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This is a manuscript version of:

Diagnosing organizational innovation: Measuring the capacity for innovation. Creativity Research Journal, 25, 388-396. If you cite it please list this version.

Diagnosing organizational innovation: Measuring the capacity for

innovation

David H CropleyDefense and Systems InstituteUniversity of South Australia

Australia

Arthur J CropleyUniversity of Hamburg

Germany

Belinda A ChieraSchool of Mathematics and Statistics

University of South AustraliaAustralia

James C KaufmanLearning Research Institute

California State University, San BernardinoUnited States of America

Corresponding author:David Cropley, Defence and Systems Institute, University of South Australia, Mawson Lakes Campus, SA 5095, AUSTRALIA.Email: david.cropley@unisa.edu.au

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Diagnosing organizational innovation: Measuring the capacity for

innovation

Abstract

Organizational innovation involves reconciling many

contradictions or paradoxes: Dividing the process of innovation

into phases ranging from Activation to Validation and examining

each phase in terms of the six Ps of creativity offer a framework

for making sense of these contradictions. The Innovation Phase

Assessment Instrument (IPAI) was designed to assess organizations

according to such an approach. The scale was administered to 454

student volunteers and an analysis of their responses indicated

that the IPAI is highly reliable and has substantial construct

validity. At a practical level it can be used for assessing the

strengths/weaknesses of organization in a differentiated way and

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for making recommendations for improving their capacity for

innovation. It is also a source of research questions for

examining creativity and innovation in an organizational context.

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Diagnosing organizational innovation: Assessing the

capacity for innovation

In an earlier article in this journal Cropley and Cropley (2012)

presented a psychological taxonomy of organizational innovation

aimed at casting light on the question of how to “shape

production, business, marketing, or finance environments in ways

that promote innovation” (p.29). The key issue attacked by

Cropley and Cropley was solving the paradoxes (e.g., Miron, Erez,

& Naveh (2004) of organizational creativity, which involve what

Bledow et al (2009a, p. 306) called “conflicting demands” and

require “conflicting activities” in the process of innovation.

Put simply: What is good for innovation at one point in the

process may be bad for it at another.

These paradoxes involve “tensions” (Lewis, Welsh, Dehler, &

Green, 2002), and “dilemmas” (Benner & Tushman, 2003). Haner

(2005) gave a good example of a paradox: Research on groups and

innovation has shown that innovation requires “simultaneous

agreement and disagreement” (p. 291) among the members of the

group—consensus and yet absence of consensus. Looking at the

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individual, Hulsheger, Anderson, and Salgado (2009) gave another

example: the need both to do things your own way and yet also

rigorously implement other people’s ideas. Maital and Seshadri

(2007, p. 27) summed up the paradox as “the need for free,

unfettered creativity, together with the need for focused,

systematic discipline – and the overriding imperative to make

these two qualities … co-exist.”

Organizational ingenuity – the ability to make it possible

for unfettered and focused, systematic activities to co-exist –

is only possible when individuals and organizations have a map

that identifies where the obstacles lie and when they are likely

to occur. Haner (2005, p. 297) thus called for research on

“principles according to which organizational innovation … can

be conceptualized” [emphasis added]. In the earlier article Cropley

and Cropley (2012) presented such principles: These involved a

theoretical conceptualization of organizational innovation based

on a division of the innovation process into seven phases

(Preparation, Activation, Generation, Illumination,

Verification, Communication and Validation), and an analysis of

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each phase in terms of six “dimensions” (Process, Motivation,

Personal Properties, Feelings, Product, Press). The Phases are

based on an expansion of Wallas’s (1926) stages of creativity to

include an initial phase of gaining familiarity with the area in

which innovation is required (Preparation), and two phases in

which products are presented to clients, customers, investors,

and the like, and these people react positively or negatively

(Communication, Validation).1 The “Dimensions” are based on the

now familiar Four Ps model of creativity (Person, Process,

Product and Press), with person further differentiated to

encompass Motivation, Personal Properties and Feelings), thus

yielding six Ps (or Dimensions as they are called here).

