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Article

The Impact of Digitalization on Happiness: A European Perspective

by
Liliana Ionescu-Feleagă
1,*,
Bogdan-Ștefan Ionescu
2 and
Oana Cristina Stoica
3
1
Accounting Department, The Bucharest University of Economic Studies, 010374 Bucharest, Romania
2
Management Informatics System Department, The Bucharest University of Economic Studies, 010374 Bucharest, Romania
3
Accounting Doctoral School, The Bucharest University of Economic Studies, 010374 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Mathematics 2022, 10(15), 2766; https://doi.org/10.3390/math10152766
Submission received: 20 July 2022 / Revised: 28 July 2022 / Accepted: 1 August 2022 / Published: 4 August 2022
(This article belongs to the Special Issue Mathematical Modeling in Economics, Ecology, and the Environment)
Versions Notes

Abstract

:
One of the most important goals of humanity has always been happiness. In our daily life, happiness is conditioned by different variables, such as relationships with certain groups of individuals, health, security values, expectations, etc. Over the years, technology, especially digitalization, has revolutionized the world and changed our lives. In this context, empirical research on digitalization has grown enormously during the last decade; however, studies on the relationship between digitalization and happiness remain limited. As such, the objective of the present paper is to present an empirical investigation on the relationship between digitalization and happiness in the European Union (EU) during the period 2019–2021, before and during the COVID-19 pandemic. In this context, the link between the Digital Economy and Society Index (DESI) and World Happiness Index (WHI) globally for all EU countries, at the level of each WHI variable and at the level of geographical groups in the EU was analyzed using correlations. While the DESI indicator acts as a basis for policymakers, governments, regional administrators and public officials to invest in areas of priority with an evidence-based approach, the WHI indicator can be an important tool for guiding public policy and measuring its effectiveness. The results show that there was a positive and significant relationship between the two indicators at the level of EU countries in all three years. The results also show that in the Western and Northern regions of the EU, the relationship between the two indicators was stronger compared to the other regions. Thus, our study offers supporting arguments for the digital transformation of happiness and provides alternate methodologies and perspectives on the interactions between digitalization and happiness. Moreover, it can help policymakers direct their attention to the importance of digitalization for people’s happiness.

1. Introduction

Happiness has been and remains one of the most important objectives of humanity. It is described as a general state of well-being, satisfaction and accomplishment, generated by positive aspects of social, spiritual, economic, psychological and physiological life [1].
In other words, happiness is conditioned by variables such as relationships with family and friends, professional activity, personality traits, the use of free time, the macroeconomic environment, income, parental conditions, home, security, health, values, expectations, etc. Although the meaning of happiness in everyday life seems very evident [2] its definition represents a huge challenge for researchers. Previous studies were heterogeneous in terms of formulating the question used to define happiness [3,4]. Authors have used happiness as a synonym for life satisfaction or well-being [5,6] or they investigated happiness sources and vaguely described them as definitions of happiness [7]. In addition, cultural differences lead to differences in the understanding of happiness, its predictors and its relationship with social change [8]. Such a heterogeneous use of a single term leads to conceptual ambiguity, which can affect the credibility of the field of happiness research.
Many studies have focused on measuring happiness. According to [2], collecting data about people’s perceptions of measuring happiness may not be a reliable way to identify what leads to happiness. For this reason, surveys have been most frequently used to ask people to answer closed questions about happiness or to indicate their happiness on a verbal or numerical scale. Happiness can be measured at two levels, the individual one and the collective one, and this distinction has consequences on how the measured responses are treated in the subsequent analysis. Thus, while in the individual analysis, the researcher links the answers about happiness to the study of each respondent separately, measuring happiness at a collective level involves measuring the statistical distribution of individual responses of a community’s members and characterizing this distribution using one or more indices.
The idea of measuring happiness to show the success of a collective should not be exclusively associated with Bhutan. It has also been the basis for other initiatives, such as: the Good Country Index, which measures how much each country contributes, through policies and behavior, to the common good of the planet; the Human Development Index (HDI), which takes into account, in addition to per capita income, factors such as life expectancy and education; and the World Happiness Index (WHI), which uses data from global surveys to identify how people rate their own lives in different countries around the world.
In the last decade, technological advancement has influenced all areas of activity, contributing to an increase in individuals’ well-being, to education development, and to strengthening the feeling of freedom. The COVID-19 pandemic induced the rapid implementation of some radical changes that led to the large-scale growth of digital transformation. Efforts have been made to adopt emerging digital technologies, such as mobile and visual connectivity, cloud computing, blockchain, smartphones, Internet of Things (IoT), robotics, artificial intelligence (AI), etc. [9]. Digitalization created new opportunities for spending free time during the period of successive shutdowns imposed by the pandemic and made social distancing easier. Without digitalization, “telemedicine”, “home office”, mobile health applications, virtual trainers and support from online communities would not exist. Obviously, digitalization also has negative effects, such as dependence on social media, the loss of confidentiality, and exposure to cybernetic crimes, but they can be attenuated through appropriate regulations, education for the healthy use of technological innovations and technological improvements.
Although the benefits of implementing digital solutions are obvious, they need to be properly measured. Over time, several indices were developed to measure progress in a so-called field of application, such as internet access or broadband adoption. However, it is considered that the transition to a digital society should not be associated only with the adoption of technology. It is necessary to identify factors with a high impact on the competitiveness of local economies in the global context. To address this need, complex indices, such as the Digital Density Index (DDI), which measures how digital technologies influence economic growth, and the Digital Economy and Society Index (DESI), which summarizes indicators related to digital performance and competitiveness of the EU member states, have been created [10]. Unlike other indices that are more general in nature, DESI shows the specific values of each country regarding the impact of ICT on its economic development and how much the government invests in the digitization of the economic activities of market players. In other words, it plays a central role in analyzing how digital recommendations, specific reforms and investments are implemented in each country, with the level reached being a benchmark for future actions and access to some financial facilities.
The objective of the present study was to analyze the relationship between digitalization and the level of happiness in as many countries as possible during the period 2019–2021. Because DESI values are only available for EU member countries, we analyzed the link between DESI and WHI globally for all of these countries. Although empirical research on digitalization has grown enormously during the last decade, studies on the relationship between digitalization and happiness remain limited. To the best of our knowledge, there have been no other studies that made a link between DESI and WHI at the EU level. Given that there is considerable variability across EU countries, it is necessary to group them by region. There are several different methods of grouping them, for example, based on welfare state regimes, cultural, historical, geographical contexts, etc. Usually, the number of groups identified ranges from three to five. Considering previous classifications, we grouped countries included in the analysis into three categories. These categories comprise Central and Eastern Europe, Western and Northern Europe and Southern Europe, given that other studies found different digitalization levels in countries belonging to these regions [11,12].
The findings show that there was a significant and positive relationship between the DESI index and WHI at the level of EU countries in all three years and between the DESI index and the majority of the WHI components. The results also show that in the Western and Northern region of the EU, the relationship between the two indicators was stronger compared to the other regions. These findings are in line with institutional theory [13]. The digital performance of a country is linked to a large and complex sociotechnical system, in which multiple logics are present. As a result, by investigating the evolution of digital performance in different countries, we obtained an alternative explanation for the mechanisms behind changes in peoples’ happiness, as well as the diffusion of institutional logic through a field.
This paper is structured as follows. The first section is dedicated to the relevant literature review. In the next section, the research methodology is presented, followed by the results analysis. The last section presents the main conclusions of the paper, implications and future research paths.

