Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Modeling utilization of planned information technology

T D Stettheimer1, A D Cleveland

  • 1University of North Texas, Denton, USA.

Proceedings. AMIA Symposium
|February 3, 1999
PubMed
Summary

Understanding technology adoption requires examining user, system, task, and organizational factors. Measuring interaction effects between these elements can predict technology utilization and guide future technology implementation.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same journal

Progressive display of very high resolution images using wavelets.

Proceedings. AMIA Symposium·2002
Same journal

The Chronus II temporal database mediator.

Proceedings. AMIA Symposium·2002
Same journal

Gene expression levels in different stages of progression in oral squamous cell carcinoma.

Proceedings. AMIA Symposium·2002
Same journal

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

Proceedings. AMIA Symposium·2002
Same journal

Filtering for medical news items using a machine learning approach.

Proceedings. AMIA Symposium·2002
Same journal

Enriching the structure of the UMLS semantic network.

Proceedings. AMIA Symposium·2002

Area of Science:

  • Information Systems
  • Human-Computer Interaction
  • Organizational Behavior

Background:

  • Technology adoption is influenced by a complex interplay of user, system, task, and organizational characteristics, alongside external factors.
  • Evaluating every individual attribute is impractical for predicting technology utilization.
  • Interaction effects between these entities can serve as a proxy for individual attribute values.

Purpose of the Study:

  • To propose a model for predicting technology utilization based on interaction effects.
  • To offer insights into the relationships between the antecedents of technology utilization.
  • To develop a predictive model and taxonomy for technology adoption and implementation.

Main Methods:

  • Focus on measuring the interaction effects between user, system, task, and organizational characteristics.
  • Utilizing these interaction effects as a proxy for individual attribute values.
  • Developing a predictive model based on the evaluated interaction effects.

Main Results:

  • The proposed model, by evaluating interaction effects, can predict technology utilization.
  • The approach provides a method to understand the relationships among technology use antecedents.
  • A predictive model and taxonomy of variables for technology utilization are established.

Conclusions:

  • Interaction effects are valuable predictors of technology utilization.
  • The model offers a practical approach to understanding and influencing technology adoption.
  • This framework can be applied to predict or manipulate the likelihood of planned technology use.

Related Experiment Videos