Google Gemini 1.5 Flash scores were compared with ChatGPT 4o-mini on evaluations of(a)51 of the author’s journal articles and(b)up to 200 articles in each of 34 field-based Units of Assessment(UoAs)from the UK Resear...Google Gemini 1.5 Flash scores were compared with ChatGPT 4o-mini on evaluations of(a)51 of the author’s journal articles and(b)up to 200 articles in each of 34 field-based Units of Assessment(UoAs)from the UK Research Excellence Framework(REF)2021.From(a),the results suggest that Gemini 1.5 Flash,unlike ChatGPT 4o-mini,may work better when fed with a PDF or article full text,rather than just the title and abstract.From(b),Gemini 1.5 Flash seems to be marginally less able to predict an article’s research quality(using a departmental quality proxy indicator)than ChatGPT 4o-mini,although the differences are small,and both have similar disciplinary variations in this ability.Averaging multiple runs of Gemini 1.5 Flash improves the scores.展开更多
Purpose:Generally,the scientific comparison has been done with the help of the overall impact of scholars.Although it is very easy to compare scholars,but how can we assess the scientific impact of scholars who have d...Purpose:Generally,the scientific comparison has been done with the help of the overall impact of scholars.Although it is very easy to compare scholars,but how can we assess the scientific impact of scholars who have different research careers?It is very obvious,the scholars may gain a high impact if they have more research experience or have spent more time(in terms of research career in a year).Then we cannot compare two scholars who have different research careers.Many bibliometrics indicators address the time-span of scholars.In this series,the h-index sequence and EM/EM’-index sequence have been introduced for assessment and comparison of the scientific impact of scholars.The h-index sequence,EM-index sequence,and EM’-index sequence consider the yearly impact of scholars,and comparison is done by the index value along with their component value.The time-series indicators fail to give a comparative analysis between senior and junior scholars if there is a huge difference in both scholars’research careers.Design/methodology/approach:We have proposed the cumulative index calculation method to appraise the scientific impact of scholars till that age and tested it with 89 scholars data.Findings:The proposed mechanism is implemented and tested on 89 scholars’publication data,providing a clear difference between the scientific impact of two scholars.This also helps in predicting future prominent scholars based on their research impact.Research limitations:This study adopts a simplistic approach by assigning equal credit to all authors,regardless of their individual contributions.Further,the potential impact of career breaks on research productivity is not taken into account.These assumptions may limit the generalizability of our findings Practical implications:The proposed method can be used by respected institutions to compare their scholars impact.Funding agencies can also use it for similar purposes.Originality/value:This research adds to the existing literature by introducing a novel methodology for comparing the scientific impact of scholars.The outcomes of this research have notable implications for the development of more precise and unbiased research assessment frameworks,enabling a more equitable evaluation of scholarly contributions.展开更多
The rapid advancements in Artificial Intelligence(AI),particularly the emergence of large language models(LLMs)such as ChatGPT and DeepSeek,have brought transformative changes to the entire scientific research ecosyst...The rapid advancements in Artificial Intelligence(AI),particularly the emergence of large language models(LLMs)such as ChatGPT and DeepSeek,have brought transformative changes to the entire scientific research ecosystem.As evidenced by the science map of more than 10,000 papers mentioning ChatGPT(see Figure 1),nearly every field of research is actively engaging with and discussing the implications of these technologies.展开更多
Purpose:In this paper,we use author clustering based on journal coupling(i.e.,shared academic journals)to determine researchers who have the same scientific interests and similar conceptual frameworks.The basic assump...Purpose:In this paper,we use author clustering based on journal coupling(i.e.,shared academic journals)to determine researchers who have the same scientific interests and similar conceptual frameworks.The basic assumption is that authors who publish in the same academic journals are more likely to share similar conceptual frameworks and interests than those who never publish in the same venues.Therefore,they are more likely to be part of the same invisible college(i.e.,authors in this subgroup contribute materially to research on the same topic and often publish their work in similar publication venues).Design/methodology/approach:Test in a controlled exercise the grouping of authors based on journal coupling to determine invisible colleges in a research field using a case study of 302 authors who had published in the Information Science and Library Science(IS&LS)category of the Web of Science Core Collection.For each author,we retrieved all the scientific journals in which this author had published his/her articles.We then used the cosine measure to calculate the similarity between authors(both first and second order).Findings:In this paper,using journal coupling of IS&LS authors,we found four main invisible colleges:“Information Systems”,“Business and Information Management”,“Quantitative Information Science”and“Library Science.”The main journals that determine the existence of these invisible colleges were Inform Syst Res,Inform Syst J,J Bus Res,J Knowl Manage,J Informetr,Pro Int Conf Sci Inf,Int J Geogr Inf Sci,J Am Med Inform Assn,and Learn Publ.However,the main journals that demonstrate that IS&LS determine a field were J Am Soc Inf Sci Tec/J Assoc Inf Sci Tech,Scientometrics,Inform Process Manag,and J Inf Sci.Research limitations:The results shown in this article are from a controlled exercise.The analysis performed using journal coupling excludes books,book chapters,and conference papers.In this article,only academic journals were used for the representation of research results.Practical implications:Our results may be of interest to IS&LS scholars.This is because these results provide a new lens for grouping authors,making use of the authors’journal publication profile and journal coupling.Furthermore,extending our approach to the study of the structure of other disciplines would possibly be of interest to historians of science as well as scientometricians.Originality/value:This is a novel approach based on journal coupling to determine authors who are most likely to be part of the same invisible college.展开更多
Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors f...Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors face an ever increasing scarcity of experts willing to act as reviewers.It is not infrequent that reviews diverge,which forces editors to recur to additional reviewers or make a final decision on their own.The purpose of the proposed bibliometric system is to support of editors’accept/reject decisions in such situations.Design/methodology/approach:We analyse nearly two million 2017 publications and their scholarly impact,measured by normalized citations.Based on theory and previous literature,we extrapolated the publication traits of text,byline,and bibliographic references expected to be associated with future citations.We then fitted a regression model with the outcome variable as the scholarly impact of the publication and the independent variables as the above non-scientific traits,controlling for fixed effects at the journal level.Findings:Non-scientific factors explained more than 26%of the paper’s impact,with slight variation across disciplines.On average,OA articles have a 7%greater impact than non-OA articles.A 1%increase in the number of references was associated with an average increase of 0.27%in impact.Higher-impact articles in the reference list,the number of authors and of countries in the byline,the article length,and the average impact of co-authors’past publications all show a positive association with the article’s impact.Female authors,authors from English-speaking countries,and the average age of the article’s references show instead a negative association.Research limitations:The selected non-scientific factors are the only observable and measurable ones to us,but we cannot rule out the presence of significant omitted variables.Using citations as a measure of impact has well-known limitations and overlooks other forms of scholarly influence.Additionally,the large dataset constrained us to one year’s global publications,preventing us from capturing and accounting for time effects.Practical implications:This study provides journal editors with a quantitative model that complements peer reviews,particularly when reviewer evaluations diverge.By incorporating non-scientific factors that significantly predict a paper’s future impact,editors can make more informed decisions,reduce reliance on additional reviewers,and improve the efficiency and fairness of the manuscript selection process.Originality/value:To the best of our knowledge,this study is the first one to specifically address the problem of supporting editors in any field in their decisions on submitted manuscripts with a quantitative model.Previous works have generally investigated the relationship between a few of the above publication traits and their impact or the agreement between peer-review and bibliometric evaluations of publications.展开更多
As the global community strives to achieve the Sustainable Development Goals(SDG),bibliometric analysis offers valuable insights into research trends,impact,and collaboration patterns related to these critical areas.W...As the global community strives to achieve the Sustainable Development Goals(SDG),bibliometric analysis offers valuable insights into research trends,impact,and collaboration patterns related to these critical areas.We are excited to announce a special issue focused on“Fostering SDG-related Research through the Lens of Bibliometrics.”展开更多
The author regrets that the paper titled“Gauging scholars’acceptance of Open Access journals by examining the relationship between perceived quality and citation impact”(DOI:10.2478/jdis-2025-0002),as published,con...The author regrets that the paper titled“Gauging scholars’acceptance of Open Access journals by examining the relationship between perceived quality and citation impact”(DOI:10.2478/jdis-2025-0002),as published,contains errors in four of the table captions.For Tables 12-15,“CABS business journals”should read“CABS economics journals.”The tables do have the correct values for the economics journals,and the findings reported in the text do not need revision.The author apologizes for any inconvenience.展开更多
Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)...Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.展开更多
Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design...Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.展开更多
Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publish...Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publishing practices.Design/methodology/approach:Using data from the Retraction Watch Database and Web of Science(WoS),188 unique retractions involving Romanian authors(2000-2022)were analyzed.The study compared retraction patterns before and after the 2016 reforms,which prioritized the publication of articles in WoS-indexed journals over non-WoS outputs.Findings:The analysis identified two key trends:(1)before the 2016 reforms,retractions predominantly involved non-WoS journals(99 non-WoS retractions to 38 WoS retractions),a trend that reversed post-reform(16 non-WoS to 35 WoS),and(2)while the total number of WoS-indexed retractions increased after the reforms,the retraction rates for WoS articles remained stable.Post-reform reliance on MDPI journals,which have low retraction rates,partially explains this stability.Excluding MDPI publications,retraction rates for articles and reviews increase by 14.91%,aligning with patterns seen elsewhere.Research limitations:The study focuses on retractions involving Romanian authors,limiting its generalizability.Furthermore,reliance on database records may not fully capture all retractions.Practical implications:These findings underscore the need for research policy reforms to consider a broader range of effects,and the need for nuanced interpretations of retraction data,which are influenced by a complex range of factors,including specific publisher practices.Originality/value:This research is the first to investigate the complex relationship between research policy reforms,publisher behavior,and retraction trends.展开更多
Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a g...Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.展开更多
Purpose:This research addresses the challenge of concept drift in AI-enabled software,particularly within autonomous vehicle systems where concept drift in object recognition(like pedestrian detection)can lead to misc...Purpose:This research addresses the challenge of concept drift in AI-enabled software,particularly within autonomous vehicle systems where concept drift in object recognition(like pedestrian detection)can lead to misclassifications and safety risks.This study introduces a proactive framework to detect early signs of domain-specific concept drift by leveraging domain analysis and natural language processing techniques.This method is designed to help maintain the relevance of domain knowledge and prevent potential failures in AI systems due to evolving concept definitions.Design/methodology/approach:The proposed framework integrates natural language processing and image analysis to continuously update and monitor key domain concepts against evolving external data sources,such as social media and news.By identifying terms and features closely associated with core concepts,the system anticipates and flags significant changes.This was tested in the automotive domain on the pedestrian concept,where the framework was evaluated for its capacity to detect shifts in the recognition of pedestrians,particularly during events like Halloween and specific car accidents.Findings:The framework demonstrated an ability to detect shifts in the domain concept of pedestrians,as evidenced by contextual changes around major events.While it successfully identified pedestrian-related drift,the system’s accuracy varied when overlapping with larger social events.The results indicate the model’s potential to foresee relevant shifts before they impact autonomous systems,although further refinement is needed to handle high-impact concurrent events.Research limitations:This study focused on detecting concept drift in the pedestrian domain within autonomous vehicles,with results varying across domains.To assess generalizability,we tested the framework for airplane-related incidents