Market Research Report Master

1
Examination of the Likelihood of Griffith Gold
Coast University Students
to buy produce Online
Individual Market Research Report
7207MKT Market Research Course
–
Course Convenor: Dr Helen Perkins
Griffith University Gold Coast campus, QLD
By
Robert KriTikos
s2788287
21 October 2011

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Table of Contents
Table of Contents.................................................................................................................................1
Abstract................................................................................................................................................4
Introduction .........................................................................................................................................5
Problem Definition...............................................................................................................................7
Research Question...............................................................................................................................7
Research Objectives.............................................................................................................................7
Research Objective 1 .......................................................................................................................7
Hypothesis 1.................................................................................................................................7
Hypothesis 2.................................................................................................................................7
Hypothesis 3.................................................................................................................................7
Hypothesis 4.................................................................................................................................7
Research Objective 2 .......................................................................................................................7
Hypothesis 5.................................................................................................................................8
Hypothesis 6.................................................................................................................................8
Hypothesis 7.................................................................................................................................8
Hypothesis 8.................................................................................................................................8
Hypothesis 9.................................................................................................................................8
Hypothesis 10...............................................................................................................................8
Hypothesis 11...............................................................................................................................8
Hypothesis 12...............................................................................................................................8
Methodology........................................................................................................................................9
Participants ......................................................................................................................................9
Survey Instrument............................................................................................................................9
Procedure.......................................................................................................................................10
Ethics..............................................................................................................................................10
Results................................................................................................................................................11
Descriptives....................................................................................................................................11
Hypotheses Testing....................................................................................................................13
Research Objective 1 .................................................................................................................13
Hypothesis 1...............................................................................................................................13
Hypothesis 2...............................................................................................................................15
Hypothesis 3...............................................................................................................................16
Hypothesis 4...............................................................................................................................17
Research Objective 2 .................................................................................................................18
Hypothesis 5...............................................................................................................................18
Hypothesis 6...............................................................................................................................19
Hypothesis 7...............................................................................................................................20
Hypothesis 8...............................................................................................................................21
Hypothesis 9...............................................................................................................................22
Hypothesis 10.............................................................................................................................22
Hypothesis 11.............................................................................................................................23
Hypothesis 12.............................................................................................................................23
Discussion...........................................................................................................................................25
Implications........................................................................................................................................26
Limitations and Recommodation.......................................................................................................27
Citation...............................................................................................................................................28

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Appendix 1: Ethics Applications.........................................................................................................29
Appendix 2: Survey Instrument .........................................................................................................30

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Abstract
The study determines how likely university students are to buy their produce online. The study has
been conducted at Griffith University Gold Coast campus. Students of various disciplines were
asked to fill out a survey that consisted of 14 questions regarding students’ demographics, grocery
shopping habits and specific factors that would encourage them to buy produce online. Nominal
type of data was collected within categorical level of mesurement. Numerical type of data was
collected by using Likert scales of measurement. Twelve hypotheses were tested against a
significance level of .05 (p‐value). Tests included independent samples t test, ANOVAs, correlations
as well as regressions. Categorical data was analysed by reporting frequencies and percentages.
The underlying result of the study was that students were not particularly interested in the idea of
buying produce online as the majority stated that they were unlikely to buy groceries online.
However, respondents emphasized on the importance of ‘price’ followed by ‘quality’ as a factor
that would encorage them to buy groceries online. It can be therefore inferred that focusing on
these two aspects would in fact increase the liklihood of the respondents of buying produce
online.

