In line with the overall Objectives set out in the"Outline Scheme for the Academic Divisions of theChinese Academy of Sciences (CAS) during theNinth Five-year Plan (1996-2000)," CAS has donea good job of the...In line with the overall Objectives set out in the"Outline Scheme for the Academic Divisions of theChinese Academy of Sciences (CAS) during theNinth Five-year Plan (1996-2000)," CAS has donea good job of the supplementary election of CASmembers and the development of the virtues ofscience and fine style of research. In addihon, con-sultation and appraisal, academic exchanges, andthe popularization of science have progressivelybeen focuses of the academic divisions, and manyaccomplishments have been achieved in these areas.展开更多
All intellectual property rights of the articles published in this joumal,including but not limited to reproduction,distribution,translation and adaptation,are exclusively owned by the journal's editorial board.No...All intellectual property rights of the articles published in this joumal,including but not limited to reproduction,distribution,translation and adaptation,are exclusively owned by the journal's editorial board.No individual or institution may use any part of the published content in any form or by any means without the prior written permission of the editorial board.Brief quotations for academic review or research purposes shall clearly indicate the source and comply with international academic norms.Any unauthorized use will be held legally responsible.展开更多
This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal sub...This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal submissions,we compared the performance of six leading GLLMs(Claude 3.5,GPT-4O,Gemini 2.5,Deepseek-R3,Moonshot-V1(kimi),and Qwen-Long)against human editors and reviewers.The results show that,at the editorial screening stage,GLLMs can help editors identify manuscripts with low publication potential,with aggregated model scores closely matching human editorial decisions.At the review stage,comments generated by the union of any three GLLMs from six GLLMs can cover over 61%of issues raised by human reviewers and are rated as superior by management professors.These findings demonstrate that GLLMs can complement human judgment in multi-stage,knowledge-intensive decision processes,improving both the efficiency and quality of academic paper reviews.The study expands the application boundaries of generative Al in management research evaluation and offers practical insights for integrating GLLMs into scholarly review workflows.展开更多
文摘In line with the overall Objectives set out in the"Outline Scheme for the Academic Divisions of theChinese Academy of Sciences (CAS) during theNinth Five-year Plan (1996-2000)," CAS has donea good job of the supplementary election of CASmembers and the development of the virtues ofscience and fine style of research. In addihon, con-sultation and appraisal, academic exchanges, andthe popularization of science have progressivelybeen focuses of the academic divisions, and manyaccomplishments have been achieved in these areas.
文摘All intellectual property rights of the articles published in this joumal,including but not limited to reproduction,distribution,translation and adaptation,are exclusively owned by the journal's editorial board.No individual or institution may use any part of the published content in any form or by any means without the prior written permission of the editorial board.Brief quotations for academic review or research purposes shall clearly indicate the source and comply with international academic norms.Any unauthorized use will be held legally responsible.
基金supported by the National Natural Science Foundation of China[grant number 72372102]for the project'Research on the coordination mechanism of digital transformation strategies between leading firms and follower firms in business ecosystem'.
文摘This study investigates the role of generative large language models(GLLMs)in supporting complex selection and evaluation tasks within the academic paper review process.Using empirical data from management journal submissions,we compared the performance of six leading GLLMs(Claude 3.5,GPT-4O,Gemini 2.5,Deepseek-R3,Moonshot-V1(kimi),and Qwen-Long)against human editors and reviewers.The results show that,at the editorial screening stage,GLLMs can help editors identify manuscripts with low publication potential,with aggregated model scores closely matching human editorial decisions.At the review stage,comments generated by the union of any three GLLMs from six GLLMs can cover over 61%of issues raised by human reviewers and are rated as superior by management professors.These findings demonstrate that GLLMs can complement human judgment in multi-stage,knowledge-intensive decision processes,improving both the efficiency and quality of academic paper reviews.The study expands the application boundaries of generative Al in management research evaluation and offers practical insights for integrating GLLMs into scholarly review workflows.
