriers can severely handicap or even prevent innovation altogether if they are
* Katja Rost, Assistant Professor, Chair for Organization Theory, Technology and Innovation Management, Uni-
versity of Zürich, Plattenstraße 14, CH-8032 Zürich, e-mail: katja.rost@iim.unibe.ch; Katharina Hölzle, Ph.D.
candidate, Chair for Innovation and Technology Management, Technical University of Berlin, Straße des 17.
Juni 135, H 71, D-10623 Berlin, e-mail: katharina.hoelzle@tim.tu-berlin.de; Hans Georg Gemünden, Head of
Chair for Innovation and Technology Management, Technical University of Berlin, Straße des 17. Juni 135, H
71, D-10623 Berlin, e-mail: hans.gemuenden@tim.tu-berlin.de.
** The authors would like to thank the reviewers for their valuable and helpful comments.

Electronic copy available at: http://ssrn.com/abstract=1030009
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not overcome by the organization. Witte assumed that since these barriers are created by
people who either do not want the innovation or are not capable of implementing it, then
only people can overcome these barriers. Witte’s concept assigns the success of an inno-
vation not only to one all-around “star”, but also to the cooperation of several different
kinds of specialized promotors (Hauschildt (2004, 197)).
Admittedly Witte’s concept of specialized promotors conflicts with the Great-Man eory
of generalized champions. In this tradition, the success of an innovation used to be accred-
ited solely to one outstanding individual, who was called champion (Hauschildt (2004,
195)). Witte challenged this general belief of a single person’s actions. He argued that
innovation processes involve very complex and multi-person decision processes that
cannot be borne by only one individual. However, so far, the promoter concept has not
been too successful in Anglo-American research, as the Great-Man eory is still leading
the discussion (Research on champions, e.g., Schon (1963); Chakrabarti (1974); Achill-
adelis et al. (1971); Burgelman (1983); Roberts and Fusfeld (1988); Frost and Egri (1991);
Day (1994); Dougherty and Hardy (1996); Howell and Higgins (1990); Howell et al.
(2005), Lam (2005)). Since there is extensive empirical proof for both promotors as well
as champions, we discuss the circumstances under which specialized promotors or gener-
alized champions are more suited for economic progress (Research on promotors, e.g.,
Witte (1973); Gemünden (1985); Gierschner (1991); Gemünden and Walter (1996);
Hauschildt and Kirchmann (1997); Klöter (1997); Walter (1998); Folkerts (2001); Folk-
erts and Hauschildt (2002), Gemünden and Hölzle (2005)).
2 the model o f sPeC ial ize d Pr omo tor s
2.1 Wi t t e’s tWo-Ce nter theor y of Po Wer and Kn oW-ho W
Innovations are changes signifying that old “traditions” are disappearing and “something
new” has to be accepted. If these changes “… developed automatically and more or less
on its own, without encountering any personnel or technical barriers, no specific organi-
zational structure encouraging innovation would be required. But we cannot simply take
it for granted that, once the problems of decision-making are mastered intellectually, the
rational solution will be immediately understood and implemented by the competent
authorities. Indeed, empirical studies have shown that innovation decision-making prob-
lems can be solved only by complex, multi-personnel and multi-operational decision-
making processes. ….” (Witte (1973, 48-49)). Because innovations cause decision-making
problems, they often lead to the resistance by employees. ese problems arise from the
uncertainty of the new situation and are expressed as the wish to maintain the status quo
(Witte (1973, 7); March and Simon (1958)). “…e new is quite usually synonymous
with the unreasonable, the dangerous, the impossible…” (Kallen (1973, 450)). Barriers
delay or even prevent the implementation of new ideas (Witte (1973, 6)). Employees
express their resistance against innovations by their attitude or motivation towards the
“new.”
1
Most employees have no reason to support the innovation, as the previous behavior
1 Witte (1973, 5ff.) calls these motivational barriers to willingness, i.e., not willing.

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patterns were successful and they cannot predict what the new situation will be like, or
what advantages and disadvantages will be connected to it (Hauschildt (2004, 175)). e
“new” can also lead to cognitive resistance2: many employees seem incapable of giving up
previous knowledge and painfully acquired experiences, particularly since the objectives
concerning the innovation are too fuzzy (Hauschildt (2004, 175)). us, the progress of
innovation depends on the employees’ willingness and ability to cooperate.
Barriers, i.e., rejection, ignorance, or opposition, appear in the form of people who either
do not want the innovation or are not capable of implementing it. Consequently, to
surmount these barriers, organizations need persons who can start the innovation process
and keep it going on until a final decision is reached. Witte called these people promo-
tors. Promotors are those individuals who actively and enthusiastically promote innova-
tions throughout the crucial organizational stages.
Because the problem-solving capacities of every human are limited, different actors have
different previous knowledge (Bandura (1976); Rumelhart (1980); Dosi, Nelson, and
Winter (2000)). Actors can only consider those goals and alternatives for a problem’s
solution that correspond to their previous knowledge (March and Simon (1958)). It
seems plausible that the kind of previous knowledge an individual has influences the
problem-solving capacity of that person and their recognition of barriers during these
search efforts. erefore, Witte postulates that activities to overcome barriers in the inno-
vation process are contributed by different specialized persons, i.e., from employees with
different previous knowledge. Witte differentiates between two kinds of specialization, the
“power promoter” and the “expert promoter” and bases this distinction on the following
assumptions.
(1) Correspondence between barriers and contributions. In each organization there is a
correspondence between the resistance of some employees and the resistance-overcoming
contributions of other employees. e motivational resistance of some employees is recog-
nized and overcome by the hierarchical potential of other employees. e cognitive resist-
ance of some employees is recognized and overcome by the expert knowledge of other
employees.
(2.) Role specialization of the contributor. e contributions to overcoming the resist-
ance of some employees are made by specialized persons. e “power promoter” contrib-
utes through hierarchical power and the “expert promoter” contributes through expert
knowledge.
(3.) Promoter cooperation. e innovation process will be successful if both specialized
promotors work closely together (Hauschildt and Kirchmann (1997, 68)).
Because changes need the cooperativeness of employees, “power promoters” actively foster
the innovation process by means of hierarchical power. (Witte (1973, 17)). e defining
characteristics of the power promoter are a certain position within the organizational
2 Cognitive barriers are called ability barriers or barriers of not knowing. See Witte (1973, 5ff.).

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structure and a certain type of behavior. Power promotors recognize barriers, sanction
antagonists, and support and protect innovation-enthusiastic employees based on their
hierarchical position (Shepard (1967, 471)).
“Expert Promotors” actively encourage the innovation process by means of specific knowl-
edge (Witte (1973, 18)). Usually, this promoter has a line function in a department
that closely connected with the innovation. e expert promoter may become aware of
the potential innovation by recognizing weaknesses within the daily work routine. ese
promotors also help to overcome employees’ cognitive barriers by recognizing problems.
To do so, they use their extraordinary specific expert knowledge, since many employees
lack the cognitive prerequisites to find specific problem solutions or to engage in multi-
disciplinary interactions with others (Walter (1998, 60)). Expert promotors also assist
other employees to understand new problems and use their expert knowledge as argument
against antagonists. For this reason, a solitary scientist is not an expert promoter, because
such a person does not motivate others to work for an innovation.
ese two kinds of promotors must be understood as normative role types. Both explain
social roles of actors, i.e., an abstract bundle of abilities, social behaviors, and motives for
action (Fuchs-Heinritz et al. (1995); Wiswede (2004, 1289ff.)). However, reality does not
always correspond to these theoretical role concepts.
2.2 exte nsi on o f the Promoter -Con CeP t
In the 1990s, Hauschildt and Chakrabarti discovered a third barrier that can hinder
economic progress: administrative barriers (Hauschildt and Chakrabarti (1988, 378-388)).
ese barriers emerge in those organizations that are predominantly run by routines, for
example, by a risk-averse financial controlling philosophy (Hauschildt and Gemünden
(1999, 93)). Moreover, cooperation barriers (Allen (1967); Allen et al. (1979)) and
dependency barriers (Gemünden and Walter (1995)) prevent innovations. Coopera-
tion barriers result from significant mental, language, and intercultural distance between
employees. Dependency barriers are caused by a disequilibrium in relationships. Some-
times, and especially in changing situations, the asymmetric power of relationships may
be used to dictate activities to the other party or to prevent activities.
Because Witte assumed that there does exist a correspondence between the resistance
of some employees and the resistance-overcoming contributions of other employees,
other studies specify additional contributions. Administrative barriers can be recognized
and overcome by organizational knowledge, cooperation barriers by socialization, and
dependency barriers by network competence (Gemünden and Ritter (2003)). Based on
Witte’s assumption of role specialization, these contributions are made by specialized
persons. “Process promotors” possess organizational knowledge, technological gatekeepers
3
3 The technological gatekeeper – one of the oldest roles of innovation management – is often not represented by
the promoter concept. We add the technological gatekeeper as fifth specialized role, since these specific contri-
butions are not expressed in the promoter concept.

