Sustainability decision making is a complex task for policy makers, considering the possible unseen consequences it may entail. With a broader scope covering environmental, economic, and social aspects, Life Cycle Sustainability Assessment (LCSA) is a promising holistic method to deal with that complexity. However, to date, this method is limited to the hotspot analysis of a product, service, or system, and hence only assesses direct impacts and overlooks the indirect ones (or consequences). This critical literature review aims to explore the challenges and the research gaps related to the integration of three methods in LCSA representing three pillars of sustainability: (Environmental) Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and Social Life Cycle Assessment (S-LCA). The challenges and the research gaps that appear when pairing two of these tools with each other are identified and discussed, i.e., the temporal issues, different perspectives, the indirect consequences, etc. Although this study does not aim to remove the shadows in LCSA methods, critical research gaps are identified in order to be addressed in future works. More case studies are also recommended for a deeper understanding of methodological trade-offs that might happen, especially when dealing with the consequential perspective.

https://www.mdpi.com/2071-1050/11/3/636/pdf

Exploring the Current Challenges and Opportunities of Life Cycle Sustainability Assessment

Addressing temporal considerations in life cycle assessment

Durable goods last for years, decades, or even centuries. The environmental implications of the changing social, economic, and material conditions in which these goods are embedded can be overlooked by conventional life cycle assessment (LCA) that assumes a static world. To avoid this oversight, methods such as dynamic LCA (DLCA) are increasingly being used. Despite the growing use of DLCA, numerous questions remain, including how this dynamism is incorporated and what aspects of any given DLCA are dynamic. To answer these questions, we performed a review of 56 DLCAs, of which 44 propose a framework for DLCA covering all International Organization for Standardization phases of an LCA or that carry out a DLCA. Three types of LCA dynamism are identified and assessed for the reviewed literature: dynamic process inventory, dynamic systems, and dynamic characterization, while a further 2 types of LCA dynamism, dynamic scope and dynamic weighting, are proposed but not applied in the assessed literature. We found that the implementation of DLCA varies widely, and inventories accounting for dynamic characteristics are by far the most prevalent expression of DLCA. To reduce confusion surrounding the discussion of DLCA, we propose a definition of DLCA and its subtypes: full DLCA, partial DLCA, and prospective LCA. It is concluded that, among the current array of DLCA definitions, the implementation of partially dynamic LCA (PDLCA), which applies dynamism in only some parts of the LCA, is common and likely to continue. This is because PDLCA offers quantifiable marginal utility in terms of increased validity of the assessment, in relation to conventional LCA methods, but caution is needed in applying PDLCA because of potential for introducing bias into the LCA. To avoid this problem, we propose incorporating system dynamism as part of a sensitivity analysis, particularly in PDLCA that are limited by missing data. Integr Environ Assess Manag 2020;16:314-323. © 2019 SETAC.

/pdf/defining-temporally-dynamic-life-cycle-assessment-a-review-5fqjo3d1bf.pdf

Defining Temporally Dynamic Life Cycle Assessment: A Review.

Modeling cumulative effects in life cycle assessment: The case of fertilizer in wheat production contributing to the global warming potential

The purpose of this study is to conduct a bibliometric analysis of Service Quality (SERVQUAL) research in private higher education institutions (HEIs). This analysis aims to provide a comprehensive evaluation of SERVQUAL's current state and future potential in private HEIs. This study collected 205 journal articles from the Web of Science database using a bibliometric approach. Then, co-citation and co-word analyses were conducted to determine the most influential publications, analyze the knowledge structure, and forecast future trends. This review offers valuable insight into the expanding field of SERVQUAL research, despite its limitations, as the analysis revealed five clusters in co-citation and co-word analysis, respectively. This study contributes to the existing body of knowledge by offering a comprehensive understanding of SERVQUAL in the context of private HEIs. Additionally, it provides insight into potential future developments in this field. 

Service quality (SERVQUAL) model in private higher education institutions: A bibliometric analysis of past, present, and future prospects

Huge advances in peer-to-peer systems and attempts to develop the semantic web have revealed a critical issue in information systems across multiple domains: the absence of semantic interoperability. Today, businesses operating in a digital environment require increased supply-chain automation, interoperability, and data governance. While research on the semantic web and interoperability has recently received much attention, a dearth of studies investigates the relationship between these two concepts in depth. To address this knowledge gap, the objective of this study is to conduct a review and bibliometric analysis of 3511 Scopus-registered papers on the semantic web and interoperability published over the past two decades. In addition, the publications were analyzed using a variety of bibliometric indicators, such as publication year, journal, authors, countries, and institutions. Keyword co-occurrence and co-citation networks were utilized to identify the primary research hotspots and group the relevant literature. The findings of the review and bibliometric analysis indicate the dominance of conference papers as a means of disseminating knowledge and the substantial contribution of developed nations to the semantic web field. In addition, the keyword co-occurrence network analysis reveals a significant emphasis on semantic web languages, sensors and computing, graphs and models, and linking and integration techniques. Based on the co-citation clustering, the Internet of Things, semantic web services, ontology mapping, building information modeling, bioinformatics, education and e-learning, and semantic web languages were identified as the primary themes contributing to the flow of knowledge and the growth of the semantic web and interoperability field. Overall, this review substantially contributes to the literature and increases scholars’ and practitioners’ awareness of the current knowledge composition and future research directions of the semantic web field.

/pdf/charting-past-present-and-future-research-in-the-semantic-3vr3bqzf.pdf

Charting Past, Present, and Future Research in the Semantic Web and Interoperability

One of the major problems existing in current LCA is the temporal homogeneity issue in the compiled life cycle inventory data [1–2]. In current practice, the life cycle inventory data are aggregated along a product's life cycle without considering the data's temporal differences. The aggregating approach introduces temporal uncertainties in LCA and may cause inaccurate estimates of the environmental impact and lead to improper decision-making in the sustainability management and environmental practices, in particular on those long-lived products and systems [3].

Temporal discounting for life cycle assessment: Differences between environmental discounting and economic discounting

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Charting Past, Present, and Future Research in the Semantic Web and Interoperability

Temporal discounting for life cycle assessment: Differences between environmental discounting and economic discounting