{"title":"有效使用分析DSS和工作绩效:超越技术接受","authors":"Damon E. Campbell, Nicholas H. Roberts","doi":"10.1080/10919392.2019.1571756","DOIUrl":null,"url":null,"abstract":"ABSTRACT This study extends and test the work done on effective use of information systems (IS) by developing measures for this construct which expands the conceptualization of use beyond the popular technology acceptance model (TAM). Effective use posits dimensions of use (informed action, representational fidelity, and transparent interaction) which are intended to measure a user’s ability to effectively use an IS in a given context. Moving beyond simple adoption and use contexts is an important distinction that expands researcher’s and practitioner’s ability to assess usage effectiveness. In a work context, it is more important to have high performance and effective usage of systems in comparison to just having high usage rates. Therefore this study uses the context of analytic decision support systems (DSS) and tests the relationship between the proposed dimensions of effective use and job performance. A survey (N = 265) of executives with work experience using analytic DSS was conducted to maximize realism and generalizability. This study is the first to empirically test the proposed relationships of effective use to performance. Results indicate that informed action is a significant predictor of individual job performance. However, representational fidelity and transparent interaction are not significant predictors of job performance.","PeriodicalId":54777,"journal":{"name":"Journal of Organizational Computing and Electronic Commerce","volume":"29 1","pages":"125 - 138"},"PeriodicalIF":2.0000,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10919392.2019.1571756","citationCount":"3","resultStr":"{\"title\":\"Effective use of analytic DSS and job performance: Looking beyond technology acceptance\",\"authors\":\"Damon E. Campbell, Nicholas H. Roberts\",\"doi\":\"10.1080/10919392.2019.1571756\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT This study extends and test the work done on effective use of information systems (IS) by developing measures for this construct which expands the conceptualization of use beyond the popular technology acceptance model (TAM). Effective use posits dimensions of use (informed action, representational fidelity, and transparent interaction) which are intended to measure a user’s ability to effectively use an IS in a given context. Moving beyond simple adoption and use contexts is an important distinction that expands researcher’s and practitioner’s ability to assess usage effectiveness. In a work context, it is more important to have high performance and effective usage of systems in comparison to just having high usage rates. Therefore this study uses the context of analytic decision support systems (DSS) and tests the relationship between the proposed dimensions of effective use and job performance. A survey (N = 265) of executives with work experience using analytic DSS was conducted to maximize realism and generalizability. This study is the first to empirically test the proposed relationships of effective use to performance. Results indicate that informed action is a significant predictor of individual job performance. However, representational fidelity and transparent interaction are not significant predictors of job performance.\",\"PeriodicalId\":54777,\"journal\":{\"name\":\"Journal of Organizational Computing and Electronic Commerce\",\"volume\":\"29 1\",\"pages\":\"125 - 138\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2019-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/10919392.2019.1571756\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Organizational Computing and Electronic Commerce\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/10919392.2019.1571756\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Organizational Computing and Electronic Commerce","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/10919392.2019.1571756","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Effective use of analytic DSS and job performance: Looking beyond technology acceptance
ABSTRACT This study extends and test the work done on effective use of information systems (IS) by developing measures for this construct which expands the conceptualization of use beyond the popular technology acceptance model (TAM). Effective use posits dimensions of use (informed action, representational fidelity, and transparent interaction) which are intended to measure a user’s ability to effectively use an IS in a given context. Moving beyond simple adoption and use contexts is an important distinction that expands researcher’s and practitioner’s ability to assess usage effectiveness. In a work context, it is more important to have high performance and effective usage of systems in comparison to just having high usage rates. Therefore this study uses the context of analytic decision support systems (DSS) and tests the relationship between the proposed dimensions of effective use and job performance. A survey (N = 265) of executives with work experience using analytic DSS was conducted to maximize realism and generalizability. This study is the first to empirically test the proposed relationships of effective use to performance. Results indicate that informed action is a significant predictor of individual job performance. However, representational fidelity and transparent interaction are not significant predictors of job performance.
期刊介绍:
The aim of the Journal of Organizational Computing and Electronic Commerce (JOCEC) is to publish quality, fresh, and innovative work that will make a difference for future research and practice rather than focusing on well-established research areas.
JOCEC publishes original research that explores the relationships between computer/communication technology and the design, operations, and performance of organizations. This includes implications of the technologies for organizational structure and dynamics, technological advances to keep pace with changes of organizations and their environments, emerging technological possibilities for improving organizational performance, and the many facets of electronic business.
Theoretical, experimental, survey, and design science research are all welcome and might look at:
• E-commerce
• Collaborative commerce
• Interorganizational systems
• Enterprise systems
• Supply chain technologies
• Computer-supported cooperative work
• Computer-aided coordination
• Economics of organizational computing
• Technologies for organizational learning
• Behavioral aspects of organizational computing.