Abstract

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.

Highlights

  • Online and blind peer review of manuscripts submitted by authors is an important part of the publication process

  • From the conformance analysis class, LTL Checker and Performance Analysis techniques were used in order to compare, check, and audit the authentic dataset with a pre-defined model

  • The main goals of the study were: (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

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Summary

Introduction

Online and blind peer review of manuscripts submitted by authors is an important part of the publication process. It is a process that includes selection and invitation of expert reviewers, allocation of deadline for reviewers, collection of comments from reviewers, discussion of manuscripts. We aimed to apply two classes of process mining techniques (i.e., Discovery and Conformance Analysis) in order to discover models, organizational structures, and bottlenecks related to the handling of proceedings’ peer reviews in an international conference in Thailand. Alpha (α) Algorithm, Heuristic, Fuzzy and Social Network mining techniques (from Discovery class) were used in order to automatically construct the proceedings’ review models based on the authentic data and without having any priori model. By using Social Network Miner technique we aimed to analyze the organizational perspective of the peer review process in terms of three metrics, namely as: (a) Handover of Work, (b) Working Together, and (c) Similar Tasks (Aalst 2011)

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