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Modelling and Measuring Innovation Culture
Muriel Davies and Stéphanie Buisine
CESI, LINEACT, Nanterre, France
mdavies@cesi.fr
sbuisine@cesi.fr
Abstract: We aim to provide a conceptual model of innovation culture in organizations and build a survey tool
to measure it. Innovation management focuses often on formalized processes whereas unwritten rules related
to organizational culture are also a major factor for innovation and firms’ performance. We first position the
role of culture with regard to innovation processes, then provide a model of innovation culture relying on five
branches (External links, Teams, Organizational context, Individuals, and Leaders). Following the elaboration of
this model called ETOILe, we address the issue of measuring it. In this paper, we focus on the less-known
components such as External Links and design an ad hoc questionnaire.
The validation study is performed through a laboratory test with 115 professional participants followed by
reliability analysis of data and principal components analysis. The results of the study enabled us to refine the
diagnosis tool as well as the underlying model of innovation culture. The current version includes four
branches (Team, Organization, Individuals, Leaders) and ten sub-dimensions including promotion and
prevention regulatory focus, managerial practices, discovery and delivery skills, etc.
Because of its implicitness and intangibility, culture is often disregarded in the analysis of key ingredients of
firms’ performance. Our model of innovation culture gathering such unwritten rules contributes to
understanding why innovation is so natural and efficient in some companies, and why it is sometimes painful,
despite robust managerial structure and methodological processes. Finally, we provide a diagnosis tool
intended for all hierarchical levels of the organization, and not only for managerial staff. Our model and tool
could be used at several levels: at the company’s level to grasp the overall cultural profile, at the department
or team level to assess differences in innovation culture between subdivisions in a given company, and at a
trans-company level to characterize cultural differences associated to business sectors (e.g., manufacturing
sector, consulting sector, retail sector).
Keywords: Organizational culture, Innovation, Survey
1. Innovation as a driver of firms’ performance
Innovation is considered as central to solve the major problems of societies (e.g., social and demographic
challenges, climate change) while still supporting economic growth. In the long term, innovation is believed to
fuel society’s transformation towards more wellbeing and more prosperity (OECD, 2016). However, the
concept of innovation is polysemous in itself (Battistelli, 2014; Beylat and Tambourin, 2013). The last version of
the Oslo Manual defines innovation as a result (new or improved product or process differing significantly
from the unit’s previous products or processes and made available to potential users or brought into use;
OECD, 2018). However, measuring innovation remains a challenge, as existing assessment tools still mix
outcomes and process indicators (Edquist et al, 2018; European Commission, 2018). Furthermore, in our view,
a third side, namely innovation culture, is missing to gain a complete view of firms’ innovation.
We model innovation factors through an analogy with the interactionist paradigm known as the Lewin
equation (Lewin, 1936), which models human behaviour (B) as the result of interactions between personal
characteristics (P) and situational features (S): B = f(P,S). In our case, the target is innovation performance. The
situational features may correspond to all observable innovation rules that were formalized as a process, or a
framework to innovate. The personal characteristics, in the case of an organization, may refer to implicit
cultural features influencing innovation. We therefore model innovation as follows:
Innovation performance = f(innovation culture, innovation process).
Both process and culture define how people act in firms, but they are fundamentally different: we consider
that innovation process gathers rules that are explicit, and usually written, whereas innovation culture refers
to the rules that are implicit and seldom officially described. Culture and process may be independent
orthogonal dimensions that are not necessarily consistent within a given organization. One can imagine an
organization with formalized processes regarding innovation activities, but a culture inhibiting innovative
thinking at the same time. Conversely, some organizations may possess a culture prone to innovation but weak
innovation processes structuring these activities. The aim of this paper is to set out the basis for a model of
innovation culture and a method to assess it. The other terms of the equation (innovation performance and
innovation process) are usually approached through declarative, objective or observational data.
Culture constitutes the unwritten rules of the social game (Hofstede et al, 2010). Organizational culture may
mainly rely on practices: people gathered for work come with their own values that can hardly be changed, but
they can adopt common symbols, heroes and rituals. In line with this approach, we consider organizational
culture as a set of habits, behaviours, and representations shared by its members (Davies and Buisine, 2018).
Innovation culture is a particular configuration that makes innovative thinking natural within the organization
and encourages innovation activities at all levels of the organization.
