Communications of the ACM
Rough Set Based Data Exploration Using ROSE System
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
ROSE - Software Implementation of the Rough Set Theory
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model
Information Sciences: an International Journal - Special issue: Medical expert systems
Review: Dimensionality reduction based on rough set theory: A review
Applied Soft Computing
Discovering patterns of missing data in survey databases: An application of rough sets
Expert Systems with Applications: An International Journal
Rough sets to help medical diagnosis - Evidence from a Taiwan's clinic
Expert Systems with Applications: An International Journal
Service-Level Agreements in Call Centers: Perils and Prescriptions
Management Science
Financial time-series analysis with rough sets
Applied Soft Computing
Attribute reduction for dynamic data sets
Applied Soft Computing
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Managers in call centers use metrics to measure organizational performance; unfortunately, these metrics only reveal how well service agents process calls. To achieve substantial quality improvement, managers need to obtain in-depth information from operational metrics such as first call resolution (FCR). This research incorporated rough set theory (RST) in analyzing FCR to produce decision rules. RST has been known to reduce the number of attributes and attribute values without affecting the original results. Data from a tariff (industry segment) call center in Taiwan were used in this study, and a four-step process was used to produce the final decision rules. The results were verified by a 10-fold cross-validation process against the decision rules produced without applying RST. The decision rules produced with RST are as effective as those produced without, but with reduced number of attributes and attribute values. This reduced decision rule set can help managers analyze the current operator procedures more efficiently and subsequently improve the call center efficiency. Without affecting effectiveness, the RST application reduces the needed number of attributes and attribute values to produce a more compact decision rule set, and this increased efficiency, in turn, allows managers to delve deeper into the operational factors.