Assessing innovation potential

Aiman-Smith et al (2005) turned to the issue of assessing

innovation potential. They presented an instrument based on a

range of factors, and backed up by empirical evidence of

1 Bledow et al (2009a, p. 305) stressed the importance in organizational innovation of not merely generating novelty (creativity), but of going further and implementing it in practice as well. The theoretical derivation of the seven phase/six dimension model was presented in detail in Cropley and Cropley (2012), and will not be repeated here.

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satisfactory reliability and validity. However, this tool

remained anchored in a theoretical framework which fails to

address the changing pattern of freedom and constraint that

governs the innovation process as it unfolds, and is

encapsulated in the idea of “paradoxes”. By analyzing the Phases

in terms of the six Ps, Cropley and Cropley (2012) moved the

focus of the discussion away from properties of the organization

itself such as physical structure of work spaces, institutional

norms, communication chains, rewards systems or openness of

decision-making to the micro level of ideation and personal

properties of the individual working in an organization and the

interactions among properties of the individual, the kind of

product produced, and the press from management. At the end of

their earlier article Cropley and Cropley called for a

“diagnostic instrument” capable of offering a “more formal and

structured analysis” (p. 39) based on their approach, and closed

by indicating that such an instrument was in preparation. The

present article takes the next step by introducing this

instrument and providing empirical evidence of its reliability

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and validity.

The Innovation Phase Assessment Instrument (IPAI)

Cropley and Cropley (2012) argued that the Dimensions (such as,

for instance, Process, Motivation or Feelings) are not unitary

traits that are either present or absent (e.g., motivation is

not either present or absent), but that they have various levels

or kinds. For ease of understanding these can be stated as

dichotomies: Thus, the Process of thinking may be convergent or

divergent, Motivation may be proactive or reactive, and Feelings

may be generative or conserving, to give several examples. The

crucial point is that both kinds of Process (divergent and

convergent thinking), both kinds of Motivation (proactive and

reactive), and both kinds of Feelings (generative and

conserving) are important for innovation. However, they are

important in different phases of the overall process of innovation.

For instance, the Process of divergent thinking may be favorable

for innovation in the Phase of Generation, but unfavorable in

the Phase of Verification. The crucial issue is that each

particular combination of a specific Phase and a specific

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Dimension requires a particular form of the Dimension (e.g., in

the phase of Generation, the kind of Process required is

divergent thinking, whereas in the Phase of Verification the

kind of Process required is convergent thinking).

To focus on the specific combinations of Phase and

Dimension, each particular combination is referred to here as a

“node”. Thus Process (thinking) during let us say Generation

defines a node (referred to as Generation/Process), as does

Motivation during Verification (defining the node

Verification/Motivation), and so on. This yields 6 X 7 = 42

nodes, each node defined by the conjunction of a Phase and a

Dimension. In the node Generation/Process, for instance,

divergent thinking is favorable for innovation, while in the

node Verification/Motivation proactive motivation is favorable,

whereas in the node Communication/Process convergent thinking is

favorable and in the node Communication/Motivation reactive

motivation is what is needed. Cropley and Cropley (2012, p. 38)

listed the crucial pole of each particular Dimension (such as

proactive versus reactive motivation) for all 42 nodes in a

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table, which is reproduced here in Table 1.

--------------------------------------------------

Insert Table 1 about here

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An innovative organization needs to foster let us say

divergent thinking in some nodes, but convergent thinking in

others. It should enable its members to combine “tendencies of

thought and action that in most people are segregated”

(Csikszentmihalyi, 1996, p. 47), to oscillate, as Martindale

(1989, p. 228) put it, or to operate in “alternating psycho-

behavioral waves” (Koberg & Bagnall,1991, p. 38), through what

Bledow et al (2009b, p. 365) called “dynamic shifting.” The

purpose of the IPAI is to diagnose in which nodes an

organization offers favorable conditions for innovation, in

which ones conditions are unfavorable, and to offer insights

into the conditions in the organization which are favorable or

unfavorable.

