-
Paper to be presented at the DRUID 2011
on
INNOVATION, STRATEGY, and STRUCTURE - Organizations,
Institutions, Systems and Regions
atCopenhagen Business School, Denmark, June 15-17, 2011
Does organizational creativity really lead to innovation?
Mette Praest KnudsenUniversity of Southern Denmark
Marketing & Management, [email protected]
zge Cokpekin
[email protected]
AbstractCurrent research claims that the presence of
organizational motivation, resources and a creative climate
inorganizations leads to innovation. Just as strong as the
relationship is carved out in the literature, just as weak is
theempirical evidence reported in the literature. This paper
utilizes a survey of 147 firms from a particular region ofDenmark
to analyze whether organizational creativity does lead to
innovation in small firms. We follow the most oftenreferred
creativity and innovation model and the pre-existing creative
climate assessment tools to assess the stimulantsof product and
process innovation. The logistic regression analyses demonstrate
that organizational motivation,resources and idea time are
positively associated with product innovation. However, this result
did not hold for processinnovation, where strategy and risk are
important. We also found that enhanced freedom and autonomy for
employeesaffect probability of product innovation adversely. We
conclude that indeed organizational motivation, resources andidea
time spawn product innovation, whereas managers are recommended to
exercise freedom cautiously. The paperraises three future research
directions to further analyze the relationship between
organizational creativity andinnovation. Jelcodes:O32,O31
-
[1]
Does organizing creativity really lead to innovation?
zge Cokpekin1
Mette Prst Knudsen
Integrative Innovation Management Unit, DRUID
Dept. of Marketing & Management
University of Southern Denmark
Keywords: creative climate, organizational creativity, product
innovation, process innovation
Abstract
Current research claims that the presence of organizational
motivation, resources and a creative climate in
organizations leads to innovation. Just as strong as the
relationship is carved out in the literature, just as
weak is the empirical evidence reported in the literature. This
paper utilizes a survey of 147 firms from a
particular region of Denmark to analyze whether organizational
creativity does lead to innovation in small
firms. We follow the most often referred creativity and
innovation model and the pre-existing creative
climate assessment tools to assess the stimulants of product and
process innovation. The logistic
regression analyses demonstrated that organizational motivation,
resources and idea time are positively
associated with product innovation. However, this result did not
hold for process innovation. We also
found that enhanced freedom and autonomy for employees affects
the probability of product innovation
adversely. We conclude that organizational motivation, resources
and idea time spawn product innovation,
whereas managers are recommended to exercise freedom cautiously.
The paper raises three future
research directions to further analyze the relationship between
organizational creativity and innovation.
1 Corresponding author: [email protected].
-
[2]
1. Introduction and motivation
Creativity in an organizational context is the conceptualization
and development of novel ideas, products,
processes or procedures by individuals or a group of individuals
working together (Amabile, 1988, Shalley,
1991, Woodman, Sawyer and Griffin, 1993). Creativity ignites
innovation, because innovation is
characterized as the successful application of what creativity
produces in organizations, (Amabile, Conti,
Coon, Lazenby and Herron, 1996, Oldham and Cumming, 1996). In
short, all innovation begins with creative
ideas (Amabile et al, 1996: 1154).
Creativity and innovation are perceived to be so closely linked
that these terms are often used
interchangeably (Ford, 1996). Indisputable, one is guided to the
presumption that creativity leads to
innovation, and just as strongly, we expect to find substantial
empirical evidence confirming this
relationship. Surprisingly, only a few empirical contributions
are subsequently identified in a thorough
literature review. From a qualitative viewpoint, Mohamed and
Rickards (1996) study aspects of the key
relationship and Soo, Devinney, Midgley and Deering (2002)
briefly discuss the difficulties of turning
creativity into innovative products. Bharadwaj and Menon (2000)
provide a quantitative analysis on
creativity mechanisms in the firm and Sohn and Jung (2010)
discuss but only find an indirect relationship
between creativity and innovative performance. Somewhat
thought-provoking, we realize along with
Puccio and Cabra (2010, 147-148) that relevant empirical
research remains surprisingly limited.
This paper aims to identify the creativity factors that
stimulate innovation by analyzing the following
research question: Does the organizing of creativity increase
the likelihood of product and process
innovation?
Compared to previous research, this paper extends the work of
Bharadwaj and Menon (2000), by focusing
not just on organizational structuring mechanisms, but also by
adding organizational motivation, specific
resources and the characteristics of a creativity stimulating
climate. Additionally, we include the
availability of time for creativity in our analysis. The
elements tested empirically in this paper therefore
cover a more complete range of factors for organizational
creativity; organizational motivation, resources,
dedicated time for creativity and creative climate factors.
Founded on the coherent theoretical arguments, this paper
delivers some intriguing empirical results.
Some aspects of organizational creativity lead to product and/or
process innovation, but simultaneously
there are hampering aspects that management must consider
carefully. We found that encouraging
employees toward appropriate risk taking, following a proactive
strategy and allocating sufficient
resources including time, foster product innovation but do not
affect process innovation. Allowing freedom
to employees, however, hampers product innovation. To obtain
these results, we utilize survey data
collected in 2010 on small Danish firms. The first contribution
of this paper to the existing literature is the
deepened understanding of the main effects of organizational
creativity on innovation contributing thereby
to the broader innovation management research.
The second contribution of this paper is that this is the first
empirical study to analyze a coherent set of
factors of organizational creativity leading to innovation. In
addition to the findings, the paper raises future
research questions to explore the relationship between
organizational creativity and innovation further.
