Page 1 MKTG204 Integrated Marketing Communications .docx

MKTG204 Integrated Marketing Communications
Consumer insights survey results for Task 2B
1. About this document
The following document has been prepared for students enrolled
in MKTG204 during Session 1, 2016
at Macquarie University. This document provides students with
the information required to complete
Task 2B (Consumer insights report). The following results come
from selected data, collected by
MKTG204 students from the Assessment Task 2A (Consumer
insights data collection).
Please refer to the Assessment Criteria document for details on
the Task 2B assessment and its
marking rubric. The Assessment Criteria document and the
template for completing Assessment Task
2B can both be found on iLearn.
2. Copyright
The following document is a copyright material. Reproduction
of this material without obtaining prior
permission from the unit convenor or deputy convenor is strictly
prohibited.

3. Research aim, questions and significance
This research aims to gain insights into foodie consumers and
the influence of photographic depiction
types of food ads on consumer responses and marketing
communications outcomes for Sara Lee.
This research asks: how foodie consumers can be described and
what the role of photographic
depiction types in food advertising communication is. This
research provides practical implications on
creative and media strategies of marketing communications
campaigns for its new chocolate chip
cookie brand.
4. Research method
This research employed a 1 factor (chocolate chip cookie) x 3
factor (depiction types: Image 1. cookie
alone, Image 2. cookie bitten by a consumer and Image 3.
cookie shared by people) between-subject
experimental online survey (see these visual ad stimuli in Table
2 on page 4). This means each
participant saw one ad in a randomised fashion. Before
exposure, all participants rated their hunger.
All participants were told to view the ad and see if the product
is desirable to eat and that they could
view the ad as long as they wished just like how they viewed a
magazine ad. After exposure, all
participants were asked the same questions to investigate the
influence of photographic depiction
types before providing personal information.
5. How to cite this document

Pitt, J. & Ang, L. (2016). MKTG204 Understanding foodie
consumers and the influence of
photographic depiction types of food ads on consumer
responses: Assessment Task 2B, Session 1,
2016 Consumer insights survey results. North Ryde: Macquarie
University.
Page 2
6. Key constructs, definitions and operationalisations
Table 1. Key constructs investigated in this article with
definitions and operationalisations explained
Key constructs Definitions Operationalisations*
Hunger Consumer subjective evaluation of feeling
desire for food
How hungry are you feeling right now? “0 not at all hungry”, “1
Slightly hungry”, “2 Moderately hungry”, “3 Very hungry”, “4
Extremely hungry”
Brand attitude (ABrand)^ Consumer overall evaluation of the
brand/product
How good or bad do you think Kathy’s Gourmet Brand of choc
chip cookie is?: “-2 Very bad”, “-1 Bad”, “0 Neither good nor
bad”,
“1 Good”, “2 Very good”

Ad attitude (AAd) Consumer overall evaluation of the
advertisement
How much do you like or dislike the ad?: “-2 Dislike very
much”,
“-1 Dislike”, “0 Neither like nor dislike”, “1 Like”, “2 Like
very
much”
Social proof
(Popularity)
Consumer evaluation of the brand/product
popularity influenced by another
consumer’s/other consumers’ actions
depicted in an advertisement
After viewing the ad, how popular or unpopular do you think
the
food is?: “-2 Very unpopular”, “-1 Unpopular”, “0 Neither
popular
nor unpopular”, “1 Popular”, “2 Very popular”
Sociableness of food
experience
Consumer evaluation of the friendliness of the
food consumption experience
The picture seems to convey a food experience that is….: “-2
Very unsociable”, “-1 Unsociable”, “0 Neither sociable nor
unsociable”, “1 Sociable”, “2 Very sociable”
Source (background)
attractiveness

