Events at The University of Manchester
  • University home
  • Events
  • Home
  • Exhibitions
  • Conferences
  • Lectures and seminars
  • Performances
  • Events for prospective students
  • Family events
  • All Events

Mercury Talk: Data-Driven Modelling of Technology Acceptance: A Machine Learning Perspective

Dates:11 December 2019
Times:14:00 - 15:00
What is it:Seminar
Organiser:Department of Computer Science
Who is it for:University staff, Adults, Current University students
Speaker:Asim Alwabel
See travel and contact information
Add to your calendar

More information

  • Computer Science Mercury Talk

Other events

  • In category "Seminar"
  • In group "(CS) Computer Science seminar series"
  • By Department of Computer Science

Join us for the next Computer Science Mercury Talk with speaker Asim Alwabel in Kilburn L.T 1.5

Forecasting and understanding technology adoption have dominated research of Information Systems (IS) for more than two decades. Although structural equation modelling is suitable for explanatory modelling, it was regarded by majority of IS research as a predictive technique. On the other hand, despite development and utility of predictive analytics, its use in estimating technology usability remains scarce. This research demonstrates a unique data driven approach utilising linear and non-linear machine learning (ML) techniques, predictive analytics-based modelling, to advance technology adoption modelling, assess its predictability, evaluate relevance of its current determinants, and introduce new ones. Inspired by current literature, the resulting model comprised 37 features and was tested on 32 technologies with heterogeneous subjects. Content validity of the model was attained applying Twitter API, text-mining technique and interviews. Before modelling, the discriminant validity was accomplished applying multitrait-multimethod analysis. Performance of the proposed model was estimated employing multiple linear regression, k-nearest neighbour, decision tree, multilayer perceptron, and support vector machine with mean absolute percentage error as loss metric. The model was benchmarked against the current literature to highlight differences and similarities. As a result, ML-based modelling revealed the distance between theory and practice.

Speaker

Asim Alwabel

Role: PhD student

Organisation: University of Manchester

Travel and Contact Information

Find event

L.T 1.5
Kilburn Building
Manchester

Contact event

0161 275 6166

Share / follow event

Contact us

  • +44 (0) 161 306 6000

Find us

The University of Manchester
Oxford Rd
Manchester
M13 9PL
UK

Connect with the University

  • Facebook page for The University of Manchester
  • Twitter page for The University of Manchester
  • YouTube page for The University of Manchester
  • Google+ page for The University of Manchester
  • Pinterest page for The University of Manchester

  • Privacy /
  • Copyright notice /
  • Accessibility /
  • Freedom of information /
  • Charitable status /
  • Royal Charter Number: RC000797
  • Close menu
  • Home
    • Featured events
    • Today's events
    • The Whitworth events
    • Manchester Museum events
    • Jodrell Bank Discovery Centre events
    • Martin Harris Centre events
    • The John Rylands Library events
    • Exhibitions
    • Conferences
    • Lectures and seminars
    • Performances
    • Events for prospective students
    • Family events
    • All events