Accessibility of Urban Nonprofit Public Nursery Services Based on Big Data

Area of Science:

• Social Sciences
• Urban Planning
• Public Policy

Background:

• Increasing societal pressure for family care and a growing demand for childcare services, particularly for 0-3 year olds.
• Existing literature identifies factors negatively impacting demand for nursery services, including family size and facility concerns.
• Key positive influences on demand include grandparental support, parental age, and willingness to pay for services.

Purpose of the Study:

• To address the accessibility challenges of urban non-profit public nursery services.
• To leverage big data analytics for understanding and improving childcare service accessibility.
• To identify and analyze factors influencing public demand for early childhood care.

Main Methods:

• Utilized big data methodology to analyze urban non-profit public nursery service accessibility.
• Conducted comparative analysis to verify and evaluate the proposed scheme.
• Extracted key factors impacting demand from existing literature.

Main Results:

• Identified factors with negative impacts: children's age gap, attention to nursery facilities, environment, and food safety in specific family structures.
• Identified factors with positive impacts: grandparents' help, parents' age, and psychological tolerance of service fees.
• Demonstrated exceptional performance of the proposed big data scheme in resolving accessibility issues.

Conclusions:

• Big data analysis provides an effective approach to resolving accessibility issues in urban non-profit public nursery services.
• Understanding the multifaceted factors influencing demand is crucial for service provision.
• The proposed scheme shows significant potential for improving access to essential childcare services.