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contribute to the socialization of teams, and “relationship promotors” add their network
competence to innovation processes.
“Process promotors” actively arbitrate between the technical and economic world by means
of organizational knowledge (Hauschildt (2004, 213f.); Hauschildt and Chakrabarti
(1988, 385f.)). Since innovations not only affect the innovating department but also influ-
ence other departments in the organization, economic progress needs both the good will
of the immediate participants and also the good will of the affected actors. Process promo-
tors overcome administrative barriers by recognizing organizational hurdles (Hauschildt
and Chakrabarti (1988, 378ff.); Hauschildt and Kirchmann (1997, 69); Hauschildt and
Schewe (1997, 509)). e defining characteristics of the process promoter is his or her role
in interfacing within the organizational structure, e.g., as project leader. Based on their
negotiation skills, the process promoter mediates between involved and affected parties
(Hauschildt (2004, 213)).
Technological Gatekeepers actively support cross-organizational knowledge transfer (Allen
(1967, 35; 1977, 141ff.)). e defining characteristics of the gatekeepers are their tech-
nological competence and their cross-organizational relationships with other scientists.
Innovations often derive from the combination of external information with internal
knowledge. However, external information is often unconsciously ignored, suppressed,
forgotten, distorted, or seen and commented on in a prejudiced way (Nisbett and Ross
(1980); Janis (1972); Mehrwald (1999)). Gatekeepers overcome these barriers by recog-
nizing relevant information and communicating this information to their colleagues: ...
gatekeepers are among the organization′s highest technical performers...” (See Allen (1977;
171)). Gatekeepers often start socialization processes in work groups, i.e., they help to
overcome significant mental, language, and intercultural distances between members of
different organisations (Katz and Tushman (1981)).
“Relationship promotors” actively encourage an innovation process by means of innovation-
related business relationships inside and between the organization and its external part-
ners (Gemünden and Walter (1995, 971, 974). e defining characteristic of relationship
promotors is their extensive network competence, i.e., powerful relationships with other
parties. Sometimes employees do not want to share knowledge, for example, because they
dislike or envy one another. Relationship promotors overcome dependency barriers by
recognizing knowledge transfer barriers and initiate, design, and foster relationships to
important actors and third parties (Gemünden and Walter (1996, 273ff.).
3 Gr e at-man theo ry o f th e Ch amP i on
Contrary to the promoter-concept, champion research is looking for generalists who play
multiple roles (Schon (1963); Achilladelis et al. (1971); Chakrabarti (1974); Rothwell
et al. (1974); Burgelman (1983); Howell and Higgins (1990); Frost and Egri (1991);
Day (1994); Dougherty and Hardy (1996)). Champions are “individuals who informally
emerge to actively and enthusiastically promote innovations through the crucial organiza-
tional stages” (Howell et al. (2005, 642)). Champion research often refers to this general

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definition without defining precise role attributes of the champion: “Most of what has
been reported about champions is largely anecdotal, reflecting the researcher’s impressions,
rather than reliable and valid measurement using well accepted instruments” (Howell et al.
(2005, 644)). Schon describes champions based on the attributes of informal selling, inno-
vative ideas, informal power, reliability, and heroic qualities (Schon (1963)). Burgelman
adds that champions mobilize forgotten ideas and launch these ideas by communicating
with the top management (Burgelmann (1983)). Moreover, champions act in concert with
other stakeholders for a common achievement of objectives (Galbraith (1982); Markham
and Griffin (1998); Shane (1994)). Howell et al. attempt to close the research gap in the
champion literature by specifying precise behaviours of the champion role. Unfortunately,
the results are imprecise, just as we would expect for an all-round champion role concept.
e authors conclude that champions belong to middle management, and possess enthu-
siasm, persistence, and network competence (Howell et al. (2005)).
Ultimately, the champion role, i.e., the universal promoter, corresponds with Witte’s
personal union. Witte mentions in his research that promoter roles can be combined in
one role. e personal union of the power and expert promotors refers to a person who
actively promotes an innovation process by using both hierarchic potential and object-
specific know-how. In Witte’s sense, the concentration of promoter roles is inferior to the
team of independent promotors, because a one-man decision cannot offset a two-man
decision (Witte (1973, 21)). Furthermore, Hauschildt and Kirchmann also supports the
notion of specialized promotors as being the most efficient for complex processes like
innovations (Hauschildt and Kirchmann (1997, 71)).
4 Pr omo tor s or Cha mPi o ns?
In a sense, not only specialized promotors are suited for economic progress, as but the
Anglo-American literature still favors and empirically confirms the champion. In fact, this
contradiction in innovation research makes sense as promotors or champions are hardly
observable. ese work roles informally emerge to actively and enthusiastically promote
innovations, but are not a part of the employment agreement. Research in organizations
often finds empirical confirmation for promotors and champions. erefore, both kinds
of individuals must be an integral part of innovation processes. It also does not seem
feasible that cultural differences lead to the description of an all-rounder in the Anglo-
American area and to the specialist in the German area. We believe that both types appear.
However, it remains unclear under which circumstances champions or specialists foster
economic progress.
Research shows that the cognitive abilities of each person are limited (Ellis (1965); Estes
(1970); Pirolli and Anderson (1985)). Consequently, innovation experts have only two
possibilities for using their abilities: specialization or generalization. Specialization implies
that all cognitive abilities of a person are predominantly allocated to one field of knowl-
edge (component knowledge) (Henderson (1996, 370)), but at the same time, this allo-
cation limits the cognitive abilities in other related areas of knowledge (architectural
knowledge) (Henderson (1996, 370)). As we noted earlier, specialization corresponds

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with the promoter concept, which postulates that activities in the innovation process are
contributed from different specialized persons. Generalization implies a more balanced
distribution of the sum of all cognitive abilities of a person in multiple fields of knowl-
edge (architectural knowledge), but synchronous implies less-deep knowledge in one field
(component knowledge). Generalization is the equivalent of the concentration of work
roles in the champion concept, that is, the all-embracing previous knowledge of one
employee in different areas.
e distinction between component and architectural knowledge, or between the special-
ization and generalization of the cognitive abilities of a person, underscores the idea
that successful innovation requires two types of knowledge. First, a successful innovator
requires deep or basic knowledge about the product as a set of components. For example,
a car’s major components include the motor, the control system, and the mechanical
housing. Second, a successful innovator requires broad knowledge about the ways in
which the components are linked together into a coherent whole. For example, the deci-
sion to use an electric motor instead of a gasoline engine establishes the product as a
system (Henderson and Clark (1990)).
e advantages of both kinds of knowledge depend on the kind of economic progress
that can be attained by refining and improving an existing design or by introducing
a new concept that differs in a significant way from past practice (Mansfield (1968)).
Incremental innovation introduces relatively minor changes to the existing product and
exploits the potential of the established system of components (Nelson and Winter (1982);
Tushman and Anderson (1986)). Although incremental innovation does not draw from a
dramatically new science, it often calls for considerable new skills because employees must
build on previous knowledge. Over time, incremental innovations might have significant
economic consequences (Hollander, 1965). In contrast, radical innovation often intro-
duces major changes and explores the potential of a new system of components. Radical
innovation is based on a different set of engineering, scientific, and economic principles.
It often calls for broad knowledge in multiple fields and opens up new applications, new
markets, or even redefines an industry (Tushman and Anderson (1986), Henderson and
Clark (1990)).
Radical innovation creates unmistakable challenges, since it often destroys the useful-
ness of established knowledge. For example, once the dominant automobile design had
been accepted, engineers did not re-evaluate the decision to use a gasoline engine in every
subsequent design, because incremental innovation only refines and elaborates on the
initial set of components. e emergence of a radical new technology is usually a period
of considerable confusion. Recognizing what is useful and what is not, and acquiring and
applying new knowledge when necessary, may be difficult. ere is little agreement about
what the major components of the product should be or how they should be put together
(Clark (1985)). erefore, radical changes lead to even stronger decision-making problems
between the diverse parties and increase the barriers against innovations.
For radical changes, research recommends an overlap of the problem solving capabili-
ties of persons who act jointly, i.e., architectural knowledge (Langlois (1992); Spender

