Waiting Experience in Open-Shop Service Networks: Improvements via Flow Analytics & Automation

49 Pages Posted: 24 Mar 2022 Last revised: 18 Jan 2024

See all articles by Manlu Chen

Manlu Chen

Renmin University of China - School of Business

Opher Baron

University of Toronto - Rotman School of Management

Avishai Mandelbaum

Technion - Israel Institute of Technology

Jianfu Wang

City University of Hong Kong

Galit Yom-Tov

Technion-Israel Institute of Technology

Nadir Arber

affiliation not provided to SSRN

Date Written: January 27, 2022

Abstract

Problem definition: We study open-shop service networks where customers go through multiple services. We were motivated by a partnering health screening clinic, where customers are routed by a dispatcher and operational performance is measured at two levels: micro-level, via waits for individual services, and macro-level, via overall wait. Both measures reflect customer experience and could support its management. Our analysis revealed that waits were long and increased along the service process. Such long waits give rise to negative waiting experience and the increasing shape is detrimental as it is known to create perceived waits that are even longer. Our goal is hence to analyze strategies that shape and improve customers' perceived experience.

Methodology/results: Analytically, we use a stylized two-station open-shop network to show that prioritizing advanced customers, jointly with pooling (virtual) queues, can improve both macro- and micro-level performance. We validate these findings with a simulation model, calibrated with our clinic's data. Practically, we find that an automated routing system (ARS), recently implemented in the clinic, had a negligible impact on overall wait --- it simply redistributed waiting among wait-for-routing and wait-for-service. Still ARS renders applicable sophisticated priority and routing policies (that were infeasible under the manual routing practice), specifically the ones arising from the present research.

Managerial implications: Our study amplifies performance benefits of accounting for individual customers' system-status in addition to station-level load information. We offer insights into the implementation of new technologies: firms better plan for fundamental changes in their operation, rather than harness new technology to their existing operation, which may be sub-optimal due to past technical limitations.

Keywords: Service analytics, information technology, wait time management, open shop, priority policy

Suggested Citation

Chen, Manlu and Baron, Opher and Mandelbaum, Avishai and Wang, Jianfu and Yom-Tov, Galit and Arber, Nadir, Waiting Experience in Open-Shop Service Networks: Improvements via Flow Analytics & Automation (January 27, 2022). Available at SSRN: https://ssrn.com/abstract=4018744 or http://dx.doi.org/10.2139/ssrn.4018744

Manlu Chen (Contact Author)

Renmin University of China - School of Business ( email )

Beijing
China

Opher Baron

University of Toronto - Rotman School of Management ( email )

Avishai Mandelbaum

Technion - Israel Institute of Technology ( email )

Israel

Jianfu Wang

City University of Hong Kong ( email )

Kowloon
Hong Kong
Hong Kong

Galit Yom-Tov

Technion-Israel Institute of Technology ( email )

Technion City
Haifa 32000, Haifa 32000
Israel

Nadir Arber

affiliation not provided to SSRN ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
121
Abstract Views
673
Rank
428,887
PlumX Metrics