The impact of global values at an individual level on creativity : evidence from Belgium and Italy

THE IMPACT OF GLOBAL VALUES AT AN INDIVIDUAL LEVEL ON CREATIVITY 1
The impact of global values at an individual level on creativity
Evidence from Belgium and Italy.
Joelle Barthel, Tarig Bouazzati and Elimra Seitakhmetova
Solvay Brussels School of Economics and Management
Author Note
This research was made for the EuroMarketing class (GEST-S-510) under the supervision of
Dr. Sandra Rothenberger and Professor Christian Blumelhuber.

Abstract
The purpose of this paper is to analyze the influence of individual global values on the
individual creative output in Italy and in Belgium. So the main objective is to see to what
extend an individual that has a more global culture could be more creative than individuals
who are culturally conservative.
The key results conclude that the GAP, which is defined the difference between a person’s
cultural values and the culture of the country she/he lives in, is found to exert a positive effect
on creativity output
Keywords: creativity, innovation, cultural diversity, Geert Hofstede, Guilford Alternative
Uses Task, Belgium, Italy.

The impact of global values at an individual level on creativity.
Evidence from Belgium and Italy.
In a globalized economy, the relation between creativity1
, innovation and cultural
diversity is a crucial issue. Jean-Paul Agon, CEO and Chairman of L’Oréal, said that “A
diversified workforce in every function and on all levels strengthens our creativity and our
understanding of consumers and it enables us to develop and market products that are
relevant”. Coca-Cola Company has also included global diversity in its 2020 Vision People.
One of its objectives is to build an inclusive workplace environment where the talent of global
team of associates will be leveraged.
According to the European Patent Office, in 2011, the number of granted patents was
of 701 in Belgium and 2286 in Italy. However, expenditures for Research and Development
(public and private) as percentage of GDP amounted for 2.04% in Belgium and 1.25% in Italy
(World Bank Database). Hence, this might suggest that apart from expenditures for R&D
there are other factors that influence the level of innovation in a country (Balachandra &
Friar, 1997).
In this paper, we will examine if there is a link between « individual global values »
and creativity. The « individual global values » represent the gap between a person’s cultural
values and the culture of the country she/he lives in. The more the cultural values differ from
country values, the more the latter are perceived as global or diverse. Creative output has been
chosen as dependent variable because it can have a positive impact on innovation, as we will
show below. Several studies have analyzed the existence of a link between creativity,
innovation and cultural diversity.
Yusuf (2009) analyzed the link between innovation and creativity and the factors,
which influence them. In this study, creativity is expressed through a scientific approach
which goes from innovations to commercial results. From his point of view, innovation is
generated by a creative use of knowledge. Three factors make the creativity higher in a
society: talent quality, culture and wikicaptial2
. Yusuf (2009) argues that wikicapital enables
higher creativity “through the formation of local and global teams, partnerships, associations,
and learning societies that facilitate the deepening and sharing of knowledge and bring
1
“In marketing literature, creativity is widely viewed as actions, processes, and programs that are meaningfully
novel relative to existing practices” (Bharadwaj & Menon, 2000, p. 425)
2
“As the amount of collaboration has intensified, a subfield called ‘‘wikinomics’’ is emerging. It analyzes the
modalities of collaboration and their implications for innovation” (Shahid Yusuf, 2009, p. 4).

together diverse talents with different perspectives, viewpoints, and spheres of knowledge.”
(p.4). He also concluded that innovation hubs are often located in major urban centers which
are highly connected with other world cities and where people and ideas can circulate freely.
Cultural differences and diversity can create superior innovative performance
(Westwood & Low, 2003). Murray (1989) studied the effect of top management heterogeneity
on firm performance. In this study, heterogeneity was characterized by “…the age of
members, their tenure with the firm and with the top management group, as well as their
occupational and educational backgrounds” (p. 129). In the definition of performance he
included the capability to adapt to environmental changes (e.g. create new strategies). Murray
(1989) concluded that demographic heterogeneity within top management teams has a
positive effect on the performance of a company.
McLeod et al. (1996) conducted an experimental study in order to see the influence of
ethnic diversity on creativity. During this experiment, in order to measure people’s creativity,
researchers used a brainstorming task (The tourist Problem). Two types of groups undertook
this brainstorming task. Some groups were composed of only Anglo-Americans and some
groups were composed of Anglo, Asian, African, and Hispanic Americans. The study
concluded that ethnically diverse groups produced better ideas (higher quality, efficiency and
feasibility) than the homogeneous groups.
Kanter (2003) argues that the most innovative companies promote diversity within
their teams. This diversity within the company is mostly characterized by gathering together
people from different departments (cross-functional) and hierarchical level (cross-level). He
suggests that diversity enables the creation of multiple ideas and points of view when dealing
with problems. He also observed that innovative companies perform better in eradicating
discriminations (racism and sexism) than less innovative companies.
Nathan and Lee (2013) conducted an econometric study in order to see the impact of
cultural diversity on London firms’ performance. They defined “…diverse firms…” (p. 370)
as firms with migrant or ethnically mixed owners/partners. Firms with top teams composed
of only U.K. born, only migrant or other minority ethnics are called “…homogeneous
firms…” (p. 370). The analysis is based on a survey of more than 7,600 firms between 2005
and 2007. The study found a small but significant “diversity bonus” (p. 367) for innovation,
market orientation, and entrepreneurship. Nathan and Lee (2013) concluded that the diversity

