Naiara Pikatza Gorrotxategi¹, Izaskun Alvarez-Meaza¹, Rosa María Río-Belver² and Enara Zarrabeitia Bilbao¹

¹ Industrial Organization and Management Engineering Dept. University of the Basque Country. Ingeniero Torres Quevedo 1, 48013 Bilbao (Spain)

² Industrial Organization and Management Engineering Dept. University of the Basque Coun-try. Nieves Cano 12, 01006 Vitoria-Gasteiz,(Spain)

naiara.picaza@ehu.eus

Keywords: sLCA, bibliometric analysis, network analysis.

1. Introduction

Social life cycle assessment (sLCA) is a methodology to support decision making on social impacts, positive and negative, actual or potential, related to product life cycles [1,2]. Being a relatively new tool, the indicators are not yet homogenized and the method does not have a standard to be followed nor a code of practice [3] [4]. Therefore, describing the state-of-the-art scientific research into sLCA is necessary to clarify the current situation and to determine future development goals [5]. The aim of this paper is, to describe the scientific trends related to sLCA through a bibliometric and a network analysis. This will enable us to identify the main collaborations and help to standardize the sLCA methodology.

2. Methodology

The research process consists of four steps. 1, define the search query. 2, retrieve data. 461 articles from the Scopus database and 348 from the WOS database were obtained and exported. 3, clean up the refined database. Using Vantage Point (VP) text mining software, the obtained data were cleaned up, applying fuzzy logic algorithms to clean up the data fields. 4, generate the sLCA scientific profile and the network analysis. This scientific profile will define the publication trends and academic performance, and the network analysis will allow us to determine the main collaboration relationships.

3. Results

3.1. Publications

Analysing the evolution of publications on sLCA from 1996 to 2020, there is an evident upward trend, starting in 2009(9). The second turning point occurs in 2013with 26 publications. The number of publications continues to grow and there is a substantial quantitative leap in 2018. This trend continues in 2019 (91), although it drops down to 59 publications in 2020.

3.2. Countries

In terms of countries that have published the most on sLCA, Germany stands out with 99 publications, followed by Italy (66) and the USA (57). The other countries lag considerably behind, led by Canada (33), and France and Spain with 31 each. The co-occurrence network shows that Germany, Italy, USA and Netherlands are the most collaborative countries and, as they belong to the same cluster, they collaborate with each other. The most intermediary countries are USA, Italy, France, Denmark and Germany, It has also been found that connections to nodes in other clusters are high.

3.3. Organizations

In terms of the institutions that have published on sLCA, there is a clear dominance of universities. The Technical University of Berlin comes first, followed by the Technical University of Denmark (16), Hong Kong Polytechnic University (15) and RWTH Aachen University (14). The institution that collaborates the most is the Technical University of Berlin, followed by UTFPR. Identifying the organizations from the business world, there were found companies from the automotive sector (BMW, Daimler, Good- year…), the chemical sector (BASF, Avantium), the steel sector (Arcelor Mittal), the computer sector (Dell…) and consultancy (Ernst&Young, KPMG). In addition, the European Union stands out as the main driver of research, financing 8% of the publications developed and almost 20% of the total number of publications financed, following Ger- many, USA and China, among others.

3.4.  Authors

After measuring scientific collaboration among authors, it was found that there is a very high modularity level (0,945), indicating “closed” collaboration between clusters. Finkbeiner, Traverso, De Luca, Iofrida and Benoit Norris stand out as major contributors with the highest weighted degree. Hauschild and Saling are not among the top contributing authors, however, they rank third and fifth in degree of intermediation, as indicated by the betweenness centrality data.

3.5. Research topics

Quantifying the most important keywords in terms of number of collaborations (weighted degree) and intermediation (betweenness centrality), it was found that among the most frequently used keywords are those related to sLCA, such as LCA, Sustainability, LCC and LCSA. These terms are in line with the major intermediate terms. Among these, the term “industrial Ecology”, which does not appear among the top contributors, appears in fifth place.

4. Conclusions

sLCA, as a methodology for measuring the social impacts of companies, is gaining prominence. More and more is being published on sLCA, especially since 2018. The countries doing the most research on the subject are European, with Germany leading by far, followed by Italy. Nonetheless, the United States, Canada, China and Brazil are also among the top researchers. In terms of scientific collaborations, the same countries appear as the main collaborators, although the United States ranks first as an intermediary country. The institutions that contribute the most scientific production on sLCA are mainly European universities of technology. These universities have a closed pat- tern of scientific collaboration on sLCA, i.e. they form research clusters that collaborate little with other clusters. The same is true for the main authors; research is also carried out in closed clusters. In addition, the European Union is the main economic driver of this research topic. Finally, the most frequently used keywords in the publications are those related to life cycle, assessment and sustainability.

References

1. UNEP Setac Life Cycle Initiative Guidelines for Social Life Cycle Assessment of Products. Management 2009, 15, 104.
2. Jørgensen, A. Social LCA – A way ahead? Int. J. Life Cycle Assess. 2013, 18, 296–299, doi:10.1007/s11367-012-0517-5.
3. Arcese, G.; Lucchetti, M.C.; Massa, I.; Valente, C. State of the art in S-LCA: integrating literature review and automatic text analysis. Int. J. Life Cycle Assess. 2018, 23, 394– 405, doi:10.1007/s11367-016-1082-0.
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