Authors: Anna Wilbik, Baris Ozkan, Oktay Türetken, Paul Grefen, Rick Gilsing
Tags: 2020, conceptual modeling
Given its essential role in understanding, explaining and structuring digital innovation, we see the increased prevalence of the business model concept as a unit of analysis in IS research. In contemporary, fast-paced markets, business models are volatile in nature and should be continuously innovated to accommodate new customer needs and technology developments. Business model innovation can be considered as an iterative process to guide business models from ideation towards implementation, in which the proper evaluation of business model prototypes is essential. For this evaluation, we need normative guidance, tools and rules to understand the relative performance of a new business model design. In the early design phases, this implies dealing with high levels of uncertainty. A few techniques and methods have been proposed for this purpose, but these lack the formal basis required for systematical application and development of automated evaluation tools. As a novel approach, we have earlier proposed the application of linguistic summarization to support early-phase, soft-quantitative business model evaluation. In this paper, we focus on a structural formalization of this approach as the basis for the development of well-defined user guidelines and automated evaluation tools. In doing so, we bridge the existing gap between qualitative and quantitative business model evaluation. We demonstrate the formalization by means of a running case inspired by a real-world project in the highly dynamic urban mobility domain.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-030-49418-6_29
