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.

This book constitutes the refereed proceedings of the 12th Enterprise Engineering Working Conference on Advances in Enterprise Engineering XVI, EEWC 2022, held in Leusden, The Netherlands, November 2–3, 2022. 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 4 full papers and 2 short papers included in this book were carefully reviewed and selected from 13 submissions. In addition, there are 2 invited papers from keynote presentations. They were organized in topical sections as follows: Invited Papers from Keynote Presentations and Presented Papers.

The expectation for the future of the 21st century enterprise is complexity and agility. In this digital age, business processes are scattered not only throu- out the labyrinth of their own enterprises, but also across di?erent enterprises, and even beyond the national boundaries. An evidence of this is the gr- ing phenomenon of business process outsourcing. Increasing competition, higher customer demands, and emerging technologies require swift adaptation to the changes. To understand, design, and engineer a modern enterprise (or an enterprise network) and its interwoven business processes, an engineering and systematic approach based on sound and rigorous theories and methodologies is necessary. Along with that, a paradigmshift seems to be needed for addressing these issues adequately. An appealing candidate is to look at an enterprise and its business processes as a social system. In its social setting, an enterprise and its bu- ness processes represent actors with certain authorities and assigned roles, who assume certain responsibilities in order to provide a service to its environment. The need for this paradigm shift along with the complexity and agility of modern enterprises, gives inspiration for the emerging discipline of Enterprise Engineering. For the study of this socio-technical phenomenon, the prominent tools ofModeling andSimulation play a signi?cant role.Both (conceptual) m- eling and simulationare widely used for understanding,analyzing,andengine- ing an enterprise (its organization and business processes).

The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as ?enterprise data?. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.

"This book provides a comprehensive assessment of the latest developments in the EIS revolution. including Enterprise Resource Planning (ERP) adoption, the integration of enterprise systems, personalized ERP, and the Semantic Web, and ideas and solutions for the future of the global enterprise"--Provided by publisher.

Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterpri