Artificial Intelligence Innovation Related Factors Affecting Organizational Performance

Author:

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

Abstract

Organisations paid more attentionto the innovations of artificial intelligence (AI)technology to improve the organizational performance. Hence, using AI-related innovations to support the organizationrequires understanding of factors affecting organizational performance. Thus, this paper presents the development of PLS-SEMmodelof AI-related innovations factors that affect the organisational performance. The study identified 21innovation AI-related factors that were clustered into four groups namely process innovation; management capabilities; personal expertise and organization structure.The model comprised of fourexogenous constructs of the innovationfactors and one endogenous construct of organisational performance. The data used to develop the model was derived from 384valid 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 modelhas achieved its goodness-of-fit, GoF criteria of0.596which 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 ismanagement 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.

Publisher

Penerbit UTHM

Subject

Building and Construction,Civil and Structural Engineering,Environmental Engineering

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