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A cross-cultural examination of the Kirton Adaption-Innovation Inventory
Person. indirid. Di#J Vol. 22. No. I, pp. 55-60, 1997 Copyright Q 1997 Elsevier Science Ltd
Pergamon
Printed in Great Britain. All rights reserved
SO191-8869(96)00178-X
0191-8869/97
$17.00+0.00
A CROSS-CULTURAL EXAMINATION OF THE KIRTON ADAPTION-INNOVATION INVENTORY Robert Loo’* and Kunio Shiomi’ ‘Faculty of Management, University of Lethbridge, Lethbridge, Alberta, Canada TIK 3M4 and ‘Department of Psychology, Hyogo University of Teacher Education, Shimokume, Yashiro-Cho, Hyogo 673-14, Japan ( Receiwd
22 March 1996)
Summary-This study examined the factor structure and other psychometric properties of the Kirton Adaption-Innovation Inventory (KAI) with a sample of Canadian (N = 144) and two samples of Japanese undergraduates (N = 144, N = 204). The three-factor solution generally supported Kirton’s three subscales (Originality, Rule/Group Conformity, Efficiency) but accounted for only 23335% of the variance. There was some support for Kirton’s view that females are more adaptive than males. Cross-national comparisons of KAI scores and factors were made between the present samples and those reported in the literature from the U.S.A., Italy, and Great Britain among other countries. These comparisons showed moderate to strong support for Kirton’s three-factor structure and the utility of the inventory. Several recommendations are presented to improve the psychometric properties of the KAI and the usefulness of studies in this area. Copyright 8 1997 Elsevier Science Ltd.
INTRODUCTION Kirton’s (e.g. 1976, 1980, 1989) theory ofcognitive style addresses individual differences in creativity, problem-solving approach, and decision-making approach along a continuum ranging from ‘adaption’ to ‘innovation’. Individuals at extremes of this continuum show marked style differences such that adaptors have a preference for making decisions and improvements within existing methods and systems whereas innovators are more likely to ignore existing conventions and seek novel solutions or directions. Not surprisingly, innovators prefer less structured situations and are more willing to take risks than are adaptors. Kirton (1977) developed a 33-item self-report inventory to measure individual differences on this cognitive-style continuum. The first item is an unscored warm-up item whilst the other 32 items in the Kirton Adaption-Innovation Inventory (KAI) reflect three subscales: Originality (13 items) describes the creative person; Efficiency (nine items) describes the Weberian precise, reliable and disciplined person; and Rule/Group Conformity (10 items) describes the rule-following person who fits in well in bureaucracies. The response scale consists of a 17-dot line, which converts to a fivepoint scale ranging from “very easy” to “very hard”. The possible range of scores is from 32 (extreme adaptor) to 160 (extreme innovator) with a theoretical mean of 96. Most researchers report only overall scores whilst some researchers report both the overall as well as the three subscale scores. This theory and inventory has been widely-used for a variety of purposes and used in many different occupational, educational, and cultural settings. For example, Foxall (1990) has conducted many studies using the KAI including the examination of gender differences among MBA students in three countries. Fleenor and Taylor (1994) recently examined the construct and concurrent validity of the KAI using a large, heterogeneous sample of managers. Some psychometric studies have also added support to Kirton’s (1977) early inventory development. For example, Keller and Holland’s (1978) early validation study using a sample of professional employees from three research and development organizations supported Kirton’s three-factor model. Similarly, Goldsmith (1985) found support for the three-factor structure of the KAI using a sample of urban American adults as did Beene and Zelhart (1988) with a sample of American college students and university administrators. *To whom all correspondence
should be addressed. 55
56
Robert Loo and Kunio Shiomi Table I. KAI descriptive
KAI
statistics for the Canadian
and Japanese samples Correlations 0
R
0.65** 0.00
0.19
M
SD
Range
Alpha
Full
94.55 42.40 34.58 17.55
14.44 1.66 6.98 4.21
53-131 2&6l IS&52 l-29
0.83 0.77 0.74 0.59
0.85** 0.X9** 0.398:
Japanese ‘A Sample (N = 144) Full scale 94.49 Originality 40.84 Rule/group conformity 34.46 Effiwncy 19.23
12.26 6.25 6.56 5.30
67-141 2454 19-54 X-33
0.78 0.68 0.74 0.80
0.50** 0.86” 0 66**
0.14 -0.19
0.59”
Japanese ‘B’ Sample (N = 204) Full scale Originahty Rule/group conformity Efficiency
12.22 6.29 6 I9 4.98
64125 24-54 21-52 9-34
0.75 0.64 0.66 0.72
0.66** 0.83** 0.59**
0.30** -0.03
0.40**
Cuna&n SumpIe (N = 144) Full scale Originality Rule/group conformity Efficiency
*P
< 0.05, two-tailed;
**
96.89 40.61 36.09 20.27
P < 0.01, two-tailed.
However, other research on the KAIs psychometric properties has produced mixed findings. Taylor (1989a) found up to 12 poor items that did not load substantially on a factor or loaded on the wrong factor or cross-loaded substantially on at least two factors. Taylor (1989b) also reported stronger support for a four-factor rather than three-factor solution. The main proposes of the present study are (a) to examine the cross-cultural similarities and differences in KAI full and subscale scores between Canadian and Japanese samples; (b) to examine gender differences; (c) to determine if the three-factor structure can be recovered in support of Kirton’s model; and (d) to compare the factors obtained in the present study with those factors reported in the literature from other nations.
