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1. Cultural Differences in Innovative Behaviour:
4-country Study with Representative Samples
Martin Lukeš
Alena Černíková
Ute Stephan
Tomáš Svátek
Prague University of Economics
14th EAWOP Congress
Santiago de Compostela, May 13-16
2. Study objectives
Identification of cultural differences in
innovative behaviour
Creation of an independent measure of
innovative behaviour and innovation support
Comparing the role of culture with other
factors influencing innovative behaviours
3. Key definitions
Innovation
– process of new idea creation or adoption and a
subsequent effort to develop it into a new product,
service, process or business model with an
expected added value for a potential user
Culture
– shows up in the values, beliefs, norms, behavioral
practices, and symbols shared, acquired, and
advanced by the members of a large group
4. Model
Values General
Personal IB
Innovativeness
General
Beliefs
about Work-related IB
Innovations
- Idea Generation
Social / - Idea Search
Innovation
Demographic - Communicating Ideas
Outcomes
Variables - Implementation Starting
Activities
Business / - Involving Others
Job-related - Overcoming Obstacles
Variables
Manager’s Organizational
Support – MP/EP Support
5. Questionnaire development - Pilot
Step 1:
– 13 scales tested, 95 items in total
– 57 newly developed items, other items used or modified based on
previous surveys - 12 items from Scott and Bruce (1994), 8 items
from Howell, Shea, and Higgins (2005), 5 items from Jackson
Personality Inventory (1994), etc.
– piloted with 96 students of VSE
– December 2007
Step 2:
– 5 items reformulated, 2 added, 20 deleted, 77 items in total
– translation and backtranslation to EN, DE, IT, FR
– Sample: students of WHU and Regensburg U. (N=24 and 55),
Bocconi (N=42), EPFL Lausanne (N=36), employees of Skoda
Auto (N = 172)
– January - March 2008
Final version for Adult population survey
– 50 items, 13 scales
6. Sample & Data gathering
Sample: 4795 adults, Czech Rep. (N=1004),
Germany (N=1285), Italy (N=1256), Switzerland
(N=1250)
Representativeness: checked for each country by
using χ2 test of good fit (exc. CZ + IT - education,
CH – age)
Data gathering: May - July 2008 by CATI technique
by agencies Median, IFAK, Linksystem, P. Roberts
and Partners
In total, 121281 calls done, 66792 taken, response
rate 15 % (CZ) – 24 % (IT)
7. Results of Confirmatory Factor Analysis:
Work-Related Innovative Behavior Scales
Loading Cronbach’s
Items Cronbach’s
Aspects of work-related innovative (standardized) Alpha
Alpha CZ/D/It/Ch
behavior 1st-order 2nd-order
C2 .67 .85 .69 .73 .74 .72 .561
Idea generation C3 .63
C5 .69
D2 .62 .74 .73 .75 .74 .71 .73
Idea search D1 .76
D3 .72
E1 .67 .72 .83 .86 .81 .86 .80
Communicating ideas E4 .78
F4 .79
G1 .79
E7 .72 .74 .78 .84 .79 .77 .72
Implementation starting activities E8 .71
D4 .78
G3 .60 .72 .75 .82 .72 .75 .73
Involving others G4 .81
G5 .73
H1 .79 .74 .85 .89 .82 .87 .83
Overcoming obstacles H2 .73
H4 .71
H5 .74
I7 .74 .82 .81 .83 .81 .81 .76
Innovation outputs I9 .73
I10 .68
I11 .64
Note. Cz – Czech Republic, D – Germany, It – Italy, Ch – Switzerland, 1The low Cronbach’s Alpha for Switzerland seems
to be due to translation problems of item C2 within the French version used in Switzerland (cf. also results of measurement invariance tests).
