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The Nordics have been since a longer time a role model for a social and reliable management style. However, this statement was in the last just proven by doing few case studies with top executives. This study wants to describe the corporate culture and management style in the biggest companies of the Nordics and from that wants to answer if this management approach fosters a sustainable business culture. For defining the management and cultural approach applied in Nordic companies, the method of text mining in relation with machine learning will be used. Among European companies, the Nordic companies show a higher focus on sustainability. The cultural dimensions which describe the uniqueness of the Nordic business culture are to a high degree predictors of a more sustainable business.
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PhD paper extr. I
Nordic Management and
sustainable business
Björn Preußa
1
a Departement of Int. Management and Economics, Copenhagen Business School, Denmark
Departement of Economics, Radboud University Nijmegen, Netherlands
Abstract
The Nordics have been since a longer time a role model for a social and reliable man-
agement style. However, this statement was in the last just proven by doing few case
studies with top executives. This study wants to describe the corporate culture and man-
agement style in the biggest companies of the Nordics and from that wants to answer if
this management approach fosters a sustainable business culture. For defining the man-
agement and cultural approach applied in Nordic companies, the method of text mining
in relation with machine learning will be used. Among European companies, the Nordic
companies show a higher focus on sustainability. The cultural dimensions which de-
scribe the uniqueness of the Nordic business culture are to a high degree predictors of a
more sustainable business.
Keywords: Management; Nordic; Crises; Culture; Coprorate; Stability; Leadership
Introduction
The Nordic countries are from a historical perspective closely related to each other. Not
just from their relation due to trading but also from a cultural perspective. Nearly all
1 Björn Preuß. Tel.: +46 768349492
E-mail address: bp.int(at)cbs.dk.
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countries of the region including Norway, Finland, Denmark and Sweden belonged at
one point in time together (Smith, et al., 2003). Management principles and cultural
similarities among companies in the Nordic countries have been proved over the last
decades by many scholars such as (Hofstede, 1980; Hofstede, 1991; Ronen & Shenkar,
1985; Grenness, 2000; Grenness & Joynt, 1996). The corporate culture is mainly influ-
enced by the national culture and companies exist surrounded by this. Due to this fact,
the corporate culture can be better understand by looking at the national culture (Selnes,
1996). Studies have shown that the Nordic countries have, when it comes to leadership
styles, similarities that have an impact on their market orientation (Selnes, 1996).
The goal of researching the impact of culture might be to draw conclusions in which
way the cultural factors influence the sustainability of corporate management. In fact,
research faces in this way some difficulties that arise from the nature of culture. The
hidden nature of cultural behavior causes some difficulties in measurement and defining
these (Smith, et al., 2003). In order to cope with this difficulties, researchers from out-
side the region have developed measurements that measure culture on a general scale in
order to compare differences among cultures (Hofstede, 1980) and management styles
(House, et al., 2003). These results can be used in order to define similarities in a region
and or differences to other regions. Not just on country level but also on corporate level
might the culture and their difference play a role in the way on how companies react on
the development of the worlds economy. The fact that current research showed the
stakeholder orientation from Nordic companies (Carlsson, 2007) lead to the conse-
quences that they are more stable and long term oriented, according to (Freeman, 1984)
whos main research was contributing to the development of the stakeholder approach
which is mainly taught by Nordic scholars and has therefore a big influence on the de-
velopment of Nordic management styles (Strand & Freeman, 2013). However, beside
this logical assumption, current research took this fact more as granted and did not re-
searched on this relation between the long term stability and the cultural and leadership
approach in the Nordic countries.
Due to this fact, the following paper aims to analyze the relation between the Nordic
corporate culture and the long term sustainable development of companies. In this con-
nection the study aims to look on the sustainability of management actions and how the
corporate culture might influence this. The study collects data from the blue chip com-
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panies of the Nordic countries listed in the large cap indices of Denmark, Sweden,
Norway and Finland. In order to present differences to other European companies and
in order to show the impact of a specific corporate culture a peer group from companies
of other European countries was selected. These are listed in the Euro Stoxx 50 index.
From this the study uses text mining in order to process an extensive amount of text
describing the cultural and management practices in the target companies. Software for
text mining and principles or language processing allows to process and quantifies the
information and throughout this link it to the economic data which will be collected for
each of the countries and companies.
Furthermore, methods from machine learning will be used in order to describe patterns
in the linked data and with that present a significant relation between the sustainability
of companies in the Nordics and their specific management approach. The models being
used for this will be described in more detail under the method selection topic.
The Nordic Management Approach
The four countries Denmark, Sweden, Norway and Finland can be summarized under
the name Nordic region. (Nordstrom, 2000; Bonderson, 2003) These country group
shares according to current research an equal approach to management that differenti-
ates them from other countries. (Schramm Nielsen, et al., 2004; Smith, et al., 2003)
Corporate culture is according to Weber (1996) a system of believes, values and as-
sumptions that are shared among the managers of an organization and that are influenc-
ing the way how the organization is managed. Gjølberg (2010) showed that in Scandi-
navia cultural norms and institutional structures that encourage the relationship between
stakeholders and the companies are dominant. The structures in companies from the
Nordics follow mainly a participative culture. (Grenness, 2003) The organizations fol-
low an approach of a high degree of employee engagement and flat hierarchies. (Mors-
ing et al., 2007; Bondeson, 2003) According to Midttun et al. (2006) companies from
the Nordics follow a culture of combining economic interests within a broader societal
interest. Furthermore, Scandinavian companies show an involvement of the employees
in the management by having participations from the employee side in the board. (Sin-
ani et al., 2008) The whole corporate governance in the Nordics is stakeholder orientat-
ed and the corporate ownership is concentrated. (Carlsson, 2002; Carlsson, 2007) A
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high percentage of owners are the state (Porta et al., 1999) by foundations and families
(Carlsson, 2007). Research showed furthermore that owners in this case behave not as
individuals who are just hunting for the short term profit rather than having a long term
interest in the company (Strand & Freeman, 2013) This can be backed up by findings
that state that Nordic management seems to be more stability orientated. (Lindoe &
Engen, 2007; Kvande & Brøve, 2012) Mintzberg et al. (2009) showed that in the Nor-
dics is a high conformity what theory of stakeholder management says and what is done
in the practical world. Researchers like Kakabadse et al. (2005) claimed that the stake-
holder approach nearly dominated the teaching at universities in Scandinavia as well as
that the approach has an important status in Scandinavian management since the 1960’s.
According to the GLOBE study, the following dimensions can be used to classify the
management style in Sweden. Inspirational integrity, visionary, team integration, per-
formance orientation, collaboration. (Jagdeep, et al., 2007) The level of top and middle
management is on the same high. This is due to a low level of hierarchy in Scandinavia
and in particular Sweden. (Tollgerdt-Andersson, 1989) This participative style in lead-
ership comes in connection with egalitarism and status conscious. (Jagdeep, et al.,
2007) There are according to current research certain factors that inhibit leadership in
Sweden. These are according to Jagdeep, et al. (2007) Autocratic, face saver, self-
centered, malevolent. As a challenge for the Swedish leader can be seen to balance
these factors for good leadership with some of the in depth values of the culture as for
example equality. (Jagdeep, et al., 2007)
Working in Denmark is characterized by a relatively liberal labor market. (Due &
Madsen, 2008) which means that it is based on self-regulatory mechanisms. In order to
provide stability beside this flexible set up, there is a high level of social security pro-
vided. (Sørensen, et al., 2009) This set up of the labor market can also be found in a
way in the management style in Danish companies. The focus lies on worker involve-
ment, autonomy and corporation. This had in the latest decade’s influence on a positive
development of productivity, higher quality and innovativeness. (Hvid & Hasle, 2003;
Hansen, 2007; Cottini, et al., 2011) Practice in Denmark has shown that practices which
create management involvement a positive internal working climate and less repetitive
jobs have a positive on the financial performance in Danish companies. In the same,
Danish work life can be described as trust in employees and corporation. This had ac-
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cording to current research a positive influence on creating less absenteeism and less
strikes. (Hvid & Hasle, 2003; Hansen, 2007; Cottini, et al., 2011) In general Danish
employees feel adequately informed regarding management decisions. This is due to
good information policy in companies as well as a high level of flat hierarchies. (Lund,
2004)
One main reason for the economic development of Norway is the increasing democracy
both in the public as well as in the management style. (Levin, et al., 2012) Norway did
not take part in the Globe project. However, there is research that adapted the question-
naire from these project to Norway. (Warner-Søderholm, 2010) The results have shown
that Norway similar to Denmark scores low in power distance and very high in human
orientation and collectiveness. In these high score categories, it outperforms all other
Nordic countries by far. (Warner-Søderholm, 2010) When it comes to uncertainty
avoidance, Norway scores much lower as Sweden which is the highest scoring country
in this measure of the Nordic cluster.
In Finland the situation looks a bit like in Sweden. The importance of nonhierarchical
dialogue and participative leadership are established values in the Finish management
practice. (Jones, et al., 2010; Fey, et al., 2009; Andreeva & Kianto, 2012) Advances in
productivity of Finish companies can be related to team tasks, the structure and pro-
cesses of organizations as well as the creation of social workspaces. (Bosch-Sijtsema, et
al., 2009) The individualistic behavior as well as the high equality between men and
women is in Finland same as in Sweden an important element of the culture in compa-
nies and society. (Jagdeep, et al., 2007) Another factor that influence the working life as
well as the management style is that according to Jagdeep, et al. (2007) the power dis-
tance in Finland can be described as low. This creates an equality among the employ-
ees. An interesting point that can be found in Finland and differentiate the country in
some way from other Nordic societies is that there is a low performance orientation
according to the GLOBE study. (House, et al., 2004) Beside this which can have an
effect on the performance and reward system in companies, the future orientation is
higher as the average country in the GLOBE study. (Jagdeep, et al., 2007)
Sustainability is not just environmental friendliness
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In the past year’s research has shown that the industrialization had negative effects on
the environment (World Ressource Institute, 2004). However, the economic output is to
a high proportion dependent on the natural system (Constanza, et al., 1997). This leads
to more sustainability and environmental friendliness in business. Furthermore, the eco-
nomic environment is unstable so that business needs to adapt fast to this condition in
order to reduce risk of failure (Miller, 1992).
In the 21st century the environment is an important factor that should be preserved for
upcoming generations. In order to measure the impact that companies have on the envi-
ronment multiple methods and measures have been developed. See for this (Verfaille &
Bidwell, 2000). One prominent measure of companies’ environmental impact are the
ESG ratings. The available ESG scores cover a multiple factor that describe company’s
social responsibility and combine them in one score. This social factors relate to treat-
ment of employees, labor conditions, human rights, supply chains, and treating stake-
holders in society fairly. The last factor, governance, covers abuses in executive pay,
diversity on boards, equal employment opportunities, business transparency and disclo-
sure, and corruption inter alia. (Charles, et al., 2015; Hudson, 2006) However the
prinicples of score calculation are not transparent. Butz and Pictet (2008) argue that
ESG scores have become commodities, which has led to firms proactively adopting
ESG strategies that live up to these rating criteria. Thereby, adopting ESG strategies on
a firm level can increase the potential investor base and potentially lead to a higher
share price (Mónika & Erzsébet, 2014). Beside the impact on the environment a com-
pany can also be defined as sustainable from a business perspective. Porter (2010) de-
fined a company as sustainable when it creates long term sustainable value for its stake-
holders.
The Nordic companies score especially high in responsibility measures. (Midttun, et al.,
2006; Campell, 2007; Gjølberg, 2010; Broberg, 1996) This might be due to the fact that
shareholder value is teached extensively in business schools as well as used in business.
(Strand & Freeman, 2013; Pettersen, et al., 2002) In current research, Harrison et al.
(2010) provided in his work a demonstration that managing stakeholders leads to stake-
holder trust and with this to additional value creation.
Method- and Sample Selection
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In this section we describe the method that was used in order to analyze big data of cul-
tural statement document corpus. The corpus contained 3000 documents with single
statements about the corporate culture, the management and leadership style in Scandi-
navian and European companies. The text extraction in order to apply text mining and
machine learning was done from .txt files. For doing both the extraction, mining the
software rapidminer was used. The machine learning algorithms where optimized by
using the R extension of rapidminer.
