Rooswita Loing
Universitas Klabat

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Queues, Service Efficiency, and Social Proof: Multi-Site Non-Participant Observation of Mie Gacoan Rooswita Loing; Aldo Franco Karinda; Reymond Kowaas; Harke Revo Leonard Polii
Jurnal Informatika Ekonomi Bisnis Vol. 8, No. 1 (March 2026)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v8i1.1383

Abstract

Queues in budget-priced food-service retail commonly arise when customer arrivals exceed service capacity during peak hours. This study examines queuing as a dual phenomenon: an indicator of service-process efficiency and a form of social proof that may shape customers’ decisions to join, remain in, or abandon a queue. Non-participant observations were conducted at three Mie Gacoan branches in North Sulawesi (Manado, Tondano, and Airmadidi) across nine weekend sessions (midday peak 11:00–13:30 WITA; evening peak 18:00–21:30 WITA). Data were compiled from field notes, time logs of estimated waiting times, service-flow mapping using a service blueprint, and anonymized documentation of service artefacts. The findings indicate a multi-stage queue, with bottlenecks shifting across the cashier, preparation, and handover phases. Manado exhibited the highest intensity (maximum queue length: 95 customers; maximum waiting time: 60 minutes) and the greatest number of abandonment events (19), whereas Tondano showed lower levels (62 customers; 42 minutes; 9) and Airmadidi fell in between (78 customers; 50 minutes; 13). Sessions with longer waiting times were associated with higher levels of abandonment; however, persistent queue density during the evening peak suggests that the queue did not subside to low levels over the observation period despite rising time costs. Overall, the results provide descriptive evidence consistent with P1–P3 concerning multi-stage queue dynamics, the influence of service-design variation on where congestion accumulates, and the trade-off between time costs and the social-proof value of queuing in customers’ decisions.