2. Literature Review

2.1. The Light Side and the Dark Side of Digitization from the Perspective of Human Quality of Life

The quality of life is determined by the ability of individuals to build social capital, to achieve their professional goals, to receive a quality education and to develop interpersonal relationships and connections [14]. In this paradigm, digitalization is perceived as a key factor of human development that acts simultaneously on the objective elements of quality of life in all its spheres and on how it is perceived. It is revolutionizing business, consumer, civic and personal logistics, opening a wide range of opportunities and options. Thus, digitalization has been shown to contribute to economic growth and to the well-being of individuals and local and global communities, to save time and increase productivity, to facilitate trade and access to finance, and to improve transparency and governance [15]. The implementation of digital technologies contributes to the development of social capital through the access it provides to a large amount of information related to education, health, medical services and entertainment and creates unlimited opportunities to improve scientific progress through quick access to scientific publications, scientific data and resources [16].
In addition, digitalization connects people to people and transforms the way people interact with the world around them, increasing the availability of communications through access to social networks and responding to people’s innate desire for acceptance and belonging [17]. Digitalization increases the inner world of each person, with new digital technologies offering opportunities for self-development and the manifestation of creativity and influencing the self-esteem of individuals, their social integration in communities, and the way they perceive reality and interact with that reality [18]. In other words, access to digital technologies allows people to remove certain barriers and improve or reinvent their lives through self-actualization, goal achievement, networking and communication with others.
However, digitalization also has negative economic, social and psychological effects on the individual and on society in general. These effects are especially related to cybersecurity risks and data, financial resources and personal life insecurity [19]. There are also sustainability issues, driven by the automation of service provision and data processing [20], but also the increase in unemployment and wage inequality generated by structural changes in the economy [21].
Digital technologies create conditions for intrusive connectivity that has detrimental cognitive and emotional consequences for some individuals because it affects their ability to think analytically and their creativity, memory and concentration. Many organizations use dopamine-dosing tools designed specifically to capture the public’s attention and cause addictive effects in people by overloading them with information or sending notifications, fake news, captivating headlines, games or personalized news [22]. In addition, some people do not have access to the Internet or digital skills that allow them to adapt to rapid technological change and the digitization of services, which makes them vulnerable, lowers their self-confidence and increases their feelings of stress, anxiety, depression and insomnia [23,24]. People who, through their structure and behavior, fail to make connections or to feel accepted and integrated face the same feelings, falling into the traps of isolation or social comparison in the context of the explosive development of social networks [17].
The negative effects of digitalization are sometimes enhanced by economic, social and political contexts. Thus, in the context of different levels of economic development, significant gaps appear between countries, social classes and individuals regarding scientific and technological potential, access to information and communication technologies, and the development of digital competence opportunities, which lead to true digital inequality [25,26]. The political regime of each country, the civic culture of the members of the respective community and the degree of spread of democracy also contribute to this inequality [27,28].
However, experts in technology, education and health believe that, globally, digitalization has a rather positive effect on people’s overall physical and mental well-being, even with the most reserved recognizing that digital tools will continue to improve various aspects of life [22]. In order for digitalization to have a major impact on well-being, measures are, however, needed to combat the problems caused by digital technologies. The most important measure in this regard would be digital literacy [29]. This requires people, regardless of age, to be educated about how technological systems work, their impact on well-being, the importance of their proper and healthy use, and the avoidance of possible pitfalls and threats. In addition, companies should design people-centered technologies that serve their interests and improve their experiences and outcomes, and governments should take steps to reduce security and privacy concerns in the context of increased digitalization. Civic and cultural actions can be added to these measures to make individuals aware of the proper use of digital tools [30].

2.2. Happiness and Digital Technologies

Today, digital technologies are part of our daily lives, meaning that they are inevitably closely linked to happiness. Although happiness involves a balance between material prosperity and subjective well-being, researchers pay special attention to the impact that digitalization has on the second component [31]. Explanations for variations in happiness usually involve social relationships, health and work [32].
The results of studies on the relationship between digitization and happiness are far from convergent because they depend on how the two concepts are defined and operationalized. Thus, starting from the premise that digital technologies have a beneficial impact on people’s sociability, their connections with other people and their well-being, ref. [33] analyzed the impact of social networks on happiness and found that, regardless of age, individuals who used social networks were, on average, more satisfied with their lives than those who did not use them. This satisfaction stems from the fact that digital networks offer the opportunity to communicate and share messages, images, videos, etc., with other people. In addition, he noted that satisfaction was higher among people over the age of 65 because social networks seem to contribute to combating loneliness. Similarly, shy, anxious, lonely people who lack direct communication skills use digital technologies to create and develop virtual relationships, which sometimes prove to be at least as intimate as face-to-face ones [34,35,36]. Even young people use digital technologies in their daily work to develop social relationships [37]. Ref. [38] showed that social media has both positive (affirmation and fun) and negative effects (isolation and envy) on American teenagers. Conversely, ref. [39], who studied the use of social networks based on simple clicks on links and the Like button on Facebook, showed that digitalization has only negative effects on subjective well-being. Other studies have highlighted negative effects, especially on adolescents [40,41]. However, some psychological research aimed at linking time spent by adolescents on screen with depression or anxiety has indicated clinically insignificant relationships [42]. In addition, person-centered research has shown that while technology is ubiquitous, screen time does not induce uniform effects on subjective well-being because feelings, motivations and uses vary from individual to individual [43].
At the same time, digital technologies contribute to reducing the effort that employees make to solve work problems, which has beneficial effects on their physical and mental health [44]. In addition, these technologies can increase people’s professional motivation and job satisfaction. Thus, digital technologies help to increase productivity, quality and efficiency in production activities and allow for monitoring and risk reduction [45]. Similarly, they increase performance in marketing activities by enabling efficient product placement and reducing price dispersion [46] and they improve quality of services in hospitals [47]. In education, digital technologies help teachers improve their performance by creating creative and interactive materials for students, support research and administrative activities, and especially change behaviors [48]. Such achievements provide professional satisfaction. Job satisfaction is a positive emotional state that results from the evaluation of one’s work and work experiences and is often associated with happiness [49]. Thus, in higher education institutions, digital technology is implicitly associated with increased happiness, which leads to increased performance in the workplace [50].
Previous studies have highlighted both negative and positive effects that digitalization has on happiness and the fact that the respective results do not have a generalizable impact. In addition, there have been no studies that measure intra- and inter-individual effects over time. As a result, to obtain generalized knowledge, continuous conceptual work is necessary to identify, formalize, develop and assess the research on this topic. Given the above arguments, we stated the following two hypotheses to analyze the relationship between digitization and the level of happiness in European Union countries:
H1: 
There is a positive relationship between DESI and WHI.
H2: 
There is a positive relationship between DESI and the variables of WHI.
According to [11,12] countries from Western and Northern Europe generally reached the highest score of digitalization in 2018, while countries from Central and Eastern and Southern Europe obtained the lowest score of digitalization. As such, a third hypothesis was stated to assess the relationship between digitalization and happiness in the three European regions in 2019, 2020 and 2021:
H3: 
There is a positive relationship between DESI and WHI for each geographical group in the EU.

