Vincent Charles , Ali Emrouznejad , Werner H. Kunz
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Advancements in Artificial Intelligence-based prescriptive and cognitive analytics for business performance: a special issue editorial
The rapid advancement of Artificial Intelligence (AI) is transforming business decision-making across industries. AI-based prescriptive and cognitive analytics offer significant potential to enhance decision-making, optimise performance, and create new avenues for value creation. This special issue explores the state-of-the-art advancements in these analytics and their business implications. We introduce the Analytics Onion as a conceptual foundation, comprising three interrelated layers: Perspective Analytics, Responsible Analytics, and the Descriptive-Diagnostic-Predictive-Prescriptive-Cognitive Analytics framework. The Analytics Onion captures the interplay between human judgment, ethics, analytical rigour, and AI techniques. The featured papers exemplify these layers through various topics, namely humanoid service robots, business location optimisation, ESG evaluation, energy efficiency, customer churn, prediction-led prescription, innovation culture, user satisfaction with AI, responsible AI in business models, and executives’ emotions influencing firm value. We highlight emerging opportunities and challenges and offer a forward-looking research agenda to guide future developments in this evolving field.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.