Two dimensions of national culture may particularly influence innovation process, namely power distance and
uncertainty tolerance (Hofstede, 2016; Hofstede et al, 2010; Chai and Xiao, 2018; He and Lee, 2020).
Innovation is encouraged by a low power distance and a high level of tolerance for uncertainty (Hofstede et al,
2010). An organization’s culture may also depend on its stage of evolution (Laloux, 2015). According to this
evolutionary model, Amber (i.e., conformist and stable structures with well-defined functions and processes,
like many public administrations) and Orange organizations (which promote innovation, responsibility, and
meritocracy, like many multinationals) are predominant in today's society. More recent and marginal forms of
organizations are named Green (fostering empowerment, inclusiveness, and meaningfulness) and Teal (based
on self-management, wholeness, and evolutionary purpose, or reason for being). The Orange stage flourished
with the development of industry and resulted in an innovation strategy mainly driven by economic
performance. Green organisations will stress environmental and social innovation, and Teal ones will
emphasize the societal impact and sense of purpose in innovation activities.
2. Building a model of innovation culture
Innovation culture has specific characteristics that can be observed from five viewpoints. The first one is the
presence of innovative leaders and managers. The most innovative organizations are led by innovators who
are equipped with high discovery skills (e.g., who have created new products, and believe they can change the
world; Christensen et al, 2013). Leaders have a central role to play in supplying all company departments with
innovative individuals (Christensen et al, 2013) and in encouraging staff creativity (Amabile et al, 1996;
Mathafena and Grobler, 2021). Leaders and managers are therefore key to approaching an organization's
innovation culture.
Innovation culture is also implemented at teams’ level (Barnhill, Smith and Oja, 2021). Promotion-oriented
teams (seeking benefits aimed at an ideal, as opposed to prevention-oriented teams focused on avoidance of
losses) perform better on idea generation and diffusion (Rietzschel, 2011). In addition, innovative teams gather
individuals with complementary skills, some excelling in discovery skills (Christensen et al, 2013), others with
good communication, openness to new ideas, ability to challenge, trust, and help each other (Amabile et al,
1996). To enhance team’s capacity to innovate, it is recommended to increase its diversity (Jones et al, 2020;
Park et al., 2021).
The third level of innovation culture is supported by innovative individuals (Volery and Tarabashkina, 2021)
exhibiting higher discovery skills (Christensen et al, 2013). Among factors contributing to innovation culture,
Dobni (2008) identified several individual characteristics such as empowerment, freedom, creativity and
commitment to the innovation process. In addition, the results of work engagement surveys also suggest that
there is a direct link between individual engagement and firm-level innovation (Gallup, 2013). Engaged
individuals are those who work with passion, in accordance with their company’s vision. They stimulate
innovation and are strong driving forces.
Innovation culture can also be inferred from how external links are managed (Fu, 2022). Networking is one of
the discovery skills (Dyer et al, 2008). In innovative companies (Christensen et al, 2013), one will find this skill
at all levels (individuals, teams, management), to develop both internal relationships inside the company and
external relationships outside. Innovation culture is characterised by numerous and easy relationships with the
outside (Cameron and Quinn, 2011; Hwang and Horowitt, 2012). In Laloux’ model (2015), organizations
develop a specific type of external relationship at each stage of evolution. At the Amber stage, the
organization seeks to have no connection with the outside world, wants to be self-sufficient and aims for
monopoly. Others are suspicious. In the Orange stage, competition reigns. Others are rivals, and you have to
be better than them. With the Green stage, justice, equality, and harmony are sought with stakeholders,
shareholders, management, employees, civil society and nature. Others are valuable partners. With the Teal
stage, the organization integrates humans as a whole; each relationship is possibly fruitful, whether internal or
external. Borders of the company tend to disappear. Thus, depending on the type of organization, external
relationships can be denied, suspected, or trusted. In highly innovative start-up companies (Hwang and
Horowitt, 2012), relationships with the external environment favouring innovation have three characteristics:
first, a benevolent view of the external environment, then a multiplicity and variety of internal/external
contact points, and finally the ease and speed of setting-up collaborations.
