Impact of Hofstede’s Cultural Dimensions on the Human Development Index of European Countries

Longitudinal Time Series Analysis. Secondary Research


Bachelor Thesis, 2018

72 Pages, Grade: 75%


Free online reading

Contents

Acknowledgements

List of Tables & Figures

Abstract

Impact of Hofstede’s Cultural Dimensions on the Human Development Index of European Countries

1.0 | Introduction
1.1| Impact/Issues of Hofstede’s cultural dimensions on HDI (Research Importance)
1.2 | Research Rationale
1.2.1 | Research Problem
1.3 | Research Aim
1.4 | Research Objectives
1.5 | Research Questions
1.6 | Research Structure

2.0 | Literature Review
2.1 | Definition of Key Terms:
2.1.1 | Hofstede’s Cultural Dimensions (8 Definitions)
2.1.2 | Human Development Index (3 Definitions)
2.2 | Critical Review of Models and Theories
Hofstede’s Cultural Dimensions
Hall’s Contextual Model
Trompenaar’s Cultural Dimensions
Justification of Hofstede’s Cultural Dimensions
Human Development Index Critical Review
Duncan’s Socioeconomic Index
Hollingshead’s Four Factor Index
Justification of HDI
2.3 | Literature Gap: Empirical Studies in the last 10 years (10)
2.4 | Summary of Variables
2.5 | Formulating Hypotheses
2.6 | Conceptual Framework

3.0 | Methodology
3.1 | Research Design
3.1.1 | Descriptive Research
3.1.2 | Exploratory Research
3.1.3 | Explanatory Research
3.2 | Research Methods
3.1 | Research Paradigm
3.2.2 | Data Collection (Primary or Secondary)
3.2.3 | Population
3.2.4 | Sample Size
3.3 | Ethical Consideration
3.4 | Analysis Method
3.5 | Data Analysis Plan
3.6 | Research limitations

4.0 | Results & Discussion
4.1 | Descriptive Analysis
4.1.1 | Normality and Kurtosis
4.1.2 | Interpretation
4.1.3 | Mean and Standard Deviation
4.2 | Charts
4.2.1 | Bell Curve
4.2.2 | Regression Line
4.2.3 | Scatterplots
4.3 | Regression Analysis
4.3.1 | Adjusted R-Square and Durbin-Watson
4.3.2 | ANOVA
4.3.3 | Hypothesis Testing
VIF
Beta Coefficients
Discussion and Interpretation

5.0 | Conclusion & Discussion
5.1 | Conclusion
5.2 | Recommendation
5.3 | Implication

References

APPENDIX A

APPENDIX B

APPENDIX C

APPENDIX D

List of Tables & Figures

Table 1: Research gap

Table 2: Data Analysis Methods

Table 3: Descriptive Statistics (SPSS Generated)

Table 4: Descriptive Statistics Table (SPSS Generated)

Table 5: Model Summary of Regression (SPSS Generated)

Table 6: Anova Summary (SPSS Generated)

Table 7: Coefficients Table (SPSS Generated)

Table 8: Aligning Hypotheses with Results

Table 11: List of European Nations

Table 12: Secondary Data Collection

Figure 1: Hall's Contextual Model (Hall, 1989)

Figure 2: Trompenaar’s Cultural Dimenisons (Trompenaar & Hampden-Turner, 2011)

Figure 3: Types of Skews (Kim, 2013)

Figure 4: Illustration of Kurtosis peaks (Kim, 2013)

Figure 5: Bellcurve HDI (SPSS Generated)

Figure 6: Regression Line (SPSS Generated)

Figure 7: Standardized Regression Plot

Figure 8: 6 Dimensions Scatter Plot

Figure 9: Illustration of Hofstede's Cultural Dimensions validated through Hofstede (2018)

Acknowledgements

I would like to thank Dr. Ismail Nizam for taking me under his wing. He really helped me during the times I was stuck and it is because of him I was able to finish this dissertation. I would also like to thank Mr. Abdul Basit for assisting me at a major point in my dissertation during the data collection phase. It was his advice that added polish to this dissertation. I would like to thank Mr. Zubair Hassan and Mr. Sahibzada Hamza for their remarks during the defence which improved various parts of my dissertation. I would also like to thank my fellow colleagues and friends for giving me minor tips and adjustments which further polished my dissertation.

Abstract

Hofstede’s cultural dimensions is a cultural dimension tool which was used as the independent variable and its impact was tested on the Human Development Index, a socio-economic cultural development index; only in Europe. Through research concluded that both these models were the best fit due to availability of data as well as time constraints. The literature gap revealed that no other research did this research fully with all cultural dimensions, HDI, and only in Europe. A longitudinal secondary quantitative study was done considering the latest 5 years of HDI scores from UNDP and a regression, descriptive analysis, and normality test was done to determine the impact. Data was collected through reputable primary sources online. The test revealed that only 3 of the cultural dimensions proved to have an impact on HDI. Power distance had a negative significant impact. Individualism and Indulgence had a significant positive impact. Three of the six null hypotheses were deemed true. This study can provide useful insights for businesses and academics that are looking towards the continent of Europe to further expand their cultural knowledge for various purposes.

Keywords: Hofstede’s cultural dimensions, Hofstede’s model of national culture, Human Development Index, Culture, Power Distance, Individualism, Masculinity, Long Term Orientation, Uncertainty Avoidance, Indulgence, HDI.

Impact of Hofstede’s Cultural Dimensions on the Human Development Index of European Countries

1.0 | Introduction

This research paper’s purpose is to investigate the Impact of Hofstede’s cultural dimensions on the Human Development Index (HDI) of European Countries. There has always been an socio-economic gap between countries of Europe. Although the gap is mainly between the eastern and western side of Europe, minor differences can be seen within each nation in the continent of Europe. (Tallinn, et al., 2005). The Human Development Index (HDI) was an index developed by a Pakistani scholar named Mahbub Ul Haq, Muhab developed the HDI by creating a scoring system comprising of socio economic scoring of a nation based on the nation’s people’s level of education, standard of health, and overall standard of living (The Economic Times, 2018). Geert Hofstede’s National Cultural model, or more commonly known as the 6-D [Dimensions] model or Hofstede’s Cultural Dimensions is the selected model that will be used to determine how each those six dimensions in the model correlate with the socio-economic development of European countries (Hofstede, 2018). The cultural dimensions include Power Distance, Individualism, Femininity/Masculinity, Uncertainty Avoidance, Long Term Avoidance, Indulgence/Restraint (Hofstede, 2018).

In 1967, with affiliation with International Business Machines (IBM), Geert Hofstede set out to create a model which had the ability to survey global employee values by IBM through the method of factor analysis. The original model used four dimensions that had the ability to analyze cultural values through a numerical stand. The four dimensions were individualism-collectivism; uncertainty avoidance; power distance (strength of social hierarchy) and masculinity-femininity (task orientation versus person-orientation). Further independent research away from IBM led to this model being refined over the years. In Hong Kong, Hofstede added a fifth dimension to his model of national culture, which was Long Term Orientation. Finally, in 2010, a sixth dimension was added called indulgence-restraint (Hofstede, 2018). Up until then the country scores have not been altered and no further additions to the model has been done. However constant refining of this model from 1967 up until 2010 gives this model reasonable grounds for it to be a viable model to be used in this research paper.