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(1993); Nooteboom (2000)). Architectural or general knowledge implies that employees
not only have deep knowledge in one field, but are also well educated in other areas. For
this reason, they are better able to see problem solutions from different viewpoints and to
agree about what the major components of the new product should be or how they should
be put together. For example, industrial engineers have engineering and business skills and
are able to see problem solutions from the viewpoint of both an engineer and a manager.
e champion also has a high amount of architectural or general knowledge. erefore,
generalized champions should be better positioned to reduce the barriers against radical
innovation, i.e., to reduce the decision-making problems between the diverse parties. e
findings of Folkerts and Hauschildt support this assumption. e authors observed that
champions are the most useful to promote radical innovation (Folkerts and Hauschildt
(2002, 11)). e idea that all-rounders are better suited for radical innovation is also
supported by the concepts of the “t-shaped employee” (Leonard-Barton (1998); Carlile
(2004)) and of the interpersonal diversity (Bunderson and Sutcliffe (2002)). In the case
of radical innovation, the cited research shows that both concepts foster economic prog-
ress. e assumption that all-rounders are better suited for radical innovation could also
explain why Anglo-American studies only consider the champion. Most research deals
with radical rather than incremental technological change.
Since success in the market not only builds on the synthesis of unfamiliar technologies for
creative new designs, organizations must actively develop knowledge about new ways in
which components could be linked together and basic knowledge about the product as a
set of components. For example, electric-powered cars as a technology of choice encourage
organizations to learn more about electric-fired engines. erefore, successful organiza-
tions adjust their attention between learning a great deal about a new design and learning
a little bit more about the old design. In the case of incremental change, employees must
build on their earlier knowledge, since incremental innovation creates a scarce source of
existing, mostly slightly changed knowledge.
As employees build on existing knowledge, incremental changes lead to fewer decision-
making problems between the diverse parties. Many employees have comparable skills
from existing knowledge, e.g., from education or former experiences (Polanyi (1985)).
Moreover, existing knowledge can be better phrased and reproduced. Existing knowledge
also helps to build common understanding between employees with different educational
backgrounds and skills. However, if knowledge has been accepted, it looses its competi-
tive advantages. Knowledge about the product as a set of components is more likely to
be managed explicitly and can easily be imitated (Barney (1991)). Organizations that are
actively engaged in incremental innovation thus only achieve comparative advantages if
they are specialized, i.e. if they make use of the division of labour (Chandler (1990, 593);
Milgrom and Roberts (1992); Foss and Iversen (1997); Kräkel (2002); Frese (2002)).
Specialization and the division of labor are in line with the promoter concept. In advanced
technologies specialized employees with deep basic knowledge, i.e., component knowl-
edge, recognize opportunities better than do generalized employees with broad marginal
knowledge, i.e., architectural knowledge, which explains why champions are less suited
to reducing the barriers against incremental innovation. ey cannot see problem solu-

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tions by refining and improving an existing design, and therefore are not able to agree on
what the minor changes to the existing product should be or how the established system
of components should be exploits.
In summary, the contributions of promotors and champions to surmounting barriers
depend on the kind of economic progress within an industry or an area. If economic prog-
ress builds on previous knowledge and organizations only need to refine and improve an
existing design, the specialized promotors are more suitable. If economic progress cannot
be built on previous knowledge and organizations must introduce a new concept that
differs in significant ways from past practice, then generalized champions are more suit-
able.
To test these assumptions, we measure how promotors or champions influence the inno-
vation output of other employees.
Hypothesis:
e higher the previous knowledge of an organization in one technology area and the greater
the extent of improvements of existing designs within this technology area, the better suited are
specialized promotors to increase the innovation output of other employees
e less the previous knowledge of an organization in one technology area and the greater the
extent of uncertainty within this technology area, the better suited are generalized champions
to increase the innovation output of other employees.
5 me thod
5.1 sa mPl e
We conducted a survey in the automotive industry. We chose the automotive industry
because it is characterized by both incremental and radical technological changes (Tietze
(2003). We explore only one industry, since the amount and quality of new knowledge
is dependent on the sector (Michel and Bettels (2001); Harhoff and Reitzig (2001)). To
acquire an adequate sample we used the population of all European (EP-) patents granted
to German automotive companies from 1990-1999 and drew a random sample using
the snowball procedure. e random sample consists of 1287 EP-patent families (in the
following called EP-patents) of 533 inventors from 69 different companies. Using the
technology classes of the patents, we looked at whether the selected sample mirrored the
population of all patents. ere were no significant differences4.
Next, we contacted the 533 inventors by mail and, if possible, by phone. We excluded
147 inventors from the analysis because of movement, pension, or death. Overall, 386
4 Michel and Bettels (2001); Harhoff, Scherer, and Vopel (2003) show that knowledge rate of returns in different
industries are not comparable. The snowball procedure started with cooperation patents of big automotive man-
ufacturers.

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persons were directly accessible. From this final sample 142 filled-out questionnaires were
returned, yielding a response rate of 36%. On the basis of different indicators, i.e., the
technology classes, firm affiliation, application date of a patent, number of EP patents per
inventor, and the answer date, we examined whether the return rate mirrored the selected
sample of the 533 inventors. We found that the differences between participants and non-
participants were not significant, i.e., random5.
5.2 mea sur eme nts
e method of egocentric network analysis was used to identify promotors and cham-
pions. An egocentric network consists of the Alteri, i.e., the personal contacts of the
interviewed person
6
. To select relevant Alteri from all contacts of a person, this method
uses specific questions, so-called name generators. One example of a name generator is
the naming of all network partners with whom the interviewed person shares knowl-
edge. e respondent quotes his network partners via name codes, e.g., the network
partner “Otto Baum” is specified by the name code “OB”. Later, we identify network
partners who have been named by two respondents. In our study, the participants could
indicate a maximum of eight network partners per each name generator. Overall, we
used 15 different name generators. In total, we identified 1,905 job-related network
partners of the 142 respondents.
Identification of work roles. We used five name generators to identify different network
partners who were widely acknowledged in the organization as innovation experts and
who were thought to actively and enthusiastically promote innovations through the
crucial organizational stages (Walter (1998); Hauschildt and Gemünden (1999); Folk-
erts and Hauschildt (2002)). We asked for the work roles of the promoter concept,
i.e., the power promoter, expert promoter, process promoter, and the relationship
promoter, and the technological gatekeeper. An typical question we used to iden-
tify expert promoter was: “Please name those persons in your COMPANY, who -
after general understanding – actively encourage an innovation process by means of
specific knowledge. In particular, such persons who are proven technical and/or proce-
dure-specific experts in innovation projects and who assist by the development of new
5 We found an average age of 46 years and approximately 21 years of employment. We split these 21 years into 15
years of employment in the actual company and 12 years in the current technology area. The work activity of
the participants consisted to 26% of operative, application-oriented activities and to 17% of scientific activities
(32%: discussions/meetings, 25%: administrative activities). On average, each participant held 18 patents, 12
new product or process developments, and eight publications. Furthermore, each inventor was five times more
involved in non-disclosure activities of his current company and received an average bonus per year of €1500.00
for his inventions.
6 See Wasserman and Faust (1994). Egocentric networks represent the only network approach that permits the re-
searcher to pull a random sample and is therefore compatible with survey research. The free choice of persons –
in contrast to the presentation of a list of names – further validates the measurements.