and demonstrated adaptability.However,unpredictable events and data biases from social media and news may obscure domain-specific drifts.Further evaluation across diverse applications is needed to enhance robustness in evolving AI environments.Practical implications:The proactive detection of concept drift has significant implications for AI-driven domains,especially in safety-critical applications like autonomous driving.By identifying early signs of drift,this framework provides actionable insights for AI system updates,potentially reducing misclassification risks and enhancing public safety.Moreover,it enables timely interventions,reducing costly and labor-intensive retraining requirements by focusing only on the relevant aspects of evolving concepts.This method offers a streamlined approach for maintaining AI system performance in environments where domain knowledge rapidly changes.Originality/value:This study contributes a novel domain-agnostic framework that combines natural language processing with image analysis to predict concept drift early.This unique approach,which is focused on real-time data sources,offers an effective and scalable solution for addressing the evolving nature of domain-specific concepts in AI applications.展开更多
Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether ...Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.展开更多
Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive mo...Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.展开更多
Editors Yang Wang,Xi'an Jiaotong University Dongbo Shi,Shanghai Jiaotong University Ye Sun,University College London Zhesi Shen,National Science Library,CAS Topic of the Special Issue What are the top questions to...Editors Yang Wang,Xi'an Jiaotong University Dongbo Shi,Shanghai Jiaotong University Ye Sun,University College London Zhesi Shen,National Science Library,CAS Topic of the Special Issue What are the top questions towards better science and innovation and the required data to answer these questions?展开更多
Purpose:This study investigates whether publication-centric incentive systems,introduced through the National Scientific Accreditation(ASN:Abilitazione Scientifica Nazionale)for professorships in Italy in 2012,contrib...Purpose:This study investigates whether publication-centric incentive systems,introduced through the National Scientific Accreditation(ASN:Abilitazione Scientifica Nazionale)for professorships in Italy in 2012,contribute to adopting“salami publishing”strategies among Italian academics.Design/methodology/approach:A longitudinal bibliometric analysis was conducted on the publication records of over 25,000 Italian science professors to examine changes in publication output and the originality of their work following the implementation of the ASN.Findings:The analysis revealed a significant increase in publication output after the ASN’s introduction,along with a concurrent decline in the originality of publications.However,no evidence was found linking these trends to increased salami slicing practices among the observed researchers.Research limitations:Given the size of our observation field,we propose an innovative indirect approach based on the degree of originality of publications’bibliographies.We know that bibliographic coupling cannot capture salami publications per se,but only topically-related records.On the other hand,controlling for the author’s specialization level in the period,we believe that a higher level of bibliographic coupling in his scientific output can signal a change in his strategy of disseminating the results of his research.The relatively low R-squared values in our models(0.3-0.4)reflect the complexity of the phenomenon under investigation,revealing the presence of unmeasured factors influencing the outcomes,and future research should explore additional variables or alternative models that might account for a greater proportion of the variability.Despite this limitation,the significant predictors identified in our analysis provide valuable insights into the key factors driving the observed outcomes.Practical implications:The results of the study support those who argue that quantitative research assessment frameworks have had very positive effects and should not be dismissed,contrary to the claims of those evoking the occurrence of side effects that do not appear in the empirical analyses.Originality/value:This study provides empirical evidence on the impact of the ASN on publication behaviors in a huge micro-level dataset,contributing to the broader discourse on the effects of quantitative research assessments on academic publishing practices.展开更多
Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relation...Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relations and firm innovation performance,(2)examine the moderating role of executive academic backgrounds,(3)analyze the paths for firms to leverage knowledge spillovers from regional universities to promote firm innovation by their geographic location.Design/methodology/approach:A social network approach is used to construct alumni relationship networks of A-share listed companies in Shanghai and Shenzhen,China.A two-way fixed effects model is used to assess the impact of firms’structural position in executive alumni networks on firms’innovation performance.In addition,the research also delves into the interactions between knowledge spillovers from geographic locations and executives’alumni networks,aiming to elucidate their combined effects on firms’innovation performance.Findings:This paper explores the curvilinear relationship between executive alumni networks’centrality and firm innovation within the Chinese context.It also finds that in the positive effect interval on the right side of the“U-shaped,”the industry with the highest number of occurrences is the high-tech industry.Moreover,it elucidates the moderating influence of executives’academic experience on the alumni networks-innovation nexus,offering a nuanced understanding of these dynamics.Lastly,we provide novel insights into optimizing resource allocation to leverage geographic knowledge spillovers for innovation.Research limitations:The study may not fully represent the broader population of firms,particularly small and medium-sized enterprises(SMEs)or unlisted companies.Future research could expand the sample to include a more diverse range of firms to enhance the generalizability of the findings.Practical implications:Firstly,companies can give due consideration to the alumni resources of executives in their personnel decisions,but they should pay attention to the rational use of resources.Secondly,universities should actively work with companies to promote knowledge transfer and collaboration.Originality/value:The findings help clarify the influence mechanism of firms’innovation performance,providing theoretical support and empirical evidence for firms to drive innovation at the executive alumni relationship network level.展开更多