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Introduction
Research from Boston in 2006 found that 98% of college students have made purchases online
(Experience Inc, 2011).  When a study of online grocery shopping was completed in Denmark
and the United Kingdom, there were a variety of factors to consider.  Many participants viewed
online shopping in terms of attributes offered, and beliefs towards the products and service
(Ramus & Nielson, 2005). The customers were impressed with online grocery shopping
because of its convenience and lack of line‐ups.  Also, avoiding crowded shops that require
lengthy commutes, visits, and competing with other customers was viewed as a positive
attribute.  Customers had concerns with the degree of risk associated with online shopping,
specifically the trust and payment system.  There was also a belief that selection and quality
may be compromised, or a visit online in lieu of a visit to the grocery store may cause the
customer to miss specials or sales.  As well, customers expressed a concern with the complaint
process related to online shopping, as they would not be interacting with other people during
the purchase process.  The sphere of influence was an important factor as to why customers
began shopping online, as was their exposure to advertisements for the sites.  Furthermore,
many customers said they started online shopping through accidental browsing, or following
links from related commercial sites (Ramus & Nielson, 2005).
Research performed on university students in 2009 focused on the shopping habits of
university students, with a focus on internet clothing shops compared to brick and mortar
shops (Arnaudovska, Bankston, Simurkova, & Budden, 2010). It was found that university
students have a technological focus, and were comfortable shopping online.  The respondents
believed shopping online was the best way to get the best price and value for their time,
however, the 80.6% of the students still responded that they were likely to make purchases in
store, rather than online (Arnaudovska et al, 2010).
Students in Newcastle University, United Kingdom were studied to determine if there is an
association between time and food shopping (Dobson & Ness, 2009). Convenience was found
as a significant factor for students in terms of their buying behaviour.  As well, three distinct
segments of buying behaviour were identified, allowing for better targeting of products and
services.  However, this research was not generalizable, as it relied on a small convenience
sample.  The researchers themselves state, “the context of student grocery shopping is worth
further research.” (Dobson & Ness, 2009)

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Research of the online shopping behavior in two key segments of the world’s most advanced IT
nations, Finnish and American university students suggests that the amount of online shopping
has increased in both countries.  It was also noticed that the average monetary amount of
purchase has decreased in Finland, while the purchase quantities have increased, giving clues
that people are going online for more ‘everyday’ type of shopping. The internet also has
increased in popularity as a tool used to contribute to and assist in the buying process.  As the
total number of online purchases continues to increase, the e‐marketer who effectively serves,
satisfies, and delights their online buyers will enjoy repeat patronage. (Comegys, Hannula, &
Väisänen, 2006).
Another research made in the Boston area says that many implications suggest that young
people, both single and married, are stressed for time and that these people are a potential
market for online grocery shopping. (Corbett, 2001)
Other findings show that many consumers revert to the traditional mode of supermarket
shopping whenever they are dissatisfied either with specific or with general aspects of the
online experience, which suggests that the process of diffusion of the e‐grocery innovation by
no means follows a smooth and continuous path. The adoption decision seems to be re‐
evaluated more frequently and consequently post‐adoption evaluation appears very important
to the decision of whether to continue with or to drop the innovation. This finding basically
means that the offline and online modes of grocery shopping are complementary, rather than
substitutive. Results also suggest that the reliability of the service provided, both in terms of
delivery and the price, quality and range of the goods on offer, is a crucial factor for loyalty to a
website, meaning that dissatisfaction with any of these aspects may trigger the termination of
e‐grocery shopping (Dall'Olmo Riley, Hand, Rettie, Robinson, & Singh, 2007).
Online grocery shopping seems to be hindered by several factors. Groceries are tangible
products and that challenges the full commercial cycle to be unattainable via a network.
Another fact is that groceries are perishable products meaning that consumers’ want physically
see and touch these products for their quality and consumers have different preferences for
products. By example some like bananas green when others like them ripe.
A survey with 3800 consumers points out that about 400 respondents currently shop online,
and about 500 have shopped online in the past, but not anymore.  The majority use Coles
online shop, followed by Woolworths' online shop (Browne, 2010).

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Problem Definition
Little research has been done on the grocery purchasing habits of university students.  The
research that has been done has not been comprehensive, with the researchers stating that
further research may need to be done in order to complete the picture. Particularly, there is
little focus on validity of creating an online grocery store targeted towards university students.
Research Question
How likely are university students to buy their produce online?
Research Objectives
Research Objective 1
To investigate the perception of university students towards the idea of buying produce online.
Hypothesis 1
University students will be interested in buying produce online if it provides them with
perceived benefits by comparing those who are likely to buy groceries online with the factors
that would encourage them to use the service.
Hypothesis 2
Students will be opposed to the idea of buying groceries online if they value a physical
interaction with their produce.
Hypothesis 3
Students who drive to the grocery store will be less likely to purchase groceries online than
students who do not drive.
Hypothesis 4
Respondents who value knowledgeable staff at brick and mortar stores will be less likely to
switch to buying groceries online than those who do not value that factor.
To determine what factors would make university students switch from buying produce in a
store to buying produce online.