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products or procedure.” (see footnote 7 for all questions). To check whether our meas-
urements clearly identify informal work roles, we ran a pretest in a small organization.
e external validity of the measurements was good, since we were able to clearly iden-
tify the same persons over multiple respondents as promotors or champions8.
In total, we identified 860 informal role owners in the networks of the 142 respondents.
e number of role owners per work role are listed in table 1 (persons with multiple work
roles are possible). e expert promoter occurs most frequently in networks and the power
promoter occurs most rarely. ese results are in line with previous empirical findings
(Folkerts and Hauschildt (2002)).
Table 1: Descriptive statistic of informal role owners in ego networks*
Variable Min. max. mean std.dev.
Informal role types in ego networks
Expert promoter (KnwProAlteri) 0.00 1.00 0.22 0.41
Power promoter (PowProAlteri) 0.00 1.00 0.15 0.36
Process promoter (ProProAlteri) 0.00 1.00 0.16 0.37
Relationship Promoter (RelProAlteri) 0.00 1.00 0.16 0.36
Technological Gatekeeper (TecGaAlteri) 0.00 1.00 0.17 0.38
*N = 1,905 (multiple work-roles of persons are possible)
7 Please name those persons in your COMPANY, who – after general understanding – :
(1) ... actively encourage an innovation process by means of specific knowledge. In particular, those persons who
are proven technical and/or procedure-specific experts in innovation projects and who assist by the development
of new products or procedure. (2) ... actively promote an innovation process by means of hierarchic power. In par-
ticular, those persons who order sanctions against opponents and provide protection for those who are in favor of
innovation. (3) ... actively arbitrate between the technical and economic world by means of organizational knowl-
edge. In particular, those persons who recognize organizational hurdles and contribute to innovation processes
through their negotiation capabilities. (4) ... actively encourage an innovation process by means of innovation-re-
lated business relationships inside and between the organization. In particular, those persons who initiate, design,
and foster relationships to important actors and third parties. (5) ... actively support cross-organizational knowl-
edge transfer. In particular, those persons who assist and help by searching out and evaluating external technical
information.
8 We selected one company that develops and tests new production technologies for automotive manufacturers.
This company employs 111 employees in eight business units. We asked two employees and one departmental
manager from each unit about their egocentric networks. We also talked to the CEOs. In total, we obtained 26
non-anonymous data sets, which allowed an external validation of highly ranked actors in the company. This pre-
test confirmed with 60% accuracy a high reply consistency between the respondents.

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Promotors compared to champions. We followed Witte by measuring promotors as the
specialization of a person on only one work role. We measured champions as the concen-
tration of work roles in one person, i.e., the personal union. From the 860 named role
owners, 445 persons are specialized on only one work role i.e., promotors, and 415
persons are non-specialized champions. is result stands supports our assumption that
both promotors and champions are an integral part of innovation processes.
Specialized promotors and generalized champions. We assume that promotors have a higher
amount of component knowledge and that champions have a higher amount of architec-
tural knowledge. We empirically test these assumptions in table 2. Overall, the respondents
regard champions as technical more similar to themselves as promotors. us, champions
are more able to play a linking pin between different specialized employees. However, in
comparison to champions, promotors are seen as more innovative within a nongeneric
technical field. e innovativeness of a person within a nongeneric technical field needs
specialist knowledge, which is an indication of a higher amount of component knowl-
edge.
Table 2: Champion’s combination knowledge compared to promoter’s component
knowledge
Promoter/Champion Technical proximity to the respon-
dent as an indicator for architec-
tural knowledge
(1= low, 5 = high)
Outstanding innovativeness in a
technical field as an indicator for
component knowledge
(1 = low, 5 = high)
Promoter (N = 445) 3.54 2.17
Champion with 2 roles (N = 168) 3.76 2.06
Champion with 3 roles (N = 85) 4.12 1.78
Champion with 4 roles (N = 73) 3.96 1.85
Champion with 5 roles (N = 42) 4.37 1.59
F-Value 9.82*** 7.61***
Division of labor. According to Witte, different promotors make different specialized
contributions within the innovation process. To measure specialized contributions, we
used 11 name generators to examine four different kinds of contributions within the
innovation process. We distinguish between the exchange of knowledge, the exchange of
meaningful opinions, the access to legitimate power, and the exchange of complementary
help to achieve objectives. An example question for knowledge exchange was “With which
persons, regardless of whether they work inside or outside COMPANY, are you discussing
job-related questions, e.g., new product developments or new problem solutions?” (see

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352 SBR 59 October 2007 340363
footnote 9 for all questions). e results in table 3 overall confirm Witte’s assumption.
According to these findings the technological gatekeeper and the expert promoter more
frequently take part in the exchange of knowledge, the relationship promoter more
frequently takes part in the exchange of opinions, the power promoter more frequently
opens the access to legitimate power, and the process promoter more frequently assists in
complementary contributions to achieve objectives.
Table 3: Specialized contributions of the promotors*
Promoter Number of trans-
actions to exchange
knowledge
Number of
transactions to
exchange mean-
ingful opinions
Number of
transactions to
access legiti-
mate power
Number of trans-
actions to exchange
complementary
help to achieve
objectives
Technolog. Gatekeeper (N = 94) 1.16 .22 .11 .21
Other Promoter (N = 351) .87 .21 .44 .28
F-Value 4.18** .03 17.50*** 1.15
Expert promoter (N = 150) 1.18 .28 .25 .22
Other Promoter (N = 295) .81 .18 .43 .29
F-Value 9.19*** 3.38** 6.26** 1.66
Relationship Promoter (N = 60) .85 .34 .40 .33
Other Promoter (N = 385) .94 .22 .36 .26
F-Value .31 5.09** .14 .83
Power promoter (N = 73) .53 .16 .85 .26
Other Promoter (N = 372) 1.01 .23 .27 .27
F-Value 9.45*** .83 45.77*** .02
Process promoter (N = 68) .58 .07 .44 .41
Other Promoter (N = 377) 1.00 .24 .36 .24
F-Value 6.82** 5.91** .87 4.85**
* N = 445, shaded fields symbolize high cooperation contributions of each promoter
9 Abbreviated version:
(1) exchange of knowledge: (a) assistance by tricky and specialized development tasks, for which only little docu-
mented knowledge is available, (b) co-operation in the initial stage of projects, e.g., by the search of ideas, (c)
knowledge exchange on job-related technical questions, e.g., on new developments or new solutions, (d) close
technical collaboration;
(2) exchange of meaningful opinions : (a) discussion and evaluation of important job-related decisions, (b) confi-
dential discussion of business and/or private matters;
(3) access to legitimate power: (a) most important contacts for further vocational success, (b) acceptance as a di-
rect superior, (c) most important contacts for past vocational career;
(4) exchange of complementary help to achieve objectives: (a) cooperation in the implementation stage of projects,
e.g., transferring results into other operational departments, (b) cooperation in the final stage of project, e.g.,
project management. The name generators are based on the research of Hansen (1999) und Burt (1992).