Numerous previous studies have been done on cultural impact of socio-economicdevelopment. For instance Nekane Basabe & Maria Ros did a research on Cultural dimensions, socioeconomic development, climate, and emotional hedonic level and found Individualism showed positive correlation with subjective well-being and various other factors such as socio-economic development control, power distance, uncertainty avoidance and climate (Basabe & Ros, 2005). Hamid Yeganeh wrote a paper called Cultural values and gender gap: a cross‐national analysis and found that cultural dimensions along with socio-economic indexes have an impact on gender gaps (Yeganeh, 2011). Maria Martins and Hidio Lopes wrote a paper on Culture and Profitability: Empirical Evidence at a European Level and found that countries with higher development (including socio-economic) correlated with low Power Distance, Uncertainty Avoidance, and Long Term Orientation as well as higher Indulgence (Martins & Lopes, 2016).

1.1| Impact/Issues of Hofstede’s cultural dimensions on HDI (Research Importance)

Hofstede’s cultural dimensions is a very thorough model which has been improved and expanded for decades, therefore it constantly keeps up with socio-economic dimensions of a country through six of the dimensions and explains the cultural gaps and differences between those countries (Hofstede, 2018). The HDI is another tool that measures the improvement or decrease on Human development in general on a country (The Economic Times, 2018). Hofstede’s dimensions and HDI are both measured by generalizing culture and development in an entire country, therefore patterns between the two can be identified with ease. This gives an importance to the research because it gives it potential to identify a pattern between the two models in order to better understand the cultural development in European Nations.

1.2 | Research Rationale

Finding a connection in HDI through cultural factors can be seen as a very important part of evaluating a country based on their socio-economic outlook. Victor Anderson mentioned the importance of economic indicators allows the country’s strength to be measured through various different factors. This allows a country to improve these factors to improve their overall economic strength which ultimately benefits the country as a whole (Anderson, 2014). Freeman argues that learning about factors in the past can help understand and prepare for the future; through this logic it can be determined that another rationale for research dictates that conducting this study that links cultural factors to economic strength can assist in learning and increasing the knowledge about both cultural and economic factors of European nations and the concept of socio-economy as a whole (Freeman, et al., 2009).

Lastly, according to Leann (Zarah, 2018), there is no point in doing business research unless it helps the corporate world. That being said, this research could give a clear sight of cultural patterns and human development for different European nations for businesses looking to migrate or expand to selected countries in Europe.

A research gap helps identify what separates a current study with previous studies (Muller-Bloch & Kranz, 2015). Muller-Bloch and Kranz (2015) created a vigorous framework for identifying the research gap in qualitative analysis where they illustrated a definition of the said concept of research gap. According to the authors, the gap is defined as a fundamental goal of reviewing literature which proposes a new concept that fills in a gap of research never had been filled before. Therefore, for this research paper the research gap will be illustrated in tabular format.

illustration not visible in this excerpt

Table 1: Research gap

As it can be seen from the table above, there have been numerous studies done regarding Hofstede’s cultural dimensions and socio-economic development. However, all of these studies are extremely niche and very specific. This not only shows that there are various gaps to be filled due to the niche patterns of these studies, but it also shows that there has not been done a study which entirely focuses on only Hofstede’s cultural dimensions’ impact on the HDI of European countries.

1.2.1 | Research Problem

A major difficulty in this research paper is the usage of Hofstede’s dimensions. Although the dimensions are easy to calculate on because of their numerical scores and save time in doing so in research (Hofstede, 2018), the model of Hofstede itself has been mentioned various times by various authors that it is out of date and slowly leaving relevance (Taras, et al., 2012). Therefore relevance is a method that can be improved in future studies by perhaps giving more time to the study and using a newer cultural model with surveys to reach numerical scores and get even more relevant outcomes.

1.3 | Research Aim

As Hofstede said himself “National Culture cannot be changed, but you should understand and respect it” (Hofstede, 2018). The aim of this research is to find the impact of Hofstede’s cultural dimensions on the HDI of European nations. This is because this research aims to fulfill two different sectors of learning.

The first sector is teaching, this research can help the learning process of understanding the impact of national culture on socio-economic development. It can be used by professors, researchers, students, and even independent knowledge seekers to further understand how culture impacts human development and what are its good and bad points.

The second sector of teaching is helping businesses. It can prove to be useful for businesses to know how culture affects socio-economic development for various different sectors in business in order to either improve their business model or to gain knowledge about European nations before entering the market.

1.4 | Research Objectives

ü To examine the impact of Hofstede’s 6 Cultural Dimensions on Human Development Index

1.5 | Research Questions

ü What is the impact of Hofstede’s 6 Cultural Dimensions on Human Development Index?

1.6 | Research Structure

This research will follow a pattern of five individual chapters. Chapter one, introduction, will introduce the research title, the models that will be used, the variables that will be used, the gap in the research, the importance of the research, the aim of the research, the research objectives and the research questions. The second chapter will be the literature review where key terms will be defined along with a critical review of the theory and models. The literature review will also implore past empirical studies related to the topic and a summary of variables which will introduce a conceptual framework of the study whilst formulating hypotheses for the study. Next will come chapter three, methodology, where the research paradigm will be stated, the research design and methodology will be established, a data collection method will be chosen, population and sample population sizes will be determined, accessibility will be indulged, and the ethical considerations as well as the data analysis plan will be revealed. Once the data is collected, it will be calculated using software and the results will be thoroughly discussed. The results will reveal whether upcoming hypotheses are accepted or rejected. It will then conclude the paper with recommendations and implications for future uses of this research and ways to improve it.

2.0 | Literature Review

2.1 | Definition of Key Terms:

2.1.1 | Hofstede’s Cultural Dimensions (8 Definitions)

According to the model, there are six cultural dimensions: Power Distance, Individualism, Femininity, Uncertainty Avoidance, Long Term Orientation, and Indulgence (Hofstede, 2018). Each country was tested by the model and each dimension received a score out of hundred. These dimensions can be seen as a spectrum where each end of the score dictates different cultural behaviors of a nation. Geert Hofstede defines these dimensions as a management tool used to determine better management practices in each specific country usually done for the process of internationalization (Hofstede, 1984). Mastin and Kang define power distance as the distance of power between two employees on different levels indicating that the higher the distance, the less approachable the higher staff is (Kang & Mastin, 2008). Shi and Wang define the model’s Individualism scale as the higher the country is on the scale the more the people in the country will be individualistic and look out for their own well being first; the opposite end of the spectrum shows that people are more collectivistic and work better as a team (Shi & Wang, 2011). Orr and Hauser define Hofstede’s third dimension of feminine/masculinity as power versus nurture where as a masculine society will cater more importance towards power whereas a feminine society will be more of a nurturing society (Orr & Hauser, 2008). Laura Migliore defines it uncertainty avoidance a personal level by implying that this dimension if on a high scale will ensure people are more prepared and have various mitigation plans compared to countries with this dimension on a lower scale (Migliore, 2011). Signorini and Wiesemes defines long term orientation as countries who put long term goals ahead of them first if they are high on the scale rather than countries on a lower scale who prefer to live in the moment (Signorini & Wiesemes, 2009). Bergiel et al. defines indulgence as a really important dimension which illustrates whether or not a country fixates on happiness or not. Countries with a high score of indulgence would have people who would choose happiness over working extra and vice versa for countries with a lower score (Bergiel, et al., 2012).

2.1.2 | Human Development Index (3 Definitions)

The human definition index is a way to calculate human development by immersing various factors and setting a score on them; these factors include life expectancy, education, and income per capita as mentioned by Elizabeth Stanton (Stanton, 2007). Sabrina Alkire defines human development index is expanding the freedom of people in a country so they can choose what to do with their lives (Alkire, 2010). Kamal Dervis defines the human development index as a method of measuring human progress as relative to other countries (Dervis, 2011).

