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

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Date

2019

Journal Title

Journal ISSN

Volume Title

Publisher

Mdpi

Open Access Color

GOLD

Green Open Access

Yes

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OpenAIRE Views

Publicly Funded

No
Impulse
Top 10%
Influence
Average
Popularity
Top 10%

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Journal Issue

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
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OpenCitations Citation Count
9

Source

Administrative Sciences

Volume

9

Issue

3

Start Page

55

End Page

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Citations

CrossRef : 11

Scopus : 9

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Mendeley Readers : 68

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