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Process modeling and bottleneck mining in online peer-review systems

This paper is divided into three main parts. In the first part of the study, we captured, collected and formatted an event log describing the handling of reviews for proceedings of an international conference in Thailand. In the second part, we used several process mining techniques in order to disc...

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Detalles Bibliográficos
Autores principales: Premchaiswadi, Wichian, Porouhan, Parham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546073/
https://www.ncbi.nlm.nih.gov/pubmed/26312206
http://dx.doi.org/10.1186/s40064-015-1183-4
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author Premchaiswadi, Wichian
Porouhan, Parham
author_facet Premchaiswadi, Wichian
Porouhan, Parham
author_sort Premchaiswadi, Wichian
collection PubMed
description This paper is divided into three main parts. In the first part of the study, we captured, collected and formatted an event log describing the handling of reviews for proceedings of an international conference in Thailand. In the second part, we used several process mining techniques in order to discover process models, social, organizational, and hierarchical structures from the proceeding’s event log. In the third part, we detected the deviations and bottlenecks of the peer review process by comparing the observed events (i.e., authentic dataset) with a pre-defined model (i.e., master map). Finally, we investigated the performance information as well as the total waiting time in order to improve the effectiveness and efficiency of the online submission and peer review system for the prospective conferences and seminars. Consequently, the main goals of the study were as follows: (1) to convert the collected event log into the appropriate format supported by process mining analysis tools, (2) to discover process models and to construct social networks based on the collected event log, and (3) to find deviations, discrepancies and bottlenecks between the collected event log and the master pre-defined model. The results showed that although each paper was initially sent to three different reviewers; it was not always possible to make a decision after the first round of reviewing; therefore, additional reviewers were invited. In total, all the accepted and rejected manuscripts were reviewed by an average of 3.9 and 3.2 expert reviewers, respectively. Moreover, obvious violations of the rules and regulations relating to careless or inappropriate peer review of a manuscript—committed by the editorial board and other staff—were identified. Nine blocks of activity in the authentic dataset were not completely compatible with the activities defined in the master model. Also, five of the activity traces were not correctly enabled, and seven activities were missed within the online submission system. On the other hand, dealing with the feedback (comments) received from the first and the third reviewers; the conference committee members and the organizers did not attend to those feedback/comments in a timely manner.
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spelling pubmed-45460732015-08-26 Process modeling and bottleneck mining in online peer-review systems Premchaiswadi, Wichian Porouhan, Parham Springerplus Research This paper is divided into three main parts. In the first part of the study, we captured, collected and formatted an event log describing the handling of reviews for proceedings of an international conference in Thailand. In the second part, we used several process mining techniques in order to discover process models, social, organizational, and hierarchical structures from the proceeding’s event log. In the third part, we detected the deviations and bottlenecks of the peer review process by comparing the observed events (i.e., authentic dataset) with a pre-defined model (i.e., master map). Finally, we investigated the performance information as well as the total waiting time in order to improve the effectiveness and efficiency of the online submission and peer review system for the prospective conferences and seminars. Consequently, the main goals of the study were as follows: (1) to convert the collected event log into the appropriate format supported by process mining analysis tools, (2) to discover process models and to construct social networks based on the collected event log, and (3) to find deviations, discrepancies and bottlenecks between the collected event log and the master pre-defined model. The results showed that although each paper was initially sent to three different reviewers; it was not always possible to make a decision after the first round of reviewing; therefore, additional reviewers were invited. In total, all the accepted and rejected manuscripts were reviewed by an average of 3.9 and 3.2 expert reviewers, respectively. Moreover, obvious violations of the rules and regulations relating to careless or inappropriate peer review of a manuscript—committed by the editorial board and other staff—were identified. Nine blocks of activity in the authentic dataset were not completely compatible with the activities defined in the master model. Also, five of the activity traces were not correctly enabled, and seven activities were missed within the online submission system. On the other hand, dealing with the feedback (comments) received from the first and the third reviewers; the conference committee members and the organizers did not attend to those feedback/comments in a timely manner. Springer International Publishing 2015-08-22 /pmc/articles/PMC4546073/ /pubmed/26312206 http://dx.doi.org/10.1186/s40064-015-1183-4 Text en © Premchaiswadi and Porouhan. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Premchaiswadi, Wichian
Porouhan, Parham
Process modeling and bottleneck mining in online peer-review systems
title Process modeling and bottleneck mining in online peer-review systems
title_full Process modeling and bottleneck mining in online peer-review systems
title_fullStr Process modeling and bottleneck mining in online peer-review systems
title_full_unstemmed Process modeling and bottleneck mining in online peer-review systems
title_short Process modeling and bottleneck mining in online peer-review systems
title_sort process modeling and bottleneck mining in online peer-review systems
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4546073/
https://www.ncbi.nlm.nih.gov/pubmed/26312206
http://dx.doi.org/10.1186/s40064-015-1183-4
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