Items of the IPAI

The instrument contains four items for each of the 42 nodes

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represented by the intersection of a Phase and a Dimension. This

results in a total of 168 items. Table 2 gives a sample item from

the scale for each of the six dimensions in three of the seven

phases: Preparation, Generation and Validation.

----------------------------------------------

Insert Table 2 about here

----------------------------------------------

A listing of the full 168 items of the scale would take up

an excessive amount of space here. For this reason, Table 2

contains only examples. However, the complete scale can be

obtained from the corresponding author. Each item consists of a

dichotomous statement. All statements extend the common stem: “In

this organization…” Respondents are asked to indicate whether a

statement is true or untrue about their organization in the usual

course of events. For example, the items for the node

Activation/Process are:

In this organization, staff help to define the goals of

their work;

In this organization, within broad guidelines, staff decide

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for themselves what they will focus on;

In this organization right from the beginning managers state

clear criteria for recognizing solutions;

In this organization staff do not analyze their own work.

The four items relating to any particular node are not clustered

in a single block, but are scattered randomly throughout the 168-

item scale, in order to reduce the likelihood of raters

recognizing that certain items belong together and answering

accordingly. In some cases items are phrased positively (e.g.,

“Staff produce lots of ideas”), in others negatively (e.g.,

“Products are not released unless we are very confident that they

will proceed”).

Each item has a response that, according to the model

(Cropley & Cropley, 2012.p. 38), is ideal for a particular node.

The ideal response describes a particular combination of Phase

and Dimension which is optimal for innovation. For the purposes

of the psychometric analysis which follows, these ideal responses

are referred to as “standard” answers. The standard answer is

sometimes True (e.g., “Staff are open to criticism from

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outsiders”), and sometimes False (e.g., “Staff feel overwhelmed by

too many ideas”). For example in the case of the node

Generation/Motivation one item is, “In this organization staff

prefer unambiguous information.” According to the Cropley/Cropley

model, high tolerance for ambiguity is favorable in the

Generation phase. Therefore the standard answer to this statement

(i.e. the one favorable to innovation) is False. The right-hand

column of Table 2 indicates the standard answer for the sample

items in the table.

Administering and scoring the scale

The scale is suitable for administration to individuals in a

group setting. Respondents fill out the scale by answering True

or False to each item. They are asked to respond in terms of their

own understanding of what the item means, not to agonize about

what the test constructors might have meant. They are reminded

that they are describing their own organization as they perceive

it as actually being, not giving their opinions about what a work

environment ought to be like, or the way they would like their

organization to be. Their task is also to describe what is typical

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of the organization they are assessing, even if there are

occasional deviations or special situations where things are

sometimes different. They are asked to respond according to what

comes into their minds immediately when they read an item, not to

think long and hard about, for instance, the exact percentage of

the time their response actually applies to their organization,

or to check back over their responses to earlier items. The

responses are then scored by checking them against a key which

specifies the standard response for that item. A response that

corresponds to the defined standard response receives one point;

a response that differs from the standard response receives zero

points.

Individual responses are aggregated to yield a score for the

organization out of 168. In addition, scores can be calculated

for each of the 42 nodes by summing the four items for each

particular node. They can also be aggregated for each Phase by

adding the scores across the six Dimensions relating to that

Phase (24 items for each Phase) or for each Dimension by

aggregating scores across the 7 Phases for that Dimension (28

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items for each Dimension).

Interpreting scores

Our interest here is not anointing the more ingenious

organization, but diagnosing an organization’s strengths and

weaknesses and making suggestions for remedial action. The key to

more specific results is to identify areas of strength and

weakness at the level of Phases, or Dimensions, or in specific

nodes. For instance, examining individual Phases, an organization

might be high on Preparation, Verification, Communication and

Validation, but low on Activation, Generation and Illumination.

Such an organization would be good at defining tasks, selecting

promising solutions, presenting solutions to customers, consumers

and the like, and assessing the effectiveness of solutions or

products, but weak at encouraging staff to build up wide-ranging

knowledge of a field, identify and seek to solve problems, see

alternative approaches to finding a solution, and so on. Such a

company would be more likely to continue producing standard

products in an efficient way than to innovate. The particular

value offered by the IPAI is the ability to examine an

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organization’s capacity for innovation at the level of Phases,

Dimensions and individual nodes.

