管理学最新文献

{"title":"When digital platforms meet tradition: Phygital innovation in the cultural heritage","authors":"Danilo Pesce ,&nbsp;Claudia Franzè","doi":"10.1016/j.jengtecman.2025.101896","DOIUrl":"10.1016/j.jengtecman.2025.101896","url":null,"abstract":"<div><div>The digitalization of cultural and creative industries has often followed a path of convergence between physical and digital artefacts, leading to the rise of digital platforms that reshape value chains. However, the cultural heritage sector has undergone a different form of digital transformation. Digital platforms in this field create a “phygital” experience that blends tradition with innovation. This study examines the role of digital platforms in fostering social and economic development in the cultural heritage sector, focusing on Google Arts &amp; Culture, launched by Google in 2011. Through a longitudinal case study, we explore how digital platforms create value for multiple stakeholders—museums, users, and the platform itself—by enhancing efficiency, complementarities, novelty, and lock-in mechanisms. Our findings indicate that digital platforms introduce a more dynamic and complex ecosystem that drives growth and innovation while shifting cultural organizations from integrated supply chains to networks of strategic partnerships. The success of digital platforms in promoting social and economic development depends on museums’ ability to internalize legacy knowledge and platforms’ capacity to reinterpret this knowledge using advanced digital tools. This research contributes to the literature on innovation and strategic management by demonstrating that, rather than disrupting tradition, digital platforms enhance the cultural heritage experience. Additionally, while platforms like Google Arts &amp; Culture operate under a non-profit model to democratize culture, they capture significant value through data aggregation, which may play a key role in training artificial intelligence systems.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"77 ","pages":"Article 101896"},"PeriodicalIF":3.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"‘Gospel’ or ‘Curse’: How Tourism Resource Endowment Affects Human Capital","authors":"Hui Zhang,&nbsp;Qiao Zhou,&nbsp;Liqi Tian,&nbsp;Yueyue Tan,&nbsp;Mengxiu Zeng,&nbsp;Chao Luo","doi":"10.1002/jtr.70073","DOIUrl":"https://doi.org/10.1002/jtr.70073","url":null,"abstract":"<div>\u0000 \u0000 <p>Tourism resources and human capital have an important impact on regional sustainable development. Based on the resource curse theory, this paper combines the characteristics of the industry to analyze in depth the role of tourism resources on the level of human capital and the mechanism of influence. The results show that tourism resource endowment significantly relates to regional human capital in an inverted U-shaped. The mediating effect analysis suggests that industrial structure mediates the relationship. The heterogeneity test indicates this relationship is evident only in the eastern regions. This research expands the application scope of the resource curse theory and the three-step test method. It helps understand how tourism resources affect human capital through industrial structure and offers suggestions for sustainable tourism development and regional economic growth in China.</p>\u0000 </div>","PeriodicalId":51375,"journal":{"name":"International Journal of Tourism Research","volume":"27 4","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"External validation of a proprietary risk model for 1-year mortality in community-dwelling adults aged 65 years or older.","authors":"Erica Frechman, Byron C Jaeger, Marc Kowalkowski, Jeff D Williamson, Kristin M Lenoir, Jessica A Palakshappa, Brian J Wells, Kathryn E Callahan, Nicholas M Pajewski, Jennifer L Gabbard","doi":"10.1093/jamia/ocaf062","DOIUrl":"10.1093/jamia/ocaf062","url":null,"abstract":"<p><strong>Objective: </strong>To examine the discrimination, calibration, and algorithmic fairness of the Epic End of Life Care Index (EOL-CI).</p><p><strong>Materials and methods: </strong>We assessed the EOL-CI's performance by estimating area under the receiver operating characteristic curve (AUC), sensitivity, and positive and negative predictive values in community-dwelling adults ≥65 years of age in a single health system in the Southeastern United States. Algorithmic fairness was examined by comparing the model's performance across sex, race, and ethnicity subgroups. Using a machine learning approach, we also explored local re-calibration of the EOL-CI considering additional information on past hospitalizations and frailty.</p><p><strong>Results: </strong>Among 215 731 patients (median age = 74 years, 57% female, 12% of Black race), 10% were classified as medium risk (15-44) and 3% as high risk (≥45) by the EOL-CI. The observed 1-year mortality rate was 3%. The EOL-CI had an AUC 0.82 for 1-year mortality, with a positive predictive value of 22%. Predictive performance was generally similar across sex and race subgroups, though the EOL-CI displayed better performance with increasing age and in older adults with 2 or more outpatient encounters in the past 24 months. Local re-calibration of the EOL-CI was required to provide absolute estimates of mortality risk, and calibration was further improved when the EOL-CI was augmented with data on inpatient hospitalizations and frailty.</p><p><strong>Discussion: </strong>The EOL-CI demonstrates reasonable discrimination, albeit with better performance in older adults and in those with greater health system contact.</p><p><strong>Conclusion: </strong>Local refinement and calibration of the EOL-CI score is required to provide direct estimates of prognosis, with the goal of making the EOL-CI a more a valuable tool at the point of care for identifying patients who would benefit from targeted palliative care interventions and proactive care planning.