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The ranking of universities and other research-intensive institutions in global ranking systems is based on numerous indicators, including number of articles with external collaboration, number of articles with international collaboration, number of articles with industry collaboration as well as co-patents with industry. The purpose of this paper is to examine university–industry research collaboration in Ghana, with the aim of exploring the relationship between the research output collaborations in the top four universities in Ghana and industry across different geographical scales.

This study’s data was obtained from the SciVal database, which drawn its data from the Scopus bibliographic and citation database. The bibliographic and citation data were extracted using a search of the publications affiliated to the University of Ghana, for the period 2011–2020.

Key findings demonstrate a constant rise in the number of research publications by the selected universities over time. Research collaboration intensity in the selected universities in terms of co-authored publications was higher as compared to single-authored publications. University–industry research co-authorships were, however, lower when compared to university–university research co-authorships. The university–industry research co-authorships occurred mostly with Europe, Asia-Pacific and North American-based institutions as opposed to African-based institutions. In Ghana, four industry-based institutions were engaged in intensive research with the selected universities.

This study demonstrates that, for each selected university, it is possible to measure the performance of individual universities in both intra-regional and international collaboration. Such results may be useful in informing policy as well as merit-based public funding of universities in Ghana.

This article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

In 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.

Compared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

On the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.

Improving and assuring the quality of higher education has become a key element of policy agendas worldwide. To this end, a complete accountability system has been developed through various evaluation procedures. Specifically, this study analyzes the perceptions of university teaching staff on the impact of performance appraisal systems on their professional activity, health and personal lives.

The study adopted a nonexperimental descriptive and causal-comparative design using a questionnaire that was completed by a sample of 2,183 Spanish teachers. The data obtained were analyzed using descriptive statistics and comparisons of differences.

The results show that, according to teachers, the evaluation criteria undermine the quality of their work by encouraging them to neglect teaching, increase scientific production and engage in unethical research practices. Their views also emphasize the social and health-related consequences of an increasingly competitive work climate, including increased stress levels. Finally, significant differences are observed regarding gender, professional category and academic discipline, with women, junior faculty and social sciences teachers expressing particularly strong views.

The originality of this study lies in the application of a method that contributes to the international debate through a national perspective (Spain) that has so far received little attention.

The purpose of this study is to identify papers that have produced the most significant impact on research on strategic alliances in the biotechnology industry. The authors attempt to illustrate the thematic evolution of its intellectual structure through 616 papers published between 1992 and 2021.

The present research methodology relies on three distinct techniques, implemented using SciMat software: (1) bibliometric techniques, (2) scientific map analysis and (3) content analysis of research documents from the Web of Science (WoS). In this manner, the authors analyse the intellectual structure of the field of strategic alliances in the biotechnology industry, tracking its evolution over a period of three decades.

The study emphasises the relevance of “innovation” as a key theme and identifies several potential areas for future research, which could serve as a foundation for further investigations.

This study represents a novel contribution to the literature as it is the first to use the SciMat tool to analyse strategic alliances in the biotechnology industry. This research reveals that while strategic alliances have been assessed extensively across various industries, some topics, such as the types and formation of alliances, have not been specifically studied in the biotechnology industry. These areas as well as the barriers and variables influencing the formation of alliances offer promising avenues for future research in this field.

本研究旨在確定對關於生物科技產業內的策略聯盟的探究產生極其顯著影響的學術論文。我們擬透過探討於1992年至2021年期間發表的616篇學術論文，去闡明策略聯盟的知識結構的主題演變。

研究依賴三個不同的技術來進行，並以SciMat 可視化軟件來做具體實施的工作。這三個技術為、(一) 文獻計量技術;(二) 科學製圖分析;和 (三) 就取自 Web of Science 的學術文章而進行的內容分析。我們採用這研究法，對在生物科技產業內的策略聯盟的知識結構進行分析，俾能對有關的知識結構的主題演變進行一個涵蓋三十載的跟蹤調查。

研究強調了創新，並視之為主要的主題的重要相關概念;研究亦確定了一些今後可供研究的潛在領域，這或許會成為進一步研究的基礎。

由於本研究是首個研究、使用SciMat這工具去分析在生物科技產業內的策略聯盟，故就有關的文獻而言，它給予新穎的貢獻。研究結果顯示，雖然策略聯盟已在各個不同的產業裡被廣泛評價，但在生物科技產業裡，一些如聯盟的種類和形成方式等的課題仍未得到適切的研究。這些課題，以及影響著聯盟的形成的障礙和變數，會為這領域內今後的學術研究、提供光明的途徑。

This study aims to critically review the research on food eco-labels to identify research gaps and recommend future research directions in business and management.

A hybrid integrated review combines bibliometric analysis with an in-depth framework-based study of theory–context–characteristics–methodology (TCCM) and reviews quality research published over 21 years between 2002 and 2022.

We identify key research themes and the knowledge structure of food eco-label research. Future researchers should explore food eco-label dynamics and phenomena in areas related to consumer behaviour, information, consumer knowledge, environmental concerns, trust, packaging and willingness-to-pay as antecedent factors.

This review contributes to the business and management literature by quantifying existing research and consolidating its evolution. The articles were sourced from the established Web of Science (WoS) database. Other databases should be included in future reviews. We also focus on research published in business and management. Further studies could include research beyond such specialised domains.

Consumers need more information on the objectives and meaning of food eco-labels. The dissemination of knowledge on eco-labels, as well as effective communication and information on eco-labels, are relevant to future research issues.

The knowledge derived from this research holds significant potential in shaping policies and devising tools aimed at reducing the carbon footprint linked to food production and consumption. Considering the substantial impact of these activities on our planet’s carbon footprint, addressing food security and sustainability emerges as a crucial concern for humanity. Recognising the importance of eco-label communication and information becomes particularly pertinent for future generations, who stand to bear the most substantial impact of climate change and sustainable development. These generations are also more inclined toward embracing and implementing sustainable practices.

