International Journal of Innovation Management
Vol. 7, No. 3 (September 2003) pp.1–30
© Imperial College Press
SUCCESS AND FAILURE OF INNOVATION:
A LITERATURE REVIEW
GERBEN van der PANNE, CEES van BEERS and
ALFRED KLEINKNECHT
Dept. Economics of Innovation, Delft University of Technology
The Netherlands
Received 7 January 2003
Revised 16 June 2003
Accepted 17 June 2003
In this paper 43 recent studies on determinants of success and failure of innovation are
reviewed. Several studies report a larger number of success factors and provide some
rank ordering. Analyzing these ranks, we observe consistency among the studies on the
ten highest-ranking success factors; however, the studies are far from consistent when
lower-ranking factors are considered. Agreement exists on the positive impact of factors
such as firm culture, experience with innovation, multidisciplinary R&D teams or the
advantages of the matrix organization. On factors such as fierceness of competition, R&D
intensity, top management support and the degree to which a project is innovative or
technologically advanced, ambiguity remains.
Keywords: Innovation; success factors; viability.
1
“But in capitalist reality as distinguished from its textbook
picture, it is not…(price) competition which counts but the
competition from the new commodity, the new source of
supply, the new type of organization…competition which
commands a decisive cost or quality advantage and which
strikes not at the margins of the profits…of the existing
firms but at their very lives. This kind of competition is as
much more effective than the other as a bombardment is in
comparison with forcing a door.”
(Schumpeter 1943: 84)
Introduction
Why does not everybody innovate? It is widely recognized that innovation is key to the
economic performance of firms. Innovative firms grow faster in terms of employment
and profitability (see for example the econometric studies by Geroski et al., 1993; or
Kleinknecht et al., 1997). If nonetheless many firms do not engage in innovation, this is
due to several types of uncertainties involved. Asplund and Sandin (1999) and Cozijnsen
et al. (2000) observe that only one out of every five projects ever initiated proves viable.
Against this background, there is an obvious need to systematically assess factors
decisive for success and failure of innovation. Not surprisingly, a large body of literature
on success factors has emerged during the past 20 years. At first glance this literature
remains inconclusive. Different views exist regarding the relevance of success factors.
While some studies argue a certain group of factors being crucial, other studies ignore the
very same factors and claim different factors to be decisive. Studies also differ in terms of
alleged causalities.
This inconsistency among studies may have several reasons. One is the heterogeneity in
samples as well as methodology. Samples differ as some studies investigate one specific
industry, whereas others cover several industries. Methods differ, as some studies are
qualitative while others adopt a quantitative approach. The studies also remain
inconsistent in measuring (degrees of) success. There is little effort among the various
contributors to assess (causes of) differences between their studies, or as Crawford (1987:
22) puts it: “None tried to compare, except to themselves”. A more general problem is
that perceptions may be biased and misleading as respondents are personally involved in
the projects evaluated. In this paper it is investigated whether, in spite of a seemingly
large diversity, some common insights can be distilled from recent contributions.
2
The first major investigation of success factors was the SAPPHO-study (Scientific
Activity Predictor from Patterns with Heuristic Origins), conducted in the early 1970s in
the United Kingdom. The study compared 29 successful with 29 unsuccessful
innovations in chemicals and scientific instruments and found 27 characteristics of the
innovation process that discriminated between success and failure. These relate to the
innovator’s ability to understand customer needs, marketing capabilities, the efficiency of
the development process, the extent to which the firm is able to adequately absorb
external information and management skills (Freeman et al., 1972).
The SAPPHO-study was followed by Cooper's (1980) study Project NewProd. Based on
200 Canadian innovations, it showed that viability is determined by three factors. Of
primary importance is the degree to which the product is unique and superior compared
to existing alternatives. The innovator’s understanding of (future) market developments is
the second most important factor. Along with the product’s synergy with the firm’s
overall technological and manufacturing resources, these factors determine half the
product’s viability. Of equal importance is Maidique and Zirger’s (1984) Stanford
Innovation Project, arguing that success is the outcome of a wide range of firm and
project related factors; a single magical factor does not exist.
In addition to these explorative studies, there is a larger literature investigating a wide
variety of factors affecting a new product’s viability — technologically as well as
commercially. Our review of these studies eventuates in a classification of four major
headings (see Figure 1):
(1) Firm related factors;
(2) Project related factors;
(3) Product related factors; and
(4) Market related factors.
In their assessment of the literature, some authors engaged in meta-analyses, estimating
“regressions on regressions” (e.g. Henard & Szymanski, 2001). Given the nature of the
literature to be reviewed, we have chosen for a qualitative review as a first step. In order
to arrive at a more systematic assessment, we proceed with a rank correlation analysis
and round up, in Appendix A, with a stylized overview of all studies reviewed in this
paper.
3
The qualitative review follows the categories exhibited in Figure 1. In the next section,
unambiguous success factors are discussed; factors lacking consensus are reviewed in
section 3. In section 4 the rank order analysis is presented. Section 5 covers conclusions.
Considering the large number of studies covered, references are confined to those authors
typical for (or typically deviant from) a particular argument.
Figure 1:
Critical factors for successful innovation
Firm related factors:
•
Firm culture
•
Experience
•
R&D team
•
Strategy towards
innovation
•
Organisational
structure
•
R&D intensity
Product related
factors:
•
Relative price
•
Relative quality
•
Innovativeness
•
Technologically
advanced
Technological viability
Project related factors:
•
Complementarity
•
Management
style
•
Top management support
Success
Commercial
viability
Market related
factors:
•
Concentration
of target market
•
Timing market
introduction
•
Competition
•
Marketing
2 Factors of Consensus
Following the categories exhibited in Figure 1, in this section generally acknowledged
success factors are discussed. Factors affecting the project's technological viability, i.e.
firm and project related factors (Sec. 2.1) are distinguished from determinants of
commercial viability, i.e. product and market related factors (Sec. 2.2).
4
2.1 Technological viability
Firm related factors
With respect to the technological viability of an innovation project, four factors
concerning the firm are generally considered relevant: the firm's culture, experience with
innovation, the Research and Development (R&D) team and the firm’s strategy towards
innovation.
