Intentional linguistic summaries for collaborative business model radars

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Abstract

We propose the use of linguistic summarization concept to support business model design evaluation. In contrast to traditional linguistic summarization, we do not infer these linguistic summaries from data, but use their structure to express intentions or conditions for stakeholders to participate in the designed business model. Early phase business model design is highly uncertain, for which it is often difficult to quantify under what conditions the business model design would be acceptable for the stakeholders involved. Through generation of intentional linguistic summaries (ILS), stakeholders can make explicit under what conditions a certain business model design would be acceptable. Therefore ILS can allow a discussion on benefits and costs without focusing too much on details, which are rarely available in the early phases of business model design. These intentional linguistic summaries can consequently be used as soft KPIs to be validated once the business model is operational.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
Number of pages7
ISBN (Electronic)9781728169323
DOIs
Publication statusPublished - Jul 2020
Event2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020 - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020

Conference

Conference2020 IEEE International Conference on Fuzzy Systems, FUZZ 2020
CountryUnited Kingdom
CityGlasgow
Period19/07/2024/07/20

Keywords

  • Business model radars
  • Evaluation
  • Linguistic summaries
  • Protoforms

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