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Internal organizational factors driving digital transformation for business model innovation in SMEs

Published: 30.08.2023

by Chanté van Tonder , Sandra Hasanefendic , Bart Bossink , Chris Schachtebeck , Cecile Nieuwenhuizen

Abstract

Purpose: The primary purpose of this paper is to investigate which internal organizational factors drive the renewal of SMEs’ business strategy and business culture to support their digital transformation trajectory.

Design/methodology/approach: The paper builds on a literature study and Delphi study from both a South African and Dutch scholarly and industry perspective. For the Delphi study a questionnaire was used to determine the commonly cited internal organizational factors that drive digital transformation for business model innovation in SMEs in an emerging and a developed economy. These factors were then confronted with the insights from the literature study to draw literature-based and empirically grounded insights.

Findings: Specific internal organizational factors are identified that contribute to the renewal of SMEs’ business strategy and business culture which support their digital transformation trajectory.

Research Limitations: The model was applied to three use cases in Smart Cities and Urban Digital Twins. Consequently, the data ecosystems concern a high presence of public actors, yet also includes private companies. The applicability needs to be identified in other sectors in further research. Additionally, as the scope of the study was on business models, data governance, data-sharing and data ecosystems, abstraction was made of fields of study beyond these topics.

Originality/value: The study contributes to the current understanding of the internal organizational factors that drive digital transformation for business model innovation in SMEs. Researchers can use these factors as a basis for future research. For practitioners, the findings provide a guideline which SMEs can use to (re)arrange business activities to enable digital transformation-induced business model innovation.

More information about this paper

DOI: https://doi.org/10.54337/jbm.v11i2.7403

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