2.2 | Critical Review of Models and Theories

There are a total of two models that are being used for this research paper. Both of the models are in the title. The first model is Hofstede’s cultural dimensions developed by Professor Geert Hofstede (2018) which portrays six dimensions in total for each country (Appendix A). The second model is the Human Development Index developed by Muhab Ul Haq which portrayed human development through 3 variables (The Economic Times, 2018).

Hofstede will be justified by being compared to two other models of national culture. The first model is Hall’s contextual model of culture (Hall, 1989) and the other is Trompenaar’s cultural dimensions (Trompenaars & Hampden-Turner, 2011). HDI will be justified by being compared to Duncan’s Socioeconomic Index or SEI for short (Duncan, 1961). It will also be compared to Hollingshead’s Four Factor Index of Social Status (Hollingshead, 1975).

Hofstede’s Cultural Dimensions

Hofstede’s 6-D Cultural Dimensions (Hofstede, 2018)

Description

6 Dimensions, including Power Distance, Individualism, Femininity/Masculinity, Uncertainty Avoidance, Long Term Avoidance, Indulgence/Restraint to measure cultural differences in countries

Strengths

Data is readily and accurately available through Hofstede’s official website (Compare Countries Hofstede, 2018). The model analyzes organizational culture alongside with national culture for better accuracy along with the fact that is one of the highest cited models of all time (Huettinger, 2008). The model is constantly being improved and expanded to attain more countries for a wider research possibility (Taras, et al., 2012). Perhaps the biggest strength comparison between the other models is that Hofstede’s dimensions have numerical scores between 0 and 100. This is a big advantage because ready-made officially released scores are much better compared to models which do not have scores. Both Hall and Trompenaar’s models have no scores attached to them and if a numerical analysis is to be done, primary research and questionnaires might need to be done which cannot be done in this desk-based research project. This method of assigning numbers to the model also goes against the time restraints forced upon this research paper.

Weaknesses

The core methodology of the model was questioned by the authors as they did studies with the methodology and found varying results showing inaccurate findings (Orr & Hauser, 2008). It was also argued that people misuse the concept of this model and get results which are inaccurate and that is academically not allowed (Orr & Hauser, 2008). It was also argued that the results of the study are not stable over the course of time due to various external factors such as immigration and tourism (Sjoerd, et al., 2015)

Hall’s Contextual Model

Hall’s Contextual Model (Hall, 1989)

Description

Categorizes countries into two different levels of context (high-low) and relates a series of variables to each context type suggesting a basic “opposites” model:

illustration not visible in this excerpt

Figure 1: Hall's Contextual Model (Hall, 1989)

Strengths

Has a series of variables involved in it which allows the model to achieve a broad spectrum of niche cultural factors allowing for an in-depth research (Zautra, et al., 2010). Compared to Hofstede’s cultural dimensions, these dimensions are not generalized but in fact are very specific and niche (Cardon, 2008). Finally, since the concept of Culture is divided into two different extremes, it allows for different branches of interpretations to be made from just these variables. Hall also goes into different cultural models of space and time which further elaborate on culture on a much deeper model compared to Hofstede (Cardon, 2008).

Weaknesses

In terms of weaknesses, Hall’s contextual model, if done fully with all variables adds a lot of time constraints to a research paper due to the excess amount of factors involved. Secondly, Hall’s cultural factors are incredibly niche and one can reach difficulties when evaluating culture on a broad spectrum such as a country or continent. Finally, since the cultural factors of Hall have no numerical values attached to them, it makes it difficult for calculative researches (Cardon, 2008; Hall, 1989)

Trompenaar’s Cultural Dimensions

Trompenaar’s Cultural Dimensions (Trompenaars & Hampden-Turner, 2011)

Description

Highly similar model to Hofstede where culture is divided into a number of dimensions. Contrasting to Hofstede, Trompenaar’s model has 7 dimensions:

illustration not visible in this excerpt

Figure 2: Trompenaar’s Cultural Dimenisons (Trompenaar & Hampden-Turner, 2011)

Strengths

The model offers similar dimensions as compared to Hofstede, however it adds another dimension to the mix allowing for a more broader research paradigm (Trompenaars & Hampden-Turner, 2011). The model is much more recent compare to Hofstede’s dimensions and authors are arguing that its modernism allows for a more relevant cultural study (Orr & Hauser, 2008). Trompenaar’s, similar to Hall (1989), has a time based dimension in one of his seven dimension which is something Hofstede has not covered in depth so far (Trompenaars & Hampden-Turner, 2011).

Weaknesses

The cultural dimension is slowly gaining popularity but this means that compared to Hofstede and Hall there are not many researches using this model so far. This shows a lack of research material which could cause research problems (Google Scholar, 2018). Secondly, although the dimensions are similar to Hofstede’s, Trompenaar’s does not have official dimension scores making it difficult for a regression to be done in low time constraints.

Justification of Hofstede’s Cultural Dimensions

There are more than one models which are globally accepted as models of national cultures; models such as Hall’s contextual model (Hall, 1989), Hofstede’s cultural dimensions in 1980, and even Trompenaar’s cultural dimensions (Trompenaars & Hampden-Turner, 2011). Although each model has its own set of advantages and disadvantages, and it has been argued that there are models more accurate and specific than Hofstede’s cultural dimension (Crane, et al., 2016, p. 20). However, it is also worth noting that Hofstede’s work currently is the most cited work available online (Ferraria , et al., 2014). It is also worth noting that Hofstede’s cultural scores have been officially and readily collected all properly placed in the official website giving it a sense of convenience that this research paper needs due to time constraints (Hofstede, 2018). Hofstede has official websites which have scores available and data ready to be collected and calculated (Hofstede, 2018). Even if the other cultural models are more relevant and modern, the fact that Hofstede has so much literature available online and the fact that it has scores available online makes it perfect for this desk based research project which is limited due to time constraints.

Human Development Index Critical Review

Human Development Index (The Economic Times, 2018)

Description

Created by a Pakistani economist, the Index creates a relative scoring system of general human development based on life expectancy, overall education acquired, and national income per capita. (The Economic Times, 2018)

Strengths

The United Nations Development Programme releases a HDI report every year and it is one of their best and most accurate tools of measuring human development (The Economic Times, 2018). The official UNDP page released an official informational panel on HDI where they mentioned that it is an external outlook of human development as before only the GDP showed a nations progress (Jahan, 2018). The page also mentioned that the HDI is the border between measuring human development which is not as shallow as just measuring income since there are other factors contributing to human well-being (Jahan, 2018).

Weaknesses

The HDI is not a comprehensive measurement of human development but rather a shallow overview (Jahan, 2018). A critical paper of the HDI done shows various criticisms such as it restricts the socio-economic sphere of life ignoring political aspects as well as civil aspects rendering it less accurate (Bagolin & Comim, 2008). The paper also argues that human development is so complicated and complex that it can’t possibly be measured by an Index that only follows a few variables (Bagolin & Comim, 2008).

Duncan’s Socioeconomic Index

Duncan’s SEI (Duncan, 1961)

Description

In 1969, Otis Dudley Duncan used 1950 consensus data of education and income to create a numerical index of socio-economic status as a unique index that can be used for research.

Strengths

At its time, the research was brand new and proved to be very useful for researchers as it is the earliest showing socio-economic index when searched online (Google Scholar, 2018). Education and income are a very specific niche and once combined into an index can be used for various studies about GDP and job projections by researchers and even governments. Finally, having a numerical index gives it various time and convenience advantages over models which are non-numerical (Grimes & William, 1974).