A major preliminary issue in developing and applying the

IPAI is establishing its psychometric goodness. The data

presented below are concerned with this issue.

Method

To examine the technical properties of the IPAI (e.g.,

reliability and validity) the instrument was administered to a

sample of 454 college students from a public state university in

Southern California who took part in the study online,

voluntarily, but for extra credit. The sample included 372

participants who identified as female (81.9%), 44 who identified

as male (9.7%), and a further 38 (8.4%) who chose to give no

answer for this demographic. The most common age group was 18-24

years, (67.8%) followed by 25-29 years (10.7%). The demographic

breakdown of the sample was as follows: 200 Hispanic American

(44.1%); 130 European American/Caucasian (28.6%); 35 African

American (7.7%); 16 Asian American (3.5%); 34 of other

ethnicities (7.5%) and 39 who chose not to identify their

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ethnicity (8.6%).

It might seem that this sample is inappropriate for the

purposes of the present study, since it does not consist of

people with extensive experience within organizations. However,

the purpose of the research reported here is not to investigate

the nature of organizations, nor to show that the dimensions of

the IPAI really are present in organizations, nor even to

demonstrate that the respondents’ image of organizations is

accurate. The purpose of the study is to show that relatively

literate people have some understanding of what the IPAI items

mean and can respond systematically, in that they do not answer

randomly or simply by guessing, that this understanding is stable

(reliability), and that the items correlate with each other in a

systematic way which corresponds with the theoretical structure

of the scale (construct validity). A sample involving in essence

non-experts (people with limited experience of working in

organizations) also offers the advantage that such people are

unlikely to already be acclimatized/desensitized to nuances of

organizational workplace culture and are thus likely to be better

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placed to distinguish between the Phases and Dimensions explored

in this study. The sample covers differences in gender,

ethnicity, race and age, so that it studies a diverse group of

individuals. Research with a sample of people with intensive

experience in a particular organization is the next step.

Procedure

Participants were directed to a website where the scale was

hosted online. They were asked to rate their beliefs about how

creativity and innovation are perceived at their institution

(their University) on the 168 items of the IPAI using a

dichotomous response format (true-false). Participants were also

asked to complete a basic demographic questionnaire, debriefed,

and given extra credit for their participation when applicable.

Missing data were removed using listwise deletion. Before

analysis, the normality of the data was examined: visual

inspection of histograms of the data indicated no severe

departures from normality, further supported by skewness and

kurtosis statistics, all of which were within acceptable limits.

As there were no statistically serious violations of normality,

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the application of parametric statistics was deemed appropriate.

RESULTS

Reliability

The reliability (Cronbach’s alpha) of the 168-item scale was

.96, with the alpha for the 42-item scale defined by the 42 nodes

also at .96. There was no node whose omission led to any

noticeable improvement in overall reliability, so that all 42

nodes made a positive contribution to the reliability of the 42-

item scale. When scores were pooled across the seven Phases to

yield scores on the six Dimensions, alphas ranged from .74

to .87, with a median of .78.

The minimum and maximum alphas for each Dimension were also

determined; for instance removal of the node Generation/Process

resulted in the lowest reliability within the Process dimension

(0.75), whereas removal of the node Illumination/Process produced

an alpha (0.80) in the vicinity of the overall Process alpha.

Similarly, pooling scores across the six Dimensions to yield

scores for the seven Phases produced alphas ranging from .74

to .81 (median alpha = .79) with the reliability within each

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Phase also calculated to produce the corresponding minimum and

maximum alphas. The alpha coefficients for the seven Phases and

six Dimensions are shown in Table 3.

---------------------------------------------- Insert Table 3about here ----------------------------------------------

Consistent with criteria specified by Nunnally and Bernstein

(1994), or George and Mallery (2003), these coefficients indicate

internal consistency levels that are acceptable, if not good.

