Designing normative open virtual enterprises

García, Emilia; Giret, Adriana; Botti, Vicente

doi:10.1080/17517575.2015.1036927

Cited by 6 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several papers describe the use of ABM in the multi-organizational context. Agent-based simulation can be used to analyze cross-organizational performance [41] and is suitable for formalizing business processes in virtual enterprises [42]. Risk-aware business process management can benefit from the ability of ABM to describe agentenvironment interactions [43].…”

Section: ) Abm In Bpmmentioning

confidence: 99%

Agent System Mining: Vision, Benefits, and Challenges

2021

View full text Add to dashboard Cite

In the Agent-Based Modeling (ABM) paradigm, an organization is a Multi-Agent System (MAS) composed of autonomous agents inducing business processes. Process Mining automates the creation, update, and analysis of explicit business process models based on event data. Process Mining techniques make simplifying assumptions about the processes discovered from data. However, actual business processes are often more complex than those restricted by Process Mining assumptions. Several Process Mining approaches relax these standard assumptions by discovering more realistic process models. These approaches can discover more realistic process models. However, these models are often difficult to visualize and, consequently, to understand. Many MASs induce processes whose behaviors become more complex with each next embraced time step, while the complexities of these MASs remain constant. Thus, the ABM paradigm can cope naturally with the increasing complexity of the discovered process models. This paper proposes Agent System Mining (ASM) and ASM Framework. ASM combines Process Mining and ABM in the Business Process Management (BPM) context to infer MAS models of operational business processes from real-world event data, while ASM Framework maps ASM activities to different phases of the MAS modeling lifecycle. The paper also discusses the benefits of using ASM and outlines challenges associated with the implementation of the ASM Framework.

show abstract

Section: ) Abm In Bpmmentioning

confidence: 99%

Agent System Mining: Vision, Benefits, and Challenges

2021

View full text Add to dashboard Cite

show abstract

“…In this context, the NOP and MAS can be considered as two synergic approaches, but with different scopes. The MAS use higher-level abstraction concepts (Garcia, Giret, and Botti 2016), whereas the NOP is proposed to deal with basiclevel computational objects (as can be seen in Section 2.2) (Simão and Stadzisz 2008;Ronszcka, Ferreira, et al 2017;Ronszcka, Valença, et al 2017).…”

Section: Nop and Masmentioning

confidence: 99%

A notification-oriented solution for data-intensive enterprise information systems – A cloud manufacturing case

Liao

Panetto

Stadzisz

et al. 2018

Enterprise Information Systems

View full text Add to dashboard Cite

The application of Industrial Internet of Things (IIoT) has brought a series of new challenges to the traditional Enterprise Information Systems (EIS). More and more networked manufacturing entities are combined with data sensing, collection, transmission, and actuation capabilities. EIS are now facing large amounts of heterogeneous data. To address this issue, this paper proposes a notification-oriented solution for the data-intensive EIS within a distributed, collaborative, and heterogeneous environment. The solution is then applied in terms of model to a cloud-based smart factory prototype. This work indicates the suitability of the proposition and discusses the existing drawbacks and perspectives that include the manual modelling process and the application on a prototype.

show abstract

Petri Net Classes for Collaboration Mining: Assessment and Design Guidelines

Benzin,

Rinderle-Ma

2024

Lecture Notes in Business Information Processing

View full text Add to dashboard Cite

Designing normative open virtual enterprises

Cited by 6 publications

References 32 publications

Agent System Mining: Vision, Benefits, and Challenges

Agent System Mining: Vision, Benefits, and Challenges

A notification-oriented solution for data-intensive enterprise information systems – A cloud manufacturing case

Petri Net Classes for Collaboration Mining: Assessment and Design Guidelines

Contact Info

Product

Resources

About