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Table 4 compares the contributions of promotors and champions. e results confirm that
champions perform universal roles. In contrast to promotors, champions play multiple
roles, and therefore make diverse, and consequently more, contributions: e more work
roles a champion owns, the more often he is part of exchanges. e exceptional contribu-
tions of champions could be an additional explanation why the Anglo-American studies
mainly find proof for the champion concept. Champions are easier observed by third
parties than are the specialized promotors.
Table 4: Contributions of promotors compared to contributions of champions
Promoter/Champion Number of transac-
tions to exchange
knowledge
Number of transac-
tions to exchange
meaningful
opinions
Number of trans-
actions to access
legitimate power
Number of transac-
tions to exchange
complementary help
to achieve objectives
Promoter (N = 445) .93 .22 .37 .27
Champion with 2 roles (N = 168) 1.38 .32 .64 .50
Champion with 3 roles (N = 85) 2.15 .44 .85 .72
Champion with 4 roles (N = 73) 2.04 .53 .93 .79
Champion with 5 roles (N = 42) 2.45 .69 1.29 1.00
F-Value 31.43*** 10.07*** 19.34*** 23.32***
Proportion of promotors in networks. We created an overall index to test how promotors
respectively champions influence economic progress. is index measures the percentage
of promotors in the network of one respondent, compared to all role owners (promotors
plus champions). We assigned the value of one to all Alteri which take a promoter role
and a value of zero to all Alteri that take a champion role. Afterwards, we calculated an
overall index for each ego network. e maximum value of one indicates that a respondent
has only promotors within the ego network. e minimum value of zero indicates that a
respondent has only champions within the ego network.
Former technological knowledge. We measured the amount of former organizational knowl-
edge within a technology area and extent of uncertainty within this technology area via the
following questions, using a Likert scale. “Fast growing amount of technological knowledge
within the technology area” (value of one) or rather “few documented technological knowl-
edge within the technology area” (value of seven). “Specialized technological improvements
within the technology area” (value of one) or rather “uncertain technological changes within
the technology area” (value of seven). We calculated an overall index. Higher values indicate
less available and less certain knowledge within the technological area10.
10 For measurement, see Winter (1987), Hansen (1999), Turner and Makhija (2006). High values indicate a vague
optimization of the offering by the inventors. The parties share little common information on how knowledge
should be produced (uncertainty with fast technological change) and overall few common skills, as only little
documented knowledge is available (available amount of technological knowledge).

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5.3. measure men t of t he dePend ent Var iab les
We used measures of the respondent’s past knowledge creation, since a scarce amount of
new knowledge with a high assessed market value can only be measured retroactively. Our
knowledge measurements are widely accepted: patents reflect the criteria of novelty, inven-
tive activity, and commercial applicability. We looked only at patents that were announced
by the respondent’s institution. We do not consider private registrations or patent appli-
cations for other institutions. We measured new knowledge directly by previous revenues
from patents and indirectly over the number of patents and the technological impact of
these patents. e novelty of the underlying technology reflects a long-time measure-
ment. Radical innovation is often based on new technologies that will meet the demand
years later11.
Number of patents. e number of patents measures the quantity of new, commercially
applicable knowledge of an R&D-employee that is based on an inventive activity. is
indicator does not assign a value to the specific quality of knowledge.
Economic impact of patents. We asked what the average annual amount of inventor remu-
neration was that an R&D employee received from his company in the last two years
(rating scale: one = none, six = more than €10,000 per year). e inventor remunera-
tion is prescribed by the German legislation. e inventor must be given a percentage of
the corporate profits from his patents. If small turnovers are realized, then the inventor
receives a fixed inventor’s bonus. If there is high turnover, the inventor receives a turn-
over-related remuneration12.
Technological impact of patents. We used external patent data to measure the technological
novelty of patents. We calculated the number of directly received citations on company
patents (EPi) of an inventor i. is index indicates in what respect the underlying tech-
nologies of patents were significant for other developments. Patent citations are based on
the statements of an independent examiner. We limited the period of the citations per
patent EP
i
to four years after publication, since older patents are cited with a higher prob-
ability. To compare inventors with different work experiences, we calculated the average
annual number of citations for each inventor. We divided the number of patents by the
years of work experience Ti′13.
11 The use of patents in the industrial economics is documented by Scherer (1982), Griliches (1990), Harhoff and
Reitzig (2001). We checked via publicly available information on the patent date which patents of a respondent
were applied by his employer. The difference between technology and market aspects of new knowledge is dis-
cussed in detail by e.g., Danneels and Kleinschmidt (2001).
12 A fixed inventor’s bonus denotes the requirement on appropriate remuneration if the company uses the inven-
tion only to a small extent. The payment is effected after disclosure and amounts to max. 500,- EUR for single
inventors (see § 2,4,5,6,9,10 of ArEG). Turnover-related remunerations are based on a considerable use of the
invention by the enterprise. It is calculated based on the annual sales multiplied by the royalty rate multiplied by
a portion factor (see § 2,4,5,6,9,10 of ArbEG).
13 We only considered direct citations. For a discussion on the advantages and disadvantages of considering indirect
citations see von Wartburg et al. (2005). We exclude non-European patents because of they could not be com-
pared.

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patent_impacti = ∑
ep=1
EPiT
∑
t′=t
t+3
citipt′*
[
∑
ep=1
EPiT
____
T
i
′
]
A disadvantage of our research design is that the dependent variables for knowledge are
based on previous success, but the independent variables, i.e., the proportion of promo-
tors/champions in ego networks, were asked at a later time. In regression analyses, only
those actors may effect knowledge generation who were employed in the company at the
time, whereas the knowledge was invented. is assumption is realistic for our sample:
the respondents know 86% of all named contacts longer than five years and 53% even
longer than ten years.
5.4 mea sur eme nt of Co ntr ol Variabl e s
We controlled for the following personal characteristics of the respondent: Years of work
experience within the current technology area,14 years of miscellaneous work experience,
leading position in the company ( zero = “none/ little co-worker responsibility”, one =
“medium/ large co-worker responsibility”), technological specialization (overall index of
the items: one = “expert in one technological area,” seven = “expert in various technolog-
ical areas”; one = “technical and/or procedure specialist,” seven = “all-rounder in various
technologies/ procedures”), self-practice of a promoter/champion role (15 items to the five
normative role types, in each case three items per role type; one = respondent exercises
at least one work role; zero = respondent exercises no work role), and portion of single
inventions (measured by external patent data, index reaches maximally the value one if all
patents represent single inventions15).
We also controlled for the following aspects of the work environment: e number of
informal role owners in the network of the respondent, the number of the remaining
network contacts (based on the name generators of all job-related contacts, i.e., other
persons who contribute to the innovation process). Table 5 shows the statistics of the vari-
ables.
14 85% of all respondents have a university degree. Consequently, it is not necessary to control for this variable.
15 The index shows for the last 10 years how many additional inventors N contributed to the patent EPi of the in-
ventor i. If several persons contributåed to a patent, it is not fully attributed to the inventor i but rather the re-
ciprocal value of the total number of partners N. Finally, we calculated an average index for all patents of an in-
ventor i.

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356 SBR 59 October 2007 340363
Table 5: Descriptive statistics of the indexes (N = 136)
Variables Min. Max. Mean Std.dev. Skewness Kurtosis
Number of patents 1.00 136.00 18.66 23.79 2.70 9.05
Economic impact of patents 1.00 6.00 3.51 1.44 1.27 .93
Technological impact of patents .00 79.00 12.54 18.12 1.86 2.96
% of promotors in networks .00 1.00 .47 .28 –.21 –.86
Former technological knowledge 1.00 6.50 3.81 1.39 .31 –.63
Technological work experience 1.00 38.00 11.46 9.00 1.15 .46
Miscellaneous work experience 0.00 36.00 9.83 8.36 .75 .02
Leading position .00 1.00 .39 .49 .46 –1.81
Technological specialization .50 13.00 4.43 2.95 1.09 .92
Self-practice of a promoter/champion role .00 1.00 .40 .49 .40 –1.85
Portion of single inventions .33 1.00 .75 .25 –.27 –1.59
Network size of promoter/champions 1.00 23.00 7.11 4.41 1.41 1.93
Network size minus promoter/champions 1.00 22.00 8.51 4.37 .74 .53
5.5 met h od o f analysi s
We analyzed the pros and cons of promotors compared to champions by the interac-
tion between the previous technological knowledge and the proportion of promotors in
networks on knowledge generation. Without this interaction, the amount of specializa-
tion in networks, i.e., the proportion of promotors in networks should have only weak
effects on knowledge generation. Considering the interaction between previous knowl-
edge and the amount of specialization, we expected to find significant and opposite effects.
We looked for a positive main effect of the proportion of promotors in networks and a
negative interaction effect of the proportion of promotors in the network, simultaneously
considering the amount of previous knowledge. e proportion of promotors should
positively affect the generation of knowledge. However, this effect presupposes that much
previous knowledge is available within a technological area. If there is a lower degree of
previous knowledge within a technological area, then we expect that a high proportion of
promotors hinder the knowledge generation of an employee.
We predict the dependent variable inventor remuneration using an OLS test. e
dependent variable patent output represents an uncensored count variable, as all inven-
tors own at the least one patent. To predict the patent output we used a Poisson regres-
sion. For the dependent variable patent impact we observe a truncated distribution:
approximately 40% of the inventors are involved in patents which are never cited.