Consumer evaluation of the attractiveness of
visual elements other than the product, text,
logo and slogan
Ignoring the product, text and logo, how attractive or
unattractive
is the rest of the picture?: “-2 Very unattractive”, “-1
Unattractive”,
“0 Neither attractive nor unattractiveness”, “1 Attractive”, “2
Very
attractive”
Source (background)
familiarity
Consumer evaluation of the relatability of
visual elements other than the product, text,
logo and slogan
Ignoring the product, text and logo, how much can you relate to
the picture?: “0 Cannot relate at all”, “1 Can relate very little”,
“2
Can somewhat relate”, “3 Can relate very much”, “4 Can relate
extremely”
*Each construct was measured on a 5-point scale (unless stated
otherwise). Participants were prompted with the above
question/statement for each measure. All
scales were numerically and verbally anchored as shown.
^Key marketing communications outcome

7. Quality control before data collection
We ensured the quality of data prior to data collection by
following Podsakoff, MacKenzie, Lee &
Podsakoff’s (2003) procedural remedies. We counterbalanced
question order where it would not
disrupt the flow of the survey. We used both radio button and
slider scale formats in a randomized
fashion. Rotated scale options were used and randomized. In
addition, all scale points were verbally
and numerically anchored to reduce response biases of scales
anchored only at endpoints among
some respondents who may exhibit extreme response style
(Dolnicar & Grün, 2007).
8. Quality control after data collection
In this survey, 1834 participants were recruited. We excluded
293 participants from analyses based on
pre-defined exclusion criteria. We removed participants who
used mobile devices (n = 76), delayed
responses (n = 86), extreme speeding response (n = 126),
consistent outlying (n = 1) and extreme
flat-lining (n = 4). After elimination, 1541 participants (49%
male) were included for data analyses.
Participants’ age ranged from 18 to 28.
9. Analyses and results

There are two parts in this section: Part 1. Experimental study
and Part 2. Foodie survey. Note that the
number of participants in the experimental study is small. This
is because only a small number of
participants was randomized to participate in this particular
experimental study that we selected to
include in this article.
Part 1: Experimental study
9.1. The effect of depiction type on consumer responses
To understand the effect of depiction type on consumer
responses, we first investigated the mean value
of each depiction type (image) on each construct. The mean
values are shown in Table 2 along with the
depiction types (images) of chocolate chip cookie product on
page 4.
Next, we conducted a number of Independent samples t-tests to
investigate whether the mean values are
significantly different between depiction types. Table 2 shows
mean comparisons and test statistics on
page 5.
Page 4
Table 2. Visual ad stimuli used in the experiment and mean
values of each measure

Construct
Mean value of Image 1:
Cookie alone (n = 21)
Cookie bitten by a consumer (n = 26)
Cookie shared by people (n = 40)
Brand attitude (ABrand) 0.381 0.538 0.575
Ad attitude (AAd) 0.000 0.231 0.575
Social proof
(Popularity)
0.000 0.538 0.725
experience
0.048 0.385 1.175
Source (background)
attractiveness
-0.095 0.269 0.250
Source (background)
familiarity

1.333 1.731 1.850
Notes:
The image sizes shown to participants are 450 x 320 pixels. The
sizes are reduced here for the layout purpose. This research is
not aimed to investigate the
effects of brand name, logo and slogan (Freshness is our
recipe). Hence, these elements are standardised throughout. The
brand name, Kathy’s Gourmet, is
fictitious so that the findings can be easily generalised for a
new brand of the same product.
Mean is the measure of central tendency. It is the average score,
which is calculated by adding up all of the scores from all
sampled participants and then divided
by the total number of sampled participants (n).
Page 5
Table 3. Comparing between two means - Independent samples
t-test results
Mean difference value of

Image 1 Cookie alone
vs.
Image 2 Cookie bitten by
a consumer
with t value and p value
Image 1 Cookie alone
vs.
Image 3 Cookie shared by
people
Image 2 Cookie bitten by a
consumer
vs.
Image 3 Cookie shared by people
Brand attitude (ABrand) -0.158
t (45) = -0.688, p =0.495
-0.194
t (59) = -0.827, p =0.412
-0.037
t (64) = -0.179, p =0.859
Ad attitude (AAd) -0.231

