How to Boost Innovation Culture and Innovators?

March 15, 2010 14:45 WSPC/Trim Size: 9.75in x 6.5in SPI-b778 b778-ch15

Chapter 15

How to Boost Innovation Culture and Innovators?

ANDREA BIKFALVI

Department of Business Administration and Product Design (OGEDP),University of Girona, Campus Montilivi, Edifici PI,

Av. Lluıs Santalo s/n 17071 Girona, Spain

[email protected]

JARI JUSSILA∗, ANU SUOMINEN† and HANNU VANHARANTA‡

Industrial Management and Engineering,Tampere University of Technology at Pori,

PL 300, 28101 Pori, Finland∗[email protected]

†[email protected]‡[email protected]

JUSSI KANTOLA

Department of Knowledge Service Engineering,KAIST 335, Gwahangno (373-1 Guseong-dong),

Yuseong-gu, Daejeon 305–701, Korea

This chapter examines abstract concepts of innovators’competences and innovation culture.For people to be innovative, both concepts need to be considered. Ontologies provide a wayto specify these abstract concepts into such a format that practical applications can beapplied in organizations. Self-evaluation of innovation competence and innovation culturein organizations can be conducted by utilizing a fuzzy logic application platform calledEvolute. The approach described in this chapter has management implications. The abstractconcepts of innovation culture and innovation competence become manageable, whichsuggests that organizations should be able to get better innovation results.

Keywords: Innovation; innovators; culture; ontology.

1. Introduction

For people to be innovative, it seems to require a special mindset and environment,additionally according to Ulijn and Brown (2004) not all innovative people areentrepreneurial. Although some work exists on how to create an organization wideculture of innovation and intra- and entrepreneurship, culture and especially the

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link between culture and innovation has generally not been studied. A variety ofreasons might explain this: the broad concept of what we understand as culture,the multitude of links to other sciences — sociology, anthropology, psychology, orthe depth of the concept when referring to national culture, corporate culture, orprofessional culture.

From organization’s management point of view there is another difficulty. Man-agement theories are scattered over a wide area of different management disciplines,and therefore it is difficult to get a holistic view of these different and specific man-agement areas and their detailed content, i.e., constructs, concepts, variables, andindicators. For management research, there is a new area that may help to attain thisholistic view: object ontology research. Additionally, system science is trying tohelp solve this dilemma with many different technologies to help holistic perceptionand understanding in management.

This research, based on previous research on management objects ontologies(Kantola, 2005), aims to build up constructs for management purposes in dynamicorganizational environment of innovations management from two points view: indi-vidual and organizational. The focus of this chapter is on specific interrelated factorsof innovation competences and organizational innovation enablers and barriers. Themain targets of this research form the two main objectives of study. The first objectiveis to examine the nature of personal innovation competences through the concept ofcreative tension (Senge, 1994). The second objective is to investigate the essence oforganizational innovation enablers through the concept of proactive vision (Aramo-Immonen et al., 2005; Kantola et al., 2005; Paajanen et al., 2004). Through the firstobjective, we expect to identify the competences needed by individuals in order tobe innovative. This would provide a better understanding of the potential impact(if any) of personal innovation competences on the level of employees’ innovation.Through the second objective, we expect to identify those innovation enablers andbarriers in terms of the whole organization as a more responsive innovation envi-ronment. This will provide a better understanding of the management of innovationwithin organizations.

To make all this possible we have created two conceptual models, i.e., ontologiesto help analyze the above. After that we have created computer-supported manage-ment questionnaires for self-evaluation of those two above-mentioned ontologies.By making the questionnaires dynamic with internet, we have performed test runswith a group of test subjects.After that we have shown the first signs of the ontologybuilding process. In our future research we will further develop those ontologiesand expand the testing also in different industry organizations.

2. Conceptual Framework

2.1. National Systems of Innovation

The concept of a national system of innovation provides a good starting pointin analyzing both innovation and culture. The standard schematic for a country’s


How to Boost Innovation Culture and Innovators? 361

Macroeconomic andregulatory context

Global

g y

Knowledge generation, diffusion & use

m

Innovation networks

Education andtraining system

Communicationinfrastructures

Firms’capabilities& networks

Otherresearchbodies

Sciencesystem

Clu

ste

rs o

fin

du

stries

Re

gio

nal

nova

tion

syst

em

bodiesy

Supportinginstitutions

National innovation

Inn

Product marketconditions

Factor marketconditions

system

National innovation capacityNational innovation capacity

COUNTRY PERFORMANCEGrowth, jobs, competitiveness

Figure 1. Main actors and linkages in the innovation system (adapted from OECD).

innovation system depicted in Fig. 1 can be revisited. Although schematic andresumed, it provides a holistic picture of the actors and linkages established in acertain innovation system. Still, the core of the system remains illustrated in thecenter of Fig. 1. Meanwhile, firms, the research and science base, and the supportinginstitutions represent Etzkowitz and Leydesdorff’s (1998) triple helix model.

