Citation
(2017), "Corrigendum", Journal of Product & Brand Management, Vol. 26 No. 4, pp. 429-432. https://doi.org/10.1108/JPBM-07-2017-999
Publisher
:Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited
It has come to our attention that the article “Peak-end pizza: prices delay evaluations of quality” by David R Just, Ozge Sigirci and Brian Wansink published in Journal of Product & Brand Management, Vol. 24 Issue: 7, pp. 770-778 contains errors in the data presented and does not fully attribute one of the sources drawn upon.
In response to recent criticism of the original work and in addition to institutional reanalysis, the authors have sought the independent feedback of a researcher at Mathematica Policy Research who has in turn reviewed the text, tables and Stata output contained in this correction for consistency. Mathematica was compensated for this work.
These analyses focused on pizza; therefore, diners who did not report eating at least one piece of pizza were not included in the analyses. Consistent with the original manuscript, two additional diners were eliminated from this analysis because one person’s height was noted as 8 inches and another one’s weight was noted as 450 lbs.
Table I originally reported the number of observations for each column erroneously as n = 62, n = 60 and n = 122 for the US$4 buffet, US$8 buffet and all treatments, respectively. In fact, the number of observations varies by question due to respondents skipping questions. The corrected table, below, lists the number of observations for each cell. In addition, there are two other slight changes due to rounding errors (all changes appear in bold type). The online version of Table I has been corrected to attribute the original source “Lower Buffet Prices Lead to Less Taste Satisfaction” published in Journal of Sensory Studies, 2014, 29, 5.
In conducting this updated analysis, the authors opted to use Stata 14.0 for convenient scripting and log file generation and to use a Hotelling’s test of differences in ratings rather than the F-test reported in the article. The article reports F-tests for differences in average ratings of first, middle and last slice, respectively, of 16.56 (p = 0.00) and 0.65 (p = 0.53) for the US$4 and US$8 conditions, respectively. The Hotelling’s test produces F-statistics of 10.44 (p < 0.01) and 0.98 (p = 0.39), respectively. Minor differences in rounding were found in Tables II and III. Note that in Table III, different numbers of observations are used for each line due to differential response rates to survey questions. A full script and log file can be found here: https://doi.org/10.6077/J5CISER2783
These errors have been corrected in the online version. The authors apologize sincerely for these errors.
Corrected descriptive statistics
Demographics | Half price ($4) | Full price (US$8) | All treatments | F-test (p-value) |
---|---|---|---|---|
Age | 44.16 (19.00) | 46.08 (14.46) | 45.12 (16.82) | 0.42 (0.52) |
(N) | (64) | (65) | (129) | |
Height | 68.52 (3.95) | 67.91 (3.93) | 68.22 (3.94) | 0.76 (0.38) |
(N) | (64) | (63) | (127) | |
Weight | 180.84 (48.37) | 182.31 (48.41) | 181.53 (48.19) | 0.03 (0.87) |
(N) | (62) | (54) | (116) | |
Number in group | 3.03 (1.52) | 3.28 (1.29) | 3.16 (1.41) | 1.04 (0.31) |
(N) | (65) | (68) | (133) | |
Other potential utility measures | ||||
I was hungry when I came in | 6.62 (1.85) | 6.64 (2.06) | 6.63 (1.96) | 0.00 (0.95) |
(N) | (66) | (70) | (136) | |
I am hungry now | 1.88 (1.34) | 1.85 (1.75) | 1.86 (1.55) | 0.01 (0.91) |
(N) | (67) | (66) | (133) |
Regression analysis for first, middle, last and peak taste ratings of the pizza and the overall evaluation of the taste of the pizza
Variables | Half price (US$4) | Full price (US$8) | All treatments | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Models | Models | Models | |||||||||||||
Beginning Model B (SE) | Total Model B (SE) | End Model B (SE) | Peak Model B (SE) | Peak-End Model B (SE) | Beginning Model B (SE) | Total Model B (SE) | End Model B (SE) | Peak Model B (SE) | Peak-end Model B(SE) | Beginning Model B (SE) | Total Model B (SE) | End Model B (SE) | Peak Model B (SE) | Peak-end Model B (SE) | |
Taste of first slice | 0.92** (0.07) | 0.79** (0.10) | 0.97** (0.02) | 1.06** (0.07) | 0.96** (0.03) | 0.85** (0.06) | – | – | – | ||||||
Taste of middle slice | – | 0.26 (0.13) | −0.11 (0.18) | 0.15 (0.10) | – | – | – | ||||||||
Taste of last slice | – | 0.07 (0.09) | 0.55** (0.08) | 0.21** (0.06) | −0.01 (0.18) | 0.97** (0.11) | 0.37 (0.30) | 0.10 (0.08) | 0.65** (0.06) | 0.21** (0.07) | |||||
Peak taste | – | – | – | 0.91** (0.08) | 0.86** (0.10) | 0.99** (0.07) | 0.68* (0.32) | 0.96** (0.05) | 0.85** (0.09) | ||||||
R2 | 0.75 (n = 62) | 0.86 (n = 41) | 0.49 (n = 47) | 0.70 (n = 62) | 0.82 (n = 47) | 0.97 (n = 60) | 0.96 (n = 26) | 0.68 (n = 38) | 0.79 (n = 60) | 0.71 (n = 38) | 0.87 (n = 122) | 0.90 (n = 67) | 0.56 (n = 85) | 0.75 (n = 122) | 0.78 (n = 85) |
R̄2 | 0.74 | 0.85 | 0.48 | 0.69 | 0.81 | 0.97 | 0.96 | 0.67 | 0.78 | 0.70 | 0.87 | 0.90 | 0.55 | 0.75 | 0.77 |
Regression statistics for all models
Models | Taste | ||
---|---|---|---|
Half price (US$4) | Full price (US$8) | All treatments | |
R̄2 | R̄2 | R̄2 | |
a. Regression statistics for taste | |||
Beginning model | 0.74 | 0.97 | 0.87 |
Total model | 0.85 | 0.96 | 0.90 |
End model | 0.48 | 0.67 | 0.55 |
Peak model | 0.69 | 0.78 | 0.75 |
Peak-end model | 0.81 | 0.70 | 0.77 |
b. Regression statistics for satisfaction | |||
Models | Satisfaction | ||
Half price (US$4) | Full price (US$8) | All treatments | |
R̄2 | R̄2 | R̄2 | |
Beginning model | 0.46 | 0.78 | 0.64 |
Total model | 0.60 | 0.78 | 0.68 |
End model | 0.44 | 0.74 | 0.58 |
Peak model | 0.52 | 0.52 | 0.53 |
Peak-end model | 0.62 | 0.75 | 0.63 |
c. Regression statistics for enjoyment | |||
Models | Enjoyment | ||
Half price (US$4) | Full price (US$8) | All treatments | |
R̄2 | R̄2 | R̄2 | |
Beginning model | 0.57 | 0.75 | 0.68 |
Total model | 0.69 | 0.74 | 0.71 |
End model | 0.50 | 0.47 | 0.50 |
Peak model | 0.58 | 0.58 | 0.59 |
Peak-end model | 0.73 | 0.51 | 0.64 |
Different numbers of observations are used for each line due to differential response rates to survey questions. Therefore, the sample size differs by row (i.e. model) within a column