Focusing on nodes, the inter-node correlations were

predominantly between 0.20 and 0.80, which is considered ideal

(Nunnally & Bernstein, 1994). There were a small number of

correlations less than 0.20, within either the same Dimension or

the same Phase, but no single node demonstrated low correlations

with every other node, suggesting retention of all nodes for the

ensuing analysis. There were no correlations exceeding 0.80

suggesting that redundancy in the scale was also not an issue.

Moreover, the correlation values themselves were all positive,

suggesting that the 42 nodes measure the same underlying

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characteristic, thereby further justifying the retention of all

42 nodes.

To determine the reliability of each node, an alternative to

Cronbach’s alpha was sought as there were only four items per

node in the original questionnaire. A type of intra-class

reliability specifically for binary data for more than 2 raters

is Fleiss’s Kappa (Fleiss, 1981). For each node, the Kappa

statistic K was computed using the 4 items for that node. The

Kappa statistics for each node were low (< 0.2), but testing the

hypothesis H0: K = 0 versus H1: K ≠ 0 with the z-test yielded p-

values < 0.001 in all cases, suggesting there was agreement

within each node not due to chance. However as there are a

small number of items available for each node, these results must

be interpreted cautiously. Following Di Iorio (2005), a selection

of scores was computed in support of Classical Test Theory,

namely that true scores are not correlated with error scores. For

all 168 items, reliability was determined by examining the

correlation between the Standard Answer with the actual response

to a given item as well as the error scores, where the errors

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scores were coded as 1 if the response matched and 0 if it did

not. The results indicated:

The true scores were uncorrelated;

The correlations among the error scores were negligible;

The standard answer correlated highly with the observed

answers; and

There were high correlations among the observed answers for

each group of 4 items that comprise a given node.

Empirical versus theoretical item means

Of the 168 test items, the “correct” response for 96

involved answering True and 72 involved answering False. Thus, a

person who randomly answered “True,” to every item would achieve

a score of 92, yielding an average item score of 0.5714. In fact,

the 454 item means for the entire group of respondents were in

the neighborhood of the “standard” mean of 0.5714. The

difference between the mean item score for each respondent and

the standard mean was approximately 0 in most cases. Only around

10% (48 responses out of 454) was the difference > |0.3|

suggesting that random errors in the test have largely been

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removed. The correlations between the error scores of

respondents (deviation of the respondent’s mean item score from

the standard mean) showed some significant correlations –

suggesting that there was still some randomness in some

respondent’s answers. Despite this, the correlations between the

standard answers and participants’ answers were predominantly

statistically non-zero, suggesting that responses were

overwhelmingly non-random.

Differentiation

The Innovation Phase Assessment Instrument (IPAI) is based

on a theoretical framework which pre-supposes that the scores

obtained on any single node will not be too highly predictable

from those of any other node. Each node seeks to measure a

distinct and unique intersection of the phase and dimension

characteristics that contribute to the overall process of

innovation. To examine this hypothesis, two tests were performed:

computation of the determinant of the covariance of the data

matrix, and computation of its rank. A non-zero determinant and a

matrix of full rank would indicate that no node was a linear

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combination of any other node.

For the 42 nodes, the determinant was 2.78e-09 (i.e. small,

but non-zero) and the data matrix was of full rank (rank = 42)

confirming that no node was a linear combination of any other.

Indeed, the determinant for all 168 items was also non-zero, and

the data matrix was of full rank (168), indicating that scores on

the 168 items could also be considered distinct from one another.

In the same way that individual nodes (and items) should,

according to the theoretical model, be distinct, the seven Phases

(Preparation through to Validation) and six Dimensions (Process

through Press) should also yield non-zero determinants and data

matrices of full rank when data are combined. In fact all

determinants were non-zero and the matrices were all of full

rank, indicating that the aggregated scores obtained on the IPAI

for any single dimension or phase can be considered distinct from

each other.

