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Constructing a consumption model of fine dining from the perspective of behavioral economics

Overview of attention for article published in PLOS ONE, April 2018
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Article details
Title
Constructing a consumption model of fine dining from the perspective of behavioral economics
Published in
PLOS ONE, April 2018
DOI 10.1371/journal.pone.0194886
Pubmed ID
Authors
Abstract

Numerous factors affect how people choose a fine dining restaurant, including food quality, service quality, food safety, and hedonic value. A conceptual framework for evaluating restaurant selection behavior has not yet been developed. This study surveyed 150 individuals with fine dining experience and proposed the use of mental accounting and axiomatic design to construct a consumer economic behavior model. Linear and logistic regressions were employed to determine model correlations and the probability of each factor affecting behavior. The most crucial factor was food quality, followed by service and dining motivation, particularly regarding family dining. Safe ingredients, high cooking standards, and menu innovation all increased the likelihood of consumers choosing fine dining restaurants.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 17 13%
Student > Ph. D. Student 13 10%
Student > Bachelor 10 8%
Student > Doctoral Student 9 7%
Lecturer 6 5%
Other 13 10%
Unknown 64 48%
Readers by discipline
Readers by discipline Count As %
Business, Management and Accounting 16 12%
Social Sciences 14 11%
Nursing and Health Professions 8 6%
Economics, Econometrics and Finance 4 3%
Engineering 3 2%
Other 18 14%
Unknown 69 52%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 April 2018.
All research outputs
#18,601,965
of 23,041,514 outputs
Outputs from PLOS ONE
#156,674
of 196,494 outputs
Outputs of similar age
#255,517
of 329,169 outputs
Outputs of similar age from PLOS ONE
#2,700
of 3,438 outputs
Altmetric has tracked 23,041,514 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 196,494 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,169 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3,438 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.