Sample - A company selection
The sample size selection for this paper was made by choosing companies from the blue
chip indices from the Nordic companies and the European union. See for detailed in-
formation the following table. The selection was made in align with the fact that the
companies in the analysis represent the main economic activity in the selected regions.
(SOURCE) With that it will be possible to draw conclusions about the corporate culture
in the target countries and companies.
Country
Index
Num. Companies
Norway
OBX 26
26
Denmark
OMX Copenhagen 20
20
Sweden
OMX Stockholm 30
30
Finland
OMX Helsinki 25
25
EU
EUROSTOXX 50
492
Table 1: Covered indices
The data was collected from websites which give employees a platform to comment on
the management and leadership style as well as the corporate culture of their current or
former employees (e.g. glassdoor.com, indeed.com). This posts give in their total a real-
istic view on the culture in the various firms. Although the way of data collection makes
this study less dependent on the companies and also has a lower level on influence
through participants. (Bryman & Bell, 2015)
The sample consists of in total 3.000 attributes where each describes the culture of a
specific company. For each company ca. 20-30 of such descriptions where collected.
2
Excluding Nokia since it is already included in the Finish index
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Text Mining for Data Collection
Text mining is a method to process and analyze unstructured textual data. It uses tech-
niques from data mining and machine learning in order to extract knowledge from mul-
tiple documents. Clustering- trend analysis or association rules are common fields in
which text mining is applied. (Feldman & Sanger, 2007) The method of text mining
finds in multiple research areas of social science an application e.g. (Torvaten, et al.,
2015; Kinra, et al., 2016; Hippner & Rentzmann, 2006). In this paper the software
Rapidminer® was used in order to process the text with the goal to get the text data in a
structured for which can be analyzed by a statistics program. This was necessary in or-
der to use machine learning and also for later linking the findings to the economic data.
Furthermore, this method allows to draw also a picture of the cultural set up in each of
the companies which makes it different to the current studies on culture and for the pur-
pose of this study necessary.
The text mining process is presented in Figure 1 and contains different steps that lead to
a list of words that mainly describe the underlying text and with that includes the core
information of the text. The first step is that the words get tokenized. That means that
the text will be split into the single words. After that the words were filtered by length.
In this case words with less than 4 and with more than 25 characters where excluded.
The words got also filtered by English stop words so that words like “and” and “then”
etc. were excluded from the sample since they do not contain specific content infor-
mation. The next step that was performed was stemming. The used operator (written in
the snowball language) stems the words in the documents based on their English word
stem. This is necessary in order to not have multiple words with just different forms in
the output of the text mining process. After all the words were transformed to a homo-
geneous case (here lower case), the result was then written into an excel document for
further analysis.
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Figure 1: Text mining process
The outcome is a list of words that each of the documents contain and the number of it.
Each document is linked to the company it belongs to and it can therefore easy be
linked to data from the country or the company.
Machine learning to predict defined patterns
As a part of the method, machine learning algorithms were applied on the text corpus in
order to classify the text. The text classification uses a supervised machine learning
approach and can be seen as a process were the machine assigns predefined labels to
new documents. This is done by using a probabilistic measure of likelihood using a
training set of documents that where labeled before. (Yang & Liu, 1999)
First sample data sets where defined. This was done for each of the cultural dimensions.
The sample data were statements that described for example a more future oriented cul-
ture or a less future oriented culture. After that, a linear support vector machine (SVM)
was used as a classifier. (Ben-Hur, et al., 2001) The SVM groups the data points into
classes by designing a hyper plane between these.
 
  
(1.1)
There can be multiple hyper planes be designed but the algorithm choses the one which
leaves the maximum margin between both classes. The hyperplane delivers for each
class different value:
   
(2.1)
   
(2.2)
  
(2.3)
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With minimizing the distance , the algorithm minimizes the separability of the classes.
This is done by using a nonlinear optimization task using the KKT method and Lagran-
gian multipliers λ. (Mangasarian & David, 2001; Wu, 2009)
 

(3.1)
  
(3.2)
The vector that describes distance between the hyperplane and the data points
is
also named support vector. The hyperplane is the used for classifying the data. This
process was repeated for each of the cultural dimensions. The resulting data was then
saves as .xlsx file. This process can be described in the following rapidminer processes.
Figure 2: Building and testing SVM model
After training the model with a split of the sample, the model was applied to classify the
rest of the data set. This process is described in the following figure.
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Figure 3: Applying VSM model on data set
This was done several times in order to classify the corpus with different labels for each
of the cultural dimensions defined by the GLOBE project as well as for sustainability.
The data that results from the text mining and machine learning operations will be ana-
lyzed with descriptive statistics and regression modeling. Based on a selection made by
the descriptive statistics, the main cultural dimensions will be analyzed by simple re-
gression models and together in a multiple regression model which can be described by
the following formula.
 
(4.1)
In the descriptive statistics the scores for the Nordic countries and the other EU coun-
tries will be described and compared with each other.
Nordic Management on top of Europe
The management of the Nordic countries was in the past extensively studied on country
level. This study examines the leadership culture on company level in order to bring it
into relation with the companies’ actions related to sustainability.
The difference in leadership between the Nordics and rest of Europe
The first step in order to define the leadership styles in each of the companies that are
contained in the sample size was to extract the word list by using the above described
algorithms in rapidminer. The resulting word count list can be requested from the au-
thor but will not be displayed in this paper due to limited space for the rich data. In the
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first step of the analysis an exploratory factor analysis was performed. The number of
factors was distinguished by theory and the definitions of the GLOBE study were cho-
sen since they were more detailed and it allowed to make the model more precise.
The following graphs show how the Nordic countries differ in terms of management
approach based on the GLOBE study dimensions.
Figure 2: Graphs cultural dimensions
It is from the graphs clear to see that companies in the Nordics score lover then in the
rest of Europe when it comes to the dimension’s collectivism, uncertainty avoidance,
power distance and masculinity. In Human and future orientation have the Nordic com-
panies higher scores then I the rest of Europe. These findings out of the text mining
process is in align with the findings of previous research related to the Nordic culture.
Impact of Nordic corporate culture on stability
The first look on the difference of sustainability of the Nordic countries compared to the
other Europeans shows that there is not a huge difference in how they talk about sus-
tainability. However, all the Nordic companies score slightly higher as the average Eu-
ropean company.
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Figure 3: Sustainability score
The data analysis shows that the average European company scores lower as companies
from the Nordic countries. This is in align with the findings from current research re-
garding the social and environmental friendly orientation of Nordic companies. Howev-
er, these descriptions show just the current situation and do not focus on the question
whether there is a relation between the Nordic leadership and the higher sustainable
orientation of the Nordic countries. In order to discover this multiple regression models
were performed. To oversee the relations between the sustainable orientation and the
corporate culture see the following scatter plots.
Figure 4: Scatter plots - relation sustainability and cultural dimensions
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The strongest relationship is between sustainability and the cultural dimension’s future
orientation, masculinity and human orientation. This can be also seen in the correlation
matrix in the appendix of this paper. Therefore, the further analysis will have a more in-
depth look on these. The sustainability measure is for all following in depth analysis the
same and can be described by the following descriptive statistics.
Sustainability
Mean
0.7094
Standard Error
0.0013
Median
0.7095
Standard Deviation
0.0149
Sample Variance
0.0002
Kurtosis
0.8843
Skewness
0.0090
Range
0.0887
Minimum
0.6677
Maximum
0.7564
Sum
97.1873
Count
137
Table 2: Summary descriptive statistics Sustainability
It can be said that the median and the mean are nearly the same which indicate a normal
distribution. The regression model with the highest prediction power is between Sus-
tainability and Masculinity.
Masculinity
Mean
0.3705
Standard Error
0.0025
Median
0.3702
Standard Deviation
0.0293
Sample Variance
0.0009
Kurtosis
1.7119
Skewness
-0.3237
Range
0.1897
Minimum
0.2781
Maximum
0.4678
Sum
50.7625
Count
137
Table 3: Summary descriptive statistics masculinity
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Also in for this dimension is the mean close to the median. However, over all is this
dimensions wider spread then the dimension describing sustainability which indicates
for a higher variety among the data set. The regression statistics in the following table
highlight that the model has a maximum prediction power of ca. 25%. This is for just
one cultural dimension high. The R square as well the adjusted R square are much low-
er but this can be in this case neglected since it accounts for a small sample size. How-
ever, since the number of companies is given, can this not be adjusted.
Regression Statistics
Multiple R
0.247168228
R Square
0.061092133
Adjusted R Square
0.05413726
Standard Error
0.014458545
Observations
137
Table 4: regression statistics masculinity-sustainability
Also the ANOVA table supports the hypothesis that a higher masculinity has a negative
impact on the sustainability of a company. And with that accounts this for a higher sus-
tainable management in Nordic companies which have in average a lower masculinity
then the average European company.
df
SS
MS
F
Significance F
Regression
1
0.001836307
0.00183631
8.78407589
0.003593041
Residual
135
0.028221687
0.00020905
Total
136
0.030057994
Table 5: ANOVA statistics regression model masculinity-sustainability
The significance of the model is below 0.005 so it can be used as a predictor for the
outcome of the model.
The second cultural dimension which has a high impact on the sustainability based on
the regression model is the future orientation. This is also logic and was proven my cur-
rent research that a more towards the future oriented company search also for more in-
novative and sustainable solutions. The dimension can be described by the following
descriptive statistics:
Future Orientation
Mean
0.7129
Standard Error
0.0010
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Median
0.7137
Mode
n/a
Standard Deviation
0.0113
Sample Variance
0.0001
Kurtosis
2.3612
Skewness
-0.4369
Range
0.0742
Minimum
0.6704
Maximum
0.7445
Sum
97.6695
Count
137
Table 6: Descriptive statistics future orientation
The dimension is like the sustainability not wide spread across the companies as well as
has a median which is near to the mean. The regression model between future orienta-
tion and sustainability can be described by the key figures in the following table.
Regression Statistics
Multiple R
0.199037629
R Square
0.039615978
Adjusted R Square
0.032502022
Standard Error
0.01462297
Observations
137
Table 7: regression statistics future orientation- sustainability
The prediction power of the future orientation is slightly lower as the one of masculinity
which is could have been based on current research the other way around. However,
both R are with 25% and 20% close to each other. The ANOVA table for this model
can be seen in the following table:
df
SS
MS
F
Significance F
Regression
1
0.001190777
0.001190777
5.568769207
0.019715952
Residual
135
0.028867217
0.000213831
Total
136
0.030057994
Table 8: ANOVA future orientation-sustainability
With ca 0.02 is the significance much higher as for the masculinity but still can be ac-
cepted since the model contains just one cultural dimension which is only a piece of the
whole corporate culture and management style of a company. The last dimension which
has a major impact on how sustainable a company is managed is the human orientation.
The more human a company is oriented the more sustainable is the company managed.
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This is in align with current research and also logic since how a company interacts with
employees as well as other human is also a factor for how sustainable a company is.
Human Orientation
Mean
0.6193
Standard Error
0.0024
Median
0.6168
Mode
n/a
Standard Deviation
0.0283
Sample Variance
0.0008
Kurtosis
6.8426
Skewness
1.1802
Range
0.2220
Minimum
0.5273
Maximum
0.7493
Sum
84.8414
Count
137
Table 9: Descriptive statistics human orientation
Also hear is the mean close to the median. But the maximum and minimum are wider
spread then at the future orientation ore the sustainability.
Regression Statistics
Multiple R
0.153911585
R Square
0.023688776
Adjusted R Square
0.016456841
Standard Error
0.014743726
Observations
137
Table 10: regression statistics human orientation- sustainability
The prediction power of the model is with ca. 15% 5 %points lower as the other two
dimensions but still one of the most important once (see scatter plots).
df
SS
MS
F
Significance F
Regression
1
0.000712037
0.000712037
3.275579221
0.072542563
Residual
135
0.029345957
0.000217377
Total
136
0.030057994
Table 11: ANOVA table regression model human orientation-sustainability
Parallel with the prediction power of the model is also the significance changed. With
0.07 is it the highest out of the main predictors. If these three cultural dimensions are
put together in a multiple regression model, then then culture defined by this dimen-
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sions can predict 32.6% of the outcome of the sustainability. The regression model can
be seen in the appendix of this paper.
