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The purpose of this study is to measure the quality of nuclear science and technology research using the scientometric indicators, like activity index, attractivity index and publication efficiency index.

The present scientometric study is based on the bibliographic data extracted from the core collection of the Web of Science database from 1989 to 2019. The data was collected using the advanced search feature, with a search string of 28 related terms. The bibliographic data for all the journal articles, excluding all other formats, was downloaded for statistical analysis.

The present study highlights the growth pattern and the research efforts devoted to the field of nuclear science and technology worldwide, as reflected through the Core Collection of the Web of Science database, for 31 years from 1989 to 2019. The USA has emerged as the topmost producer, with a total share of almost 29% with respect to the world literature followed by Japan, Germany, France and UK. However, the relative citation impact has been the highest for Netherlands followed by the USA, Germany, France and UK, respectively. The study depicted that the activity index, also called as the relative performance indicator, has been the highest for the USA, whereas the attractivity index has been the highest for China, indicating its dominance in attracting citations to its publications in the field of nuclear science and technology. The publication efficiency index, the value has been the maximum for Iran, for which the value has been greater than 1 (1.618). The measure suggests that Iran’s research effectiveness in the field of nuclear science and technology has been more than the research effort devoted to the field.

The paper was based on the data retrieved from a single database, and the results may vary across other databases. Hence, caution should be taken while generalizing the findings.

Several scientometric studies have taken place in the field of nuclear science and technology, particularly in its allied branches, but none of the studies has focused on evaluating the research efforts carried out by the countries in terms of activity index, attractivity index and publication efficiency index, and the present study is an attempt to fill the gap.

The focus of this study was to evaluate the relationship between research publications in the pesticide field, a country’s gross domestic product (GDP) and GDP per capita. The study aims to analyze pesticide use in association with a country’s population and research publications. The purpose of this study is to uncover the country’s contribution to pesticide research and assess the financial resources allocated to it as a percentage of their GDP by exploring these factors.

The Web of Science database was used to retrieve data for the period of 2001–2020. The use of scientometric indicators allowed for the analysis of the collaborative patterns and active performance of countries in pesticide research. Socio-economic analysis was used to determine the contribution of countries toward pesticide research.

This study demonstrated a strong association (0.952%) between a country’s GDP and its research publications in the field of pesticide research. Countries, such as Denmark, Belgium and Australia, have benefited from global collaboration, which has enhanced their research efforts. Despite ranking lower in pesticide utilization, India focused on pesticide research, as indicated by its high publication/GDP per capita ratio (0.26).

Research on pesticides directly impacts agricultural practices, which, in turn, influence the economic production of the agricultural sector. Changes in pesticide usage can have inference for crop yields, food price and, eventually, the GDP. Comparative analysis can assist in evaluating the efficiency of regulatory policies in balancing ecological concerns with economic interests. Changes in regulations may impact both pesticide usage and economic outcomes.

This study provides a bibliometric analysis of bank efficiency and competition over the past years (from 1993 to 2022) to (1) discover the past and current state of knowledge on bank competition and efficiency, (2) identify leading and authoritative journals and scholars who made significant contributions to the distribution of knowledge and impact, (3) identify nations that made a significant contribution and impact to the literature and (4) identify the structure of collaboration that exists between scholars in the areas of bank competition and efficiency and key thematic areas.

A total number of 868 documents made up of articles, reviews, book chapters, book and conference papers from the Scopus database were gathered. This study used a bibliometric analytic approach.

The number of documents on bank competitiveness and efficiency has increased significantly, as have their total publications, citations and national output. Additionally, the most esteemed and prestigious academic journals of eminent academics who have had a significant impact on the dissemination of knowledge on bank efficiency and competition literature champion papers on banking efficiency and competition. In terms of citation performance and collaborative efforts, the United States tops the developed countries, led by China, which is also the most productive. Additionally, single-country publications predominate in the literature, with China ranking first among the top five countries with corresponding authors. While the Lerner index, H-statistic, concentration index and market power were used to measure bank competitive behaviour, the data envelopment analysis approach predominates efficiency estimation techniques that are linked to cost, profit or revenue, scale, technical and productivity indexes.

This study is one of the first to offer bibliometric evidence of both bank competition and efficiency. It also offers proof of the distribution of knowledge and intellectual structure of the concepts and concerns in bank competition and efficiency.