There are no comprehensive, integrated reviews exploring the methods, variables and constructs used in studies on food eco-labels based on all articles published in WoS journals in the business and management domains. This is the first comprehensive literature review using a hybrid approach (bibliometric review with TCCM framework) in the field of food eco-label research.

本研究擬以批判性的態度,審閱過去有關食物生態標籤的研究,以能確認研究缺口,並於商業和管理的範疇裡,建議今後的研究方向。

這是一個混合綜合審閱研究。研究結合了文獻計量分析方法和理論 -背景 - 特徵 - 方法論 (TCCM) 框架; 研究人員審閱於2002年與2022年間二十一年裡出版的高水平學術研究。

我們確認了關於食物生態標籤的研究裡主要的研究主題和知識結構。研究人員和學者今後應致力關於消費行為、資訊、顧客知識、環境關注、信任、包裝和支付意願等議題的研究範疇,以能在這些範疇內,把食物生態標籤的變革動力和現象,作為是先前因素進行探索。

本研究確定了現存有關的研究的數量,並幫助鞏固了這類研究的發展,就此,對商業和管理文獻作出了貢獻。審閱的學術論文均來自被認可的 Web of Science 資料庫。今後的研究應涵蓋其它資料庫; 而且,我們的焦點是放在關於商業和管裡的文獻上; 研究人員和學者今後或許也應致力於其它研究範疇。

消費者需要更多關於食物生態標籤目標和意義的資訊; 因此,今後的研究須關注生態標籤知識的傳播,以及生態標籤的有效溝通和資訊。

根據於 Web of Science 出版、以及在商業和管理領域內的學術論文,似乎沒有全面的或綜合的審閱,去探索有關食物生態標籤研究內採用的研究方法、變數和構築。本研究為在食物生態標籤研究領域裡,首個使用混合方式 (結合文獻計量分析方法和理論 -背景 - 特徵 - 方法論 (TCCM) 框架)的全面文獻審閱。

The key aim of this study is to highlight current financial technology (FinTech) trends by conducting a bibliometric review of literature derived from the Scopus database.

A bibliometric analysis was conducted on articles gathered from the Scopus database. Microsoft Excel was used to perform the frequency analysis, VOSviewer for visualising the data, and Harzing’s Publish or Perish for the metrics citation.

According to this investigation, research into FinTech has been consistently increasing since 2008. The results indicate that the most active publisher of FinTech literature is Bina Nusantara University in Indonesia. In terms of country of publication, China is identified as the most active. The most cited author is Buckley, R.P., with Rabbani, M.R., having the most publications. It was also identified that FinTech researches come under three primary domains namely business management, computer science and economics.

The primary limitation of this current study is that it only relied on one data source, i.e. Scopus. Implications wise, researchers and practitioners can gain a deeper understanding of FinTech from this study, which also describes the trend in related publications on the concept. Future studies could significantly benefit from the findings of the present paper.

The outcomes of this study can assist researchers in better comprehending and summarising the key drivers of FinTech. In addition, the findings can help new researchers identify the starting point for their research on FinTech.

As far as the authors are aware, this is the first study that reviews FinTech publications derived from Scopus from 2008 to 2022. Hence, it is a pioneering study into FinTech bibliometric analysis, providing an understanding of the structural knowledge by reviewing the timeline of academic progression in FinTech.

This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.

The study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.

The results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.

The current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.

Going beyond the traditional approach of formal and informal institutions as antecedents of entrepreneurship (directly) and development (indirectly), this paper seeks to explore knowledge institutions as a necessary input for entrepreneurship and the development of societies.

Institutional economics lenses are utilized to observe other factors (e.g. the number of R&D staff and researchers from the public sector) that involve laws and socialization processes, which at the same time create knowledge useful for entrepreneurs and society. These ideas are tested through a sample of 281 observations from 17 autonomous communities and two autonomous cities in Spain. The information coming from the Global Entrepreneurship Monitor (GEM), Ministry of Economics, Industry, and Competitiveness, and INE (Instituto Nacional de Estadística), was analyzed through 3SLS, which is useful for a simultaneous equation strategy.

Knowledge institutions such as the number of R&D staff and researchers from the public sector are found positively associated with entrepreneurship, which is a factor directly and positively linked to economic development across Spanish regions.

The findings help the operationalization of other institutions considered in institutional economics theory and its application to entrepreneurship research. Moreover, the results bring new insights into the knowledge spillover theory of entrepreneurship in the public sector, in which the institutional analysis is implicit.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

Understanding China's carbon dioxide (CO2) emission status is crucial for getting Carbon Neutrality status. The purpose of the paper is to calculate two possible scenarios for CO2 emission distribution and calculated input-output flows of CO2 emissions for every 31 China provinces for 2012, 2015 and 2017 years.

In this study using the input and output (IO) table's data for the selected years, the authors found the volume of CO2 emissions per one Yuan of revenue for the industry in 2012 and the coefficient of emission reduction compared to 2012.

Results show that in the industries with a huge volume of CO2 emissions, such as “Mining and washing of coal”, the authors cannot observe the reduction processes for years. Industries where emissions are being reduced are “Processing of petroleum, coking, nuclear fuel”, “Production and distribution of electric power and heat power”, “Agriculture, Forestry, Animal Husbandry and Fishery”. For the “construction” industry the situation with emissions did not change.

“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of CO2 emissions, but they do not take products characterized by significant emissions from other provinces. Shandong produces a lot of emissions and consumes many of products characterized by large emissions from other provinces. However, Shandong showed a reduction in CO2 emissions from 2012 to 2017.