The fifth level of innovation culture is the organizational context in itself (Nani and Safitri, 2021). For
Christensen et al (2013), innovative companies are characterised by a general philosophy that includes four
principles: Innovation is everyone's business, disruptive innovation is central, small and structured project
teams are preferred, intelligent risks are taken. Most of the key factors proposed by Dobni (2008) to evaluate
innovation culture are related to organizational context and philosophy of action: social representation of
innovation, organizational learning capacity, market orientation (product, customer, competitor), value
orientation, and agile and flexible context. Another school of thought focuses on the work environment, and
how it enables and promotes innovation (Amabile et al, 1996; Amabile and Kramer, 2011; Amabile and Pratt,
2016). A work environment which will enable innovation is characterized by the absence of organizational
obstacles, meaningful work, a good level of challenge for everyone, and motivation to innovate. Hwang and
Horowit (2012) compare the Silicon Valley with the Amazonian forest (hence the title of their book, The
Rainforest). This model implies that innovation would occur preferentially in luxuriant contexts, rich in
exchanges, and would often emerge from "weeds" that develop spontaneously without having been expected
or encouraged. This image contrasts with that of the field (planted with “seeds”), with a well-defined process,
everything all lined up, in which weeds are regularly eliminated. A parallel could be drawn with Laloux's (2015)
model: When innovation is natural, it does not need a formalized process, it develops no matter what
happens, like a weed.
3. The ETOILe model
We gather these insights from the literature in a model called ETOILe, which stands for External links, Team,
Organization, Individuals and Leaders. The word “étoile” also means “star” in French, which seems appropriate
to refer to innovation. Table 1 summarizes the aforementioned references used to ground this model.
Table 1: Innovation culture model ETOILe sources.
Branches
References
E
External links
(Amabile et al, 1996; Amabile and Pratt, 2016; Cameron and Quinn, 2011;
Christensen et al, 2013; Fu, 2022 ; Hofstede et al, 2010; Laloux, 2015 )
T
Innovative Team
(Amabile et al, 1996; Barnhill, Smith and Oja, 2021 ; Christensen et al,
2013; Rietzschel, 2011 )
O
Organization context
(Amabile et al, 1996; Amabile and Pratt, 2016; Cameron and Quinn, 2011;
Dobni, 2008; Hofstede et al, 2010; Hwang and Horowitt, 2012; Laloux,
2015; Nani and Safitri, 2021)
I
Innovative Individuals
(Amabile et al, 1996; Amabile and Kramer, 2011; Amabile and Pratt, 2016;
Christensen et al, 2013; Dobni, 2008; Gallup, 2013; Hwang and Horowitt,
2012; Volery and Tarabashkina, 2021)
Le
Innovative Leaders and
managers
(Amabile et al, 1996; Amabile and Pratt, 2016; Cameron and Quinn, 2011;
Christensen et al, 2013; Hofstede et al, 2010; Laloux, 2015 ; Mathafena
and Grobler, 2021)
On the basis of this model we designed a tool to diagnose innovation culture, as elaborated in the following
section.
4. Diagnosing innovation culture
4.1 Design of the questionnaire
The questionnaire we built actually addressed only four branches of the ETOILe model, namely External links,
Team, Organization and Individuals. The Leader’s branch was disregarded for several reasons. First, our
preliminary investigations on the issue of evaluating leadership in organizations suggested that it was a
sensitive matter. Therefore, leadership evaluation may be highly prone to a social desirability bias. Secondly,
the literature regarding leadership style evaluation is already abundant and we felt it was not necessary to
build a new tool on this topic. For example, the MLQ (Multifactor Leadership Questionnaire; Bass et al, 2003) is
a validated and widely used tool to do so.
The questionnaire we designed draws on existing scales measuring sub-dimensions of the ETOILe model. Table
2 details the sub-dimensions included, the relevant references, the total number of items selected for each
sub-dimension, and an example of these items. Some items were directly extracted from existing validated
scales; others were translated, rephrased, or written by us, which further justifies that a laboratory validation
was required. The final questionnaire was written in French.
Table 2: Innovation culture questionnaire sources.
Branches of the
ETOILe model
Sub-dimensions
References
Item’s examples
Number
of
questions
E
External links
Outward-links:
multiplicity and
diversity of relations
with the external
environment
(Bertelli et al, 2016;
Hwang and Horowitt,
2012; Mercan and
Goktas, 2011)
“In my company, I can
easily and quickly launch
a project with external
partners.”
8
T
Team
Encouragement to
use discovery skills
(Christensen et al,
2013)
“We are encouraged to
ask questions even if it
means changing habits.”
