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, DRUIDmpk@sam.sdu.dk

Özge Cokpekin

ozge@sam.sdu.dk

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?

Özge Cokpekin1

Mette Præst 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: ozge@sam.sdu.dk.

[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 CEO’s 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 1½ 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 1½ 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 one’s 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 <3). This analysis shows that some responses varied in

the scale rather than being accumulated around the mean. A possible bias caused by the tendency to choose

neutral answers caused by lack of attention is therefore reduced as well.

The consistency bias and other types of common method bias whose sources are not detectable to the

authors (Podsakoff et al, 2003) may have affected some responses and distorted the correlation structure

of the variables (Lance, Dawson, Birkelbach and Hoffman, 2010). Common method bias is often considered

to be inflating the true correlations among the variables (Conway and Lance, 2010, p. 327), but Lance et al

(2010, pp. 436-437) have recently shown that this concern does not hold true. Therefore, even if non-

detectable common method bias or consistency still exists in the study, it does not inflate correlations, as

opposed to the common concern. Thus, given the relatively low risk of the two first sources of bias, the

undetectable problems associated with the third possible bias, and the discussed irrelevance of the

multicollinearity problem, we do not take further action and treat results as common method bias free.

[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<250 and number of items=11): CFI=0.850; RMSEA=0.084 and

CMIN/DF=2.04. These values indicate the model fit is at an acceptable level (Hair et. al., 2006). Extracted

variance for each of the components: strategy and risk = 0.427; employee appraisal = 0.498; resources =

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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 (<0.0001), and are close but

not all above the threshold value of 0.5. In particular, the resource component appears to be not correctly

specified using the suggested items and it is recommendable that these be scrutinized in future research.

The model fit for the five creative climate variables (N<250 and number of items = 14): CFI=0.967;

RMSEA=0.052 and CMIN/DF=1.39. These values indicate a solid model fit. Extracted variance for each of

the components: challenge = 0.680; freedom = 0.647; idea support = 0.749; proactiveness = 0.479; idea

time = 0.551. These results indicate a solid convergence (with VE > 0.5) for all components, but

proactiveness. All of the standardized regression weights are highly significant (<0.0001), and above the

threshold value of 0.5 (smallest value is 0.601) indicating a good representation of the latent constructs.

These results indicate that especially for the strategy and risk, employee appraisal and resources

components further validation of the items and the latent constructs must be encouraged for other samples

(see table 3 for the descriptives).

“Strategy and Risk” and “Employee Appraisal” Variables

These variables are constructed upon Amabile`s (1988, 1997) organizational motivation component. The

strategy and risk variable refers to the firm`s forward facing strategy towards opportunities and risks. The

latent factor is constituted by the measures; to what extent a firm follows opportunities and changes in its

market to achieve innovation rather than maintaining the status-quo and how explicitly the firm

demonstrates creativity to internal and external stakeholders.

The latent variable behind the employee and appraisal variable measures up to what extent a firm

encourages its employees to show a creative and an innovative attitude. The construct depicts the

psychological encouragement such as showing explicit enthusiasm and pride towards employees’ positive

attitude, and organizational encouragement in terms of establishing flexible management systems to

accommodate the desired behavior.

Resources

This construct includes Amabile`s (1988, 1997) resource component and captures all resources necessary

for achieving innovation. Ordinary working time available for thinking new ideas, expertise of employees to

generate new ideas for problems, widely available material and information resources and training

opportunities are measured.

Challenge

This construct measures the extent that employees emotionally involve in their tasks and put high amount

of energy. The goal is to measure how well employees’ capabilities match with task requirements so that

employees feel intellectually challenging and developing (Ekvall, 1996). This latent construct does not aim

to measure negative challenge in terms of excessive workload inhibiting fulfillment and job satisfaction.

Freedom

This variable refers to the freedom of the employees to plan their work and choose one’s means to

accomplish an assigned task (Amabile, 1988, Ekvall, 1996).

[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.

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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<0.01, **p<0.05, *p<0.1 (Two tail test)

Table 5: Logistics regression results

An important observation relates to the number of observations (n1= 105; n2=100 and n3=88). These

numbers indicate a loss of observations from the original 147 cases. To decrease the loss of information

and to run a sensitivity analysis of the reported results, the missing cases were checked against the full set

of cases in terms of differences of means. Since these tests were insignificant, it is possible to impute the

missing values using regression analysis. The resulting logistic regression models yielded the same

significant variables and same magnitude of the coefficients. The paper therefore reports the original

models. The results of the imputed models can be obtained from the corresponding author upon request.

[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<0.1 (2 tail-test)

Table 6: Correlation among the dependent variables and dropped independent variables

An overall view of the models states that the product innovation model produces significant results for

further discussion. However, the process innovation model provides limited information suggesting that

other factors must be more important for stimulating process innovation, thereby raising the process

innovation and organizational creativity link as a new research opportunity. Hence, for the remainder of

the paper, the attention is at discussing the product innovation model.

Interpretation of coefficients

Magnitudes of coefficients are not meaningful per se in logistic regression models; an exponential

transformation is required to interpret the coefficients and calculate changes in the probability of

occurrence of the dependent variable (Wooldridge 2009, p. 577, Hoetker 2007, p.332). Following this

advice, the changes in the probability of doing product innovation are calculated and graphed (figure 1).

Each line in the graph below illustrates the corresponding probabilities when responses to a significant

variable (strategy and risk, freedom, idea time and resources) vary between 1 and 5, while keeping all other

(significant or insignificant) variables at their means.

[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

ba

bili

ty o

f do

ing

pro

du

ct in

nova

tion a

ccord

ing t

o th

e r

esp

on

ses

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!

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