The role of organizational culture and voluntariness in the adoption of artificial intelligence for disaster relief operations

Abstract

PurposeThe 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).Design/methodology/approachWe 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, we employed partial least squares structural equation modeling (PLS-SEM).FindingsOur findings confirm that resources (time, money and skills) significantly influence the behavioral intentions related to the adoption of AI tools for DRO. Additionally, we identified that the behavioral intentions positively translate into the actual adoption of AI tools.Research limitations/implicationsOur 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.Originality/valueOur 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.

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“…, 2018); (5) automate quality management investigation and recommendation, manage supply, logistics and fleet assets (logistics or transport and most industries) (Di Francescomarino and Maggi, 2020; Rubin et al. , 2010; Sikdar, 2018); and (6) and to the rescue, helping to process natural and man-made disasters-related data in ways that support informed disaster management (disaster relief operation) (Behl et al. , 2021).…”

Examining the relationship between fear of COVID-19, intolerance for uncertainty, and cyberloafing: A mediational model

“…Moreover, continuous threats outside the workplace deplete individuals’ personal resources (both cognitive and emotional). This vicious loss cycle may lead to undermining employees’ ability to assign significant energy to other cognitive consuming tasks and work assignments ( Hobfoll et al, 2001 , Behl et al, 2021 , Behl et al, 2021 ). This, in turn, may increase counterproductive behaviors such as cyberloafing.…”

Integrating artificial intelligence into a talent management model to increase the work engagement and performance of enterprises

“…Organizational culture is key to building an artificial intelligence-driven enterprise (Munir et al, 2022). Enterprises that manage to build a positive artificial intelligence culture and an inclusive and inspiring environment will successfully manage change and attract all their employees (Behl et al, 2021). The leader must create a culture that will allow the enterprise to develop and adapt to new business realities quickly.…”

“…It is important to create a new organizational culture that encourages experimentation and continuous innovation, and the development of new solutions. This in turn leads to increased performance of the enterprise (Behl et al, 2021). Building a culture that supports innovation with artificial intelligence affects competitiveness.…”