5
Promotion regulatory
focus
(Rietzschel, 2011)
To which extend this
proverb is
representative of your
work team:
“Nothing ventured,
nothing gained.”
9
Prevention regulatory
focus
(Rietzschel, 2011)
To which extend this
proverb is
representative of your
work team: “Prevention
is better than cure.”
9
O
Organization
Significance of
innovation
(Dobni, 2008)
“In my company, we
invent and propose new
products and services.”
5
Focus on products and
customers
(Dobni, 2008)
“In my company, every
employee knows the
customers and their
needs.”
4
Managerial practices:
position with regard
to Laloux’ model
(Amber, Orange,
Green and Teal
stages)
(Laloux, 2015)
“In my company, leaders
are mainly focused on
short-term objectives.”
12
I
Individuals
Engagement
(Gallup, 2013)
“There is someone at
12
work encouraging my
development”
Discovery skills
(Christensen et al,
2013)
“I often experiment new
methods.”
10
Delivery skills
(Christensen et al,
2013)
“I am extremely careful
to avoid mistakes in my
job”
10
Demographics
Age, gender, tenure
6
4.2 Laboratory test
4.2.1 Hypotheses
In order to validate our questionnaire, we hypothesized that:
H1: Each branch is consistent and the chosen items are coherent with one another.
H2: The four branches (External links, Team, Organization and Individuals) are independent from one another.
4.2.2 Participants and procedure
115 French-speaking participants volunteered to take the survey; the sample was composed of 60 women, 52
men and 3 persons who did not identify their gender. They were on average 29.1 years old (SD = 7.75). All of
them were working for different companies; 34% had less than 2-year work experience, 42 % between 2 and 5
years, and 24% for more than 5 years. Respondents were all engaged in a one-year executive training program
that they followed as initial or as continuing training in our institute and were recruited in this context. The
participants filled out paper forms of the questionnaire during their training time, during a 30-min dedicated
session.
4.2.3 Results
To test H1, we performed a reliability test on each branch of the ETOI model, as detailed in Table 3. In the
Managerial-practices sub-dimension of the Organization branch, only the items related to Green and Teal
stages proved reliable, hence we decided to remove the items related to Amber and Orange stages. With this
new set of items, the three sub-dimensions (Significance, Focus and Managerial-practices) are consistent as a
branch (α = 0.708). We then kept 10 sub-dimensions allocated to four branches of our model: External links,
Team, Organization and Individuals.
Table 3: Reliability of the branches and sub-dimensions of the ETOI model.
Branches
Sub-dimensions
Cronbach’s alpha
Reliability
E
External links
Outward-links: multiplicity and diversity
of relations with external environment
0.809
α=0.809
T
Team
Encouragement to use discovery skills
0.841
α=0.686
Promotion regulatory focus
0.690
Prevention regulatory focus
0.825
O
Organization
Significance of innovation
0.841
α= 0.708
Focus on products and customers
0.690
Managerial practices:
position in Laloux’
model
Amber
0.178 (items removed)
Orange
0.378 (items removed)
Green and Teal
0.842
I
Individuals
Engagement
0.914
α=0.673
Discovery skills
0.787
Delivery skills
0.787
To test H2, we performed a principal component analysis (rotation method: Varimax with Kaiser
normalization) with the 10 aforementioned sub-dimensions. Analysis converged after five iterations. Three
components appeared, that are presented in Table 4 together with factors loadings of each sub-dimension.
Table 4: Components matrix after rotation.
1
2
3
External links
Outward-links
0.687
0.38
0.009
Team
Encouragement
0.607
0.315
0.479
Promotion
0.269
0.789
0.218
Prevention
0.095
0.839
0.171
Organization
Significance
0.768
0.296
0.224
Focus
0.714
-0.231
0.169
Managerial-practices
0.703
0.29
0.164
Individuals
Engagement
0.447
0.371
0.469
Discovery
0.024
0.151
0.863
Delivery
0.305
0.128
0.743
The first component gathers the branch External links, the three sub-dimensions of Organization (Significance,
Focus, Managerial-practices), and the sub-dimension Encouragement, which we had initially positioned in the
Team branch. This component best matches the Organization branch of our model. The second component
gathers two Team sub-dimensions (Promotion and Prevention) and therefore matches the Team branch of our
model. The third component gathers 2 of the 3 sub-dimensions related to Individuals (Discovery and Delivery
skills) and matches our Individuals branch. The sub-dimension Engagement is equally distributed on the three
components. The principal component analysis shows that all ETOILe branches are not independent, as
External links and Organization fall within a unique component. H2 is therefore partly validated.
