Decision-Making in Knowledge-intensive Processes: The Case of Value Ascription and Goal Processing

• Published in: Conceptual Modeling Vol. 11788; pp. 363 - 377
• Main Authors: Richetti, Pedro H. Piccoli, Baião, Fernanda Araujo, Campos, Maria Luiza M.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2019; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Goal Processing; Knowledge-intensive Process; Value Ascription
• ISBN: 9783030332228; 3030332225
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-33223-5_30

Knowledge-intensive Processes (KiPs) are a range of business processes which are rather unpredictable, highly variable, and very dependent on human knowledge and collaboration. Despite the recent efforts to provide comprehensive support for KiP management, there are still few discussions about how human aspects influence process execution. For example, in a disaster management KiP, why someone decides to take action when the action itself may put their own life at stake? This work aims to provide an ontological background for properly understanding human decision-making actions by analyzing cognitive states of agents participating in a KiP. We introduce a novel perspective of decisions seen as value and risk experiences, and a formal characterization of agents’ beliefs in a goal processing framework, which paves the way for precisely and systematically explaining decision-making towards process goals. We claim that these value-oriented conceptual models are capable of describing the rationale of decision-making in KiPs in terms of value and risk ascriptions and by a set of belief types that supports goal processing. In a practical example, the proposed conceptual models were applied in the analysis of a real-life KiP instance from the air traffic control domain.