Understanding Low-Code Evolution, Adoption and Ecosystem for Software Development
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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ICSOB-C 2024, Software Business: PhD Retreat and Posters & Demos Track 2024: Companion Proceedings of the 15th International Conference on Software Business (PhD Retreat, Posters & Demos Track), Utrecht, the Netherlands, November 18–20, 2024. Hrsg. / Deekshitha; Rodrigo Santos; Dron Khanna; Edona Elshan. Aachen: Rheinisch-Westfälische Technische Hochschule Aachen, 2025. (CEUR workshop proceedings; Band 3921).
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - Understanding Low-Code Evolution, Adoption and Ecosystem for Software Development
AU - Naqvi, Syed Asad Ali
AU - Drews, Paul
N1 - Conference code: 15
PY - 2025
Y1 - 2025
N2 - Faced with the high demands of digital transformation, organizations have turned to low-code as a solution, utilizing visual programming to meet these challenges. Given that low-code is an emerging research phenomenon, there is little understanding of its origins, adoption motives and approaches, and its ecosystem. In my PhD thesis, I use qualitative and visualization methods to address these research gaps. My work has five contributions. First, I developed an intellectual map of the low-code literature and identified related research streams. Second, I created a model underscoring aspects that support or hinder low-code adoption. Third, I provide use cases demonstrating low-code adoption in established organizations and its use in the public sector during crises. Fourth, I identify the technology partnerships forming the low-code ecosystem. Fifth, I investigate the impact of generative AI on low-code adoption and whether it presents a threat to the low-code ecosystem.In conclusion, I outline potential directions for future research.
AB - Faced with the high demands of digital transformation, organizations have turned to low-code as a solution, utilizing visual programming to meet these challenges. Given that low-code is an emerging research phenomenon, there is little understanding of its origins, adoption motives and approaches, and its ecosystem. In my PhD thesis, I use qualitative and visualization methods to address these research gaps. My work has five contributions. First, I developed an intellectual map of the low-code literature and identified related research streams. Second, I created a model underscoring aspects that support or hinder low-code adoption. Third, I provide use cases demonstrating low-code adoption in established organizations and its use in the public sector during crises. Fourth, I identify the technology partnerships forming the low-code ecosystem. Fifth, I investigate the impact of generative AI on low-code adoption and whether it presents a threat to the low-code ecosystem.In conclusion, I outline potential directions for future research.
KW - Business informatics
KW - low-code
KW - Low-code platforms
KW - low-code ecosystem
KW - technology adaption
KW - software development
UR - http://www.scopus.com/inward/record.url?scp=85218470263&partnerID=8YFLogxK
M3 - Article in conference proceedings
T3 - CEUR workshop proceedings
BT - ICSOB-C 2024, Software Business: PhD Retreat and Posters & Demos Track 2024
A2 - , Deekshitha
A2 - Santos, Rodrigo
A2 - Khanna, Dron
A2 - Elshan, Edona
PB - Rheinisch-Westfälische Technische Hochschule Aachen
CY - Aachen
T2 - 15th International Conference on Software Business - ICSOB 2024
Y2 - 18 November 2024 through 20 November 2024
ER -