4.3 Discussion
As our results show, the External links branch appears to be part of the Organization branch. This result is not
so surprising. Our initial model was in line with Cameron and Quinn’s (2011) vision which classifies
organizations along two orthogonal axes (flexibility vs. control and internal vs. external focus) but the results of
our study are consistent with Laloux’ (2015) model, in which all the characteristics of an organization evolve
concurrently at the same time: individuals and hierarchy roles, perception of the outside of the organisation,
interest in and naturalness of change and innovation… Besides, the innovative ecosystem described in
Rainforest (Hwang and Horowitt, 2012) highlights the absence of border between the inside and the outside of
an organization. The same rules apply with collaborators, external stakeholders and society as a whole. This
analysis supports the view that Organization and External links can be seen as a single branch and operate
alongside in innovation culture.
Concerning the Team branch, we hypothesized that it has three sub-dimensions. One of them
(Encouragement) appears to be part of the Organization branch. Encouragement is related to how far the use
of discovery skills is supported and rewarded within a team. Our results suggest that the level of
encouragement in teams, in this sense, is actually representative of the level of encouragement in the
organization. Although one may observe some teams with practices non-aligned to their parent organizations
(Amabile and Pratt, 2016), our data appear to be consistent with Christensen et al’s (2013) view that, in
innovative firms, the organization core processes drive the possibility to implement extensively and reward the
discovery skills at all levels.
The Team branch of our model is now restricted to Promotion and Prevention regulatory focus. These two sub-
dimensions appear to correlate positively whereas we expected them to correlate negatively at the team level,
with teams particularly used to risk taking (Promotion), or to uncertainty avoidance (Prevention), but not to
both. It seems possible that, at the individual level, promotion and prevention regulatory focus are
independent, but can be positively correlated at the team level, each team being composed of individuals with
different profiles and building on everyone’s dispositions. In this respect, it could be interesting to replicate
Rietzschel’s (2011) protocol to study individual regulatory focus of each team member, and confront it to the
team-level regulator focus. This would enable us to understand if the team is structured as the intersection or
as the union of its members. Furthermore, group’s mechanisms might be different depending on the team
mission (e.g., control laboratory, innovation project).
Regarding the Organization branch, two of the three sub-dimensions are consistent (Significance of innovation
and Focus on product and customers). However, concerning Managerial practices, neither Amber items nor
Orange ones were reliable. In contrast, Green and Teal items were aggregated to create a Teal index which
gathers elements dealing with the terms in which missions and responsibilities are defined, and the role of
every member of the organization. It seems conceptually related to power distance (Hofstede et al, 2010).
Power distance is indeed defined as the extent to which the less powerful members of organizations expect
and accept that power is distributed unequally. The higher the Teal Index, the lower the power distance.
However, power distance may vary within a given organization. According to Hofstede’s studies, educational
level, type of job and social class are highly interdependent and power distance strongly decreases with higher
education, more qualified and socially recognized jobs (Hofstede et al, 2010). In our sample, the respondents
were highly educated (master’s degree). It would be interesting to check out the reliability of the Teal index
with a sample from a single organization, with varying types of job and levels of qualification.
Concerning the Individuals branch, the three sub-dimensions are reliable. The Engagement sub-dimension
appeared in the three components of the Principal Component Analysis: Organization, Team and Individuals.
Therefore its contribution to the model of innovation culture is not clear. One can even wonder whether it
may not be a result of innovation culture rather than a precondition. Hence we decided to remove it from the
ETOILe model.
Further validation of the diagnosis tool would be necessary. We should notably include a leadership metric and
study its relation with the other branches of the model. Furthermore, a predictive model including metrics of
innovation performance would also enable to test the respective predictive power of each branch of our
innovation model with regard to the final results of innovation. Such a study would be consistent with our
analogy to Lewin’s equation (1936) supporting the view that innovation performance partly results from
innovation culture. In order to test a full equation of innovation performance, the study could also include
metrics measuring the presence and importance of innovation process, in OECD’s (2018) framework. Hence
the respective predictive power of implicit cultural traits and explicit organizational processes could also be
evaluated.
