Towards reliable primary data collection and harmonized set of indicators in S-LCA on the stakeholder worker

Abstract Introduction S-LCA has emerged within sustainability assessment in the last 20 years, aiming at assessing the social impacts of products and services. Several improvements on the methodological and theoretical backgrounds were reported in the literature, since its early beginning. However, there are still some gaps that must be filled: lack of consensus on the indicators, methodological limitations, and hegemony of secondary data, among others. Therefore, this research aimed to benefit from one area related to social sciences, named as psychometrics, to develop 14 questionnaires (scales) to collect primary data regarding all worker’s impact subcategories. Method In general terms, the methodological steps were as follows: (1) literature review of the impact subcategories; (2) definition of the constitutive and operational definitions; (3) run focus groups with workers from different economic sectors and positions to deep understand their reality; (4) creating scales’ items; (5) run semantics analysis; (6) run specialists’ analyses; (7) pilot and final application of the scales; and (8) run exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results and discussion Five different focus groups were run to better understand each subcategory, and 14 semantics analyses to check the understanding of the scales’ items. Five different groups comprised of four different experts on S-LCA assessed the items’ content. Kappa’s Fleiss indicated from moderate to almost perfect agreement. The scales were applied in two rounds. On the first, EFA was run pointing out to factor retention solution identical or close to the literature review. CFA confirmed the models proposed with adequate adjustment indices. The analyses have shown that all 14 scales indicated to have evidence of content validity and validity based on the internal structure. The reliability coefficients relating to the indicators appointed to a high precision on the measurement. Conclusions This study contributes to overcoming some of the current theoretical and methodological gaps in S-LCA. Practitioners can benefit from 14 scales to collect primary data regarding worker in a reliable, scientific, and confidential way. Data can be used in both types of impact assessment methods. The scales may also support other research initiatives that aim at studying and improving working conditions for all workers, from any economic sector.

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Publication Details

Journal
The International Journal of Life Cycle Assessment
Published
2024-11-29
DOI
https://doi.org/10.1007/s11367-024-02400-z
Citations
6
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
1.23

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article

Towards reliable primary data collection and harmonized set of indicators in S-LCA on the stakeholder worker

Cássia Maria Lie Ugaya, Arij Mohamad Radwan Omar Chabrawi, Marzia Traverso, Josemberg Moura de Andrade
6 citations
The International Journal of Life Cycle Assessment
Environmental Impact and Sustainability
1.23
article

Towards reliable primary data collection and harmonized set of indicators in S-LCA on the stakeholder worker

Cássia Maria Lie Ugaya, Arij Mohamad Radwan Omar Chabrawi, Marzia Traverso, Josemberg Moura de Andrade
article en
6 citations

Abstract

Abstract Introduction S-LCA has emerged within sustainability assessment in the last 20 years, aiming at assessing the social impacts of products and services. Several improvements on the methodological and theoretical backgrounds were reported in the literature, since its early beginning. However, there are still some gaps that must be filled: lack of consensus on the indicators, methodological limitations, and hegemony of secondary data, among others. Therefore, this research aimed to benefit from one area related to social sciences, named as psychometrics, to develop 14 questionnaires (scales) to collect primary data regarding all worker’s impact subcategories. Method In general terms, the methodological steps were as follows: (1) literature review of the impact subcategories; (2) definition of the constitutive and operational definitions; (3) run focus groups with workers from different economic sectors and positions to deep understand their reality; (4) creating scales’ items; (5) run semantics analysis; (6) run specialists’ analyses; (7) pilot and final application of the scales; and (8) run exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results and discussion Five different focus groups were run to better understand each subcategory, and 14 semantics analyses to check the understanding of the scales’ items. Five different groups comprised of four different experts on S-LCA assessed the items’ content. Kappa’s Fleiss indicated from moderate to almost perfect agreement. The scales were applied in two rounds. On the first, EFA was run pointing out to factor retention solution identical or close to the literature review. CFA confirmed the models proposed with adequate adjustment indices. The analyses have shown that all 14 scales indicated to have evidence of content validity and validity based on the internal structure. The reliability coefficients relating to the indicators appointed to a high precision on the measurement. Conclusions This study contributes to overcoming some of the current theoretical and methodological gaps in S-LCA. Practitioners can benefit from 14 scales to collect primary data regarding worker in a reliable, scientific, and confidential way. Data can be used in both types of impact assessment methods. The scales may also support other research initiatives that aim at studying and improving working conditions for all workers, from any economic sector.

The International Journal of Life Cycle AssessmentVol. 30(6)
Universidade Tecnológica Federal do Paraná (BR), Universidade de Brasília (BR), RWTH Aachen University (DE)
RWTH Aachen University
Responsible consumption and production
Openalex Percentile: Top 23%
Environmental Impact and Sustainability
1.23
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