within the management team has a positive effect on “…the development and implementation
of major new products” (p. 389).
Cox and Blake (1991) argue that when cultural diversity is managed well, it can be a
strong competitive advantage. They believe that “Attitudes, cognitive functioning, and beliefs
are not randomly distributed in the population but tend to vary systematically with
demographic variables such as age, race, and gender. Thus, an expected consequence of
increased cultural diversity in organizations is the presence of different perspectives for
problem solving, decision making and creative tasks” (p. 50). Cox and Blake (1991) defined
diversity as a difference in age, race and gender.
Bassett-‐Jones (2005) has a mixed opinion regarding the benefits of cultural diversity
within a company. He recognizes “...that diversity is … a source of creativity and innovation
that can provide a basis for competitive advantage.” (p. 169). He defined diversity as
differences in ethnicity/nationality, intellectual capability, culture, gender, tenure, function,
ability, language, religion or lifestyle. He also argues that diversity can create some problems
such as “…misunderstanding, suspicion and conflict in the workplace that can result in
absenteeism, poor quality, low morale and loss of competitiveness.” (p. 169). In his view,
companies face a dilemma regarding diversity. Diversity can be associated with competitive
advantage and decrease in efficiency. He concluded that carefully thought human resource
management system can help to better manage diversity.
Most studies based their measurements of ‘cultural diversity’ by taking into
consideration various socio-demographic variables such as - age, gender, education, job and
ethnicity. The purpose of this research paper is to examine if there is a link between
« individual global values » and creativity. We have defined the first one as being the gap
between the cultural values and norms of an individual and the country’s3
culture. Therefore,
we took inspiration from the measurements of the cultural values defined in the Values
Survey Module by Hoofstede et al. (2008). These are the following: power distance,
individuality, masculinity, uncertainty avoidance, long-term orientation, indulgence and
monumentalism.
3
We have made sure that the country of respondents is also the country of their ethnical origins in order not to
bias the research by taking into account the respondents who come from another ethnicity.

Ho: The more an individual is far from the culture values and norms of his country,
the more this individual is creative.
Method
Participants
In total 150 students responded to the online questionnaire. 98 respondents were from
Italy and 52 from Belgium. Their age varies between 19 and 25 years (Mage = 23 for Belgium
and Mage = 22.5 for Italy). All of them were students at either a university in Belgium or in
Italy. For Italy 61 women and 37 men responded compared to 21 women and 31 men in
Belgium. 30 of Belgian and 52 of Italian students were following a scientific education,
whereas 22 Belgian and 46 were students following a non-scientific one. Furthermore, all our
respondents have an ethnicity that corresponds to the one of their country of residence.
Both of our samples exceeded the required sample size to infer our results, which
amounts at 49, for a confidence level of 95% and a precision level of 5%.
With zα/2 =1.96 (for a confidence level of 95%)
σ =0.89 (variance of our first research question)
E= 0.05*5 (With a 5% precision level for a likert-scale of 5)
Research Design
Our research was designed according to the following variables: The dependent
variable was the creativity score calculated for each individual. The independent variables
were defined as the education (scientific and nonscientific), the gender (male and female) and
the GAP, which represents the difference between a person’s cultural values and norms and
the culture of the country she/he lives in. Education and gender were two binary variables
(0=female, 1= male and 0= non-scientific, 1= scientific). The GAP value, a scale, was based
on the difference between the average individual values and its related sample average
values4
, where the sample here was either Italy or Belgium. The creativity score, also a scale
value, was based on the individual’s sum of the four different creative criteria scores. (Figure
1.0)
4
We have considered that the sample is representative of the country

Figure 1.0 The Research Design
Measures
The creativity score was measured by using the Guildford’s Alternative Uses Task
(Bonk, 2003a). Each participant was given one minute in order to brainstorm about different
tasks, which can be done with a newspaper (e.g. “read”, “use as a weapon”). The scoring was
given on four different criteria. Originality – each participant received one point if his idea
was just mentioned once among all the ideas of his sample. Fluency – each participant was
given a point per idea he cited. Flexibility- each contributor received a point per different
category among his ideas (e.g. “read” and “read the news” are the same category, which gives
one flexibility point. “Read” and “tear apart” are different categories, which give two
flexibility scores) Elaboration – a participant received one point for each of his ideas, which
included between one and three words and two points if his ideas contained more than three
words. (e.g. “read” = 0 pts, “read the news” = 1pts, “read the news in the morning” = 2pts).
After the evaluation of the four sections, the respective points were summed up individually
in order to determine the participant’s score of creativity. Small variations could appear in the
scoring. Regarding the factors of originality and flexibility, the evaluation of the ideas was not
obvious for both. Some ideas were similar but a different vocabulary was used. Thus, some
participants might have received a lower score if the evaluation would have been more severe.
The questions for the GAP value were taken from the Value Survey Module 2008
Questionnaire, designed by Hofstede et al. (2008). 28 questions were asked to answer
according to a likert scale between 1 and 5. With the responses of the questionnaire, it was
possible to calculate the following indexes: power distance, individualism, masculinity,

