Despite the ongoing research on energy efficiency and innovation in the context of Industry 4.0, little is known on how degree of leakages in economy can impact the energy efficiency-innovation association. This issue has been addressed by the United Nations in their Sustainable Development Goals (SDG) report also. In the era of Industry 4.0, this issue can be crucial from the perspective of sustainable development, and we are analyzing this issue in case of Middle East and North African (MENA) countries over a period of 1990-2016. The secondgeneration methodological approaches have been adopted. Our results show that technological innovation has a positive impact on energy efficiency, whereas growth in shadow economy has a detrimental impact on energy efficiency. The structural transformation of economy has positive impact on energy efficiency. Based on our results, we have designed an SDG framework, which might help the MENA countries to achieve the objectives of SDG 7, SDG 8, SDG 9, and SDG 4.

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Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future.

There are an increasing number of academic researches and sustainable development policies focusing on planetary boundaries. However, no research has been conducted to far on drawing scienti c investigation map of planetary boundaries. Therefore, this paper conducted a scientometric analysis of 530 academic publications and their 1784 references on planetary boundaries from 2009 to 2021 by visualizing the social network, dual-map overlay, co-cited references, structure variation article, and cooccurrence keywords with Citespace. The results show that as a new achievement and paradigm in the eld of sustainable development research, the planetary boundaries framework is gradually getting global attention and promotion, which increasingly becomes an interdisciplinary hot research topic. The most productive authors and institutions are concentrated in England, the United States, Germany, and Sweden. Relevant articles were mainly published in journals focusing on ecology, earth, marine, veterinary, animal, economics and politics, as represented by the dual-map overlay. In addition, we summarized three predominant research themes by clustering keywords: the calculation of single boundary threshold and present value, the integration with assessment methods such as life cycle assessment and footprint families, the downscaling of planetary boundaries, and the expansion to economic and social domains. For scholars interested in this topic, this paper would be a useful reference and guideline. a timeline map of the keywords (representative node "climate change")