IF 10.5 1区管理学

Journal of Business Research Pub Date : 2024-11-13 DOI: 10.1016/j.jbusres.2024.115048

Wanqing Li , Jiang Yu , Feng Chen

{"title":"Linking firm performance with innovation culture: An algorithmic approach towards theory building","authors":"Wanqing Li , Jiang Yu , Feng Chen","doi":"10.1016/j.jbusres.2024.115048","DOIUrl":"10.1016/j.jbusres.2024.115048","url":null,"abstract":"<div><div>To address the growing demand for theory development in computational social science research, this study employs an algorithm-driven approach to formulate a comprehensive six-step theory generation process. By applying this original research method, a new theoretical model—the “Dynamic Resource-Culture Synergy Theory” is proposed which enhances the explanatory power regarding how firms maintain competitiveness in rapidly changing environments by emphasizing the pivotal role of culture in resource integration and innovation processes. Drawing on empirical data from 887 Chinese high-tech manufacturing firms, our analysis identifies key drivers of organizational performance, with a particular focus on the role of organizational culture, especially innovation culture, as a mediating force. Utilizing the GWO-SVM technique, we gain a nuanced understanding of how different cultural traits interact with innovation and leverage, uncovering how the initial enhancement of innovation culture positively impacts performance metrics such as ROA. The findings confirm that innovation, facilitated by organizational culture, significantly enhances performance outcomes. Furthermore, this study considers factors such as leverage and the proportion of technical personnel, investigating their moderating effects on the relationship between innovation culture and firm performance. This study not only deepens the understanding of how innovation and culture interact to influence firm performance but also provides significant theoretical and practical contributions to the study of the dynamics of high-tech manufacturing enterprises.</div></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"187 ","pages":"Article 115048"},"PeriodicalIF":10.5,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652646","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}

引用次数: 0

Imagined futures in sustainability transitions: Towards diverse future-making 可持续性转型中的想象未来：实现多样化的未来创造

IF 3 3区管理学

Futures Pub Date : 2024-11-13 DOI: 10.1016/j.futures.2024.103502

Jonathan Friedrich , Abe Hendriks

引用次数: 0

Learning health system linchpins: information exchange and a common data model. 学习卫生系统的关键：信息交换和通用数据模型。

IF 4.7 2区医学

Journal of the American Medical Informatics Association Pub Date : 2024-11-13 DOI: 10.1093/jamia/ocae277

Aaron S Eisman, Elizabeth S Chen, Wen-Chih Wu, Karen M Crowley, Dilum P Aluthge, Katherine Brown, Indra Neil Sarkar

{"title":"Learning health system linchpins: information exchange and a common data model.","authors":"Aaron S Eisman, Elizabeth S Chen, Wen-Chih Wu, Karen M Crowley, Dilum P Aluthge, Katherine Brown, Indra Neil Sarkar","doi":"10.1093/jamia/ocae277","DOIUrl":"https://doi.org/10.1093/jamia/ocae277","url":null,"abstract":"Objective: To demonstrate the potential for a centrally managed health information exchange standardized to a common data model (HIE-CDM) to facilitate semantic data flow needed to support a learning health system (LHS).Materials and methods: The Rhode Island Quality Institute operates the Rhode Island (RI) statewide HIE, which aggregates RI health data for more than half of the state's population from 47 data partners. We standardized HIE data to the Observational Medical Outcomes Partnership (OMOP) CDM. Atherosclerotic cardiovascular disease (ASCVD) risk and primary prevention practices were selected to demonstrate LHS semantic data flow from 2013 to 2023.Results: We calculated longitudinal 10-year ASCVD risk on 62,999 individuals. Nearly two-thirds had ASCVD risk factors from more than one data partner. This enabled granular tracking of individual ASCVD risk, primary prevention (ie, statin therapy), and incident disease. The population was on statins for fewer than half of the guideline-recommended days. We also found that individuals receiving care at Federally Qualified Health Centers were more likely to have unfavorable ASCVD risk profiles and more likely to be on statins. CDM transformation reduced data heterogeneity through a unified health record that adheres to defined terminologies per OMOP domain.Discussion: We demonstrated the potential for an HIE-CDM to enable observational population health research. We also showed how to leverage existing health information technology infrastructure and health data best practices to break down LHS barriers.Conclusion: HIE-CDM facilitates knowledge curation and health system intervention development at the individual, health system, and population levels.","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The paradox of product scarcity: Catalyzing the speed of innovation diffusion 产品稀缺的悖论：催化创新传播的速度

IF 18.2 1区化学

ACS Catalysis Pub Date : 2024-11-13 DOI: 10.1007/s11747-024-01060-7

Surya Pathak, P. V. Sundar Balakrishnan

{"title":"The paradox of product scarcity: Catalyzing the speed of innovation diffusion","authors":"Surya Pathak, P. V. Sundar Balakrishnan","doi":"10.1007/s11747-024-01060-7","DOIUrl":"https://doi.org/10.1007/s11747-024-01060-7","url":null,"abstract":"Product shortages are known to slow down the diffusion process. However, we counterintuitively theorize and empirically demonstrate that under specific conditions of social influence, the diffusion process may be accelerated by early product scarcity. Using an Agent-Based framework and Genetic Algorithm-based estimation, we analyzed 20 product categories to identify the critical trade-off influencing diffusion: the interplay of the social influence ratio of waiting customers to adopters, the external influence, and level of product scarcity. Strategic managerial actions can accelerate the adoption of products. For example, in the case of fitness trackers, we were able to simulate speed-up by up to two years compared to the standard Bass model. Importantly, we introduce a novel framework to study competition dynamics, analyzing how the timing of market entry and the production capacity of competitors, along with the initial installed capacity of the pioneering firm affect diffusion speed. This acceleration, whether due to managerial foresight or serendipity, necessitates careful orchestration to harness the enthusiasm of waiting customers and strategically allocate marketing spending on social media platforms, thereby differentially amplifying the influence of adopters and potential customers.","PeriodicalId":9,"journal":{"name":"ACS Catalysis ","volume":"1 1","pages":""},"PeriodicalIF":18.2,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142601925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Oncointerpreter.ai enables interactive, personalized summarization of cancer diagnostics data. Oncointerpreter.ai 可对癌症诊断数据进行交互式、个性化的汇总。

