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This paper examines the relationship between digitalization and sustainable
development and presents the composite index used for measuring the digital
competitiveness of nations – the Digital Economy and Society Index (DESI). Today’s
environment is highly dependent on technological capabilities. Tracking
contemporary technological development is b...
Contexts in source publication
Context 1
... level has 12 sub-dimensions, and the third level has 31 individual indicators. Complete structure of DESI with the weighting system is presented in Figure 2. The five principal dimensions are defined by the five principal policies for digital economy and society. ...
Context 2
... weighting system used for the computation of final DESI score, not all the dimensions have the same share: Connectivity and Human Capital are having the largest impact with 25% each, then Integration of Digital Technology with 20%, while Use of Internet and Digital Public Services have the lowest impact of 15%. Within dimensions, the sub-dimensions also have different weighting system shown in Figure 2 (European Commission, 2017). Analysing the structure and methodology used for computation of the DESI, we can conclude that the indicators are carefully examined, selected and appropriate for the phenomenon they measure. ...
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Citations
... Existing literature also found a positive contribution of digitalization in most drivers of sustainable development (Kelly & Kamil-Thomas, 2020;Singh et al., 2024c). For instance, Jovanović et al. (2018) reported that digitalization is crucial to increase the sustainable development of society. Public health is also a significant pillar of sustainable development (Singh & Jyoti, 2023c). ...
... Here, DII and PHI are used as representative variables for digitalization and public health, respectively. Previous studies also used estimated indexes as DVs and IVs in the empirical analysis (Jovanović et al., 2018). Furthermore, the progress of digitalization and public health is also determined by many indicators like exports of goods and services, final consumption expenditure, GDP per capita, employment to population ratio, population density, population growth, scientific and technical journal articles and total vulnerable employment. ...
This study assesses the influence of digitalization on the public health sector across 52 countries. For the above-mentioned investigation, it creates a digital infrastructure index (DII) which is used to observe the progress of these countries in digitalization. Public health index (PHI) is also created for selected countries during 2010 – 2022. Further, estimated values of the PHI are considered to explore the relative progress of these countries in public health. The Karl-Pearson correlation coefficient analysis is adopted to observe the association of digitalization and public health with other macro indicators. It also examines the association of digitalization with public health as including specific control variables in regression analysis. It found a positive causal association among the mentioned indexes. The global countries cannot improve their health sector without adopting digitalization. The empirical results are helpful to improve public health using digitalization, digitalization as improving public health.
... Digital platforms also support entrepreneurship, particularly in emerging markets where formal financial services might not be easily available. Jovanović et al. (2018) noted that the more digitized nations exhibit more viable, and advanced entrepreneurship actions. Consequently, DI would create sustainable entrepreneurship and business ecosystems. ...
... Nevertheless, these equal opportunities of DI can enable high-speed connectivity, and create collective efforts across G20 countries. In the past two decades, the societal structure has been highly dependent and shaped by DI (Jovanović et al., 2018). Rapid digital transformation could be helpful for increasing the change in social, and economic structures (Schwab, 2016). ...
This chapter examines the significance of digital infrastructure (DI) to achieve sustainable development goals (SDGs) in G20 countries during 2010-2022. It develops a set of simultaneous models to assess the causal association of SDGs and its other drivers with DI. SDGI is the inclusion of its three main supportive drivers. It also detects the causal interlinkages of SDGI and its other supportive components with DI. There is also noted a diversity in a group of specific countries in DI and SDGs. Most European Union (EU) countries could achieve better positions in SDGs and DI. Hence, high diversity in SDGs and DI is creating obstacles to achieve SDGs in low-ranking countries. Moreover, SDGs and their other drivers (except environmental sustainability) have positive and significant interlinkages with DI. It also provides numerous policy suggestions to achieve SDGs in G20 countries and scope of further research.