The interaction of university–industry–government is at the basis of innovation,a process that becomes an endogenous process of “taking the role of the other,”encouraging hybridization among the institutional spheres (Etzkowitz, 2003).

More concretely, universities facing their third mission, higher education canno longer avoid experimenting in entrepreneurial areas. Scientists should be ableto complement their basic research activities with research having an imme-diate commercial value contributing this way to local and regional economicdevelopment and growth. Competition and turbulent environment are other areasthat nowadays make public research institutions resemble each time more to thebusiness area.

Furthermore, government acts as a public entrepreneur and venture capitalist inaddition to its traditional role of creating an environment conductive to innovation.Recent public schemes go far beyond the increase of R&D investment, designingand promoting complementary “soft” tools for innovation promotion.



However, firms remain to be the backbone of the systems. Their productive,employing, competitive, innovative and growth capabilities put them in the “spot-light.” The environment in which they operate, often characterized by high complex-ity and low predictability, converts them into special actors. They are the ultimateinnovator operating and facing markets and final customers, whose verdict labelstheir product and/or services with either success or failure. As firms raise their tech-nological level, they move closer to an academic model, engaging in higher levelsof training and in sharing of knowledge.

All these show, up to some point, overlapping and common areas rather thanisolation between these three pillars. Knowledge generation, diffusion, and uselater becoming innovation are a common characteristic to all. During the last twodecades, innovation and innovation management were among the top prioritieson the research agenda of academics, practitioners, and policy makers. Differ-ent trends succeeded in its study, reflected by the richness in definitions col-lected, for example, by Cumming (1998) in his overview on innovation and futurechallenges.

Focus topics passed from technical, industrial, and commercial aspects, throughcreativity and culture, large firms versus small firm innovation, sources, patterns,standardization, measurement and monitoring, to human aspects and organizationalconcepts among others. As the study of innovation’s areas of richness would be tooambitious, focusing on few concepts seems a more appropriate option. Thereforein the following sections we give special attention to organizational innovation ingeneral, and its enablers and barriers in particular.

2.2. Co-evolution of Systems

The nature of conscious experience at work is a puzzle for the modern knowledgesociety. Companies, enterprises, groups, and teams emphasize now more and moreon the unique value of individuality in a context of organizational excellence andteamwork. These entities also attempt to learn about the individual’s knowledge interms of his/her own professional competences, as well as the individual’s aspira-tions and desires to change and improve those competences.

Furthermore, many enterprises would like to guide and support employees’personal growth, development and personal vision in order to improve their corecompetences according to the competitive pressures of the business world. Basedon the employees’ self-evaluation, the gap between personal vision and currentreality forms an individual’s creative tension (Senge, 1994). This creative ten-sion is the energy, which can move an individual from the place of current realitytowards the reality of his/her own vision. This is one real achievement driver of theenterprise.

When the objects are management processes, it is possible to analyze the cur-rent management processes from bottom-up perspectives in order to understandhow these processes can be improved. Similarly to creative tension, the other real



achievement driver in organizations is proactive vision (Aramo-Immonen et al.,2005; Kantola et al., 2005; Paajanen et al., 2004). With proactive vision, employ-ees get opportunity to understand the current state of organizational variables andlook to the future and give their opinion, i.e., proactive vision about how these pro-cesses should be changed. By combining these two important drivers, i.e., creativetension and proactive vision, it is possible to get more information of the organi-zation, in order to develop organization towards higher performance levels. In thefollowing pages this combination is explained and illustrated in more detail.

In our previous research, strong emphasis has been put to a new proposedtheory and methodology, i.e., co-evolution (Vanharanta et al., 2005). In the the-ory formulation, the attempt has been to see the current (perceived) reality fromdifferent points of view. Additionally it is emphasized that it is important to under-stand the time dimension and the change processes inside the systems and subsys-tems. By increasing the different views it is possible to increase the informationvariety in human brains and that way decrease the errors to perceive the currentreality.

From human point of view, it is therefore important to understand both ourinternal world as well as the external environment in which we live. Co-evolutionapplied towards an internal view (introspection of own properties or characteris-tics) extends our ability to evaluate and develop simultaneously different personalcharacteristics. Co-evolution focused on the external world and different externalprocesses provides a possibility to frame, categorize, conceptualize, understand,and perceive the current reality in a diversified way. From the organizational pointof view, the co-evolutionary process viewpoint helps us to identify the need for achange, both in people as well as management processes.

