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"Intelligence operations"
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Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions
In this digital era, data is new oil and artificial intelligence (AI) is new electricity, which is needed in different elements of operations management (OM) such as manufacturing, product development, services and supply chain. This study explores the feasibility of AI utilization within an organization on six factors such as job-fit, complexity, long-term consequences, affect towards use, social factors and facilitating conditions for different elements of OM by mining the collective intelligence of experts on Twitter and through academic literature. The study provides guidelines for managers for AI applications in different components of OM and concludes by presenting the limitations of the study along with future research directions.
Journal Article
The revisionists
An agent from the future where all the world's problems have been solved goes back in time to ensure that every disaster throughout history runs its course.
Book
Adoption and use of AI tools: a research agenda grounded in UTAUT
This paper is motivated by the widespread availability of AI tools, whose adoption and consequent benefits are still not well understood. As a first step, some critical issues that relate to AI tools in general, humans in the context of AI tools, and AI tools in the context of operations management are identified. A discussion of how these issues could hinder employee adoption and use of AI tools is presented. Building on this discussion, the unified theory of acceptance and use of technology is used as a theoretical basis to propose individual characteristics, technology characteristics, environmental characteristics and interventions as viable research directions that could not only contribute to the adoption literature, particularly as it relates to AI tools, but also, if pursued, such research could help organizations positively influence the adoption of AI tools.
Journal Article
An American spy
When the CIA's Department of Tourism is dismantled by an elaborate Chinese intelligence scheme that has caused numerous agent deaths, survivor Milo Weaver is placed at risk by his former boss, Alan Drummond, who uses one of Milo's aliases to exact revenge.
Book
Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics
This study explores digital business transformation through the lens of four emerging technology fields: artificial intelligence, blockchain, cloud and data analytics (i.e., ABCD). Specifically, the study investigates the operations and value propositions of these distinct but increasingly converging technologies. Due to the dynamic nature of innovation, the potential of this ABCD hybridization, integration, recombination and convergence has yet to be considered. Using a multidisciplinary approach, the findings of the study show wide-reaching and diverse applications among a variety of vertical sectors, presenting exploratory research avenues for future investigation. The study also highlights the practical implications of these new technologies.
Journal Article
Disruptive technologies in agricultural operations: a systematic review of AI-driven AgriTech research
The evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of agricultural technology (AgriTech) with applications of artificial intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations.
Journal Article
The nearest exit
Forced to prove his loyalty to his new bosses in order to return to the CIA, reluctant spy Milo Weaver finds himself caught between the self-interests of patriots and traitors.
BOOK
Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics
Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.
Journal Article