Firm culture
A culture susceptible to innovation is a prerequisite for the firm to acknowledge the
necessity to innovate and is therefore undisputedly considered crucial to the firm’s
technological capabilities in the long term (e.g. Ekvall & Ryhammar, 1998; Lester,
1998).1 Cultural resistance to innovation may arise from entrenched routines and
interpretative barriers. Routines structure activities, processes and information. This
tempts employees to focus solely on their own tasks and responsibilities. Consequently,
barriers are incurred when searching for solutions that surpass individual responsibilities.
This is incompatible with the inherent collective nature of innovation projects,
demanding all participants to work towards a common objective (Dougherty, 1992).
Likewise, interdepartmental cooperation affects technological viability (Souder, 1988).
Two out of every three innovative firms report that interdepartmental cooperation is
hampered, mainly due to a lack of mutual trust (Rochford & Rudelius, 1997).
Departments should be involved from the onset. Along with well-defined tasks and
responsibilities for all departments concerned, this creates cultural susceptibility to
innovation. Adequate interdepartmental communication should be aimed for (Calantone
et al., 1993). The term “adequate” should be read as flexible since formal and
institutionalized communication is considered an impediment to success (Hopkins, 1981).
A mission statement emphasizing the value of product development and internal
entrepreneurship further adds to the firm’s cultural susceptibility (Johne & Snelson,
1988).
1
Openness of a firm's culture to R&D results is directly associated with commercial viability as well. Mansfield and
Wagner (1975) argue that a culture susceptible to R&D-results improves the rate of successfully commercialized
innovation projects by 15%.
5
Experience with innovation
Previous engagements in innovation projects are conducive to the firm’s technological
capabilities as these improve skills decisive for the course of innovation projects. Firms
should engage in projects that resemble the firm specific experiences with the
technology, production and marketing skills involved2 (Stuart & Abetti, 1987; Bessant,
1993). In addition, projects resembling previous engagements allow for substantial
reduction of the time-to-market (Wind & Mahajan, 1988). Experience enables the firm to
capitalize upon learning-by-doing and learning-by-failing effects. Whereas the first
improves the firm’s R&D efficiency, the latter exposes the firm’s weaknesses. Both
phenomena are considered crucial in the product learning cycle (Maidique & Zirger,
1985; Zirger, 1997).
Characteristics of the R&D team
Several characteristics of the R&D team affect the firm’s technological capabilities. One
is the team’s configuration; interdisciplinarity adds to the project's viability (Roure &
Keeley, 1990). Although technological capabilities are indispensable, equilibrium
between both technological and marketing skills should be aimed for: most often the
emphasis is on the former (Cooper, 1983).
A second distinctive feature is the attendance of a product champion. Confronting
internal resistance to innovation, R&D teams supported by an individual acting as an
innovation-dedicated internal entrepreneur are more successful than teams lacking this
support (Link, 1987; Kleinschmidt & Cooper, 1995). In processing the firm’s internal and
external scientific information, the product champion also acts as an efficient
technological gatekeeper (Stuart & Abetti, 1987; Rothwell, 1992). Many projects lack the
product champion’s devotion, mainly due to lack of top management support: only 40
percent of innovating firms deliberately encourage product champions to arise (Page,
1993). This is attributed to lacking familiarity with concepts to single out potential
candidates (Wind & Mahajan, 1988). Two such concepts are psychological tests (Howell
& Higgins, 1990) and adequate merit payments (Page, 1993). Rothwell (1992) opposes
these concepts and argues that official nomination disrupts intrinsic motivation and
dedication.
2 Experience is associated with commercial capabilities as well. Experience adds to the firm’s ability to understand
customer needs, improving marketing skills (Maidique & Zirger, 1985).
6
Firm strategy towards innovation
An articulated innovation strategy is generally considered as a success factor. First, it
provides a guideline for dealing with strategic issues, such as selecting the markets to
enter and the skills to develop (Lester, 1998). Second, strategically planned projects
enable the firm to take advantage of synergy between similar innovation projects. Third,
learning-by-doing effects materialize, enabling the firm to reap benefits of previous
successful innovations along with firm-specific skills that emanate from them (Rothwell,
1992). The relevance of innovation strategies has been evidenced by empirical studies; in
order to maximize the benefits of previous innovations, innovation activities must be
given a strategic direction (Cottam et al., 2001).
Numerous innovation strategies are defined in the literature. Pro-active can be
distinguished from re-active strategies. The first pursue product innovations in order to
obtain product leadership in the market, whereas re-active strategies pursue product
development as a safeguard against competing products (Johne & Snelson, 1988).
One constitution of the pro-active strategies is the portfolio strategy, in which the firm
simultaneously proceeds with several innovation projects in different phases of
development (Gobeli & Brown, 1987). This strategy is generally considered appropriate.
First, it preserves the firm from a short-term low risk profile. Second, portfolio planning
induces projects targeted at specific, profitable market segments to be counter-balanced
by projects based on fundamental R&D activities. Therefore, portfolio planning comes
down to improvement as well as radical rejuvenation of the firm’s product line (Wind &
Mahajan, 1988). Third, working on both incremental and radical innovations, this
strategy allows for financing the latter with the bread-and-butter profits generated by the
former. This preserves the firm from relying solely on product differentiation (Zirger,
1997). Fourth, portfolio planning adds directly to R&D skills: R&D teams involved in
several projects simultaneously are more successful than those that are not (Kleinschmidt
& Cooper, 1995). Although innovation strategies are conducive to the firm’s
technological capabilities, these are not common practice; according to Page (1993), only
half the innovating firms articulate an innovation strategy.
Project related factors
Two project related factors affect successful completion and hence contribute to the
technological viability of an innovation project. These are the project’s complementarity
with the firm’s resources and the management style.