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Hypothesis 5
It is assumed students are limited by budget constraints, and price will be the most important
factor in both online and brick and mortar grocery stores when compared to the other factors
analyzed.
Hypothesis 6
Students with a job will be more interested in the convenience an online produce market
would afford them than students without one.
Hypothesis 7
Female students will be more concerned with Prices, Layout of Store, and Quality factors than
male students.
Hypothesis 8
Students who are aware of the price wars between the major grocery chains will consider the
factor of price important, in both online and brick and mortar stores.
Hypothesis 9
People who are further away from their local grocery store will be more likely to buy groceries
online than those who do not.
Hypothesis 10
People who grocery shop more often will be more likely to buy groceries online than those
who do not.
Hypothesis 11
People who go to the store to get ideas are more likely to value a selection in an online shop.
Hypothesis 12
Business and health students would be more likely to purchase online than any other faculty

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Methodology
Participants
Participants were located on the Gold Coast Griffith University Campus and selected based on
enrollment at the University as a full or part time student.  The sampling method used was a
non‐probability judgment convenience sample.  A total of 51 students were surveyed, and all
surveys were completed on campus. 27 of the respondents were female (52.9%), while 24
were male (47.1%).
Survey Instrument
Quantitative and qualitative research was done in the form of a questionnaire, which was
designed in accordance with the hypotheses to collect information about grocery purchasing
habits of Griffith University students. Specially designed questions helped to understand the
grocery shopping habits amongst Griffith University students. The questionnaire also helped to
determine the reliability and validity of the hypotheses.
Specific information was collected to get to know both the in‐person and online grocery
purchasing habits of University students by asking questions similar to the following:
- How often do you grocery shop?
- How close is your local grocery store?
- How do you get to your grocery store?
- What is your primary consideration when choosing where to buy groceries?
- Would you buy groceries online?
- Why wouldn’t you buy groceries online?
- What types of fruits and veggies do you buy?
- Which fruits and veggies do you think are too expensive?
- Are the prices of your favorite fruits and veggies affected by the price wars between the
major grocery stores?

These questions measured customers’ attitudes or potential behaviors and were measured
using a Likert scale with options ranging from 1 to 5, where 1 indicates not important or
unlikely and 5 indicates essential or very likely.  A copy of the survey can be found in Appendix
2.

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Procedure
The survey was distributed on the Gold Coast Griffith University Campus from September 9th
,
2011 to September 22, 2011. Participants were approached by researchers, asked if they
attended Griffith University and asked if they would be interested in filling out a quick survey.
Once data was collected, it was collated into an SPSS file with SPSS version 18.0 used to code
and measure data.
Ethics
Participants were given an informed consent cover sheet and ensured no identifiable personal
data would be collected.  As well, the survey was operated under the following ethics protocol
number: MKT/04/10/HREC.  A copy of the ethics application can be found in Appendix 1.

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Results
Descriptives
The sample was nearly equally split between male (47%)
and female students (53%) of the Griffith University Gold
Coast campus with the majority of the respondents
studying Business and Commerce (53%), followed by a
considerable portion of health students (19.6%), as well as
educational students accounting for nearly 10 per cent (9.6%).
The remaining respondents were from
study areas including environment (5.9%),
criminology, visual & arts and engineering
with each corresponding group
representing 3.9 per cent. Of all the
participants roughly 45 per cent (45.1%)
had a job compared to almost 55 per cent
(54.9%) who did not have a job.  Almost every one of the surveyed students (98%) had access
to the Internet.

Table 3
As far as the grocery shopping habits, the majority of respondents (52.9%) stated that they
would at least shop groceries once a week. There was a stalemate between the participants
shopping only every other fortnight,
compared to the participants who were
shopping twice a week with both groups
accounting for nearly 22 per cent (21.6%)
each. Over 88 per cent of the respondents
lived within 2 kilometers of a grocery store,
while 52.9 per cent of the respondents
would choose to walk to the grocery store compared to 47.1 per cent preferring to drive to the
Gender
Frequency Valid Percent
male 24 47.1
femal
e
27 52.9
Vali
d
Total 51 100.0
Table 1
What is your study discipline
business and commerce 27 52.9
criminology and law 2 3.9
education 5 9.8
engineering 2 3.9
environment 3 5.9
health 10 19.6
Visual and creative arts 2 3.9
Valid
Total 51 100.0
Table 2
Do you have internet
yes 50 98.0
no 1 2.0
Valid
Total 51 100.0
Do you have a job
yes 23 45.1
no 28 54.9
Valid
Total 51 100.0
Table 4
How often do you grocery shop

Once a month 2 3.9
Once every 2 weeks 11 21.6
Once a week 27 52.9
Twice or more a week 11 21.6
Valid
Total 51 100.0

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grocery store. As for the remaining respondents, cycling (5.9%) or public transportation
(11.8%) was the preferred means of transportation.

