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December 14, 2002Diane M. Strong, WPI1 A Unified Model of IT Use Choices: Contributions from TAM, TTF, and CSE Diane M. Strong* Worcester Polytechnic Institute.

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Presentation on theme: "December 14, 2002Diane M. Strong, WPI1 A Unified Model of IT Use Choices: Contributions from TAM, TTF, and CSE Diane M. Strong* Worcester Polytechnic Institute."— Presentation transcript:

1 December 14, 2002Diane M. Strong, WPI1 A Unified Model of IT Use Choices: Contributions from TAM, TTF, and CSE Diane M. Strong* Worcester Polytechnic Institute Invited Presentation First Annual Workshop on HCI Research in MIS Barcelona, Spain 2002 *This is joint work with Mark T. Dishaw, University of Wisconsin Oshkosh

2 December 14, 2002Diane M. Strong, WPI2 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

3 December 14, 2002Diane M. Strong, WPI3 Task-Technology Fit Models

4 December 14, 2002Diane M. Strong, WPI4 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)

5 December 14, 2002Diane M. Strong, WPI5 Dimensions of Fit Fit along two dimensions –Production Fit: how well the tools production functions support software maintenance activities –Coordination Fit: how well the tools coordination functions support maintenance coordination activities Compute Fit using an interaction approach (Venkatramen, 1989) (Dishaw & Strong, 1998)

6 December 14, 2002Diane M. Strong, WPI6 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 R 2 of 0.63 (Dishaw & Strong, Forthcoming)

7 December 14, 2002Diane M. Strong, WPI7 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

8 December 14, 2002Diane M. Strong, WPI8 TTF-TAM Combined Model

9 December 14, 2002Diane M. Strong, WPI9 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)

10 December 14, 2002Diane M. Strong, WPI10 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

11 December 14, 2002Diane M. Strong, WPI11 Computer Self-Efficacy Derived from the Social Cognition literature, and is based on Banduras work on self-efficacy A specialized definition of Self-efficacy, i.e., a persons belief in their ability to accomplish a specific task A judgment of ones ability to use a computer

12 December 14, 2002Diane M. Strong, WPI12 Adding CSE to TTF/TAM

13 December 14, 2002Diane M. Strong, WPI13 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

14 December 14, 2002Diane M. Strong, WPI14 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

15 December 14, 2002Diane M. Strong, WPI15 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

16 December 14, 2002Diane M. Strong, WPI16 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

17 December 14, 2002Diane M. Strong, WPI17 General TTF Model Chi Sq , d.f. 17, p=0.061 AGFI = 0.89, GFI = 0.95

18 December 14, 2002Diane M. Strong, WPI18 General TTF Model with CSE Chi Sq , d.f. 22, p=0.202 AGFI = 0.91, GFI = 0.96

19 December 14, 2002Diane M. Strong, WPI19 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

20 December 14, 2002Diane M. Strong, WPI20 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

21 December 14, 2002Diane M. Strong, WPI21 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

22 December 14, 2002Diane M. Strong, WPI22 References to the Studies Study 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 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 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


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