-
[3]
The paper proceeds by presenting the main theoretical arguments
for organizational creativity and
innovation leading to the formulation of main hypotheses
(section 2). The details of the study are presented
along with the method applied for the test of the hypotheses
(section 3). The results section presents the
analytical results based on logistic regression models (section
4). Finally, the results are discussed (section
5), and the paper concludes on the findings and discusses the
recommendations for managers of innovation
processes and future research directions (section 6).
2. Linking organizational creativity and innovation
Organizational creativity
The two main organizational creativity models in the literature
are Amabile`s (1988) componential model
and Woodman, Sawyer and Griffin`s (1993) interactionist model
(Shalley and Zhou, 2009: 12). The
componential model defines the requirements for creativity and
innovation and conceptualizes the
relationship between these. In this model, creativity is
associated with individuals while innovation is
described as an organizational phenomenon.
According to Amabile (1997), an organization is motivated to
innovate if it places explicit value on
innovation, is oriented towards risk rather than sticking to
status-quo, takes a proactive approach to
change rather than following a defensive strategy, expresses
pride in employees capabilities and efforts,
and finally provides supervisory and work team encouragement on
employees. Resources needed for
innovation are defined as the financial, material and
informational resources made available to employees,
training provided to improve creative thinking skills, and
sufficient time allocated to think creatively and
explore new ways of doing tasks (Amabile, 1997). Appropriate
managerial practices conducive to
innovation are organization of work teams according to the
skills of employees, provision of regular and
clear feedback, provision of project autonomy and goal setting
that is tied to the overall mission, but
flexible at procedural progress (Amabile, 1988, 1997).
Motivation, resources and skills among employees stimulate
creativity and, in turn, creativity feeds
innovation if the firm is motivated to innovate, provides
resources for doing innovation, and ensures
appropriate managerial practices to support the smooth flow of
the innovation process (Amabile, 1997).
The interactionist model (Woodman, Sawyer and Griffin, 1993)
assumes that creativity is a phenomenon
that is affected by situational and behavioral factors in
particular emphasizing the interactions among
individuals, groups and organizations. The model explicitly
recognizes intra-organizational influences that
either stimulate (enhancers) or inhibit (constrainers)
organizational creativity. As Woodman and his
colleagues (1993) draw attention to the importance of these
enhancers and constraints, several other
researchers such as Amabile and Gryskiewicz (1989), Amabile et
al (1996), Oldham and Cummings, (1996),
Ekvall et al (1983) and Ekvall (1997), Shalley, Gilson and Blum
(2000) also emphasize the importance of
work environment characteristics for stimulation of
creativity.
Although creativity per se cannot be directly managed (Amabile,
1995: 78, Woodman, 1995: 60), the
work environment characteristics can be. Hence, innovation
managers can motivate the employees and the
organization to activate the creative potential (Taggar, 2002),
and subsequently to foster innovation
(Amabile, 1988, 1997, Heinze, Shapira, Rogers, Senker, 2009,
Oldham and Cummings, 1996, Shalley, Gilson
and Blum, 2000, Woodman, Sawyer and Griffin, 1993).
-
[4]
Empirically, the literature supports the adoption of the KEYS
construct (Amabile and Gryskiewics, 1989,
Amabile et al, 1996) and the Creative Climate Questionnaire
(CCQ) (Ekvall, 1996). These are developed to
quantify the degree of creativity stimulants in the firm`s work
environment. KEYS measures the level of
encouragement of creativity, freedom, resources, pressures and
organizational impediments in a firm
(Amabile et al, 1996). CCQ covers challenge, motivation,
freedom, idea-support, trust and openness,
dynamism, humor/playfulness, debate, conflict, risk-taking and
idea-time measures for assessing the level
of support for creativity (Ekvall, 1996).
Following the structure of these tools, it can be inferred that
an organizational climate conducive to
creativity should be characterized as challenging enough to keep
the motivation of employees high to
accomplish a task, offering a certain degree of freedom to
choose ways of accomplishing the task, encouraging
a healthy level of risk-taking, supporting generation of ideas,
allowing some free time to try new things, and
explore unused ways to accomplish task rather than overloading
employees with pre-defined work.
Determining the optimum amount of time available to balance the
tradeoff between time pressure and
unconstrained space for innovative activities is important
(Amabile, 1988, Hsu and Fan, 2010). A certain
amount of urgency stimulates creative thinking, but being
overloaded with work within an unrealistic time
frame may completely hamper any innovative activity. A simple
mechanism may remedy this tradeoff by
allocating some free time dedicated to creativity and innovation
activities. This managerial initiative sends
signal to employees by securing time and space to realize the
best potential in them without sacrificing
direction and planning in the process. Allocation of dedicated
time may therefore release the tension of
overloading, and encourage employees to think creatively and
work on innovations. The above discussion
leads us to formulate an overarching hypothesis on the link
between creativity and innovation:
A firm is more likely to innovate when the managers unleash the
creative potential by motivating the
employees to innovate, allocating resources for this purpose,
enabling appropriate management
practices to establish the organizational climate conducive to
creativity, and allocating specific time for
idea development and creativity.
Conceptualizing innovation
The above hypothesis is not directly testable, although measures
are available from the literature. Hence, a conceptualization of
innovation is called for. Generally, the concept of innovation as
the concept of creativity encapsulates too much to be directly
measurable.