2.2.1. Co-evolution in human performance

In order to illustrate an application of the co-evolutionary management paradigmin the human resource management area, Beer (1994) has provided the followingrelationships, by defining first the levels of human achievement:

• Actuality: is what people manage to do now, with existing resources, under exist-ing constraints.

• Capability: is what people could achieve now, if really worked at it, with existingresources and under existing constraints.

• Potentiality: is what people might be doing by developing their resources andremoving constraints, although still operating within the bounds of what isalready known to be feasible.

Furthermore, the important indices are as follows (Beer, 1994):

• Latency: the ratio of potentiality and capability• Productivity: the ratio of capability and actuality



Potentiality

Capability

Actuality

Latency

Productivity

Performance

÷

÷

x ÷

Figure 2. Measures of human performance (cf. Beer, 1994; Jackson, 2003).

• Performance: the ratio of potentiality and actuality and also the product of latencyand productivity.

In the above framework, an application of the co-evolutionary paradigm would leadto the most desired outcomes. First, it can be observed that the above equationsindicate the importance of keeping the ratios up (high values) in order to increasethe overall human performance. If this potentiality (Fig. 2) is carried out evenfurther, the personal level of the future state a person is targeting towards should befound out, i.e., the individual’s creative tension. On the current level (actuality), itis important to know what a person manages to do now, i.e., how she/he performs atthe present and what are the constraints of such performance? The capability or thecapabilities to do something is the best ability or the best qualities that the personcould exhibit now. The human competence, in turn, is the ability of doing somethingwell and effectively in the immediate future (expanding on the potentiality), i.e.,capability for active use. This also gives reasoning to the importance of time in theoverall equation (see Fig. 2).

2.2.2. Co-evolution in business performance

Another example of the application of the co-evolutionary management paradigm(Vanharanta et al., 2005) can be illustrated by using the concept of productivityin company performance calculations (see Fig. 3). The all-important operationalattribute influencing overall company performance is productivity (cf. Kay, 1993;Kidd, 1985).

Capital productivity indicates how much capital is invested in relation to added-value operations in the company, and market productivity indicates how much profitis yielded in relation to all added-value activities. Capital productivity is added-value divided by total capital (total assets), and market productivity is operatingprofit divided by added-value. Added-value is the market price of products and



Profit

Added-value

Total assets

Marketproductivity

Capitalproductivity

Return of total assets

÷

÷

x ÷

Figure 3. Measures of capital performance (cf. Kay, 1993; Kidd, 1985).

services sold less the market costs of purchased materials (or services) containedwith them (cf. Kay, 1993; Kidd, 1985).

The same kind of performance patterns can be seen in Fig. 3 as in the humanperformance illustration in Fig. 2. Similarly, in this example, it is important to keepthe ratios high to assure goods results, i.e., the overall profitability performance.However, before the ratios can be changed, the company’s position (situation) atpresent has to be found out. After that, by understanding the present position (sit-uation) of the company, it is possible to provide new instructions of the means toincrease the overall return on total assets through important constructs, concepts,and variables.

In real life, the notions illustrated in these two figures (Figs. 2 and 3) haveto be understood and utilized simultaneously and concurrently, so that the capitalprofitability as well as human performance at present and in the immediate futurecan be comprehended. The equations are similar, giving the asymptotic curves.By combining the information in these equations, the possible new space can bedetermined where both these concepts can be handled simultaneously.

What can be seen are the relationships that are important in order to changethose ratios. It is the co-evolutionary way of thinking related to the two equa-tions (which cannot be directly combined), that lead to the overall performance offinancial and intellectual capital, i.e., the market value (cf. Edvinsson and Malone,1997).

From the financial point of view, it has to be considered how financial assetsare harnessed to create added value and how the customers are willing to pay forthat created value. On the other hand, from the human point of view, it has to beconsidered, which human characteristics (properties) are the best that human per-formance can be related with. Within the concept of actuality, the current state withexisting resources can be managed. By developing these resources and by removingrelevant constraints, the potentiality can be increased. It raises the question: “Whatmight then be the best possible way to develop those resources?”



According to Senge (2004), learning organization has several issues to consider,i.e., systems thinking, team learning, shared vision, mental models, and personalmastery. In the context of our co-evolutionary paradigm, all of these concepts areimportant, and each of them should be developed simultaneously with another,in the co-evolutionary way. In the personal mastery concept, the driving forcebehind co-evolution is the creative tension. On the other hand, in the businessprocesses the people who face the real world each day in their work are the peoplewho understand the current and future state of the business process, i.e., proactivevision, the best. By gathering all their individual opinions, the collective view ofthe organization regarding the proactive vision can be attained for making betterperformance through peoples’ understanding and motives.