3. Materials and Methods

The present research performed an analysis of the relationship between digitalization and the level of happiness in European Union countries.
For the digitization component, we decided to use the Digital Economy and Society Index (DESI). The decision to use the DESI indicator was based on the structure and methodology used for its calculation, which shows that the indicators were carefully chosen so that they were appropriate for the phenomenon that they measure. Additionally, the indicators are quantitative and provide objective measures of performance regarding the level of digitization achieved. Moreover, DESI considers the different significance of certain aspects of digitization, removing the shortcoming of most methodologies related to global indices that use an equal weighting system [51]. This index, composed of a set of indicators related to the digital policy mix, was first calculated in 2014 to monitor the digital progress of the EU member states [10]. In 2021, DESI was adjusted to reflect the provisions of the Recovery and Resilience Facility (RRF) and the Digital Decade Compass. The indicators are structured in four dimensions to reflect the four cardinal points of the Digital Compass and the corresponding targets for 2030. Each component has a score calculated in the range of 0–100 with the same degree of coverage. Details on the four major components of DESI are presented in Table 1.
In our research, we decided to analyze the period 2019–2021 to capture the evolution of this index before and during the COVID-19 pandemic. Thus, the DESI 2021 reports are based on 2020 data and present the state of the digital economy and society in the first year of the pandemic. The main characteristics of the analyzed variables are presented in Table 2 and in Appendix A.
Table 2 presents the descriptive statistics of the DESI index and its four dimensions (as variables). The highest value of the DESI indicator was obtained by Finland in 2019 and 2020 and by Denmark in 2021, while the lowest value was obtained by Bulgaria in 2019 and 2020 and by Romania in 2021. The country with the highest human capital index in 2019, 2020 and 2021 was Finland, while the country with the lowest human capital index was Bulgaria in 2019, Italy in 2020 and Bulgaria in 2021. In terms of connectivity, Sweden achieved the largest value of this indicator in 2019 and 2020, whilst in 2021, Denmark was situated at the top of the list. The lowest value of this indicator belonged to Greece in all three years. With respect to the integration of the digital technology index, the highest value was obtained by Ireland in 2019 and 2020 and Finland in 2021, whereas Bulgaria was the country with the lowest value of this indicator in all three years. The last component, the digital public services index, had the highest value in Estonia in the three years analyzed and the lowest value in Romania every year in the analysis.
For the happiness component, we use the World Happiness Index (WHI), given that this is the only index published on an annual basis. WHI indicates the level of happiness and satisfaction among the inhabitants of a certain country. It is published annually by the Sustainable Development Solutions Network and is based on comprehensive data from Gallup World surveys in 149 countries. Surveys specifically monitor performance in six categories, described in Table 3 [52]. To correctly compare each country’s data, the researchers created a fictional country called Dystopia, where the world’s unhappiest people live; Dystopia was considered a benchmark for each of the six categories, and the scores of real-world countries were measured in relation to this value. The six variables were then combined to create a single combined score for each country.
Table 4 shows the descriptive statistics of the World Happiness Index and its components. The highest value of this indicator was obtained by Finland in all three years, while the lowest value of this indicator was obtained by Bulgaria in all three years. The country with the largest value of gross domestic product per capita was Luxembourg in 2019, 2020 and 2021, whereas the country with the smallest value of this indicator was Bulgaria in all three years. The social support index was the highest in Finland in 2019 and Denmark in 2020 and 2021, whilst the lowest was obtained by Greece in 2019 and Cyprus in 2020 and 2021. The third component, healthy life expectancy, had the largest value in Spain in 2019, 2020 and 2021 and the smallest one in Latvia in 2019 and Bulgaria in 2020 and 2021. With respect to the freedom to make your own life choices indicator, the highest value was obtained by Finland in 2019, Denmark in 2020 and Finland in 2021, while Greece had the lowest value in 2019, 2020 and 2021. The generosity of the general population index had the largest value in Malta in 2019 and 2020 and in the Netherlands in 2021 and the lowest value in Greece in 2019, 2020 and 2021. The last component of the World Happiness Index, the perceptions of internal and external corruption levels, was the highest in Denmark in 2019, Bulgaria in 2020 and Croatia in 2021. Bulgaria was situated at the bottom of the list in 2019, and Denmark was at the bottom in 2020 and 2021.
The three hypotheses were tested using Pearson correlation analysis in SPSS software for each of the three years. This analysis helps in understanding the evolution of the relationship between the DESI index and the World Happiness Index between 2019 and 2021 (before the COVID-19 pandemic and during the COVID-19 pandemic) in EU countries.

