Pub Date : 2023-09-13DOI: 10.1007/s10799-023-00410-1
Yonghong Sun
{"title":"Versioning for information goods with development costs","authors":"Yonghong Sun","doi":"10.1007/s10799-023-00410-1","DOIUrl":"https://doi.org/10.1007/s10799-023-00410-1","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135786429","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}
Pub Date : 2023-08-29DOI: 10.1007/s10799-023-00409-8
S. Oh, S. Xiao, B. Park, Taewoo Roh
{"title":"Coping or threat? Unraveling the mechanisms enabling user acceptance of blockchain technologies","authors":"S. Oh, S. Xiao, B. Park, Taewoo Roh","doi":"10.1007/s10799-023-00409-8","DOIUrl":"https://doi.org/10.1007/s10799-023-00409-8","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82447790","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}
Pub Date : 2023-08-16DOI: 10.1007/s10799-023-00407-w
Nisar Ahmad, Shaofu Du, Fawad Ahmed, Noor ul Amin, Xu Yi
{"title":"Healthcare professionals satisfaction and AI-based clinical decision support system in public sector hospitals during health crises: a cross-sectional study","authors":"Nisar Ahmad, Shaofu Du, Fawad Ahmed, Noor ul Amin, Xu Yi","doi":"10.1007/s10799-023-00407-w","DOIUrl":"https://doi.org/10.1007/s10799-023-00407-w","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79283814","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}
Pub Date : 2023-08-10DOI: 10.1007/s10799-023-00408-9
Haonan Wang, Fangjuan Qiu
{"title":"AI adoption and labor cost stickiness: based on natural language and machine learning","authors":"Haonan Wang, Fangjuan Qiu","doi":"10.1007/s10799-023-00408-9","DOIUrl":"https://doi.org/10.1007/s10799-023-00408-9","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90252618","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}
Pub Date : 2023-07-06DOI: 10.1007/s10799-023-00404-z
Fabian Lang, Lukas Riegel
{"title":"Acceptance of online customer channels for damage claims in Germany","authors":"Fabian Lang, Lukas Riegel","doi":"10.1007/s10799-023-00404-z","DOIUrl":"https://doi.org/10.1007/s10799-023-00404-z","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84422539","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}
Pub Date : 2023-06-28DOI: 10.1007/s10799-023-00405-y
R. Banker, A. Amirteimoori, T. Allahviranloo, R. Sinha
{"title":"Performance analysis and managerial ability in the general insurance market: a study of India and Iran","authors":"R. Banker, A. Amirteimoori, T. Allahviranloo, R. Sinha","doi":"10.1007/s10799-023-00405-y","DOIUrl":"https://doi.org/10.1007/s10799-023-00405-y","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79379420","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}
Pub Date : 2023-06-27DOI: 10.1007/s10799-023-00402-1
Bo Zhang, Weizhu Hou, Ximeng Zhang
{"title":"Employee training and audit fees","authors":"Bo Zhang, Weizhu Hou, Ximeng Zhang","doi":"10.1007/s10799-023-00402-1","DOIUrl":"https://doi.org/10.1007/s10799-023-00402-1","url":null,"abstract":"","PeriodicalId":13616,"journal":{"name":"Information Technology and Management","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80566019","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}
Pub Date : 2023-06-03DOI: 10.1007/s10799-023-00399-7
Robin Hirt, Niklas Kühl, Dominik Martin, Gerhard Satzger
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.
{"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}
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