Analyzing the Impact Level of SMEs Features Over Digital Transformation: A Case Study

Analyse du niveau d'impact des caractéristiques des PME sur la transformation numérique: Une étude de cas

Melissa Liborio Zapata, Lamia Berrah and Laurent Tabourot ()
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Melissa Liborio Zapata: SYMME - Laboratoire SYstèmes et Matériaux pour la MEcatronique - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc, LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc
Lamia Berrah: LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc
Laurent Tabourot: SYMME - Laboratoire SYstèmes et Matériaux pour la MEcatronique - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc

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Abstract: Digital Transformation (DT) represents a real challenge for companies worldwide, not only because of its complexity due to technology's fast evolution, but also because of the lack of appropriate guidance. Available approaches are judged generic as they do not take into account the specific context of companies. In this sense, this work explores the influence of context in DT success and introduces a performance indicator to measure the impact of the company features that represent its specific context on the dimensions involved in a DT. As the second phase in a research project aimed to build a quantitative model that explains this relationship, this paper focuses on the application of the Impact Level (IL) factor in a real case scenario. The goal is to validate a previous theoretical analysis and also to identify changes in the results with a different characterization of company features. Relevant findings confirm the critical importance of Culture (f3) and R&D investment (f9) for DT success, but many differences arise from the comparative analysis that reveals the DT process as highly contextual. Future work will be focused on translating the insights of both studies into a quantitative model that presents the IL as an aggregator but also with the possibility to provide enough detail for better decision-making during the DT process.

Date: 2021-09-05
Note: View the original document on HAL open archive server: https://hal.science/hal-03500160
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Published in IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.40-48, ⟨10.1007/978-3-030-85902-2_5⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03500160

DOI: 10.1007/978-3-030-85902-2_5

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