uncertainty, long-term orientation, indulgence versus restraint and monumentalism.
(Appendix 1) According to the formulas on table 1.0 (a), each index was calculated on an
individual and on a country level. By analyzing the impact of each one of the index gaps (the
difference between individual and country level scores) separately, no significance on
creativity was found. Therefore the average of the seven indexes was taken at an individual
level and at a country level in order to provide a unique individual and country score. Finally
the GAP value represents the gap between the average individual scores (AVRi) and the
average country scores (AVRc). For example the AVRi equals 50 and the AVRc equals 70,
the GAP equals ABS(AVRi-AVRc) which is 20. (Table 1.0 (b)) The GAP values should thus
explain to which extend the individual differs from his/her country’s culture by taking the
difference between the individual and country cultural values. A higher GAP should therefore
stand for an individual who has more global (broader) values.
Table 1.0 (a) : Formulas of the seven indexes
Index Formula
The Power Distance Index PDIc = 35*(mq07 – mq02) + 25*(mq23 – mq26)
PDIi = 35*(q07 – q02) + 25*(q23 – q26)
The Individualism Index IDVc = 35*(mq04 – mq01) + 35*(mq09 – mq06)
IDVi = 35*(q04 – q01) + 35*(q09 – q06)
The Masculinity Index MASc = 35*(mq05 – mq03) + 35*(mq08 – mq10)
MASi = 35*(q05 – q03) + 35*(q08 – q10)
The Uncertainty Index UAIc = 40*(mq20 - mq16) + 25*(mq24 – mq27)
UAIi = 40*(q20 - q16) + 25*(q24 – q27)
The Long-Term Orientation LTOc = 40*(mq18 – mq15) + 25*(mq28 – mq25)
LTOi = 40*(q18 – q15) + 25*(q28 – q25)
The Indulgence versus Restraint Index IVRc = 35*(mq12 – mq11) + 40*(mq19 – mq17)

IVRi = 35*(q12 – q11) + 40*(q19 – q17)
The Monumentalism Index MONc = 35*(mq14 – mq13) + 25*(mq22 – mq21)
MONi = 35*(q14 – q13) + 25*(q22 – q21)
(Note: With m= mean, and following number corresponds to the number of the question; e.g mq07 = mean of the
question 7. For individual results, there were no means; only the outcome of the given question was taken in
order to calculate individual scores, e.g q07 = outcome of the question 7 )
Table 1.0 (b): Calculation of the GAP value
AVRi = (PDIi + IDVi + MASi + UAIi + LTOi + IVRi + MONi )/7)
AVRc = (PDIc + IDVc + MASc + UAIc + LTOc + IVRc + MONc )/7)
GAP = ABS(AVRi-AVRc)
(Note: ABS stands for the absolute value)
Finally, questions related to the gender and the type of education of each individual was
included in the survey.
Procedure
A pretest was done before the launch of the survey. Two Italians and two Belgians
were asked to complete the questionnaire in order to see if every question was understood
correctly. Small language modifications were done for the Italian one, as according to the
interviewees the given Italian language version of the VSM08 questionnaire contained some
inappropriate terms or sentence formulations, which made the question too difficult to
understand.
The questions were inserted into a free online survey software, namely Qualtrics.5
The
participants were chosen as randomly as possible, most of them were recruited via social
media platforms such as Facebook, Twitter and Google+. Each participant took around 15min
in order to respond to the questionnaire. Everyone was required to fill out the survey on his
own. No one was compensated for his or her participation and the number of participants
were not limited to a maximum.
5
http://www.qualtrics.com

It should have been noticed, that Guilford’s Alternative Uses Task test was one of the
most suitable to integrate in an online questionnaire. Other creative tests such as the Torrance
Test of Creative Thinking (Bonk, 2003b) could have given more extensive results on
individual creativity but they were inappropriate to test online and/or not possible to include
in the used online survey software.
Results
In this section we will describe the statistical models used in our study and present for
each of the countries selected, the results of the data analysis.
In order to see, if there is a link between cultural values at individual level and the
creative output, we have decided to use a multi linear regression with the stepwise method
and an alpha level of 0.05. The results of the analysis are discussed by comparing Italians
(left) with Belgians (right).
Tables 1.1 Description of the variables means, standard deviations and N (sample size) used
in the multilinear regression model for each country.
Tables 1.2 Correlation coefficients between Creativity, Gender, edu and NG at the individual
level in Italy (left) and Belgium (right).
ITALY BELGIUM