METHOD
AND
RESULTS
The KAI (Kirton, 1977) was administered under neutral conditions to 144 Canadian volunteer undergraduates (89 males and 55 females) at a Canadian university and one sample of 144 Japanese volunteer undergraduates (sample ‘A’: 48 males and 96 females) and another sample of 204 (sample ‘B’: 8 1 males and 123 females) at a Japanese university. The second author, who is a native Japanese speaker, developed the Japanese version of the KAI for this study through a forward translation from English to Japanese with consultations with the first author throughout the process of semantics such as connotations of words and phrases. Descriptbe
statistics
The means, standard deviations, score ranges, Cronbach’s alpha coefficients for internal reliability, and intercorrelations for the full scale and the three subscales are presented in Table 1 for the three national samples. There was a significant gender difference on the full scale (t = 2.68, d.f. = 140, P < 0.01) in the Japanese ‘A’ sample such that males had a higher KAI mean (M = 98.27, SD = 13.27) than females (M = 92.56, SD = 11.30). An examination of this gender difference pinpointed the effect to the Originality subscale (t = 4.32, d.f. = 141, P > 0.01). There were no other gender effects. Cross-national
sample comparisons
t-Tests were performed to detect differences in KAI full-scale scores among the three present samples and between these three samples and those in the open literature where sufficient statistical information was published to enable testing. Table 2 presents the brief sample descriptions and sources and the obtained z-tests. As can be seen from the t-tests, there were no significant differences among the Canadian and Japanese samples but the Canadian and Japanese samples generally had lower full-scale scores than the other national samples.
Kirton Adaption-Innovation
57
Table 2. r-Tests of KAI full-scale means for sample comparisons* Japanese Sample/source 144 Canadian undergraduates 144 Japanese undergraduates ‘A’ 204 Japanese undergraduates ‘B’ 58 Australian managers (Foxall, 1990) 34 British managers (Foxall & Hackett. 1992a) 143 Australian managers in MBA program (Foxall & Hackett, 1992b) 156 United Kingdom managers in MBA program (Foxall & Hackett, 1992b) I31 Amencan managers in MBA program (Foxall & Hackett, 1922b) 12.1 IS American managers (Fleenor & Taylor, 1994) 98 Amencan undergraduates (Goldsmith, 1986 Study I) 374 Irish sixth-form students (Hammond, 1986) 51 Saudi-British bank managers (Holland, 1987) 18 British line managers (Holland et al., 1991) 184 American university students (Isaksen & Puccio, 1988) 256 American R & D professionals (Keller & Holland, 1978) 532 British population sample (Kirton, 1977) 64 Canadian managers (Klrton. 1980) 110 American university students (Masten. Caldwell-Colbert & Morse, 1987) 835 Italian populaiton sample (Previde, 1991) 207 Italian managers (Prewde, 1991) 189 American managers (Rosenfeld et al., 1993) 186 British management students (Taylor 1989b) 75 Singaporean general management sample (Thomson, 1980) *Sources
listed in the References. * P i 0.05. two-tailed;
Item factor analyses and factor
M
SD
94.55 94.49 96.89 105.71 102.56 106.04 110.07 101.94 104.80 100.02 102 57 91.20 108.17 100.12 100.92 95.33 113.44 93.00 94.07 99.27 102.33 102.80 95.00
14.44 12.26 12.22 12.82 1735 14.43 16.50 1677 17.10 II.78 13.53 17.30 14.26 14.23 14.26 17.54 16.20 12.50 17.64 17.38 16.39 15.20 12.60
Canadian t-tests
‘A’
‘B’ l-tests
0.04 0.04 - 1.63 -5.13** -2.79+* -6.74** ~ 8.64** -3.93** -7.16** -3.11** -5.93** - 1.35 -3.78** -3.49** -4.27** -0.49 -8.38** 0.89 -0.19 -2.68** -4.52** -4.50** -0.23
5.81** 3.17** 7.31** 9.22** 4.23** 7.21** 3.50** 6.25** - 1.47 4.38** -3.7a** -4.55** -0.54 -9.28** 0.95 -0.27 - 2.84** -4.81** -5.35** -0 29
- I .63 - 1.80 4.80** 2.34* 6.37** 8.71** 3.18** 6.58** 2.11’ 4.99** -2.72** 3.53** - 2.40* -3.21** I 17 -8.70** 2.67** 2.16* 1.61 -3.75** -4.25** 1.14
