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Managing knowledge is relevant for the innovativeness of an organization. The innovation of the organization currently aligns with the environment and applies green innovation concepts. Knowledge management (KM) is a key to fostering green innovation and to saving the environment from unnecessary pollution. In line with this, this study aims to evaluate the relationship between KM and green innovation in the literature from 2000 to 2023 synthesize and suggest future directions.

This study used the preferred reporting items for systematic review and meta-analysis technique to identify eligible articles. The papers were identified from the Web of Science core collection and ScienceDirect databases. The results were presented using tables, graphs and the co-occurrence of citations was analyzed using VOSviewer software.

From the review, the authors were assured that there is a strong relationship between KM practices and green innovation in different organizations. Some papers were supported by different theories. From the total of 48 papers, 16 have not mentioned the theories applied in their studies. The geographical distribution of the papers is asymmetrical. Asian and European scholars published more papers. The papers distribution across publishers also varies. For instance, Elsevier and Emerald Group Publishing Ltd. published 29 papers and the remaining papers were published in BMC, Springer, Frontiers Media Sa, IEEE-Inst Electrical Electronics Engineers Inc., MDPI, Routledge Journals and Taylor & Francis Ltd. Major themes were identified and future research directions were forwarded.

The limitation of this review is the authors generated the papers from two databases (WoS and ScienceDirect). This paper does not consider other databases (Scopus, dimensions, etc.) papers. This can be considered as a limitation of this review.

The review is original by integrating PARISMA and bibliometric analysis method (VOS Viewer). The paper tried to explore the role of KM on green innovation.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

Airline self-service technology (SST) has attracted attention from both the academic and aviation sectors. As the use of SST can reduce airlines’ operating costs, investigating SST usage at airports is particularly important for the aviation sector. The extant literature has explored users’ SST usage intention, but users’ switching intentions from traditional manual counter services to SST is still limited. Therefore, to address this issue, we used the push–pull–mooring (PPM) theoretical framework to develop a research model to explore user switching intention.

We utilized a mixed-methods approach. A qualitative approach (i.e., semistructured interviews) was first employed to recognize and choose the candidate factors. Then, we collected 450 valid responses through an online survey to test the model. The partial least squares method was used for data analysis.

We found that several push (perceived dissatisfaction and perceived inconvenience), pull (perceived ease of use, perceived usefulness and service process fit), and mooring (personal innovativeness and inertia) factors significantly influence switching intention. Additionally, mooring factors exert contextual effects on the relationships between push and switching intentions and between pull factors and switching intentions.

This study contributes to the literature by further increasing our understanding of user switching intentions regarding SSTs from the PPM perspective and offering guidance for the aviation sector to attract and retain customers.