Authors:
Mouna Rekik
1
;
Khouloud Boukadi
1
and
Hanene Ben-Abdallah
2
Affiliations:
1
University of Sfax and Mir@cl Laboratory, Tunisia
;
2
King Abdulaziz University and Mir@cl Laboratory, Saudi Arabia
Keyword(s):
Business Process Outsourcing, Cloud Computing, BPMN Extension, Genetic Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Business Process Management
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Software Technologies
;
Health Engineering and Technology Applications
;
Intelligent Problem Solving
;
Knowledge Engineering and Ontology Development
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Business process outsourcing to the Cloud is increasingly being adopted as a strategy to save costs, improve the business process performance, enhance the flexibility in responding to costumers' needs, etc. However, the adoption of an outsourcing strategy faces several challenges like the enterprise data security, vendor-lock-in and labor union. Weighing the pros and cons of outsourcing one’s business process is an arduous task. This paper provides for assistance means: it extends the BPMN language to explicitly support the specification of outsourcing criteria, and it presents an automated approach to help decision makers identify those parts of their business process that benefit most from outsourcing to the Cloud.