Purpose:This study explores the combined effects of structural and relational embeddedness within alliance networks on firm innovation.By focusing on the interplay between network structures and relationships,this stu...Purpose:This study explores the combined effects of structural and relational embeddedness within alliance networks on firm innovation.By focusing on the interplay between network structures and relationships,this study provides a nonlinear framework to unravel the complex dynamics between alliance networks and firm innovation performance within the manufacturing industry.Design/methodology/approach:Using social network analysis,this study examines the topological structure of firms’alliance networks.An exploratory approach involving K-Means clustering and decision tree methods is employed to identify heterogeneous network types within the alliance networks.The analysis further explores the nonlinear relationships between network characteristics,including closeness centrality,betweenness centrality,clustering coefficient,and relational attributes,including collaboration intensity and breadth,and their combined influence on firm innovation.Findings:The study identified four distinct heterogeneous network types:dyadic,star,ringlike,and complex networks.Each type reveals unique network characteristics and their impact on innovation performance.Key decision rules were extracted,showing that strong relational embeddedness can hinder innovation in dyadic networks,while a greater distance from the central firm correlates with higher innovation performance in star alliance networks.For ringlike alliance networks,moderate cooperation intensity is beneficial for innovation when the clustering coefficient is not high.In complex alliance networks,the combined effects of cooperation intensity,breadth,and clustering coefficient significantly influence innovation.Research limitations:The research presented in this study,while offering valuable insights into the relationship between alliance networks and firm innovation within the manufacturing sector,is subject to several limitations.A focus on the manufacturing industry may restrict the generalizability of our findings to other sectors,where the dynamics of innovation and collaboration might differ significantly.Additionally,our reliance on patent data,while providing a quantifiable measure of innovation,may overlook other forms of innovation that are equally critical in different contexts,such as service innovations or business model transformations.Practical implications:This research offers significant insights into how firms can leverage both network structure and relational aspects to enhance innovation outcomes.By revealing the nonlinear and complex interactions between network embeddedness dimensions,this study makes a valuable contribution to both theory and practice.This highlights that strategic management of both structural and relational embeddedness can foster superior innovation performance,offering firms a competitive advantage by optimizing their alliance network configurations.Originality/value:This study’s originality lies in its examination of the combined effects of structural and relational network embeddings on innovation performance.By identifying distinct network types and their impact on innovation,this study advances the theoretical understanding of how network characteristics interact to shape firm innovation.It contributes to the literature by offering a novel,multidimensional framework that integrates social network theory and resource-based view,providing new insights for firms to leverage their network positions and relationships for competitive advantage.展开更多
Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Desig...Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Design/methodology/approach:We analyze bibliometric data from three prominent fluids journals-Physics of Fluids,Journal of Fluid Mechanics,and Physical Review Fluids-over the period 1999-2023.The analysis examines the relations among annual fractional journal publication growth,citation growth,and bibliographic metric suppressions.Findings:Our findings reveal that the suppression of impact factor growth is significantly influenced by annual fractional journal publication growth rather than citation growth.All three journals exhibit similar responses to publication growth with minimal scatter,following a consistent functional relation.We also identify narrow,nearly Gaussian distributions for annual fractional journal publication growth.Furthermore,we introduce a new growth-independent dimensionless bibliometric metric,journal urgency,the ratio of annual fractional citation growth to the 4-year running average immediacy index.This metric captures effectively the dependency of citation growth on urgency and reveals consistent distributions across the journals analyzed.Research limitations:The study is limited to three major fluids journals and to the availability of bibliometric data from 1999 to 2023.Future work could extend the analysis to other disciplines and journals.Practical implications:Understanding the relation between publication growth and bibliometric suppressions can inform editorial and strategic decisions in journal management.The proposed journal urgency metric offers a novel tool for assessing and comparing journal performance independent of growth rates.Originality/value:This study introduces a new bibliometric metric-journal urgency-that provides fresh insights into citation dynamics and bibliographic metric behavior.It highlights the critical role of publication growth in shaping journal impact factors and CiteScores,offering a unified framework applicable across multiple journals.展开更多
Purpose:In this paper,we develop a heterogeneous graph network using citation relations between papers and their basic information centered around the“Paper mills”papers under withdrawal observation,and we train gra...Purpose:In this paper,we develop a heterogeneous graph network using citation relations between papers and their basic information centered around the“Paper mills”papers under withdrawal observation,and we train graph neural network models and classifiers on these heterogeneous graphs to classify paper nodes.Design/methodology/approach:Our proposed citation network-based“Paper mills”detection model(PDCN model for short)integrates textual features extracted from the paper titles using the BERT model with structural features obtained from analyzing the heterogeneous graph through the heterogeneous graph attention network model.Subsequently,these features are classified using LGBM classifiers to identify“Paper mills”papers.Findings:On our custom dataset,the PDCN model achieves an accuracy of 81.85%and an F1-score of 80.49%in the“Paper mills”detection task,representing a significant improvement in performance compared to several baseline models.Research limitations:We considered only the title of the article as a text feature and did not obtain features for the entire article.Practical implications:The PDCN model we developed can effectively identify“Paper mills”papers and is suitable for the automated detection of“Paper mills”during the review process.Originality/value:We incorporated both text and citation detection into the“Paper mills”identification process.Additionally,the PDCN model offers a basis for judgment and scientific guidance in recognizing“Paper mills”papers.展开更多
文摘Google Gemini 1.5 Flash scores were compared with ChatGPT 4o-mini on evaluations of(a)51 of the author’s journal articles and(b)up to 200 articles in each of 34 field-based Units of Assessment(UoAs)from the UK Research Excellence Framework(REF)2021.From(a),the results suggest that Gemini 1.5 Flash,unlike ChatGPT 4o-mini,may work better when fed with a PDF or article full text,rather than just the title and abstract.From(b),Gemini 1.5 Flash seems to be marginally less able to predict an article’s research quality(using a departmental quality proxy indicator)than ChatGPT 4o-mini,although the differences are small,and both have similar disciplinary variations in this ability.Averaging multiple runs of Gemini 1.5 Flash improves the scores.