Data Envelopment Analysis (DEA) is a nonparametric mathematical programming technique used to measure the relative efficiency of the production organization's operations. This paper presents the theoretical measures of the railway systems, along with the bootstrap DEA analysis. A DEA model is applied to evaluate the relative efficiency of railway operations of 29 UIC (Union Internationale des Chemins de fer) countries, based on the data obtained from the International UIC publications. The bootstrap DEA analysis provides information (bias estimates) on the sensitivity of the DEA efficiency index to the sampling variations. The model results are analyzed and evaluated in terms of their relative operational performance efficiency. The model results facilitate an organization's decision-making by providing valuable information.

This paper aims to present a citation-based bibliometric review of Islamic banking efficiency literature from 2000 until August 2020 for analyzing the content of the literature and mapping future research directions.

Using bibliometric citation analysis, this study reviews and examines a total of 278 documents from Web of Science (WoS) indexed sources coupled with content analysis.

The results identified that the growth of Islamic banking efficiency literature has begun to rise since 2008 with an annual growth rate of 12.5% while identifying the most influential aspects of Islamic banking efficiency literature in terms of topics, papers, authors and keywords. The outcomes of science mapping (i.e. co-citation network, bibliometric coupling and co-authorship network) reveal that there are three underlying research streams in Islamic banking efficiency literature: growth of Islamic banking efficiency literature, stability and genuineness of Islamic banking operations and the methods in Islamic banking efficiency literature.

To the best of the knowledge, this is the first bibliometric review paper on Islamic banking efficiency literature. It successfully unveils the scientific mapping of published WoS documents with a future research agenda also proposed based on the review outcomes. These findings can be used in efficiency-related initiatives by managers or regulators for managing Islamic bank operations worldwide.

This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for text retrieval. We analyse parallel IR systems using a classification defined by Rasmussen and describe some parallel IR systems. We give a description of the retrieval models used in parallel information processing. We describe areas of research which we believe are needed.

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to benchmark one company for best performance on the basis of selected alternatives among its peer group companies.

The present study has used a hybrid model by applying data envelopment analysis (DEA)-technique for order performance by similarity to ideal solution (TOPSIS) to measure the efficiency and ranking of various decision units on the basis of specified variables.

The findings of DEA have given the best alternative or best decision-making unit (DMU) among the set of 25 DMUs considered for empirical testing. The DEA technique is used with TOPSIS, which is another popular multi-criteria decision model. The integrated DEA-TOPSIS model has helped to compute the efficiency score of all 25 DMUs of study and also provide a unique rank to each of the efficient unit identified with the help of DEA technique.

The findings of the study have provided Benchmark Company amongst the companies following best practices for saving energy and having best operating profits too. This benchmark business unit can be studied extensively by peer group companies to compare various parameters affecting their efficiency and profits both.

The findings of the study will promote the socially responsible practices by corporate citizens and adopt the practices to reduce their carbon footprints. It will also suggest to socially responsible investors to select the benchmark and most efficient companies for investment purpose.

The study is original in terms of measuring efficiency and ranking of companies known for best practices for controlling their carbon footprints and suggesting a benchmark company to its peer group. Also, the integrated approach of using DEA-TOPSIS for such type of studies also makes it distinctive from earlier work done in the related field.

Many jurisdictions fine illegal cartels using penalty guidelines that presume an arbitrary 10% overcharge. This article surveys more than 700 published economic studies and judicial decisions that contain 2,041 quantitative estimates of overcharges of hard-core cartels. The primary findings are: (1) the median average long-run overcharge for all types of cartels over all time periods is 23.0%; (2) the mean average is at least 49%; (3) overcharges reached their zenith in 1891–1945 and have trended downward ever since; (4) 6% of the cartel episodes are zero; (5) median overcharges of international-membership cartels are 38% higher than those of domestic cartels; (6) convicted cartels are on average 19% more effective at raising prices as unpunished cartels; (7) bid-rigging conduct displays 25% lower markups than price-fixing cartels; (8) contemporary cartels targeted by class actions have higher overcharges; and (9) when cartels operate at peak effectiveness, price changes are 60–80% higher than the whole episode. Historical penalty guidelines aimed at optimally deterring cartels are likely to be too low.