It would also be necessary to run complementary validations of our tool with a new type of population in the
context of a case study. Our sample was generic but heterogeneous. In particular, we had only one respondent
for each company, which was acceptable to check out the psychometric properties of our diagnosis tool
(internal reliability of each branch, relations between branches) but would be insufficient to characterize a
given organization’s culture. To be reliable, the diagnosis of an organization’s culture should be performed by
several members representing several departments and hierarchical levels and building a consensual view
(Cameron and Quinn, 2011; O’Reilly et al., 1991).
5. Conclusion
On the basis of the results of this study, we proposed to refine our initial model and corresponding tool to
measure innovation culture. Even if we did not study the Leaders’ branch in the present experiment, we still
believe that it is a major factor to understand innovation culture. Therefore, to date, we consider that a fruitful
model of innovation culture should include four branches: Team, Organization, Individuals, Leaders. We
rename it TOILe accordingly, which has several meanings in French: a “toile” may be a plain weave, a robust
and sustainable material for everyday life; it is also used to designate canvas, which support artwork – canvas
being also a concept frequently used in innovation to structure its spreading.
Overall, we view our contribution as threefold. First, from a theoretical viewpoint, our model intends to
introduce an evolutionary approach and go beyond previous models of organizational culture which were
thought in the Orange paradigm. Secondly, we also set the basis for a specific model of innovation culture to
meet a contemporary need of companies to transform towards more innovation. Finally, from a
methodological viewpoint, we provide a diagnosis tool for helping companies identify their strengths and
weaknesses with regard to innovation.
All in all, organizational culture appears as a critical factor to master innovation strategy, implement relevant
and efficient processes, and develop innovation performance and growth. Through our model of innovation
culture and our diagnosis tool, we hope to contribute to supporting organizations to question themselves, gain
awareness of their own position with regard to innovation requirements, existing drivers, limitations and
barriers in their mindset and behavior. Such consciousness-raising process could be the first step towards a
deeper transformation. In an evolutionary perspective, this transformation may meet current demands for
sustainable innovation and be consistent with sociocognitive evolution of mankind.
6. References
Amabile, T. et al. (1996) ‘Assessing the work environment for creativity’, Academy of management journal,
39(5), pp. 1154–1184.
Amabile, T. and Kramer, S. (2011) The Progress Principle: Using Small Wins to Ignite Joy, Engagement, and
Creativity at Work. 1 edition. Boston, Mass: Harvard Business Review Press.
Amabile, T. and Pratt, M. (2016) ‘The dynamic componential model of creativity and innovation in
organizations: Making progress, making meaning’, Research in Organizational Behavior, 36, pp. 157–183.
doi:10.1016/j.riob.2016.10.001.
Barnhill, C.R., Smith, N.L. and Oja, B.D. (2021) ‘Creative and innovative teams’, in Organizational behavior in
sport management. Springer, pp. 165–173.
Bass, B.M. et al. (2003) ‘Predicting unit performance by assessing transformational and transactional
leadership.’, Journal of applied psychology, 88(2), p. 207.
Battistelli, A. (2014) ‘La recherche psychosociale sur le processus d’innovation individuelle et d’équipe: un bilan
des connaissances’, The psychosocial research in individual and team innovation process: a literature review
(English), 20, pp. 336–352. doi:10.1016/S1420-2530(16)30021-8.
Bertelli, N. et al. (2016) All you need, innove : Les clés d’un écosystème innovant. La Documentation française
(Fondation Nationale Entreprise et Performance).
Beylat, J.-L. and Tambourin, P. (2013) L’innovation: un enjeu majeur pour la France, dynamiser la croissance des
entreprises innovantes. Paris: Ministère du Redressement Productif & Ministère de l’Enseignement Supérieur
et de la Recherche.
Cameron, K.S. and Quinn, R.E. (2011) Diagnosing and Changing Organizational Culture: Based on the
Competing Values Framework. 3rd Edition. San Francisco, CA: John Wiley & Sons.
Chai, L. and Xiao, Y. (2018) ‘High-performance work system and employee innovation performance: The role of
obse and power distance orientation’, in Third International Conference on Economic and Business
Management (FEBM 2018). Atlantis Press, pp. 404–409.
Christensen, C., Dyer, J. and Gregersen, H. (2013) Le gène de l’innovateur: Cinq compétences qui font la
différence. 1 edition. Pearson.
