Detecting and tackling run-time obstacles in social business processes
Document Type
Conference Proceeding
Source of Publication
Proceedings - International Conference on Advanced Information Networking and Applications, AINA
Publication Date
5-5-2017
Abstract
© 2017 IEEE. This paper presents an approach for detecting and tackling obstacles that could fail the execution of social business processes. Existing approaches target regular (non-social) business processes and thus, rely mainly on business logs that contain details such as who executes what, when, and where. However, interactions between a business process's three components namely task, machine, and person, are overlooked. This deprives process engineers from valuable details that could help detect and tackle obstacles. These details refer to task-2-task, machine-2-machine, and person-2-person interactions and are recorded in social logs. Both business and social logs are part of an architecture that includes monitor, solver, and crawler components. A system implementing the architecture is also presented in the paper and illustrates how logs are developed and structured using eXtensible Event Stream format.
DOI Link
ISBN
9781509060283
ISSN
Publisher
Institute of Electrical and Electronics Engineers Inc.
First Page
371
Last Page
378
Disciplines
Business
Keywords
Business process, Log, Obstacle, Social interaction
Scopus ID
Recommended Citation
Maamar, Zakaria; Sellami, Mohamed; Faci, Noura; and Lefebvre, Sylvain, "Detecting and tackling run-time obstacles in social business processes" (2017). All Works. 1213.
https://zuscholars.zu.ac.ae/works/1213
Indexed in Scopus
yes
Open Access
no