One can notice that the values for each variable are greater in Italy.
Tables 1.2, give the correlations between the GAP (NG), the gender, the creativity and the
type of education (scientific or non scientific) for both countries - Italy (left) and Belgium
(right). One can notice that, in both countries, the highest correlations are between the GAP
(NG), and the creativity at .329 (Italy) and at .411 (Belgium). The latter are also significant at
the .05 level. However, there are no other significant correlations between the variables of the
two models.
Tables 1.3 Models summary
As given in the tables 1.3 that summarize the models, one can observe that both R² adjusted
amount for .099 (Italy) and .169 (Belgium). This value gives us an insight of how much of the
dependent variable’s variance is explained by our independent variables. Thus the higher the
R², the better our model is.
In order to be able to use the results of a multiple regression model, it is important to support
three main hypothesis on the error terms :
1. E() = 0 for all i=1,..,n : this hypothesis is automatically supported due to the insertion
of a constant in our model.
2. Normal distribution of the error terms ∼𝒩: the figures 1.1 and 1.2 give us an insight
on the distribution of the error terms in both samples. As it can be observed, the
distributions in both models are close to a Normal distribution. However the figures
1.2 indicate that in the error terms for the Belgian sample approach less a normal
distribution than the Italian one. This might be due to the fact that the Belgian sample
is smaller. Meanwhile, both tests allow us to think that the hypotheses on a normal
distribution of error terms are verified. The consequences of non-compliance of the

latter would have been that we could not use the Fisher test. Considering the size of
both samples (N>30) the Fisher tests are valid.
3. Non auto-correlation cov() = 0 for ⩝i : in order to verify this test, we had to conduct a
Durbin-Watson test, with a significant level at .20, on both samples. This test
indicates that the closer the DW value is to 2, the higher is the likelihood we have to
reject the H₀ : cov() ≠ 0. In both of our models, the DW are close to 2 as one can
observe in the last column of the tables 1.3.
4. Homoscedasticity var() = for ⩝i : in order to support this hypothesis of
homoscedasticity we analyze the Q-Q plot and the distribution of the error terms on
the graph. The less structured the scatter plot is, the higher is the likelihood of
supporting homoscedasticity hypothesis. One can notice by observing Figures 1.3 that
in both samples, the scatter plots are randomly distributed and that the variances are
almost constants, verifying thus the assumption of homoscedasticity.
Figures 1.1 Histogram of the variables distribution in our model following
a Normal distribution

As the four basic hypotheses on error terms are supported, we will now start to analyze the
robustness of the variables that are significant in our models. As given in the table 1.4, one
can notice that Fisher tests are significant in both models. This indicates that at least one
independent variable of our model is significantly explaining the dependent variable
creativity.
Figures 1.2 P-P Plot comparing standardized residuals
distribution with a normal distribution
Figures 1.3 Q-Q Plot. The scatter plot shows the variance of
standardized residuals

The regression method we have used in this research is the stepwise one. This method is a
mix between the forward and the backward method. It adds independent variable one by one
as long as the latter is significant in the model at .05. In our model, one can notice that the
only exogenous significant variable for both countries (tables 1.5) is the NG (cultural gap).
The two other exogenous variables - Gender and edu, were rejected by the model (tables 1.6).
Tables 1.4 Fisher tests of our models for Italy (top) and
Belgium (bottom)
Tables 1.5 Coefficients values of the exogenous variables that are
significant in our stepwise multi regression models for Italy (top) and
Belgium (bottom)

The coefficients of the only significant exogenous variable amour for - B = .329 (Italy) and B
= .411 (Belgium).
Discussion
In this section we will discuss the results obtained throughout our models. As a reminder, the
purpose of this research paper was to see to which extent the individual « culture » impacts
the creative output in Italy and in Belgium and finally to see if there is a difference between
the two countries. As stated in the previous section, the only exogenous variable that is
statistically significant to explain the creativity, given the education type and the gender, was
the GAP (NG). The GAP, as already mentioned, represents the gap between the individual «
culture » and the country’s culture. Therefore, our basic hypothesis to support was: the more
an individual is far from the cultural values and norms of his country, the more this individual
is creative. One can notice that the latter is in fact supported by our models. Indeed, the
models predict that a variation of GAP (NG) of one unity (NG=1) is associated with a
variation of .329 unity of creativity in Italy and a variation of .411 in Belgium. Thus, higher
GAP (NG) would have a bigger impact on creativity in Belgium.
Despite the fact that our main hypothesis is supported in both countries, we would like to
qualify these results. In fact, the impact of personal culture on the creative output seems
disproportionate to us. Regarding the values of the R² adjusted values for both models, we
could assume that these values are actually a lot exaggerated and clearly illustrate the
limitations of our models. As our statistical model only explains 9.9% (Italy) and 15.2%
(Belgium) of the creativity’s variance, we can consider that this model is not really strong.
Tables 1.6 Coefficients values of the exogenous variables that are
significant in our stepwise multi regression models for Italy (top) and
Belgium (bottom)