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e remaining inventors receive an average of 21 citations per patent. us, the vari-
able patent impact represents a censored variable and can be predicted by using a Tobit
regression (maximum likelihood estimation). We confirmed the results of the Tobit
regression by means of an alternative estimation procedure, the negative binomial regres-
sion (Fleming and Sorenson (2004)).
6 em Pir i C al res u lts
We conduct a step-wise analysis. In a first step, we enter all variables without the interac-
tion terms (model 1 in table 6) and in our second step, all variables considering the inter-
action terms (model 2 in table 6). e results in model 1 indicate that the proportion of
promotors only slightly influences the knowledge generation of a respondent. e propor-
tion of promotors is significantly and positively related to the number of patents. us,
the number of specialized promotors seems to support the number of inventions more
than do the number of generalized champions.
e findings in model 2 that consider the interaction terms demonstrate that the propor-
tion of promotors is significantly and positively related to the knowledge generation of
the respondent. ese effects are significant in all models except for the negative bino-
mial regression. e regression coefficients of the proportion of promotors are 0.34 for
the number of patents (p < 0.001), 20.1 for the technological impact of patents (p <
0.05), and 10.78 for the economic impact of patents (p < 0.001). In addition, the data
supports the fact that in the case of less and uncertain previous knowledge, a high propor-
tion of promotors prevents the knowledge generation. We find several robust moderation
effects, that is, previous knowledge consistently alters the usefulness of promotors. e
regression coefficients of the interaction between the amount of previous knowledge and
the proportion of promotors are –0.81 for the number of patents (p < 0.001), –27.05
(p < 0.001) and –0.68 (p < 0.1) for the technological impact of patents, and –2.41
for the economic impact of patents (p < 0.001). Overall, our findings confirm the idea
that for incremental innovation, promotors are better suited to fostering the economic
progress within organizations, but for radical innovation, champions are better suited to
fostering the economic progress within organizations.
Our results also show that the knowledge generation is higher in technological areas where
there is little previous knowledge. We do not consider the alternating algebraic signs of the
control variables. e causes are explained in more detail by Rost (Rost (2006)).
7 di sCu ssi o n & imP liCati ons
Our empirical results confirm the assumption that both promotors and champions are a
fundamental part of organizations. Both promotors and champions support the knowl-
edge generation of other employees by promoting innovations through the crucial organ-
izational stages. Whether promotors or champions are better or worse is determined by
the amount of the previous knowledge in the industry. If organizations only refine and

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358 SBR 59 October 2007 340363
improve an existing design, then promotors are more qualified. In advanced technologies,
specialized employees with deep basic knowledge, i.e., component knowledge, recognize
opportunities better than do generalized employees with broad marginal knowledge, i.e.,
architectural knowledge. is is the reason why champions are less suited to reduce the
barriers against incremental innovation. If economic progress cannot build on previous
knowledge and organizations introduce a new concept that differs in a significant way
from past practice, then champions are more capable. Champions possess a high amount
of architectural or general knowledge and are therefore better positioned to reduce the
barriers against radical innovation, i.e., to reduce the decision-making problems between
the diverse parties.
In summary, the champion approach and the promoter approach are part of the same
phenomenon: both work roles actively and enthusiastically promote innovations. e
advantages of one over the other depend on the character of economic progress within an
industry. Anglo-American studies apparently focus more on radical innovation and there-
fore observe the successful “great man”, i.e., the champion. German-speaking studies
based on Witte focus more on incremental innovation and favour the division of labour,
i.e., promotors.
Finally, we ask what organizations can learn from informal work roles. Practitioners often
ignore informal work roles as they appear irrelevant to managerial practice. Traditional
command-and-control systems seem to ensure rule-following and apparently regulate
employees’ performance well enough. So far, only researchers discuss how to search for,
find, and foster promotors or champions. Nevertheless promotors, champions, and other
voluntary behaviors occur in organizations, and research consistently confirms that espe-
cially informal organizational structures support innovations. e fact that command-
and-control systems are not very effective for innovating is hardly surprising; given that
research on promotors and champions shows that these helping behaviors are typically
volunteered. e question of how the existing organizational structure can enhance inno-
vation is unclear. In principle, it is not the job of promotors and champions to overcome
barriers of other employees. However, it is obvious that managers fulfil this task only
suboptimally (e.g. Hauschildt (2004)). Nevertheless, it is not enough to highlight the
advantages of informal structures and the disadvantages of formal structures. Researchers
must also show alternative command-and-control systems that optimally support innova-
tions. e search for alternative command-and-control systems calls for further research.
It seems that organizations are between the devil and the deep blue sea: tough informal
structures foster innovations, but they are not a systematic part of the command-and-
control system. Tough formal structures steer the organization, but they undoubtedly
prevent innovations.

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Table 6: Regression results (N = 136)
Variables: Number of patents Technological impact of patents Economic impact of
patents
PoissonRegression Tobit Regression Negative binomial
regression OLSTests
Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Model 1 Model 2
Coef. | z | Coef. | z | Coef. | t | Coef. | t | Coef. | z | Coef. | z | Coef. | t | Coef. | t |
Former technological knowledge .01 .80 .21 7.79*** –.33 .25 2.73 1.58 .01 .08 .09 .70 .00 .02 1.02 4.48***
% of promotors in networks .71 8.19*** .34 5.79*** 2.11 .27 20.10 1.96** .13 .24 .35 1.46 1.27 2.52 10.78 5.25***
Former techn. knowledge * % –.81 9.75*** –27.05 2.62*** –.68 1.88*–2.41 4.75***
of promotors
Technological work experience .05 18.92*** .05 19.30*** .16 .66 .08 .32 .01 .73 .01 .62 .03 1.86*.01 .92
Miscellaneous work experience .06 21.56*** .06 21.65*** .07 .31 .01 .07 .00 .20 .00 .19 .04 2.80*** .09 5.27***
Leading position .39 8.81** .46 10.04** –7.95 –1.98** –10.78 2.59** –.61 2.21** –.64 2.31** .78 2.96*** .78 3.20***
Technological specialization –.52 5.38*** –.33 3.37*** .47 .78 .46 .77 .09 2.06** .09 2.07** .05 1.11 .00 .03
Self-practice of a promoter/champion role .04 7.02*** .05 8.77*** –12.18 3.07*** –13.10 3.33*** –.60 2.31** –.56 2.14** .49 1.95*1.04 4.01***
Portion of single inventions –.11 2.41*** –.14 3.11*** –26.73 –3.36*** –28.43 3.60*** –2.23 3.70*** –2.23 3.75*** –.47 .89 –.73 1.50
Network size of promoter/champions –.07 8.85*** –.09 10.99*** 1.14 1.80*1.40 2.20** .12 2.32** .13 2.48** .00 .00 –.01 .46
Network size less promoter/champions .02 3.63*** .04 6.36*** –.72 1.37 –.95 –1.80*–.05 1.26 –.06 1.41*–.01 .41 .06 1.88*
Constant 1.52 10.96*** 2.16 13.88*** 28.20 2.36*20.69 1.69*3.82 4.02*** 3.49 3.42*** .93 1.22 –4.29 3.30***
Log likelihood –1050.85 –1002.66 –827.19 –823.74 –846.55 –844.62
LR chi2(df) 1066.87*** 1163.25*** 28.82*** 35.72*** 23.39*** 27.23***
R2/ Pseudo R2 .34 .37 .02 .02 .01 .02 .22 3.42*** .34 5.72***