A review reveals that it is relevant to distinguish product from
process and organizational innovation
(Damanpour and Gopalakrishnan, 2001) focusing on the outcome of
the innovative activity. A product is a
good or service provided to customers, while a process is the
mode of production and delivery of the
good or service (Barras, 1986). Product innovation can
accordingly be defined as a new technology or
combination of technologies introduced commercially to meet a
user or market need (Utterback and
Abernathy, 1975:642). Process innovation is defined as the new
elements introduced into the firm`s
production or service operations to produce product or render a
service (Damanpour and Gopalakrishnan,
2001: 48). These two types of innovations may require similar,
but still different organizational skills since
product innovations are market-driven, while process innovations
concern efficiency within the firm (Ettlie
and Reza, 1992).
-
[5]
A number of studies reveal that product and process innovations2
are closely related and applicable
simultaneously (Damanpour and Gopalakrishnan, 2001). For
example, Pisano and Wheelwright (1995)
argue that simultaneous development of products and process is
necessary since the congruent adoption of
both types of innovation smoothes the launch of new products and
rapid penetration of the market.
Following the literature, therefore, it is inferred that firms
are not expected to do either product or process
innovation, rather they do both types of innovations, regardless
of the sequence of innovation.
Consequently, we assume that any study of the link between
creativity and innovation should involve both
types of innovations, rather than one over the other. Our
hypothesis developed from the literature merely
specifies that creativity is important for innovation, but not
whether there are distinct differences between
e.g. product and process innovation.
Hypotheses
Product innovations require continuous intelligence about
customers, markets and other uncertainty
factors. Accordingly, it is crucial that the firm allocates
sufficient informational, material and monetary
resources to stay tuned with the external environment. An
increase in explicitly placing high value on
innovation, expressing pride and high confidence in employees`
achievements, taking an attitude towards
risk taking and proactive strategy rather than retaining the
ongoing activities, and establishing creativity
conducive work environment leads to higher product
innovation.
Hypothesis 1: All creativity components; organizational
motivation, allocation of free-time and
resources, and establishment of a stimulating work climate are
expected to be positively and
significantly related to product innovation.
As mentioned above the lack of distinction of different
innovation types in the creativity literature leads us
to the formulation of mirror hypotheses, that:
Hypothesis 2: All creativity components; organizational
motivation, allocation of free-time and
resources, and establishment of a stimulating work climate are
expected to be positively and
significantly related to process innovation.
3. Data and variables
Population and the survey
The paper is based on a survey carried out in February and March
2010. Beforehand, five qualitative
interviews were conducted to identify the most important topics
of creativity and innovation to include in
the survey. The interviewees were CEOs or innovation managers in
small and medium-sized companies
(from 12-300 employees) from various industries. The selected
firms were considered to be at the front
end of innovation in the particular region, and therefore would
more naturally speak of the topics of
2 How product and process innovations are related to each other
and whether product innovation leads process innovation or vice
versa have been widely discussed in the innovation literature. It
is not of further relevance for this paper, how the innovative
forms are related and evolve, but for key references please consult
Abernathy and Utterback (1978), Barras (1986), and Anderson and
Tushman (1991).
-
[6]
interest to the survey3. The interviews lasted between 1 and 1
hours and were carried out in October
2009. The topics included in the survey4 were selected as a
combination of existing questions and items
from the literature and insights from the interviews. The
questions to track innovation activities were
based on the CIS format. The questionnaire consists of 20
creativity-related and 21 innovation-related
questions that are used in the subsequent test of the
hypotheses. The final survey was pre-tested on a
company, which first filled out the survey, and then was
interviewed about the main subjects of concern.
This interview did not highlight any particular problems related
to content or formulations.
The population consisted of firms with more than 5 employees in
a particular geographical area (Funen) in
Denmark. The project is concerned with service and manufacturing
firms delimiting the population to 1250
companies. A further cleansing of the firms
(double-registrations and branches) resulted in 897 eligible
companies. These firms received an introductory letter from the
mayor and an invitation to participate. An
email linking to the electronic survey was subsequently sent,
asking for the innovation manager or CEO to
respond. Two email reminders were issued resulting in 147
responses at a response rate of 16, 4%.
Approximately 64, 6% of the respondents were CEO, administrative
director, vice or senior director,
research manager and leader, and the rest was marketing or group
managers with titles such as sales
director, marketing director, production chief. The average
tenure of the respondents was 18.4 years.
The firms that responded to the survey are primarily smaller
firms with less than 10 employees, whereas
only two companies have more than 250 employees. The results are
therefore relevant predominantly in a
SME context. The distribution of responses fits the original
distribution of companies in the population.
Number Percentage Valid
percentage
Less than 10 employees 79 53,7 58,5
10-49 employees 37 25,2 27,4
50-249 employees 17 11,6 12,6
More than 250 employees 2 1,4 1,5
Total 135 91,8 100,0
Missing System 12 8,2
Total 147 100,0
Table 1: Distribution of respondents according to the number of
employees
In the empirical sections, we have used the following summarized
form:
Manufacturing: Industry, rock extraction and utilities. 26 firms
comprising 17.7 % of the sample.
Services: Trade, transport, information & communication, and
business services. 93 firms
comprising 63.3% of the sample.
Others: Agriculture, forestry and fishing, building and
construction, financing and insurance and
culture. 28 firms comprising 19% of the sample.
3 The semi-structured interviews dealt with the topics of the
financial crisis and the firms reactions to the crisis, strategies
for innovation, creative processes and creative employees, and
network relationships for innovation. 4 The survey contains
questions relating to the following topics, creativity and
innovation in general, innovative activity, the importance of
inter-organizational relationships for innovation, creative
employees, mechanisms to stimulate creativity and the creative
environment.
-
[7]
The data collection took place in a period of the financial
crisis and commenced about 1 after the crisis
took off in Denmark. The crisis was strongest in the year 2009;
however firms still suffered in 2010.
