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Tuesday, October 16, 2018 at 4:15pm
Service delivery relies on interactions with customers, which can be via various channels including face-to-face, phone calls, and chats. The operation of customer contact is highly complex and must balance service quality with efficient use of resources. Recent research in behavioral operations has helped deepen the understanding of how operational decisions (e.g., load or queue structure) impact agent efficiency. The current research concerns the interaction between customers and agents in an attempt to deepen the understanding of how customer behavior influences system efficiency through its impact on agents. The critical issue in this context, about which little is understood, is the influence of customers’ emotional behavior. We claim that such behavior creates an “emotional load” which is distinct construct—separated from general workload.
The advancement of technology in the service sector makes data for addressing this issue more available; new NLP tools provide sentiment analysis models that can capture aspects of human emotional behavior. We examine technologically mediated service, specifically chat service, where agent and customer behavior within an interaction is fully accessible for analysis. In a series of studies, we developed and validated sentiment analysis tools for chat interactions and analyzed large-scale databases of service companies. This research explores the relationships between customer emotions, employee behavior, and service effectiveness, as well as the operational implications thereof. We then continued to develop a queueing model that captures this type of multi-dimensional load. We discuss implications in other contexts such as healthcare and court systems.
Galit Yom-Tov is an assistant professor at Technion at the IE&M faculty. Previously, she was a postdoc fellow and an adjunct professor at Columbia University at the IEOR department. She did her M.Sc. and Ph.D. at the Technion and worked in the industry as industrial engineer and IT specialist. Her research focuses on service systems. She studies how data obtained from various service systems (such as call-centers and hospitals) can teach us about customer and agent behavior in such systems, and how queueing models can help understanding the operational implications of such behavior. Professor Yom-Tov aims to build new operation methods for these systems in a way that will balance service and financial goals.
Professor Yom-Tov's focus is mainly on healthcare systems (like hospitals) where her research can help to allocate resources such as beds, nurses, and physicians so that patients will receive adequate service while considering financial constraints.