Construct Validity

The most common way of interpreting the concepts measured by

a questionnaire or rating scale is factor analysis. In the

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present case, the 168-items were designed to measure 42 separate

nodes, so that the theoretical factor structure of the scale

involved 42 factors. However, this is a very large number of

factors for factor analysis. Indeed, applying a well-used

heuristic of testing the determinant of the correlation matrix

against an accepted cut-off of 1e05 (Field, 2009), it was found

the determinant was far below this value, suggesting the presence

of multi-collinearity in the data, thereby rendering factor

analysis unsuitable. Consequently, further analysis of the

interaction between Phase and Dimension was based on a two-way

repeated measures analysis of variance, one factor in the ANOVA

being Phase (with seven levels) and the other Dimension (with six

levels).

Two-way ANOVA (Within-Subjects Effects)

An analysis of Within-Subjects Effects and the result of

Mauchly’s test showed that the assumption of sphericity had been

violated for both the main effects of Phase, 2 (20) = 96.11, p =

0.00 and Dimension, 2 (14) = 49.67, p = 0.00. Consequently, the

degrees of freedom for this study were corrected using

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Greenhouse-Geisser estimates of sphericity (= 0.92 for the main

effect of Phase and = 0.96 for the main effect of Dimension)

(Field, 2009). All effects were significant at p < 0.05 and the

effect size r was calculated for all analyses. Specifically,

there was a significant main effect for Phase, F (5.5, 2512.65) =

77.58, r = 0.92 and Dimension, F (4.79, 2170.21) = 160.21, r =

0.92.

These results indicated that there is a reliable difference

between each of the Phases and the Dimensions in the instrument –

that is there were at least two distinct levels within the

construct Phase and within the construct Dimension. Further post-

hoc statistical analysis indicated which of the phases and

dimensions were distinct. Similarly, an analysis of Within-

Subjects Effects for the interaction between Phase and Dimension

F (22.34, 10119.94) = 105.84 (r = 0.98) indicated that there was

a statistically significant interaction between the two (p

< .05), making it feasible to analyze these two constructs

together. This result was further supported by the outcome of the

Chi-square test for independence, for which 2 (5, n = 36874) =

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1148.65, p = 0.00, Cramer’s V = 0.079, indicating that Phase and

Dimension were not independent.

Two-way ANOVA (Within-Subjects Contrasts)

Testing of within-subject contrasts yielded F-values

indicating that all levels were significantly distinct from each

other at the p < .01 level and confirming the presence of the

hypothesized seven distinct Phases. Testing of within-subject

contrasts for Dimension, however, indicated that a single result

(Product and Press, F (1,453 = 0.71), r=0.29), was non-

significant, the remainder being significant at the p < .01

level. Thus, the dimensions Product and Press (p = .401) were

not differentiated from each other by this group of respondents.

In addition, testing of within-subject contrasts between

Phase and Dimension indicated non-significant results for two

small blocks of nodes, suggesting that this group of respondents

also did not differentiate these nodes from each other. These

blocks are:

a. Illumination/Process + Illumination/Motivation +

Verification/Process + Verification/Motivation;

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b. Verification/Personal properties + Verification/Feelings

+ Communication/Person + Communication/Feelings.

It is, perhaps, noteworthy that respondents had particular

difficulty differentiating the Phase of Verification into

specific components in terms of the ideational processes,

personal properties, motivation and feelings associated with it.

Two-way ANOVA (Pairwise Comparisons)

In relation to Phases, pairwise comparisons indicated that

the instrument had difficulty in distinguishing (p > .05) between

four pairs (Preparation and Generation; Activation and

Verification; Activation and Communication; Generation and

Communication) from a total of 21 possible pairwise comparisons

of Phases. In relation to Dimensions, results of pairwise

comparisons indicated that the instrument had difficulty in

distinguishing (p > .05) between three pairs (Personal Properties

and Product; Personal Properties and Press; Product and Press)

from a total of 15 possible pairwise comparisons of Dimension.

This result shows only that this particular group of participants

could not distinguish between the indicated pairs of Phases or

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Dimensions using this instrument. This difficulty in

distinguishing between, for example, Product and Press may be due

to participants’ inexperience in organizations: They may have

seen, let us say, pressure from a manager to produce a quick

result as indistinguishable from formulating or inevitably

leading to a conventional product. This does not mean that there

is no statistical foundation for having these different Phases or

Dimensions (as might be verified by a Factor Analysis).