** P < 0.01, two-tailed.
comparisons
Principal-axis factoring (SPSS, 1988) of the 32 items, using SMCs as the communality estimates, was performed separately for each of the three samples. Three factors were extracted and orthogonally rotated (varimax) to determine if the three KAI subscales wee recovered as Kirton proposes. The factor solutions are presented in Table 3. The Canadian Factor I (eigenvalue = 5.65, 17.7% variance) reflects the R subscale, Factor II (eigenvalue = 2.17,6.8% variance) reflects the 0 subscale, and Factor III (eigenvalue = 1.19, 3.7% variance) the E subscale. The Japanese ‘A’ Factor I (eigenvalue = 5.64, 17.6% variance) reflects the E subscale, Factor II (eigenvalue = 4.14, 12.9% variance) the 0 subscale, and Factor III (eigenvalue = 1.26, 4.0% variance) the R subscale. the Japanese ‘B’ Factor I (eigenvalue = 4.53, 14.2% variance) represents the 0 subscale, Factor II (eigenvalue = 2.97,9.3% variance) the E subscale, and Factor III (eigenvalue = 1.26,3.9% variance) the R subscale. Two and four-factors were also extracted and rotated to determine if more meaningful solutions resulted. The two-factor solutions simply mixed items from the three scales while the four-factor solutions split at least one of the subscales. Thus, the three-factor solution was the most meaningful and the best fit to Kirton’s model. The factor analyses were also performed using other models (i.e. principal components, alpha, and image) to determine if substantial differences in solutions resulted especially given that previous studies varied in the factor model used. No substantial differences were identified among the various solutions. Gender was also added as a variable to determine if gender loaded significantly on a factor or substantially changed the solutions. Gender did not load significantly on any factor solution in any of these three samples. Factor comparisons were performed using the S-Index (Catel, Balcar, Horn, & Nesselroade, 1969) to determine the degree of similarity between factors from the different sample that supposedly reflect the same subscale. As shown at the end of Table 3, the Canadian 0 (S-Index: 0.77) and E (SIndex: 0.52 and 0.71) factors showed only moderate similarity to their respective Japanese ‘A’ and ‘B’ factors and the Canadian R factor (S-Index: 0.55 and 0.38) showed weak similarly to their Japanese R factors. The two Japanese 0 (S-Index: 0.92) factors were highly similar to each other while the E (S-Index: 0.77) factors were moderately similar and the R (S-Index: 0.50) factors weakly similar. Cross-national factor
Factor comparisons reported in the open
comparisons
were performed between the factors obtained in the present study and those literature where published factor analyses presented factor structures for
58
Robert Loo and Kunio Shiomi Table 3. KAI factor structure and comparisons*
Item/subscale 2 3 4 5 6
I
31 I4 I2 01 22 23 45 41 34 20 43 55 01 I3 42 26 15 06 18 08 05 23 59 40 45 59 21 64 49 03 50 47
R 0 E 0 R R R R R 0 0 0 E E 0 E 0 0 R 0 E 0 0 E 0 R E R R 0 E E
1
8 9 IO II I2 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
33 63 05 36 -15 I6 21 I2 39 60 14 17 -07 06 35 -11 55 33 31 57 -18 37 IO -01 59 I7 06 I5 IO 45 20 43
R
SubscaleiS-Index Canadian Japanese ‘A’ *Decimal
Canadian II
Japanese ‘A’ II
Japanese ‘B II
111
I
I7 -17 56 02 07 I4 22 I9 -29 -10 04 -OS 67 34 -26 29 -02 07 -10 -04 SO -31 -10 34 02 06 24 -00 03 06 00 -01
32 -18 38 -07 08 05 61 53 II -33 04 -10 50 66 -44 61 -29 -14 29 -08 14 -23 46 60 03 57 53 09 32 I4 33 27
03 30 -09 44 -23 -04 I3 -00 09 49 53 -46 -22 02 50 -10 35 41 -04 61 -20 54 -26 -00 61 29 04 I8 -02 60 02 28
53 -01 I1 I2 -41 32 21 33 37 26 -06 05 II 05 -03 -08 48 I6 45 36 02 07 I3 34 13 36 52 44 75 -01 30 27
I4 44 -20 34 -24 -02 I5 08 28 62 28 -48 -04 04 44 -14 44 48 I4 58 -26 58 -14 04 50 34 21 20 21 56 02 29
28 04 34 -00 01 -08 46 24 05 -04 I6 -16 50 68 -19 52 -02 -18 12 -07 63 -14 20 51 I9 52 48 14 31 22 09 II
II 14 -08 08 26 48 23 I7 26 II -24 -04 06 -10 I4 -06 27 07 54 I2 I4 -06 -03 I2 I2 26 28 54 53 06 44 36
E 52
0 77
R 55
0 77 92
E 71 77
R 38 50
E
0
III
I
111
points omitted
comparison. Summarized results involving the seven studies reported in the open literature are presented in Table 4. Overall, these comparisons show moderate to strong similarities between factors identified in the present study and those reported in the literature. The highest mean similarities were found for the 0 factor (S-Index range: 0.7220.83) and the lowest for the R factor (S-Index range: 0.55-0.60). DISCUSSION KAIfull scale and subscales Many studies report only the full sale scores and their relationships to other variables; however, results from the present study emphasize the need to also report subscale scores as well as their relationships to other variables of interest. One reason is that a given full scale score may reflect differing mixes of the three subscales, therefore, people with the same full score may be quite different in their adaption-innovation orientation. Another reason is that the pattern of interTable 4. Summary of S-Index factor comparisons Rule/group Conformity
Originality
Sample Canadian Japanese ‘A’ Japanese ‘B’
across studies*
Efficiency
S-Index Range
Meall S-Index
S-Index Range
Mean S-Index
S-Index Range
Mean S-Index
0.45Xl.80 0.69-0.96 0.69-0.87
0.72 0.83 0.77
0.384.67 0.47-0.62 0.3&0.71
0.55 0.55 0.60
0.524.92 0.52-0.77 0.594.82
0.69 0.64 0.75
*The lengthy table containing
the complete set of factor comparisons
is available
from the first author
Kirton Adaption-Innovation
59
correlations among the three subscales can vary from sample to sample and from population to population. For example, the 0 and R subscales were significantly correlated (0.65) in the present Canadian sample whereas E and R were significantly correlated (0.59) in the Japanese ‘A’ sample (see Table 1). Foxall and Hackett (1992b) as well as Rosenfeld and his associates (1993) also demonstrated the importance of using subscales and the differences in pattern among subscales for different groups of Ss. Thirdly, the Adaption-Innovation dimension is a complex construct, therefore, subscale scores may be more useful in detecting and pinpointing relationships with other variables such as personality variables or gender differences than full scale scores. KAI reliability
