Decoding the Dining Atmosphere: Ambient Conditions and Customer Satisfaction in Restaurant Servicescapes

This study investigates the effects of ambient conditions, one of the essential dimensions of the Servicescape Model, on restaurant customer satisfaction. Ambient conditions like lighting, music, scent, and temperature are extremely influential in shaping customer feelings and perceptions. Based on Bitner's Servicescape and the Stimulus-Organism-Response (S-O-R) model, the study collected data from 230 survey participants in Indian urban restaurants. Using descriptive statistics, correlation matrices, and multiple regression analysis, the research determines scent and lighting to be strong predictors of satisfaction, then music. Temperature, although applicable, failed to show a statistically significant effect. Results of the findings provide practical implications for optimizing service environments in the hospitality industry.

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Publication Details

Journal
Asean Journal on Hospitality and Tourism
Published
2025-08-31
DOI
https://doi.org/10.5614/ajht.2025.23.2.05
Primary Topic
Consumer Retail Behavior Studies
Type
article
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article

Decoding the Dining Atmosphere: Ambient Conditions and Customer Satisfaction in Restaurant Servicescapes

Nilanjan Ray, Moumita Roy, Pema Lama, Tanmoy Majumder
Asean Journal on Hospitality and Tourism
Consumer Retail Behavior Studies
article

Decoding the Dining Atmosphere: Ambient Conditions and Customer Satisfaction in Restaurant Servicescapes

Nilanjan Ray, Moumita Roy, Pema Lama, Tanmoy Majumder
article en

Abstract

This study investigates the effects of ambient conditions, one of the essential dimensions of the Servicescape Model, on restaurant customer satisfaction. Ambient conditions like lighting, music, scent, and temperature are extremely influential in shaping customer feelings and perceptions. Based on Bitner's Servicescape and the Stimulus-Organism-Response (S-O-R) model, the study collected data from 230 survey participants in Indian urban restaurants. Using descriptive statistics, correlation matrices, and multiple regression analysis, the research determines scent and lighting to be strong predictors of satisfaction, then music. Temperature, although applicable, failed to show a statistically significant effect. Results of the findings provide practical implications for optimizing service environments in the hospitality industry.

Asean Journal on Hospitality and TourismVol. 23(2)
University of Calcutta (IN)
Openalex Percentile: Top 69%
Consumer Retail Behavior Studies
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Decoding the Dining Atmosphere: Ambient Conditions and Customer Satisfaction in Restaurant Servicescapes — Nilanjan Ray, Moumita Roy, et al. · Asean Journal on Hospitality and Tourism (2025) | TGRS Research Map | TGRS