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December 14, 2002 Diane M. Strong, WPI 1
A Unified Model of IT Use Choices: Contributions from
TAM, TTF, and CSE
Diane M. Strong*
Worcester Polytechnic InstituteInvited Presentation
First Annual Workshop on HCI Research in MIS
Barcelona, Spain 2002
*This is joint work with Mark T. Dishaw, University of Wisconsin Oshkosh
December 14, 2002 Diane M. Strong, WPI 2
General Research Objective
• Understand the software utilization choices of end users, by using and extending existing models – Task-technology Fit (TTF) models
– Technology Acceptance Model (TAM)
– Individual Abilities Constructs, e.g., Experience, Computer Self-efficacy
• Conduct a series of studies testing the models and combinations of them
December 14, 2002 Diane M. Strong, WPI 3
Task-Technology Fit Models
Individual Abilities
Technology Characteristics
FIT
Technology Utilization
Performance
Task Characteristics
Technology includes HW, SW, and data
*individual perf. *organizational perf.
December 14, 2002 Diane M. Strong, WPI 4
1. TTF Model Study
Operationalize the TTF model in the software maintenance context
• Task Model - Vessey's debugging model (planning, knowledge building, diagnosis, modification activities) plus coordination
• Technology Model - Henderson & Cooprider Functional Case Technology Model (Production and Coordination functionality)
December 14, 2002 Diane M. Strong, WPI 5
Dimensions of Fit • Fit along two dimensions
– Production Fit: how well the tool’s production functions support software maintenance activities
– Coordination Fit: how well the tool’s coordination functions support maintenance coordination activities
• Compute Fit using an interaction approach (Venkatramen, 1989)
(Dishaw & Strong, 1998)
December 14, 2002 Diane M. Strong, WPI 6
2. Add Experience to TTF
Operationalize Individual Abilities as:
– experience with the task– experience with the technology
Tool experience and its interaction with tool characteristics is significant
Task experience not significant
Adjusted R2 of 0.63(Dishaw & Strong, Forthcoming)
December 14, 2002 Diane M. Strong, WPI 7
3. Combined TAM and TTF
• TAM: beliefs about the technology, i.e., perceived usefulness and perceived ease of use
• TTF: matching of the technology to the needs of the task to deliver benefits
• TAM + TTF: addresses both technology beliefs and rationally computed fit to task– Tool experience as an individual ability
– Path model, rather than regression
– Fit as latent variable, rather than computed as interaction
December 14, 2002 Diane M. Strong, WPI 8
TTF-TAM Combined Model Intention
to Use Tool
Attitude Towards
Use
Perceived Ease of
Use Perceived Usefulness
Actual Tool Use
Task- Technology
Fit Tool
Experience
Task Characteristics
Tool Functionality
TAM
TTF
December 14, 2002 Diane M. Strong, WPI 9
Combined TAM / TTF Results
Better results than either TAM or TTF alone
Utilization variance explained:
• 36% with TAM
• 41% with TTF
• 51% with TAM/TTF
(Dishaw and Strong, 1999)
December 14, 2002 Diane M. Strong, WPI 10
4. Add Computer Self-efficacy(Work-in-progress)
• CSE may be a better predictor of individual ability for new tools than is tool experience
• Generalize TTF assessment beyond software maintenance tasks and tools – Develop an instrument for assessing problem-solving
tasks, and the support of such tasks with software
– Test previous TTF and TAM/TTF models with a new dataset
December 14, 2002 Diane M. Strong, WPI 11
Computer Self-Efficacy
• Derived from the Social Cognition literature, and is based on Bandura’s work on self-efficacy
• A specialized definition of Self-efficacy, i.e., a person’s belief in their ability to accomplish a specific task
• A judgment of one’s ability to use a computer
December 14, 2002 Diane M. Strong, WPI 12
Adding CSE to TTF/TAM
Perceived Ease of