IF 4.7 2区医学

Journal of the American Medical Informatics Association Pub Date : 2024-11-13 DOI: 10.1093/jamia/ocae284

Arihant Tripathi, Brett Ecker, Patrick Boland, Saum Ghodoussipour, Gregory R Riedlinger, Subhajyoti De

{"title":"Oncointerpreter.ai enables interactive, personalized summarization of cancer diagnostics data.","authors":"Arihant Tripathi, Brett Ecker, Patrick Boland, Saum Ghodoussipour, Gregory R Riedlinger, Subhajyoti De","doi":"10.1093/jamia/ocae284","DOIUrl":"10.1093/jamia/ocae284","url":null,"abstract":"Objectives: Cancer diagnosis comes as a shock to many patients, and many of them feel unprepared to handle the complexity of the life-changing event, understand technicalities of the diagnostic reports, and fully engage with the clinical team regarding the personalized clinical decision-making.Materials and methods: We develop Oncointerpreter.ai an interactive resource to offer personalized summarization of clinical cancer genomic and pathological data, and frame questions or address queries about therapeutic opportunities in near-real time via a graphical interface. It is built on the Mistral-7B and Llama-2 7B large language models trained on a local database trained using a large, curated corpus.Results: We showcase its utility with case studies, where Oncointerpreter.ai extracted key clinical and molecular attributes from deidentified pathology and clinical genomics reports, summarized their contextual significance and answered queries on pertinent treatment options. Oncointerpreter also provided personalized summary of currently active clinical trials that match the patients' disease status, their selection criteria, and geographic locations. Benchmarking and comparative assessment indicated that the model responses were generally consistent, and hallucination, ie, factually incorrect or nonsensical response was rare; treatment- and outcome related queries led to context-aware responses, and response time correlated with verbosity.Discussion: The choice of model and domain-specific training also affected the response quality.Conclusion: Oncointerpreter.ai can aid the existing clinical care with interactive, individualized summarization of diagnostics data to promote informed dialogs with the patients with new cancer diagnoses.Availability: https://github.com/Siris2314/Oncointerpreter.","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What drives users to tip? The impact of contributor experience, content length, and content type on online video sharing platforms 是什么促使用户给小费？贡献者经验、内容长度和内容类型对在线视频分享平台的影响

IF 8.2 2区管理学

Information & Management Pub Date : 2024-11-13 DOI: 10.1016/j.im.2024.104054

Wang Cao , Yipeng Liu , Shengli Li , Zheyuan Pu

引用次数: 0

A classification framework for generative artificial intelligence for social good 促进社会公益的生成式人工智能分类框架

IF 11.1 1区管理学

Technovation Pub Date : 2024-11-13 DOI: 10.1016/j.technovation.2024.103129

Jack Crumbly , Raktim Pal , Nezih Altay

{"title":"A classification framework for generative artificial intelligence for social good","authors":"Jack Crumbly , Raktim Pal , Nezih Altay","doi":"10.1016/j.technovation.2024.103129","DOIUrl":"10.1016/j.technovation.2024.103129","url":null,"abstract":"<div><div>Many policy makers and corporate leaders are adjusting their strategies to harness the power of GenAI. There are numerous debates on how GenAI would fundamentally change existing business models. However, there is not much discussion on roles of generative AI in the domain of social good. Broader views covering potential opportunities of GenAI to enable diverse initiatives in the social good space are largely missing. We intend to reduce the gap by developing a classification framework that should allow researchers gauge the potential impact of GenAI for social good initiatives. Through case analysis, we assess how value-added abilities of GenAI may influence various social good initiatives. We adopt/develop two loosely connected classification frameworks that are grounded in task-technology fit (TTF) theory. Subsequently, we investigate how our analyses of GenAI initiatives utilizing different dimensions of these two frameworks may be synthesized to provide appropriate explanation for potential success of GenAI for social good. We develop five propositions that will provide guidance to practitioners and researchers. The theoretically grounded analysis of 21 GenAI for social good use cases based on the two classification frameworks, and the resulting propositions are the original contributions of this paper to the AI for social good literature.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"139 ","pages":"Article 103129"},"PeriodicalIF":11.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657974","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}

引用次数: 0

Socio-politically silent brands: A double edged sword 社会政治沉默品牌：一把双刃剑

IF 10.5 1区管理学

Journal of Business Research Pub Date : 2024-11-13 DOI: 10.1016/j.jbusres.2024.115046

Aaminah Zaman Malik , Fayez Ahmad , Francisco Guzmán

引用次数: 0

Trust and Generative Artificial Intelligence: A Reply to Killoran, Park, and Kietzmann 信任与生成式人工智能：对 Killoran、Park 和 Kietzmann 的回复

IF 16.4 1区化学

ACS Materials Letters Pub Date : 2024-11-13 DOI: 10.5465/amr.2024.0397

Bart S. Vanneste, Phanish Puranam

引用次数: 0

Tourism forecasting: A dynamic spatiotemporal model 旅游预测：动态时空模型