2.3. Organizational Innovation Enablers and Barriers

Many authors have identified those enablers and barriers of organizational inno-vation (e.g., Amabile et al., 1996; Amabile, 1997, 1998; Ekvall, 1996; Martinsand Terblanche, 2003; Trott, 2005). Suominen et al. (2008a) have discovered fromliterature, 22 of those enablers and/or barriers and illustrated them with a vividmetaphor of Hydro Power Plant, Fig. 4.

Freedom

Freedom of flowOpenness and trustCommunication

Requisite variety

Understanding strategy

Direction of flow

Understanding strategy

Organizational flexibilityStress management

ChangeabilityChallenge

Innovation Culture

Direction of flow Challenge

Empowerment

Constructive feedback

Risk tolerance

Organisation support development

Transformation of the flow

Organisation support development

Organisation support learning

Idea generationIdea documentationTransformation of the flow Idea documentation

Idea screening and evaluation

Teamwork and collaboration

Seeking information

Maintaining of the flowSeeking informationAbsorptive capacity

Networking

Situational constraints

Figure 4. Innovation culture ontology.



The four part metaphor first illustrates the organizational climate variables,then the organizational management and structure variables, thirdly the innovationprocess variables, and fourth the supportive organizational variables. Here, theentity of these four parts of the metaphor constructs a metaphor called Innovationculture. However, most of these enablers and barriers are more or less visual orconcrete parts of organization, whereas culture is often seen more as an invisible,yet sensible part of organization to their members and even to a third party (McLean,2005; Schein, 2004).

2.4. Innovator’s Competences

Innovator’s competences are like items on a menu, we can identify those that rep-resent our strengths and those that represent our weaknesses and those which wewant to focus on (cf. Miller, 1987). The Innovator’s competence ontology describesthose competences that the literature (Jussila et al., 2008) emphasizes as importantcharacteristics of creative and innovative people. The major components of individ-ual creativity necessary in any domain are expertise, creative-thinking skills, andintrinsic task motivation (Amabile, 1997). However, rarely an individual is able torely solely on his own motivation and technical skills to get the job done, mostof us work in environments in which we must constantly deal with other people(Merrill and Reid, 1999). The same is true for innovations; innovations are hardlyever the result of only one individual. Therefore more than creativity is needed inmaking innovations happen. The major components supporting creativity in theontology are self-awareness, self-regulation, empathy, and relationship manage-ment (Goleman, 1998). The innovator’s competence ontology consists of two parts(personal competences and social competences) and seven major components (self-awareness, self-regulation, motivation, expertise, creative thinking, empathy, andrelationship management) divided into a total of 27 competences (Fig. 5).

The clustering of innovator’s competence ontology is theoretical and basedon the earlier theoretical models (Amabile, 1997; Goleman, 1998). More recently,Goleman (2006) has published a model of social intelligence that parallels emo-tional intelligence. However, as he has pointed out: “The model of social intelli-gence . . . is merely suggestive, not definitive, of what that expanded concept mightlook like . . . More robust and valid models of social intelligence will emerge grad-ually from cumulative research” (Goleman, 2006, p. 330).

3. Methodology

3.1. Self-Evaluation of Humans and Systems

In self-evaluation, a person is evaluating oneself, or a system that this individ-ual evaluator is part of. The results from self-evaluation can be used for differentpurposes, such as motivation, identification of development needs, evaluation



Self-awarenessAccurate self-assesment

Self-confidence

Flexibility

Personalcompetences

Self-regulation

Motivation

IndependenceResponsibility

Self-control

Stress tolerance

Expertise

Trustworthiness

Innovator’scompetences

Absorptive capacity

Professional and technical expertise

Creative thinking

p Stress tolerance

Trustworthiness

Analytical thinking

Conceptual thinkingg

Divergent thinking

Intuitive thinking

Leveraging diversity

Socialcompetences

Empathyg g y

Understanding others

Communicationp Relationship

managementConflict management

Relationship building

Teamwork and cooperation

Figure 5. Innovator’s competence ontology.

of potential, evaluation of performance, career development purposes, etc. (cf.Nurminen, 2003). Self-evaluation is an efficient method of developing oneself,managing personal growth, clarifying roles, and committing to project related goals(e.g., Nurminen, 2003). On the other hand, self-evaluation has limitations too. Theresults of a self-evaluation are less reliable in the evaluation of work performance(Stone, 1998). People have the tendency to evaluate their own performance bet-ter than others (Dessler, 2001). People are also limited in their ability to observethemselves and others accurately (Beardwell and Holden, 1995). Still, there is noquestion that people are able to evaluate themselves if they are motivated to doso. We have observed that the presentation of self-evaluation projects to target isvery important. The effectiveness of self-evaluation also depends on content of theevaluation, application method, and the culture of an organization (Torrington andHall, 1991).