... Di certo, le tecnologie digitali sono responsabili di cambiamenti epocali nella velocità di funzionamento dell'economia globale: Internet e i dispositivi digitali sarebbero, pertanto, da considerarsi autentici motori di crescita economica (Afonasova, Panfilova, Galichkina et al., 121 A conferma di ciò, per converso, militano studi di settore che individuano i principali fattori responsabili dei ritardi dell'Europa nel recepire gli effetti di crescita delle tecnologie digitali nella natura immateriale delle stesse -diversa, cioè, dal carattere tangibile dell'industria manifatturiera tradizionale -che impone una politica correlata ad hoc. I fallimenti del mercato vengono, inoltre, ricondotti alle esternalità derivanti da analfabetizzazione informatica della 2019; Jovanović, Dlačić & Okanović, 2018;Melnyk, Dehtyarova, Kubatko et al., 2019). ...
The "Big Data Governance and Legal Aspects" booklet delves into the governance challenges and legal implications surrounding Big Data in an era marked by the rapid evolution of Emerging and Disruptive Technologies (EDTs). It highlights the essential processes for managing data throughout its lifecycle, emphasizing collection, storage, and analysis while ensuring data security and ethical usage. The text also navigates the balance between privacy and national security, exploring the necessity for ethical and legal frameworks that can address these evolving threats.
The publication investigates the dual potential of Big Data: maximizing value for national security and minimizing privacy risks. It discusses the complexity of reconciling privacy with national security, particularly in the context of CBRNe threats. The book includes a comprehensive examination of Open Source Intelligence (OSINT) methods and the deployment of demonstrators to monitor global asymmetric threats. By analyzing regulatory landscapes and presenting case studies, it offers an integrated approach to understanding Big Data's role in contemporary security and defense, providing a valuable resource for policy makers, researchers, and security professionals.
... An international survey examined whether digitalisation has an impact on the sustainable development of society. The results showed that the social components of the countries studied are positively affected by the process of digitalisation (Jovanović et al., 2018). ...
Nowadays, we live in the fourth industrial revolution (the so-called digital revolution), which is fundamentally reshaping industry and business as well as the economy and civil society. Within the research activities of the National Laboratory for Social Innovation project, a research plan has been drawn up taking into account the quadruple helix model. The aim of this research is to map the social impacts of digitalisation based on the perspective of Hungarian experts. The research aims to map the social impact of digitalisation, its whether the perception of the impact of digitalisation on society depends on the individual perceptions of the experts involved in the research (age, education) or organisational (sector of the organisation represented). The research seeks to answer the following research questions: Q1. How can the social impact of digitalisation be described? Q2. Do individual (age, education) or organisational (sector of the organisation represented) characteristics influence the experts’ opinion? Q3. Are there any significant relationships between experts' responses to questions on the social impact of digitalisation and, if so, how strong are they? The data analysed are the results of a qualitative and quantitative, empirical survey carried out in 2021 with experts from academia, government, business and civil society. The former was conducted in the form of focus group interviews with invited experts (n=9) and the latter, in the form of an online questionnaire survey (n=78) using descriptive statistics and relationship analysis methods (Cramer's V and Kendall's Tau). The results show that the majority of experts consider the social impact of digitalisation to be rather positive, highlighting for example more efficient problem solving. It can be shown that the development of digitalisation requires a well thought-out but not over-regulated framework. As the transfer of knowledge improves, the opportunities for those who use digital technologies increase, but so does awareness of its harmful effects. The results can guide digital policy makers in identifying key areas for intervention.
... Social Sustainability: In the last two to three decades, the current societal structure has been highly dependent on and shaped by digital transformation (Jovanović et al., 2018). Rapid digital transformation, and use of latest technologies and novel innovations bring a profound change in social, and economic structures (Schwab, 2016). ...
... Sustainability in Human Development and Social Welfare: Jovanović et al. (2018) argued that higher levels of digitalization have a significant contribution to increase human development. Sahoo et al. (2021) also suggested that digitalization may be active to increase human resources. ...
This chapter is written to explore the impact of digitalization on SDGs in G20 countries. It creates digital infrastructure index (DII) and sustainable development goal index (SDGI) as considering the digitalization and sustainable development (SD) promoting indicators during 2004-2022. DII and SDGI are created as employing composite Z-score method. The values of DII and SDGI are used to pronounce the comparison of G20 countries in digitalization and SD, respectively. The various forms of empirical models are adopted to assess the causal relationship between digitali-zation and SD. The G20 countries showed a substantial variation in digitalization and overall SDGs. Digitalization and SD showed a positive and one-way causality
... Thus, the results of the studies using a digitalisation index as a dependent or independent variable (see, e.g. Jovanović et al., 2018;Kryzhanovskij et al., 2021) may depend on the index chosen, especially if they are made in a group of similarly developed countries. Comparison of international digitalisation indexes: A quantitative analysis perspective | 39 ...