DISCUSSION

The high reliability of the participants’ responses shows that

they answered the items in a systematic and rational way, and

not, for instance, by guessing or answering randomly. They could

make sense of the items and understood the system for responding

to them. The 168 items were also seen by participants as

involving 168 distinguishable questions, not simply repetitions

of a smaller number of highly similar questions. Content analysis

of the matrices of raw scores, node scores, and Phase or

Dimension scores showed that participants responded to the items

largely as the theoretical structure of the scale intended: By

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and large they distinguished 42 blocks of related items (the

nodes), 7 broader blocks of items relating to Phase and 6 broader

blocks of items relating to Dimensions. This “factor analysis

through the back door” suggests that this first approximation of

the final scale is approaching the theoretical structure in terms

of which it was designed.

Participants in the study found differentiation of

Verification into separate components based on psychological

dimensions such as Process and Personal feelings difficult. In

particular, the node Verification/Personal Properties was a

matter of concern: The Verification Phase was, in fact, more

reliable without this node, while Verification/Personal

Properties was one of the nodes which could not be distinguished

from other Verification nodes through pairwise contrasts. It

seems that items more sharply capturing the differences among

Verification nodes are needed. This may be partly solvable

through improved wording of the relevant items, although

clarification of the underlying concepts may also be needed.

Equally, this weakness may be addressed by improving the wording

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of items in neighboring nodes (e.g., Illumination/Process and

Illumination/Motivation). The ability of the instrument to

distinguish more clearly among Verification nodes may be improved

by more distinct contrasts with these neighboring nodes. Much the

same can be said of the scale's weakness in distinguishing

between Product and Press: The scale did not capture the

difference between the nature of a product (e.g., novel vs.

correct or elegant vs. effective) and the management behavior

that supports the one or other kind of product.

In a purely psychometric sense, the scale has made a good

start on the task of identifying and measuring a set of factors

in organizational environments that are understandable to

respondents and really do capture a differentiated picture of the

organizational environment. In addition to technical improvements

such as sharper differentiation between Product and Press or

among the nodes associated with Verification, a major practical

task is demonstrating the predictive validity of the scale: Do

the components captured by the scale relate to actual differences

in organizational performance? Do different profiles of strengths

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and weaknesses identified by the scale predict differences in

practical outcomes such as successful development of new products

or processes, ability to recruit and hold particularly innovative

staff, or even simply the bottom line?

Two kinds of use for the scale presented here and the model

on which it is based are apparent: The first involves its

application as a source of research questions. It must be

admitted that the specific configurations listed in the cells of

Table 1 as “optimal” are largely intuitive in origin, so that the

first research task would be to provide better evidence of the

accuracy of these contents. A number of further research

questions arise: How does experience in one Phase affect behavior

in a later one? When is the right time to switch into a new

Phase? How could an individual, a group or a manager recognize

that it is time to switch? What kind of training would be needed

to teach people how to see the need to switch and to do it? It is

known, for instance (Rietzschel, Nijstad, & Stroebe, 2010) that

even problem-solving groups which have successfully generated

novel ideas not infrequently have difficulty picking the best

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ideas from among the ones they have just generated. Using the

terminology presented here, the problem can be described as

involving switching from Generation to Illumination and

Verification, and

such groups would be “diagnosed” as experiencing difficulty in

switching from divergent to convergent thinking, or from a

freedom orientation to a necessity orientation. Special training

may well be needed to learn to make this switch.

The model also offers promise of application for assessing

the relative strength/weakness of the various nodes in a

particular organization. An organization might be good at

identifying problems in existing circumstances, but poor at

building up staff members' willingness or ability to produce

novel ideas for dealing with such problems. It is also possible

to focus on Phases: For instance an organization might be good at

evaluating and communicating novel ideas to customers, but poor

at promoting conditions leading to the generation of such ideas.