The results of self-evaluations conducted by an individual, vary to some extent.In the short term, the results change because individuals’ power of observation,intentions, and motives change (Cronbach, 1990). In the long term, the resultsalso change because of mental growth, learning, and changes in personality andhealth.

Self-evaluation is more effective in evaluating the relation between differentitems, such as competencies, than comparing individuals’ performance to others’performance (cf. Torrington and Hall, 1991). In our approach, competences and



systems are evaluated indirectly through the statements related to individuals’everyday work — therefore individuals are not evaluating their performance. In thiscontext, we mean self-evaluation of innovation culture (the system) and innovator(human in the system).

When we want to include the concept of creative tension (Senge, 1994) in anevaluation, we must use self-evaluation. This is because no one can tell the futureintentions and aspirations of another person.

Noticeable is that the data generated though self-evaluation has a certain nature.For instance every single individual has their own, personal scale of degree. There-fore traditional scientific statistical methods are not applicable for such data. Thus asanalysis method, we have used Friedman test, which is suitable for non-parametricdata produced with self-evaluation. The Friedman test is one scientifically validnon-parametric statistical method (Conover, 1999), named after its inventor NobelLaureate economist Milton Friedman. The Friedman test sums the ranked valuesof each respondent. Consequently the ranked values can be clustered into groups(Suominen et al., 2008b).

3.2. The Evolute Application Environment

Evolute is the name of a generic web-based technology that supports fuzzy logic(Zadeh, 1965) applications on the Internet (Kantola, 2005). Evolute supports specialpurpose fuzzy logic applications to be developed and run globally. Each applicationis based on a specified ontology of the target domain (Kantola, 2005). Therefore,each application on Evolute has a unique content and structure specified by theexperts of the target domain. Applications can be added and fine-tuned withoutadditional programming. Evolute supports co-evolutionary applications, which areintended for helping in simultaneous development of business enterprises or systems(Vanharanta et al., 2005) that include humans and organizations.

3.3. Self-evaluation of Innovation Competence and OrganizationalInnovation Enablers and Barriers with Evolute-System

Individual’s creativity and organizational innovation have been linked with eachother in the literature previously (e.g., Amabile, 1997, 1998; Amabile et al., 1996;Martins and Terblanche, 2003; McLean, 2005). Creativity is a characteristic of anindividual, whereas innovation is a process, often within an organization (McLean,2005). Therefore, creating Management Object Ontology (MOO) (Kantola, 2005)regarding organizational innovation also requires the perception of individual’scapability, i.e., competence to innovate to be included.

In this chapter, the first three phases of five phases of ontology development(Sure et al., 2003), feasibility study, kickoff, and refinement (Fig. 6), of two MOOswith co-evolutionary method are presented.



Feasibilitystudy

Kickoff Refine-ment

Evalua-tion

Go/ No Go?

Sufficientrequirements?

Meetsrequirements? Roll-out? Changes?

Identify…

1.Problems andopportunities

2.Focus of KMapplication

3. (OTK-) Tools

4. People

7. Refines emi-formal ontologydescription

8. Formalize intotargetontology

5. Capturerequirementsspecification inORSD

6. Create semi-formal ontologydescription

13. Applyontology

14. Manageevolution andmaintenance

9. CreatePrototype

10. Technology-focusedevaluation

11. User-focusedevaluation

12. Ontology-focusedevaluation

Ontology Development

KnowledgeManagementApplication

Common KADSWorksheets

ORSC + Semi-formal ontologydescription

Targetontology

Evaluatedontology

Softwareengineering

Decisions

Outcomes

Iterations

Application&Evolution

Evolvedontology Human

issues

Figure 6. The knowledge meta process (adapted Staab and Studer, 2003, p. 121).

In the first two overlapping phases, the feasibility study and kickoff for Knowl-edge Management Application (KMA) for innovation was studied. The preliminarystudy regarding organizational innovation, carried out mainly by literature review,brought forward the facts that innovation as an object of study is both timely, evenfashionable and additionally that some parts of innovation, especially regardingorganization, are rather poorly researched (McLean, 2005). This is due to the factthat organizational study regarding innovation has many problems and difficulties:on one hand organizations are different in their size, branch, personnel, and focuson e.g., innovation. On the other hand, many of the methods for studying, e.g., orga-nization culture are normally time consuming and require heavy, even subjectiveanalysis by the researchers. This also makes the results indefinite and constrainedto a certain time slot, lacking the desired focus to the future.