When asked what their top three
produces were, 13 of the participants
(26%) listed apples first followed by
tomatoes, capsicums and bananas
second, answered by 4 respondents
equivalently corresponding to 8
Table 6 percent each (see Figure 1).
The second most listed
produce were again
apples answered by 10
(20%), ahead of
tomatoes stated by 6
(12%) and oranges
mentioned by five (10%)
students respectively
(See Figure 2).
As detailed in Table 7 the importance of the following factors including price, distance to store,
knowledgeable and courteous staff, layout of store as well as quality of produce were
How close is your local grocery store
less than 500m 8 16.0
500m‐1km 18 36.0
1km‐2km 18 36.0
more than 2km 6 12.0
Valid
Total 50 100.0
Missing System 1
Total 51
Figure 3
Figure 1

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measured. The participants were asked which of these factors would influence their decision
the most when choosing where to buy groceries. A Likert scale had been applied in order to
calculate means signifying importance ranging from 1 to 5, thereby 1 translating to ‘would not
encourage me’ while 5 translating to ‘would definitely convince me’.
Importance of different features  when choosing where to buy groceries
Importance of different features   Mean Std. Deviation
How important is price 4.16 .703
How important is distance to the store 3.86 .800
How important is knowledgeable and courteous staff 2.51 .880
How important is the layout of the store 3.04 .871
How important is the quality of produce 4.37 .720
Table 7
By comparing these means it was reported that the most important factor was quality ( m=
4.37, SD= 0.720) ahead of price (m= 4.16, SD= 0.703) when choosing where to buy groceries.
Hypotheses Testing
To investigate the perception of university students towards the idea of buying produce online.
Hypothesis 1
The first hypothesis examined the factors or benefits that would encourage the surveyed students to
buy groceries online. Factors including price, quality of produce, convenience, availability are all
significant predictors of likelihood of buying groceries online (significance of the regression ANOVA p =
.048, p < .05). These factors combined account for 21.4% of the variance of likelihood of the
respondents buying groceries online (r2
=.214) with the highest predictor being price (Beta =.577).
In order to assess the relationship between the factors and the likelihood of buying groceries online, a
bi‐variate Pearson’s correlation was conducted. Price was found to be the only positive and moderately
strong related (r= .428) factor (see Table 11). The remaining factors were only weak positive correlated.

The only “perceived benefit” that would influence people to buy online was therefore price.
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .462
a
.214 .126 1.035
a. Predictors: (Constant), Would selection encourage you to buy online, Would price encourage you to buy
online, Would convenience encourage you to buy online, Would quality of produce encourage you to buy online,
Would availability encourage you to buy online
1

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Table 8
ANOVA
b

Model Sum of Squares df Mean Square F Sig.
Regression 13.112 5 2.622 2.447 .048
a

Residual 48.221 45 1.072
1
Total 61.333 50
a. Predictors: (Constant), Would selection encourage you to buy online, Would price encourage you to buy
online, Would convenience encourage you to buy online, Would quality of produce encourage you to buy online,
Would availability encourage you to buy online
b. Dependent Variable: How likely would you be to buy groceries online
Table 9
Coefficients
a

Unstandardized
Coefficients
Standardized
Coefficients
Model B Std. Error Beta t Sig.
(Constant) .503 .890 .565 .575
Would price encourage you to buy online .688 .218 .577 3.156 .003
Would quality of produce encourage you to
buy online
‐.160 .190 ‐.140 ‐.842 .404
Would convenience encourage you to buy
online
‐.078 .184 ‐.063 ‐.423 .674
Would availability encourage you to buy
online
‐.179 .240 ‐.145 ‐.747 .459
1
Would selection encourage you to buy
online
.214 .191 .191 1.123 .267
a. Dependent Variable: How likely would you be to buy groceries online
Table 10
Correlations

How likely would you be to
buy groceries online
Would price encourage you
to buy online
Pearson
Correlation
1 .428
**

