An economic lab experiment for the best offer and approval in face-to-face service interaction situation

Kenju Akai, Keiko Aoki, Kenta Onoshiro

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

Abstract

This article investigates what types of social distance affect the best offer from an employee and its approval from a customer in general service situation. We conduct the deception game (Gneezy, 2005) and investigate the effects of the social distance (face-to-face vs. anonymous interaction) in a laboratory experimental economics method. We observed increases in the rate at which employees made best offers and the rates at which customers accepted offers when face-to-face interactions were conducted. But a statistically significant difference was not observed. Also, the level of trust in others reported by the subject playing the role of the employee had a statistically significant positive effect in cases in which the employee made a best offer. It was also observed that, regardless of whether the interaction was conducted face to face or anonymously, if the subject playing the role of the customer exhibited a low level of tolerance for falsehood, he or she was less likely to accept offers.

Original languageEnglish
Title of host publicationServiceology for Services - 5th International Conference, ICServ 2017, Proceedings
EditorsYoshinori Hara, Dimitris Karagiannis
PublisherSpringer Verlag
Pages64-74
Number of pages11
ISBN (Print)9783319612393
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event5th International Conference on Serviceology for Services, ICServ 2017 - Vienna, Austria
Duration: Jul 12 2017Jul 14 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10371 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Serviceology for Services, ICServ 2017
CountryAustria
CityVienna
Period7/12/177/14/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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