The study offers a fresh perspective in understanding how the organizational culture and perspectives of government officials influence their inclinations to adopt AI for disaster relief operations.
Authors
Abhishek Behl, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Meena Chavan, Macquaire University, North Ryde, Australia.
Kokil Jain, Amity International Business School, Amity University, Noida, India.
Isha Sharma, School of Administrative Studies, York University, Toronto, Canada.
Vijay Edward Pereira, People and Organisations, NEOMA Business School ‐ Campus de Reims, Reims, France.
Justin Zuopeng Zhang, University of North Florida, Jacksonville, Florida, USA.
Summary
The study explores the readiness of government agencies to adopt artificial intelligence (AI) to improve the efficiency of disaster relief operations (DRO). For understanding the behavior of state-level and national-level government agencies involved in DRO, this study grounds its theoretical arguments on the civic voluntarism model (CVM) and the unified theory of acceptance and use of technology (UTAUT).
The researchers collected the primary data for this study from government agencies involved in DRO in India. To test the proposed theoretical model, we administered an online survey questionnaire to 184 government agency employees. To test the hypotheses, the researchers employed partial least squares structural equation modeling (PLS-SEM).
Our findings confirm that resources (time, money and skills) significantly influence the behavioral intentions related to the adoption of AI tools for DRO. Additionally, the researchers identified that the behavioral intentions positively translate into the actual adoption of AI tools.
The study provides a unique viewpoint suited to understand the context of the adoption of AI in a governmental context. Companies often strive to invest in state-of-the-art technologies, but it is important to understand how government bodies involved in DRO strategize to adopt AI to improve efficiency.
The study offers a fresh perspective in understanding how the organizational culture and perspectives of government officials influence their inclinations to adopt AI for DRO. Additionally, it offers a multidimensional perspective by integrating the theoretical frameworks of CVM and UTAUT for a greater understanding of the adoption and deployment of AI tools with organizational culture and voluntariness as critical moderators.
Published in: International Journal of Manpower
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