Speech-Act-Based Adaptive Case Management

Tenschert J (2019)

Publication Language: English

Publication Type: Thesis

Publication year: 2019

URI: https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/12543


With a focus on their pragmatic intention, speech acts have been proposed to improve the design of interactive systems for decades. Yet, early prototypes were isolated applications with limited inferencing capabilities. Alongside, the share of knowledge work in the workforce rapidly increased, and knowledge-intensive processes became customary. The objectives, interactions, intermediate results, and final outcomes of knowledge-intensive processes are typically scattered across many systems. Often, important information is not documented at all. Adaptive case management is intended for emerging, knowledge-intensive processes, where the course of action unfolds as more information becomes available. We apply speech act theory in adaptive case management, since the representation of interactions considers the context they are performed in, regardless of whether this context is a structured, semi-structured, or ad-hoc process. This common representation enables inference regardless of whether an interaction or activity is modeled a priori or documented ad hoc, and ultimately helps in resolving the issue of scattered process information that is loosely coupled by the knowledge workers performing the process. This thesis verifies that speech acts are prevalent and diverse in actual business processes. Moreover, it substantiates that a manageable set of common speech acts for modeling and ad-hoc documentation is applicable in representative knowledge work domains. It investigates the requirements and expectations of adaptive case management in a more fine-grained classification of the knowledge workers to be supported. This way, for complex work with high interdependence, it results in a speech-act-based approach of adaptive case management, that does not require a predefined process model for knowledge-intensive processes or cases. It initially expects activities to be ad hoc, and additional models to simplify or automate routine work can be introduced on demand. It establishes speech-act-based techniques for semantic annotation, modeling, and business rules for compliance monitoring as well as for integration. Thereby, the approach combines structured, semi-structured, and ad-hoc work, while providing guard rails, and line markings for one consolidated, knowledge-intensive process.

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How to cite


Tenschert, J. (2019). Speech-Act-Based Adaptive Case Management (Dissertation).


Tenschert, Johannes. Speech-Act-Based Adaptive Case Management. Dissertation, 2019.

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