Weaknesses

The index is one of the first of its kind yet it is very old and is from consensus data from 1950. That is an outdated consensus and it will make modern researches using this method invalid (Google Scholar, 2018). Education and Income are just two factors, compared to HDI and Four Factor Index this index only has half the amount of variables the other two has (Hollingshead, 1975; Jahan, 2018).

Hollingshead’s Four Factor Index

Holliongshead’s Four Factor Index of social status (Hollingshead, 1975)

Description

In 1975 August B. Hollingshead designed a social index based on four different factors: Marital Status, Employment Status, Educational Attainment, and Occupational prestige.

Strengths

The model is widely used by various scholars as one of the primary socio-economic indexes (Google Scholar, 2018). The four factors index is another numerical index and has various factors involved in it for a various research papers. Since this is another numerical index, it gives it advantages over non-numerical indexes which make it difficult for numerical regressions (Grimes & William, 1974).

Weaknesses

The “nuclear family” has changed since 1975 considering divorce statistics and same sex marriages. A part time worker is not classified in this index making the data inaccurate in that sector only. Finally, a stay-at-home partner in the family who takes care of the house is not included in the model which is an important factor of social upkeep (Costello & Osborne, 2005).

Justification of HDI

UNDP adopted HDI as an index over the other models giving it more global backing. This enough should justify why HDI should be used because UNDP keeps the model up to date and offers numerical data on it every single year (UNDP, 2018). Secondly, this model is specifically based on human development whereas the other indexes are either out of date or are not completely relevant to this study. Therefore it can be concluded that HDI is the best index to be used in this research paper.

2.3 | Literature Gap: Empirical Studies in the last 10 years (10)

Due to lack of literature access available online as well as time constraints, a maximum of ten (10) empirical studies were found which closely related to Hofstede and Human Development. Although this is not ideal, it provided enough information for a literature gap to be discovered and hypotheses to be formed.

Basabe et al. (2010) did a research on Cultural dimensions, socioeconomic development, climate, and emotional hedonic level using national data from 25 countries where data was available including many European countries. Their sample size was 2,955 students 70% of which were female. Their variables included 4 of the 6 cultural dimensions from Hofstede (Hofstede, 2018), their dependent variables were HDI and climate. Their results showed that Individualism showed positive correlation with subjective well-being and various other factors such as socio-economic development control, power distance, uncertainty avoidance, and climate. They also found that Power Distance and Uncertainty Avoidance has a negative impact socioeconomic emotional pleasantness, Masculinity has a negative effect, and Individualism has a positive correlation. Their limitations, which were included in their paper showed single-term inventory scores which shows results can be further accurately proceeded if approached more thoroughly (Basabe, et al., 2010). The gap here was that they did not use all available European countries and the fact that they only used 4 of the six Hofstede’s dimensions.

Driouchi and Gamar (2014) wrote a paper on Hofstede’s Cultural Indicators, Knowledge Economy and Entrepreneurship in Arab Countries where they gained data from World Bank and Hofstede (2018). Although their study was directed towards countries in the Arabic gulf, they compared their results to Eastern European countries to gain relevant information. Their sample size was Arabic gulf countries and Eastern European through an empirical analysis. Their variables included Hofstede’s cultural dimensions (Hofstede, 2018) and dependant variables were HDI and Knowledge Economic. The results of their research do reveal a link between the dependant and independent variables and through that it revealed a gap between Arab and Eastern European Countries. They also discovered a link between entrepreneurship and cultural variables in Arabic nations. Their biggest limitation of the study as mentioned by the authors is a limited number of observations even though the results are sufficient. With more observations perhaps a more accurate result can be revaled (Driouchi & Gamar, 2014). The gap here is that only Eastern European nations were used and limited number of Hofstede’s dimensions was used.

Yeganeh (2014) wrote a paper called Cultural values and gender gap: a cross‐national analysis. The purpose of this paper was to investigate how the gender gap is affected by cultural values through an empirical study. Their sample size was 53 countries, a lot of which were European countries. Their variables were HDI, GDP, Hofstede’s cultural dimensions and Schwartz’s cultural dimensions. Results in their research showed that controlling socio-economic variables does have impacts on gender gaps. They also speculated that autonomous cultural dimensions could perhaps lead to gender equality. A major limitation of this paper as stated by the author is that it resides in the theoretical framework and linear data analysis techniques. It implies that it relies heavily on the theoretical framework (Yeganeh, 2011). The gap here is that they did not use all European nations and the fact that their study was more gender focused and so not many regressions were done using Hofstede’s dimension on focus with Human Development Index.

Martins and Lopes (2016) wrote a paper on Culture and Profitability: Empirical Evidence at a European Level where they targeted all European countries. Their sample size was 450 financial companies in europe and their variables were Hofstede’s cultural dimensions, profitability (ROA and ROE). Their results that companies that have high overall profitability also showed specific patterns on Hofstede’s cultural dimensions indicating a clear pattern forming. They found that countries with higher development correlated with low Power Distance, Uncertainty Avoidance, and Long Term Orientation as well as higher Indulgence. The limitations on the study were that they only studied a cultural impact on profitability and although there were results, high or low profitability could be caused by an array of factors other than culture (Martins & Lopes, 2016). This study did use most of Hofstede’s cultural dimensions but they did not compare countries, they compared companies.

Edvard Konrad (2012) wrote a paper on National Cultures and Human Development Index. This research used 9 cultural dimensions including Hofstede on 60 Countries, 14 of which were European nations. According to their results, not all but some cultural factors showed an impact on HDI with acceptable amounts of deviation. Relevant results show that Power Distance and Collectivism shows positive correlation with HDI. Limitations of the study included the fact that countries were handpicked within sub regions and therefore do not give a region wide average or deviation (Konrad, 2012). This paper only used 14 European nations and used only 2 of the 6 Cultural dimensions.

Činjarević & Veselinović (2017) wrote a paper on The Interplay of Socioeconomic Development, Enterpreneurship, National Culture and innovation Performance where they calculated the interplay of Hofstede’s dimensions, HDI, GEM, GII across 77 countries within 7 regions of the world including Europe. Their results regarding Hofstede’s impact on HDI showed that lower power distance nations have a higher innovation performance. According to the authors, a major limitation is not getting sufficient data from low income countries and so those nations were not in the study (Činjarević & Veselinović, 2017). This paper only used a few European nations and only 2 of the 6 cultural dimensions.

Lopes & Serrasqueiro (2017) wrote a paper on The influence of culture and transparency on global research and development intensity: An overview across Europe where they did a cross cultural study on Europe testing the impact of culture on general human development. Their results showed that all dimensions have an impact but Power Distance and Masculinity has a negative impact whereas the other dimensions have a positive signal. According to the authors, future research could be done with more countries to help increase the research pool and get more varied results (Lopes & Serrasqueiro, 2017). This paper did use all of the cultural dimensions on all European countries but they did not use that to measure the impact on HDI but rather just general human development; therefore the gap here is that the HDI model wasn’t in play.

Duguleana (2014) wrote a paper on National Cultural Dimensions And Well-Being In Some Countries Of The World, In 2013 where she used Hofstede’s cultural dimensions, Erin Meyer’s Cultural Map, HDI, and CPI. This was done in European nations amongst a few others. The results were varied and Hofstede’s dimensions were aligned with Erin Meyer’s cultural map. Collectivism was shown to have strong a strong positive impact on HDI. Uncertainty avoidance and Masculinity also showed a strong negative impact on HDI. Since this paper was mostly educational, their limitations are expanding the countries and adding more cultural factors for a better understanding (Duguleana, 2014). This paper did not use all European nations and only 3 of the 6 cultural dimensions were used.