t (45) = -0.849, p =0.400
-0.575
t (59) = -2.323, p =0.024
-0.344
t (64) = -1.510, p =0.136
Social proof
(Popularity)
-0.538
t (34.430) = -1.911, p =0.064
-0.725
t (59) = -2.714, p =0.009
-0.187
t (64) = -0.851, p =0.398
experience
-0.337
t (45 = -1.382, p =0.174
-1.127
t (59) = -4.344, p < 0.001
-0.790
t (64) = -3.483, p =0.001
Source (background)
attractiveness
-0.364

t (34.430) = -1.019, p =0.314
-0.345
t (59) = -1.134, p =0.261
0.019
t (64) = 0.071, p =0.944
Source (background)
familiarity
-0.397
t (34.430) = -1.195, p =0.238
-0.517
t (59) = -1.649, p =0.104
-0.119
t (64) = -0.434, p =0.666
Notes:
Mean difference is the difference between two mean values,
which is calculated by Mean a minus Mean b. For example, the
mean difference of Image 1 vs. Image
2 on ABrand is -0.158, which is derived from the mean value of
Image 1 (0.381) minus the mean value of Image 2 (0.538).
t is a test statistic to test whether the two mean values are
significantly different from zero (in this context). When the t
value is + or -1.96, it means
the difference is significant at 95% Confidence interval.
p is a test statistic to test how it is evidently weak or strong to

reject the null hypothesis (i.e. in this context the null hypothesis
is that Mean a –
Mean b = 0 or no difference). When the p value is smaller than
or equal to 0.05 (i.e. <= 0.05), it means there is strong evidence
against the null
hypothesis (i.e. there is a significant difference). When the p
value is larger than 0.05 (i.e. >0.05), it means there is a weak
evidence to reject the
null hypothesis (i.e. there is no significant difference). If the p
value ranges from 0.051 to 0.100, it means there is a moderate
evidence to reject
the null hypothesis (i.e. the difference is marginally
significant).
Page 6
9.2. The influence of Ad attitude (AAd), Social proof
(Popularity), sociableness of food experience,
source (background) attractiveness, source (background)
familiarity and hunger on Brand attitude
(ABrand)
Next, we combined the data from the experimental study (n =
87) and investigated if AAd, Social proof
(Popularity), sociableness of food experience, source
(background) familiarity, source (background)
attractiveness and hunger could significantly influence Brand
attitude (ABrand) by conducting a multiple
regression analysis with ENTER approach. Brand attitude
(ABrand) was loaded as the dependent variable
and all other variables were loaded as predictors in the order
appeared above. Table 4 shows the multiple
regression results. In addition, the model showed that it

significantly explained the variation in ABrand (R2 =
0.191, p = 0.008).
Table 4. Multiple regression results.
Model
Unstandardized
Coefficients
Standardized
Coefficients
t value p value
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) .567 .203 2.796 .006
AAd .081 .111 .092 .732 .466 .634 1.578
Social proof
(Popularity)
.243 .109 .286 2.226 .029 .613 1.632
Sociableness of
food experience
.052 .097 .064 .534 .595 .701 1.426
Source
(background)

familiarity
-.049 .089 -.067 -.546 .586 .663 1.508
Source
(background)
attractiveness
.106 .094 .146 1.125 .264 .599 1.670
Hunger -.104 .068 -.165 -1.540 .128 .884 1.131
Notes:
Multiple regression is a model in which an outcome (i.e.
ABrand in this context) is predicted by a linear combination of
two or more predictor variables (i.e. AAd, Social proof
(Popularity), sociableness of food experience, source
(background) familiarity, source (background) attractiveness
and hunger). That is: Yi = b0 + b1X1i + b2X2i + … + bnXni)
+ Ɛi.
B is an unstandardized value of coefficient of determination or
the proportion of variance in the outcome variable (i.e.
ABrand in this context) explained by a predictor variable. For
081. This
means when AAd increases by one unit (i.e. scale point), it is
estimated that ABrand would increase by 0.081.
t and p are test statistics – in this multiple regression context,
the values show whether the B value is significantly
differe

