{"title":"A Task-Technology Fit Model for Digital Audio Workstations Evaluation","authors":"D. Etinger","doi":"10.54941/ahfe1002867","DOIUrl":null,"url":null,"abstract":"Music industry changes in the last decade largely shifted the music\n production tasks from big established studios to music artists. With the\n addition of online music streaming platforms, an end-to-end process of music\n creation, publishing, delivery, and consummation is achieved. This\n phenomenon emphasizes music artists as content creators to handle music\n production. Digital audio workstation systems enabled end users to compose,\n record, mix and master music. This research focuses on identifying the fit\n between various tasks music artists must perform during music creation and\n the technical characteristic of the tools used, particularly modern digital\n audio workstations. Ultimately, it is tested whether the task- technology\n fit (TTF), a well-established information systems theory model is a good\n predictor of the intention to use digital audio workstation systems by music\n artists. By applying the PLS-SEM method, results show that TTF positively\n influences music artists' intention to use DAWs.","PeriodicalId":269162,"journal":{"name":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems, February 22–24, 2023, Venice, Italy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1002867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

Music industry changes in the last decade largely shifted the music production tasks from big established studios to music artists. With the addition of online music streaming platforms, an end-to-end process of music creation, publishing, delivery, and consummation is achieved. This phenomenon emphasizes music artists as content creators to handle music production. Digital audio workstation systems enabled end users to compose, record, mix and master music. This research focuses on identifying the fit between various tasks music artists must perform during music creation and the technical characteristic of the tools used, particularly modern digital audio workstations. Ultimately, it is tested whether the task- technology fit (TTF), a well-established information systems theory model is a good predictor of the intention to use digital audio workstation systems by music artists. By applying the PLS-SEM method, results show that TTF positively influences music artists' intention to use DAWs.
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数字音频工作站评估的任务-技术匹配模型
在过去的十年里,音乐产业的变化很大程度上将音乐制作任务从大型工作室转移到了音乐艺术家身上。随着在线音乐流媒体平台的加入,实现了音乐创作、发布、发布和完善的端到端流程。这种现象强调了音乐艺术家作为内容创造者处理音乐制作的重要性。数字音频工作站系统使最终用户能够作曲、录制、混音和掌握音乐。这项研究的重点是确定音乐艺术家在音乐创作过程中必须执行的各种任务之间的契合度,以及所使用的工具的技术特征,特别是现代数字音频工作站。最后,测试了任务-技术契合度(TTF),一个完善的信息系统理论模型是否能很好地预测音乐艺术家使用数字音频工作站系统的意图。应用PLS-SEM方法,结果显示TTF正影响音乐艺术家使用DAWs的意愿。
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