Finally, the instrument provides a more person-centered

vocabulary for discussing what is actually happening at any stage

34

of the innovation process. The possibility of saying more

precisely what is going on at a specific point in the innovation

process, what is needed, what should be changed, and so on, would

be a considerable help in improving actions during the innovation

process.

35

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39

Table 1: Optimal poles of the six dimensions in the Phases of innovation

DimensionPhase

Process Personalmotivati

on

Personal

properties

Personal

feelings

Product

Press

Preparation Convergent

thinking

MixedMotivation

Adaptivepersonal

ity

Conserving

feelings

Routineproduct

Freedom-oriented

Activation Divergent

thinking

ProactiveMotivation

Innovative

personality

Generative

feelings

Radicalproduct

Freedom-oriented

Generation Divergent

thinking

ProactiveMotivation

Innovative

personality

Generative

feelings

Radicalproduct

s

Freedom-oriented

Illumination Divergent

thinking

ProactiveMotivation

Innovative

personality

Generative

feelings

Radicalproduct

Freedom-oriented

Verification Convergent

thinking

MixedMotivation

Adaptivepersonal

ity

Conserving

feelings

Routineproduct

Necessity-oriented

Communication

Convergent

thinking

ReactiveMotivation

Adaptivepersonal

ity

Conserving

feelings

Routineproduct

Necessity-oriented

Validation Convergent

thinking

ReactiveMotivation

Adaptivepersonal

ity

Conserving

feelings

Routineproduct

Necessity-oriented

40

Table 2: Examples of items for the stages of Preparation, Generation and Validation

Phase Sample Item (“In this organization…”) StandardAnswer

Preparation

Before a new project is undertaken, staff focus exclusively on their own jobs.

False

Staff will work hard for the satisfaction of doing a good job.

True

Staff are satisfied with the way things are done.

False

Staff value change positively. True

Challenges to old perspective rarely emerge.

False

We have clearly defined staff roles. False

Generation

Staff often link unrelated disciplines. True

Staff enjoy the challenge of contradictory ideas.

True

Staff are anxious about making mistakes. False

Staff feel overwhelmed by too many ideas.

False

Staff produce lots of ideas. True

Staff are encouraged to find solutions quickly.

False

Staff protect the ideas they produce from external scrutiny.

False

41

Validation

Staff feel a need for feedback from the external world.

True

Staff are open to criticism from outsiders.

True

Staff feel under attack when others judge their work.

False

Products are not released unless we are very confident that they will succeed.

False

Wild ideas are supported if they solve the problem.

True

42

Table 3: Reliability scores and Scale Differentiation for Dimensions and Phases

DimensionCronbachAlpha

MinimumCronbach if

itemdeleted

MaximumCronbach ifitem deleted

Determinant

Rank

Process 0.80 0.75Gen/Proc

0.80Ill/Proc

0.2410 7

Motivation 0.85 0.82Ver/Mot

0.85Ill/Mot

0.1547 7

PersonalProperties

0.74 0.70Act/Per

0.72Ill/Per;Val/Per

0.3798 7

Feelings 0.87 0.84Act/Feel

0.85Com/Feel

0.1625 7

Product 0.77 0.72Com/Prod

0.75Act/Prod;Val/

Prod

0.2576 7

Press 0.78 0.71Act/Press

0.77Prep/Press

0.1715 7

PhasePreparation 0.75 0.67

Prep/Mot0.75

Prep/Press0.5342 6

Activation 0.81 0.76Act/Pre

0.81Act/Prod

0.2920 6

Generation 0.81 0.76Gen/Proc

0.81Gen/Press

0.1969 6

Illumination 0.74 0.67Ill/Feel

0.72Ill/Proc

0.3428 6

Verification 0.79 0.74Ver/Mot

0.80Ver/Per

0.5210 6

Communication

0.80 0.74Com/Prod

0.79Com/Per

0.3059 6

Validation 0.78 0.72 0.78 0.1449 6

43

Val/Feel Val/Press

Note: Node names (e.g., Cognition/Process) are shortened in this table, e.g., Generation/Process is abbreviated to Gen/Proc.