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ref ere n Ces
Achilladelis, Basil, Paul Jervis, and A. B. Robertson (1971), A Study of Success and Failure in Industrial Innovation,
Sussex, UK: University of Sussex Press.
Allen, Thomas J. (1977), Managing the Flow of Technology: Technology Transfer and Dissemination of Technological
Information within the R&D-Organization, Cambridge, MA: MIT Press.
Allen, Thomas J. (1967), Communication in the Research and Development Laboratory, Technology Review 70,
31-38.
Allen, Thomas J., Michael Tushman, and David M. Lee (1979), Technology Transfer as a Function of Position in
the Spectrum from Research through Development to Technical Services, Academy of Management Journal 22,
694-708.
Bandura, Albert (1976), Social Learning Theory, Upper Saddle River, NJ: Prentice Hall.
Barney, Jay B. (1991), Firm Resources and Sustained Competitive Advantages, Journal of Management 17, 99-120.
Bunderson, J. Stuart and Kathleen M. Sutcliffe (2002), Comparing alternative conceptualizations of functional diver-
sity in management teams. Process and performance effects, Academy of Management Journal 45, 875-893.
Burgelman, Robert A. (1983), A process model of internal corporate venturing in the diversified major firm, Admini-
strative Science Quarterly 28, 223-244.
Burt, Ronald S. (1992), Structural Holes. The Social Structure of Competition, Cambridge, MA: Harvard University
Press.
Carlile, Paul R. (2004), Transferring, Translating, and Transforming: An Integrative Framework for Managing Knowl-
edge Across Boundaries, Organization Science 15, 555-568.
Clark, Kim B. (1985), The Interaction of Design Hierarchies and Market Concepts in Technological Evolution,
Research Policy 14, 235-251.
Chakrabarti, Alok K. (1974), Role of Champion in Product Innovation, California Management Review 17(2), 58-
62.
Chandler, Alfred D. (1990), Scale and Scope. The Dynamics of Industrial Capitalism, Cambridge, MA: Harvard Uni-
versity Press.
Danneels, Erwin and Elko J. Kleinschmidt (2001), Product innovativeness from the firm’s perspective: Its dimen
-
sions and their relation with project selection and performance, Journal of Product Innovation Management 18,
357-373.
Day, Diana L. (1994), Raising radicals: different processes for championing innovative corporate ventures, Organisa-
tion Science 5, 148-172.
Dosi, Giovanni, Richard R. Nelson, and Sidney G. Winter (2000), The Nature and Dynamics of Organizational Ca-
pabilities, Oxford, UK: Oxford University Press.
Dougherty, Deborah and Cynthia Hardy (1996), Sustained product innovation in large, mature organizations: over-
coming innovation-to-organization problems, Academy of Management Journal 39, 1120-1153.
Ellis, Henry C. (1965), The Transfer of Learning, New York, NY: MacMillan.
Estes, William K. (1970), Learning Theory and Mental Development, New York, NY: Academic Press.
Fleming, Lee and Olav Sorensen (2004), Science as a map in technological search, Strategic Management Journal
25(8-9), 909-929.
Folkerts, Liesa (2001), Promotoren in Innovationsprozessen. Empirische Untersuchung zur personellen Dynamik, Wies-
baden: Deutscher Universitäts-Verlag.
Folkerts, Liesa and Hauschildt, Jürgen (2002), Personelle Dynamik in Innovationsprozessen. Neue Fragen und Be-
funde zum Promotorenmodell, Die Betriebswirtschaft 62, 7-23.

CHAMPIONS
SBR 59 October 2007 340363 361
Foss, Nicolai J. and Martin Iversen (1997), Promoting Synergies in Multiproduct firms: Toward a Resource-Based
View, Working Paper Nr. 97-12, Department of Industrial Economics and Strategy, Copenhagen Business School,
Copenhagen.
Frese, Erich (2002), Der Glaube an die organisatorische Weisheit des Marktes, Frankfurter Allgemeine Zeitung 131
(10.06.2002), 23.
Frost, Peter J. and Carolyn P. Egri (1991), The political process of innovation, in Berry M. Staw and Larry L. Cum-
mings (eds.), Research in Organizational Behavior, Greenwich: Jai Pr, 229-295.
Fuchs-Heinritz, Werner, Rüdiger Lautmann, Otthein Rammstedt, and Hanns Wienold (1995) (eds.), Lexikon zur
Soziologie, Opladen: VS Verlag für Sozialwissenschaften.
Galbraith, Jay R. (1982), Designing the innovating organization, Organizational Dynamics 10, 5-25.
Gemünden, Hans Georg (1985), Promotors – Key Persons for the Development and Marketing of Innovative In-
dustrial Products, in Klaus Backhaus, David Wilson (eds.), Industrial Marketing. A German-American Perspective,
Berlin/Heidelberg/New York/Tokyo: Springer, 134-166.
Gemünden, Hans Georg and Katharina Hölzle (2005): Schlüsselpersonen der Innovation – Champions und Promo-
toren, in Oliver Gassmann and Sönke Albers (eds.), Handbuch Technologie- und Innovationsmanagement. Strategie
– Umsetzung – Controlling, Wiesbaden: Gabler, 459-474.
Gemünden, Hans Georg and Achim Walter (1996), Förderung des Technologietransfers durch Beziehungspromoto-
ren, Zeitschrift Führung und Organisation 65, 237-245.
Gemünden, Hans Georg and Achim Walter (1995), Beziehungspromoter, Schlüsselperson für inter-organisationale
Innovationsprozesse, Zeitschrift für Betriebswirtschaft 65, 971-986.
Gierschner, Hans C. (1991), Information und Zusammenarbeit bei Innovationsprozessen, Frankfurt am Main: Lang.
Grant, Robert M. (1996), Toward a Knowledge-Based Theory of the Firm, Strategic Management Journal 17, 109-
122.
Griliches, Zvi (1990), Patent Statistics as Economic Indicators: A Survey, Journal of Economic Literature 28, 1661-
1707.
Hansen, Morten T. (1999), The search-transfer problem: The role of weak ties in sharing knowledge across organiza-
tion subunits, Administrative Science Quarterly 44, 82-111.
Harhoff, Dietmar and Markus Reitzig (2001), Strategien zur Gewinnmaximierung bei der Anmeldung von Patenten,
Wirtschaftliche und rechtliche Aspekte als Entscheidungsgrössen beim Schutz von FuE, Zeitschrift für Betriebs-
wirtschaft 71, 509-530.
Harhoff, Dietmar, Frederic M. Scherer, and Katrin Vopel (2003), Citations, Family Size, Opposition and the Value
of Patent Rights, Research Policy 32, 1343-1363.
Hauschildt, Jürgen (2004), Innovationsmanagement, 3. Auflage, München: Verlag Vahlen.
Hauschildt, Jürgen and Alok K. Chakrabarti (1988), Arbeitsteilung im Innovationsmanagement – Forschungsergeb-
nisse, Kriterien und Modelle, Zeitschrift für Organisation 57, 378-388.
Hauschildt, Jürgen and Hans Georg Gemünden (1999) (Hrsg.), Promotoren – Champions der Innovation, Wiesbaden:
Gabler.
Hauschildt, Jürgen and Edgar Kirchmann (1997), Arbeitsteilung im Innovationsmanagement. Zur Existenz und
Effizienz von Prozesspromotoren, Zeitschrift Führung und Organisation 66, 68-73.
Hauschildt, Jürgen and Günter Schewe (1997), Gatekeeper und Promotoren. Schlüsselpersonen in Innovationspro-
zessen in statischer und dynamischer Perspektive, Die Betriebswirtschaft 57, 506-516.
Henderson, Rebecca M. (1996), Technological Change and the Management of Architectural Knowledge, in Cohen,
Michael D. and Lee S. Sproull, (eds.), Organizational Learning, Thousand Oaks, CA: Sage Publications, 359-
375.

