The Electronic Journal of Information Systems Evaluation provides critical perspectives on topics relevant to Information Systems Evaluation, with an emphasis on the organisational and management implications
For general enquiries email
Click here to see other Scholarly Electronic Journals published by API
For a range of research text books on this and complimentary topics visit the Academic Bookshop
Journal Issue
Volume 23 Issue 1 / Feb 2020  pp1‑167

Editor: Prof Shaun Pather

Download PDF (free)

Evaluating Factors Affecting User Satisfaction in University Enterprise Content Management (ECM) Systems  pp1‑16

Daha Tijjani Abdurrahaman, Acheampong Owusu, Akeem Soladoye Bakare

Look inside Download PDF (free)

Cultural Influence on e‑Government Development  pp17‑33

Sushant Kumar, Kuldeep Baishya, Pradip H Sadarangani, Harsh V Samalia

Look inside Download PDF (free)

Sandbox Environments in an ERP System Context: Examining User Attitude and Satisfaction  pp34‑44

Tim Klaus, Chuleeporn Changchit

Look inside Download PDF (free)

Big Data Analytics Usage and Business Performance: Integrating the Technology Acceptance Model (TAM) and Task Technology Fit (TTF) Model  pp45‑64

Hemlata Gangwar

Look inside Download PDF (free)


The purpose of this study is to propose a unified model integrating both the technology acceptance model (TAM) and task technology fit (TTF) model, and explore the organizational and environmental fit of the integrated model in order to investigate usage of Big Data Analytics and its effect on business performance. A questionnaire was used to collect data from 280 companies in CPG & Retail, Healthcare, Banking and Telecom in India. The data were analysed using exploratory and confirmatory factor analyses. Further, structural equation modelling was used to test the proposed model. The findings show that the research model for integrating the TAM for adoption and TTF model for utility provides a more comprehensive understanding of Big Data Analytics usage. The study identified task technology fit , individual technology fit, organizational data fit, organizational process fit, and business strategy fit as Tidd important variables for affecting Big Data Analytics usage using perceived ease of use (PEOU) and perceived usefulness (PU) as mediating variables. Competitive fit and partner support/customer fit were also found to be directly affecting Big Data Analytics usage, which in turn has significant influence on business performance. The model explained 71.4 percent of Business performance. The integrated model may be used as a guideline to ensure a positive outcome of Big Data Analytics usage in organizations. This study combined both the key ideas of TAM and TTF to show that they were necessary in predicting Big Data Analytics usage and business performance. 


Keywords: Big Data Analytics, Technology Acceptance Model, Task Technology Fit, Technological Fit, Organizational Fit, Environmental Fit


Share |
O2O Adoption Benefits: A Managerial Perspective of Customer Benefits  pp65‑78

Jiwat Ram, Ashokkumar Manoharan, Siyao Sun

Look inside Download PDF (free)

Factors Influencing Online Game‑Based Learning Effectiveness  pp79‑95

Segomotso Mosiane, Irwin Brown

Look inside Download PDF (free)

Augmenting the Business Intelligence Lifecycle Model with Usability: Using eye‑Tracking to Discover the why of Usability Problems  pp96‑111

T.R. Beelders, J.E. Kotzé

Look inside Download PDF (free)

The Impact of IT‑Business Alignment on SME Performance: The Mediating Effects of Strategic Collaboration, Coordination, and Responsiveness  pp112‑125

Rui Bi

Look inside Download PDF (free)

The Relationship Between Strategic Information Systems Planning (SISP) and Facilitators to Achieve Successful Business Outcomes in South Korean Organizations  pp126‑149

Jungho Yang, Nelson K. Y. Leung, Bill Young

Look inside Download PDF (free)

Information Systems Values: A Study of the Intranet in Three French Higher Education Institutions  pp150‑167

Philippe Cohard

Look inside Download PDF (free)