Use Perceived Usefulness
Task- Technology
Fit
Computer Self-Efficacy
TAM
TTF
December 14, 2002 Diane M. Strong, WPI 13
Model Operationalization
• Software maintenance TTF is generalized by changing the questionnaire items since– Task model is well grounded in the problem
solving and cognitive science literature
– Technology model is grounded in the literature on information technology support functionality
• Add Compeau & Higgins (1995) 10-item, single factor measure of CSE
December 14, 2002 Diane M. Strong, WPI 14
Item and Scale Testing
• Item Testing using a panel of faculty, advanced students, and professionals
• Pilot Study using a small number students and professionals in the university
December 14, 2002 Diane M. Strong, WPI 15
Data Collection• Use revised instrument
• Subjects are students in several classes after the completion of an ordinary assignment
• Currently, have 136 data points from:– Operations Management simulation class doing
modeling
– Programming class doing 3 GL program maintenance
– Programming class doing OO program maintenance
– Business analysis class doing statistical modeling
December 14, 2002 Diane M. Strong, WPI 16
Data Analysis
Using Amos 4.0, test the models
1. TTF
2. TTF plus CSE
3. Combined TAM/TTF
4. Combined TAM/TTF plus CSE
Have results for Models 1 and 2
December 14, 2002 Diane M. Strong, WPI 17
Task
.56mode4
.45kbe3
.53plane2
.70
diage1
Tech.76
transe7
.41
analysise6 .64
.48
construct e8
.20check e9
.66
utilization
.44
.56
.55
.31
Fit
-.16
-.48
e10
e12
.38
.75
.84
.73
.69.70
.87
.67
General TTF Model
•Chi Sq. 26.77, d.f. 17, p=0.061
•AGFI = 0.89, GFI = 0.95
December 14, 2002 Diane M. Strong, WPI 18
Task
.56
mode4
.75
.45
kbe3
.67
.53
plane2 .73
.70
diage1.84
Tech.80
transe7
.39
anylse6.62
.52
const e8.18
check e9
.82
Utilization
.72
.42
.41
.26
.35
Fit
-.44
-.38
.53
e10
e12
.37
self eff
.46
.46
.36
.41
csee11
.64
.89
.43
General TTF Model with CSE
•Chi Sq. 27.24, d.f. 22, p=0.202
•AGFI = 0.91, GFI = 0.96
December 14, 2002 Diane M. Strong, WPI 19
Lessons for a Unified Model:Importance of Task
• Traditional HCI focuses on Usability, with little or no Task emphasis
• TAM adds Usefulness, which implicitly includes Task
• TTF has explicit Task focus, which adds to the explanatory power
December 14, 2002 Diane M. Strong, WPI 20
Lessons for a Unified Model:The Fit Construct
• Beyond production and coordination Fit to additional dimensions of Fit
• Beyond a point estimate of Fit to a process of Fitting over time (as in implementation)
• Beyond individual level models (TTF, TAM) to organizational level models, e.g., for Enterprise systems
December 14, 2002 Diane M. Strong, WPI 21
Lessons for a Unified Model:Experience and CSE
• Measure Experience and Self-efficacy for both Task and Technology
• Self-efficacy theory: As Experience increases, Experience dominates abilities as measured by Self-efficacy– Need to better understand relationship between
Experience and Self-efficacy
December 14, 2002 Diane M. Strong, WPI 22
References to the StudiesStudy 1: Dishaw, M. T. and D. M. Strong, "Supporting Software Maintenance
with Software Engineering Tools: A Computed Task-Technology Fit Analysis", Journal of Systems and Software, Vol. 44, No. 2, December 1998, pp. 107-120.
Study 2: Dishaw, M. T. and D. M. Strong, "The Effect of Task and Tool Experience on Maintenance CASE Tool Usage", Information Resources Management Journal, Forthcoming.
Study 3: Dishaw, M. T. and D. M. Strong, "Extending the Technology Acceptance Model with Task-Technology Fit Constructs", Information & Management, Vol. 36, No. 1, July 1999, pp. 9-21.
Study 4 (in-progress): Dishaw, M. T., D. M. Strong, and D. B. Bandy, “Extending the Task-Technology Fit Model with Self-Efficacy Constructs”, Proceedings of the Americas Conference on Information Systems, August 9-11, 2002, Dallas, TX, pp. 1021-1027.