Although the internal consistency reliability of the full scale is generally adequate, the reliabilities of the subscales could be improved. Given the relationship between the number of items in a scale and the upper limit on obtained reliability coefficients, then the subscales should have been developed to have equal numbers of items and a sufficient numbers of items to be able to obtain adequate reliabilities. Note that the E subscale has only seven items whilst the 0 and R subscales have 13 and 12 items respectively. Perhaps the E subscale should be expanded to, say, 13 items. This change should improve poor reliabilities; for example, raise the E subscale’s alphas of 0.57, 0.59, and 0.62 found in the Canadian sample (see Table 1). As well, items showing poor item-subscale and itemtotal correlations should be replaced. Factor structure of the KAI andfactor comparisons
The factor solutions provide support for the three subscales. However, the three-factor solutions account for only a small proportion of the total variance (23.2-34.5%) show an undesirable crossloading of items on more than one factor, and that some items do not load substantially on any of the three factors. These problems are related to the points raised earlier about reliability. It is not surprising that subscales, with only moderate internal reliability and unequal numbers of items, do not show a clean recovery in factor structures. Perhaps further refinements to the KAI by slightly increasing the number of items in the E and R subscales and having an equal number of items across subscales (i.e. 13 items/subscale) would improve both the internal consistency reliabilities and factor structure. In spite of these problems, factor comparisons between factors obtained in the present study and those reported in the literature revealed moderate to strong factor similarities for the 0 factor and weak to moderate similarities for the E and R factors (see Table 4). Cross-cultural comparisons
Overall, cross-cultural comparisons revealed that both the present Canadian and Japanese samples had lower KAI full-scale scores than most other samples reported in the open literature. The Canadian sample had a significantly lower mean (M = 94.55, SD = 14.44) than 15 of the other samples, which included samples from the U.S.A., the U.K., Australia, Ireland, and Italy (see Table 2). This Canadian sample did not differ from seven of the other samples. When subscale scores were used for the five cross-cultural comparisons where subscale scores were reported, the Canadian sample had a lower 0 mean (M = 42.40, SD = 7.66) than five of the other samples, which were drawn from the U.S.A., the U.K., and Australia; a lower R mean (M = 34.58, SD = 6.98) than the other five samples; and a lower E mean (M = 17.55, SD = 4.21) than four of the other five samples. The Japanese samples ‘A’ (M = 94.49, SD = 12.26) and ‘B’ (M = 96.89, SD = 12.22) had significantly lower KAI means than 15 and 17 of the other samples respectively but the Japanese samples did not differ from the Canadian sample (see Table 1). When the subscales scores were examined, the Japanese samples tended to have lower 0 and R means but did not differ on E. These findings reveal that both Canadian and Japanese national samples are generally lower in innovation than most other national samples. One could speculate that this finding might reflect the greater tendency in these two cultures to socialize persons to conform to social norms rather than to express ‘rugged individualism’ or to be high risk-takers. Cross-cultural as well as other group comparisons on the KAI would be facilitated if researchers publish their subscale statistics in addition to the full scale statistics. Differences on the full scale
60
Robert Loo and Kunio Shiomi
might be pinpointed using subscales and, sometimes, only full scale comparisons are made.
differences
in a subscale
might be missed if
Gender comparisons The present study did not find any substantial gender differences in the pattern of intercorrelations among the subscales for the Canadian and Japanese samples (see Table 1). In line with Kirton’s position that males have higher KAI scores than females, the males in the present Canadian sample and Japanese sample ‘A’ had significantly higher KAI means than the females but there was no difference for Japanese sample ‘B’ (see Table 1). When the subscales were used, Canadian males were higher on the R subscale whilst Japanese males in sample ‘A’ were higher on the 0 subscale and no differences were found for sample ‘B’. Gender results in the present study are reflected by those in the open literature, which also show a mix of significant and non-significant gender differences. Overall, these results show some support for Kirton’s proposed gender difference but gender differences may be waning given changing societal norms and the influence of educational systems in the advanced nations such as Japan and Canada. Acknowledgements~This study was supported in part, by a grant from the University Research Assistant, Jerrie Andreasson-Richardson.
of Lethbridge.
Special thanks
to our
REFERENCES Beene, J. M. & Zelhart, P. F. (1988). Factor analysis of the Kirton Adaption-Innovation inventory. Perceptual and Moror Skills, 66, 667~611. Cattell, R. B., Balcar, K. R., Horn, J. L., & Nesselroade, J. R. (1969). Factor matching procedures: An improvement on the S-Index; with tables. Educational and Psychological Measurement, 29,781-792. Fleenor, J. W. &Taylor, S. (1994). Construct validity of three self-report measures ofcreativity. Educationaland Psychological Measurement, 54(2), 464410. Foxall, G. R. (1990). An empirical analysis of mid-career managers’ adaptive-innovative cognitive styles and task orientations in three countries. (Psychological Reports, 66, I 115-l 124. Foxall, G. R. & Hackett, P. M. W. (1992a). Cognitive style and extent of computer use in organizations: Relevance of sufficiency of originality, efficiency and rule-conformity. Percepfual and Motor Skills, 74, 491497. Foxall, G. R. & Hackett, P. M. W. (199213). The factor structure and construct validity of the Kirton Adaption-Innovation Inventory. Personalit)’ and Individual Differences, 13(9), 961-975. Goldsmith, R. E. (1985). The factorial composition of the Kirton Adaption-Innovation Inventory. Educational and Psychological Measurement, 45,245%250. Hammond, S. M. (1986). Some pitfalls in the use of factor scores: The case of the Kirton Adaptation-Innovation Inventory. Personality and Individual Differences, 7(3), 401-407. Holland, P. A. (1987). Adaptors and innovators: Application of the Kirton Adaption-Innovation Inventory to bank employees. Pswhological Reports, 60, 263-270. Holland, P. A., Bowskill, I., & Bailey, A. (1991). Adaptors and innovators: Selection versus induction. Psychological Reports. 