Detecting Customer Queue “at-risk” Behaviors Based on Ethograms to Minimize Overall Service Dissatisfaction

Magali Dubosson, Emmanuel Fragnière, Nathalie Junod, Bettina Willaerts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

40 Downloads (Pure)

Abstract

Every service encounter corresponds to a “queue network” in which a system of waiting lines is connected to servers. We posit that each production service type (e.g., restaurant, airport) requires an adapted queue design in order to maximize attributes salient to customers (i.e., their primary elements of perceived value) in today’s globalized service environment. While the queues have been studied from many angles, a scientific contribution based on a human ethology approach proposing the early identification of “at-risk” behaviors to regulate queue dynamics seems to be novel. To remedy this shortcoming, the large-scale food distribution sector has been chosen for the application of a naturalistic observation approach to describe in detail the behavior of customer queues. Sixteen immersion episodes were conducted in the months between May and June 2016. Using RQDA, we analyzed the immersion transcripts and identified typical customer queue behavioral patterns. Then, we developed an ethogram containing what we considered to be “at-risk” queue behaviors. This ethogram can ultimately be used as an anticipatory indicator in the context of feedforward management controls. Feedforward control, as opposed to classical feedback controls, is based on the early detection of risks and the implementation of mitigation before damage occurs. While this approach requires human attention and expertise (which can be labor-intensive), there is also potential for human ethology to assist managers with supportive or complementary automation. Indeed, the factual description of behaviors contained in our ethogram can easily be coded with modern technology like facial expression and body recognition technologies.

Original languageEnglish
Title of host publicationInternational Conference on Service-Oriented Computing (ICSOC), 2017
Subtitle of host publicationService-Oriented Computing – ICSOC 2017 Workshops
EditorsL. Braubach
Place of PublicationCham, Switzerland
PublisherSpringer Verlag
Pages18-29
Number of pages12
ISBN (Electronic)978-3-319-91764-1
ISBN (Print)9783319917634
DOIs
Publication statusE-pub ahead of print - 16 Jun 2018
Event15th International Conference on Service-Oriented Computing, ICSOC 2017, Workshop track: 2nd Workshop on Adaptive Service-Oriented and Cloud Applications, ASOCA 2017, 2nd Workshop on IoT Systems Provisioning and Management in Cloud Computing, ISyCC 2016, 13th International Workshop on Engineering Service-Oriented Applications and Cloud Services, WESOACS 2017 and Satellite Events - Malaga, Spain
Duration: 13 Nov 201716 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10797

Conference

Conference15th International Conference on Service-Oriented Computing, ICSOC 2017, Workshop track: 2nd Workshop on Adaptive Service-Oriented and Cloud Applications, ASOCA 2017, 2nd Workshop on IoT Systems Provisioning and Management in Cloud Computing, ISyCC 2016, 13th International Workshop on Engineering Service-Oriented Applications and Cloud Services, WESOACS 2017 and Satellite Events
CountrySpain
CityMalaga
Period13/11/1716/11/17

    Fingerprint

Keywords

  • Enterprise risk management
  • Human ethology
  • Service science
  • Waiting line management

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Dubosson, M., Fragnière, E., Junod, N., & Willaerts, B. (2018). Detecting Customer Queue “at-risk” Behaviors Based on Ethograms to Minimize Overall Service Dissatisfaction. In L. Braubach (Ed.), International Conference on Service-Oriented Computing (ICSOC), 2017: Service-Oriented Computing – ICSOC 2017 Workshops (pp. 18-29). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10797 ). Cham, Switzerland: Springer Verlag. https://doi.org/10.1007/978-3-319-91764-1_2