4. Results

The correlation analysis between the DESI index and World Happiness Index in the EU for the period 2019–2021 is presented in Table 5.
The results show that, in 2019, there was a positive and significant relationship between the DESI index and the World Happiness Index, thus providing support for our first hypothesis. Similar results were obtained when correlating the DESI index with each component of the World Happiness Index, except for healthy life expectancy, where the correlation was positive but not significant. Therefore, the second hypothesis is partially supported. In 2020, the results show that there was a higher positive and significant correlation between the DESI index and World Happiness Index compared to 2019. Except for the perceptions of internal and external corruption component, which was negatively and significantly correlated with the DESI index, and the healthy life expectancy component, which was positively but not significantly correlated with the DESI index, all other components of the World Happiness Index were positively and significantly correlated with the DESI index. The results for 2020 provide support for the first hypothesis, but they only partially support the second hypothesis. A lower correlation, though positive and significant, between the DESI index and World Happiness Index was obtained in 2021 compared to the previous years. Additionally, in 2020, the perceptions of internal and external corruption indicator were negatively and significantly correlated with the DESI index, and all other components had a positive and significant correlation with the DESI index. For 2021, again, the first hypothesis is supported, but the second hypothesis is only partially supported.
The third hypothesis of the present study refers to the relationship between the DESI index and the World Happiness Index at the level of geographical groups in the EU. To identify whether there were differences between EU regions at the level of each indicator, we first performed a one-way ANOVA analysis in SPSS and then a correlation analysis for each group of countries.
Table 6 shows that there were significant differences between the three groups of countries with respect to the DESI index and the World Happiness Index in every year of the analysis. Additionally, significant differences were observed at the level of DESI and World Happiness Index components, except for DESI connectivity, DESI digital public components, the generosity of the general population in 2019, DESI connectivity and DESI generosity of the general population in 2020 and DESI connectivity, healthy life expectancy and the generosity of the general population in 2021.
Table 7 presents the correlation analyses between the DESI index and World Happiness Index for each EU region in the period 2019–2021. The first analysis refers to the Central and Eastern EU region. As can be seen, in 2019, the only positive and significant relationships were represented by the DESI index and social support component of the World Happiness Index and the DESI index and the perception of corruption component. In 2020, significant relationships existed between the DESI index and gross domestic product per capita component of the World Happiness Index, between the DESI index and the generosity of the general population component, and between the DESI index and the perception of corruption component, but the last relationship was a negative one. In 2021, there were only two significant relationships, as follows: between the DESI index and the generosity of the general population component and between the DESI index and the perception of corruption component, which again was a negative relationship.
The second analysis refers to the Western and Northern EU region. As can be seen, in 2019, there was no significant relationship between the DESI index and World Happiness Index, but there was a significant and positive relationship between the DESI index and the freedom to make your own life choices component of the World Happiness Index and a significant and negative relationship between the DESI index and the perception of corruption component. In 2020 and 2021, the situation looks different for this region. There was a positive and strongly significant relationship between the DESI index and the World Happiness Index but also a positive and significant relationship between the DESI index and the freedom to make your own life choices component of the World Happiness Index. Moreover, the results show that a negative and significant relationship existed between the DESI index and the perception of corruption.
The third analysis refers to the Southern EU countries. As reported in the table, in 2019 and 2020, there was a significant and positive relationship between the DESI index and World Happiness Index, but there was no significant relationship between the two indicators in 2021. In 2019, significant and positive relationships existed between the DESI index and the following indicators: gross domestic product per capita, generosity of the general population and the perception of corruption. Similar relationships existed in 2020, except for the relationship between the DESI index and the perception of corruption indicator, which was negative. In 2021, the only positive and significant relationship existed between the DESI indicator and gross domestic product per capita, and a negative and significant relationship existed between the DESI indicator and the perception of corruption indicator.
In summary, the Western and Northern EU region had the strongest relationship between the DESI index and World Happiness Index, but only in 2020 and 2021, followed by the Southern region, where the relationship was not that strong, and it existed only in 2019 and 2020. In Central and Eastern EU countries, the DESI and World Happiness indicators were not significantly correlated.

5. Conclusions

Digital technologies can have a significant impact on people’s happiness. Digitalization connects people and changes the way that they interact with each other [17]. As previous studies found, people, especially older individuals, are more satisfied with their lives when using digital networks due to the opportunity for communication and sharing messages, images, videos, etc., with other people [33]. Studies have identified both negative and positive effects of digitalization on happiness and the fact that the obtained results do not have a generalizable impact. Although empirical research on digitalization has grown enormously during the last decade, studies on the relationship between digitalization and happiness remain limited. As such, the objective of the present study was to analyze the relationship between digitalization and the level of happiness in European Union countries during the period 2019–2021. In this context, the link between DESI and WHI globally for all EU countries, at the level of each WHI variable and at the level of geographical groups in the EU was analyzed using correlations.
The results show that there was a significant and positive relationship between the DESI index and WHI at the level of EU countries in each year of the analysis and between the DESI index and WHI components, except for healthy life expectancy in 2019, the perceptions of internal and external corruption component, which is negatively and significantly correlated with the DESI index, the healthy life expectancy component, which was positively but not significantly correlated with the DESI index in 2020, and the perceptions of internal and external corruption indicator, which was negatively and significantly correlated with DESI in 2021. The results also show that in the Western and Northern region of the EU, the relationship between the two indicators was stronger compared to the other EU regions. The findings of the present paper are generally in line with the findings of some previous studies that showed a positive relationship between digital technologies and people’s satisfaction and well-being [33,45], but it must be specified that no other study has made a link between DESI and WHI at the EU level. Overall, the relationship between DESI and WHI appears to have been stronger in 2020 compared to 2019 but weaker in 2021 compared to 2020 and 2019. These results show that, in the year that the COVID-19 pandemic started and social and professional lives moved online to a larger extent than ever before, people started to feel happier with technology, but as time passed, they realized that technology is not beneficial for their well-being.
Our research offers an optimistic outlook for the impact of digitalization on happiness in the EU. The results could be of interest to researchers, as they provide a starting point in studying people’s happiness in relation to digitalization. The results could also be of interest to people in general, as they show the evolution of the relationship between digitalization and happiness one year before and during the COVID-19 pandemic. In these periods, countries made efforts related to digitalization and allocated increasing budgets for this activity. The effect of digitalization on countries’ happiness will become more pronounced if people and policymakers learn to harmonize these two aspects. Therefore, our study is a signal that everyone must understand digitalization and act so that this factor has a discernible impact on the happiness of nations.
However, this study has several limitations, mainly determined by the analyzed period, which covers only three years, and by the variables for DESI and WHI, which were only set at the level of their dimensions. Despite these limitations, we consider that this work is a challenge for future research regarding the link between digitalization and happiness. Thus, it would be interesting to see how the DESI vs. WHI clusters change in the post-pandemic period and to what extent the change at the level of sub-dimensions and indicators is in line with the change at the global level of the two indices. Future studies could also analyze this relationship at a global level and compare the results with those at the EU level, identifying the factors that drive the positive or negative relationships between the two indicators.