Thus, the interpretation of the results could become non relevant. Furthermore, the GAP
variable includes a lot of dimensions that are basically defined to measure the culture of a
country (anthropology) and are not properly designed to fit the personal cultural values and
norms (psychology). Therefore, it is hard to clearly determine the impact of the cultural
influences on an individual on his/her creative output throughout our definition of GAP.
However, once the limitations of our model described and the interpretation contextualized, it
remains interesting to note that there might be a real impact of personal cultural values and
norms on individual creative output. Thus, this creative approach could be a good start to
design more socially anchored studies to explore deeply the nourishing sources of creativity.

References:
SCIENTIFIC PAPERS
Balachandra, R., & Friar, J. H. (1997). Factors for success in R&D projects and new product
innovation: a contextual framework. Engineering Management, IEEE Transactions on, 44(3),
276-287.
Bassett-‐Jones, N. (2005). The paradox of diversity management, creativity and
innovation. Creativity and innovation management, 14(2), 169-175.
Bharadwaj, S., & Menon, A. (2000). Making innovation happen in organizations: individual
creativity mechanisms, organizational creativity mechanisms or both?. Journal of product
innovation management, 17(6), 424-434.
Cox, T. H., & Blake, S. (1991). Managing cultural diversity: Implications for organizational
competitiveness. The Executive, 45-56.
Kanter, R. M. (2003). Challenge of organizational change: How companies experience it and
leaders guide it. Simon and Schuster.
McLeod, P. L., Lobel, S. A., & Cox, T. H. (1996). Ethnic diversity and creativity in small
groups. Small group research, 27(2), 248-264.
Murray, A. I. (1989). Top management group heterogeneity and firm performance. Strategic
Management Journal, 10(S1), 125-141.
Nathan, M., & Lee, N. (2013). Cultural Diversity, Innovation, and Entrepreneurship: Firm-‐
level Evidence from London. Economic Geography,89(4), 367-394.
Westwood, R., & Low, D. R. (2003). The multicultural muse culture, creativity and
innovation. International Journal of Cross Cultural Management, 3(2), 235-259.
Yusuf, S. (2009). From creativity to innovation. Technology in Society, 31(1), 1-8.

OTHERS
Bonk, C. (2003a). Creativity Tests: Guilford‟s Alternative Uses Task (1967). Indiana
University: school of education: department of educational psychology, retrieved the 12th of
April, 2014, available at http://www.indiana.edu/~bobweb/Handout/sub/Bob_CT_Uses.html
Bonk, C. (2003b). Creativity Tests: Torrance Tests of Creative Thinking (1962). Indiana
University: school of education: department of educational psychology, retrieved the 12th of
April, 2014, available at
http://www.indiana.edu/%7Ebobweb/Handout/sub/Bob_CT_Torrance.html
Hofstede, G., Hofstede,G. J., Minkov, M., Vinken, H., Values Survey Module 2008, Manual,
VSM08, retrieved the 29 of March, 2014, available at http://www.geerthofstede.eu/vsm-08
Hofstede, G., Hofstede,G. J., Minkov, M., Vinken, H., Values Survey Module 2008,
Questionnaire, VSM08, English language version and Italian language version, retrieved the
29 of March, 2014, available at http://www.geerthofstede.eu/vsm-08
L’Oreal, retrieved the 29 of March, 2014, available at http://www.loreal.com/csr-
commitments/diversities.aspx
The Coca Cola Company, L’Oreal, retrieved the 29 of March, 2014, http://www.coca-
colacompany.com/our-company/diversity/global-diversity-mission

APPENDIX:
Table 1: Index and their definition
INDEX MEANING
Power Distance Index (PDI) Power Distance is defined as the extent to which the less powerful members of
institutions and organizations within a society expect and accept that power is
distributed unequally.
Individualism Index (IDV) Individualism is the opposite of Collectivism. Individualism stands for a society in
which the ties between individuals are loose: a person is expected to look after
himself or herself and his or her immediate family only. Collectivism stands for a
society in which people from birth onwards are integrated into strong, cohesive in-
groups, which continue to protect them throughout their lifetime in exchange for
unquestioning loyalty.
Masculinity Index (MAS) Masculinity is the opposite of Femininity. Masculinity stands for a society in which
social gender roles are clearly distinct: men are supposed to be assertive, tough, and
focused on material success; women are supposed to be more modest, tender, and
concerned with the quality of life. Femininity stands for a society in which social
gender roles overlap: both men and women are supposed to be modest, tender, and
concerned with the quality of life.
Uncertainty Avoidance Index
(UAI)
Uncertainty Avoidance is defined as the extent to which the members of institutions
and organizations within a society feel threatened by uncertain, unknown,
ambiguous, or unstructured situations.
Long Term Orientation Index
(LTO)
Long Term Orientation is the opposite of Short Term Orientation. Long Term
Orientation stands for a society which fosters virtues oriented towards future
rewards, in particular adaptation, perseverance and thrift. Short Term orientation
stands for a society which fosters virtues related to the past and present, in particular
respect for tradition, preservation of “face”, and fulfilling social obligations.
Indulgence versus Restraint Index
(IVR)
Indulgence stands for a society which allows relatively free gratification of some
desires and feelings, especially those that have to do with leisure, merrymaking with
friends, spending, consumption and sex. Its opposite pole, Restraint, stands for a
society which controls such gratification, and where people feel less able to enjoy
their lives.
Monumentalism Index (MON) Monumentalism stands for a society which rewards people who are, metaphorically
speaking, like monuments: proud and unchangeable. Its opposite pole, Self-
Effacement, stands for a society which rewards humility and flexibility. The
Monumentalism Index will probably be negatively correlated with the Long Term
Orientation Index, but it includes aspects not covered by the latter.
Source: Hofstede et al.(2008)