68, 1283-1290. Isaksen, S. G. & Puccio, G. J. (1988). Adaption-innovation and the Torrance tests of creative thinking: The level-style issue revisited. Psychological Reports, 63, 659-670. Keller, R. T. & Holland, W. E. (1978). A cross-validation study of the Kirton Adaption-Innovation Inventory in three research and development organizations. Applied Psychological Measurement, 2(4), 563-570. Kirton, M. J. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psycholoqq, 61, 622-629. Kirton, M. J. (1977). Manual of the Kirton Adapfion-Innovation Inventory. London: National Foundation for Educational Research. Kirton, M. J. (1980). Adaptors and innovators in organizations. Human Relations. 3314). 213-224. Kirton, M. J. (1989). Adaptors and innovators: Stylesof creativity andproblem-solving. London: Routledge. Masten, W. G.. Caldwell-Colbert A. T. & Morse. D. T. (1987). Self-estimates of adantors and innovators on the Kirton Adaption-Innovation Inventory. Psychological Reports, 63,‘587-590. Previde, G. P. (1991). Italian adaptors and innovators: Is cognitive style underlying culture? Personality and Individual D~/‘erences. 12(l), I-IO. Rosenfeld, R. B., Winger-Bearskin, M., Marcic. D. & Braun, C. L. (1993). Delineating entrepreneurs’ styles: Application of adaption-innovation subscales. Psychological Reports, 72, 287-298. SPSS Inc. (1988). SPSS user’s guide. Chicago, Illinois: SPSS Inc. Taylor, W. G. K. (1989a). The Kirton Adaption-Innovation Inventory: Should the sub-scales be orthogonal? Personalir) and Individual D@rences, IO, 92 l-929. Taylor, W. G. K. (1989b). The Kirton Adaption-Innovation Inventory: A re-examination of the factor structure. Journal of Organizational Behavior, IO, 297-307. Thomson, D. (1980). Adaptors and innovators: A replication study on managers in Singapore and Malaysia. Psychological Reports, 47, 383-387.
Pergamon
Printed in Great Britain. All rights reserved
SO191-8869(96)00178-X
0191-8869/97
$17.00+0.00
A CROSS-CULTURAL EXAMINATION OF THE KIRTON ADAPTION-INNOVATION INVENTORY Robert Loo’* and Kunio Shiomi’ ‘Faculty of Management, University of Lethbridge, Lethbridge, Alberta, Canada TIK 3M4 and ‘Department of Psychology, Hyogo University of Teacher Education, Shimokume, Yashiro-Cho, Hyogo 673-14, Japan ( Receiwd
22 March 1996)
Summary-This study examined the factor structure and other psychometric properties of the Kirton Adaption-Innovation Inventory (KAI) with a sample of Canadian (N = 144) and two samples of Japanese undergraduates (N = 144, N = 204). The three-factor solution generally supported Kirton’s three subscales (Originality, Rule/Group Conformity, Efficiency) but accounted for only 23335% of the variance. There was some support for Kirton’s view that females are more adaptive than males. Cross-national comparisons of KAI scores and factors were made between the present samples and those reported in the literature from the U.S.A., Italy, and Great Britain among other countries. These comparisons showed moderate to strong support for Kirton’s three-factor structure and the utility of the inventory. Several recommendations are presented to improve the psychometric properties of the KAI and the usefulness of studies in this area. Copyright 8 1997 Elsevier Science Ltd.
INTRODUCTION Kirton’s (e.g. 1976, 1980, 1989) theory ofcognitive style addresses individual differences in creativity, problem-solving approach, and decision-making approach along a continuum ranging from ‘adaption’ to ‘innovation’. Individuals at extremes of this continuum show marked style differences such that adaptors have a preference for making decisions and improvements within existing methods and systems whereas innovators are more likely to ignore existing conventions and seek novel solutions or directions. Not surprisingly, innovators prefer less structured situations and are more willing to take risks than are adaptors. Kirton (1977) developed a 33-item self-report inventory to measure individual differences on this cognitive-style continuum. The first item is an unscored warm-up item whilst the other 32 items in the Kirton Adaption-Innovation Inventory (KAI) reflect three subscales: Originality (13 items) describes the creative person; Efficiency (nine items) describes the Weberian precise, reliable and disciplined person; and Rule/Group Conformity (10 items) describes the rule-following person who fits in well in bureaucracies. The response scale consists of a 17-dot line, which converts to a fivepoint scale ranging from “very easy” to “very hard”. The possible range of scores is from 32 (extreme adaptor) to 160 (extreme innovator) with a theoretical mean of 96. Most researchers report only overall scores whilst some researchers report both the overall as well as the three subscale scores. This theory and inventory has been widely-used for a variety of purposes and used in many different occupational, educational, and cultural settings. For example, Foxall (1990) has conducted many studies using the KAI including the examination of gender differences among MBA students in three countries. Fleenor and Taylor (1994) recently examined the construct and concurrent validity of the KAI using a large, heterogeneous sample of managers. Some psychometric studies have also added support to Kirton’s (1977) early inventory development. For example, Keller and Holland’s (1978) early validation study using a sample of professional employees from three research and development organizations supported Kirton’s three-factor model. Similarly, Goldsmith (1985) found support for the three-factor structure of the KAI using a sample of urban American adults as did Beene and Zelhart (1988) with a sample of American college students and university administrators. *To whom all correspondence
should be addressed. 55
56
Robert Loo and Kunio Shiomi Table I. KAI descriptive
KAI
statistics for the Canadian
and Japanese samples Correlations 0
R
0.65** 0.00
0.19
M
SD
Range
Alpha
Full
94.55 42.40 34.58 17.55
14.44 1.66 6.98 4.21
53-131 2&6l IS&52 l-29
0.83 0.77 0.74 0.59
0.85** 0.X9** 0.398:
Japanese ‘A Sample (N = 144) Full scale 94.49 Originality 40.84 Rule/group conformity 34.46 Effiwncy 19.23
12.26 6.25 6.56 5.30
67-141 2454 19-54 X-33
0.78 0.68 0.74 0.80
0.50** 0.86” 0 66**
0.14 -0.19
0.59”
Japanese ‘B’ Sample (N = 204) Full scale Originahty Rule/group conformity Efficiency
12.22 6.29 6 I9 4.98
64125 24-54 21-52 9-34
0.75 0.64 0.66 0.72
0.66** 0.83** 0.59**
0.30** -0.03
0.40**
Cuna&n SumpIe (N = 144) Full scale Originality Rule/group conformity Efficiency
*P
< 0.05, two-tailed;
**
96.89 40.61 36.09 20.27
P < 0.01, two-tailed.