Sig. (2‐tailed) .002
How likely would you be to
N 51 51
Pearson
Correlation
.428
**
1
Sig. (2‐tailed) .002
Would price encourage you to
buy online
N 51 51
**. Correlation is significant at the 0.01 level (2‐tailed).
Table 11

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Hypothesis 2
In order to test Hypothesis 2 and to assess whether the students were opposed to the idea of
buying groceries online if the value a physical interaction with their produce ,an independent‐
samples t‐test was undertaken. The hypothesis was not supported as there was no significant
difference in the number of people who were likely and unlikely to buy groceries if they like to
see what they buy (p =.785, p > .05) However, 4 respondents did emphasize the fact that
ensuring fresh produce is an essential part of their in‐store grocery shopping experience, by
filling out the “other” section of the question.
Independent Samples Test
Levene's Test
for Equality of
Variances t‐test for Equality of Means
95% Confidence
Interval of the
Difference

F Sig. t df
Sig. (2‐
tailed)
Mean
Difference
Std. Error
Difference Lower Upper
Equal
variances
assumed
.030 .862 .275 49 .785 .094 .344 ‐.596 .785 How likely
would you be
to buy
groceries
online Equal
variances
not
assumed

.274 26.174 .786 .094 .344 ‐.613 .802
Table 12

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Hypothesis 3
An independent samples t test was undertaken to examine whether students who drove to
the grocery store would be less likely to purchase groceries online than students who did
not drive. The t test was statistically significant (p < .05), with the people who drive will be
less likely to purchase groceries online (M=2.0, SD =1.251) than those who do not (M=2.63,
SD =.884).
Levene's Test
for Equality of
95% Confidence
Interval of the
Difference

F Sig. t df
Sig.
(2‐
tailed)
Mean
Difference
Std. Error
Equal
variances
assumed
2.217 .143 2.094 49 .041 .630 .301 .025 1.234 How likely
would you
be to buy
groceries
online
Equal
variances
not
assumed

2.052 40.817 .047 .630 .307 .010 1.249
Table 13
Group Statistics

drive N Mean Std. Deviation Std. Error Mean
no 27 2.63 .884 .170 How likely would you be to
yes 24 2.00 1.251 .255
Table 14

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Hypothesis 4
A one‐way between groups analysis of variance (ANOVA) was used to investigate whether
students who valued knowledgeable staff at brick and mortar stores would be less likely to
switch to buying groceries online than those who do not value that factor. The ANOVA was
statistically not significant (p= .838, p > .05). There is not a significant difference in the
likelihood to buy groceries online between those who value knowledgeable staff and those
who do not. The hypothesis was therefore not supported.
ANOVA
How likely would you be to buy groceries online
Sum of Squares df Mean Square F Sig.
Between Groups 1.086 3 .362 .282 .838
Within Groups 60.248 47 1.282
Total 61.333 50
Table 15

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To determine what factors would make university students switch from buying produce in a
store to buying produce online.
Hypothesis 5
By comparing the means of the different factors in order to find out whether students would
evaluate price as the most important factor in both online and brick and mortar grocery stores,
price was rated as important (M = 4.157). However, quality was rated to be the most
important (M= 4.373). Therefore, the fifth hypothesis that budget constraint students would
evaluate price to be the most important factor in both online and brick and mortar stores
when compared to all other analyzed factors was not supported.

Figure 4

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Hypothesis 6
An independent samples t test was used to compare whether students with a job would be
more interested in the convenience an online produce market would afford them compared to
students without a job. There was no significant difference between those who do have a job
and those who do not in valuing convenience an online produce market would afford them (p
= .246, p > .05)
Levene's Test
for Equality
of Variances t‐test for Equality of Means
95% Confidence
Interval of the
Difference

F Sig. t df
Sig.
(2‐
tailed)
Mean
Difference
Std. Error
Equal
variances
assumed
.267 .608 ‐
1.17
5
49 .246 ‐.297 .252 ‐.804 .211 Would
convenience
encourage you
to buy online Equal
variances
not
assumed

‐
1.20
8
48.669 .233 ‐.297 .245 ‐.790 .197
Table 16

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Hypothesis 7
An independent samples t test was undertaken to investigate whether Female students would
be more concerned with Prices, Layout of Store and Quality factors than male students. Again,
there was no significant difference between male and female students of either group being
more concerned with price, layout of store, and quality than the other (p = .764, p >.05).