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1110-1119"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12199354/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supporting rapid innovation in research data capture and management: the REDCap external module framework.","authors":"Alex C Cheng, Stephany N Duda, Kyle McGuffin, Mark McEver, Rob Taylor, Günther A Rezniczek, Andrew Martin, Eduardo Morales, Paul A Harris","doi":"10.1093/jamia/ocaf073","DOIUrl":"10.1093/jamia/ocaf073","url":null,"abstract":"<p><strong>Objectives: </strong>Establishing a robust and secure framework allowing creation and sharing of custom features within the REDCap electronic data capture platform.</p><p><strong>Materials and methods: </strong>In partnership with REDCap Consortium members, we developed a framework for creating external modules enabling project-specific REDCap custom functionality (EM Framework). The EM Framework includes guidance and standard processes for developers to ensure basic functionality, compatibility, and security across REDCap instances. The EM Framework also includes an optional dissemination mechanism, the REDCap Repository of External Modules (Repo), for developers to easily share their work with other institutions in the REDCap Consortium.</p><p><strong>Results: </strong>From the EM Framework's launch in 2017 through 2024, 356 external modules have been published to the Repo by software developers at 59 institutions. These modules have been used on 29 485 projects at 2107 institutions in 67 countries. Over time, features from 22 of these external modules have been integrated into the core REDCap code serving 7700+ REDCap Consortium members in 160 countries.</p><p><strong>Discussion: </strong>The EM Framework permits developers to create, test, and deploy custom features to their local REDCap platform. It further enables a process to distribute these features to other REDCap administrators across the Consortium.</p><p><strong>Conclusion: </strong>The EM Framework has enhanced innovation in electronic data capture and dissemination of those innovations to a global research community.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1149-1156"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12202089/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144057082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semi-automated pipeline to accelerate multi-site flowsheet alignment and concept mapping in electronic health records.","authors":"Hao Fan, Sarah C Rossetti, Jennifer Thate, Rosemary Mugoya, Albert M Lai, Po-Yin Yen","doi":"10.1093/jamia/ocaf076","DOIUrl":"10.1093/jamia/ocaf076","url":null,"abstract":"<p><strong>Objectives: </strong>Health-care institutions customize electronic health record (EHR) configurations to reflect their unique workflows and patient care priorities. Ensuring EHR alignment across sites facilitates seamless information exchange. We developed a pipeline for EHR flowsheet alignment between health-care organizations. The pipeline is augmented by mapping flowsheet data fields to concepts in the Clinical Care Classification (CCC) nursing terminology.</p><p><strong>Materials and methods: </strong>Flowsheet templates and measures from 2 study sites were transformed into template-measure (T-M) pairs. They were aligned through exact, lexical, or semantic matching. Lexical matches were assessed using Jaccard similarity and fuzzy matching methods. Semantic alignment was determined using cosine similarity between large language model-generated embeddings of T-M pairs and CCC concepts to rank and recommend the top n concepts in CCC. Concept mappings were evaluated based on whether concepts were mapped consistently within the CCC hierarchy.</p><p><strong>Results: </strong>We totally aligned 31 255 unique T-M pairs in acute care units and 27 012 T-M pairs in intensive care units from 2 study sites. When restricted to the top-ranked CCC concept (n = 1), we achieved a 63% flowsheet alignment rate with a 53% concept mapping rate. Expanding to the top 3 concepts (n = 3) improved alignment to 96.5% and concept mapping to 96%.</p><p><strong>Discussion and conclusion: </strong>Electronic health record data field alignment with concept mapping offers opportunities to standardize data elements presented in flowsheets across health-care sites. We demonstrated the feasibility of leveraging a semi-automated pipeline to streamline the EHR flowsheet alignment and accelerate the manual concept mapping process.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1140-1148"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12202140/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144081789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Be mindful in organizational change: team mindfulness and employee openness to change","authors":"Dan Ni ,&nbsp;Mengyi Zhang ,&nbsp;Xiaoming Zheng","doi":"10.1016/j.jbusres.2025.115551","DOIUrl":"10.1016/j.jbusres.2025.115551","url":null,"abstract":"<div><div>Combining social information processing (SIP) theory and the mindfulness literature, we propose that team mindfulness is positively related to both team psychological safety climate and team positive affective climate; in turn, these factors are positively related to employee openness to change. We further propose that a higher (versus lower) level of leader workplace mindfulness enhanced the positive effects of team mindfulness on team climates and the above indirect effects. We conducted two quantitative studies (i.e., a scenario-based experiment and a time-lagged and multi-source survey with Western and Chinese samples). Data largely support our hypotheses. Theoretical contributions and practical implications are discussed.</div></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"199 ","pages":"Article 115551"},"PeriodicalIF":10.