Table 2: Calculation of the variables for the Belgian model
Calculation of the country’s average score (The Belgian AVRc)
Calculation of the individual GAP score (The GAP (NG))
Note: GAP= ABS(AVRi-AVRc)
Question number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Reponse 1 13 7 13 8 18 28 10 4 2 6 14 0 9 3 18 3
Response 2 27 33 30 23 27 20 26 22 13 22 27 11 22 14 28 18
Response 3 7 9 7 14 5 2 13 18 18 18 9 23 15 18 6 19
Response 4 4 1 0 4 0 0 2 5 13 5 1 13 5 13 0 10
Response 5 1 2 2 2 2 2 1 3 6 1 1 5 1 4 0 2
Total responses 52 52 52 51 52 52 52 52 52 52 52 52 52 52 52 52
Score 109 114 104 122 97 84 114 137 164 129 104 168 123 157 92 146
Mean Score 2.10 2.19 2.00 2.39 1.87 1.62 2.19 2.63 3.15 2.48 2.00 3.23 2.37 3.02 1.77 2.81
Question number 17 18 19 20 21 22 23 24 25 26 27 28 PDIc 14.42
Reponse 1 7 8 1 13 0 4 2 6 20 5 2 6 IDVc 64.21
Response 2 31 25 11 22 2 6 5 33 28 16 10 17 MASc 0.67
Response 3 9 6 27 13 10 19 15 9 2 17 17 22 UAIc (51.63)
Response 4 5 6 12 4 6 17 29 4 1 10 20 6 LTOc 52.35
Response 5 0 6 1 0 34 6 1 0 1 4 3 1 MONc (4.52)
Total responses 52 51 52 52 52 52 52 52 52 52 52 52 IVRc 74.62
Score 116 130 157 112 228 171 178 115 91 148 168 135 TOT 150.11
Mean Score 2.23 2.55 3.02 2.15 4.38 3.29 3.42 2.21 1.75 2.85 3.23 2.60 AVRc 21.44
IP Adress PDI IDV MAS UAI LTO MON IVR TOTAL AVRi GAP (NG)
109.128.139.21 0 70 70 -105 65 -110 -75 -85 (12.14) 33.59
109.128.139.21 60 105 -70 -50 185 -35 110 305 43.57 22.13
109.128.75.3 -35 140 0 -195 -130 45 220 45 6.43 15.02
109.129.147.93 0 70 35 -40 40 -30 -80 -5 (0.71) 22.16
109.89.161.25 50 35 70 10 145 -85 110 335 47.86 26.41
109.89.235.18 -50 105 -35 -40 55 -15 110 130 18.57 2.87
122.149.172.69 40 35 35 -50 25 45 105 235 33.57 12.13
130.82.245.238 85 70 -35 -145 50 -50 110 85 12.14 9.30
130.88.99.221 25 70 35 -65 -15 20 115 185 26.43 4.98
141.134.29.127 -35 0 35 30 145 165 30 370 52.86 31.41
158.64.104.243 -35 70 -35 75 0 10 115 200 28.57 7.13
164.15.117.129 -25 70 105 -50 75 -50 40 165 23.57 2.13
164.15.117.232 -35 140 -35 -105 10 25 155 155 22.14 0.70
164.15.41.240 60 35 105 -105 120 -85 -5 125 17.86 3.59
176.241.11.159 50 175 -35 -40 0 0 110 260 37.14 15.70
179.52.30.103 15 70 0 -50 50 145 115 345 49.29 27.84
187.187.179.135 85 35 0 -90 75 -25 145 225 32.14 10.70
190.18.158.51 -60 105 -35 -70 65 -25 155 135 19.29 2.16
195.46.228.75 -50 210 70 -160 90 10 115 285 40.71 19.27
195.46.241.230 -85 35 0 -115 50 5 80 -30 (4.29) 25.73
207.244.77.3 60 70 35 -50 90 -50 110 265 37.86 16.41
212.68.223.119 75 -35 35 -10 105 45 25 240 34.29 12.84
212.68.252.129 110 105 -70 -90 65 -15 110 215 30.71 9.27
217.136.40.90 120 0 35 -10 65 15 75 300 42.86 21.41
37.62.28.244 0 -35 35 15 40 35 -5 85 12.14 9.30
62.235.186.195 50 35 0 -105 -15 60 110 135 19.29 2.16
62.235.228.243 -10 0 0 95 80 -25 -35 105 15.00 6.44
77.109.96.208 50 105 -35 -50 90 45 180 385 55.00 33.56
78.129.57.160 25 35 -35 -65 0 -25 115 50 7.14 14.30
80.223.250.84 60 175 -105 -90 0 -60 40 20 2.86 18.59
81.245.231.164 -95 35 -35 -65 65 25 115 45 6.43 15.02
83.134.186.207 -45 -35 0 -80 35 20 120 15 2.14 19.30
83.217.147.6 35 140 0 -65 25 -35 110 210 30.00 8.56
83.99.17.154 25 70 -70 120 120 -50 -115 100 14.29 7.16
83.99.94.148 0 0 0 -95 0 35 110 50 7.14 14.30
84.17.25.210 -15 70 -35 25 -25 35 0 55 7.86 13.59
84.198.123.45 50 35 35 -105 90 -120 75 60 8.57 12.87
85.27.13.18 35 35 0 55 145 -145 -80 45 6.43 15.02
85.27.16.96 -25 70 0 55 90 -15 -115 60 8.57 12.87
85.27.18.87 -35 70 -35 -90 -15 -15 -5 -125 (17.86) 39.30
85.27.18.87 60 -35 70 -50 -15 -10 -35 -15 (2.14) 23.59
87.66.55.234 35 70 0 -10 15 35 110 255 36.43 14.98
87.66.92.137 75 70 70 -130 -25 -75 185 170 24.29 2.84
91.177.164.133 50 0 0 -40 120 0 40 170 24.29 2.84
91.177.52.137 25 35 35 -65 0 10 110 150 21.43 0.02
91.178.164.100 35 105 -35 -90 25 35 35 110 15.71 5.73
91.182.207.252 35 70 35 -105 25 10 155 225 32.14 10.70
91.182.215.192 35 0 -70 -25 40 45 0 25 3.57 17.87
91.183.59.174 -170 105 -105 -65 145 90 145 145 20.71 0.73
92.109.44.139 -35 35 35 -35 50 -40 0 10 1.43 20.02
94.252.13.213 50 140 -35 -55 40 20 300 460 65.71 44.27
25 70 0 -50 50 -75 115 135 19.29 2.16