As a goal to create a KMA for leadership purposes, the focus of the applicationwas determined as duplex: on one hand to organizational enablers and barriers forinnovation, on the other hand to individuals’ innovation competences. Naturally,there is a wide range of other subjects of innovation that could have been the focusof the study, but these topics were seen most usable from the management’s point ofview for leading the entire personnel of an organization by gathering the informationfrom bottom-up and then using the collected collective data for determining theneeded management procedures.



The sources for creating the semi-formal ontology description were scientific,mainly journal literature. The literature handled individual competences, also capa-bilities for innovation, innovation inductive organizational culture and climate andinnovation process among others. The literature review resulted from 27 individ-ual innovation competences (Jussila et al., 2008) and 22 organizational innovationenablers and barriers (Suominen et al., 2008a).

In this first phase, evolute-system was used as a platform for creating twoself-evaluation questionnaires, collecting data and doing the needed computationoperations for accumulating the data into collective result. The questionnaires —innovation competence questionnaire having 103 statements and the organizationalinnovation questionnaire having 94 statements — have sliding scale, a bar thatallows the responder to answer on an individual range. The people evaluate subjec-tively one’s individual capabilities and objectively the environment — in this caseone’s organization. The other evolute characteristic is that the evaluation answeris placed on both for current and future states, thus illustrating the creative ten-sion (Senge, 1994) of individuals, or likewise proactive vision for organizations.Besides, the evolute-system uses fuzzy logic for the computation operations to sim-ulate human reasoning, which by nature is fuzzy. Those two questionnaires wereformulated according to the found competences and organizational enablers andbarriers, each competence and enabler or barrier including 3 to 8 statements foreach responder to answer.

As a result of the refinement phase, the first version of the parallel created semi-formal ontologies was represented (Table 1). Most of the individual variables havea counter part with the organizational ontology.

The next phase in the ontology development process would be the evaluationphase including an interview of the test runs with the web-based questionnairesin order to gather comments from the test persons of those two ontologies. Thisevaluation round should then be followed by a new iteration round of refinement.

4. A Case Test Run

After the completion of the semi-formal ontology, a test run was done at an educa-tional and research unit of University with a group. First the results of the individualinnovation competences are illustrated in a bar chart (Fig. 7). The n = 10 signifiesthe 10 respondents of staff members and α = 0.05 signifies the used significancelevel of 0.05. The sums have been divided into three groups: the most significant(black bars), middle group (white bars), and the least significant (grey bars).

The gap between individual’s innovation competences’current and future statesportrays the creative tension, whereas the gap between organization’s innova-tion enablers and barriers current and future states portrays the proactive vision.Thus, both the creative tension and proactive vision, point out those competencesor enablers and barriers that need the most attention: where the current state isrelatively low compared to the future desired state. This way the organization’s



Table 1. Individual Innovation Competences and Organizational InnovationEnablers and Barriers (Adapted from Suominen et al., 2008b).

Individual innovation competencesOrganizational innovation enablers and

barriers

Connection to innovation enablers andbarriers

(1) Absorptive capacity(2) Accurate self-assessment(3) Achievement orientation(4) Change orientation(5) Communication(6) Flexibility(7) Independence(8) Initiative(9) Stress tolerance

(10) Leveraging diversity(11) Professional and technical expertise(12) Relationship building(13) Risk orientation(14) Seeking information(15) Self-development(16) Teamwork and cooperation(17) Trustworthiness(18) Analytical thinking(19) Conceptual thinking(20) Divergent thinking(21) Imagination(22) Intuitive thinking

Connection to innovation competences

(1) Absorptive capacity(2) Constructive feedback(3) Challenge(4) Changeable(5) Communication(6) Flexibility(7) Freedom(8) Empowerment(9) Stress management

(10) Requisite variety(11) Organization support learning(12) Networking(13) Risk tolerance(14) Seeking information(15) Organization support development(16) Team work and collaboration(17) Trust and openness(18) Idea generation

No connection to innovation enablers andbarriers

(1) Conflict management(2) Responsibility(3) Self-control(4) Self-confidence(5) Understanding others

No connection to innovationcompetences

(1) Idea documentation(2) Idea screening and evaluation(3) Understanding strategy(4) Situational constraints

management can direct their attention to those matters requiring most urgentdevelopment.

