A Country's Green Brand and the Social Responsibility of Business

Abstract

Recently, the topic of carbon neutrality has been gaining momentum. Such trends are mainly related to the adoption of important global agreements, such as the European Green Deal, as well as the implementation of the Sustainable Development Goals. Such trends have a positive effect on countries, but in such situations, states must quickly respond to the challenges and needs of the world and have an understanding of how to respond to these trends. To date, there are many ratings that can be used to form a portrait of a country (investment, social, environmental, etc.), but currently the rating of the green brand of a country is becoming more relevant. There are problems regarding its improvement and filling, yet this is a new evaluation of a country for this period of time. It is relevant today to study the nature and architecture of the concept of a green brand, as well as the search for the main determinants of its impact. The purpose of the article is to analyse publications in order to identify patterns in the development of the green brand and the social responsibility of business. The article provides a bibliometric analysis of research in the field of green branding and corporate social and environmental responsibility. The authors selected more than 10,000 works published in 2000–2021 indexed by the scientometric databases Scopus, Web of Science and Google Scholar. Using VOSviewer, the results of the bibliometric analysis were visualized on the definition map. This made it possible to identify seven clusters that combine 58 terms. As a result of the research, using the constructed bibliographic map, the connection between the terms ‘green brand’ and ‘corporate social responsibility’ was revealed.

Digitalization and Energy in Attaining Sustainable Development: Impact on Energy Consumption, Energy Structure, and Energy Intensity

“…This suggests that the instruments employed in the system-GMM estimation are sound, affirming that the model avoids overfitting. Additionally, the AR (2) tests indicate that the model effectively addresses second-order serial correlation, reinforcing the credibility of the system-GMM estimators in capturing temporal dependencies within the data.…”

“…However, for ES, the coefficient is positive (0.535, z value = 4.450), suggesting a positive correlation between DESI and the energy structure. The results of the AR (1) and AR (2) tests indicate that the model adequately addresses first-order (AR (1) p value = 0.000) and second-order (AR (2) p value = 0.239, 0.230, 0.104) serial correlations. The p values (0.612, 0.599, 0.565) of the Sargan tests indicate that the instruments used in the system-GMM estimation are valid.…”

“…The positive coefficients for FEC (0.975) and EI (0.890) underscored the influence of past energy consumption and intensity on the present values, while the positive coefficient for ES (0.063) indicated a notable effect on the structure of energy consumption. The results of the AR (1) and AR (2) tests indicate that the model effectively addresses both first-order and second-order serial correlations. The p-values of the Sargan tests confirm the validity of the instruments used in the system-GMM estimation, further affirming the soundness of the model's approach.…”

“…Achieving sustainable development goals (SDGs) [1][2][3][4][5][6] requires the development and implementation of new and effective instruments that consider ongoing trends in world development [7][8][9][10][11], such as digitalization, integrating sustainable development into all economic activities and levels [12][13][14][15]. It should be noted that sustainable development is a multifaceted concept that, at its core, seeks to balance environmental stewardship, economic growth, and social equity for current and future generations [16].…”

Environmental Sustainability within Attaining Sustainable Development Goals: The Role of Digitalization and the Transport Sector

“…Scholars [31] have proven that digital twin technologies are conducive to smart use of available transport systems and optimize the mobility of passengers. At the same time, it requires the relevant knowledge [40][41][42][43][44][45] and infrastructure readiness of the business sector. Mulholland et al [28] show that carbon infrastructure, relevant digital technologies, and data sharing in the supply chain catalyze CO 2 reduction by 56% between 2015 and 2050.…”