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Erschienen in:
Fine Tuning a Bayesian Network and Fairly Allocating Resources to Improve Procurement Performance Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

A Bayesian Network for Improving Organizational Regulations Effectiveness: Concurrent Modeling of Organizational Resilience Engineering and Macro-Ergonomics Indicators

verfasst von : A. Azadeh, M. Partovi, M. Saberi, Elizabeth Chang, Omar Hussain

Erschienen in: Advances in Intelligent Networking and Collaborative Systems

Verlag: Springer International Publishing

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Abstract

This study presents a novel Bayesian Network (BN) based model for improving organizational regulations effectiveness (OREF) through concurrent modelling of organizational resilience engineering (ORE) and macro-ergonomics (ME) indicators in an organization. Six indicators namely teamwork, preparedness, fault tolerance, flexibility, redundancy and self-organization are considered as representatives of ORE. The macro-ergonomics indicators considered in this study are redesign, decision-making pace and information flow. The construction of the proposed model is composed of five steps. The BN is then used to track the status of OREF by considering ORE and ME indicators. Since these indicators represent the nodes of the Bayesian Network, in the first step they have been selected and confirmed by experts to be further considered in the model. The causal relationships between the nodes are acquired through aggregating experts’ opinions by using the Dempster-Shafer theory.

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Vorheriges Kapitel k-core Decomposition on Giraph and GraphChi
Nächstes Kapitel Behavioral Keys in Cryptography and Security Systems
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Metadaten
Titel
A Bayesian Network for Improving Organizational Regulations Effectiveness: Concurrent Modeling of Organizational Resilience Engineering and Macro-Ergonomics Indicators
verfasst von
A. Azadeh
M. Partovi
M. Saberi
Elizabeth Chang
Omar Hussain
Copyright-Jahr
2018
Buch
Advances in Intelligent Networking and Collaborative Systems

Print ISBN: 978-3-319-65635-9

Electronic ISBN: 978-3-319-65636-6

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-65636-6_25