Integrating the Expanded Task-technology Fit Theory and the Technology Acceptance Model: A Multi-wave Empirical Analysis

被引:5
作者
Howard, Matt C. [1 ]
Hair Jr, Joseph F. [1 ]
机构
[1] Univ S Alabama, Mitchell Coll Business, Mobile, AL 36688 USA
来源
AIS TRANSACTIONS ON HUMAN-COMPUTER INTERACTION | 2023年 / 15卷 / 01期
关键词
Task-technology Fit Theory; Expanded Task-technology Fit Theory; Technology Acceptance Model; PLS-SEM; CONTINUANCE INTENTION; CONSUMER ACCEPTANCE; SOCIAL MOTIVATION; USER ACCEPTANCE; TAM; METAANALYSIS; EXTENSION; ADOPTION; SYSTEM;
D O I
10.17705/1thci.00184
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Task-technology fit theory proposes that the match between tasks and technologies, known as task-technology fit, has a positive relation with technology use and performance. Researchers have recently extended task-technology fit theory by conceptualizing task-technology misfit, which describes instances in which technology provides too few (too little) or too many (too much) features to perform a task. We link this newly expanded theory, which we label expanded task-technology fit (E-TTF) theory, with the technology acceptance model (TAM). We conducted a study and found that task-technology fit and too little significantly related to the variables in the TAM and that each ultimately had an indirect effect on use. In contrast, too much did not significantly relate to any variable in the TAM. These results support that E-TTF theory explains meaningful variance in the TAM, which suggests that integrating these theories is important for understanding technology use. Likewise, these results emphasize the importance of the multidimensional conceptualization that the E-TTF theory proposes. Too little (too few features) predicted outcomes beyond task-technology fit and meaningfully improved our model's predictive abilities. In contrast, too much's (too many features) relationships lacked significance, which emphasizes the need to distinguish types of task-technology misfit. Therefore, our study provides benefits for research on E-TTF theory, the TAM, and their integration.
引用
收藏
页码:83 / 110
页数:29
相关论文
共 81 条
[71]   Indian Travellers' Adoption of Airbnb Platform [J].
Tamilmani, Kuttimani ;
Rana, Nripendra P. ;
Nunkoo, Robin ;
Raghavan, Vishnupriya ;
Dwivedi, Yogesh K. .
INFORMATION SYSTEMS FRONTIERS, 2022, 24 (01) :77-96
[72]   Continuance Intentions to Use Gamification for Training in Higher Education: Integrating the Technology Acceptance Model (TAM), Social Motivation, and Task Technology Fit (TTF) [J].
Vanduhe, Vanye Zira ;
Nat, Muesser ;
Hasan, Hasan Fahmi .
IEEE ACCESS, 2020, 8 :21473-21484
[73]   A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies [J].
Venkatesh, V ;
Davis, FD .
MANAGEMENT SCIENCE, 2000, 46 (02) :186-204
[74]   User acceptance of information technology: Toward a unified view [J].
Venkatesh, V ;
Morris, MG ;
Davis, GB ;
Davis, FD .
MIS QUARTERLY, 2003, 27 (03) :425-478
[75]   Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model [J].
Venkatesh, V .
INFORMATION SYSTEMS RESEARCH, 2000, 11 (04) :342-365
[76]   Technology Acceptance Model 3 and a Research Agenda on Interventions [J].
Venkatesh, Viswanath ;
Bala, Hillol .
DECISION SCIENCES, 2008, 39 (02) :273-315
[77]   THE CONCEPT OF FIT IN STRATEGY RESEARCH - TOWARD VERBAL AND STATISTICAL CORRESPONDENCE [J].
VENKATRAMAN, N .
ACADEMY OF MANAGEMENT REVIEW, 1989, 14 (03) :423-444
[78]   Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model [J].
Wu, Bing ;
Chen, Xiaohui .
COMPUTERS IN HUMAN BEHAVIOR, 2017, 67 :221-232
[79]  
Yousafzai SY, 2007, J MODEL MANAG, V2, P251, DOI 10.1108/17465660710834453
[80]   What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age [J].
Zhao, Yang ;
Ni, Qi ;
Zhou, Ruoxin .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2018, 43 :342-350