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144516934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDEMapper: enhancing National Institutes of Health common data element use with large language models.","authors":"Yan Wang, Jimin Huang, Huan He, Vincent Zhang, Yujia Zhou, Xubing Hao, Pritham Ram, Lingfei Qian, Qianqian Xie, Ruey-Ling Weng, Fongci Lin, Yan Hu, Licong Cui, Xiaoqian Jiang, Hua Xu, Na Hong","doi":"10.1093/jamia/ocaf064","DOIUrl":"10.1093/jamia/ocaf064","url":null,"abstract":"<p><strong>Objective: </strong>Common Data Elements (CDEs) standardize data collection and sharing across studies, enhancing data interoperability and improving research reproducibility. However, implementing CDEs presents challenges due to the broad range and variety of data elements. This study aims to develop a CDE mapping tool to bridge the gap between local data elements and National Institutes of Health (NIH) CDEs.</p><p><strong>Methods: </strong>We propose CDEMapper, a large language model (LLM)-powered mapping tool designed to assist in mapping local data elements to NIH CDEs. CDEMapper has 3 core modules: (1) CDE indexing and embeddings. NIH CDEs were indexed and embedded to support semantic search; (2) CDE recommendations. The tool combines Elasticsearch (BM25 methods) with GPT services to recommend candidate CDEs and their permissible values; and (3) Human review. Users review and select the best match for their data elements and value sets. We evaluate the tool's recommendation accuracy and usability against manual annotations and testing.</p><p><strong>Results: </strong>CDEMapper offers a publicly available, LLM-powered, and intuitive user interface that consolidates essential and advanced mapping services into a streamlined pipeline. The evaluation results demonstrated that the augmented BM25 with GPT embeddings and a GPT ranker achieved the overall best performance. The usability test also highlighted the effectiveness and efficiency of our tool.</p><p><strong>Discussions and conclusions: </strong>This work opens up the potential of using LLMs to assist with CDE mapping when aligning local data elements with NIH CDEs. Additionally, this effort helps researchers better understand the gaps between their data elements and NIH CDEs while promoting CDE reusability.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1130-1139"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12202029/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144005421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Call for Papers: Towards Stronger Theorising of Temporary Organising","authors":"","doi":"10.1016/j.ijproman.2025.102725","DOIUrl":"10.1016/j.ijproman.2025.102725","url":null,"abstract":"","PeriodicalId":48429,"journal":{"name":"International Journal of Project Management","volume":"43 5","pages":"Article 102725"},"PeriodicalIF":7.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What sparks team learning? Refining the conceptual understanding of team learning and learning triggers","authors":"Katrien Vangrieken ,&nbsp;Shannon L. Marlow","doi":"10.1016/j.hrmr.2025.101101","DOIUrl":"10.1016/j.hrmr.2025.101101","url":null,"abstract":"<div><div>Teams and their capacity to learn are considered key cornerstones of organizational success. Research on team learning has substantially grown in recent years, with studies identifying a myriad of positive outcomes and key antecedents. Despite these advances, empirical research remains fragmented due to persistent conceptual ambiguities. Team learning has been conceptualized in numerous ways, encompassing a wide variety of distinct learning behaviors, with limited integration. Moreover, although antecedents and boundary conditions have been extensively investigated, a unified understanding of how team learning is initiated remains unaddressed. This paper presents a systematic review analyzing 239 empirical studies on team learning to address these issues. We introduce a trigger-based process model examining how learning is initiated and unfolds over time, accounting for the vast diversity of learning conceptualizations, theoretical perspectives, and empirical findings in the field. Based on this model, we identify important opportunities for future research on team learning.</div></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"35 4","pages":"Article 101101"},"PeriodicalIF":8.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards an estimate of the impact of censorship on biomedical literature.","authors":"Clair Kronk, Os Keyes, Megh Marathe","doi":"10.1093/jamia/ocaf089","DOIUrl":"10.1093/jamia/ocaf089","url":null,"abstract":"<p><strong>Objective: </strong>To determine how much of the current biomedical literature would be flagged or require modification in relation to the presence of terms from leaked lists prepared by the Centers for Disease Control (CDC), the National Science Foundation (NSF), and the National Security Administration (NSA) in early 2025.</p><p><strong>Materials and methods: </strong>We searched PubMed (from 1996 to 2024) for all records that match at least one of the given terms, combined the terms and analyzed yearly and total frequency.</p><p><strong>Results: </strong>At least 36.3% of all biomedical literature analyzed, representing more than 10 million records, would be flagged for review or modification with the given term lists. It is conservatively estimated that such term lists could impact more than 2.7 million biomedical publications over the next four years.</p><p><strong>Discussion: </strong>Censorship of scientific findings and the use of term lists to judge the content of scientific materials could significantly impede scientific progress.</p><p><strong>Conclusion: </strong>Future research should investigate the long-term implications of, and interim strategies used to navigate, the imposition of censorship on the production and dissemination of scientific knowledge.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1199-1205"},"PeriodicalIF":4.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144227401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}