Author Contributions

Conceptualization, L.I.-F. and B.-Ș.I.; methodology, B.-Ș.I.; formal analysis, O.C.S. and L.I.-F.; data curation, O.C.S. and B.-Ș.I.; writing, B.-Ș.I., L.I.-F. and O.C.S.; supervision, B.-Ș.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data in the manuscript are from the Digital Economy and Society Index (DESI) and the World Happiness Index database.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Database

Ref. NoYearCountryRegionDESIDESI
HC		DESI
Con		DESI
IDT		DESI
DPS		WHIWHI
GDP		WHI
SS		WHI
HLE		WHI
FMLC		WHI
G		WHI
PC
12021AustriaCentral and Eastern56.953.35341.379.87.2710.910.9373.300.910.040.48
22021BelgiumWestern and Northern53.750.848.449.865.86.8310.820.9172.200.78(0.15)0.65
32021BulgariaSouthern36.832.738.120.5565.2710.020.9367.000.79(0.10)0.93
42021CroatiaSouthern4646.745.440525.8810.220.9270.800.75(0.12)0.94
52021CyprusSouthern43.539.741.830.561.86.2210.580.8073.900.76(0.01)0.84
62021Czech RepublicCentral and Eastern47.447.244.639.158.66.9710.560.9570.810.86(0.21)0.87
72021DenmarkWestern and Northern70.161.27457.987.17.6210.930.9572.700.950.030.18
82021EstoniaCentral and Eastern59.457.946.641.591.86.1910.480.9468.800.91(0.11)0.53
92021FinlandWestern and Northern67.171.151.359.586.77.8410.780.9572.000.95(0.10)0.19
102021FranceWestern and Northern50.647.447.434.8736.6910.700.9474.000.82(0.15)0.57
112021GermanyCentral and Eastern54.155.25835.567.57.1610.870.9072.500.880.010.46
122021GreeceSouthern37.34137.728.541.95.7210.280.8272.600.58(0.29)0.82
132021HungaryCentral and Eastern41.240.55223.349.25.9910.360.9468.000.75(0.19)0.88
142021IrelandWestern and Northern60.354.156.44882.67.0911.340.9572.400.880.080.36
152021ItalySouthern45.535.142.441.463.26.4810.620.8873.800.69(0.08)0.87
162021LatviaCentral and Eastern59.541.150.426.879.66.0310.310.9367.100.71(0.16)0.80
172021LithuaniaCentral and Eastern51.846.141.741.2786.2610.500.9467.910.77(0.20)0.83
182021LuxemburgWestern and Northern5956.26139.479.47.3211.650.9172.600.91(0.03)0.39
192021MaltaSouthern59.649.154.150.884.26.6010.670.9372.200.930.130.65
202021NetherlandsWestern and Northern65.161.568.450.779.97.4610.930.9472.400.910.180.34
212021PolandCentral and Eastern4137.745.325.955.16.1710.380.9069.700.84(0.16)0.74
222021PortugalSouthern49.845.648.536.668.55.9310.420.8872.600.89(0.24)0.89
232021RomaniaSouthern32.933.153.223.821.56.1410.280.8367.360.85(0.22)0.94
242021SlovakiaCentral and Eastern43.243.846.329.153.76.3310.370.9469.200.77(0.12)0.91
252021SloveniaCentral and Eastern52.847.853.242.3686.4610.530.9571.400.95(0.10)0.81
262021SpainSouthern57.448.36238.880.76.4910.570.9374.700.76(0.08)0.75
272021SwedenWestern and Northern66.164.659.656.3837.3610.870.9372.700.940.090.24
12020AustriaCentral and Eastern54.356.747.240.680.87.2910.740.9373.000.900.090.50
22020BelgiumWestern and Northern58.750.45265.971.76.8610.670.9172.000.81(0.08)0.61
32020BulgariaSouthern36.433.938.517.961.85.109.870.9466.800.75(0.14)0.94
42020CroatiaSouthern47.649.241.241.555.85.5110.070.8770.210.71(0.13)0.92
52020CyprusSouthern4435.838.534.5696.1610.410.8173.700.780.040.86
62020Czech RepublicCentral and Eastern50.848.644.949.662.46.9110.400.9170.050.82(0.23)0.86
72020DenmarkWestern and Northern69.161.345.865.187.17.7510.770.9672.400.950.070.17
82020EstoniaCentral and Eastern61.166.751.941.189.36.0210.340.9368.600.88(0.11)0.62
92020FinlandWestern and Northern72.378.459.267877.8110.640.9571.900.95(0.06)0.20
102020FranceWestern and Northern52.247.449.84276.76.6610.580.9473.800.83(0.13)0.58
112020GermanyCentral and Eastern56.156.459.439.566.47.0810.730.9072.200.870.080.46
122020GreeceSouthern37.334.833.428.251.55.5210.130.8172.410.54(0.30)0.86
132020HungaryCentral and Eastern47.541.859.825.357.86.0010.250.9267.610.72(0.19)0.89
142020IrelandWestern and Northern61.856.445.774.380.67.1311.160.9472.300.890.150.36
152020ItalySouthern43.632.55031.267.56.3910.480.8973.600.66(0.04)0.87
162020LatviaCentral and Eastern50.73561.828.385.15.9510.180.9266.810.67(0.19)0.80
172020LithuaniaCentral and Eastern53.943.848.949.581.46.2210.340.9367.290.75(0.22)0.81
182020LuxemburgWestern and Northern57.958.263.338.273.77.2411.450.9172.600.91(0.00)0.37
192020MaltaSouthern62.761.858.754.978.16.7710.530.9372.200.920.210.66
202020NetherlandsWestern and Northern67.764.260.365.7817.4510.810.9472.300.910.210.36
212020PolandCentral and Eastern4537.351.326.167.46.1910.270.8769.310.86(0.21)0.69
222020PortugalSouthern49.637.853.940.975.15.9110.260.8972.400.89(0.22)0.89
232020RomaniaSouthern4033.256.224.948.46.1210.110.8367.210.84(0.20)0.93
242020SlovakiaCentral and Eastern45.241.847.532.655.66.2810.350.9268.910.75(0.12)0.92
252020SloveniaCentral and Eastern51.248.350.240.970.86.3610.390.9471.100.94(0.08)0.82
262020SpainSouthern57.547.660.841.287.36.4010.460.9274.400.75(0.05)0.77
272020SwedenWestern and Northern69.771.764.462.179.37.3510.760.9372.600.940.110.25
12019AustriaCentral and Eastern51.155.743.534.876.37.251.381.481.020.530.240.23
22019BelgiumWestern and Northern5349.639.961.465.86.921.361.500.990.470.160.21
32019BulgariaSouthern33.828.537.216.956.55.011.091.510.810.310.080.00
42019CroatiaSouthern44.346.837.238.550.85.431.151.270.910.300.120.02
52019CyprusSouthern41.534.634.633.565.76.051.261.221.040.410.190.04
62019Czech RepublicCentral and Eastern47.344.843.542.759.96.851.271.490.920.460.050.04
72019DenmarkWestern and Northern6661.159.261.282.77.601.381.571.000.590.250.41
82019EstoniaCentral and Eastern58.362.449.939.8855.891.241.530.870.500.100.16
92019FinlandWestern and Northern68.177.554.560.1827.771.341.590.990.600.150.39
102019FranceWestern and Northern49.8474840.869.36.591.321.471.050.440.110.18
112019GermanyCentral and Eastern51.254.447.739.258.86.991.371.450.990.500.260.26
122019GreeceSouthern35.132.729.530.246.45.291.181.161.000.07-0.03
132019HungaryCentral and Eastern42.342.145.924.950.75.761.201.410.830.200.080.02
142019IrelandWestern and Northern5854.242.569.178.17.021.501.551.000.520.300.31
152019ItalySouthern41.63248.23061.96.221.291.491.040.230.160.03
162019LatviaCentral and Eastern49.940.459.824.780.25.941.191.460.810.260.070.06
172019LithuaniaCentral and Eastern51.842.24647.679.46.151.241.520.820.290.040.04
182019LuxemburgWestern and Northern54.557.457.137.464.97.091.611.481.010.530.190.32
192019MaltaSouthern55.35543.949.675.26.731.301.521.000.560.380.15
202019NetherlandsWestern and Northern63.66250.562.679.67.491.401.521.000.560.320.30
212019PolandCentral and Eastern40.736.843.823.561.56.181.211.440.880.480.120.05
222019PortugalSouthern4735.248.441.473.45.691.221.431.000.510.050.02
232019RomaniaSouthern36.531.15021.3456.071.161.230.820.460.080.00
242019SlovakiaCentral and Eastern42.944.239.633.150.76.201.251.500.880.330.120.01
252019SloveniaCentral and Eastern48.746.348.639.164.56.121.261.520.950.560.140.06
262019SpainSouthern53.644.555.441.380.96.351.291.481.060.360.150.08
272019SwedenWestern and Northern67.571.660.157.977.97.351.391.491.010.570.270.37