However, other research on the KAIs psychometric properties has produced mixed findings. Taylor (1989a) found up to 12 poor items that did not load substantially on a factor or loaded on the wrong factor or cross-loaded substantially on at least two factors. Taylor (1989b) also reported stronger support for a four-factor rather than three-factor solution. The main proposes of the present study are (a) to examine the cross-cultural similarities and differences in KAI full and subscale scores between Canadian and Japanese samples; (b) to examine gender differences; (c) to determine if the three-factor structure can be recovered in support of Kirton’s model; and (d) to compare the factors obtained in the present study with those factors reported in the literature from other nations.
METHOD
AND
RESULTS
The KAI (Kirton, 1977) was administered under neutral conditions to 144 Canadian volunteer undergraduates (89 males and 55 females) at a Canadian university and one sample of 144 Japanese volunteer undergraduates (sample ‘A’: 48 males and 96 females) and another sample of 204 (sample ‘B’: 8 1 males and 123 females) at a Japanese university. The second author, who is a native Japanese speaker, developed the Japanese version of the KAI for this study through a forward translation from English to Japanese with consultations with the first author throughout the process of semantics such as connotations of words and phrases. Descriptbe
statistics
The means, standard deviations, score ranges, Cronbach’s alpha coefficients for internal reliability, and intercorrelations for the full scale and the three subscales are presented in Table 1 for the three national samples. There was a significant gender difference on the full scale (t = 2.68, d.f. = 140, P < 0.01) in the Japanese ‘A’ sample such that males had a higher KAI mean (M = 98.27, SD = 13.27) than females (M = 92.56, SD = 11.30). An examination of this gender difference pinpointed the effect to the Originality subscale (t = 4.32, d.f. = 141, P > 0.01). There were no other gender effects. Cross-national
sample comparisons
t-Tests were performed to detect differences in KAI full-scale scores among the three present samples and between these three samples and those in the open literature where sufficient statistical information was published to enable testing. Table 2 presents the brief sample descriptions and sources and the obtained z-tests. As can be seen from the t-tests, there were no significant differences among the Canadian and Japanese samples but the Canadian and Japanese samples generally had lower full-scale scores than the other national samples.
Kirton Adaption-Innovation
57
Table 2. r-Tests of KAI full-scale means for sample comparisons* Japanese Sample/source 144 Canadian undergraduates 144 Japanese undergraduates ‘A’ 204 Japanese undergraduates ‘B’ 58 Australian managers (Foxall, 1990) 34 British managers (Foxall & Hackett. 1992a) 143 Australian managers in MBA program (Foxall & Hackett, 1992b) 156 United Kingdom managers in MBA program (Foxall & Hackett, 1992b) I31 Amencan managers in MBA program (Foxall & Hackett, 1922b) 12.1 IS American managers (Fleenor & Taylor, 1994) 98 Amencan undergraduates (Goldsmith, 1986 Study I) 374 Irish sixth-form students (Hammond, 1986) 51 Saudi-British bank managers (Holland, 1987) 18 British line managers (Holland et al., 1991) 184 American university students (Isaksen & Puccio, 1988) 256 American R & D professionals (Keller & Holland, 1978) 532 British population sample (Kirton, 1977) 64 Canadian managers (Klrton. 1980) 110 American university students (Masten. Caldwell-Colbert & Morse, 1987) 835 Italian populaiton sample (Previde, 1991) 207 Italian managers (Prewde, 1991) 189 American managers (Rosenfeld et al., 1993) 186 British management students (Taylor 1989b) 75 Singaporean general management sample (Thomson, 1980) *Sources
listed in the References. * P i 0.05. two-tailed;
Item factor analyses and factor
M
SD
94.55 94.49 96.89 105.71 102.56 106.04 110.07 101.94 104.80 100.02 102 57 91.20 108.17 100.12 100.92 95.33 113.44 93.00 94.07 99.27 102.33 102.80 95.00
14.44 12.26 12.22 12.82 1735 14.43 16.50 1677 17.10 II.78 13.53 17.30 14.26 14.23 14.26 17.54 16.20 12.50 17.64 17.38 16.39 15.20 12.60
Canadian t-tests
‘A’
‘B’ l-tests
0.04 0.04 - 1.63 -5.13** -2.79+* -6.74** ~ 8.64** -3.93** -7.16** -3.11** -5.93** - 1.35 -3.78** -3.49** -4.27** -0.49 -8.38** 0.89 -0.19 -2.68** -4.52** -4.50** -0.23
5.81** 3.17** 7.31** 9.22** 4.23** 7.21** 3.50** 6.25** - 1.47 4.38** -3.7a** -4.55** -0.54 -9.28** 0.95 -0.27 - 2.84** -4.81** -5.35** -0 29
- I .63 - 1.80 4.80** 2.34* 6.37** 8.71** 3.18** 6.58** 2.11’ 4.99** -2.72** 3.53** - 2.40* -3.21** I 17 -8.70** 2.67** 2.16* 1.61 -3.75** -4.25** 1.14