文摘Purpose:Generally,the scientific comparison has been done with the help of the overall impact of scholars.Although it is very easy to compare scholars,but how can we assess the scientific impact of scholars who have different research careers?It is very obvious,the scholars may gain a high impact if they have more research experience or have spent more time(in terms of research career in a year).Then we cannot compare two scholars who have different research careers.Many bibliometrics indicators address the time-span of scholars.In this series,the h-index sequence and EM/EM’-index sequence have been introduced for assessment and comparison of the scientific impact of scholars.The h-index sequence,EM-index sequence,and EM’-index sequence consider the yearly impact of scholars,and comparison is done by the index value along with their component value.The time-series indicators fail to give a comparative analysis between senior and junior scholars if there is a huge difference in both scholars’research careers.Design/methodology/approach:We have proposed the cumulative index calculation method to appraise the scientific impact of scholars till that age and tested it with 89 scholars data.Findings:The proposed mechanism is implemented and tested on 89 scholars’publication data,providing a clear difference between the scientific impact of two scholars.This also helps in predicting future prominent scholars based on their research impact.Research limitations:This study adopts a simplistic approach by assigning equal credit to all authors,regardless of their individual contributions.Further,the potential impact of career breaks on research productivity is not taken into account.These assumptions may limit the generalizability of our findings Practical implications:The proposed method can be used by respected institutions to compare their scholars impact.Funding agencies can also use it for similar purposes.Originality/value:This research adds to the existing literature by introducing a novel methodology for comparing the scientific impact of scholars.The outcomes of this research have notable implications for the development of more precise and unbiased research assessment frameworks,enabling a more equitable evaluation of scholarly contributions.
文摘The rapid advancements in Artificial Intelligence(AI),particularly the emergence of large language models(LLMs)such as ChatGPT and DeepSeek,have brought transformative changes to the entire scientific research ecosystem.As evidenced by the science map of more than 10,000 papers mentioning ChatGPT(see Figure 1),nearly every field of research is actively engaging with and discussing the implications of these technologies.
文摘Purpose:In this paper,we use author clustering based on journal coupling(i.e.,shared academic journals)to determine researchers who have the same scientific interests and similar conceptual frameworks.The basic assumption is that authors who publish in the same academic journals are more likely to share similar conceptual frameworks and interests than those who never publish in the same venues.Therefore,they are more likely to be part of the same invisible college(i.e.,authors in this subgroup contribute materially to research on the same topic and often publish their work in similar publication venues).Design/methodology/approach:Test in a controlled exercise the grouping of authors based on journal coupling to determine invisible colleges in a research field using a case study of 302 authors who had published in the Information Science and Library Science(IS&LS)category of the Web of Science Core Collection.For each author,we retrieved all the scientific journals in which this author had published his/her articles.We then used the cosine measure to calculate the similarity between authors(both first and second order).Findings:In this paper,using journal coupling of IS&LS authors,we found four main invisible colleges:“Information Systems”,“Business and Information Management”,“Quantitative Information Science”and“Library Science.”The main journals that determine the existence of these invisible colleges were Inform Syst Res,Inform Syst J,J Bus Res,J Knowl Manage,J Informetr,Pro Int Conf Sci Inf,Int J Geogr Inf Sci,J Am Med Inform Assn,and Learn Publ.However,the main journals that demonstrate that IS&LS determine a field were J Am Soc Inf Sci Tec/J Assoc Inf Sci Tech,Scientometrics,Inform Process Manag,and J Inf Sci.Research limitations:The results shown in this article are from a controlled exercise.The analysis performed using journal coupling excludes books,book chapters,and conference papers.In this article,only academic journals were used for the representation of research results.Practical implications:Our results may be of interest to IS&LS scholars.This is because these results provide a new lens for grouping authors,making use of the authors’journal publication profile and journal coupling.Furthermore,extending our approach to the study of the structure of other disciplines would possibly be of interest to historians of science as well as scientometricians.Originality/value:This is a novel approach based on journal coupling to determine authors who are most likely to be part of the same invisible college.
文摘Purpose:Scholars face an unprecedented ever increasing demand for acting as reviewers for journals,recruitment and promotion committees,granting agencies,and research assessment agencies.Consequently,journal editors face an ever increasing scarcity of experts willing to act as reviewers.It is not infrequent that reviews diverge,which forces editors to recur to additional reviewers or make a final decision on their own.The purpose of the proposed bibliometric system is to support of editors’accept/reject decisions in such situations.Design/methodology/approach:We analyse nearly two million 2017 publications and their scholarly impact,measured by normalized citations.Based on theory and previous literature,we extrapolated the publication traits of text,byline,and bibliographic references expected to be associated with future citations.We then fitted a regression model with the outcome variable as the scholarly impact of the publication and the independent variables as the above non-scientific traits,controlling for fixed effects at the journal level.Findings:Non-scientific factors explained more than 26%of the paper’s impact,with slight variation across disciplines.On average,OA articles have a 7%greater impact than non-OA articles.A 1%increase in the number of references was associated with an average increase of 0.27%in impact.Higher-impact articles in the reference list,the number of authors and of countries in the byline,the article length,and the average impact of co-authors’past publications all show a positive association with the article’s impact.Female authors,authors from English-speaking countries,and the average age of the article’s references show instead a negative association.Research limitations:The selected non-scientific factors are the only observable and measurable ones to us,but we cannot rule out the presence of significant omitted variables.Using citations as a measure of impact has well-known limitations and overlooks other forms of scholarly influence.Additionally,the large dataset constrained us to one year’s global publications,preventing us from capturing and accounting for time effects.Practical implications:This study provides journal editors with a quantitative model that complements peer reviews,particularly when reviewer evaluations diverge.By incorporating non-scientific factors that significantly predict a paper’s future impact,editors can make more informed decisions,reduce reliance on additional reviewers,and improve the efficiency and fairness of the manuscript selection process.Originality/value:To the best of our knowledge,this study is the first one to specifically address the problem of supporting editors in any field in their decisions on submitted manuscripts with a quantitative model.Previous works have generally investigated the relationship between a few of the above publication traits and their impact or the agreement between peer-review and bibliometric evaluations of publications.