Onel & Mukherjee (2014) wrote a paper on The effects of national culture and human development on environmental health where they used Hofstede’s dimensions, and HDI and measured its impact on Environmental Performance Index (EPI) within 67 countries including European Countries. Their findings were irrelevant to this study but they did mention in the end that 3 hypotheses were nulled due to the HDI having a high positive correlation with Power Distance and Individualism. Their study was limited to the fact that it was just a baseline study and it gives way to more in depth and specific studies in the future (Onel & Mukherjee, 2014). This paper did not use all European nations and only 2 dimensions were correlated with HDI.

Matusitz & Musambira (2013) did a research on Power Distance, Uncertainty Avoidance, and Technology: Analyzing Hofstede's Dimensions and Human Development Indicators where they took a few of Hofstede’s dimensions, HDI, and technology and did regressions. They did this on UN nations which includes a lot of European countries. Their results which are relevant to this study found a negative correlation between power distance and HDI. According to the authors, more technology indicators can be used for a broader spectrum of results in the future (Matusitz & Musambira, 2012). This study only worked with United Nations countries involved in Europe and only 2 cultural dimensions were used.

As it can be seen from the studies reviewed above, Hofstede’s cultural dimensions is a highly used tool in order to measure Human Development. Furthermore, Human Development is usually measured by the Human Development Index. Lastly it can also be seen that various studies find the impact Hofstede’s cultural dimensions on the Human Development Index. However the gap discovered here is that although the model is applied, usually a certain amount of the 6 total dimensions are used. Secondly a gap was also discovered that no study so far has done this research purely from all dimensions on just the European continent. Therefore, the literature gap here which this research gap will fulfil is that it will initiate a study calculating the impact of all of Hofstede’s cultural dimensions on the entire available continent of Europe.

2.4 | Summary of Variables

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Table 3: Summary of Variables

There are various socioeconomic factors which contribute to human development and can theoretically be impacted by culture. However the chosen variable for this research paper is the Human Development Index solely because this index comprises of various socio-economic factors making it relatively more accurate than just one socio-economic factor (Jahan, 2018). Furthermore, it was shown in the critical review of models and theories that this index is more relevant and up to date compared to other indexes.

2.5 | Formulating Hypotheses

Based on the above literature review of the empirical studies it can be assumed that Hofstede’s cultural dimensions (Hofstede, 2018) as independent variables do in fact have an impact on dependent socioeconomic factors such as the variable of the Human Development Index (Jahan, 2018). Therefore the following hypotheses can be derived from the following data:

H1: Hofstede’s Cultural Dimension of Power Distance negatively and significantly impacts the Human Development Index when it is high on the scale. This hypothesis was reached due to similar results found in various authors in empirical researches such as: (Činjarević & Veselinović, 2017; Lopes & Serrasqueiro, 2017; Basabe, et al., 2010; Martins & Lopes, 2016; Matusitz & Musambira, 2012; Konrad, 2012). However a strong positive relation was shown in (Onel & Mukherjee, 2014) but is outnumbered by other authors.

H2: Hofstede’s Cultural Dimension of Individualism positively and significantly impacts the Human Development Index as opposed to collectivism which has opposite effects. This hypothesis was reached due to similar results found in various authors in empirical researches such as: (Basabe, et al., 2010; Lopes & Serrasqueiro, 2017; Onel & Mukherjee, 2014; Konrad, 2012). However (Duguleana, 2014) showed negative results but is outnumbered by other authors.

H3: Hofstede’s Cultural Dimension of Masculinity negatively and significantly impacts the Human Development Index as opposed to Femininity which has opposite effects. This hypothesis was reached due to similar results found in various authors in empirical researches such as: (Lopes & Serrasqueiro, 2017; Basabe, et al., 2010; Duguleana, 2014).

H4: Hofstede’s Cultural Dimension of Uncertainty Avoidance positively and significantly impacts the Human Development Index when it is high on the scale. This hypothesis was reached due to similar results found in various authors in empirical researches such as: (Lopes & Serrasqueiro, 2017; Basabe, et al., 2010). However, negative correlations were shown in (Duguleana, 2014; Martins & Lopes, 2016). Yet positive correlations are favoured here because the positive studies are more relevant to this research paper compared to the negative studies.

H5: Hofstede’s Cultural Dimension of Long-Term Orientation positively and significantly impacts the Human Development Index when it is high on the scale. This hypothesis was reached due to similar results found in various authors in empirical researches such as: (Lopes & Serrasqueiro, 2017) showed a positive correlation in their results. However, (Martins & Lopes, 2016) showed negative results. Yet positive correlations are favoured here because the positive studies are more relevant to this research paper compared to the negative studies.

H6: Hofstede’s Cultural Dimension of Indulgence impacts positively and significantly impacts the Human Development Index as opposed to restraint which has opposite effects. This was because (Lopes & Serrasqueiro, 2017; Martins & Lopes, 2016) both showed similar correlations.

2.6 | Conceptual Framework

With the hypotheses formed and literature gap discovered, a conceptual framework can be produced to visualize the hypotheses of this research paper.

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3.0 | Methodology

3.1 | Research Design

According to Russell Schutt, there are three main designs of a research, a Descriptive research, an Explanatory research, and an Exploratory research. A research paper can either be one of those designs or it can be a unique combination of them (Schutt, 2011). This design dictates which direction the research will take in terms of gathering data and conducting the analysis. The design of the research is determined by the available time the researcher has, the topic that is being chosen, and the chosen variables as well as the availability of data in terms of volume of depth.

3.1.1 | Descriptive Research

A descriptive research, true to its name, gathers information on a topic that has already been well discovered and finds in-depth details of the said topic to further explore it. In his book, Russell Schutt on page 47 of his book explains this phenomenon by saying that sometimes when a study which is purely descriptive it usually expects no connection of theories and it is just meant to further explain a a phenomenon (Schutt, 2011). Therefore this method of research is mainly used to describe a phenomenon in its very depth.

3.1.2 | Exploratory Research

This type of research design is set very differently from other types of research design, exploratory research goes into research areas which have not been dabbled with much; Russell Schutt on Page 45 of his book mentions that Exploratory research usually involves qualitative research which makes use of gathering primary data in order to answer questions which were previously unanswered. Therefore, it can be concluded that research which is purely exploratory involves (Schutt, 2011).

3.1.3 | Explanatory Research

Explanatory research, according to Russell Schutt on Page 14 mentions that Explanatory research explains different phenomenon. Another name for this kind of research is the Cause and Effect research. True to the name, this research explains the causes and/or the effects of variables when they act on other variables. This method is used vastly in testing theories and models to answer questions about phenomenon that have already been explored but are not connected together (Schutt, 2011).

Although more can be mentioned about the Explanatory research design as well as the two other research designs, based on the data above and the models and variables chosen, it is clear that this research will be an explanatory research. Reason being that this theory explains and connects different theories and models that have already been well research. Hofstede’s cultural dimensions (Hofstede, 2018) and the HDI (Jahan, 2018) have already been well researched and this research method will help connect them.

3.2 | Research Methods

3.1.1 | Research Paradigm

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According to Ochieng Pamela Atieno, the research paradigm can be seen as a spectrum. Each end of the spectrum contains either a purely qualitative or a purely quantitative research. Exactly in the middle of the spectrum contains a mixed methods study (Atieno, 2009). This phenomenon continues to different parts of the spectrum but for simplicity’s sake more information will be refrained from this topic. This can be better understood by the illustration below created based off of Atieno (2009):

Considering this paper will involve two variables, one Hofstede’s cultural dimensions which is measured by scores out of hundred (Hofstede, 2018) and second is the Human Development Index which too has numerical 3 digit scores between 0 and 1 (Jahan, 2018). It can be concluded that this research paper will be a purely quantitative research.

3.2.2 | Data Collection (Primary or Secondary)

Marianne Fallon wrote a book section explaining the phenomenon of primary data collection (Fallon, 2016). There, she mentioned the importance and significance of primary data collection. She explains primary data to be data that has not been collected yet and therefore it is much more difficult to obtain compared to secondary data. Primary data is also much more accurate, personalized to primary research and is usually used in an explanatory research to answer questions that were previously unanswered (Fallon, 2016).

Melissa Johnston wrote a paper regarding secondary data collection and its importance (Johnston, 2017). In this paper she defines secondary data to be data which has already been published and/or made available and this data is used mostly in quantitative analyses in order to answer questions and make connections in explanatory researches. Secondary data is usually much more vast compared to primary data but has less depth to it and is mostly surface data.

Therefore based on the information and the fact that the data that will be used from Hofstede’s dimension (Hofstede, 2018) and the HDI data (Jahan, 2018) that will be used in this research is already collected and published making the data collection method for this research paper a secondary data collection method.

3.2.3 | Population

According to the official United Nations Development Program (UNDP) which releases HDI reports annually and uses HDI as a big part of their development calculations, there are 188 countries and various other regions and territories that have been part of the HDI calculation (UNDP, 2018). Therefore the total population available for the HDI is the amount of countries that are involved in the project. In terms of Hofstede’s cultural dimension, the official data matrix for the dimension scores are in the official Geert Hofstede websites and the entire data matrix consists of dimension scores from 111 countries in total (Hofstede, 2015).

3.2.4 | Sample Size

According to Emma Uprichard, there are two ways of collecting a sample from a population, there are probability methods and non-probability methods. The best method of choosing a sample can be determined from the variables, data, and time at hand (Uprichard, 2013).

Now that the total population has been established, the sampling size can be chosen. The sample can only be taken from the entire population, this means that the sample can be derived from whatever data that is available from both the models mentioned in the previous section. Since the research paper is about countries in Europe, the most efficient way to gather the sample data would be to retrieve data from the available population at hand from countries which are only from Europe. According to the Central Intelligence Agency (CIA)’s world map data, the physical continent of Europe has a total of 44 countries in it (CIA, 2018). A list was created deriving from that data officially listing the European countries in the world (Appendix B).

The latest global HDI reports released by the UNDP are of 2015 (UNDP, 2018), therefore reports from 2011-2015 can be taken as the latest HDI reports for a longitudinal time study. In terms of Hofstede, after thorough investigation it was determined that Hofstede scores do not get updated much. First, an official email was sent to the domain which hosts the Hofstede Cultural Dimensions < info@hofstede-insights.com> (Hofstede, 2018). A reply was given which can be seen in Appendix C redirecting me to another official website by Geert Hofstede (Hofstede, 2018) which mentioned two things. First it mentioned that a sixth dimension was added in 2010, and the second thing it mentioned was that dimension scores are similar to culture, therefore they do not usuall change once they are set (Appendix C). Therefore, the data matrix of 2015 Hofstede scores can be used (Hofstede, 2015) along with the Country Compare tool from Hofstede’s website (Hofstede, 2018) to get the sample scores.

Finally, if the list of European Countries are tallied with the available countries where both HDI and Hofstede have complete scores available, a sample can be generated with full data on European countries with both Hofstede and HDI sampling resulting with 33 countries after all the filtering of data (Appendix D).

This form of sampling is known as convenience sampling and is usually used when the research depends on the variable data available and can only use as much data as there is data available (Uprichard, 2013).

3.3 | Ethical Consideration

Considering that both Hofstede’s cultural dimensions and the HDI reports were available online and free to download, and the fact that secondary data does not promote much of an ethical issue (Tripathy, 2013), the ethical consideration verdict is that this data is allowed to be use. However, going one step further shows that both HDI and Hofstede’s dimensions gave permission for the data to be used. On the UNDP’s Human Development Report’s Copyright page (UNDP HDR, 2018) it was stated that data provided is free to use, manipulate, and change as long as proper credits are provided (Appendix E). In the official Geert Hofstede website (Hofstede, 2018), they mentioned that this data is free for academic use (Appendix E). This concludes that enough Ethical consideration has been done for this research.

3.4 | Analysis Method

Due to the fact that only 33 countries are being tested and the fact that time management allows for more of an in-depth study, the suitable method chosen for this research paper is to conduct a longitudinal study of testing the impact of Hofstede’s cultural dimensions over the latest five years of HDI publishing (Caruana, et al., 2015). This is due to the fact that Longitudinal studies are a reputable way of calculating patterns and regressions over an available time-frame giving more accurate results in studies such as this as mentioned by Caruana et al. (2015). A major disadvantage of this method of analysis is that if all the data from all the years is not deemed accurate then it could greatly affect the outcome of the study. Fortunately for this study, the sources of data were retrieved directly from the primary sources and nowhere else resulting in the data listed in Appendix D free of tampering and error (Hofstede, 2018) (UNDP, 2018).

3.5 | Data Analysis Plan

Data analysis will be done through software. Modern technology allows for various different software services that are able to calculate large amounts of data. This data calculations can be done in various different methods. The Software that will be used is called SPSS.

SPSS is a data analysis software which is owned by IBM (Analytics, 2017). This software will allow for various different analyses to be done. Since there is to be quantitative data at hand, there will be many numbers to deal with.

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Table 2: Data Analysis Methods

For the data, type of research, and variables at hand, the best course of action would be to use Regression as the chosen method of data collection. However, a combined data analysis from SPSS will also result in a Normality and Descriptive analysis which will also be incorporated into the results

3.6 | Research limitations

Although this research is rigid in its structure and has laid out a plan for the continuing research, there are a few limitations to this research. For starters, a big limitation is the data availability. The latest HDI reports are from 2015 and backwards, even though the current year is 2018, the research will be done in a time period of 2011-2015 due to the limited availability of data (UNDP, 2018). Secondly, this research paper is only testing on two variables. A more in depth research will have a higher number of independent and dependent variables to increase the reliability of results. Finally, this research is a secondary research paper, if this research was done in a primary method, more customized data would have been collecting resulting in a more accurate and specified study.

4.0 | Results & Discussion

4.1 | Descriptive Analysis

For the descriptive part of the analysis, two major indicators will be discussed in this part of the research paper. The two indicators are the Skewness and Kurtosis indicators. This is because these two indicators are essential for indicating normality and healthy distribution in a descriptive statistic (Kim, 2013).