** P < 0.01, two-tailed.
comparisons
Principal-axis factoring (SPSS, 1988) of the 32 items, using SMCs as the communality estimates, was performed separately for each of the three samples. Three factors were extracted and orthogonally rotated (varimax) to determine if the three KAI subscales wee recovered as Kirton proposes. The factor solutions are presented in Table 3. The Canadian Factor I (eigenvalue = 5.65, 17.7% variance) reflects the R subscale, Factor II (eigenvalue = 2.17,6.8% variance) reflects the 0 subscale, and Factor III (eigenvalue = 1.19, 3.7% variance) the E subscale. The Japanese ‘A’ Factor I (eigenvalue = 5.64, 17.6% variance) reflects the E subscale, Factor II (eigenvalue = 4.14, 12.9% variance) the 0 subscale, and Factor III (eigenvalue = 1.26, 4.0% variance) the R subscale. the Japanese ‘B’ Factor I (eigenvalue = 4.53, 14.2% variance) represents the 0 subscale, Factor II (eigenvalue = 2.97,9.3% variance) the E subscale, and Factor III (eigenvalue = 1.26,3.9% variance) the R subscale. Two and four-factors were also extracted and rotated to determine if more meaningful solutions resulted. The two-factor solutions simply mixed items from the three scales while the four-factor solutions split at least one of the subscales. Thus, the three-factor solution was the most meaningful and the best fit to Kirton’s model. The factor analyses were also performed using other models (i.e. principal components, alpha, and image) to determine if substantial differences in solutions resulted especially given that previous studies varied in the factor model used. No substantial differences were identified among the various solutions. Gender was also added as a variable to determine if gender loaded significantly on a factor or substantially changed the solutions. Gender did not load significantly on any factor solution in any of these three samples. Factor comparisons were performed using the S-Index (Catel, Balcar, Horn, & Nesselroade, 1969) to determine the degree of similarity between factors from the different sample that supposedly reflect the same subscale. As shown at the end of Table 3, the Canadian 0 (S-Index: 0.77) and E (SIndex: 0.52 and 0.71) factors showed only moderate similarity to their respective Japanese ‘A’ and ‘B’ factors and the Canadian R factor (S-Index: 0.55 and 0.38) showed weak similarly to their Japanese R factors. The two Japanese 0 (S-Index: 0.92) factors were highly similar to each other while the E (S-Index: 0.77) factors were moderately similar and the R (S-Index: 0.50) factors weakly similar. Cross-national factor
Factor comparisons reported in the open
comparisons
were performed between the factors obtained in the present study and those literature where published factor analyses presented factor structures for
58
Robert Loo and Kunio Shiomi Table 3. KAI factor structure and comparisons*
Item/subscale 2 3 4 5 6
I
31 I4 I2 01 22 23 45 41 34 20 43 55 01 I3 42 26 15 06 18 08 05 23 59 40 45 59 21 64 49 03 50 47
R 0 E 0 R R R R R 0 0 0 E E 0 E 0 0 R 0 E 0 0 E 0 R E R R 0 E E
1
8 9 IO II I2 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
33 63 05 36 -15 I6 21 I2 39 60 14 17 -07 06 35 -11 55 33 31 57 -18 37 IO -01 59 I7 06 I5 IO 45 20 43
R
SubscaleiS-Index Canadian Japanese ‘A’ *Decimal
Canadian II
Japanese ‘A’ II
Japanese ‘B II
111
I
I7 -17 56 02 07 I4 22 I9 -29 -10 04 -OS 67 34 -26 29 -02 07 -10 -04 SO -31 -10 34 02 06 24 -00 03 06 00 -01
32 -18 38 -07 08 05 61 53 II -33 04 -10 50 66 -44 61 -29 -14 29 -08 14 -23 46 60 03 57 53 09 32 I4 33 27
03 30 -09 44 -23 -04 I3 -00 09 49 53 -46 -22 02 50 -10 35 41 -04 61 -20 54 -26 -00 61 29 04 I8 -02 60 02 28
53 -01 I1 I2 -41 32 21 33 37 26 -06 05 II 05 -03 -08 48 I6 45 36 02 07 I3 34 13 36 52 44 75 -01 30 27
I4 44 -20 34 -24 -02 I5 08 28 62 28 -48 -04 04 44 -14 44 48 I4 58 -26 58 -14 04 50 34 21 20 21 56 02 29
28 04 34 -00 01 -08 46 24 05 -04 I6 -16 50 68 -19 52 -02 -18 12 -07 63 -14 20 51 I9 52 48 14 31 22 09 II
II 14 -08 08 26 48 23 I7 26 II -24 -04 06 -10 I4 -06 27 07 54 I2 I4 -06 -03 I2 I2 26 28 54 53 06 44 36
E 52
0 77
R 55
0 77 92
E 71 77
R 38 50
E
0
III
I
111
points omitted
comparison. Summarized results involving the seven studies reported in the open literature are presented in Table 4. Overall, these comparisons show moderate to strong similarities between factors identified in the present study and those reported in the literature. The highest mean similarities were found for the 0 factor (S-Index range: 0.7220.83) and the lowest for the R factor (S-Index range: 0.55-0.60). DISCUSSION KAIfull scale and subscales Many studies report only the full sale scores and their relationships to other variables; however, results from the present study emphasize the need to also report subscale scores as well as their relationships to other variables of interest. One reason is that a given full scale score may reflect differing mixes of the three subscales, therefore, people with the same full score may be quite different in their adaption-innovation orientation. Another reason is that the pattern of interTable 4. Summary of S-Index factor comparisons Rule/group Conformity
Originality
Sample Canadian Japanese ‘A’ Japanese ‘B’
across studies*
Efficiency
S-Index Range
Meall S-Index
S-Index Range
Mean S-Index
S-Index Range
Mean S-Index
0.45Xl.80 0.69-0.96 0.69-0.87
0.72 0.83 0.77
0.384.67 0.47-0.62 0.3&0.71
0.55 0.55 0.60
0.524.92 0.52-0.77 0.594.82
0.69 0.64 0.75
*The lengthy table containing
the complete set of factor comparisons
is available
from the first author
Kirton Adaption-Innovation
59
