Assessing Business Model Performance Using Scalability and Replicability as Performance Indicators: A Case of an Electric Commercial Vehicle Ecosystem
Dehkordi, Rashid; Ahokangas, Petri; Evers, Natasha; Sorvisto, Mika (2024-02-15)
Dehkordi, Rashid
Ahokangas, Petri
Evers, Natasha
Sorvisto, Mika
IEEE
15.02.2024
R. Dehkordi, P. Ahokangas, N. Evers and M. Sorvisto, "Assessing Business Model Performance Using Scalability and Replicability as Performance Indicators: A Case of an Electric Commercial Vehicle Ecosystem," in IEEE Transactions on Engineering Management, vol. 71, pp. 5798-5814, 2024, doi: 10.1109/TEM.2024.3365648
https://creativecommons.org/licenses/by/4.0/
© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202403252407
https://urn.fi/URN:NBN:fi:oulu-202403252407
Tiivistelmä
Abstract
In recent decades, the concept of a business model (BM) has attracted much attention as a strategic tool for understanding firm competitiveness. As organizations face increasing complexities and uncertainties, assessing performance of BMs has become increasingly important for understanding how firms can leverage their strengths, address weaknesses, and adapt to changing industry dynamics. However, assessing BMs’ performance presents inherent challenges due to multifaceted dimensions and quantification complexities, as well as the absence of well-defined and appropriate performance indicators. This study thus responds to the recent calls for research on assessing BMs’ performance by proposing an assessment framework using two BM outcomes, scalability and replicability, as potential performance indicators. Using an electric commercial vehicle (ECV) ecosystem as a case study, we employ an assessment framework, exploring the determinants of scalability and replicability in ECV BMs, which are then categorized as technical, economic (or business-oriented), and regulatory. This article contributes to the emerging BM literature by proposing scalability and replicability as two performance indicators for a comprehensive understanding of BM performance. It further illuminates both concepts of scalability and replicability, concluding with practical implications for managers designing scalable and replicable BMs.
In recent decades, the concept of a business model (BM) has attracted much attention as a strategic tool for understanding firm competitiveness. As organizations face increasing complexities and uncertainties, assessing performance of BMs has become increasingly important for understanding how firms can leverage their strengths, address weaknesses, and adapt to changing industry dynamics. However, assessing BMs’ performance presents inherent challenges due to multifaceted dimensions and quantification complexities, as well as the absence of well-defined and appropriate performance indicators. This study thus responds to the recent calls for research on assessing BMs’ performance by proposing an assessment framework using two BM outcomes, scalability and replicability, as potential performance indicators. Using an electric commercial vehicle (ECV) ecosystem as a case study, we employ an assessment framework, exploring the determinants of scalability and replicability in ECV BMs, which are then categorized as technical, economic (or business-oriented), and regulatory. This article contributes to the emerging BM literature by proposing scalability and replicability as two performance indicators for a comprehensive understanding of BM performance. It further illuminates both concepts of scalability and replicability, concluding with practical implications for managers designing scalable and replicable BMs.
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