Davies, M. and Buisine, S. (2018) ‘Innovation culture in Organizations’, in Science, technology and Innovation
Culture. ISTE-Wiley (Innovation in engineering and technology set), pp. 101–115.
Dobni, C.B. (2008) 'Measuring innovation culture in organizations', European Journal of Innovation
Management, 11(4), pp. 539–559.
Dyer, J.H., Gregersen, H.B. and Christensen, C. (2008) ‘Entrepreneur behaviors, opportunity recognition, and
the origins of innovative ventures’, Strategic Entrepreneurship Journal, 2(4), pp. 317–338.
Edquist, C. et al. (2018) ‘On the meaning of innovation performance: Is the synthetic indicator of the
Innovation Union Scoreboard flawed?’, Research Evaluation, 27(3), pp. 196–211. doi:10.1093/reseval/rvy011.
European Commission (2018) European Innovation Scoreboard 2018 : Methodology Report.
Fu, J.S. (2022) ‘Understanding the Internal and External Communicative Drivers of Organizational
Innovativeness’, Communication Research, 49(5), pp. 675–702.
Gallup (2013) State of the Global Workplace. Available at: http://www.gallup.com/services/176735/state-
global-workplace.aspx (Accessed: 4 February 2016).
He, M. and Lee, J. (2020) ‘Social culture and innovation diffusion: a theoretically founded agent-based model’,
Journal of Evolutionary Economics, 30(4), pp. 1109–1149.
Hofstede, G. (2016) Online lectures, Geert Hofstede. Available at: https://geerthofstede.com/training-
consulting/online-lectures/ (Accessed: 15 March 2018).
Hofstede, G., Hofstede, G.J. and Minkov, M. (2010) Cultures et organisations. 3e édition. Paris: PEARSON
EDUCATION.
Hwang, V.W. and Horowitt, G. (2012) The Rainforest: The Secret to Building the Next Silicon Valley. 1.02
edition. Regenwald.
Jones, G., Chirino Chace, B. and Wright, J. (2020) ‘Cultural diversity drives innovation: empowering teams for
success’, International Journal of Innovation Science, 12(3), pp. 323–343.
Laloux, F. (2015) Reinventing Organizations: Vers des communautés de travail inspirées. Diateino.
Lewin, K. (1936) Principles of Topological Psychology. New-York: McGraw-Hill.
Mathafena, R.B. and Grobler, A. (2021) ‘Perceived organizational support and leader-member exchange in
cultivating innovative behaviour in South African organizations’, African Journal of Science, Technology,
Innovation and Development, 13(5), pp. 559–571.
Mercan, B. and Goktas, D. (2011) ‘Components of innovation ecosystems: a cross-country study’, International
Research Journal of Finance and Economics, 76(16), pp. 102–112.
OECD (2016) L’impératif d’innovation : Contribuer à la productivité, à la croissance et au bien-être. OECD
Publishing.
Nani, D.A. and Safitri, V.A.D. (2021) ‘Exploring the relationship between formal management control systems,
organisational performance and innovation: The role of leadership characteristics’, Asian Journal of Business
and Accounting, 14(1), pp. 207–224.
OECD (2018) Oslo Manual 2018 - Guidelines for Collecting, Reporting and Using Data on Innovation. 4th edn.
OECD Publishing, Paris/Eurostat, Luxembourg. Available at: https://doi.org/10.1787/9789264304604-en
(Accessed: 7 January 2019).
O’Reilly III, C.A., Chatman, J. and Caldwell, D.F. (1991) ‘People and organizational culture: A profile comparison
approach to assessing person-organization fit’, Academy of management journal, 34(3), pp. 487–516.
Park, N.K. et al. (2021) ‘How to organize creative and innovative teams: creative self-efficacy and innovative
team performance’, Creativity Research Journal, 33(2), pp. 168–179.
Rietzschel, E.F. (2011) ‘Collective regulatory focus predicts specific aspects of team innovation’, Group
Processes & Intergroup Relations, 14(3), pp. 337–345. doi:10.1177/1368430210392396.
Volery, T. and Tarabashkina, L. (2021) ‘The impact of organisational support, employee creativity and work
centrality on innovative work behaviour’, Journal of Business Research, 129, pp. 295–303. Available at:
https://doi.org/10.1016/j.jbusres.2021.02.049.
