The increasing digitalization of economies has highlighted the importance of digital transformation and how it can help businesses stay competitive in the market. However, disruptive changes not only occur at the company level; they also have environmental, societal, and institutional implications. This is the reason why during the past two decades the research on digital transformation has received growing attention, with a wide range of topics investigated in the literature. The following aims to provide insight regarding the current state of the literature on digital transformation (DT) by conducting a systematic literature review. An analysis of co-occurrence using the software VOSviewer was conducted to graphically visualize the literature’s node network. Approached this way, the systematic literature review displays major research avenues of digital transformation that consider technology as the main driver of these changes. This paper qualitatively classifies the literature on digital business transformation into three different clusters based on technological, business, and societal impacts. Several research gaps identified in the literature on DT are proposed as futures lines of research which could provide useful insights to the government and private sectors in order to adapt to the disruptive changes found in business as a result of this phenomenon, as well as to reduce its negative impacts on society and the environment.
National and international organizations have introduced policies aimed at sustainable development. These policies are designed to encourage sustainable forms of business to meet the Sustainable Development Goals (SDGs) of the 2030 Agenda. Regional inequalities in sustainable development may be exacerbated by disparate levels of innovation. This paper analyzes the variations between clusters of countries according to the degree to which they have achieved the SDGs and their levels of innovation facilitators. Two types of analyses were employed. First, cluster analysis was used to examine changes in groups of regions with similar innovation characteristics between 2015 and 2020. Data for 122 countries were gathered from the World Bank, the SDG Index, and the Global Innovation Index. Second, multiple linear regression analysis was used to assess the power of the variables in the model to explain the level of sustainable development. The results reveal four clusters (low, medium, high, and very high innovative facilitators and sustainable development), as well as movements between those clusters from 2015 to 2020. The multiple linear regression analysis shows that the variables have explanatory power with respect to the dependent variable of sustainable development. This analysis also reveals different degrees of importance of the variables for each cluster. The findings highlight the need to consider the limitations of economic growth in terms of innovation facilitators to promote sustainable development. If policymakers recognize the limitations of economic growth and the physical ecosystem, degradation of the environment can be avoided, even when there is innovation. Global and individual social welfare can thus be ensured. This study offers valuable insights into how to achieve sustainable development through innovation facilitators by providing in-depth knowledge of the individual characteristics of innovation systems and considering the limitations of economic growth.
Each country has its own set of unique elements and institutions to foster innovation within its boundaries. This combination of elements and institutions is known as an innovation system. Innovation has been used to boost countries' growth and competitiveness for decades. However, it is a much questioned strategy because it may compromise the opportunities of future generations and thus sustainable development.Hence, academics and policymakers are now turning to eco-innovation to create sustainability-based innovation systems that improve not only a country's economic efficiency but also people's well-being and quality of life. However, the uncertainty and complexity around eco-innovation hinder the creation and implementation of eco-innovation policies because of a failure to identify its drivers. The aim of this paper is to detect the national-level factors that are necessary or sufficient for ecoinnovation in European countries. Fuzzy-set qualitative comparative analysis (fsQCA) is used for this purpose. The conditions in this analysis are governance, human capital capacity, research institutions, and public and private research and development (R&D) investment. The use of fsQCA to study eco-innovation systems is methodologically unique. The findings suggest that research institutions, human capital capacity, and public R&D investment are valuable for eco-innovation. Therefore, the findings of this study have implications for the design of policies aimed at creating businesses, enriching society, and boosting sustainable development through eco-innovation.Such policies should focus on education, social awareness, stakeholder engagement, support from research institutions, and public R&D investment.
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