Levene's Test
for Equality of
95% Confidence
Interval of the
Difference

F Sig. t df
Sig. (2‐
tailed)
Mean
Difference
Std. Error
Equal
variances
assumed
.064 .802 ‐
.302
49 .764 ‐.060 .199 ‐.460 .340 How important
is price
Equal
variances
not assumed

‐
.304
48.918 .763 ‐.060 .198 ‐.459 .338
Equal
variances
assumed
.500 .483 ‐
.946
49 .349 ‐.231 .245 ‐.723 .260 How important
is the layout of
the store
Equal
variances
not assumed

‐
.933
43.703 .356 ‐.231 .248 ‐.731 .268
Equal
variances
assumed
.625 .433 .023 49 .982 .005 .204 ‐.405 .415 How important
is the quality of
produce
Equal
variances
not assumed

.023 46.508 .982 .005 .205 ‐.409 .418
Table 17

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Hypothesis 8
In order to test hypothesis 8 (see Table 18) and determine the influence of consumer
awareness of the price wars and their view of the importance of price in shopping, a series of
one way ANOVAs was undertaken.  There was no significant difference between those who
were aware of price wars and those who were not, or those who were unsure in terms of the
importance they placed on price for shopping in a physical or online store (p > .05). (See Table
19).  However, there was a significant difference between those who were aware of the price
wars and those who were not in terms of whether price would encourage them to buy online
rather than via a physical store (p < .05).  Those who were aware of the price wars value price
as more important in an online store (M= 4.00) than those who were not aware (M=2.89) and
thus were more likely to consider price an encouragement to buy online than those who were
not aware (See Table 18).  These results partially support hypothesis 8.
The importance of price in shopping and consumer awareness of the price wars
Importance of Price in shopping   Mean Std. Deviation
yes 4.14 .663
no 3.89 .601
I don't know 4.25 .752
How important is price

yes 4.00 .392
no 2.89 1.269
I don't know 3.93 .858
Would price encourage you to buy online

Table 18
ANOVA
Between Groups 8.430 3 2.810 3.801 .016
Within Groups 34.746 47 .739
Would price encourage you to buy online
Total 43.176 50
Between Groups .914 3 .305 .601 .618
Within Groups 23.831 47 .507
How important is price
Total 24.745 50
Table 19
Descriptives
95% Confidence
Interval for Mean
N Mean
Std.
Deviation
Std.
Error
Lower
Bound
Upper
Bound Minimum Maximum

22
yes 13 4.00 .408 .113 3.75 4.25 3 5
no 9 2.89 1.269 .423 1.91 3.86 1 4
I don't
know
28 3.93 .858 .162 3.60 4.26 1 5
10 1 4.00 . . . . 4 4
Would price
encourage you to buy
online
Total 51 3.76 .929 .130 3.50 4.03 1 5
yes 13 4.15 .689 .191 3.74 4.57 3 5
no 9 3.89 .601 .200 3.43 4.35 3 5
I don't
know
28 4.25 .752 .142 3.96 4.54 2 5
10 1 4.00 . . . . 4 4
How important is
price
Total 51 4.16 .703 .099 3.96 4.35 2 5
Table 20
Hypothesis 9
An ANOVA was used to investigate whether people who were further away from their local
grocery store would be more likely to buy groceries online than those who do not. Once again,
no significant difference between distance to grocery store and likelihood to buy online was
found that would have supported hypothesis 9. Significance greater than .05 (p = .296, p > .05).

ANOVA
Between Groups 4.658 3 1.553 1.270 .296
Total 60.880 49
Table 21
Hypothesis 10
Another ANOVA was applied in order to assess the plausibility of the hypothesis stating that
students who grocery shop more often will be more likely to buy groceries online than those
who do not. There was no significant difference between those students who shop more often
and the likelihood to buy online compared to those who shop less frequently (p = .813, p > .05)
ANOVA
Between Groups 1.219 3 .406 .318 .813
Total 61.333 50
Table 22