7
Complementarity
The prospects of innovations depend on the project’s compatibility with the firm’s
resources in broad terms, i.e. management and market research skills, sales, distribution,
R&D and production facilities (Maidique & Zirger 1984; Stuart & Abetti 1987). Synergy
emanates from phenomena like learning-by-doing and economies of scale and scope
(Zirger 1997). Cooper (1983) and Link (1987) argue that synergy between R&D and
marketing strengths is most important. Hopkins (1981) emphasizes synergy at the product
level; the innovation must fit into the product group customers are already familiar with.
Innovation management style
Management style is often believed to affect project viability. According to Cozijnsen et
al. (2000) adequate management of time, costs, information and decision-making
determines 60% of the projects' viability. In order to make the project better manageable,
most innovators split the project into constituent phases (see e.g. Crawford, 1991: 27).
Most often, six phases are distinguished. The project is initiated by a planning phase,
followed by phases of brainstorming, screening and evaluation, development and market
research. It eventuates in the market launch phase.
The more the process is kept to this trajectory, the more successful it will be (Cooper &
Kleinschmidt, 1987). Factors crucial for success increasingly become manageable once
the project is split up (Calantone et al., 1993): skipping phases is a main cause of failure
(Wind & Wahajan, 1988). Empirical studies indeed show that technological viability
increases with the extent to which the trajectory is completed (Kleinschmidt & Cooper,
1995). More important than completing the trajectory is the attentiveness with which it is
pursued. Particularly in the cases of radical innovations this will reduce uncertainty
(Rochford & Rudelius, 1997).
In the literature, two phases of the trajectory are emphasized: planning and evaluation.
During the planning phase, a medium-term plan identifying well-defined milestones
should be formulated. Such a validation-driven planning converts uncertainties into clear
tasks and responsibilities, thereby streamlining the course of the innovation project
(Maidique & Zirger, 1985; Pinto & Slevin, 1989; Lester, 1998). The evaluation phase is
emphasized because adequate evaluation enables the firm to distinguish viable projects
from those less viable, thereby minimizing the project’s inherent uncertainty (Mansfield
& Wagner, 1975).
8
There are different views with regard to the relative impact of planning and evaluation
during earlier and later phases of development. Cooper and Kleinschmidt (1987) argue
that the early phases are most important. A detailed project definition in terms of market
needs, market preferences and product specifications enables the innovator to arrive at a
sound stop/go-decision. This contrasts with Schmidt’s view that the relevance of predevelopment activities is exaggerated. Mistakes in the early phases are much less harmful
than mistakes in the successive phases. “Upfront activities are important, but the later
activities are critical” (Schmidt, 1995: 31).
2.2 Commercial viability
With respect to the product’s commercial viability, two product (i.e. price and quality)
and two market related factors (i.e. market concentration and market introduction) are
generally acknowledged.
Product related: Relative price and quality
Though recognized by only few studies, the relevance of a product’s price relative to
competing products or substitutes remains undisputed. The extent to which the innovation
reduces the customer’s total-costs-of-use (Cooper & Kleinschmidt, 1987) as well as the
price in relation to quality is generally considered important (Madique & Zirger, 1984). It
is generally acknowledged that successful innovations meet customer needs on a number
of features simultaneously: quality, relative price, total-costs-of-use, convenience-of-use,
after-sales services, and backward compatibility (Maidique & Zirger, 1984). Conversely,
less successful innovations excel predominantly in a reduction of total-costs-of-use only
(Roy & Riedel, 1997). The literature unanimously considers product quality a
prerequisite for success (e.g. Link, 1987; Calantone et al., 1993; Hultink, 1998). Roure
and Keeley (1990) consider it the only 'real' determinant of success.
Market related: Concentration of targeted market and timing of market introduction
One market related factor associated with the product’s commercial viability is the extent
to which the product’s potential market is concentrated, reducing costs of
communication. The relation may not be linear, though. Roure and Keeley (1990) report
evidence of a U-shaped association between concentration of buyers and viability: high
as well as low degrees of buyer concentration add to viability.
9
Early market introduction may prove a competitive advantage (Hopkins, 1981; Maidique
& Zirger, 1984). Johne and Snelson (1988) estimate that six to twelve months delay
reduces financial returns by half. Therefore, it is recommended to create short-cuts in the
innovation process to abbreviate the time-to-market. (Wind & Mahajan, 1988).
Although the status of early market introduction remains undisputed, some qualifications
have been made. First, the benefits of early introduction differ by type of innovation;
whereas incremental innovations reap the benefits of accelerated introduction, original
innovations do not. The latter gain from relatively extensive development trajectories in
which the development process is pursued attentively (e.g. Yoon & Lilien, 1985).
Second, early market introduction may be in conflict with the aim of product quality (e.g.
Hultink, 1998). In spite of such arguments, many innovators respond to the need for
speed. Among others, Page (1993) reports that over 40% of the innovators attempt to
abbreviate the time-to-market.
3 Factors Lacking Consensus
In our discussion on success factors that lack consensus in the literature, we again follow
the classification in our above Figure 1 and distinguish between factors acting on
technological (Sec. 3.1) and commercial viability (Sec. 3.2).
3.1 Technological viability
Firm related factors
With respect to the technological viability of an innovation project, there is no consensus
on the relevance of two factors, i.e. organizational structure and R&D intensity.
Organizational structure
There is debate about the appropriateness of various organization structures for
innovation activities. There is agreement that functional organizations are considered
inadequate. Their pronounced levels of formalization and control are in conflict with the
trial-and-error character of innovation processes (e.g. Johne & Snelson, 1988; Calantone
et al., 1993). Innovators themselves tend to refute the functional structure as well; Larson
and Gobeli (1988) report that only 20% of the functionally organized innovating firms is
satisfied with this structure.
10
The alternative, i.e. an organic, more flexible and adaptive structure, is unanimously
preferred3. Organically organized firms outperform functionally organized firms in terms
of success rates. Firms that explicitly strive for discovering and capitalizing on new
market opportunities appear more often organically organized. Path analysis shows that
organically organized firms develop superior technical and marketing capabilities; the
latter two being recognized as important success factors autonomously (Calantone et al.,
1993). In addition to these empirical observations, two theoretical arguments in favor of
the organic structure dominate the literature.
