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Enterprise Design, Operations, and Computing

Overview of attention for book
Cover of 'Enterprise Design, Operations, and Computing'

Table of Contents

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    Book Overview
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    Chapter 1 A System Core Ontology for Capability Emergence Modeling
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    Chapter 2 What Do I Get from Modeling?
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    Chapter 3 A Generic and Customizable Genetic Algorithms-Based Conceptual Model Modularization Framework
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    Chapter 4 MARTSIA: Enabling Data Confidentiality for Blockchain-Based Process Execution
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    Chapter 5 Building an Ontological Bridge Between Supply Chain Resilience and IoT Applications
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    Chapter 6 A Model-Driven Approach to SAP S/4HANA Development
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    Chapter 7 A Methodology for the Analysis of Robotic Systems via Process Mining
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    Chapter 8 An Approach for Face Validity Assessment of Agent-Based Simulation Models Through Outlier Detection with Process Mining
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    Chapter 9 Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations
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    Chapter 10 Developing Taxonomies for Business Process Engineering
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    Chapter 11 A Taxonomy for Platform Revenue Models: An Empirical-to-Conceptual Development Approach
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    Chapter 12 Conceptual Modeling in Support of Economic and Regulatory Viability Assessment - A Reality Check on the Example of Developing an Energy Community
Attention for Chapter 2: What Do I Get from Modeling?
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Chapter title
What Do I Get from Modeling?
Chapter number 2
Book title
Enterprise Design, Operations, and Computing
Published by
Springer, Cham, January 2024
DOI 10.1007/978-3-031-46587-1_2
Book ISBNs
978-3-03-146586-4, 978-3-03-146587-1
Authors

Valle Sousa, Isadora, Prince Sales, Tiago, Guerra, Eduardo, Olavo Bonino da Silva Santos, Luiz, Guizzardi, Giancarlo

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 33%
Professor > Associate Professor 1 33%
Student > Master 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Unspecified 1 33%

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