In order to measure the irregularity of distribution amongst a variable, the skew is present. Skewness generally is present visibly on a bell cruve with left and right tails. The general rule of law of skewness is that a result is normally distributed when the skewness is perfectly 0. Any number going above or below 0 will tend to reach a positive (right tail longer on the bell curve) or a negative (left tail longer on the bell curve) skew respectively as mentioned by Kim (2013). West, et al. (1995, p.57) states that when a skew reaches a positive or a negative value of two then the results are significantly farther away from normality resulting in an insignificant result of statistics. This is illustrated in Figure 1:

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Figure 3: Types of Skews (Kim, 2013)

Whilst Skewness is used to measure positive or negative insignificant data, Kurtosis is used to measure the peak data. A more accurate statement would be to say that kurtosis measures the highest value of distribution. The general rule of law in this test is that if a value is too high or too low then the results significantly differ from normality resulting in a failed result (Kim, 2013). A high or low kurtosis can be visualized through the peak of a bell curve, an unnaturally high kurtosis result would result in a leptokurtic peak, an unnaturally low kurtosis result would result in a platykurtic peak, and a normal (within significant range) kurtosis result would result in a mesokurtic peak (Kim, 2013). This is further elaborated by Figure 2 below:

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Figure 4: Illustration of Kurtosis peaks (Kim, 2013)

4.1.1 | Normality and Kurtosis

Continuing above, Table 3 below shows the results of the descriptive statistics with the bolded columns mentioning the skewness and kurtosis results for all the independent and dependent variables in this research paper. According to the explanations above and a SPSS book written by Andy Field (2013), it is said that skewness between -2 and +2 is considered normal and Kurtosis between -3 and +3 is too considered normal and acceptable (Field, 2013, p. 237). In order to calculate the numerical values mentioned above, for both Skewness and Kurtosis, the statistic needs to be divided by the standard error (Std. Error) and the resulting number needs to be compared to the range. This is listed in the “Results” column in Table 3.

Descriptive Statistics

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Table 3: Descriptive Statistics (SPSS Generated)

4.1.2 | Interpretation

Power Distance: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of 1.764 which is a positively sided skew. Considering the rule of thumb this is within the range of -2 to +2 skewness giving this variable a normal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -1.961 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Individualism: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of -2.568 which is a negatively sided skew. Considering the rule of thumb this is not within the range of -2 to +2 skewness giving this variable an abnormal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -2.374 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Masculinity: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of 0.918 which is a positively sided skew. Considering the rule of thumb this is within the range of -2 to +2 skewness giving this variable a normal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -2.091 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Uncertainty Avoidance: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of -2.668 which is a negatively sided skew. Considering the rule of thumb this is not within the range of -2 to +2 skewness giving this variable an abnormal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -1.711 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Long Term Orientation: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of -0.973 which is a negatively sided skew. Considering the rule of thumb this is within the range of -2 to +2 skewness giving this variable a normal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -2.425 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Indulgence: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of 0.082 which is a positively sided skew. Considering the rule of thumb this is within the range of -2 to +2 skewness giving this variable a normal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -3.667 which is a platykurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are abnormal.

Human Development Index: According to Table 3 above, the skewness results from dividing the statistic by the standard error above resulted in a figure of -2.281 which is a negatively sided skew. Considering the rule of thumb this is not within the range of -2 to +2 skewness giving this variable an abnormal result. In terms of Kurtosis, dividing the statistic by the standard error resulted in a figure of -1.788 which is a mesokurtic result if one follows the rule of -3 to +3 kurtosis. Therefore, the kurtosis results in this variable are normal.

Therefore, to conclude this section, individualism, uncertainty avoidance, and the human development index had abnormal skewness. Secondly, only indulgence had abnormal kurtosis. The rest of the results were in the range of normality.

4.1.3 | Mean and Standard Deviation

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Table 4: Descriptive Statistics Table (SPSS Generated)

The mean and standard deviation levels can be used to determine whether or not the data set has been accurately calculated. For instance, the minimum and maximum statistic of each dependent and independent variable can be tallied with the data set in Appendix D. The data set is within range of the data provided to the software with no Hofstede score going below 0 in minimum and no score going above 100 in the maximum statistic. This is correct because Hofstede only measures in a scale between 0-100 (Hofstede, 2018). Similarly for HDI, the scores are in par with the data table in Appendix D. On top of that, the minimum and maximum score lie within range of HDI functionality as it only works between 0 and 1 mostly portrayed in a three decimal point range due to simplification of various decimal points (UNDP, 2018). The mean and standard deviation are also presumably correct considering that the data set is accurate and what it was intended to be. The amount of deviation between Hofstede scores is random showing differences in culture for all the European nations. The mean ranges for both Hofstede and HDI are within their designated numerical range points of between 1-100 and 0-1 respectively.

4.2 | Charts

This section will interpret all charts generated by SPSS (Analytics, 2017)

4.2.1 | Bell Curve

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Figure 5: Bellcurve HDI (SPSS Generated)

Figure 3 shows the bell curve of all 165 data points in data set. The mean is extremely close to 0 resulting in a well-established and fairly balanced curve. Although abnormalities were discussed in section 4.1.2, the overall curve is well balanced.

4.2.2 | Regression Line

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Figure 6: Regression Line (SPSS Generated)

The plots are quite in par with the regression par with only some sections going off centre. Regression lines as such are deemed acceptable (Hair et al. 2011).

4.2.3 | Scatterplots

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Figure 7: Standardized Regression Plot

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Figure 8: 6 Dimensions Scatter Plot

The rule of thumb for determining whether or not a scatterplot is acceptable or not, it needs to be heteroskedastic rather than homoscedastic (Breusch & Pagan, 1979). When a scatter plot shows a certain pattern or path then it is homoscedastic, and heteroskedastic if it shows no visible patterns. In the case for Figure 5, it shows no pattern therefore making it heteroskedastic. In the case of Figure 6 where all 6 dimensions are shown, all dimensions are heteroskedastic except indulgence which is showing minor signs of homoscedasticity.

4.3 | Regression Analysis

Regression through SPSS (Analytics, 2017) was carried out calculating the impact of Hofstede’s cultural dimensions (Hofstede, 2018) on the Human Development Index (HDI) on European nations (UNDP, 2018). Although the results of SPSS gave out conclusive regression results, it also resulted in related statistics and diagnostics all of which will be at the very least interpreted and discussed in this section. The statistic resulted in a Model Summary, ANOVA statistics, Coefficients, Collinearity Diagnostics and Residual Statistics.

4.3.1 | Adjusted R-Square and Durbin-Watson

Model Summaryb

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Table 5: Model Summary of Regression (SPSS Generated)

As it can be seen in Table 5, the R value ended up being 0.877, the R Square value ended up being 0.768 and the Adjusted R Square value through numerical adjustments by SPSS ended up in a result of 0.760. Therefore what this interprets to is that the independent variables of this research paper can predict 76% of variance related to the Human Development Index (HDI). This is more than an acceptable amount considering that a significant amount is generally accepted as any figure above 60% (Obenchain, 1977, p. 431). Based on the criteria it is certain that Hofstede’s cultural dimension have a significant relationship to HDI variance.

Durbin-Watson score above is listed as a positive 0.457. The Durbin-Watson scores shows autocorrelation between the independent variables and is displayed on a score between 0 and 4; if the score is close to 2 then there is no autocorrelation, if the score is closer to 0 or 4 then there is positive or negative autocorrelation respectively; the general rule of thumb is that there should be no autocorrelation between the independent variables (Savin & White, 1977). The results from the regression show that there is in fact a positive correlation between the independent variables considering the score is 0.457 and that is significantly closer to 0 compared to 2. However, this positive correlation is to be expected considering the 6 independent variables all come from the same model which if Hofstede’s 6 dimensions (Hofstede, 2018).

4.3.2 | ANOVA

ANOVAa

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Table 6: Anova Summary (SPSS Generated)

The ANOVA table in Table 6 portrays a series of calculations such as the Sum of Squares, degrees of freedom (df), the mean square, the F statistic, and the significance. Although all these variables are important and have various uses, they all relate to the significance (Sig.) value at the end of the table. The general rule of thumb for this figure is that the significant figure needs to be below 0.05 for the dependant variable to be statistically significant (Hair, et al., 1998). The ANOVA table thus proves that the dependent variable of Human Development Index with a significance of 0.00 is in fact significant. Another rule of thumb is that the F statistic is more significant the higher it gets. In the case of Table 6, it is 87.381 which mean that there are 87% chances of similar studies coming to similar results elsewhere (Hair, et al., 1998). Overall this ANOVA table proves that this is a fit regression model for this study.

