Search results

The global health crisis represents an unprecedented opportunity for the development of artificial intelligence (AI) solutions. This paper aims to integrate explainable AI into the decision-making process in emergency scenarios to help mitigate the high levels of complexity and uncertainty associated with these situations. An AI solution is designed to extract insights into opioid overdose (OD) that can help government agencies to improve their medical emergency response and reduce opioid-related deaths.

This paper employs the design science research paradigm as an overarching framework. Open-access digital data and AI, two essential components within the digital transformation domain, are used to accurately predict OD survival rates.

The proposed AI solution has two primary implications for the advancement of informed emergency management. Results show that it can help not only local agencies plan their resources for timely response to OD incidents, thus improving survival rates, but also governments to identify geographical areas with lower survival rates and their primary contributing factor; hence, they can plan and allocate long-term resources to increase survival rates and help in developing effective emergency-related policies.

This paper illustrates that digital transformation, particularly open-access digital data and AI, can improve the emergency management framework (EMF). It also demonstrates that the AI models developed in this study can identify opioid OD trends and determine the significant factors improving survival rates.

The purpose of this paper is to focus on an information technology (IT) deployment project in the specific field of agricultural cooperatives. It also aims to underline the importance of the IT implementation phase, but also the pre-implementation phase.

A four-year canonical action research project was conducted within a network of more than 300 agricultural cooperatives. Research was carried out both during the IT implementation and after deployment. Key information was gathered through unstructured and unofficial interviews, observations, field notes, meetings, focus groups, and documentary analysis.

Despite user resistance behavior, the findings show that information systems (IS) implementation may lead to unexpected results that extend beyond the tool’s initial objectives. Indeed, four hidden facets of the tool were revealed: inductor, symbol, pretext, and reference.

Although the research is limited to one single-case study, it puts the emphasis on in-depth research, vs cross-sectional data collection, to analyze the relationship between IT implementation initiatives and organizational intelligence. Furthermore, the authors argue that while IS literature has separately developed related theories (actor-network theory, competitive intelligence), the authors conceptualize a whole theoretic system interrelating the two above-stated theories.

The implication for IS practitioners is that, by focusing only on experiences that have occurred during IT implementation, one may disregard critical information, behaviors and knowledge from unforeseen effects that have occurred after implementation. In future IT projects, IS managers therefore need to capitalize on post-implementation knowledge, through sociology of translation and competitive intelligence, in order to anticipate potential diversions from the initial objectives. Finally, while most IT implementation methods tend naturally to manage resistance maximize users’ satisfaction and to reduce potential resistance, the authors support an alternative approach. It consists into enhancing resistance in order to anticipate and resolve latent resistance behaviors directly or indirectly related to the project.

Despite widespread literature on resistance, appropriation or acceptance during IT projects, there is little research that addresses the impact of IT projects on organizational intelligence, and the kind of behaviors that lead to its failure or success. In the case, the implemented IT tool revealed hidden structural and organizational roles, which were unanticipated by IT designers and managers.