9. Cross-cultural measurement invariance
Ensures that mean comparisons across cultures can
be validly conducted
Tested with multi-group confirmatory factor analysis
(e.g., Kline, 2005; Steenkamp & Baumgartner, 1998)
based on maximum likelihood estimation (AMOS 6)
4 types of equivalence measured
– Configural - whether the factor structures of our scales were
replicable with the same number of factors
– Metric - whether item loadings were comparable
– Scalar - whether item intercepts were comparable
– Of factor covariances - whether factors showed comparable
variance and for multi-factor models whether the relations
among factors were comparable
10. Cross-cultural measurement invariance (1)
Model Comparison RMSEA CFI ∆CFI TLI ∆TLI NFI
Personal Experimenting and Originality (Sample 1)
1 Configural - .020 .992 - .980 - .988
2 Full metric 1 vs. 2 .019 .987 -.005 .982 .002 .980
3 Full scalar 2 vs. 3 .034 .944 -.043 .944 -.038 .933
3.1 Partial scalar 2 vs. 3.1 .023 .979 -.008 .975 -.007 .970
4 Factor variance 3.1 vs. 4 .028 .964 -.015 .961 -.014 .954
Cultural Perception of Innovative Behavior (Sample 1)
1 Configural - .011 .999 - .996 - .998
2 Full metric 1 vs. 2 .027 .986 -.013 .974 -.022 .982
2.1 Partial metric 1 vs. 2.1 .024 .994 -.005 .979 -.017 .992
3. Initial partial scalar 2.1 vs. 3 .028 .988 .006 .972 .005 .985
4. Factor variance 3 vs. 4 .033 .979 -.009 .962 -.011 .975
Work-Related Innovative Behavior Scales (Sample 2)
1 Configural - .026 .943 - .931 - .919
2 Full metric 1 vs. 2 .026 .941 -.002 .932 -.001 .916
3 Full scalar 2 vs. 3 .030 .916 -.025 .908 -.024 .890
3.1 Partial scalar 2 vs. 3.1 .027 .935 -.006 .927 -.005 .909
4 Factor variances 3.1 vs. 4 .027 .931 -.004 .924 -.003 .905
5 Factor covariances 4 vs. 5 .028 .925 -.006 .922 -.002 .897
12. Comparison of culture scale means
Cz p D p It p
Personal innovativeness
Personal experimenting and originality .27*** <.001 .24*** <.001 .15*** <.001
Work-related innovative behavior
Idea generation .21*** <.001 .22*** <.001 .19*** <.001
Idea search .06 .182 .09* .024 .12** .007
Communicating ideas .08 .075 .16*** <.001 .03 .517
Implementation starting activities .10 .116 .11* .045 -.50*** <.001
Involving others .10 .051 .22*** <.001 .19*** <.001
Overcoming obstacles .10* .029 .08* .037 .01 .841
Innovation outputs .19*** <.001 .30*** <.001 -.09 .053
Support for innovative behaviour
Managerial support (employee-perceived) .19** .005 .37*** <.001 .32*** <.001
Organizational support .14* .024 .21*** <.001 .33*** <.001
Cultural perception of innovative behavior -.09* .016 .09** .005 -.27*** <.001
Notes:
Mean Differences in Innovation Scales (Estimates based on final Scalar Invariance Models)
Switzerland as ‘reference culture’, Italicized values – scale means lower compared to Switzerland, i.e. higher innovation
behavior compared to Switzerland. Significant differences in all scales
Managerial support (manager-perceived) – no scalar invariance achieved
13. Other factors than culture
Age: 8/11 scales, 18-24 x 25-54 x 55-64
Gender: 8/11 scales, men x women
Subordinates: 10/11, with x without
Occupation: 11/11, managers, professionals x clerks
Branch: 9/11, non-profits
Education: 10/11, tertiary – behavior, basic – support scales
Work status: 11/11 employer x self-employed x employee
Firm use of modern technologies: 11/11, high x medium x low
14. Next steps
Comparing our behaviour related data with the data
from the European Social Survey (values) – CZ, D,
CH, IT
Survey in multinational companies in CR
– with German, Italian, and Swiss origin
– 34 companies, 50 management interviews, 434 employee
questionnaires
– focused on innovative behaviour and innovation support
– new scales added: Monitoring implementation process and
Organizational processes for innovation
Survey in Skoda Auto subsidiaries in Russia, India,
China
15. Main conclusions
Swiss were the people with the most innovative behavior, and the
highest innovation support and Germans in many aspects of the
innovation process the least innovative ones.
Czechs and Italians perceived their culture as more innovative than
Swiss and Germans. Italians were more engaged in „implementation
starting activities“
Innovative behaviour differs based on employment status, gender,
occupation, business branch, high vs. low-tech companies, age
There are also other important factors besides culture that influence
innovation outputs - e.g. Intellectual property (EIS, 2008), and
effectiveness of organizational processes in which Germany excels
and CR or Italy lags behind.
16. Thank you for your attention!
Martin Lukeš
University of Economics
Dept. of Managerial Psychology and
Sociology
W. Churchill Sq. 4
130 67 Prague 3
lukesm@vse.cz,
17. Validation efforts
Scales
– Our own scales
– Scales used for validation (en-cz backtranslation)
Jackson Personality Inventory (1994)
Baer, Oldham (2006),
Zhou, George (2001)
Tang (2008)
Howell, Shea, Higgins (2005)
Scott and Bruce (1994)
Howell, Shea, Higgins (2005)
Hornsby, Kuratko (1999)
Graen, Uhl-Bien (1995) - LMX, Schyns, Paul (1999)
Stephan (2008)
Comparing our data with the objective data from
continuous improvement systems (e.g. Continental)