Bibliometrics in operations research and management science: a university analysis

Laengle, Sigifredo; Merigó, José M.; Modak, Nikunja Mohan; Yang, Jian‐Bo

doi:10.1007/s10479-018-3017-6

Cited by 26 publications

(18 citation statements)

References 48 publications

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“…Genetic algorithm is the process of optimization that is completely based on natural selection of resources. It relates itself with natural evolution process with an aim to select most suitable resources for productive activities (Laengle et al , 2018; Lu et al , 2018; Vouzas and Katsogianni, 2018; Luthra et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Role of artificial intelligence in operations environment: a review and bibliometric analysis

Dhamija

Bag

2020

TQM

178

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Purpose“Technological intelligence” is the capacity to appreciate and adapt technological advancements, and “artificial intelligence” is the key to achieve persuasive operational transformations in majority of contemporary organizational set-ups. Implicitly, artificial intelligence (the philosophies of machines to think, behave and perform either same or similar to humans) has knocked the doors of business organizations as an imperative activity. Artificial intelligence, as a discipline, initiated by scientist John McCarthy and formally publicized at Dartmouth Conference in 1956, now occupies a central stage for many organizations. Implementation of artificial intelligence provides competitive edge to an organization with a definite augmentation in its social and corporate status. Mere application of a concept will not furnish real output until and unless its performance is reviewed systematically. Technological changes are dynamic and advancing at a rapid rate. Subsequently, it becomes highly crucial to understand that where have the people reached with respect to artificial intelligence research. The present article aims to review significant work by eminent researchers towards artificial intelligence in the form of top contributing universities, authors, keywords, funding sources, journals and citation statistics.Design/methodology/approachAs rightly remarked by past researchers that reviewing is learning from experience, research team has reviewed (by applying systematic literature review through bibliometric analysis) the concept of artificial intelligence in this article. A sum of 1,854 articles extracted from Scopus database for the year 2018–2019 (31st of May) with selected keywords (artificial intelligence, genetic algorithms, agent-based systems, expert systems, big data analytics and operations management) along with certain filters (subject–business, management and accounting; language-English; document–article, article in press, review articles and source-journals).FindingsResults obtained from cluster analysis focus on predominant themes for present as well as future researchers in the area of artificial intelligence. Emerged clusters include Cluster 1: Artificial Intelligence and Optimization; Cluster 2: Industrial Engineering/Research and Automation; Cluster 3: Operational Performance and Machine Learning; Cluster 4: Sustainable Supply Chains and Sustainable Development; Cluster 5: Technology Adoption and Green Supply Chain Management and Cluster 6: Internet of Things and Reverse Logistics.Originality/valueThe result of review of selected studies is in itself a unique contribution and a food for thought for operations managers and policy makers.

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Section: Introductionmentioning

confidence: 99%

Role of artificial intelligence in operations environment: a review and bibliometric analysis

Dhamija

Bag

2020

TQM

178

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“…The results of the literature analysis (Figure 2a) showed that after 2010, especially after 2015, UAV remote sensing and related research on grasslands showed an exponential growth trend. [20,21]. The results (Figure 2b,c) showed that UAV remote sensing was widely applied in grassland ecosystem monitoring, focusing on grassland vegetation monitoring, and key hotspots included coverage, vegetation height, biomass, vegetation index, etc.…”

Section: Uav Remote Sensing Technology and Grassland Ecosystem 21 Dev...mentioning

confidence: 98%

Unmanned Aerial Vehicle (UAV) Remote Sensing in Grassland Ecosystem Monitoring: A Systematic Review

Lyu

Dang

et al. 2022

Remote Sensing

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In recent years, the application of unmanned aerial vehicle (UAV) remote sensing in grassland ecosystem monitoring has increased, and the application directions have diversified. However, there have been few research reviews specifically for grassland ecosystems at present. Therefore, it is necessary to systematically and comprehensively summarize the application of UAV remote sensing in grassland ecosystem monitoring. In this paper, we first analyzed the application trend of UAV remote sensing in grassland ecosystem monitoring and introduced common UAV platforms and remote sensing sensors. Then, the application scenarios of UAV remote sensing in grassland ecosystem monitoring were reviewed from five aspects: grassland vegetation monitoring, grassland animal surveys, soil physical and chemical monitoring, grassland degradation monitoring and environmental disturbance monitoring. Finally, the current limitations and future development directions were summarized. The results will be helpful to improve the understanding of the application scenarios of UAV remote sensing in grassland ecosystem monitoring and to provide a scientific reference for ecological remote sensing research.

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“…The use of bibliometric analysis has been increasing rapidly. Researchers have conducted bibliometric research in a wide range of fields, including microplastics [42], finance [43], medicine [44], supply chain management [45], operations research and management science [46], business [47], and physics [48].…”

Section: A Bibliometric Analysismentioning

confidence: 99%

Bibliometric Analysis of the Blockchain Scientific Evolution: 2014–2020

Luo

Bai

2021

IEEE Access

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As one of the disruptive technologies in the fourth industrial revolution, Blockchain has irrevocably changed how people live and work. Many scholars have studied the Blockchain, and the number of related publications has increased over time. Bibliometrics is an excellent method to study the development trend of a specific field. However, few scholars have used bibliometrics to research Blockchain; the inheritance and evolution among its different research themes have not yet been fully understood. This study emphasizes the scientific evolution and research focus of Blockchain through bibliometric analysis. We analyzed 2993 publications from 2014 to 2020 using co-word analysis and cluster analysis with bibliometric tools such as the SciMAT. The most productive author, country, institutions and leading research areas were identified, outlining the Blockchain field's fundamental developments. The results show the changes in keywords regarding Blockchain summarize the research hotspots in different periods. The study discusses the evolution process of various themes in each period, providing a meaningful reference for scholars to identify research hotspots and future research directions in the Blockchain field.

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Bibliometrics in operations research and management science: a university analysis

Cited by 26 publications

References 48 publications

Role of artificial intelligence in operations environment: a review and bibliometric analysis

Role of artificial intelligence in operations environment: a review and bibliometric analysis

Unmanned Aerial Vehicle (UAV) Remote Sensing in Grassland Ecosystem Monitoring: A Systematic Review

Bibliometric Analysis of the Blockchain Scientific Evolution: 2014–2020

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