Information Technology and Management最新文献_第4页

Versioning for information goods with development costs 对具有开发成本的信息产品进行版本控制

Information Technology and Management Pub Date : 2023-09-13 DOI: 10.1007/s10799-023-00410-1

Yonghong Sun

引用次数: 0

Coping or threat? Unraveling the mechanisms enabling user acceptance of blockchain technologies 应对还是威胁?揭示用户接受区块链技术的机制

Information Technology and Management Pub Date : 2023-08-29 DOI: 10.1007/s10799-023-00409-8

S. Oh, S. Xiao, B. Park, Taewoo Roh

引用次数: 0

Healthcare professionals satisfaction and AI-based clinical decision support system in public sector hospitals during health crises: a cross-sectional study 健康危机期间公立医院医护人员满意度和基于人工智能的临床决策支持系统:一项横断面研究

Information Technology and Management Pub Date : 2023-08-16 DOI: 10.1007/s10799-023-00407-w

Nisar Ahmad, Shaofu Du, Fawad Ahmed, Noor ul Amin, Xu Yi

引用次数: 0

AI adoption and labor cost stickiness: based on natural language and machine learning 人工智能采用和劳动力成本粘性:基于自然语言和机器学习

Information Technology and Management Pub Date : 2023-08-10 DOI: 10.1007/s10799-023-00408-9

Haonan Wang, Fangjuan Qiu

引用次数: 0

Optimal interest rates personalization in FinTech lending 金融科技贷款的最优利率个性化

Information Technology and Management Pub Date : 2023-07-25 DOI: 10.1007/s10799-023-00406-x

Yangyin Lin, Q. Ye, Hao Xia

引用次数: 0

Competitive strategy and stock market liquidity: a natural language processing approach 竞争策略与股票市场流动性:一种自然语言处理方法

Information Technology and Management Pub Date : 2023-07-22 DOI: 10.1007/s10799-023-00401-2

Xintong Wang, Ruoqing Han, Minchen Zheng

引用次数: 0

Acceptance of online customer channels for damage claims in Germany 在德国接受在线客户渠道的损害索赔

Information Technology and Management Pub Date : 2023-07-06 DOI: 10.1007/s10799-023-00404-z

Fabian Lang, Lukas Riegel

引用次数: 0

Performance analysis and managerial ability in the general insurance market: a study of India and Iran 一般保险市场的绩效分析与管理能力:以印度和伊朗为例

Information Technology and Management Pub Date : 2023-06-28 DOI: 10.1007/s10799-023-00405-y

R. Banker, A. Amirteimoori, T. Allahviranloo, R. Sinha

引用次数: 1

Employee training and audit fees 员工培训和审核费用

Information Technology and Management Pub Date : 2023-06-27 DOI: 10.1007/s10799-023-00402-1

Bo Zhang, Weizhu Hou, Ximeng Zhang

引用次数: 0

Enabling inter-organizational analytics in business networks through meta machine learning 通过元机器学习实现业务网络中的组织间分析

Information Technology and Management Pub Date : 2023-06-03 DOI: 10.1007/s10799-023-00399-7

Robin Hirt, Niklas Kühl, Dominik Martin, Gerhard Satzger

{"title":"Enabling inter-organizational analytics in business networks through meta machine learning","authors":"Robin Hirt, Niklas Kühl, Dominik Martin, Gerhard Satzger","doi":"10.1007/s10799-023-00399-7","DOIUrl":"https://doi.org/10.1007/s10799-023-00399-7","url":null,"abstract":"Abstract Successful analytics solutions that provide valuable insights often hinge on the connection of various data sources. While it is often feasible to generate larger data pools within organizations, the application of analytics within (inter-organizational) business networks is still severely constrained. As data is distributed across several legal units, potentially even across countries, the fear of disclosing sensitive information as well as the sheer volume of the data that would need to be exchanged are key inhibitors for the creation of effective system-wide solutions—all while still reaching superior prediction performance. In this work, we propose a meta machine learning method that deals with these obstacles to enable comprehensive analyses within a business network. We follow a design science research approach and evaluate our method with respect to feasibility and performance in an industrial use case. First, we show that it is feasible to perform network-wide analyses that preserve data confidentiality as well as limit data transfer volume. Second, we demonstrate that our method outperforms a conventional isolated analysis and even gets close to a (hypothetical) scenario where all data could be shared within the network. Thus, we provide a fundamental contribution for making business networks more effective, as we remove a key obstacle to tap the huge potential of learning from data that is scattered throughout the network.","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135842253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0