Paper Number
ECIS2026-2520
Paper Type
SP
Abstract
Digital innovation (DI) and digital transformation (DT) are interdependent processes shaping how organizations create and capture value from digital technologies. Prior research has offered valuable conceptual insights into their relationship, yet empirical understanding of how these processes interact and evolve over time remains limited. This study presents an exploratory longitudinal single-case investigation of a German medium-sized firm in the medical gas supply industry to examine how DI and DT unfold and interact over time. Drawing on multi-source data (interviews, documents, and observations), we trace critical events, feedback loops, and tensions linking both processes. Our findings provide initial insights into how DI and DT may occur sequentially or concurrently, how external actors shape their interaction, and how resource constraints can create tensions between both processes. These insights contribute to a more temporally informed understanding of the DI–DT relationship and provide a foundation for future theory development.
Recommended Citation
Mevs, Alexander Karl Heinz; Werner, Matthias; and Drews, Paul, "Exploring The Relationship Between Digital Innovation and Digital Transformation: A Longitudinal Study" (2026). ECIS 2026 Proceedings. 10.
https://aisel.aisnet.org/ecis2026/digitrans/digitrans/10
Exploring The Relationship Between Digital Innovation and Digital Transformation: A Longitudinal Study
Digital innovation (DI) and digital transformation (DT) are interdependent processes shaping how organizations create and capture value from digital technologies. Prior research has offered valuable conceptual insights into their relationship, yet empirical understanding of how these processes interact and evolve over time remains limited. This study presents an exploratory longitudinal single-case investigation of a German medium-sized firm in the medical gas supply industry to examine how DI and DT unfold and interact over time. Drawing on multi-source data (interviews, documents, and observations), we trace critical events, feedback loops, and tensions linking both processes. Our findings provide initial insights into how DI and DT may occur sequentially or concurrently, how external actors shape their interaction, and how resource constraints can create tensions between both processes. These insights contribute to a more temporally informed understanding of the DI–DT relationship and provide a foundation for future theory development.
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