Chatbots adoption intention in public sector in Malaysia from the perspective of TOE framework. The moderated and mediation model

Authors

Ramizatunnisah Jais, Faculty of Business, Economy and Social Development, Universiti Malaysia Terengganu, Terengganu, Malaysia
Abdul Hafaz Ngah, Faculty of Business, Economy and Social Development, Universiti Malaysia Terengganu, Terengganu, Malaysia
Samar Rahi, Hailey College of Banking and Finance, University of the Punjab, Lahore, Pakistan
Aamir Rashid, York College, City University of New York, New York, USAFollow
Syed Zamberi Ahmad, School of Management, Canadian University Dubai, Dubai, United Arab Emirates
Safiek Mokhlis, Faculty of Business, Economy and Social Development, Universiti Malaysia Terengganu, Terengganu, Malaysia

Document Type

Article

Publication Date

Fall 9-19-2024

Abstract

Purpose – This paper aims to investigate the motivating factors for Malaysian governmental agencies (MGAs) to embrace chatbot technology.

Design/methodology/approach – Based on the technology-organisation-environment (TOE) framework, using purposive and snowball sampling techniques, 262 online data from the MGA top management were gathered. Smart PLS4 was employed to test the hypotheses of the study.

Findings – The findings demonstrated positive relationships between technological readiness (TR), big data analytics (BDA), organisational readiness (OR), organisational learning capabilities (OLC) and governmental policies (GP) concerning chatbot adoption intention and also the relationship GP with OR. A mediating effect was also observed, which indicated the OLC role in positively mediating BDA, the OR role in positively mediating OLC and the OR role in positively mediating GP with OR and OLC as sequential mediators in the relationship between BDA and chatbot adoption intention. Furthermore, the presence of citizen demand (CD) strengthened the relationship between TR, OR and chatbot adoption intention.

Research limitations/implications – This study was limited to Malaysian federal government agencies who still not adopting Chatbots. Practical implications – The findings offer valuable insight into factors affect the adoption of chatbots among Malaysian government agencies. Stakeholders, including department heads, can use these findings to strategically enhance counter service by promoting chatbot adoption.

Originality/value – The study demonstrated that the TOE framework was effective in identifying the factors contributing to the decision-making process for adopting chatbots across MGAs. Organisational readiness and organisation learning capability was found to sequentially mediate the relationship between big data analytic and intention to adopt chatbot. Citizen demand was found to have moderation effect on the relationship between organisational readiness and technological readiness towards the intention to adopt a chatbot.

Comments

Originally published in Journal of Science and Technology Policy Management © Emerald Publishing Limited 2053-4620 DOI 10.1108/JSTPM-04-2024-0151