Approximately 53.7% of the firms have reduced the number of
employees in 2009. On the positive side,
almost a fourth of the companies have increased the number of
employees. The same figures for the
previous last three years are less negative. It is therefore
clear, that the survey has been answered in a
period of stress for the companies, where the focus was on
rationalizations and employee reductions;
however we have been unable to detect any differences within the
sample.
Data issues
Collecting data for both dependent and independent variables
from the same respondent at the same time
may create common method bias. Among the different sources of
bias categorized by Podsakoff,
MacKenzie, Lee and Podsakoff (2003), we identify three possible
sources of bias:
1) a social desirability bias to present ones firm as paying
closer attention to creativity than it actually
does
2) a tendency to keep responses consistent for the creative
climate measuring items
3) a tendency to choose answers around neutral rather than
choosing extreme responses such as
always/perfectly applicable and never/not applicable at all.
To assess the severity of possible biases, we first performed
Herman`s single-factor test producing four
unrotated factors with approximately 50% of the total variance
explained. The test did not suggest the
presence of common method bias, but we did not rely on this
result due to problems associated with this
diagnostic method (Podsakoff et al, 2003). As a next step, the
descriptive statistics were analyzed. Most of
the variables of interest distribute skewed negatively meaning
that most responses fall in the right side of
the distribution. Taken together with the associated kurtosis
information, the skewness supports that
social desirability to present one`s firm positively may have
slightly affected the responses, which appear
higher than the actual case. However, the relatively low
negative skewness in many items clarifies some of
this doubt, thus reducing the adverse effect of the social
desirability bias. To detect whether responses
tend to accumulate around the mean, the kurtosis information is
checked and reported. Many items, are
distributed with having flatter tops (kurtosis~= or
-
[8]
Variables
Dependent variables
The allocation of time for creativity and innovation is used as
the dependent variable of the first model
(yes/no response category). Has your firm introduced
product/processes which are new to the firm since
2007? are the questions asked to capture the innovation related
dependent variables (yes/no response
categories).
Manufacturing Services Others Total
Allocation of Time Number of firms 9 34 6 49
Yes % Within sector 39,1% 44,1% 25%
% of total 7,3% 27,4% 4,48% 39,5%
Total (Yes + No) Number of firms 23 77 24 124
% of total 18,5% 62% 19,4% 100%
Product
Innovation Number of firms 17 46 5 68
"Yes" % Within sector 65,4% 49,5% 17,9%
% of total 11,6% 31,3% 3,4% 46,3%
Total (Yes+No) Number of firms 26 93 28 147
% of total 17,7% 63,3% 19% 100%
Process
Innovation Number of firms 14 48 5 67
"Yes" % Within sector 53,8% 51,6% 17,9%
% of total 9,5% 32,7% 3,4% 45,6%
Total (Yes+No) Number of firms 26 93 28 147
% of total 17,7% 63,3% 19% 100%
Table 2: Allocation of time, introduction of new products since
2007 and implementation of new processes since 2007
distributed on sectors.
Independent variables
The independent variables are selected from the componential
model of Amabile (1988) and from the CCQ
of Ekvall (1997) following Moultrie and Young (2009). In the
survey, the motivation to innovate and the
resources for innovation components from the componential model
are adopted along with challenge,
freedom, idea support, proactiveness and idea time elements of
the CCQ tool. The scale ranges from 1 to 5 for
all variables, 1 being the at the lowest level or not applicable
and 5 being the at the highest level or
totally applicable.
An exploratory factor analysis (EFA) indicates that the
organizational motivation component should be
divided into two sub-components namely strategy and risk and
employee appraisal, whereas the
remaining factors act according to the underlying model. Factor
extraction was based on the principal
component factor method with varimax rotation. In addition to
the EFA, the factors were checked using
confirmatory factor analysis (the graphical interface in AMOS).
The results of the CFA for the organizational
motivation and resources variables are (N
-
[9]
0.420. These results indicate that less than 50% of the variance
in the items is explained by the latent
structure. Each of the standardized regression weights are
highly significant (
-
[10]
Idea Support
This variable measures how supportive the firm is towards
creative behavior; emphasizing how
constructive the climate is to support generation and
development of new ideas and how much support the
firm receives from its employees for the initiatives taken
(Ekvall, 1996).
Proactiveness
This variable measures how proactive the firm is towards risks
and opportunities. How experimental and
tolerant towards ambiguity the firm is, besides how fast
decisions are made and initiatives are taken not to
miss new opportunities. (Ekvall, 1996)
Idea Time
Idea time refers to the extent that employees use time provided
as resource to work on new ideas. The
variable captures the usage of time rather than the availability
(availability is the dependent variable of the
first model). It also includes how much employees have time to
test spontaneous opportunities arising.
Mean Std. n No. of Skewness Kurtosis Cronbach`s
Dev.
items Items of items alpha
Strategy and 3,38 0,95 121 3 -0,14 1,69 0,633
Risk
-0,44 2,49
-0,41 2,54
Employee 4,17 0,78 118 3 -1,44 5,04 0,713
Appraisal
-0,78 3,23
-1,19 3,66
Resources 3,53 0,72 118 5 -0,15 2,28 0,602
-0,45 2,52
-0,29 2,10
-1,18 3,70
-0,01 1,92
Challange 4,14 0,77 116 3 -0,67 3,12 0,859
-0,91 2,77
-0,48 1,95
Freedom 4,20 0,70 121 3 -0,88 3,23 0,819
-1,06 3,63
-0,79 2,91
Idea Support 4,24 0,70 118 3 -0,74 2,73 0,891
-0,83 3,09
-0,43 2,05
Proactivenes 3,54 0,84 117 3 -0,57 3,05 0,707
-0,20 2,62
-0,74 2,87
Idea Time 3,05 1,14 116 2 -0,09 1,75 0,693
0,07 2,11
Table 3: Descriptive statistics for independent variables
-
[11]
For the model building it is required that the independent
variables are free of multicollinarity or at least
only characterized by a low correlation (below 0.3). Since the
elements of the creative environment are
constructed theoretically to reflect aspects of the same overall
construct and the sample size is relatively
small, correlations among independent variables are in some
cases high and hence, by definition,
unsuitable for joint specification in a regression model (see
table 4 for the correlations).
