Managing Appointment-Based Services in the Presence of Walk-In Customers

Management Science, Forthcoming

56 Pages Posted: 23 Mar 2018 Last revised: 21 Oct 2018

See all articles by Shan Wang

Shan Wang

Sun Yat-sen University

Nan Liu

Boston College - Carroll School of Management

Guohua Wan

Shanghai Jiao Tong University (SJTU) - Antai College of Economics and Management

Date Written: October 18, 2018

Abstract

Despite the prevalence and significance of walk-ins in healthcare, we know relatively little about how to plan and manage the daily operations of a healthcare facility that accepts both scheduled and walk-in patients. In this paper, we take a data analytics approach and develop the first optimization model to determine the optimal appointment schedule in the presence of potential walk-ins. Our model is the first known approach that can jointly handle general walk-in processes and heterogeneous, time-dependent no-show behaviors. We demonstrate that, with walk-ins, the optimal schedules are fundamentally different from those without. Our numerical study reveals that walk-ins introduce a new source of uncertainties to the system and cannot be viewed as a simple solution to compensate for patient no-shows. Scheduling, however, is an effective way to counter some of the negative impact from uncertain patient behaviors. Using data from practice, we predict a significant cost reduction (42%-73% on average) if the providers were to switch from current practice (which tends to overlook walk-ins in planning) to our proposed schedules. Though our work is motivated by healthcare, our models and insights can also be applied to general appointment-based services with walk-ins.

Keywords: service operations management, healthcare, appointment scheduling, walk-ins, analytics

JEL Classification: C44, C61, M10, I10

Suggested Citation

Wang, Shan and Liu, Nan and Wan, Guohua, Managing Appointment-Based Services in the Presence of Walk-In Customers (October 18, 2018). Management Science, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3104045 or http://dx.doi.org/10.2139/ssrn.3104045

Shan Wang

Sun Yat-sen University ( email )

135 Xingang Xi Road
J.T. Wu Hall 320
Guangzhou, Guangdong 510275
China

HOME PAGE: http://wangshan731.wixsite.com/shan

Nan Liu (Contact Author)

Boston College - Carroll School of Management ( email )

140 Commonwealth Avenue
Chestnut Hill, MA 02467
United States

HOME PAGE: http://sites.google.com/site/nanliuacademic/

Guohua Wan

Shanghai Jiao Tong University (SJTU) - Antai College of Economics and Management ( email )

No.535 Fahuazhen Road
Shanghai Jiao Tong University
Shanghai, Shanghai 200052
China

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
266
Abstract Views
1,112
rank
132,203
PlumX Metrics