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. 2021;20(4):965-996.
doi: 10.1007/s10270-021-00894-x. Epub 2021 Jun 15.

Defining business model key performance indicators using intentional linguistic summaries

Affiliations

Defining business model key performance indicators using intentional linguistic summaries

Rick Gilsing et al. Softw Syst Model. 2021.

Abstract

To sustain competitiveness in contemporary, fast-paced markets, organizations increasingly focus on innovating their business models to enhance current value propositions or to explore novel sources of value creation. However, business model innovation is a complex task, characterized by shifting characteristics in terms of uncertainty, data availability and its impact on decision making. To cope with such challenges, business model evaluation is advocated to make sense of novel business models and to support decision making. Key performance indicators (KPIs) are frequently used in business model evaluation to structure the performance assessment of these models and to evaluate their strategic implications, in turn aiding business model decision making. However, given the shifting characteristics of the innovation process, the application and effectiveness of KPIs depend significantly on how such KPIs are defined. The techniques proposed in the existing literature typically generate or use quantitatively oriented KPIs, which are not well-suited for the early phases of the business model innovation process. Therefore, following a design science research methodology, we have developed a novel method for defining business model KPIs, taking into account the characteristics of the innovation process, offering holistic support toward decision making. Building on theory on linguistic summarization, we use a set of structured templates to define qualitative KPIs that are suitable to support early-phase decision making. In addition, we show how these KPIs can be gradually quantified to support later phases of the innovation process. We have evaluated our method by applying it in two real-life business cases, interviewing 13 industry experts to assess its utility.

Keywords: Business model evaluation; Business model innovation; Intentional linguistic summaries; Key performance indicators; Linguistic summarization.

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Figures

Fig. 1
Fig. 1
SDBM/R template for business model design (left) and example business model for bikesharing (right)
Fig. 2
Fig. 2
Example of fuzzy membership
Fig. 3
Fig. 3
Research design
Fig. 4
Fig. 4
Method overview
Fig. 5
Fig. 5
Using protoforms to define ILSs/KPIs to support decision making in business model innovation
Fig. 6
Fig. 6
Gradual quantification of linguistic summarizers for KPIs
Fig. 7
Fig. 7
Service-dominant business model for 'seamless travel experience'
Fig. 8
Fig. 8
Application of method to support decision making in business model innovation
Fig. 9
Fig. 9
Business model design to address traffic jams due to large events
Fig. 10
Fig. 10
Service-dominant business model design for 'optimal product quality'

References

    1. Adali, O.E., Turetken, O., Ozkan, B., Gilsing, R., Grefen, P.: A multi-concern method for identifying business services: a situational method engineering study. In: Enterprise, Business-Process and Information Systems Modeling, pp. 227–241. Springer, Cham (2020)
    1. Al-Debei M, Avison D. Developing a unified framework of the business model concept. Eur. J. Inf. Syst. 2010;19(3):359–376. doi: 10.1057/ejis.2010.21. - DOI
    1. Amit, R., Zott, C.: Creating value through business model innovation. MIT Sloan Manag. Rev. (2012)
    1. Anderson D, Luke R, Keller J, Skubic M, Rantz M, Aud M. Linguistic summarization of video for fall detection using voxel person and fuzzy logic. Comput. Vis. Image Underst. 2009;1(113):80–89. doi: 10.1016/j.cviu.2008.07.006. - DOI - PMC - PubMed
    1. Berends H, Smits A, Reymen I, Podoynitsyna K. Learning while (re)configuring: business model innovation processes in established firms. Strateg. Organ. 2016;14(3):181–219. doi: 10.1177/1476127016632758. - DOI - PMC - PubMed

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