With creative tensions we came into groups where the first 13 rankings werethe most significant and the last 8 the least significant. With proactive vision therankings were divided into 3 groups, where first 5 first were the most significant



0 5 10 15 20 25

Risk orientation

Independence

Divergent thinking

Trustworthiness

Achievement orientation

Teamwork and cooperation

Responsibility

Imagination

Change orientation

Seeking information

Conflict management

Leveraging diversity

Initiative

Relationship building

Conceptual thinking

Stress tolerance

Self-control

Self-development

Flexibility

Accurate self-assessment

Analytical thinking

Communication

Understanding others

Self-confidence

Professional and techical expertise

Intuitive thinking

Absorptive capacity

INNOVATION COMPETENCE Creative tension: n = 10, = 0.05

RESULTS OF FRIEDMAN TEST

α

Figure 7. Results of individual innovation competence self-evaluations.

and the last 16 the least significant. Unlike the creative tension results, the middlegroup of proactive vision is a group that remains undecided to which group it betterbelongs to, the most significant or the least significant.

Then the results of the organization’s innovation self-evaluations are presented(Fig. 8).

In order to give suggestions of the development needs according to the resultspresented above, both the results of the individual’s innovation competences andorganization’s support to those competences have to be compared parallelly. Thisis where the co-evolution of the two ontologies becomes handy. As both of theseontologies have been constructed together, most of the features and competences



0 5 10 15 20

Idea screening and evaluation

Empowerment

Situational constraints

Freedom

Idea generation

Seeking information

Openness and trust

Risk tolerance

Comprehending strategy

Challenge

Requisite variety

Communication

Organizational flexibility

Changeability

Idea documentation

Organization support development

Organization support learning

Absorptive capacity

Constructive feedback

Teamwork and collaboration

Stress management

Networking

ORGANIZATIONAL INNOVATION ENABLERS AND BARRIERS Creative tension:n = 10, = 0.05 α

RESULTS OF FRIEDMAN TEST

Figure 8. Results of organization’s innovation self-evaluations.

have a direct counterpart in the other ontology. Therefore, further analysis is madeby finding different combinations that can be discovered by comparing the statusof those pairs in the formed clusters. Below the following combinations of thepairs have been discovered: high–high, low–high, high–low, and low–low. Also theinterpretations of those combinations are enlightened.

1. In high–high combination, the creative tension is high on both individual inno-vation competence and organization’s innovation enablers. Table 2 can be inter-preted as those individual’s innovation competences and organization enablersthat need the most attention.

2. In low–high combination, the creative tension of individual innovation compe-tence is low, thus portraying the satisfaction of the current state of these compe-tences; whereas the creative tension of organization’s innovation enablers is high,thus desire the development of these organizational support features. Table 3 canbe interpreted that this organizational enabler “Teamwork and collaboration”needs attention when considering the development measures. However, people



Table 2. Results of test run with high–high combination.

Value Ranking

People want to develop within themselves

21,7 Absorptive capacity 117,8 Accurate self-assessment 816,05 Stress tolerance 1221,1 Professional and technical expertise 3

People want to be developed within organization

13,75 Absorptive capacity 514,9 Constructive feedback 415,7 Stress management 212,75 Organization support learning 6

Table 3. Results of test run with low–high combination.

Value Ranking

People do not see need for development within this competence

9 Teamwork and cooperation 22

People need for development within this organizational feature

15 Teamwork and collaboration 3

feel that their competence with “Teamwork and co-opearation” do not need thatmuch development in the future.

3. In high–low combination, the creative tension of individual innovation compe-tence is high, thus portraying desire of development; whereas the creative tensionof organization’s innovation enablers is low, thus portraying the satisfaction ofthe current state of the support from organization. Table 4 can be interpretedthat there are individual competences that people want to develop, howeverthose organizational enablers as support, are at good level for this developmentto happen.

4. In low–low combination, the creative tension of individual innovation compe-tence is high, thus portraying good level, and similarly the creative tension oforganization’s innovation enablers is low, thus portraying the satisfaction of thecurrent state of the support from organization. Table 5 can be interpreted thatwith these individual competences and also organizational enablers supportingthose competences are at good level. These competences and organizationalinnovation enablers are the stone base of this organization’s innovativeness.



Table 4. Results of Test Run with High–Low Combination.

Value Ranking

People want to develop within themselves

21,2 Intuitive thinking 218,1 Analytical thinking 716 Conceptual thinking 1318,3 Communication 616,8 Flexibility 916,7 Self-development 10

People do not see too much need for development within organization

9,5 Idea generation 189,5 Idea generation 189,5 Idea generation 1811,05 Communication 1111,2 Organizational flexibility 1012,15 Organization support development 7

Table 5. Results of Test Run with Low–Low Combination.

Value Ranking

People do not see too much need for development within themselves

10,7 Imagination 207,9 Divergent thinking 258,3 Achievement orientation 238,15 Trustworthiness 247,05 Independence 264,5 Risk orientation 27

People do not see too much need for development within organization

9,5 Idea generation 189,5 Idea generation 1810,3 Challenge 139,7 Openness and trust 169,4 Freedom 199,8 Risk tolerance 15

However, when considering this or any other organization’s development measures,the entire palette should be seen holistically. Partial optimization or overweight-ing single organizational enablers may cause more damage than good. Therefore,common sense and experience of the organization while making the development



measures can be recommended. Naturally also the current and future wanted statusof one competence or organizational enabler has to be considered, as the creativetension does not portray the entire situation.

