Exploring Effective Sensory Experience in the Environmental Design of Sustainable Cafés
Yen-Cheng Chen and
Hsiang-Chun Lin
Additional contact information
Yen-Cheng Chen: Department of Applied Science of Living, Chinese Culture University, Taipei City 111, Taiwan
Hsiang-Chun Lin: Department of Hotel Management, Jin Wen University of Science & Technology, New Taipei City 231, Taiwan
IJERPH, 2020, vol. 17, issue 23, 1-16
Abstract:
The aim of this study was to explore and construct spatial indicators suitable for green café ambience. The indicators were further empirically verified. A three-round questionnaire survey, based on the Delphi method, was conducted with 15 experts, including university professors (food and beverage services management and interior environmental design), café operators, and personnel from government agencies. Data were collected, and the results on the characteristics of the repeated feedback from the experts were convergent. Thirty-six indicators suitable for the design of green café ambience were extracted, of which 17 were verified by actual cafés as highly operable. The five-sense indicators of sustainable green ambience design obtained in this study can facilitate positive customer experiences and enhance the appeal of maintaining sustainable green trends for cafés. These indicators can also provide references for café operators in business planning and green café ambience design.
Keywords: café; green ambience; Delphi method; indicator design (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.mdpi.com/1660-4601/17/23/8957/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/23/8957/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:23:p:8957-:d:454807
Access Statistics for this article
IJERPH is currently edited by Ms. Jenna Liu
More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().