The first is sociological. Other than formal structures, which lead to selection and social
confirmation, organic structures provoke individual expression and encourage product
champions to arise. Considering the importance of the product champion’s attendance,
the firm’s degree of “organicity” can be considered a success factor (Howell & Higgins,
1990). The second argument favoring organic structures stems from the nature of the
innovation process. Equilibrium between formalization (in the interest of efficiency) and
the advantages of a loose, open, creative and adaptive organic structure should be aimed
for. Empirical studies show that successful innovative firms are loosely structured during
the initiation phase of the development process and evolve to more formal structures as
the product becomes better defined (Johne & Snelson, 1988; Rothwell, 1992; Bart, 1993).
Arguments opposing organic structures have also been made. First, some empirical
studies report a negative impact of organicity on a firm’s innovation capabilities. Among
others, Rubenstein et al. (1976) argue that one ought to control the process tightly,
especially during the early phases of the innovation process; the argument that autonomy
acts as an incentive for innovation is false (see also Stuart & Abetti, 1987). Indeed, many
successful innovators prefer tight control during the entire innovation process (Larson &
Gobeli, 1988). Differences remain regarding two different constitutions of the organic
structure: the venture team structure and the matrix structure (Johne & Snelson, 1988;
Larson & Gobeli, 1988; Rothwell, 1992; Page, 1993; Kleinschmidt & Cooper, 1995;
Lester, 1998). In both settings, a project manager is put in charge of a team composed of
personnel from several functional areas within the firm. However, whereas the venture
team does not involve the managers of the constituent functional areas, the matrixstructure does.
The arguments in favor of the venture team relate to its autonomy. A venture team,
behaving as a firm-within-the-firm, allows for an indispensable equilibrium between
internal entrepreneurship and risks management. In addition, it allows for shorter
For a concise comparison between “functional” (or “mechanistic”) and ‘’organic’’ organization structures see
the classical contribution by Burns and Stalker (1961: 119–122).
3
11
decision making trajectories and improved flexibility (Lester, 1998). Many successful
innovators have deliberately abandoned the matrix concept (Larson & Gobeli, 1988).
However, the matrix-structure does have several advantages over the venture team. First,
it imposes integration of various functional inputs. If interdisciplinarity is acknowledged
as a success factor favoring creativity, the matrix structure outperforms the venture-team
(Johne & Snelson, 1988). It also induces the firm to focus on both customer needs and
technical feasibility during the entire innovation process (Rothwell, 1992). Second,
empirical studies show that innovation projects embedded in a matrix structure obtain
improved success rates (Kleinschmidt & Cooper, 1995). Hence the matrix structure
became increasingly popular during the 1980s. During the 1960s, most innovation
activities were conducted within autonomous development departments: In the early
1990s, three out of every four innovators have implemented some kind of matrix
structure instead (Page, 1993).
Most of these arguments are valid for both the venture team and the matrix structure.
Only one argument is claimed to discriminate between both alternatives: relative to the
venture team, the matrix structure allows for superior planning techniques (Larson &
Gobeli, 1988). More generally, however, one should consider the impact of the
organizational structure in perspective: “Organizations do not make R&D projects
successful, individuals do” (Rubinstein et al. 1976: 18).
R&D intensity
Innovative output obviously increases with R&D investments. This is confirmed by
empirical studies showing that substantial financial resources are a prerequisite for
success (Page, 1993). Conversely, a lack of financial resources is considered a
predominant factor of failure (Rubenstein et al., 1976). However, regarding R&D
intensity (i.e. R&D expenditures relative to sales), this proposition is subject to debate.
R&D intensive firms generally obtain improved (commercial) success rates (Gemunden
et al., 1992); nonetheless, this relation is less than clear-cut. Among others, Acs and
Audretsch (1991) argue that the causality between R&D input and innovative output is
characterized by diminishing returns to scale. As far as large and complex organizations
are concerned, this may be due to managerial diseconomies of scale. Brouwer et al.
(1999) observe that the relation between R&D intensity and innovative output is
moderated by such factors as regional knowledge spillovers, demand-pull effects or
differences in technological opportunity. Such factors explain that R&D input and
12
innovative output are far less strongly correlated than one would intuitively expect4.
Cooper (1983) reports additional evidence. Firms spending only 1% of total sales on
R&D generate one quarter of total sales with innovative products; firms spending at least
4% of total sales on R&D generate only 40% of total sales with innovative products.
Project related factors
Under this heading, only one factor remains ambiguous: top management support.
Top management support empowers the innovation project and serves as a driving force
for major initiatives and efforts. Rothwell (1992) emphasizes that top management
support may be instrumental in overcoming internal resistance to innovation. Page (1993)
concludes that one out of every four innovators qualify top management support as a
prerequisite for success. Another argument relates to the concept of the product life cycle
and claims that one can judge on the feasibility of an innovation project earliest five years
after launch. Hence, innovation projects demand long-term commitment (Brenner, 1994).
This requires a risk-tolerant top management that not only prevents viable projects to be
aborted in advance, but also enables the firm to take advantage of learning-by-failing
(Rothwell, 1992). Gobeli and Brown (1987) observe that top management support
accounts for improved feasibility of radical innovations over incrementally improved
products. Management support endangers the innovation as well. Excessive top
management support may permit individuals to be involved for too long a period, causing
stiffening (Rubenstein et al., 1976). Kleinschmidt and Cooper (1995) argue that top
management support adds to failure as often as it does to success.
3.2 Commercial viability
The literature remains inconclusive on four product and market related factors. The
product related factors refer to the degree to which the product is innovative and
technologically advanced. The market related factors concern the fierceness of
competition and marketing capabilities.
4
For similar results see several chapters in Kleinknecht (1996) and Kleinknecht and Mohnen (2002).
13
Innovativeness
Arguments on innovativeness as a success factor are based on empirical observations.