文摘As the global community strives to achieve the Sustainable Development Goals(SDG),bibliometric analysis offers valuable insights into research trends,impact,and collaboration patterns related to these critical areas.We are excited to announce a special issue focused on“Fostering SDG-related Research through the Lens of Bibliometrics.”
文摘The author regrets that the paper titled“Gauging scholars’acceptance of Open Access journals by examining the relationship between perceived quality and citation impact”(DOI:10.2478/jdis-2025-0002),as published,contains errors in four of the table captions.For Tables 12-15,“CABS business journals”should read“CABS economics journals.”The tables do have the correct values for the economics journals,and the findings reported in the text do not need revision.The author apologizes for any inconvenience.
文摘Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.
基金supported by the Sapienza Universitàdi Roma Sapienza Awards no.6H15XNFS.
文摘Purpose:We aimed to measure the variation in researchers’knowledge and attitudes towards bibliometric indicators.The focus is on mapping the heterogeneity of this metric-wiseness within and between disciplines.Design/methodology/approach:An exploratory survey is administered to researchers at the Sapienza University of Rome,one of Europe’s oldest and largest generalist universities.To measure metric-wiseness,we use attitude statements that are evaluated by a 5-point Likert scale.Moreover,we analyze documents of recent initiatives on assessment reform to shed light on how researchers’heterogeneous attitudes regarding and knowledge of bibliometric indicators are taken into account.Findings:We found great heterogeneity in researchers’metric-wiseness across scientific disciplines.In addition,within each discipline,we observed both supporters and critics of bibliometric indicators.From the document analysis,we found no reference to individual heterogeneity concerning researchers’metric wiseness.Research limitations:We used a self-selected sample of researchers from one Italian university as an exploratory case.Further research is needed to check the generalizability of our findings.Practical implications:To gain sufficient support for research evaluation practices,it is key to consider researchers’diverse attitudes towards indicators.Originality/value:We contribute to the current debate on reforming research assessment by providing a novel empirical measurement of researchers’knowledge and attitudes towards bibliometric indicators and discussing the importance of the obtained results for improving current research evaluation systems.
文摘Purpose:This study examines the impact of research policy changes on scientific retractions of publications authored by Romanian authors,focusing on national trends and the interplay between policy reforms and publishing practices.Design/methodology/approach:Using data from the Retraction Watch Database and Web of Science(WoS),188 unique retractions involving Romanian authors(2000-2022)were analyzed.The study compared retraction patterns before and after the 2016 reforms,which prioritized the publication of articles in WoS-indexed journals over non-WoS outputs.Findings:The analysis identified two key trends:(1)before the 2016 reforms,retractions predominantly involved non-WoS journals(99 non-WoS retractions to 38 WoS retractions),a trend that reversed post-reform(16 non-WoS to 35 WoS),and(2)while the total number of WoS-indexed retractions increased after the reforms,the retraction rates for WoS articles remained stable.Post-reform reliance on MDPI journals,which have low retraction rates,partially explains this stability.Excluding MDPI publications,retraction rates for articles and reviews increase by 14.91%,aligning with patterns seen elsewhere.Research limitations:The study focuses on retractions involving Romanian authors,limiting its generalizability.Furthermore,reliance on database records may not fully capture all retractions.Practical implications:These findings underscore the need for research policy reforms to consider a broader range of effects,and the need for nuanced interpretations of retraction data,which are influenced by a complex range of factors,including specific publisher practices.Originality/value:This research is the first to investigate the complex relationship between research policy reforms,publisher behavior,and retraction trends.
基金approved by our institutional Research Ethics Committee(HREC Approval Number H13554).
文摘Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.
基金supported by U.S.Office of Naval Research(ONR)Grant number G2A62826.
文摘Purpose:This research addresses the challenge of concept drift in AI-enabled software,particularly within autonomous vehicle systems where concept drift in object recognition(like pedestrian detection)can lead to misclassifications and safety risks.This study introduces a proactive framework to detect early signs of domain-specific concept drift by leveraging domain analysis and natural language processing techniques.This method is designed to help maintain the relevance of domain knowledge and prevent potential failures in AI systems due to evolving concept definitions.Design/methodology/approach:The proposed framework integrates natural language processing and image analysis to continuously update and monitor key domain concepts against evolving external data sources,such as social media and news.By identifying terms and features closely associated with core concepts,the system anticipates and flags significant changes.This was tested in the automotive domain on the pedestrian concept,where the framework was evaluated for its capacity to detect shifts in the recognition of pedestrians,particularly during events like Halloween and specific car accidents.Findings:The framework demonstrated an ability to detect shifts in the domain concept of pedestrians,as evidenced by contextual changes around major events.While it successfully identified pedestrian-related drift,the system’s accuracy varied when overlapping with larger social events.The results indicate the model’s potential to foresee relevant shifts before they impact autonomous systems,although further refinement is needed to handle high-impact concurrent events.Research limitations:This study focused on detecting concept drift in the pedestrian domain within autonomous vehicles,with results varying across domains.To assess generalizability,we tested the framework for airplane-related incidents and demonstrated adaptability.However,unpredictable events and data biases from social media and news may obscure domain-specific drifts.Further evaluation across diverse applications is needed to enhance robustness in evolving AI environments.Practical implications:The proactive detection of concept drift has significant implications for AI-driven domains,especially in safety-critical applications like autonomous driving.By identifying early signs of drift,this framework provides actionable insights for AI system updates,potentially reducing misclassification risks and enhancing public safety.Moreover,it enables timely interventions,reducing costly and labor-intensive retraining requirements by focusing only on the relevant aspects of evolving concepts.This method offers a streamlined approach for maintaining AI system performance in environments where domain knowledge rapidly changes.Originality/value:This study contributes a novel domain-agnostic framework that combines natural language processing with image analysis to predict concept drift early.This unique approach,which is focused on real-time data sources,offers an effective and scalable solution for addressing the evolving nature of domain-specific concepts in AI applications.
