Creating a Digital Twin: Simulation of a Business Model Design Tool
Volume 4, Issue 6, Page No 53-60, 2019
Author’s Name: Kira Rambow-Hoeschelea), Nick Giani Rambow, Matthias Michael Hampel, David Keith Harrison, Bruce MacLeod Wood
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School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow, UK
a)Author to whom correspondence should be addressed. E-mail: kira.rambow-hoeschele@t-online.de
Adv. Sci. Technol. Eng. Syst. J. 4(6), 53-60 (2019); DOI: 10.25046/aj040607
Keywords: Business model development, Digital twin, Simulation tool
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Digitization forces industry players to adapt to transforming market situations and buyer behavior. Technological advances, buyer power, and sharpened competitive intensity imply that businesses are confronted with the menace of commoditization. For companies to perform successfully in the market, outdated business models ought to be rethought and new business models should be created. Unique selling propositions and differentiation through research, innovation, and holistic stakeholder involvement help industry players to master the change. A tool was built to support businesses facing the consequences of digital transformation: the Business Model Builder. This research paper explores the steps of creating a software version of the analog Business Model Builder. The digital twin enables firms to simulate the iterative adaptation of business models to permanently changing market circumstances and customer demands on an ongoing basis. The user of the tool can edit single variables, understand interrelations, and see the effect on the outcome of the business case, e.g., earnings before interest and taxes or economic value added. Accordingly, the simulation offers the opportunity to have a dynamic view of the business model where any variances of input parameters are reflected in the business case. Thus, profitability, feasibility, and functionality of a business model can be validated, tested, and reviewed in the digital simulation tool.
Received: 03 December 2018, Accepted: 02 November 2019, Published Online: 22 November 2019
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