MODEL OF ACCEPTANCE WITH PEER SUPPORT: A SOCIAL NETWORK PERSPECTIVE TO UNDERSTAND EMPLOYEES' SYSTEM USE

被引:0
|
作者
Sykes, Tracy Ann [1 ]
Venkatesh, Viswanath [1 ]
Gosain, Sanjay [2 ]
机构
[1] Univ Arkansas, Walton Coll Business, Fayetteville, AR 72701 USA
[2] Capital Grp Co, Brea, CA 92833 USA
关键词
TAM; UTAUT; social networks; behavioral intention; system use; network centrality; network density; INFORMATION-TECHNOLOGY; BEHAVIORAL INTENTION; STRUCTURAL-ANALYSIS; GENDER-DIFFERENCES; DECISION-MAKING; REASONED ACTION; CENTRALITY; USAGE; WORK; PERFORMANCE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Prior research has extensively studied individual adoption and use of information systems, primarily using beliefs as predictors of behavioral intention to use a system that in turn predicts system use. We propose a model of acceptance with peer support (MAPS) that integrates prior individual-level research with social networks constructs. We argue that an individual's embeddedness in the social network of the organizational unit implementing a new information system can enhance our understanding of technology use. An individual's coworkers can be important sources of help in overcoming knowledge barriers constraining use of a complex system, and such interactions with others can determine an employee's ability to influence eventual system configuration and features. We incorporate network density (reflecting "get-help" ties for an employee) and network centrality (reflecting "give-help" ties for an employee), drawn from prior social network research, as key predictors of system use. Further, we conceptualize valued network density and valued network centrality, both of which take into account ties to those with relevant system-related information, knowledge, and resources, and employ them as additional predictors. We suggest that these constructs together are coping and influencing pathways by which they have an effect on system use. We conducted a 3-month long study of 87 employees in one business unit in an organization. The results confirmed our theory that social network constructs can significantly enhance our understanding of system use over and above predictors from prior individual-level adoption research.
引用
收藏
页码:371 / 393
页数:23
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