文摘Purpose:Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises,appointments and promotion.It is therefore important to investigate whether Large Language Models(LLMs)can play a role in this process.Design/methodology/approach:This article assesses which ChatGPT inputs(full text without tables,figures,and references;title and abstract;title only)produce better quality score estimates,and the extent to which scores are affected by ChatGPT models and system prompts.Findings:The optimal input is the article title and abstract,with average ChatGPT scores based on these(30 iterations on a dataset of 51 papers)correlating at 0.67 with human scores,the highest ever reported.ChatGPT 4o is slightly better than 3.5-turbo(0.66),and 4o-mini(0.66).Research limitations:The data is a convenience sample of the work of a single author,it only includes one field,and the scores are self-evaluations.Practical implications:The results suggest that article full texts might confuse LLM research quality evaluations,even though complex system instructions for the task are more effective than simple ones.Thus,whilst abstracts contain insufficient information for a thorough assessment of rigour,they may contain strong pointers about originality and significance.Finally,linear regression can be used to convert the model scores into the human scale scores,which is 31%more accurate than guessing.Originality/value:This is the first systematic comparison of the impact of different prompts,parameters and inputs for ChatGPT research quality evaluations.
文摘Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.
文摘Editors Yang Wang,Xi'an Jiaotong University Dongbo Shi,Shanghai Jiaotong University Ye Sun,University College London Zhesi Shen,National Science Library,CAS Topic of the Special Issue What are the top questions towards better science and innovation and the required data to answer these questions?
文摘Purpose:This study investigates whether publication-centric incentive systems,introduced through the National Scientific Accreditation(ASN:Abilitazione Scientifica Nazionale)for professorships in Italy in 2012,contribute to adopting“salami publishing”strategies among Italian academics.Design/methodology/approach:A longitudinal bibliometric analysis was conducted on the publication records of over 25,000 Italian science professors to examine changes in publication output and the originality of their work following the implementation of the ASN.Findings:The analysis revealed a significant increase in publication output after the ASN’s introduction,along with a concurrent decline in the originality of publications.However,no evidence was found linking these trends to increased salami slicing practices among the observed researchers.Research limitations:Given the size of our observation field,we propose an innovative indirect approach based on the degree of originality of publications’bibliographies.We know that bibliographic coupling cannot capture salami publications per se,but only topically-related records.On the other hand,controlling for the author’s specialization level in the period,we believe that a higher level of bibliographic coupling in his scientific output can signal a change in his strategy of disseminating the results of his research.The relatively low R-squared values in our models(0.3-0.4)reflect the complexity of the phenomenon under investigation,revealing the presence of unmeasured factors influencing the outcomes,and future research should explore additional variables or alternative models that might account for a greater proportion of the variability.Despite this limitation,the significant predictors identified in our analysis provide valuable insights into the key factors driving the observed outcomes.Practical implications:The results of the study support those who argue that quantitative research assessment frameworks have had very positive effects and should not be dismissed,contrary to the claims of those evoking the occurrence of side effects that do not appear in the empirical analyses.Originality/value:This study provides empirical evidence on the impact of the ASN on publication behaviors in a huge micro-level dataset,contributing to the broader discourse on the effects of quantitative research assessments on academic publishing practices.
基金supported in part by the National Natural Science Foundation of China under Grant No.72264036,in part by the West Light Foundation of The Chinese Academy of Sciences under Grant No.2020-XBQNXZ-020Xinjiang University of Finance and Economics Postgraduate Innovation Project XJUFE2024K036.
文摘Purpose:Currently,different research conclusions exist about the relationship between relational capital and corporate innovation.The research aims to(1)reveal the actual relationship between executive alumni relations and firm innovation performance,(2)examine the moderating role of executive academic backgrounds,(3)analyze the paths for firms to leverage knowledge spillovers from regional universities to promote firm innovation by their geographic location.Design/methodology/approach:A social network approach is used to construct alumni relationship networks of A-share listed companies in Shanghai and Shenzhen,China.A two-way fixed effects model is used to assess the impact of firms’structural position in executive alumni networks on firms’innovation performance.In addition,the research also delves into the interactions between knowledge spillovers from geographic locations and executives’alumni networks,aiming to elucidate their combined effects on firms’innovation performance.Findings:This paper explores the curvilinear relationship between executive alumni networks’centrality and firm innovation within the Chinese context.It also finds that in the positive effect interval on the right side of the“U-shaped,”the industry with the highest number of occurrences is the high-tech industry.Moreover,it elucidates the moderating influence of executives’academic experience on the alumni networks-innovation nexus,offering a nuanced understanding of these dynamics.Lastly,we provide novel insights into optimizing resource allocation to leverage geographic knowledge spillovers for innovation.Research limitations:The study may not fully represent the broader population of firms,particularly small and medium-sized enterprises(SMEs)or unlisted companies.Future research could expand the sample to include a more diverse range of firms to enhance the generalizability of the findings.Practical implications:Firstly,companies can give due consideration to the alumni resources of executives in their personnel decisions,but they should pay attention to the rational use of resources.Secondly,universities should actively work with companies to promote knowledge transfer and collaboration.Originality/value:The findings help clarify the influence mechanism of firms’innovation performance,providing theoretical support and empirical evidence for firms to drive innovation at the executive alumni relationship network level.