Hair et al. (2006:232-233) advises that one possible correction
for multicollinarity is to exclude the
variables with highest correlation from the model building, and
subsequently use the single correlations for
evaluation of the individual relationships between the
independent (and excluded) variable with the
dependent variables. An alternative remedy would be to collapse
all correlated items into one factor
constituting creative environment, but this was rejected because
this procedure would suppress
important information.
Within the creative climate construct, a thorough examination
needs to determine, which variables to
maintain for model building. Amabile (1988: 147) provides a
ranking of variables promoting creativity
according to their percentage of being mentioned by scientists
during her field research. Freedom, idea
support and challenge were mentioned by 74%, 47% and 22% of
scientists respectively. As freedom is the
most frequently mentioned characteristics of creative climate,
this variable is kept at the expense of idea
support and challenge. Additionally, proactiveness is excluded,
because of a high correlation with idea time
and freedom. The inter-item correlations among, strategy and
risk, employee appraisal and resources
for creativity are also correlated, but without the same
systematic as previously and we therefore
maintain these. Hence, for the regression model, the following
independent variables are included: idea
time, freedom, resources for creativity, strategy and risk and
employee appraisal.
Controls
Several control variables were initially proposed for the
analysis. Two variables capturing changes in the
number of employees, a service dummy to reflect differences in
the industry characteristics and other three
dummies controlling the innovation-related characteristics were
coded. None of the variables were
statistically significant in the regression analyses, which lead
us to conclude that the sample is
homogeneous in terms of these controls. Therefore, no controls
were included in the final models that are
presented below.
-
[12]
Prod In Proc In AllocT STR_R EMP_A RESOU CHAL FREE IDEA PROA
IDEA_T
Product Innovation 1.00
Process Innovation 0.3559 1.00
(0.000)
Allocation of Time 0.2688 0.3333 1.00
(0.000) (0.000)
STRATEGY& RISK 0.3227 0.4157 0.4056 1.00
(0.000) (0.000) (0.000)
EMPLOYEE APPRAISAL 0.0689 0.10965 0.2176 0.3926 1.00
(0.4725) (0.349) (0.019) (0.000)
RESOURCES 0.2791 0.2704 0.3731 0.4662 0.4311 1.00
(0.003) (0.008) (0.000) (0.000) (0.000)
CHALLANGE -0.0361 0.1235 0.1578 0.1838 0.4028 0.3513 1.00
(0.707) (0.230) (0.095) (0.052) (0.000) (0.000)
FREEDOM -0.0642 0.1498 0.0178 0.1692 0.3350 0.3635 0.6142
1.00
(0.497) (0.140) (0.849) (0.069) (0.000) (0.000) (0.000)
IDEASUPPORT -0.1049 0.0774 0.1361 0.1366 0.3859 0.3302 0.6047
0.6467 1.00
(0.273) (0.453) (0.148) (0.149) (0.000) (0.000) (0.000)
(0.000)
PROACTIVENESS 0.1461 -0.0102 0.1055 0.2320 0.3960 0.2977 0.4109
0.4154 0.3748 1.00
(0.126) (0.921) (0.263) (0.013) (0.000) (0.001) (0.000) (0.000)
(0.000)
IDEATIME 0.2832 0.198 0.5038 0.3469 0.2526 0.3399 0.3252 0.2541
0.2637 0.4787 1.00
(0.002) (0.055) (0.000) (0.000) (0.007) (0.000) (0.000) (0.006)
(0.004) (0.000)
Table 4: Correlation and its significance (in parenthesis) for
the performance measures as dependent variables and independent
variables
-
[13]
4. Final model and results
The first model analyzes the relationship between allocation of
specific working time to idea development
and the independent variables. In all three models, the
dependent variables are binary (yes/no) requiring
logistic regression analysis. The first model tests the
overarching hypothesis that firms, which invest in
organizational creativity and innovation stimulating factors,
allocate specific working time for creativity
and innovation activities. This model is highly significant and
all creativity components, except the
employee appraisal, are significant, at least at the 10% level.
This leads us to model 2 and 3, whose
respective Hosmer and Lemeshow goodness of fit test provides
insignificant results (p=0.4722, p=0.3864,
and for the first model p=0.3742) indicating that the model fits
are satisfactory.
The second model uses introduction of new products as the
dependent variable and the third model uses
implementation of new process innovations as the dependent
variable. Models test the effects of
independent variables on the probability of doing product and
process innovation respectively (see table
5).
