Sustainable remediation through the risk management perspective and stakeholder involvement: A systematic and bibliometric view of the literature

Braun, Adéli Beatriz; Trentin, Adan William da Silva; Visentin, Caroline; Thomé, Antônio

doi:10.1016/j.envpol.2019.113221

Cited by 46 publications

(18 citation statements)

References 61 publications

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“…Furthermore, the instrumental use of this review leads to a possibility of finding the most relevant papers and researches in the specific field composed by the most accurate scientific indexes that surround the topic (Botelho et al , 2011; Denyer and Tranfield, 2009; Braun et al , 2019). Besides, this review technique mitigates the error of double research topics already consolidated in the field and, more importantly, it allows to explore the unknown or not over-researched parameters inside the main objective topic of the study itself.…”

Section: Methodsmentioning

confidence: 99%

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Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review

Pacheco

Bragagnolo

Thomé

2021

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Purpose The purpose of this article is to analyze the state-of-the art in a systematic way, identifying the main research groups and their related topics. The types of studies found are fundamental for understanding the application of artificial neural networks (ANNs) in cemented soils and the potential for using the technique, as well as the feasibility of extrapolation to new geotechnical or civil and environmental engineering segments. Design/methodology/approach This work is characterized as being bibliometric and systematic research of an exploratory perspective of state-of-the-art. It also persuades the qualitative and quantitative data analysis of cemented soil improvement, biocemented or microbially induced calcite precipitation (MICP) soil improvement by prediction/modeling by ANN. This study sought to compile and study the state of the art of the topic which possibilities to have a critical view about the theme. To do so, two main databases were analyzed: Scopus and Web of Science. Systematic review techniques, as well as bibliometric indicators, were implemented. Findings This paper connected the network between the achievements of the researches and illustrated the main application of ANNs in soil improvement prediction, specifically on cemented-based soils and biocemented soils (e.g. MICP technique). Also, as a bibliometric and systematic review, this work could achieve the key points in the absence of researches involving soil-ANN, and it provided the understanding of the lack of exploratory studies to be approached in the near future. Research limitations/implications Because of the research topic the article suggested other applications of ANNs in geotechnical engineering, such as other tests not related to geomechanical resistance such as unconfined compression test test and triaxial test. Practical implications This article systematically and critically presents some interesting points in the direction of future research, such as the non-approach to the use of ANNs in biocementation processes, such as MICP. Social implications Regarding the social environment, the paper brings approaches on methods that somehow mitigate the computational use, or elements necessary for geotechnical improvement of the soil, thereby optimizing the same consequently. Originality/value Neural networks have been studied for a long time in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, soil cementation is a widespread technique and its prediction modes often require high computational strength, such parameters can be mitigated with the use of ANNs, because artificial intelligence seeks learning from the implementation of the data set, reducing computational cost and increasing accuracy.

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Section: Methodsmentioning

confidence: 99%

“…After the starting portfolio, the data were analyzed to select the effective publications. To do so, a methodology based on previous bibliometric and systematic (Botelho et al , 2011; Braun et al , 2019; Vanzetto and Thom, 2019) review papers were developed considering the adaptions for the scenario.…”

Section: Methodsmentioning

confidence: 99%

Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review

Pacheco

Bragagnolo

Thomé

2021

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“…In recent years, bibliometric analysis has been widely employed to investigate the development of a given scientific area, such as tourism and sustainability [22][23][24], green innovation [25,26], risk management [27,28], entrepreneurship [29,30], and COVID-19 research [31][32][33]. Although Zhang [49] conducted a bibliometric analysis in 2012, it should be noted that the study was conducted in the early stages of eSports research [7,14], and the scope was limited to a Chinese digital database (China National Knowledge Infrastructure (CNKI)).…”

Section: Bibliometric Analysismentioning

confidence: 99%

Knowledge Mapping and Sustainable Development of eSports Research: A Bibliometric and Visualized Analysis

Chiu¹,

Fan²,

Nam

et al. 2021

Sustainability

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The rapid expansion of the eSports industry has attracted scholars’ attention in recent years. However, little research has investigated the evolution of the extant eSports literature. This study aimed to explore the existing knowledge base of eSports and its research networks across authors, journals, institutions, and countries by performing a bibliometric analysis. A total of 260 studies published between 2010 and 2021 were extracted from the Scopus database, which is one of the largest abstract and citation databases. Then, they were analyzed using VOSviewer. Specifically, a series of analyses were conducted: (1) citation analysis, (2) co-occurrence analysis of keywords, and (3) co-citation analysis. The findings revealed that the existing eSports literature mainly revolves around eSports games and activities closely related to eSports. Moreover, the most influential authors and publications were identified. In addition, the studies have been published in journals of various disciplines (e.g., technology and psychology), and the concepts and theories in sport-related fields (e.g., sports management) have been extensively applied in eSports research. This study’s findings contribute to a better understanding of eSports research, which can further provide directions for the sustainable development of eSports research.

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“…Amin et al (2019) used the bibliometric methodology to analyze research output on process safety and risk analysis, Fu et al (2021) analyzed Arctic shipping risk management using bibliometric analysis, Nobanee et al (2021) used a bibliometric method to analyze research output on sustainability and risk management, and Díez-Herrero and Garrote (2020) analyzed flood risk analysis and assessment research output using bibliometric analysis. Braun et al (2019) conducted systematic and bibliometric methods to analyze the literature on sustainable remediation through the risk management perspective and stakeholder involvement, Xu et al (2020) analyzed the existing literature on disruption risks in supply chain management using bibliometric analysis methodology, Ganbat et al (2018) employed the bibliometric method to review the literature on risk management and building information modeling for international construction, and Han et al ( 2020) used a bibliometric overview of research trends on heavy metal health risks. Fuentes Cabrera et al (2019) applied the bibliometric review methodology to analyze the literature on bullying among teens, ethnicity, and race risk factors for victimization.…”

Section: Introductionmentioning

confidence: 99%

Reputational Risk and Sustainability: A Bibliometric Analysis of Relevant Literature

Nobanee

Alhajjar

Abushairah

et al. 2021

Risks

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This study aims to conduct a bibliometric analysis of reputational risk and sustainability. The research was conducted using the Scopus database, which returned 88 publications published during 2001–2020, revealing that the amount of research output within this field is limited, and more research output should be conducted in the field of reputational risk and sustainability. We identified nine research streams: reputation risk, reputation risk and sustainability, supply chain management, social responsibility, reputation risk management, strategic approach, sustainable development, corporate sustainability and risk assessment. This bibliometric analysis provides managerial and policy implications for sustainability consideration of reputational risk with perceptions to advance knowledge in this important research field.

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Sustainable remediation through the risk management perspective and stakeholder involvement: A systematic and bibliometric view of the literature

Cited by 46 publications

References 61 publications

Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review

Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review

Knowledge Mapping and Sustainable Development of eSports Research: A Bibliometric and Visualized Analysis

Reputational Risk and Sustainability: A Bibliometric Analysis of Relevant Literature

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