基金supported by the National Social Science Fund of China(No.22FGLB035)Fujian Provincial Federation of Social Sciences(No.FJ2023B109).
文摘Purpose:This study explores the combined effects of structural and relational embeddedness within alliance networks on firm innovation.By focusing on the interplay between network structures and relationships,this study provides a nonlinear framework to unravel the complex dynamics between alliance networks and firm innovation performance within the manufacturing industry.Design/methodology/approach:Using social network analysis,this study examines the topological structure of firms’alliance networks.An exploratory approach involving K-Means clustering and decision tree methods is employed to identify heterogeneous network types within the alliance networks.The analysis further explores the nonlinear relationships between network characteristics,including closeness centrality,betweenness centrality,clustering coefficient,and relational attributes,including collaboration intensity and breadth,and their combined influence on firm innovation.Findings:The study identified four distinct heterogeneous network types:dyadic,star,ringlike,and complex networks.Each type reveals unique network characteristics and their impact on innovation performance.Key decision rules were extracted,showing that strong relational embeddedness can hinder innovation in dyadic networks,while a greater distance from the central firm correlates with higher innovation performance in star alliance networks.For ringlike alliance networks,moderate cooperation intensity is beneficial for innovation when the clustering coefficient is not high.In complex alliance networks,the combined effects of cooperation intensity,breadth,and clustering coefficient significantly influence innovation.Research limitations:The research presented in this study,while offering valuable insights into the relationship between alliance networks and firm innovation within the manufacturing sector,is subject to several limitations.A focus on the manufacturing industry may restrict the generalizability of our findings to other sectors,where the dynamics of innovation and collaboration might differ significantly.Additionally,our reliance on patent data,while providing a quantifiable measure of innovation,may overlook other forms of innovation that are equally critical in different contexts,such as service innovations or business model transformations.Practical implications:This research offers significant insights into how firms can leverage both network structure and relational aspects to enhance innovation outcomes.By revealing the nonlinear and complex interactions between network embeddedness dimensions,this study makes a valuable contribution to both theory and practice.This highlights that strategic management of both structural and relational embeddedness can foster superior innovation performance,offering firms a competitive advantage by optimizing their alliance network configurations.Originality/value:This study’s originality lies in its examination of the combined effects of structural and relational network embeddings on innovation performance.By identifying distinct network types and their impact on innovation,this study advances the theoretical understanding of how network characteristics interact to shape firm innovation.It contributes to the literature by offering a novel,multidimensional framework that integrates social network theory and resource-based view,providing new insights for firms to leverage their network positions and relationships for competitive advantage.
文摘Purpose:This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics,focusing on the interplay between journal publication growth and citation dynamics.Design/methodology/approach:We analyze bibliometric data from three prominent fluids journals-Physics of Fluids,Journal of Fluid Mechanics,and Physical Review Fluids-over the period 1999-2023.The analysis examines the relations among annual fractional journal publication growth,citation growth,and bibliographic metric suppressions.Findings:Our findings reveal that the suppression of impact factor growth is significantly influenced by annual fractional journal publication growth rather than citation growth.All three journals exhibit similar responses to publication growth with minimal scatter,following a consistent functional relation.We also identify narrow,nearly Gaussian distributions for annual fractional journal publication growth.Furthermore,we introduce a new growth-independent dimensionless bibliometric metric,journal urgency,the ratio of annual fractional citation growth to the 4-year running average immediacy index.This metric captures effectively the dependency of citation growth on urgency and reveals consistent distributions across the journals analyzed.Research limitations:The study is limited to three major fluids journals and to the availability of bibliometric data from 1999 to 2023.Future work could extend the analysis to other disciplines and journals.Practical implications:Understanding the relation between publication growth and bibliometric suppressions can inform editorial and strategic decisions in journal management.The proposed journal urgency metric offers a novel tool for assessing and comparing journal performance independent of growth rates.Originality/value:This study introduces a new bibliometric metric-journal urgency-that provides fresh insights into citation dynamics and bibliographic metric behavior.It highlights the critical role of publication growth in shaping journal impact factors and CiteScores,offering a unified framework applicable across multiple journals.
基金supported by the National Science Foundation of China(Grant No.62176026)Project of“Image Inspection Basic Data and Platform Construction”,Department of Science and Technology Supervision and Integrity Building,Ministry of Science and Technology(Grant No.GXCZ-D-21070106)ISTIC-Taylor&Francis Group Academic Frontier Watch Joint Laboratory Open Grant.
文摘Purpose:In this paper,we develop a heterogeneous graph network using citation relations between papers and their basic information centered around the“Paper mills”papers under withdrawal observation,and we train graph neural network models and classifiers on these heterogeneous graphs to classify paper nodes.Design/methodology/approach:Our proposed citation network-based“Paper mills”detection model(PDCN model for short)integrates textual features extracted from the paper titles using the BERT model with structural features obtained from analyzing the heterogeneous graph through the heterogeneous graph attention network model.Subsequently,these features are classified using LGBM classifiers to identify“Paper mills”papers.Findings:On our custom dataset,the PDCN model achieves an accuracy of 81.85%and an F1-score of 80.49%in the“Paper mills”detection task,representing a significant improvement in performance compared to several baseline models.Research limitations:We considered only the title of the article as a text feature and did not obtain features for the entire article.Practical implications:The PDCN model we developed can effectively identify“Paper mills”papers and is suitable for the automated detection of“Paper mills”during the review process.Originality/value:We incorporated both text and citation detection into the“Paper mills”identification process.Additionally,the PDCN model offers a basis for judgment and scientific guidance in recognizing“Paper mills”papers.