Evaluation of the individual creativity scores
Note: The fields coloured in grey are those with original ideas (only mentioned once among the sample). The
words written in red are those, where the participant mentioned two ideas originating from the same category (In
this case, the flexibility score is lower than the fluency score)
V6 Q27_1_TEXT Q27_2_TEXT Q27_3_TEXT Q27_4_TEXT Q27_5_TEXT Q27_6_TEXTQ27_7_TEXT
IPAddress What can be done with a newspaper (e.g. create a hat)-Click to write Choice 1What can be done with a newspaper (e.g. create a hat)-Click to write Choice 2What can be done with a newspaper (e.g. create a hat)-Click to write Choice 3What can be done with a newspaper (e.g. create a hat)-Click to write Choice 4What can be done with a newspaper (e.g. create a hat)-Click to write Choice 5What can be done with a newspaper (e.g. create a hat)-Click to write Choice 6What can be done with a newspaper (e.g. create a hat)-Click to write Choice 7ORIGINALITY FLUENCY FLEXIBILITY ELABORATION TOTAL
read sudoku 1 2 2 0 5
85.27.18.87 0 0 0 0 0
85.27.18.87 cover snow cover rain read stuff put shoes 1 4 3 4 12
87.66.55.234 a boat something to dry shoes eventail gossip about the stars 2 4 4 5 15
179.52.30.103 throw at my sister read emballage cado 1 3 3 3 10
91.182.215.192 lire support table voir news jouer foot 0 4 3 3 10
109.128.75.3 be read be folded cut thrown away 0 4 4 3 11
109.128.139.21 heat ass beat cheat 1 3 3 1 8
81.245.231.164 sun protection read news crosswords fold tear up 2 5 5 3 15
109.129.147.93 bricoler remettre la table droite lire 0 3 3 2 8
85.27.13.18 read boat dry shoes 0 3 3 1 7
109.128.139.21 use as a torch information use for barbecue sit on fold dry shoes 1 6 6 4 17
195.46.241.230 read tear apart play fold 0 4 4 1 9
37.62.28.244 chapeau bricoler décorer 0 3 3 0 6
84.198.123.45 built big ship 0 1 1 1 3
164.15.117.129 hat boat ship 0 3 3 0 6
91.178.164.100 décoration sécher chaussures lire battre chapeau batea 0 6 5 1 12
91.183.59.174 Spank Read Fold Cutting Learn Inform 0 6 5 0 11
207.244.77.3 support for food read 0 2 2 1 5
109.89.235.18 binocular burn hat basketball football cover against rain 1 6 5 1 13
217.136.40.90 put my shoes in bus read the news 1 1 1 3 6
87.66.92.137 ta mère 1 1 1 1 4
91.182.207.252 read make fire fold 0 3 3 1 7
62.235.186.195 boat curtain mat mattress 2 4 3 0 9
141.134.29.127 read dry shoes sports finance 0 4 4 1 9
187.187.179.135 exercise foreign language read make ship 1 3 3 2 9
195.46.228.75 sponge water read information origami bricolage 2 4 4 2 12
212.68.223.119 wrap up gift wrap up precious 0 2 1 2 5
164.15.117.232 ? 0 0 0 0 0
78.129.57.160 wash the Windows make a fit 1 2 2 2 7
164.15.41.240 0 0 0 0 0
94.252.13.213 read pack stuff stack paper aeroplane fold into small pieces 1 5 5 4 15
85.27.16.96 beat throw do something 0 3 2 1 6
83.217.147.6 built mask read weapon 1 3 3 1 8
83.134.186.207 read draw folding hat 0 4 4 0 8
130.82.245.238 finance news hat ship glasses mask 0 5 5 1 11
91.177.52.137 fire maker wrap potatoes 1 2 2 2 7
92.109.44.139 read burned folded cracked pied on 1 5 4 1 11
80.223.250.84 aeroplane cover read 0 3 3 0 6
176.241.11.159 create a boat start a fire wrap a fragile item cr 0 4 3 4 11
84.17.25.210 reading drawing on draw people 2 3 2 2 9
130.88.99.221 make jokes read news 1 2 2 2 7
83.99.94.148 Hold table Stick door Hide something 1 3 3 3 10
109.89.161.25 thrwo away old food package the fish small boat 2 3 3 4 12
122.149.172.69 keep as news are significant souvenir 2 2 2 2 8
190.18.158.51 Mosquto breaker Cast Read 1 3 3 1 8
77.109.96.208 read hit ship hat 0 4 4 0 8
158.64.104.243 decoration make stuff 0 2 2 1 5
62.235.228.243 news sport culture 1 3 3 0 7
212.68.252.129 reading 0 1 1 0 2
83.99.17.154 wrap up glasses decoration burn fire cover 0 4 4 2 10
91.177.164.133 toiletpaper notebook hat 1 3 3 1 8
EVALUATION