Additionally, it should be stressed that this representation of competences ororganizational innovation enablers is not a truth, nor it is its intention to be. It ismerely a glimpse of one vision to one organization’s reality.

5. Conclusions

This chapter has sought to explore the linkage of individual innovation compe-tences and organizational innovation through the concepts of creative tension andproactive vision. The theoretical background of this study is in co-evolutionary cre-ation of MOOs (management object ontologies). These ontologies are the basis forbuilding up dynamic computer supported questionnaires for data collection. Thecollected individual data can then be gathered for comprehending the organizationalcollective vision of the future state together with future state, thus portraying thecreative tension and proactive vision.

The study suggests that building MOOs of individual innovation competenceand organizational innovation enablers and gathering that information via question-naires is the first step of collecting interesting and comparable data of the two sidesof innovation: the individual and organizational. This new way of collecting inno-vation data may bring interesting information of innovations in the organizationsin the future. When this data collection is then moved, expanded from individualand organizational level to national and even international level, the true nature ofinnovation may be revealed — at least from one very essential point of view: thosepeople working in the organizations.

In summary, we suggest MOO when combined with data collection is an effec-tive way to approach the complex concept of innovation within organizations inthe first place. Furthermore, finding answers to the initial question of how to boostinnovation culture and innovators remains in the future, but this approach gives atool to gather more valuable information on the essence of innovation competenceand organizational innovation.

The approach described in this chapter has implications on the management.The abstract concepts of innovation culture and innovation competence becomemanageable, which suggests that organizations should be able to get better “inno-vation results.”

Acknowledgements

Finnish Funding Agency for Technology, i.e., TEKES has been the main financingbody for this research. We refer to the Flexi project E!3674 ITEA2 Flexi — AddedValue Ontology, decision Tekes 40176/07.



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Biographical Notes

Andrea Bikfalvi has a PhD in Business Administration and she conducts teach-ing and research activities in the Department of Business Administration andProduct Design at the University of Girona, Spain. Her research interest focuseson technological and organizational innovation, new technologies in businesscontexts, academia-business relationships and new venture creation, as wellas large-scale surveys. Since her incorporation, she undertook teaching activi-ties and participated on various research projects. Some of the projects referto the topic of international surveys, university spin-offs; other issues concerninnovation in education and teaching, networks of innovation, and research inteaching.

Jari Jussila is a PhD candidate at TUT, Finland. He holds an MSc (IndustrialManagement and Engineering), and his research interest is focused on knowledgemanagement. His main experience is derived from information systems projects.Since 2007 he has been working as a managing consultant at Yoso Services Oy.

Anu Suominen is a PhD candidate at Tampere University of Technology (TUT)in Finland. She holds an MSc (Industrial Management and Engineering), and herresearch interest is towards leadership and management: from strategy, knowledge,and innovation point of views. Her prior working experience is from logistics,particularly operational exports in metal and information network industries. Since2007 she has been working as a researcher at TUT.

Jussi Kantola works as an associate professor in the world’s first knowledge serviceengineering department at KAIST (Korea Advanced Institute of Science and Tech-nology) in Korea. He is an adjunct professor at Tampere University of Technologyin the Department of Industrial Management and Engineering in Pori, Finland.His research and teaching interests currently include application of ontologies, e-learning and soft-computing. He received his first PhD degree at the University ofLouisville in the Department of Industrial Engineering in USA in 1998. He receivedhis second PhD degree at Tampere University of Technology in the Department ofIndustrial Management and Engineering in Finland in 2006. Earlier he has workedas an IT consultant in USA and business and process consultant forABB in Finland.

Professor Hannu Vanharanta, 1949, began his professional career in 1973 asa Technical assistant at the Turku office of the Finnish Ministry of Trade andIndustry. In 1975–1992, he worked for Finnish international engineering compa-nies, i.e., Jaakko Poyry, Rintekno, and Ekono as process engineer, section man-ager, and leading consultant. His doctoral thesis was approved in 1995. In 1995–1996, he was a professor in Business Economics in the University of Joensuu. In1996–1998, he served as a Purchasing and Supply Management professor in the



Lappeenranta University of Technology. Since 1998 he has been a professor inIndustrial Management and Engineering in Tampere University of Technology atPori. The research interests are: human resource management, knowledge manage-ment, strategic management, financial analysis, e-business, and decision supportsystems.

How to Boost Innovation Culture and Innovators?

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