Artificial Intelligence Innovation Related Factors Affecting Organizational Performance

Authors

  • Jalal Ismail Mohammed Sharif Ismail
  • M.N. Muhammad

Keywords:

AI-related innovation factors model

Abstract

Organisations paid more attention to the innovations of artificial intelligence (AI) technology to improve the organizational performance. Hence, using AI-related innovations to support the organization requires understanding of factors affecting organizational performance. Thus, this paper presents the development of PLS-SEM model of AI-related innovations factors that affect the organisational performance. The study identified 21 innovation AI-related factors that were clustered into four groups namely process innovation; management capabilities; personal expertise and organization structure. The model comprised of four exogenous constructs of the innovation factors and one endogenous construct of organisational performance. The data used to develop the model was derived from 384 valid responses of a questionnaire survey amongst the employees of three government organizations in Dubai, which are Dubai Police, Dubai Electricity & Water Authority Dewa, and Emirates Integrated Telecommunications Company. The survey adopted simple random sampling technique in respondents’ selection. The model was developed in SmartPLS software and was evaluated at the measurement and structural components of the model. It was found that the model has achieved its goodness-of-fit, GoF criteria of 0.596 which indicates that the model has substantial validating power. The hypothesis testing results found that three out of four relationships are significant which are having t-value and p-value above the cut-off values. The significant relationships are organization structure, personal expertise and process innovation. However, the unsignificant relationship is management capabilities affecting the organisational performance. This is due to the characteristics of the collected data which is not strong enough to establish significant relationship as what have been hypothesized. The findings are contributions to any parties that involved in the application of AI innovation to improve organisational performance.

Downloads

Download data is not yet available.

Downloads

Published

09-05-2022

Issue

Section

Special Issue 2022: Knowledge Management

How to Cite

Jalal Ismail Mohammed Sharif Ismail, & M.N. Muhammad. (2022). Artificial Intelligence Innovation Related Factors Affecting Organizational Performance . International Journal of Sustainable Construction Engineering and Technology, 13(2), 203-212. https://penerbit.uthm.edu.my/ojs/index.php/IJSCET/article/view/11300