23
Hypothesis 11
There was no significant difference (p = .921,  p > .05) reported regarding the likelihood of
valuing a selection in an online shop by those students who went to the grocery store to get
ideas and those who did not. As a result the hypothesis was not supported that ‘students who
went to the store to get ideas are more likely to value a selection in an online shop’.
Levene's
Test for
Equality of
Variances
t-test for Equality of Means
95% Confidence Interval of
the Difference
F Sig. t df Sig.
(2-
tailed
)
Mean
Differenc
e
Std. Error
Differenc
e Lower Upper
Equal
variances
assumed
.492 .486 -
.10
0
49 .921 -.028 .279 -.589 .533Would
selection
encourage
you to buy
online
Equal
variances
not
assumed
-
.09
8
42.170 .923 -.028 .284 -.601 .545
Table 23
Hypothesis 12
In order to test hypothesis 12 that students from business and health disciplines would be
more likely to purchase online than other disciplines because they may be aware of the price
wars,  a one way ANOVA was undertaken.  The independent variable was discipline area and
the dependent variable was the likelihood of consumers buying online.  While there was no
significant difference between the disciplines in terms of their likelihood of purchasing online
(p > .05), Figure 5 shows that there is a trend for Health students to be more likely to buy
online (M = 3.1). These results show trends only partially in support of hypothesis, however,
trends were not significant.
ANOVA
Between Groups 10.733 6 1.789 1.556 .183
Total 61.333 50
Table 24

25
Discussion
The study investigated the perception of university students towards the idea of buying
produce online, whilst it further attempted to assess and reveal significant necessary factors
that would encourage students to switch from buying produce in a store to buying produce
online. While price and possibly convenience would have been assumed both to be important
the study found that the only significant perceived benefit of the students was price, when
assessing the likelihood to buy produce online. This result is interesting as one would have
possibly assumed that at least convenience would have demonstrated a significant relationship
encouraging students’ buying behaviour to buy groceries online. Also research being done with
respect to students buyer behaviour suggests the notion of convenience being a significant
factor. Even though price was the most important factor influencing students to buy online,
the recent price wars between major Australian grocery chains students did not find it to be
important in either online or bricks and mortar stores thereby, softening the impact of the
factor ‘price’ in this regard.
When asked, however, which factors would be important in terms of choosing where to buy
groceries, quality was perceived to be the most important ahead of price. This is worth noting
as it suggests that despite price being the most encouraging factor of buying groceries online
an absence of quality could have potentially a negative impact on consumer’s loyalty to a
website, while possibly revert to the traditional mode of supermarket shopping whenever they
are dissatisfied either with specific or with general aspects of the online experience, as
previous research found.
Furthermore, other examined factors such as whether students were driving to a grocery store
surprisingly did not really prove to have any significant influence of buying groceries online less
likely than students who did not drive. However, given the fact that more than 80 per cent of
the respondents lived within a range of 2 km of a nearby grocery store, it can be assumed that
due to the short distance driving can be neglected as being critically enough that it would have
an impact on the likelihood of students buying online. Likewise, when people were asked if
distance would encourage them to buy online, there was no significant difference reported
compared to those students that lived not so far away. Again, since over 80 per cent of the
surveyed students were living within 2 km of  a grocery store distance as a factor did not seem
to weigh enough to be considered too important on that particular matter.

26
As indicated by research respondents believed online shopping was the best price and value
for their time. However, 80.6% of the students still responded that they were likely to make
purchases in store, rather than online. This notion was also supported in the study carried out,
as people with a job and therefore with bigger time constraints did not show to significantly be
more likely to buy groceries online than students who did not work. Finally, when investigating
whether there was a difference in likelihood according to the disciplines students were
studying, interestingly business students were least likely to purchase online, contrary to
expectations. There was a trend indicating health students would be more likely to buy
groceries  online.
Implications
The study was carried out to assess how likely university students would be to buy produce
online and to determine what factors would make university students switch from buying
produce in a store to buying produce online. As there is only a small selection of secondary
research currently available the study was also intented to fill the knowledge gap thereby,
shedding further light on this matter.
Secondly the gathered information could have provided market researchers with basic but still
valuable research data based on the buying habits of university students regarding purchasing
fruits and vedgetables. Furthermore, the result could
have assisted potential grocery shop owners as well
as entrepreneurs with their decision making process
when considering setting up an online produce store
targeted at university students.
However, against common belief the overall interest
in buying groceries and particularly, produce online
was rather weak with more than 55 per cent of the
participants responded that they were more than
unlikely to purchase groceries online compared to
roughly 18 per cent stating to be likely buying produce online. This was also
surprising as current secondary research would have  suggested a somewhat different picture.