K. ROST/K. HÖLZLE/H.G. GEMÜNDEN
362 SBR 59 October 2007 340363
Henderson, Rebecca M. and Kim B.Clark (1990), Architectural Innovation: The Reconfiguration of Existing Product
Technologies and the Failure of Established Firms, Administrative Science Quarterly 35, 9-30.
Hennessy, Beth A., Teresa M. Amabile, and M. Martinange (1989), Immunizing Children Against the Negative Ef-
fects of Reward, Contemporary Educational Psychology 14, 212-227.
Hodgson, Geoffrey M. (1998), Competence and Contract in the Theory of the Firm, Journal of Economic Behavior
and Organization 35, 179-201.
Högl, Martin and Katharina Weinkauf (forthcoming), Managing task interdependencies in multi-team projects:
A longitudinal study, to appear in Journal of Management Studies.
Hollander, Samuel (1965), The Sources of Increased Efficiency: A Study of DuPont Rayon Plants, Cambridge, MA: MIT
Press.
Howell, Jane M. and Christopher A. Higgins (1990a), Champions of Technological Innovation, American Science
Quarterly 45, 317-331.
Howell, Jane M. and Christopher A. Higgins (1990b), Champions of change: Identifying, understanding and sup-
porting champions of technological innovations, Organizational Dynamics 19, 40-54.
Howell, Jane M., Christine M. Shea, and Christopher A. Higgins (2005), Champions of product innovations: defin-
ing, developing, and validating a measure of champion behaviour, Journal of Business Venturing 20, 641-661.
Janis, Irving Lester (1972), Victims of Groupthink. A Psychological Study of Foreign Policy Decisions and Fiascos, Boston:
Houghton Mifflin.
Kallen, Horace M. (1973), Innovation, in Amitai Etzioni and Eva Etzioni-Halevy (eds.), Social Change – Sources,
Patterns, and Consequences, New York: Basic Books, 447-450.
Katz, Ralph and Michael Tushman (1981), Investigation into the Managerial Roles and Career Paths of Gatekeepers
and Project Supervisors in a Major R&D Facility, R&D Management 11, 103-110.
Klöter, Ralf (1997), Opponenten im organisationalen Beschaffungsprozess, Wiesbaden: Deutscher Universitäts-Verlag.
Kräkel, Matthias (2002), Synergien, in Hans-Ulrich Küpper and Alfred Wagenhofer (eds.), Handwörterbuch der
Unternehmensrechnung, Stuttgart: Schaeffer-Poeschel, 1910-1918.
Lam, Alice (2005), Work Roles and Careers of R&D Scientists in Network Organizations, Industrial Relations 44,
242-275.
Langlois, Richard N. (1992), Transaction-Cost Economics in Real Time, Industrial and Corporate Change, Vol 1,
99-127.
Leonard-Barton, Dorothy (1998), Wellsprings of Knowledge, Cambridge, MA: Harvard Business School Press.
Mansfield, Edwin (1968), The Economics of Technological Change, New York, NY: Norton.
March, James G. and Herbert A. Simon (1958), Organizations, New York, NY: Wiley.
Markham, Stephen K. and Abbie Griffin (1998), The breakfast of champions: associations between champions and
product development environments, practices and performance, Journal of Product Innovation Management 15,
436-454.
Mehrwald, Herwig (1999), Das ‘Not Invented Here’ (NIH) – Syndrome in Forschung und Entwicklung, Wiesbaden:
Deutscher Universitäts-Verlag.
Michel, Jacques and Bernd Bettels (2001), Patent Citation Analysis, A Closer Look at the Basic Input Data form
Patent Search Reports, Scientometrics 51, 185-201.
Nelson, Robert R. and Sidney G. Winter (1982), An evolutionary theory of economic change, Cambridge, MA: Belknap
Press.
Nisbett, Richard E. and Lee D. Ross (1980), Human Inference: Strategies and Shortcomings of Social Judgment, Engle-
wood Cliffs, NJ: Prentice-Hall.
Nooteboom, Bart (2000), Learning and Innovation in Organizations and Economies, Oxford, UK: Oxford University
Press.

CHAMPIONS
SBR 59 October 2007 340363 363
Organ, Dennis W. (1988), Organizational Citizenship Behavior: the Good Soldier Syndrome, Lexington, KY: Lexington
Books.
Pirolli, Peter L. and John R. Anderson (1985), The Role of Learning from Example in the Acquisition of Recursive
Programming Skill, Canandian Journal of Psychology 39, 240-272.
Polanyi, Michael (1985), Implizites Wissen, Frankfurt am Main: Suhrkamp.
Ritter, Thomas and Hans Georg Gemünden (2003), Network Competence: Its Impact on Innovation Success and its
Antecedents, Journal of Business Research 56 (9), 745-755.
Roberts, Edward B. and Alan Fusfeld (1988), Critical functions: needed roles in the innovation process, in Ralph
Katz, (ed.), Managing Professionals in Innovative Organizations, Cambridge, MA: Ballinger, 101-120.
Rost, Katja (2006), Sozialstruktur und Innovationen. Dilemma-Entschärfung in Innovationsprozessen durch zielför-
dernde Ausgestaltung von Netzwerken, sozialen Rollen und Ressourcen, Berlin.
Rothwell, Roy (1992), Successful Industrial Innovation: Critical Factors for the 1990s, R&D Management 22, 221-
238.
Rothwell, Roy, Chris Freeman, Anthony Horlsey, V.T.P. Jervis, A.B. Robertson, and James Townsend (1974), SAP-
PHO updated – Project SAPPHO Phase II, in Research Policy 3, 258-291.
Rumelhart, David (1980), The Building-Blocks of Cognition, in William F. Brewer, Betram C. Bruce, and Rand. J.
Spiro (eds.), Theoretical Issues in Reading Comprehension, Hillsdale, NJ: Erlbaum.
Schon, Donald A. (1963), Champions for Radical New Inventions, Harvard Business Review 41, 77-86.
Shane, Scott A. (1994), Are champions different from non-champions?, Journal of Business Venturing 9, 397-421.
Shepard, Herbert A. (1967), Innovation-Resisting and Innovation-Producing Organizations, The Journal of Business
40, 470-477.
Spender, John-Christopher (1993), Some Frontier Activities Around Strategy Theorizing, Journal of Management
Studies 30 (Special Issue), 11-29.
Tietze, Oliver (2003), Strategische Positionierung in der Automobilbranche. Der Einsatz von virtueller Produktentwicklung
und Wertschöpfungsnetzwerken, Wiesbaden: Gabler.
Tushman, Michael L. and Philip Anderson (1986), Technological discontinuities and organizational environments,
Administrative Science Quarterly 31, 439-465.
Turner, Karynne L. and Mona V. Makhija (2006), The role of organizational controls in managing knowledge, Acad-
emy of Management Review 31, 197-217.
Walter, Achim (1998), Der Beziehungspromoter. Ein personaler Gestaltungsansatz für erfolgreiches Relationship Marketing,
Wiesbaden: Gabler.
Winter, Sidney G. (1987), Knowledge and competence as strategic assets, in David J. Teece (ed.), The competitive
challenge: Strategy for industrial innovation and renewal, Cambridge, MA: Ballinger Pub Co., 159-184.
Wiswede, Günter (2004), Rollentheorie, in Georg Schreyögg and Axel v. Werder (eds.), Handwörterbuch Unterneh-
mensführung und Organisation, Stuttgart: Schaeffer-Poeschel.
Witte, Eberhard (1973), Organisation für Innovationsentscheidungen – Das Promotorenmodell, Göttingen: Schwart.