4.3.3 | Hypothesis Testing

Coefficientsa

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Table 7: Coefficients Table (SPSS Generated)

VIF

There are two major parts in Table 7, the Collinearity Statistics and the Coefficients. Starting with the Collinearity statistics the VIF values can be assessed. VIF stands for the Variance Inflation Factor and is the ratio of variance in a model with multiple terms, divided by the variance of a model with one term alone; a general rule of thumb is that if the VIF value is below 10 though the lower the better (Hair, et al., 2011). Table 7 shows all VIF values to be below 3 showing ideal VIF values for all the dependent variables.

Beta Coefficients

Table 7 Indicates a column called “Sig.”, this is the significance column or the P-Value showing the significance of that independent variable on the dependent variable of HDI. The rule of thumb for this coefficient is that if the p-value is less than 0.05 then it is deemed significant and it thus proves the hypothesis true in terms of significant impact. The T column next to the p-value column in table 7 determines positive or negative impact based on whether the value is negative or positive. Finally, the “Standardized Coefficients Beta” column in Table 7 shows a value of impact that independent variable has on the dependent variable as a percentage decimal. Based on this, a table can be made determining whether the hypothesis listed in the Literature review was accepted or rejected.

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Table 8: Aligning Hypotheses with Results

Discussion and Interpretation

In terms of hypothesis, 3 out of 6 Hofstede’s cultural dimensions proved to have a significant impact on HDI. Indulgence and Individualism had a positive significant and Power Distance has a negative significant impact.

- Individualism has a 24.9% positive impact on HDI.
- Power distance has 25.2% negative impact on HDI.
- Finally, Indulgence has a 51.6% positive impact on HDI.

The research objective was to examine the impact of Hofstede’s cultural dimensions on HDI. Results from Table 8 show that the impact has indeed been exampled. Nonetheless, all 6 cultural dimensions failed to show viable results. Out of the 6, only three showed results of any significance which are Power Distance, Individualism, and Indulgence. Therefore from this research paper at the very least it can be concluded that although some dimensions of Hofstede’s cultural model show significant influence in the behaviour on HDI, not all dimensions relate to it.

According to the literature reviewed in section 2 of this paper, it is also established that the research gap identified stating that no study has attempted to study the impact Hofstede’s cultural dimensions has on HDI in just European nations have been done. Based on the data available between the two models regarding European nations and Table 8 above showing results of the impact of the entire model, it can now be properly established that this gap has been filled in research and can be used to further along different branches of this paper.

Finally, as it can be seen in Table 8, the 6 hypotheses that were created based on previous empirical studies all showed their results. 3 out of the 6 hypotheses have been accepted and deemed true and are now in line with the other empirical researches done in this paper.

5.0 | Conclusion & Discussion

5.1 | Conclusion

The central point of the research was to determine whether Hofstede’s 6 cultural dimensions had an impact on the Human Development Index. 5 years of HDI data was used as the dependent variable for a longitudinal analysis and Hofstede’s cultural model was determined to be the best pick for this project. After the testing of hypothesis it was concluded that power distance has a negative impact on HDI, individualism and indulgence both have positive impacts on HDI. Masculinity, Uncertainty Avoidance, and Long Term Orientation proved no significant impact on HDI thus their hypotheses were rejected. This conclusion agrees with previous studies done by (Lopes & Serrasqueiro, 2017) and (Konrad, 2012).

Since power distance is defined as the distance of power between two employees on different levels indicating that the higher the distance, the less approachable the higher staff is (Kang & Mastin, 2008); the variable having a negative significant impact states that low power distance (more approachable bosses) is more promising towards human development. Secondly Individualism is defined as the higher the country is on the scale the more the people in the country will be individualistic and look out for their own well-being first; the opposite end of the spectrum shows that people are more collectivistic and work better as a team (Shi & Wang, 2011); people caring more of their well-being rather than others collectively has a higher significant impact on HDI in Europe. Finally, indulgence is defined as a really important dimension which illustrates whether or not a country fixates on happiness or not (Bergiel, et al., 2012); people putting more effort into their personal lives and self-growth have a positive impact on overall human development in Europe.

5.2 | Recommendation

It is recommended that this research be used as one of the few researches done online regarding Hofstede’s cultural dimensions’ impact on HDI. This is because during the research phase not many empirical researches were found. This means that there is a minor shortage of researches similar to this one. Therefore this research paper can be implemented in the pool of those research papers to increase it further. Secondly, it is recommended that this research be used for academic and business purposes as it serves a purpose for both. Finally, this research was not able to find an impact for the remainder of the three cultural dimensions: Masculinity, Uncertainty Avoidance, and Long Term Orientation. Therefore, other cultural models can be used for future research in order to fill the gaps this model could not. Other human development tools can also be used to further expand this genre of research.

5.3 | Implication

Various implications can be drawn from this conclusion for two groups of people. The first group of people is the managers and leaders of organizations, and the second group is academics looking to expand their knowledge. For managers and leaders of an organization, this knowledge of testing the impact of one cultural tool on another socio economic cultural development index really shows some development patterns. For instance in Europe mostly all countries support low power distance and are in favor of individualistic and indulging behaviors. Therefore, if a company is looking to expand in Europe then they need to consider various factors such as people in Europe prefer low power distance and if the company has higher power distance they need to change the structure of their organization for that European branch. They also need to consider that individualism is more present in Europe so projects should be tailored more towards individualistic work rather than collectivistic group work. Finally, the company needs to know that indulgence is a big characteristic of human development in Europe and in order to get a happy workforce they need to make sure their employee’s work life does not completely overshadow their private lives and leisure activities.

Similarly, these results can also be great for continuing further research in Europe. Since the entire continent in this research paper, academics now know the impact of three of the six cultural dimensions Hofstede’s model has on HDI. This can be used to further their knowledge. These factors and how they work can also be taken into consideration if an experiment or hypothesis is being done in Europe around human beings. These factors can tailor the experiment to make sure the best results are taken due to European people being at a more comforted level if these factors are applied.

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APPENDIX A

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Figure 9: Illustration of Hofstede's Cultural Dimensions validated through Hofstede (2018)

APPENDIX B

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Table 9: List of European Nations

APPENDIX C

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APPENDIX D

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Table 10: Secondary Data Collection

These scores were retrieved from Hofstede’s Data Matrix (Hofstede, 2015), Hofstede’s country compare (Hofstede, 2018), and the official UNDP HDI data (UNDP, 2018). These are filtered to European countries with ALL of the scores available from both HDI and Hofstede. Some Hofstede countries had some incomplete dimension scores so they have been omitted from the final data sampling. The final resulted in 33 European nations.

72 of 72 pages

Details

Title
Impact of Hofstede’s Cultural Dimensions on the Human Development Index of European Countries
Subtitle
Longitudinal Time Series Analysis. Secondary Research
College
Anglia Ruskin University
Course
Bachelors (Hons) in International Management
Grade
75%
Author
Year
2018
Pages
72
Catalog Number
V427097
ISBN (Book)
9783668720701
File size
1384 KB
Language
English
Tags
hofstede, HDI, human development index, europe, european, countries, nations, national culture
Quote paper
Maisum Raza (Author), 2018, Impact of Hofstede’s Cultural Dimensions on the Human Development Index of European Countries, Munich, GRIN Verlag, https://www.grin.com/document/427097

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