Some studies establish a U-shaped impact of innovativeness on viability. Among others,
Kleinschmidt and Cooper (1991) observe that highly innovative products obtain success
rates of 80%, whereas only half the innovations classified as medium-innovative prove
viable; products characterized as moderately innovative show success rates of
approximately 70%. Highly innovative products show improved success rates as these
stand out in terms of product advantages. These innovations also benefit from relatively
comprehensive pre-development activities. The modest success rates of mediuminnovative products is ascribed to absence of synergy — technologically as well as from
a marketing point of view. Exactly these synergy effects account for the viability of
moderately innovative products. Hence one may argue that highly innovative products
are not as risky as generally presumed (Kleinschmidt & Cooper, 1991). This proposition
is in contradiction with research reported by Zirger (1997), suggesting linearity between
innovativeness and viability with highly innovative products in the lead, followed by
medium and moderately innovative products.
Technologically advanced products
The literature remains inconclusive as to whether the degree to which the product is
technologically advanced affects its prospects. Several studies argue that this variable
adds to viability (Cooper, 1983; Cooper & Kleinschmidt, 1987; Schmidt, 1995); others
fail to establish any causality (Maidique & Zirger, 1984). Rackham (1988) reports a
negative impact: an innovator’s emphasis on technical novelties may compromise
commercial performance. In the cases of technologically advanced products, salesmen
may focus on product features rather than customer needs. This discloses the essence of
numerous superior but failed innovations; the feature-based approach tends to dominate
the customer-based approach (Rackham, 1988).
Competition
Arguments on fierceness of competition as a success factor are based on empirical
observations and remain inconsistent. Link (1987) considers fierce competition as a main
factor of failure. Yoon and Lilien (1985) and Roure and Keeley (1990) argue that
fierceness of competition is inversely related to new product success: The less
competitive the market, the more viable the product. Stuart and Abetti (1987) establish
14
similar causalities and suggest that innovators should penetrate less dynamic and less
competitive (niche) markets. However, Cooper and Kleinschmidt (1987) and
Kleinschmidt and Cooper (1995) argue that such market characteristics lack any
predictive power for new product success, since fierceness of competition may be
expected to be counterbalanced by entry or exit of potential and incumbent firms,
respectively. More generally, this ambiguity resembles the long-standing discussion in
industrial economics on the impact of market structure on innovation (see Kamien &
Schwartz, 1982). Notably the survey by Scherer (1992) suggests that, if so, the impact of
market structure on innovation cannot be overwhelmingly strong.
Marketing
Skills in market research are generally considered a success factor (Cooper, 1983; Yoon
& Lilien, 1985; Calantone et al., 1993). Conversely, inadequate market research is
considered the main factor of failure: over-estimated forecasts of demand and faulty
translation of engineers’ desires into customers’ needs are well-known pitfalls (Hopkins,
1981). Although the literature is unambiguously supportive for adequate market research
as a success factor, one prevailing instrument — involving consumers into the innovation
process — remains controversial. One argument is the volatility of customer needs,
which therefore require adequate study (Wind & Mahajan, 1988; Calantone et al., 1993;
Asplund & Sandin, 1999). The majority of successful ideas originate within the market,
not within the firm (Maidique & Zirger, 1984; Johne & Snelson, 1988). These arguments
are empirically ascertained: three out of every four innovators value customer
involvement; half the innovators consider it a prerequisite for success. Innovators
involving customers attain significantly improved success rates (Gemunden et al., 1992).
An argument opposing customer involvement is the pitfall of becoming prejudiced
towards customer needs as the innovator involves customers on a more regular basis
(Maidique & Zirger, 1984). Customer involvement may bias innovators towards imitative
products, as customers express their preferences in terms of already familiar products.
Customer involvement diminishes creativity and causes the firm to discard technologydriven ideas. Instead, equilibrium between technology-push and need-pull ideas should
be aimed for (Johne & Snelson, 1988; Rackham, 1988).
15
4 A Quantitative Assessment of the Literature
To examine factors of success and failure of innovations more systematically, we proceed
with a meta-analysis of the literature reviewed above. We address two questions:
•
•
To what extent are the studies on success and failure of innovation consistent in
the importance ascribed to the various success factors?
Is the consistency or inconsistency among these studies attributable to firm,
project, product or market related factors?
As we aim at a factor ranking, not all forty-three studies discussed above can be included.
The various contributions need to fulfill two criteria:
•
•
The studies must have ranked the alleged success factors; and
The studies must have investigated a larger variety of factors. Inclusion of studies
investigating only a limited number of success factors would bias the analysis.
Nine out of the forty-three studies reviewed above meet both criteria. The ranking of
success factors by these nine studies is given in Appendix B. The appendix shows the
ranking by importance, from 1 (= most important) to 21 (= least important). A zero value
indicates that the factor was not considered or found insignificant.
In order to obtain an impression of the (dis)-similarities among the nine studies, we test
the null-hypothesis: “the ranking of factors is consistent”, using a non-parametric analysis
of variance test (Kruskal-Wallis test). In a first round, we included all success factors
exhibited in Appendix B and established significant dissimilarity5. Put differently, the
ranking by importance of all success factors differs significantly between these nine
studies. This relates to Montoya-Weiss and Calantone observing “a wide variation in
results that are surprisingly non-convergent” (1994: 397). However, more detailed
examination shows that this result is accounted for by the lower-ranking factors.
Inclusion of the factors ranking from 1 to 10 only (i.e. excluding all lower- ranking
factors) results in a highly insignificant test statistic6. This implies that consensus exists
among the nine studies with regard to their ten most important success factors.
The Kruskal-Wallis test statistic is 58.8, exceeding the critical value (15.5) at n-1 (8) degrees of freedom and
implying that the null-hypothesis cannot be accepted.
6 The Kruskal-Wallis test statistic is 5, not exceeding the critical value (15.5) at n-1 (8) degrees of freedom and
implying that the null-hypothesis cannot be rejected.
5
16
In order to identify factors that affect the ranking correlations, we divide the factors into
groups, using the categories of the above Figure 1. First the factors are divided into two
groups:
• Firm and project related factors (indicating technological viability); and
• Product and market related factors (indicating commercial viability)
Results show significant ranking dissimilarity within both these groups, independently of
whether only the first ten or all 21 ranks are included. We then subdivide the success
factors into the four main categories detailed in the above Figure 1: (1) firm related; (2)
project related; (3) product related; and (4) market related factors. We establish a
significantly consistent ranking among the nine studies on firm and product related
factors, while the rank correlation on project and market related factors is only weakly
significant (at 10% level of significance).