Result and Discussion
The results of this research present the relation between cultural dimensions and the
sustainability of the companies. For the four Nordic countries Denmark, Sweden, Nor-
way and Finland as well as the biggest European companies (Euro Stoxx50). However,
the picture remains uncomplete and the question regarding how to in detail influence
the cultural dimensions remains unanswered by this analysis. Methodological limita-
tions should also be considered when drawing conclusions from these findings.
In the first step it can be summarized that the findings about the Nordic corporate cul-
ture can support the current research. The management style in the Nordic companies is
in contrast to the rest of European companies defined by flat hierarchies. The broader
social interest of companies in Denmark, Sweden, Norway and Finland can be found
respectively in the score of the human orientation. Nordic companies are focused on
social values and highly future orientated. This future orientation is in align with the
visionary set up that is especially in the Swedish corporate set up the case.
When connecting this scores to the sustainability, the analysis showed that the cultural
dimension’s masculinity, future-orientation and human-orientation have the highest
impact on how high the firm scores in sustainability. Masculinity has a negative impact
and the other two dimensions have a positive impact on the sustainability. When com-
paring the Nordic companies with other European companies they score in these dimen-
sions in exactly the supporting direction. The way how the Nordic companies in aver-
age differentiate themselves against the rest of Europe is in align with current research.
The companies in the Nordic countries have a culture that can be defined by higher in-
dividualism and lower uncertainty avoidance. They account for a low power distance
and a higher future- and human-orientation. Furthermore, they have a less masculine
culture which can also be seen by the role of women in those societies.
Managerial Implications
Since certain studies showed already a correlation between sustainability and corporate
financial performance. (Luo & Bhattacharya, 2009; Margolis & Walsh, 2003; Sen, et
19/27
al., 2006) Managers are good advised to focus on responsibility activities. This paper
showed that by adopting a management style similar to the Nordic countries, the sus-
tainability of business operations can be increased. The Nordic approach is more future
orientated, focus on the human capital and increases the flexibility by giving the em-
ployees more freedom to act.
Future Research
The method of text analytics and machine learning is rather new in the field of social
science research. Therefore, it gives further research the possibility in finding more
suitable algorithms for certain data sets. Furthermore, the paper used also for the dis-
covery of firm’s responsibility a text mining approach. Also if the results of this are in
align with current research it can be enriching to analyze how the assessment of social
responsibility with this method scores in combination with other established rating
methods (e.g. sustainalythics ESG rating). There might be a slight difference in the out-
comes of certain methods given by the underlying data.
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Appendix
SUST
PWD
MAS
UAV
HUO
FUO
COL
SUST
1
PWD
-0.08089
1
MAS
-0.24717
0.119029
1
UAV
-0.15705
0.157317
0.020165
1
HUO
0.153912
-0.27789
-0.04053
-0.0625
1
FUO
0.199038
-0.19779
-0.09384
-0.9376
0.15795
1
COL
0.006065
0.054496
-0.27281
0.32277
-0.0783
-0.2198
1
Table 12: Correlation matrix sustainability and cultural dimensions
Regression Statistics
Multiple R
0.3259
R Square
0.1062
Adjusted R Sq.
0.0860
Standard Error
0.0142
Observations
137
ANOVA
df
SS
MS
F
Significance
F
Regression
3
0.0031
0.0010
5.2692
0.0018
Residual
133
0.0268
0.0002
Total
136
0.0300
Coefficients
Standard
Error
t Stat
P-value
Lower 95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
0.5637
0.08187
6.8846
2.07E-
10
0.4017
0.7256
0.4017
0.7256
MAS
-0.1152
0.0417
-2.7610
0.0065
-0.1977
-0.0326
-0.1977
-0.0326
FUO
0.2096
0.1100
1.9053
0.0588
-0.0079
0.4273
-0.0079
0.4273
HUO
0.0628
0.0436
1.4402
0.1521
-0.0234
0.1490
-0.0234
0.1490
Table 13: Multiple regression model
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Chapter
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