LOGIT regression results on allocation of time, product and
process innovativeness of firms
Model 1-Allocation of
Time
Model 2-Product
Innovation
Model 3- Process
Innovation
Independent
Variables Coefficient (z-value) Coefficient (z value)
Coefficient (z-value)
Strategy and Risk 0.684* (1.85) 0.684*** (2.67) 1.210***
(3.62)
Employee Appraisal -0.364 (-0.83) -0.037(-0.10) -0.627*
(-1.75)
Resources 1.161** (2.38) 0.687* (1.69) 0.413 (0.91)
Freedom -0.831** (-2.32) -0.677** (-2.14) 0.443 (1.16)
Idea Time 1.073*** (3.87) 0.456** (2.00) 0.163 (0.64)
Intercept -5.282 (-2.68) -2.879 (-1.70) -4.768 (-2.59)
Number of
observations 105 100 88
F-test 0.0001 0.0005 0.0010
McFadden`s Pseudo R2 0.3106 0.1796 0.2123
*** p
-
[14]
The results of the second model show that the strategy and risk,
resources and ideatime variables are
positively but the freedom variable is negatively affecting the
probability of introducing a new or improved
product on the market. Contrary to the product innovation model,
the organizational motivation factors are
the only variables explaining process innovation in the third
model, where strategy and risk is positive and
employee appraisal is negative. This implies that strategy and
risk are always important for innovation,
whereas the other components differences can be derived from the
innovation type.
Some of the independent variables are excluded from the logistic
regression model (table 5) as a result of
multicollinarity. The correlations between the excluded
components and the dependent variables are
investigated. However, as the correlation table shows, none of
the dropped variables is significantly related
to the innovation types (table 6).
Allocation of
Time Product Innovation
Process
Innovation
Challenge 0.158 -0.036 0.124
Idea Support 0.136 -0.105 0.077
Proactiveness 0.106 0.146 -0.010
*** p< 0.001, * * p< 0.01 level, *p
-
[15]
Figure 1: Interpretation of the coefficients and their effect on
product innovation
The average firm that has responded to all independent variables
at the sample means corresponds to a
probability of achieving product innovation at 56%. Since the
coefficients of resources, strategy and risk
and idea time variables are positive, the probability of doing
product innovation increases when the
responses increase from average to 4 or 5 on the scale. As the
freedom coefficient is negative, the
probability of doing innovation decreases when the responses of
a given firm increase. Therefore, the line
representing this relationship has negative slope.
5. Discussion
This paper draws two important conclusions; first we confirm
that firms investing in organizing creativity
have a higher probability of allocating special working time for
innovation, and second the organizational
creativity stimulating factors are correlated with product
innovation rather than process innovation. When
these two findings are evaluated together, the study reveals
that the overarching hypothesis holds true for
product innovation. The firms that motivate employees, provide
them with resources, establish
organizational creativity stimulating work climate, and
facilitate the use of time on innovative ideas are
more likely to deliver new products to the market.
The logistic regression results provide expected positive signs
and significance for the strategy and risk,
resources and idea time variables for product innovation,
confirming earlier studies (e.g. Amabile, 1988,
Kanter, 1988). Being oriented towards risk and opportunities as
well as linking these with an offensive
strategy corresponds with employees` innovative activities.
Additionally, explicitly placing value on
creativity and innovation supports the communication among
internal and external stakeholders and
conveys the message that the firm is dedicated to innovation.
This type of organizational encouragement,
when felt by the employees, appears to be linking strongest with
product innovation. Contrary to
expectations, emotional support such as being proud of employees
or being enthusiastic towards employee
achievements do not affect the probability of doing product
innovation.
.2.4
.6.8
1
Pro
babili
ty o
f doin
g p
roduct
innova
tion a
ccord
ing to the resp
onse
s
1 2 3 4 5Response scale from 1 to 5 for questions
Resources responses Freedom responses
Strategy and Risk responses Idea time responses
-
[16]
The importance of financial, material, informational resources,
expertise and time for doing product
innovation are also confirmed as discussed theoretically in the
literature.
The increasing psychological safety needs is mostly held
responsible for the insignificant outcome of the
dropped variables. Recent years with relatively difficult times
accompanied with actual downsizing or the
fear of downsizing may have nullified the risk taking incentives
of employees, the perceived idea support
and the need for challenge.
Freedom
The unexpected sign of the freedom variable is the most
controversial finding deserving re-evaluation of
previous studies, which discuss freedom or autonomy as one of
the most important characteristics of
creative climate (e.g. Amabile, 1988, Amabile 1997, Ekvall,
1983, Heinze, Shapira, Rogers and Senker,
2009). The paper demonstrates that higher levels of freedom or
autonomy decrease the probability of
doing product innovation.
Previous studies analyze scientists in R&D departments of
relatively large firms (Amabile, 1988, 1997,
Ekvall, 1997), whereas the sample of this study is composed of
small firms operating in manufacturing and
service businesses. Therefore, the freedom hypothesis
constructed upon the studies of large and heavily
R&D conducting firms may not be reflecting the priorities of
small firms well. The workforce of R&D
departments is mostly comprised of highly educated scientists,
who are capable of managing and
motivating themselves and handle freedom and autonomy
forcefully. On the other hand, other employees
may need regular management, task distribution and supervision.
Unintentionally, increasing freedom may
create confusion if employees do not have the self-management
and motivation skills. Employees may be
spending the special working time provided for creativity and
innovation activities on unnecessarily
complex tasks rather than focusing on improvement of the tasks
for facilitation of product innovation.
A recent study by Bunderson and Boumgarden (2010) provides a
different, but relevant interpretation for
the freedom finding. The study finds that self-managing teams
with higher level of formalization promotes
learning by encouraging information sharing and conflict
reduction. If these findings are considered for this
sample, an average level of freedom may lead to higher
innovation performance facilitated by clear task
specifications, flow of information and formal reporting
systems, while allowing moderate freedom.
