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Morphological analysis for design science research: The case of human-drone collaboration in emergencies


Dolata, Mateusz; Aleya, Kiram Ben (2022). Morphological analysis for design science research: The case of human-drone collaboration in emergencies. In: Drechsler, Andreas; Gerber, Aurona; Hevner, Alan. The Transdisciplinary Reach of Design Science Research. DESRIST 2022. Cham: Springer, 17-29.

Abstract

Drones are becoming pervasive in private and professional settings. The engineering of human-drone collaboration poses unique challenges. Specifically, drones’ distinctive capabilities yield a vast design space. Yet, the relevant guidance is scattered across literature such that an overview of various design dimensions is missing. This paper synthesizes adequate research and provides an overview of essential design dimensions in the form of a morphological box (MB) to support designers of drones for emergencies. Using this MB, practitioners and researchers become aware of design decisions they will have to make when designing drones or collaboration between drones and humans. It prevents fragmented or partial perspectives on drones design and provides a basis for structured, holistic design explorations. Using the case of drones, we discuss the potential of morphological analysis for design science research (DSR). New types of sociotechnical systems involve a vast, multidimensional design space, and singular studies frequently address domain or discipline-specific subsections of this space. We claim that morphological analysis supports a systematic exploration of the design space across disciplinary boundaries and might contribute towards a more transparent and traceable design of DSR artifacts.

Abstract

Drones are becoming pervasive in private and professional settings. The engineering of human-drone collaboration poses unique challenges. Specifically, drones’ distinctive capabilities yield a vast design space. Yet, the relevant guidance is scattered across literature such that an overview of various design dimensions is missing. This paper synthesizes adequate research and provides an overview of essential design dimensions in the form of a morphological box (MB) to support designers of drones for emergencies. Using this MB, practitioners and researchers become aware of design decisions they will have to make when designing drones or collaboration between drones and humans. It prevents fragmented or partial perspectives on drones design and provides a basis for structured, holistic design explorations. Using the case of drones, we discuss the potential of morphological analysis for design science research (DSR). New types of sociotechnical systems involve a vast, multidimensional design space, and singular studies frequently address domain or discipline-specific subsections of this space. We claim that morphological analysis supports a systematic exploration of the design space across disciplinary boundaries and might contribute towards a more transparent and traceable design of DSR artifacts.

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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Theoretical Computer Science
Physical Sciences > General Computer Science
Scope:Discipline-based scholarship (basic research)
Language:English
Date:25 May 2022
Deposited On:25 Apr 2023 11:33
Last Modified:25 Jun 2024 03:38
Publisher:Springer
Series Name:Lecture Notes in Computer Science
Number:13229
ISSN:0302-9743
ISBN:978-3-031-06515-6
OA Status:Green
Publisher DOI:https://doi.org/10.1007/978-3-031-06516-3_2
Official URL:https://link.springer.com/chapter/10.1007/978-3-031-06516-3_2
Other Identification Number:merlin-id:22463
  • Content: Accepted Version
  • Language: English