Advances in Enterprise Engineering XV : 11th Enterprise Engineering Working Conference, EEWC 2021, Virtual Event, November 12, 2021, and December 16-17, 2021, Revised Selected Papers (Lecture Notes in Business Information Processing)

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Advances in Enterprise Engineering XV : 11th Enterprise Engineering Working Conference, EEWC 2021, Virtual Event, November 12, 2021, and December 16-17, 2021, Revised Selected Papers (Lecture Notes in Business Information Processing)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 167 p.
  • 言語 ENG
  • 商品コード 9783031115196

Full Description

This book constitutes the proceedings of the 11th Enterprise Engineering Working Conference, EEWC 2021, which was held online on November 12, 2021, and December 16-17, 2021.EEWC aims at addressing the challenges that modern and complex enterprises are facing in a rapidly changing world. The participants of the working conference share a belief that dealing with these challenges requires rigorous and scientific solutions, focusing on the design and engineering of enterprises. The goal of EEWC is to stimulate interaction between the different stakeholders, scientists as well as practitioners, interested in making Enterprise Engineering a reality.

The 5 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The volume also contains 2 keynote papers.

 

Contents

Invited Papers from Keynote Presentations.- Conceptual Modeling and Artificial Intelligence: Challenges and Opportunities for Enterprise Engineering.- Toward AI-native Enterprise.- Presented Papers.- Modeling Payments and Linked Obligation Settlements.- Towards an Ontology Network in Finance and Economics.- Flexible Enterprise Optimization with Constraint Programming.- Adapting and evaluating the story-card-method.- Business Driven Microservice Design - An Enterprise Ontology Based Approach to API Specifications.- Evaluation of the perceived quality and functionality of Fact Model diagrams in DEMO.- Towards the X-theory: an evaluation of the perceived Quality and Functionality of DEMO's Process Model.- Use of EA Models in Organizational AI Solution Development.

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