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Table
Table 1. DESI description.
Table 1. DESI description.
DimensionsDescription of DimensionsDegree of Coverage
Human capital (HC)Assesses the Internet use skills of citizens and the advanced skills of specialists25%
Connectivity (con)Analyzes fixed broadband and mobile broadband with indicators that measure supply, demand and retail prices25%
Integration of digital technology (IDT)Includes digital intensity and the adoption of selected technologies by businesses and e-commerce25%
Digital public services (DPS)Describes the demand for and supply of e-government, as well as open data policies25%
Source: Authors, based on DESI Index data [10].
Table
Table 2. Descriptive statistics of the DESI variables for the period 2019–2021.
Table 2. Descriptive statistics of the DESI variables for the period 2019–2021.
VariableMinMaxMeanSt. Dev.
Year2019
DESI33.8068.1050.139.49
HC28.5077.5047.7812.52
con29.5060.1046.837.78
IDT16.9069.1040.8413.97
DPS45.0085.0067.5212.26
Year2020
DESI36.4072.3053.489.84
HC32.5078.4049.3012.73
con33.4064.4051.658.26
IDT17.9074.3043.3015.25
DPS48.4089.3072.1711.76
Year2021
DESI32.9070.1051.159.96
HC32.7071.1048.479.67
con37.7074.0051.148.75
IDT20.5059.5039.0110.82
DPS21.5091.8064.4716.33
Source: Authors, based on DESI Index data [10].
Table
Table 3. World Happiness Index (WHI) description.
Table 3. World Happiness Index (WHI) description.
DimensionsDescription of Dimensions
Gross domestic product per capita (GDPC)Represents the total value of goods and services produced in a country over a period of time, divided by the population of that country.
Social support (SS)Represents the national average of binary answers to the question, “Do you have relatives or friends you can rely on to help you in case you have problems?”
Healthy life expectancy (HLE)Refers to the average number of years an individual is expected to live in at least good health, taking into account current mortality rates and the prevalence of good or very good health.
Freedom to make your own life choices (FMLC)Represents the national average of binary answers to the question, “Are you satisfied or dissatisfied with your freedom to choose what to do with your own life?”
Generosity of the general population (GGP)Represents the remnant of the regression of the national average of the answers to the question, “Have you donated money to a charity in the last month?” in GDP per capita.
Perceptions of internal and external corruption levels (PC)Represents the average of binary answers to two questions: “Is corruption prevalent in government structures or not?” and “Is corruption prevalent in business or not?” Where data on government corruption were lacking, the perception of corruption in business was used as a general measure of the perception of corruption.
Source: Authors, based on World Happiness Report [53]. The questions in Table 3 are addressed to respondents in the Gallup World Poll [52].
Table
Table 4. Descriptive statistics of the WHI variables for the period 2019–2021.
Table 4. Descriptive statistics of the WHI variables for the period 2019–2021.
VariableMinMaxMeanSt. Dev.
Year2019
WHI5.017.776.440.73
GDPC1.091.611.290.11
SS1.161.591.460.11
HLE0.811.060.950.08
FMLC0.070.600.430.14
GGP0.000.380.160.09
PC0.000.410.140.14
Year2020
WHI5.107.816.530.70
GDPC9.8711.4510.490.34
SS0.810.960.910.04
HLE66.874.4071.032.37
FMLC0.540.950.820.10
GGP−0.300.21−0.070.14
PC0.170.940.660.25
Year2021
WHI5.277.846.580.64
GDPC10.0211.6510.630.35
SS0.800.950.920.04
HLE67.0074.7071.282.31
FMLC0.580.950.830.09
GGP−0.290.18−0.080.12
PC0.180.940.660.25
Source: Authors, based on World Happiness Data [52].
Table
Table 5. Correlations between DESI index and World Happiness Index.
Table 5. Correlations between DESI index and World Happiness Index.
VarDESIDESI HCDESI conDESI IDTDESI DPSWHIWHI GDPCWHI SSWHI HLEWHI FMLCWHI GWHI PC
Year2019
DESI1
DESI HC0.923 **1
DESI con0.653 **0.513 **1
DESI IDT0.841 **0.733 **0.2651
DESI DPS0.806 **0.606 **0.583 **0.613 **1
WHI0.814 **0.794 **0.518 **0.733 **0.535 **1
WHI GDPC0.660 **0.640 **0.400 *0.639 **0.428 *0.804 **1
WHI SS0.644 **0.551 **0.511 **0.500 **0.647 **0.547 **0.436 *1
WHI HLE0.3800.3270.0730.485 *0.2990.498 **0.612 **0.0571
WHI FMLC0.680 **0.668 **0.459 *0.578 **0.524 **0.726 **0.566 **0.519 **0.3411
WHI GGP0.601 **0.593 **0.2460.577 **0.422 *0.683 **0.658 **0.382 *0.518 **0.625 **1