In interpreting these outcomes, one should bear the above qualitative literature review in
mind. Here we observed that, among the project related factors, the degree to which a
product is “innovative” and “technologically advanced” is quite differently appreciated
among the studies reviewed. Similar ambiguity holds for the merits of top management
support and, within the group of market related factors, fierceness of market competition
and customer involvement. Such dissimilarity weakens the rank correlation within these
groups. Within the groups of firm and product related factors, there is little ambiguity, the
most important dissimilarities being related to the firm's organizational structure and
R&D intensity.
Different terminology complicates comparisons of our findings with the meta-analysis by
Henard and Szymanski (2001). They argue, “Of the 24 predictors of new product
performance investigated, product advantage, market potential, meeting customer needs,
pre-development task proficiencies, and dedicated resources, on average, have the most
significant impact on new product performance” (p. 362). In our view, a factor such as
“market potential” is tautological, since the success of new products (whichever measure
of success is used) will ultimately depend on successful market penetration. With some
caution we conclude that our findings are not too distant from those of Henard and
Szymanski. Our qualitative discussion allows us to be more specific. Henard and
Szymanski argue that “product advantage” and “meeting customer needs” are positive
factors throughout. We also concluded that “product quality and price relative to those of
established products” are positive factors. For “customer involvement”, our results
remain ambiguous. While customer involvement improves success rates, it may also bias
innovation efforts towards incremental innovation. Henard and Szymanski’s emphasis on
17
“pre-development task proficiencies” and “dedicated resources” relates closely to four
factors that in our review were (predominantly) appreciated: a culture susceptible to
innovation, experience with innovation, multidisciplinary R&D teams, and an articulated
innovation strategy.
5 Conclusions
In this paper we review the literature on determinants of successful innovation. We
observe that the relevant studies are consistent in their ranking of their ten most important
success factors, but remain ambiguous on less important success factors. Agreement
exists on the positive impact of:
•
•
•
•
•
•
•
A firm’s culture that is susceptible to innovation and recognizes the collective
nature of innovation efforts;
A firm’s experience with innovation projects (learning-by-doing; learning-byfailing);
The multidisciplinary character of the R&D team; in particular equilibrium
between technological and marketing skills, and the attendance of a product
champion;
An articulated innovation strategy and a management style suited to that;
Compatibility of the project with the firm’s core competences;
Product quality and price relative to those of substitutes;
Adequate timing of market introduction.
Agreement exists on a functional structure being in conflict with the trial-and-error
character of the innovation process. An organic structure is unanimously preferred.
Discussion remains as to whether the relatively autonomous venture team or matrix
structure is preferable. In contrast to the 1950s and 1960s, in the 1980s the matrix
structure is generally preferred since it better responds to the need for integration and
control.
Consensus exists on the relevance of marketing skills as many successful ideas originate
in the market. Some contributors appreciate involving consumers in the innovation
trajectory. Others argue that customer involvement may bias the innovation process
towards imitative innovation, as customer preferences are articulated in terms of already
familiar products. Obviously an innovating firm will need to aim for equilibrium between
technology-push and need-pull innovations.
18
There is no conclusive evidence on top management support, R&D intensity and the
degree to which a product is “innovative” and “technologically advanced”. This
emphasizes the limitations of a one-sided “technology-push” approach. There is also
ambiguity with respect to the fierceness of competition. These ambiguities parallel a
longstanding and not quite conclusive discussion in the Industrial Organization literature
on the relation between market structure and innovation (see the classical review by
Kamien & Schwartz, 1982; or more recently by Scherer, 1992).
Future research may examine success and failure of innovation using statistical databases
that include, besides cross-sections, a time dimension. Distinguishing “easy”
(incremental) from “heavy” innovations (changing strategic directions) may reveal the
merits of factors such as consumer involvement, top management support, R&D
intensity, market structure or innovativeness.
Appendix A: Typology of studies reviewed in this paper
(in chronological order)
Name
Sample
method
Subject
Main results
Freeman et al. (1972
(SAPPHO)
58 projects in scientific instruments and chemicals
(U.K.)
empirical
Identification of factors
discriminating between
success and failure
Discriminating factors:
•
Understanding user
needs
•
R&D efficiency
•
External scientific
communication
•
Marketing
capabilities
•
Managerial capabilities
Mansfield & Wagner
(1975)
20 firms in chemistry and
electronics (U.S.)
Rubinstein et al. (1976)
theoretical
Impact of some organizational aspects on successful innovation
•
Early evaluation of
commercial viability
significantly improves viability
•
Quantitative project
selection is effective
•
Susceptibility for
R&D results is decisive
empirical
Identification of factors of
technological- and economic success
•
Success is determined by about 50
factors simultaneously.
•
There is no single
magical success factor.
103 project in 6 firms
(U.S.)
Cooper (1980)
(Project NewProd)
195 projects (Canada)
empirical
Identification of factors of
success and failure
Three factors determine
half the viability:
•
Unique product features and superiority
•
Market knowledge
and providence
•
Technological and
production synergy
19
Name
Hopkins (1981)
Cooper (1983)
Johne (1984)
Sample
101 firms (U.S.)
method
Subject
theoretical
Identification of factors of
success and failure
103 Canadian firms (New
Prod-sample)
empirical
Importance of technological skills on viability
Main results
Important factors:
•
Timing of market
introduction
•
Market research
•
Technological skills
•
Difficulties concerning the organizational structure,
responsibilities and
planning.
16 innovating U.K. firms
in instrument industry
empirical
Experience as a guideline
for the organizational aspects of innovation activities
•
Firms with little or
no experience with
innovation benefit by
separating initiation
related tasks from
implementation
related tasks.