correlations among the three subscales can vary from sample to sample and from population to population. For example, the 0 and R subscales were significantly correlated (0.65) in the present Canadian sample whereas E and R were significantly correlated (0.59) in the Japanese ‘A’ sample (see Table 1). Foxall and Hackett (1992b) as well as Rosenfeld and his associates (1993) also demonstrated the importance of using subscales and the differences in pattern among subscales for different groups of Ss. Thirdly, the Adaption-Innovation dimension is a complex construct, therefore, subscale scores may be more useful in detecting and pinpointing relationships with other variables such as personality variables or gender differences than full scale scores. KAI reliability
Although the internal consistency reliability of the full scale is generally adequate, the reliabilities of the subscales could be improved. Given the relationship between the number of items in a scale and the upper limit on obtained reliability coefficients, then the subscales should have been developed to have equal numbers of items and a sufficient numbers of items to be able to obtain adequate reliabilities. Note that the E subscale has only seven items whilst the 0 and R subscales have 13 and 12 items respectively. Perhaps the E subscale should be expanded to, say, 13 items. This change should improve poor reliabilities; for example, raise the E subscale’s alphas of 0.57, 0.59, and 0.62 found in the Canadian sample (see Table 1). As well, items showing poor item-subscale and itemtotal correlations should be replaced. Factor structure of the KAI andfactor comparisons
The factor solutions provide support for the three subscales. However, the three-factor solutions account for only a small proportion of the total variance (23.2-34.5%) show an undesirable crossloading of items on more than one factor, and that some items do not load substantially on any of the three factors. These problems are related to the points raised earlier about reliability. It is not surprising that subscales, with only moderate internal reliability and unequal numbers of items, do not show a clean recovery in factor structures. Perhaps further refinements to the KAI by slightly increasing the number of items in the E and R subscales and having an equal number of items across subscales (i.e. 13 items/subscale) would improve both the internal consistency reliabilities and factor structure. In spite of these problems, factor comparisons between factors obtained in the present study and those reported in the literature revealed moderate to strong factor similarities for the 0 factor and weak to moderate similarities for the E and R factors (see Table 4). Cross-cultural comparisons
Overall, cross-cultural comparisons revealed that both the present Canadian and Japanese samples had lower KAI full-scale scores than most other samples reported in the open literature. The Canadian sample had a significantly lower mean (M = 94.55, SD = 14.44) than 15 of the other samples, which included samples from the U.S.A., the U.K., Australia, Ireland, and Italy (see Table 2). This Canadian sample did not differ from seven of the other samples. When subscale scores were used for the five cross-cultural comparisons where subscale scores were reported, the Canadian sample had a lower 0 mean (M = 42.40, SD = 7.66) than five of the other samples, which were drawn from the U.S.A., the U.K., and Australia; a lower R mean (M = 34.58, SD = 6.98) than the other five samples; and a lower E mean (M = 17.55, SD = 4.21) than four of the other five samples. The Japanese samples ‘A’ (M = 94.49, SD = 12.26) and ‘B’ (M = 96.89, SD = 12.22) had significantly lower KAI means than 15 and 17 of the other samples respectively but the Japanese samples did not differ from the Canadian sample (see Table 1). When the subscales scores were examined, the Japanese samples tended to have lower 0 and R means but did not differ on E. These findings reveal that both Canadian and Japanese national samples are generally lower in innovation than most other national samples. One could speculate that this finding might reflect the greater tendency in these two cultures to socialize persons to conform to social norms rather than to express ‘rugged individualism’ or to be high risk-takers. Cross-cultural as well as other group comparisons on the KAI would be facilitated if researchers publish their subscale statistics in addition to the full scale statistics. Differences on the full scale
60
Robert Loo and Kunio Shiomi
might be pinpointed using subscales and, sometimes, only full scale comparisons are made.
differences
in a subscale
might be missed if
Gender comparisons The present study did not find any substantial gender differences in the pattern of intercorrelations among the subscales for the Canadian and Japanese samples (see Table 1). In line with Kirton’s position that males have higher KAI scores than females, the males in the present Canadian sample and Japanese sample ‘A’ had significantly higher KAI means than the females but there was no difference for Japanese sample ‘B’ (see Table 1). When the subscales were used, Canadian males were higher on the R subscale whilst Japanese males in sample ‘A’ were higher on the 0 subscale and no differences were found for sample ‘B’. Gender results in the present study are reflected by those in the open literature, which also show a mix of significant and non-significant gender differences. Overall, these results show some support for Kirton’s proposed gender difference but gender differences may be waning given changing societal norms and the influence of educational systems in the advanced nations such as Japan and Canada. Acknowledgements~This study was supported in part, by a grant from the University Research Assistant, Jerrie Andreasson-Richardson.
of Lethbridge.
Special thanks
to our
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