An Intelligent Advisory System To Support Managerial Decisions for a Social Safety Net
Loading...

Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Mdpi
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Social investment programs are designed to provide opportunities to the less privileged so that they can contribute to the socioeconomic development of society. Stakeholders in social safety net programs (SSNPs) target vulnerable groups, such as the urban poor, women, the unemployed, and the elderly, with initiatives that have a transformative impact. Inadequate policy awareness remains a challenge, resulting in low participation rates in SSNPs. To achieve all-inclusive development, deliberate policies and programs that target this population have to be initiated by government, corporate bodies, and public-minded individuals. Artificial intelligence (AI) techniques could play an important role in improving the managerial decision support and policy-making process of SSNPs and increasing the social resilience of urban populations. To enhance managerial decision-making in social investment programs, we used a Bayesian network to develop an intelligent decision support system called the Social Safety Net Expert System (SSNES). Using the SSNES, we provide an advisory system to stakeholders who make management decisions, which clearly demonstrates the efficacy of SSNPs and inclusive development.
Description
Misra, Sanjay/0000-0002-3556-9331; Damaševičius, Robertas/0000-0001-9990-1084; Maskeliunas, Rytis/0000-0002-2809-2213
Keywords
managerial decision-making, welfare management, social safety net, inclusive development, inclusive development, welfare management, managerial decision-making, JF20-2112, computational intelligence, social safety net, ddc:350, Political institutions and public administration (General)
Fields of Science
05 social sciences, 01 natural sciences, 0502 economics and business, 0105 earth and related environmental sciences
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
9
Source
Administrative Sciences
Volume
9
Issue
3
Start Page
55
End Page
PlumX Metrics
Citations
CrossRef : 11
Scopus : 9
Captures
Mendeley Readers : 68
Google Scholar™