WHI PC0.866 **0.875 **0.519 **0.748 **0.581 **0.867 **0.802 **0.504 **0.479 *0.673 **0.675 **1
Year2020
DESI1
DESI HC0.917 **1
DESI con0.539 **0.422 *1
DESI IDT0.861 **0.759 **0.2031
DESI DPS0.770 **0.599 **0.401 *0.576 **1
WHI0.825 **0.761 **0.440 *0.758 **0.531 **1
WHI GDP0.672 **0.617 **0.385 *0.629 **0.468 *0.822 **1
WHI SS0.646 **0.594 **0.3580.502 **0.626 **0.477 *0.3601
WHI HLE0.3740.3310.0300.435 *0.3090.511 **0.578 **−0.0241
WHI FMLC0.702 **0.709 **0.423 *0.579 **0.496 **0.703 **0.563 **0.480 *0.2571
WHI GGP0.649 **0.622 **0.3000.590 **0.459 *0.663 **0.669 **0.3480.536 **0.582 **1
WHI PC−0.863 **−0.837 **−0.389 *−0.732 **−0.630 **−0.872 **−0.787 **−0.503 **−0.443 *−0.679 **−0.657 **1
Year2021
DESI1
DESI HC0.881 **1
DESI con0.708 **0.626 **1
DESI IDT0.841 **0.840 **0.544 **1
DESI DPS0.908 **0.734 **0.467 *0.702 **1
WHI0.774 **0.832 **0.699 **0.784 **0.579 **1
WHI GDP0.657 **0.650 **0.619 **0.600 **0.569 **0.812 **1
WHI SS0.583 **0.518 **0.385 *0.443 *0.590 **0.397 *0.2291
WHI HLE0.388 *0.401 *0.3250.515 **0.3610.522 **0.557 **−0.1141
WHI FMLC0.626 **0.672 **0.604 **0.593 **0.529 **0.647 **0.513 **0.481 *0.1611
WHI GGP0.643 **0.546 **0.634 **0.575 **0.581 **0.608 **0.602 **0.3140.416 *0.553 **1
WHI PC−0.841 **−0.891 **−0.694 **−0.750 **−0.704 **−0.865 **−0.762 **−0.410 *−0.426 *−0.649 **−0.655 **1
Source: Authors, based on DESI and WHI indicators [10,52]. Notes. * p < 0.05; ** p < 0.01.
Table
Table 6. Group tests on EU regions (one-way ANOVA).
Table 6. Group tests on EU regions (one-way ANOVA).
IndicatorsCentral and
Eastern
(n = 10)		Southern
(n = 9)		Western and Northern
(n = 8)		One-Way ANOVA
F
MeanSt. Dev.MeanSt. Dev.MeanSt. Dev.
Year2019
DESI49.806.8243.197.7059.567.579.89 **
DESI HC48.308.8437.828.8759.7711.2510.51 **
DESI con47.165.2842.718.5151.618.182.99
DESI IDT37.4611.4733.6310.3455.4111.718.34 *
DESI DPS67.8712.5561.7613.0574.397.562.31
WHI6.440.605.870.567.190.4111.77 **
WHI GDPC1.270.071.220.071.410.1011.68 **
WHI SS1.480.041.370.151.520.056.53 **
WHI HLE0.910.070.970.091.000.024.19 *
WHI FMLC0.420.130.360.150.530.063.89 *
WHI GGP0.140.090.130.110.210.071.35
Year2020
DESI53.056.8046.528.9363.107.439.10 **
DESI HC49.1510.5940.7310.0160.5411.126.96 **
DESI con53.026.1347.9110.1554.317.951.49
DESI IDT39.9312.0335.0210.9959.2313.628.57 **
DESI DPS72.5511.5466.0612.9279.446.022.95 *
WHI6.520.555.990.537.260.4211.99 **
WHI GDPC10.440.2210.260.2310.860.3211.77 **
WHI SS0.920.020.880.050.930.026.91 **
WHI HLE69.742.1671.442.7872.520.633.80 *
WHI FMLC0.820.090.760.120.900.064.11 *
WHI GGP−0.090.15−0.090.150.010.101.24
Year2021
DESI52.048.0545.429.1260.997.217.05 **
DESI HC48.377.6857.918.2741.266.529.80 **
DESI con50.867.5047.028.1656.879.232.86
DESI IDT36.068.6434.549.5549.399.466.13 **
DESI DPS69.2013.7158.8719.2979.667.763.94 *
WHI6.570.546.080.437.250.4112.00 **
WHI GDPC10.560.2310.410.2211.010.3511.05 **
WHI SS0.930.020.880.050.930.027.27 **
WHI HLE70.102.1171.662.7872.660.653.30
WHI FMLC0.840.0710.780.100.890.073.51 *
WHI GGP−0.090.12−0.080.12−0.030.100.92
Source: Authors, based on DESI and WHI indicators [10,52]. Notes. * p < 0.05; ** p < 0.01.
Table
Table 7. Correlations between DESI index and World Happiness Index on EU regions.
Table 7. Correlations between DESI index and World Happiness Index on EU regions.
VarDESIDESI HCDESI conDESI IDTDESI DPSWHIWHI GDPCWHI SSWHI HLEWHI FMLCWHI GWHI PC
RegionCentral and Eastern
Year2019
DESI1
DESI HC0.837 **1
DESI con0.4560.1181
DESI IDT0.795 **0.633 *0.0111
DESI DPS0.770 **0.4740.5880.4091
WHI0.4790.552−0.1610.618 *0.1411
WHI GDPC0.5770.726 *−0.1380.648 *0.1620.931 **1
WHI SS0.632 *0.4810.0580.704 *0.5250.1690.2401
WHI HLE0.3890.630 *−0.2170.4700.0220.855 **0.906 **0.2081
WHI FMLC0.4490.600−0.1080.4640.2380.619 *0.652 *0.4340.843 **1
WHI GGP0.5230.682 *0.0270.4620.1350.780 **0.889 **0.1070.850 **0.633 *1
WHI PC0.748 **0.845 **0.2070.5470.4260.760 **0.875 **0.1840.754 **0.621 *0.895 **1
Year2020
DESI1
DESI HC0.859 **1
DESI con0.3090.0121
DESI IDT0.793 **0.661 *−0.1061
DESI DPS0.651 *0.4210.1680.3571
WHI0.5380.585−0.0520.676 *0.0371
WHI GDP0.657 *0.718 *0.0700.650 *0.1470.943 **1
WHI SS0.5140.465−0.0260.5020.3740.1180.2011
WHI HLE0.4320.618 *−0.1090.478−0.0070.891 **0.900 **0.0851
WHI FMLC0.4770.691 *−0.2360.4650.1820.5860.644 *0.1190.825 **1
WHI GGP0.705 *0.711 *0.3010.5370.2520.801 **0.924 **0.3000.828 **0.616 *1
WHI PC−0.765 **−0.727 *−0.329−0.499−0.473−0.718 *−0.837 **−0.016−0.719 *−0.632 *−0.869 **1
Year2021
DESI1
DESI HC0.767 **1
