| Title |
An intelligent advisory system to support managerial decisions for a social safety net / |
| Authors |
Okewu, Emmanuel ; Misra, Sanjay ; Okewu, Jonathan ; Damaševičius, Robertas ; Maskeliūnas, Rytis |
| DOI |
10.3390/admsci9030055 |
| Full Text |
|
| Is Part of |
Administrative sciences.. Basel : MDPI AG. 2019, vol. 9, iss. 3, art. no. 55, p. 1-14.. eISSN 2076-3387 |
| Keywords [eng] |
managerial decision-making ; welfare management ; social safety net ; inclusive development ; computational intelligence |
| Abstract [eng] |
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. |
| Published |
Basel : MDPI AG |
| Type |
Journal article |
| Language |
English |
| Publication date |
2019 |
| CC license |
|
