Students

Daniel Altman is a Ph.D. candidate at the Industrial Engineering and Management Faculty at the Technion. He has a B.A in Psychology Sociology and Anthropology from the Max Stern Yezreel Valley College and an MSc in Organizational Psychology from the Technion. His MSc thesis, advised by Prof. Anat Rafaeli and Dr. Galit Yom-Tov, explored the effects of expressed customer emotion in service systems on consequent employee performance and behaviour using Big-Data.

Shelly Ashtar is a PhD Candidate at the Industrial Engineering and Management Faculty at the Technion, jointly supervised by Prof. Anat Rafaeli and Dr. Galit B. Yom-Tov. In her dissertation, she examines the effects of emotion dynamics within an interaction on multiple participants in service interactions. Shelly has an MSc in Behavioral and Management Sciences- Organizational Psychology from the Technion, and a BA in Psychology, Cognition and Neuroscience, from Ben-Gurion University of the Negev.

Monika Westphal is currently a third-year Ph.D. candidate in Behavioral Science at the Technion, advised by Prof. Anat Rafaeli and Dr. Galit B. Yom-Tov.

Her research focuses on service operations and takes an interdisciplinary perspective. In her dissertation, Monika tackles the question of how service organizations can and should make various unclear, hidden, or not yet known processes transparent to their stakeholders. The goal is to increase stakeholders’ understanding about the processes they go through, in a way that both the stakeholders and the organization benefit.

Monika has a B.A. in Business Administration with Tourism and Hospitality Management, from the Dual State University Ravensburg, Germany. In 2015, Monika joined the SEE-Lab team, and in 2017 she completed her M.Sc. in Behavioral Sciences at the Technion under the supervision of Prof. Anat Rafaeli and Dr. Galit B. Yom-Tov.

Antonio Castellanos is currently a PhD student in Industrial Engineering at the Technion advised by Dr. Galit Yom-Tov.

 My research develops methods for improving the operations of contact centers under information uncertainty. By data exploration, I have identified that such uncertainty results from people’s behavior in these platforms. The main problem that stems from those uncertainties is that companies hugely overestimate their service quality. For example, in one of our datasets the company believes 7.5% of its customers abandon, whereas in reality it is above 20%.

I am currently addressing the following problems: recognizing silent abandonment of customers and its operational implications, modeling service communication and unknown customer satisfaction. To solve these problems, I combine methods of operations research, statistics, and psychology.

If companies, through my research, are better able to measure performance, they will be able to improve the service quality and efficiency, and quickly identify an unsatisfied customer. This translates into wasting less of a customer’s valuable time. On the other hand, companies benefit too. If companies’ operations are more efficient, they waste less resource and save money.