DESI con0.5660.608 *1
DESI IDT0.701 *0.836 **0.4121
DESI DPS0.895 *0.658 *0.2010.635 *1
WHI0.4730.720 *0.646 *0.676 *0.2161
WHI GDP0.5700.803 **0.696 *0.706 *0.3730.945 **1
WHI SS0.2010.2180.0220.4090.1680.012−0.0551
WHI HLE0.3060.618 *0.5940.5820.0940.904 **0.884 **−0.0831
WHI FMLC0.3990.695 *0.4150.730 *0.3380.615 *0.658 *0.1180.792 **1
WHI GGP0.657 *0.786 **0.879 **0.605 *0.406 *0.796 **0.864 **−0.0420.755 **0.5801
WHI PC−0.720 *−0.845 **−0.709 *−0.598−0.605 *−0.696 *−0.833 **0.210−0.652 *−0.624 *−0.883 **1
RegionWestern and Northern
Year2019
DESI1
DESI HC0.912 **1
DESI con0.6450.6611
DESI IDT0.5080.269−0.2831
DESI DPS0.858 *0.6700.3990.6351
WHI0.9060.837 *0.1990.3900.819 *1
WHI GDPC−0.200−0.1050.198−0.263−0.2730.0161
WHI SS0.5350.393−0.4760.4750.930 **0.561−0.4241
WHI HLE−0.632−0.503−0.106−0.697−0.256−0.577−0.113−0.0571
WHI FMLC0.861 *0.850 *0.3280.2540.766 *0.933 **0.1530.488−0.3741
WHI GGP0.4740.311−0.0510.5030.3210.3800.4400.171−0.3090.5511
WHI PC−0.879 **−0.827 *−0.210−0.350−0.827 *−0.945 **−0.122−0.5740.407−0.991 **0.5851
Year2020
DESI1
DESI HC0.904 **1
DESI con0.2380.5481
DESI IDT0.6160.353−0.3691
DESI DPS0.771 *0.653−0.2120.4821
WHI0.906 **0.837 *0.1990.39000.819 *1
WHI GDPC−0.200−0.1050.198−0.263−0.2730.0161
WHI SS0.5350.393−0.4760.4750.930 **0.561−0.4241
WHI HLE−0.632−0.503−0.106−0.697−0.256−0.577−0.113−0.0571
WHI FMLC0.861 *0.850 *0.3280.2540.766 *0.933 **0.1530.488−0.3741
WHI GGP0.4740.311−0.0510.5030.3210.3800.4400.171−0.3090.5511
WHI PC−0.879 **−0.827 *−0.210−0.350−0.827 *−0.945 **−0.122−0.5740.407−0.991 **−0.5851
Year2021
DESI1
DESI HC0.874 *1
DESI con0.7220.3411
DESI IDT0.840 *0.813 *0.3871
DESI DPS0.883 **0.775 *0.6410.5621
WHI0.919 **0.938 **0.5500.7440.849 *1
WHI GDPC0.012−0.1230.341−0.3270.1690.0671
WHI SS0.5270.4260.2530.4120.7040.436−0.3661
WHI HLE−0.490−0.562−0.124−0.675−0.2490.557−0.2240.1291
WHI FMLC0.915 **0.864 *0.6580.6000.949 **0.905 **0.1620.512−0.2941
WHI GGP0.6300.3540.6770.3760.6680.3740.4100.315−0.1910.6371
WHI PC−0.960 **−0.878 **−0.663−0.704−0.971 **−0.919 **−0.072−0.6210.350−0.980 **−0.6461
RegionSouthern
Year2019
DESI1
DESI HC0.853 **1
DESI con0.5280.1741
DESI IDT0.913 **0.854 **0.2311
DESI DPS0.837 **0.4930.5220.690 *1
WHI0.726 *0.5460.6080.5770.5931
WHI GDPC0.725 *0.4650.4270.686 *0.711 *0.865 **1
WHI SS0.4980.2620.5440.2370.677 *0.3200.3081
WHI HLE0.5800.3300.1390.670 *0.6390.5160.863 **0.1071
WHI FMLC0.5620.4110.5090.4090.5300.5530.2750.370−0.0651
WHI GGP0.685 *0.726 *0.2000.5750.5470.770 *0.6360.4520.3060.5581
WHI PC0.812 **0.827 **0.1880.777 *0.6500.723 *0.691 *0.4040.5070.4090.838 **1
Year2020
DESI1
DESI HC0.875 **1
DESI con0.717 *0.4411
DESI IDT0.929 **0.871 **0.5141
DESI DPS0.786 *0.4910.5780.6171
WHI0.723 *0.4530.747 *0.6440.5811
WHI GDPC0.712 *0.4160.5530.683 *0.703 *0.922 **1
WHI SS0.5030.4870.4440.2870.5880.1040.0941
WHI HLE0.5040.2340.1690.5610.6380.5660.826 **−0.0641
WHI FMLC0.5700.4380.668 *0.4800.4840.4650.2590.330−0.1431
WHI GGP0.690 *0.6560.3800.6230.5850.699 *0.682 *0.3740.3410.4891
WHI PC−0.841 **−0.787 *−0.493−0.773 *−0.680 *−0.732 *−0.752 *−0.373−0.556−0.320−0.749 *1
Year2021
DESI1
DESI HC0.838 **1
DESI con0.6220.5251
DESI IDT0.871 **0.743 *0.4461
DESI DPS0.913 **0.6550.3570.712 *1
WHI0.6530.4070.6520.730 *0.4581
WHI GDPC0.701 *0.4380.4630.733 *0.6160.930 **1
WHI SS0.5690.4050.3710.4430.5650.024−0.0651
WHI HLE0.6410.5730.2030.6150.6270.6210.788 *−0.0971
WHI FMLC0.4070.2550.5360.2840.3150.2470.1920.356−0.2491
WHI GGP0.6110.2990.2640.5730.6570.5230.5350.4230.2130.4201
WHI PC−0.769 *−0.623−0.481−0.663−0.708 *−0.649−0.719 *−0.241−0.574−0.184−0.6111
Source: Authors, based on DESI and WHI indicators [10,52]. Notes. * p < 0.05; ** p < 0.01.
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Ionescu-Feleagă, L.; Ionescu, B.-Ș.; Stoica, O.C. The Impact of Digitalization on Happiness: A European Perspective. Mathematics 2022, 10, 2766. https://doi.org/10.3390/math10152766

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Ionescu-Feleagă L, Ionescu B-Ș, Stoica OC. The Impact of Digitalization on Happiness: A European Perspective. Mathematics. 2022; 10(15):2766. https://doi.org/10.3390/math10152766

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Ionescu-Feleagă, Liliana, Bogdan-Ștefan Ionescu, and Oana Cristina Stoica. 2022. "The Impact of Digitalization on Happiness: A European Perspective" Mathematics 10, no. 15: 2766. https://doi.org/10.3390/math10152766

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