Objective: The objective of the article is to compare the available digitalisation indexes in the EU (European Union) and Pacific Asia. The first step to tackling the between-country digital gap is to measure digital development. However, the available indexes differ substantially in terms of construction, metric used, and the areas they cover. Research Design & Methods: The first part of the study is a descriptive analysis of the scope and metrics used by three digitalisation indexes: digital economy and society index (DESI), ASEAN digital integration index (ADII) and digital intelligence index (DII). In the second part, we approach the problem from a quantitative perspective, using correlation coefficients and comparing countries’ rankings obtained using different indexes. Lastly, we performed clustering analysis with the use of an agglomerative algorithm with Euclidean distances and the Ward method. The data covers 13 countries from the Pacific Asia and 24 from the EU. Findings: We found that the specifications of indexes differ considerably, not only in the choice of particular metrics but in whole digitalisation areas. Some indexes include overall economic or social development measures that are not strictly related to the digital sphere. Despite that, for countries covered by two indexes, we found high correlations of scores: 0.932 between ADII and DII, and 0.883 between DII and DESI. Comparing rankings and using clustering analysis, we found that the indexes for Pacific Asia are more similar than for the EU, possibly because Asian countries are more heterogeneous both in digital and economic development. Implications & Recommendations: Any study of the digital divide and its causes is affected by the choice of digitalisation measure. We found that DII and ADII indexes include some socio-economic metrics that may interfere with the results in the studies of the links between economic and digital development. Although the indexes’ scores are quite highly correlated, in some cases, they can judge a country’s development very differently. This is a problem, especially in the EU, where countries are more similar in digital development than in Pacific Asia. Contribution & Value Added: The study compares digitalisation indexes from a quantitative perspective that has not yet been established in the literature. It shows how different indexes perform in ranking and clustering procedures. Researchers can use our article as a guide in choosing digitalisation indexes for the EU and ASEAN countries.
... The continuous development of intelligent manufacturing, stemming from the Fourth Industrial Revolution, swiftly integrated these sophisticated technologies. Although the process of digitization brought about significant changes, it also revealed important obstacles in terms of societal sustainability (Jovanović et al., 2018). Hybrid machine learning has emerged as a promising approach in this area. ...
Industry 4.0 has ushered in a new era of technological advancements, particularly in smart production, using technologies like the Internet of Things, big data analytics, and artificial intelligence. While much attention has been focused on the technological and economic aspects of this transformation, the concept of social sustainability within smart production remains underexplored. This paper explores the intersection of technology and social sustainability in the context of smart production in China. Machine learning, especially in hybrid models, is examined as a tool to integrate social sustainability into smart production. These algorithms can analyze vast datasets, predict social disruptions, inform policymaking, and tailor technological solutions. The paper presents a comprehensive analysis of the performance of various machine learning models in forecasting solar PV energy production, with a focus on different photovoltaic technologies and emission scenarios. The results highlight the robustness of certain photovoltaic technologies, such as p-Si and m-Si, in the face of climate variability. The study introduces the MLP-CARIMA-GPM model as a benchmark in predicting solar PV energy output, challenging the traditional belief that composite models always offer superior results. Theoretical and policy implications are discussed, emphasizing the importance of aligning solar PV energy production with Sustainable Development Goals. The research underscores the pivotal role of sophisticated, hybrid machine learning models in ensuring sustainable energy production and offers valuable insights for policymakers, industry leaders, and stakeholders navigating the challenges of energy demands, climate change, and technological advancements. This study serves as a roadmap for achieving sustainable smart production, where technology and sustainability coalesce to illuminate possibilities for the future.
... Digitalization process success in businesses is also impacted by countries' historical, cultural, and development differences (Jovanović et al. 2018;Nelson and Ellis 2019;Hartl and Hess 2017). It is important to consider that post-Soviet bloc countries in Europe experienced significant stagnation in technology adaptation and development during the Soviet era, lacking access and the required infrastructure to use technology and to engage in the earlier technological digitalization processes. ...