•
A certain loosening
of control and coordination is called
for
•
•
•
•
Success rate is significantly higher than
is generally assumed
(56%)
The relevance of
success factors
applies for all firms
regardless of their
unique characteristics
Success is independent of financial
R&D inputs
Technological
strengths are less
important than marketing capabilities
Maidique & Zirger (1984)
(Stanford Innovation Project)
158 innovations in US
electronics
empirical
Identification of factors of
success and failure
Success factors:
•
Market knowledge
•
Customer interaction
•
Early market entry
•
Planning of the process
Name
Cooper (1985)
Maidique & Zirger (1985)
Yoon & Lilien (1985)
Link (1987)
Sample
195 innovation projects in
102 US firms
empirical
Design of a model for
project selection
158 innovations in US
electronics
empirical
Identification of factors of
success and failure
135 Austrian marketing
managers
empirical
Identification of factors of
success and failure
Project selection serves as
an instrument to improve
viability. Eight properties
determine viability. These
can be employed to predict the projects viability.
•
112 innovations in 53
French firms
empirical
Comparison of incremental and radical
innovations
•
Both types of innovation differ in
objective, marketing
and timing of market
introduction
method
Subject
Main results
•
All decisive factors
are internal to the
firm and are manageable
Innovators learn
from failed projects.
Success factors:
•
Marketing and technological synergy
•
Quality
•
Customer needs
•
Price strategy
•
Distribution.
Impact of success factors
does not depend on the
firm's innovation capabilities but on the degree to
which a firm depends on
innovations
20
Name
Sample
method
Subject
Main results
Cooper & Kleinschmidt
(1987)
200 innovations in 125 US
firms
empirical
Measuring success and
identification of success
factors
Success eventuates in:
•
Financial returns
•
Windows of opportunities
•
Market dominance
The status of success
factors depends on the
measure of success
employed.
Crawford (1987)
Gobeli & Brown (1987)
Stuart & Abetti (1987)
No sample
13 US high-tech firms
24 new firms (U.S.)
theoretical
Evaluation of studies of
success and failure
empirical
Comparison of different
innovation strategies
empirical
Evaluation of perceived
success factors
Success/failure-studies remain inconclusive.
Further research is needed
on:
•
Innovation strategies
•
Critical phases of the
innovation process
•
Impact of early market introduction
•
Diffusion of innovations
•
Negative causality
between success and
•
Size / growth of
market
•
R&D intensity
•
Flexibility and adaptability of the firm's
organizational structure
•
4 types of strategies
are distinguishable
Portfolio strategy is
most appropriate for
innovation
Name
Sample
Souder (1988)
289 innovation projects
(U.S.)
Wind & Mahajan (1988)
No clearly defined sample
Larson & Gobeli (1988)
540 innovation projects
(U.S.)
John & Snelson (1988)
no sample
method
Subject
empirical
Effects of hampered
R&D/Marketing-interface
on project outcomes
Degree of disharmony
between marketing and
R&D department is correlated to viability
theoretical
Evaluation of development processes
empirical
Organizational setting of
innovation projects
theoretical
Identification of factors of
success and failure
•
Matrix structure is most
appropriate for innovation
activities as far as cost,
planning and technological opportunities
are concerned
The most common factors of success and failure
can be classified according
to McKinsey's 7s-model
Kleinschmidt & Cooper
(1991)
195 innovations from 125
U.S. industrial firms
empirical
Causality between degree
of innovation and success
Main results
•
•
Viability remains
short falling
Guidelines for successful innovation
Viability may be improved by organizational adjustments, higher degrees of innovativeness and encouraging
risk-taking attitudes
Name
Pinto & Slevin (1989)
Howell & Higgins (1990)
Roure & Keeley (1990)
Sample
159 R&D projects (U.S.)
50 firms (U.S.)
method
Subject
empirical
Identification of factors of
success and failure
empirical
Impact of product champion on viability
Main results
Identification of 10 success factors. All vary in
importance during the
development process.
•
36 start-ups in US electronics
empirical
Importance of adequate
reaction to time pressure
and uncertainty
11 measurable qualities of
the firm determine responsiveness to time pressure and uncertainty.
These qualities determine
the new ventures
performance.
•
Product champions
add to susceptibility
for innovation.
Formally organized
structures discourage
product champions
to arise.
Relationship between
success and degree of
innovation is U-shaped.
21
Name
Sample
Gemunden et al. (1992)
848 U.S. manufacturing
companies
Dougherty (1992)
no sample
Rothwell (1992)
no sample
Bessant (1993)
no sample
Method
Subject
empirical
Mobilization of external
resources and knowledge
as a success factor
theoretical
Evaluation of the innovation process
theoretical
Effective management of
technology: Which
management capabilities
are required and how to
develop these?
Main results
Three kinds of technology
oriented external relationships are important:
•
Customers
•
Research institutes
•
Other firms
theoretical
Investigation of differences among the mental
worlds of employees
which keep firms from
synthesizing their expertise
For efficient innovation in
large firms it is necessary
to deal explicitly with the
interpretative barriers to
innovation.
The development process
is evolving from technology-pushed towards a
system integrated network
model
The prime management
task is matching the technology strategy pursued to
the current and developing capabilities within the
firm
Name
Sample
Griffin & Page (1993)
no sample
Hart (1993)
369 firms
Bart (1993)
Undefined
method
Subject
theoretical
Examination of methods
employed to measure
success
empirical
Examination of performance measures used in
different studies
empirical
Importance of formal
control procedures during
the innovation process
Main results
Scientists measure success
at the level of the firm.
Innovators measure at the
level of the product.
Instead of employing
direct measures of
success, one ought to
employ indirect measures.
•
Calantone et al. (1993)
142 US firms listed in the
Fortune 500
empirical
Impact of organizational
structure, marketing and
technological skills on viability
Organizational structure
determines marketing
skills and hence viability
•
Name
Page (1993)
Schmidt (1995)
Sample
189 US firms
method
Subject
empirical
Evaluation of projects
Main results
•
two samples: 177 Canadian
manufacturing firms
obtained from Project
NewProd and 142
Fortune-500 firms
obtained from Spirit data
set
empirical
Effect of proficiency of
innovation activities on
level of success
•
Technological factors
are more important
than marketing factors
•
Product superiority is
the most important
success factor
•
•
Half the innovators
do not employ a strategy towards innovation
Success rates have
not improved since
1980
There remain opportunities for improvement.
