Optimizing Staffing and Scheduling for High-Demand Carer Support Hotlines: A Human-AI Collaborative Approach

Abstract:

Background and Purpose:

The “”Designated Hotline for Carer Support”” experiences persistent congestion with high call volumes, long wait times, and frequent call abandonment. This research aims to analyze demand patterns and develop optimized staffing and scheduling strategies to better match agent supply with caller demand, while exploring human-AI collaboration opportunities to enhance service capacity.

Research Questions:

(1) What are the temporal patterns and characteristics of demand for the carer hotline?

(2) How can staffing levels and schedules be optimized to balance service quality with operational costs?

(3) How can AI technologies augment human agents to improve service accessibility while maintaining empathetic support?”

Skills and experience required for the project:

Preferred Disciplines: Statistics, Industrial Engineering, Business Analytics, or Information Systems
Statistical Analysis: Proficiency in time-series analysis, regression modeling, and descriptive statistics
Programming: Python or R for data analysis and simulation modeling
Optimization Software: Experience with linear programming solvers (e.g.,Excel Solver)

Multimedia:

https://www.swd.gov.hk/tc/pubsvc/rehab/cat_supportcom/scpd/dhcs/