Additionally, Yuan and Woodman (2010: 328) study individual
innovative behavior and use innovativeness
as a job requirement as an explanatory variable. They find that
employees who perceive innovativeness as
part of their job requirements are more likely to believe that
these activities are positive for their work. If
these findings are then considered for our results, we may
suspect that many employees in small firms that
perform different work tasks, often on an ad hoc basis, are more
prone to feel confused by too much
freedom. We can therefore suggest that future research analyze
whether job requirements specifying needs
for creativity and innovation are stimulating product
innovation.
In sum, we recommend that a future study attempt to uncover why
increasing freedom does not contribute
to product innovation, and what the optimum freedom level is for
stimulating creativity and achieving
innovation.
Another research opportunity arises from the distinction between
product and process innovation in
relation to the organizational creativity. A study focused on
process innovation and organizational
-
[17]
creativity relationship may reveal why resources, freedom or
idea time do not contribute to process
innovativeness, and simultaneously discuss what other
organizational factors could be stimulating further
process innovation.
6. Conclusion and recommendations
This paper affirms that organizing creativity does lead to
innovation, but only product innovation. The
relation with process innovation is much weaker and must
therefore be supported by other organizational
activities. The paper delivered the first comprehensive
quantitative test of the relationship between
organizational creativity and innovation. The findings from a
sample of 147 firms from a particular region
of Denmark confirm that encouraging employees for innovative
behavior in a stimulating work
environment, allocating resources and providing idea time play a
crucial role in stimulating creativity and
supporting product innovation.
The importance of allocating idea time for creative and
innovative activities is also confirmed.
Unexpectedly, higher levels of freedom are found to be acting
against product innovation. This finding
started the discussion on the balance between job formalities
and innovation requirements leading to a
recommendation for further research on freedom and innovation.
The statistical analysis did not confirm
that other variables, challenge, proactiveness and idea support
harness innovation contrary to the
discussion in the literature. The insignificant outcome of these
variables has mostly been associated with
the severe economic conditions shifting the priority towards
maintaining ongoing business activities as a
consequence of the financial crisis. Furthermore, a notable
relationship between organizational creativity
and process innovation has not been established, and further
analyses were recommended to reveal
additional important aspects of organizational creativity and
process innovation.
The results of this paper are presented to validate the
importance of the link between creativity and
product innovation to deepen our understanding this crucial link
rather than making generalizations. At
the same time, although the sample is relatively small, we make
recommendations towards managers of
innovation. Clearly, these results demonstrate that creativity
is not only an individual characteristic, but is
related to the organizing priorities of management and has a
strong impact on product innovation.
Therefore, managers of innovation need to balance the current
dominant view on open innovation by re-
emphasizing internal organizational factors as important drivers
of product innovation. While
acknowledging the adverse effects of the financial crisis, we
recommend managers to stay oriented and
take on reasonable risk and opportunities, and link these with
an offensive strategy. Simultaneously, we
recommend that managers exercise freedom cautiously to ensure
that operations are carried out
effectively, while employees are allowed moderate freedom to
achieve product innovation. Further,
recommendations can be developed once further studies are
carried out, emphasizing the need to study
off-crisis periods.
The small sample size from a relatively homogeneous population
and the ongoing effects of severe
economic conditions constitute the main limitations of this
study. Once more data are collected in a less
severe economic situation the statistical analysis may yield
further enlightening results. In addition to the
sample limitation, a potential bias may have been introduced by
requesting that the CEO or innovation
manager of the respondent firm complete the survey, thereby
capturing senior managers perceptions of
the firm rather than those of employees. Perceptions by these
distinct parties may not necessarily match
-
[18]
and voice the real conditions in the firm, although we find that
it may be easier for management to observe
employees and be aware of general perceptions and well-being in
the small firm. Therefore, although we
acknowledge potential bias, we expect much of response to
reflect the real creativity and innovation
stimulants in the firm as perceived by the employees, whether
creative or not!
References
Abernathy, W.J. and Utterback, J.M. (1978) Patterns of
Industrial Evolution. Technology Review, June/July, 40-47.
Amabile, T.M. (1988) A model of creativity and innovation in
organizations. In Staw, B.M. and Cummings,L.L (eds.),
Research in Organizational Behaviour. Vol. 10. Greenwich, Conn.
J.A.I. Press, pp 123-167.
Amabile, T.M. (1995) Discovering the Unknowable, Managing the
Unmanagable. In Ford, C.M. and Gioia, D.A.(eds.),
Creative Action in Organizations. Sage Publications, USA,
pp.77-82.
Amabile, T. M. (1997) Motivating Creativity in Organizations: On
doing what you love and loving what you do.
California Management Review 40(1), 39-58.
Amabile, T. M. and Gryskiewicz, N.D. (1989) The creative
environment scales: Work Environment Inventory. Creativity
Research Journal 2, 231-253.
Amabile, T. M., Conti, R., Coon. H., Lazenby and J. Staw, B.M
(1996) Assesing the work environment for creativity.
Academy of Management Journal 39(5): 1154-1184.
Anderson, P. and Tushman, M.L. (1991) Managing Through Cycles of
Technological Change. Research Technology
Management, 34(3), 26-31.
Barras, R. (1986) Towards a theory of innovation in services.
Research Policy, 19(1), 215-237
Bharadwaj, S. and Menon, A. (2000) Making innovation happen in
organizations: Individual creativity mechanisms,
organizational creativity mechanisms or both?. Journal of
Product Innovation Management 17(6): 424-434.
Bunderson, J.S. and Boumgarden, P. (2010) Structure and learning
in self-managed teams: Why bureaucratic teams
can be better learners. Organization Science, 21(3),
609-624.
Conway, J.M.and Lance, C.E. (2010) What reviewers should expect
from authors regarding common method bias in
organizational research. Journal of Business and Psychology 25,
325-334.
