A Bibliometric Analysis of Carbon Labeling Schemes in the Period 2007–2019

Abstract

Carbon labeling schemes enable consumers to be aware of carbon emissions regarding products or services, to help change their purchasing behaviors. This study provides a bibliometric analysis to review the research progress of carbon labeling schemes during the period 2007–2019, in order to provide insight into its future development. Number of publications, countries of publications, authors, institutions, and highly cited papers are included for statistical analysis. The CiteSpace software package is used to visualize the national collaboration, keywords co-appearance, and aggregation. The results are given as follows: (1) there are 175 articles published in the pre-defined period, which shows a gradual increase, with a peak occurred in 2016; (2) carbon labeling schemes are mainly applied to grocery products, and gradually emerged in construction and tourism. (3) Existing studies mainly focus on examination of utility of carbon labeling schemes, by conducting surveys to investigate individual perception, preference, and willingness to pay. (4) Future research will include the optimization of life cycle assessment for labeling accreditation, improvement of labeling visualization for better expression, and normalization of various environmental labels to promote sustainable consumption.

Household CO2 Emissions: Current Status and Future Perspectives

“…However, due to the relatively insufficient output of high-quality papers, China may not be sufficiently recognized by the academic community. It is necessary to consider cooperation among developing and developed countries in academic research, for example, on carbon labeling schemes [30], and market mechanisms [31]. Thus, there is an urgent need to strengthen cooperation among China and other countries, especially USA, the UK, and Australia, to enhance China's influence on HCE research.…”

“…Burst detection is used to determine whether there has been any change in the research hotspots, and it can help to gain insights into future research topics [30,32]. We identify the keywords ranked by burst detection (the red rectangle means the strongest bursts), as shown in Figure 5b.…”

“…There is a strong correlation between these four themes, which shows that different areas and different directions of HCEs are mutually inherited and connected. Burst detection is used to determine whether there has been any change in the research hotspots, and it can help to gain insights into future research topics [30,32]. We identify the keywords ranked by burst detection (the red rectangle means the strongest bursts), as shown in Figure 5b.…”

Material Selection in Green Design: A Method Combining DEA and TOPSIS

“…At present, increasing amounts of multi-attribute decision-making and evaluation models are applied to material selection that meets different needs [11,12]. Common methods that are used in this field include AHP, Fuzzy, ELECTER, DEA, VIKOR, Grey, and TOPSIS [13][14][15][16]. These methods are applicable to different scenarios because of their own characteristics, advantages, and disadvantages.…”

Circular Economy in Low-Carbon Transition

“…To implement the circular economy in the low-carbon transition, new supply chain opportunities can be explored; at the same time, new dilemmas must be carefully solved through the life-cycle approach, to avoid the environmental burdens shifting [5,6]. The international community-including scientists, policymakers, industries, and markets-must develop new tools and competencies to support interdisciplinary innovation through the adoption of a comprehensive perspective, and to generate sustainable values from green low-carbon behavior [7,8].…”