Summary of the values used for the Belgian model
IP Adress GAP (NG) Gender Education Creativity score
109.128.139.21 33.59 0 1 8
109.128.139.21 22.13 0 1 17
109.128.75.3 15.02 1 0 11
109.129.147.93 22.16 1 1 8
109.89.161.25 26.41 0 1 12
109.89.235.18 2.87 1 1 13
122.149.172.69 12.13 1 1 8
130.82.245.238 9.30 0 1 11
130.88.99.221 4.98 0 1 7
141.134.29.127 31.41 1 1 9
158.64.104.243 7.13 0 1 5
164.15.117.129 2.13 0 1 6
164.15.117.232 0.70 0 1 0
164.15.41.240 3.59 1 1 0
176.241.11.159 15.70 1 1 11
179.52.30.103 27.84 0 1 10
187.187.179.135 10.70 1 1 9
190.18.158.51 2.16 1 1 8
195.46.228.75 19.27 0 0 12
195.46.241.230 25.73 1 1 9
207.244.77.3 16.41 1 1 5
212.68.223.119 12.84 0 1 5
212.68.252.129 9.27 1 1 2
217.136.40.90 21.41 1 0 6
37.62.28.244 9.30 1 1 6
62.235.186.195 2.16 1 1 9
62.235.228.243 6.44 0 1 7
77.109.96.208 33.56 1 0 8
78.129.57.160 14.30 1 0 7
80.223.250.84 18.59 1 1 6
81.245.231.164 15.02 0 0 15
83.134.186.207 19.30 1 0 8
83.217.147.6 8.56 0 1 8
83.99.17.154 7.16 0 0 10
83.99.94.148 14.30 0 1 10
84.17.25.210 13.59 0 0 9
84.198.123.45 12.87 1 1 3
85.27.13.18 15.02 1 1 7
85.27.16.96 12.87 1 1 6
85.27.18.87 39.30 1 1 12
85.27.18.87 23.59 1 1 0
87.66.55.234 14.98 0 0 15
87.66.92.137 2.84 0 1 4
91.177.164.133 2.84 1 1 8
91.177.52.137 0.02 0 1 7
91.178.164.100 5.73 0 1 12
91.182.207.252 10.70 1 1 7
91.182.215.192 17.87 0 1 10
91.183.59.174 0.73 0 0 11
92.109.44.139 20.02 0 1 11
94.252.13.213 44.27 0 0 15
2.16 0 1 5

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