... The European region consists of Western Europe and post-Soviet Eastern Europe countries, which are different from each other considering their historical, cultural, and technological developmental differences that have shaped their digital landscapes (Jovanović et al. 2018;Nelson and Ellis 2019;Hartl and Hess 2017). Notably, the legacy of the Soviet era has left Eastern countries at a digital crossroads, facing a unique set of challenges for digital transformation. ...
... The differences in the impact of technological digitalization between Eastern and Western European countries, as well as across company sizes, offer empirical evidence for discussions by Jovanović et al. (2018) and Buer et al. (2021). The findings suggest that the impact of digitalization investment increases operating revenue. ...
Businesses investing in production digitalization equipment are supposed to benefit from increased productivity, enhanced efficiency, and revenue growth. Despite the increasing use of digital technologies in business, many companies still struggle to measure and maximize their returns from production digitalization investments. This research assesses the impact of production digitalization investments on companies’ financial performance (operating revenue) for European businesses in the period of 2013 to 2021. To achieve this target, we performed a Fixed Effects Panel Regression analysis, using a sample size of 5706 records from the Orbis database for 30 countries, covering 634 business units. The production digitalization investment in this research is expressed by a calculated variable value, measured as the annual change in a company’s Plant and Machinery value, adjusted with corresponding an annual depreciation value for the assets. The regression output was analyzed by considering the characteristics of the company size and business location. The results suggest that companies in Eastern Europe benefit more from production digitalization than those in Western Europe. The analysis highlights the tendency for the company costs of the employee and intangible fixed asset value to increase as production digitalization investments grow. Additionally, it shows that large companies tend to gain more from such investments than smaller ones. The analysis provides support and guidance for businesses’ production digitalization investment strategic decision-making processes.
... As per Jovanović et al. [95], individualism and digitalization are moderately positively associated, indicating that societies with collectivistic traits are less digitalized compared to those favoring individualism. Building on the previous idea could be the perspective that, in more individualistic societies, where the focus is on autonomy and individual achievement, individuals might be more motivated to develop their digital skills and adapt more quickly to technological change without depending so much on external assistance, which would also indicate an increased degree of digital skills. ...
In today’s digitalized era, embracing new and emerging technologies is a requirement to remain competitive. The present research investigates the adoption of artificial intelligence (AI) by the elderly in the European landscape, emphasizing the importance of individuals’ digital skills. As has already been globally recognized, the most imminent demographic challenge is no longer represented by the rapid growth of the population but by its aging. Thus, the paper initially analyzed European perspectives on AI adoption, also discussing the importance of focusing on seniors. A bibliometric analysis was required afterward, and the review of the resulting relevant scientific publications uncovered gaps in understanding the relationship between older individuals and AI, particularly in terms of digital competence. Further exploration considered the EU population’s digital literacy and cultural influences using Hofstede’s model, while also identifying potential ways to improve the elderly’s digital skills and promote the adoption of AI. Results indicate a growing interest in AI adoption among the elderly, underscoring the urgent need for digital skills development. The imperative of personalized approach implementations, such as specialized courses, personalized training sessions, or mentoring programs, was underscored. Moreover, the importance of targeted strategies and collaborative efforts to ensure equitable participation in the digital age was identified as a prerequisite for AI adoption by seniors. In terms of potential implications, the research can serve as a starting point for various stakeholders in promoting an effective and sustainable adoption of AI among older citizens in the EU.
... The sociometric factors influence the Index. Jovanović et al. (2018) refer to this topic as such: Digitalization measured by DESI is crucial for sustainable development, impacting economic, social, and environmental compacts. The Digital Economy and Society index is measured by the European Commission, which has monitored the progress since 2014. ...
Digitalization is one of the main catalysts for innovation in the management of modern organizations. One of the main effects of the digitisation process and the tools used is the sharing of information and knowledge inside and outside companies. There are many digitalization and knowledge-sharing measures, including the DESI, or Digital Economy and Security Index, which consists of several items of an organization's digital readiness. For this research, a questionnaire survey was conducted in organisations in the Czech Republic, comparing the development of each indicator over five years. The questionnaire survey managed to collect over five hundred responses. These data will help determine the pace of development of the tools available to organisations in the process of knowledge sharing through digitalisation.