Damanpour, F.and Gopalakrishnan, S. (2001) The dynamics of the
adoption of product and process innovations in
organizations. Journal of Management Studies 38(1), 45-65.
Ekvall, G., Arvonen. J.and Waldenstrm-Lindblad, I. (1983)
Creative Organizational Climate: Construction and
Validation of a Measuring Instrument. The Swedish Council for
Management and Work Life Issues. Report 2.
17 p.
Ekvall, G. (1996) Organizational climate for creativity and
innovation. European Journal of Work & Organizational
Psychology 5(1), 105-123.
Ekvall, G. (1997) Organizational conditions and levels of
creativity. Creativity and Innovation Management 6(4), 195-
205.
Ettlie, J.E. and Reza, E.M. (1992) Organizatinal integration and
process innovation. Academy of Management Journal,
35 (4), 795-827.
Ford, C. M. (1996) A Theory of individual creative action in
multiple social domains. Academy of Management Review
21(4), 1112-1142.
-
[19]
Garcia, R. and Calantone, R. (2002) A Critical Look at
Technological Innovation Typology and Innovativeness
Terminology: A Literature Review. The Journal of Product
Innovation Management, 19(2), 110-132.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. and
Tatham, R. L. (2006) Multivariate Data Analysis (Sixth ed.).
New
Jersey: Pearson - Prentice Hall. 899 p.
Heinze, T., Shapira, P., Rogers, J.D. and Senker, J.M. (2009)
Organizational and institutional influences on creativity in
scientific research. Research Policy 38(4), 610-623.
Hoetker, G. (2007) The use of logit and probit models in
strategic management research: Critical issues. Strategic
Management Journal, 28 , pp.331-343.
Hsu, M.L.A. and Fan, H. (2010) Organizational Innovation Climate
and Creative Outcomes: Exploring the Moderating
Effect of Time Pressure. Creativity Research Journal 22(4),
378-386.
Kanter, R. M. (1988) When a thousand flowers bloom: Structural,
collective and social conditions for innovation in
organization. In Staw, B.M. and Cummings,L.L (eds.), Research in
Organizational Behaviour. Vol. 10.
Greenwich, Conn. J.A.I. Press, pp 169-209.
Lance, C.E., Dawson, B., Birkelbach, D.and Hoffman, B. (2010)
Method effects, measurement error, and substantive
conclusions. Organizational Research Methods 13(3), 435-455.
Mohamed, M.Z.and Rickards, T. (1996) Assessing and comparing the
innovativeness and creative climate of firms.
Scandinavian Journal of Management 12(2), 109-121.
Moultrie, J.and Young, A. (2009) Exploratory Study of
Organizational Creativity in Creative Organizations. Creativity
and Innovation Management 18(4), 299-314.
Oldham, G. R.and Cummings. A. (1996) Employee Creativity:
Personal and Contextual Factors at Work. Academy of
Management Journal 39(3), 607-634.
Podsakoff, P.M., MacKenzie, S.B., Lee, J. and Podsakoff, N.P.
(2003) Common method bias in behavioral research: A
critical review of the literature and recommended remedies.
Journal of Applied Psychology 88 (5), 879-903.
Pisano, G.P and Wheelwright, S.C. (1995) The new logic of
high-tech R&D. Harvard Business Review 73(5), Sept/Oct,
93-105.
Puccio, G.J. and Cabra J.F. (2010). Organizational creativity: A
systems approach. In Kaufman J.C. and Sternberg R.J.
(eds.) The Cambridge Handbook of Creativity. Cambridge
University Press, USA,pp.145-173.
Shalley, C.E. (1991) Effects of productivity goals, creativity
goals and personal discretion on individual creativity.
Journal of Applied Psychology 76, 179-185.
Shalley, C.E., Gilson, L.L., Blum, T.C. (2000) Matching
creativity requirements and the work environment: Effects on
satisfaction and intentions to leave. Academy of Management
Journal 43(2), 215-223.
Shalley, C.E. and Zhou, J.(2009) Organizational Creativity
Research: A Historical Review. In Zhou, J. and Shalley, C.E.,
Handbook of Organizational Creativity, Reprinted 2009.
Psychology Press, Taylor and Francis Group, LLC,
USA, pp .3-31.
Sohn, S. and Jung, C. (2010)Effect of creativity on innovation:
Do creativity initiatives have significan impact on
innovative performance in Korean firms?. Creativity Research
Journal, 22(3).320-328.
Soo, C., Devinney, T., Midgley, D. and Deering, A. (2002)
Knowledge management: Philosophy, processes and pitfalls.
California Management Review, Vol.44, No.4,pp.129-150.
Taggar, S. (2002) Individual creativity and group ability to
utilize individual creative resources: A multilevel model.
Academy of Management Journal 45(2), 315-330.
-
[20]
Utterback, J.M. and Abernathy, W.J. (1975) A dynamic model of
process and product innovation. OMEGA, The
International Journal of Management Science 3(6), 639-656
Woodman, R. W. (1995). Managing Creativity. In Ford, C.M and
Gioia, D.A.(eds.). Creative Action in Organizations.
Sage Publications, USA, pp.60-65.
Woodman, R. W., Sawyer, J. E. and Griffin R., W. (1993) Toward a
Theory of Organizational Creativity. Academy of
Management Review 18(2), 293-321.
Wooldridge, J.M. (2009). Introductory Econometrics: A Modern
Approach (4th Ed). South-WesternLearning.USA. 865p.
Yuan, F. and Woodman, R. W. (2010). Innovative Behavior in the
Workplace: The Role of Performance and Image
Outcome Expectations. Academy of Management Journal, 53(2):
323-342.