ABrand is 0.466. This means there is a weak evidence to reject
the null hypothesis (i.e. B = 0). Put simply, AAd could not
significantly predict ABrand when other predictors were
included in the model.
VIF is variance inflation factor, a measure of multicollinearity.
The VIF indicates whether a predictor has a strong
linear relationship with other predictors. If the VIF value is
greater than 5, it suggests that multicollinearity may be
biasing the regression model.
Page 7
Part 2: Foodie survey
9.3. About foodie consumers
Next, we looked at the entire survey (not just the experimental
study) to develop an understanding of
foodie consumers (n = 1541). Below are descriptive statistics
that give insights into foodie consumers.
9.3.1. Question: How true or untrue does the following
statement describe you? "I am a foodie",
measured on a 5 point bipolar scale: “-2 Very untrue of me”, “-1
Untrue of me”, “0 Neither true nor untrue
of me”, “1 True of me”, “2 Very true of me”
Table 5.1 How true or untrue does the following statement

describe you? – All participants
Scale Frequency Percent
-2 84 5.5
-1 224 14.5
0 473 30.7
1 557 36.1
2 203 13.2
Total 1541 100.0
Table 5.2 How true or untrue does the following statement
describe you? – By gender (Count)
Scale
Total -2 -1 0 1 2
Gender Male 51 135 250 243 71 750
Female 33 89 223 314 132 791
Total 84 224 473 557 203 1541

9.3.2. Question: Food is .................... my passion, measured on
a 5 point unipolar scale: “0 Not at all”,
“1 Not very much”, “2 Somewhat”, “3 Very much”, “4 Totally”
Table 6.1 Food is .................... my passion – All participants
0 65 4.2
1 219 14.2
2 502 32.6
3 524 34.0
4 231 15.0
Total 1541 100.0
Table 6.2 Food is .................... my passion – By gender
(Count)
Scale
Total 0 1 2 3 4

Gender Male 37 129 263 235 86 750
Female 28 90 239 289 145 791
Total 65 219 502 524 231 1541
Page 9
9.3.3. Question: I have …………….. interest in food, measured
on a 5 point unipolar scale: “0 No”, “1 A
little”, “2 Some”, “3 Much”, “4 A lot of”
Table 7.1 I have …………….. interest in food – All participants
0 33 2.1
1 141 9.1
2 359 23.3
3 522 33.9
4 486 31.5
Total 1541 100.0

Table 7.2 I have …………….. interest in food – By gender
(Count)
Scale
Total 0 1 2 3 4
Gender Male 16 80 204 248 202 750
Female 17 61 155 274 284 791
Total 33 141 359 522 486 1541
Page 10
9.3.4. Question: Imagine if the blue circle / represents your
identity and the red circle represents
food. Which picture best / describes your relationship with
food?, measured on a 5 point unipolar
scale using a venn diagram:
0

1
2
3
4
Table 8.1 Imagine if the blue circle / represents your identity
and the red circle represents food. Which
picture best / describes your relationship with food? – All
participants
0 56 3.6
1 240 15.6
2 472 30.6
3 447 29.0
4 326 21.2
Total 1541 100.0
Table 8.2 Imagine if the blue circle / represents your identity
and the red circle represents food. Which

picture best / describes your relationship with food? – By
gender (Count)
Scale
Total 0 1 2 3 4
Gender Male 29 131 236 207 147 750
Female 27 109 236 240 179 791
Total 56 240 472 447 326 1541
Page 11
9.3.5. Question: Which picture best describes your feelings
when you talk about food?, measured
on a 5 point bipolar scale with picture-oriented manikins:
-2
Hate
very much
-1

Hate
0
Neither love nor
hate
1
Love
2
Love
very much
Table 9.1 Which picture best describes your feelings when you
talk about food? – All participants
-2 9 .6
-1 31 2.0

0 292 18.9
1 709 46.0
2 500 32.4
Total 1541 100.0
Table 9.2 Which picture best describes your feelings when you
talk about food? – By gender (Count)
Scale
Total -2 -1 0 1 2
Gender Male 0 21 166 367 196 750
Female 9 10 126 342 304 791
Total 9 31 292 709 500 1541
###### END OF DOCUMENT ######

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