How likely would you be to buy
groceries online
Frequency
Valid
Percent
very
unlikely
14 27.5
unlikely 16 31.4
neutral 12 23.5
likely 8 15.7
very
likely
1 2.0
Valid
Total 51 100.0
Table 25

27
Limitations and Recommodation
A few characteristics as far as the design and methodology set parameters on the application
and interpretation of the study. With respect to the validity of the undertaken study it needs to
be emphasized that any generalizations of these findings should be approached with caution
as the sample was a very small convenience sample. The most obvious criticism about
convenience sampling is sampling bias and that the sample is not representative of the entire
population. The survey was administered in the form of an anonymous survey only to the
students at Griffith Gold Coast University and excluded other campuses as well as students
from different universities which results to a low external validity of the study.
Moreover, with respect to survey instrument there were several questions addressed using the
Likert scaling system. Scales require a great deal of decision‐making as there are only a few
options offered, with which the respondents may not fully agree and thus may limit the overall
outcome of the study.
For example, the respondents might value other factors than the ones provided, that would
encourage them to buy groceries online. Also, those surveyed may not have been completely
honest or may answer according to what they feel is expected of them as particpants.
Furthermore, questions pertaining to age were not being addressed which would have allowed
for a more thorough demographic segmentation. The questionnaire also neglected to ask
whether participants generally shopped online in order to extrapolate attitude towards the
overall idea of shopping online. More importantly the questionnaire lacked continuity in
content as most of the questions referred to groceries rather than focussing on produce only
and therefore could be misleading.
It is recommended that additional study be conducted of a larger and more representative
university student sample, to shed further light on the produce shopping behavior of students.

28
Citation
Arnaudovska, E., Bankston, K., Simurkova, J., & Budden, M. C. (2010). University
student shopping patterns: Internet vs. brick and mortar. Journal of Applied
Business Research, 26(1), 31‐31‐36. Retrieved from
http://search.proquest.com.libraryproxy.griffith.edu.au/docview/227611000?accounti
d=14543

Bill Anckar, Pirkko Walden, Tawfik Jelassi, (2002) "Creating customer value in online grocery
shopping", International Journal of Retail & Distribution Management, Vol. 30 Iss: 4,
pp.211 ‐ 220

Browne, Kate. 2010, Groceries in a click? Online grocery shopping should be quick and
convenient, but it hasn't taken off in Australia. Choice. March, 2010. 32

Comegys, C., Hannula, M., & Väisänen, J. (2006). Longitudinal comparison of finnish and us
online  shopping behaviour among university students: the five‐stage buying decision
process. Journal of Targeting, Measurement and Analysis for Marketing, 14(4), 336–356.

Corbett, J. (2001). Is online grocery shopping increasing in strength?. Journal of Food
Distribution Research, 32(1), 40

Dall'Olmo Riley, F., Hand, C., Rettie, R., Robinson, H., & Singh, J. (2007). Adoption and
motivational factors for online grocery shopping in the uk. Academy of Marketing (AM)
Annual Conference 2007

Dobson, S., & Ness, M. (2009). Undergraduate students' attitudes towards food shopping
and attitudes to time. International Journal of Consumer Studies, 33(6), 659‐668.
doi:10.1111/j.1470‐6431.2009.00820.x

Ramus, K., & Nielsen, N. A. (2005). Online grocery retailing: What do consumers think?
Internet Research, 15(3), 335‐335‐352. Retrieved from
http://search.proquest.com.libraryproxy.griffith.edu.au/docview/219871792?accounti
d=14543

Schuster, A., & Sporn, B. (1998). Potential for online grocery shopping in the urban area of
vienna. Electronic Markets, 8(2), 15.

"Survey Reveals: Online Advertising Motivates College Students to Purchase."
Experience Inc. N.p., 2011. Web. 24 Aug. 2011.
http://www.experience.com/corp/press_release?id=press_release_1138662942
335&tab= cn1&channel_id=about_us&page_id=media_coverage_news

29
Appendix 1: Ethics Applications

30
Appendix 2: Survey Instrument

32
Examination of the Likelihood of Griffith Gold
Coast University Students
to buy produce Online
Individual Market Research Report
7207MKT Market Research Course
–
Course Convenor: Dr Helen Perkins
Griffith University Gold Coast campus, QLD
By
Robert KriTikos
s2788287
21 October 2011

Market Research Report Master

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