Formal control procedures ought to be
minimized, but a minimum level of control remains necessary
Optimal level of formal control varies by
project
Kleinschmidt & Cooper
(1995)
103 innovation projects in
21 firms in chemicals
(U.S., U.K., Canada,
Germany)
Rochford & Rudelius
(1997)
79 US firms in medical
instruments
empirical
Relative importance of
perceived success factors
empirical
Relevance of completing
development phases
•
Attentively completing all
13 phases of the development process adds to
viability
•
•
Perceived impact of
factors differ from
reality
Development trajectory must be completed attentively
Marketing skills are
more important than
technological skills
22
Name
Zirger (1997)
Roy & Riedel (1997)
Lester (1998)
Sample
147 innovation projects in
US electronics
no sample
Method
Subject
empirical
Impact of experience with
innovation on viability
Main results
Technological and market
experience adds to
viability
220 innovation projects in
small and medium- sized
UK firms
empirical
Impact of degree of innovation and design on
viability
•
Degree of innovation does not determine viability
•
Successful innovations are mostly designed with a multidimensional focus
on quality, product
features and design
Name
Rackham (1998)
Sample
3 products
method
Subject
Theoretical
Identifying factors of
failure of viable innovations
Viable innovations may fail
due to the sales department, which is productoriented rather than
customer-oriented
Main results
Asplund & Sandin
(1999)
Swedish beer market
1989-1995
empirical
Survival rate of new
products
•
•
Market uncertainty
is a dominant factor
Survival rates appear to depend on
volatile consumer
preferences
Ekvall & Ryhammar
(1998)
150 Swedish university
managers
theoretical
Identification of success
factors
theoretical
Impact of leadership on
organizational outcomes
Five decisive factors:
•
Top management
commitment
•
Culture susceptible
to innovation
•
Availability of concepts and ideas
•
Organizational structure: venture teams
•
Project management
aimed at reduction
of uncertainty
By affecting the social
climate, the style of leadership affects
organizational performance in terms of
productivity
Brouwer et al. (1999)
128 new product announcements published in trade
journals
empirical
Are urban agglomerations
better breeding places for
product innovation?
Influential factors:
•
Continuity of R&D
effort
•
R&D intensity
•
Demand-pull
•
Firm size
•
Regional spillovers
23
Cooper 1980
Maidique & Zirger
1985
Voss 1985
Cooper &
Kleinschmidt 1987
Link 1987
Stuart & Abetti 1987
Pinto & Slevin 1989
Calantone &
Benedetto 1993
Kleinschmidt &
Cooper 1995
Appendix B:
Ranking of success factors by importance (0= not considered/insignificant; 1=most important)
Firm's culture
0
0
2
0
0
0
0
0
0
Strategy towards innovation
0
3
0
0
0
0
0
0
0
0
0
2
0
0
0
0
8
0
0
2
0
0
4
0
1
0
12
0
0
0
7
0
0
0
2
0
R&D team
R&D team (in general terms) 0
interdisciplinarity
0
attendance product champion 0
2
0
3
0
0
1
0
0
0
0
0
8
0
0
0
2
0
0
0
0
0
0
13
6
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
4
0
0
0
0
0
10
0
0
0
2
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
1
0
0
10
0
1
2
9
0
0
0
9
Experience
experience (in general terms)
experience/skills with
technology
experience/skills with
marketing
Organization
organizational structure
'organicity'
autonomy R&D team
interdepartmental communication
intradepartmental communication
embeddedness R&D team in
firm
R&D expenses
R&D intensity
availability financial resources
Innovation management
innovation management (in
general terms)
completing development
phases
planning/analysis
project definition
project selection
explicit responsibilities
process evaluation
0
0
0
0
0
0
0
1
0
0
9
0
0
0
0
1
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
0
0
0
0
0
0
0
0
6
6
0
0
5
0
0
0
0
0
3
8
7
10
0
Complementarity
complementarity
marketing synergy
technological synergy
distribution synergy
production synergy
synergy core capabilities
5
5
1
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
2
12
4
0
0
0
0
1
2
0
2
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
14
15
19
17
10
24
Maidique & Zirger
1985
Voss 1985
Cooper &
Kleinschmidt 1987
Link 1987
Stuart & Abetti 1987
Pinto & Slevin 1989
Calantone &
Benedetto 1993
Kleinschmidt &
Cooper 1995
Ranking of success factors by importance (continued)
Cooper 1980
Appendix II:
Top management support
0
1
0
0
0
0
5
0
0
Quality
0
0
0
3
3
0
0
3
1
0
0
0
1
0
0
0
0
0
11
0
0
5
0
0
0
0
0
0
0
0
0
0
0
0
2
20
0
3
3
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
6
2
0
0
0
0
0
0
0
Price
price
price relative to quality
limited risk of purchase
Innovativeness
innovativeness
unique / newness
Technological
technologically advanced /
complexity
Product advantages / product
superiority
meeting customer needs
ease of use
lower total-cost-of-use
3
0
0
5
4
0
0
0
4
4
0
0
1
0
0
0
0
0
9
0
11
0
10
4
0
0
0
0
0
0
0
0
0
5
0
0
Concentration
Timing market introduction
0
0
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
Market competition
market competitiveness
market size
market growth
4
7
7
0
0
0
0
0
0
0
0
0
0
11
11
0
1
1
0
0
0
0
0
0
18
0
21
2
8
0
1
1
1
0
0
0
0
0
10
0
10
6
0
0
0
3
0
0
5
0
0
0
0
16
2
0
0
0
1
0
0
0
0
0
0
0
0
1
0
5
7
0
0
0
0
0
0
0
0
0
1
0
0
5
0
0
0
11
0
8
Marketing
marketing (in general terms)
advertisement / promotion
adequacy of sales force /
distribution
forecasting turnover
market research
customer involvement
market definition
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