Research Report on Pricing Strategies and Consumer Purchase Intention

This report presents a business marketing research study focusing on the influence of pricing strategies on consumer purchase intention within the grocery industry in the United Kingdom. The research employs an explanatory research design, utilizing a quantitative approach with data collected through online surveys from 100 respondents in London. The methodology includes stratified sampling and a structured questionnaire with questions on demographics, pricing strategies, and consumer purchase intentions. Data analysis involves SPSS and MS Excel, with Pearson's correlation and regression analysis to examine relationships between variables. The report details the reliability and validity of the data through Cronbach's alpha, KMO, and Bartlett's tests. The findings reveal an average mean response, and the results are linked to the literature review to form valid discussions. The report also adheres to ethical considerations, ensuring respondent privacy and data integrity. The study highlights key statistical results, descriptive statistics, and the correlation and regression analysis to prove the hypothesis mentioned in the literature review section. The report demonstrates a strong internal consistency and scale of the data gathered.

Running head: BUSINESS MARKETING
Business marketing
Name of the student
Name of the university
Author note

1BUSINESS MARKETING
CHAPTER 3: RESEARCH METHODOLOGY
3.1 INTRODUCTION
This chapter provides a detail description of the research methods,
frameworks and instruments used to gather and evaluate data. Choy (2014) states
that research methodology is the method of generating high level of awareness and
understanding about the addressed research problem. It is key to choose methods,
frameworks and philosophical assumptions which are tested for reliability and validity
and designed to be unbiased and objective. Applied research is the main theme for
the majority of the research and can be implied in different fields of research. In this
study, Saunders’ research onion has been used to discuss the different layers in the
research method (Saunders et al. 2015). There are numerous methods of generating
results and these results ranges from high scientific structural methods to informal
ways of fulfilling the objective of the research. The main objective of the research is
evaluating the influence of pricing strategies on the consumer purchase intention in
the grocery industry in United Kingdom. As per the objective, it can be stated that
evaluating the cause and effect relationship between both the variables in the
purpose of the research.
3.2 RESEARCH DESIGN
Research design is the overall process of choosing techniques and methods
that can be used to combine various components logically. On the contrary, the
choice between qualitative and quantitative methods is also defined as research
design. It also provides insights on the way a methodology can be used to perform
the study effectively (Creswell and Poth 2017). This means that it provides the
outline of the way, research needs to be conducted in the study. Research design
explains the type and nature of study to be performed. This can be experimental,
quasi experimental, correlational, review and others. The four key characteristics of
research design are reliability, neutrality, validity and generalisation (Ioannidis et al.
2014). This means that the results developed from the research needs to unbiased
and the reproducibility of the design is high. Validity measures the appropriateness
of the research instruments. Moreover, the results developed should be applicable to
the whole population sample and not the chosen sub set.

2BUSINESS MARKETING
Research designs are mainly divided into three concepts; descriptive
research design, explanatory research design and exploratory research design. The
current research has chosen the explanatory research design as it has facilitated in
measuring the cause and effect relationship between two variables (Meyers, Gamst
and Guarino 2016). The explanatory research design is also known as causal
research design. It has also been used to depict the pattern in association between
two variables. This uses a high structured design which facilitates in performing
quantification of the observed data. This means that the changes in the pricing
strategies and its possible impacts can be identified using this design. A single
research design has been developed in the research and quantitative data has been
collected using the mentioned design.
3.3 SAMPLING TECHNIQUE
Sampling is the process of the choosing elements from the total population
which forms the sample sub set in the research. As stated by Jishan et al. (2015), it
is not feasible for a study to use the whole population as the sample population so
elements have to be chosen for representing the total target population. The process
of sampling is used for reducing the cost and timeframe of the research. This is
highly relevant in quantitative studies due to the involvement of the large sample
data. The process of sampling follows series of events and steps to select the
sample population and target population (Taherdoost 2016). The first step is
choosing the target population and the target population for the current research are
the retail consumers in the United Kingdom. However, all the consumers cannot be
used in this research and consumers having possible effective contribution to the
research needs to be chosen. Sampling frame is the technique which comes into
play due to this requirement where the sample elements having significant
contribution to the research are chosen. The sampling frame in this research
consists of the retail consumers in London.
The next step is choosing the sampling size and in this current study, the data
has been collected from 100 respondents by conducting an online survey. The online
survey resulted in no missing data and helped in measuring the relationship between
pricing strategies and consumer purchase intention. The next step is choosing the
sampling technique and there are mainly two types of sampling method, one is
probabilistic sampling method and second is non-probabilistic sampling method.

3BUSINESS MARKETING
However, in quantitative studies the probabilistic sampling method is preferred where
randomisation of sample elements in the key characteristics of the method. In this
research, stratified sampling has been used to choose respondents from different
strata. This helps in gathering a more diversified response group in the research.
3.4 RESEARCH INSTRUMENT
In this research, the study has chosen online survey questionnaire has been
chosen as the instrument (Cook and Reed 2015). The research questionnaire has
been divided into three sections and consists of 10 questions. The first section
consists of demographic questions, the second section consists of questions on
pricing strategy and the third section consists of the questions on consumer
purchase intention. The first section consists of 4 questions, the second section
includes 2 questions and the last sections also consists of 4 questions.
3.5 PROCEDURE FOR DATA COLLECTION
The process of data uses primary data collection method to gather data from
survey questionnaire. The questionnaire has been sent to respondents through
emails. The survey questionnaire consists of close ended questions where the
questionnaire used nominal scale, ordinal scale and ratio scale to collect relevant
data (Palinkas et al. 2015). The questionnaire uses a structured format to collect
data from different respondents. The questionnaire has been developed based on
the conceptual framework developed in the literature review section to examine the
relationship discussed.
3.6 METHOD OF DATA ANALYSIS
This research uses a quantitative approach where the data collected has
been analysed using statistical tools like SPSS and MS Excel. SPSS has been used
to perform Pearson’s correlation between the variables. Pearson’s correlation
measures the degree of correlations between the chosen elements. The research
has regression analysis to develop a model and perform trend analysis (Palinkas et
al. 2015). The regression line follows the equation, y=mx + c + E, where m is the
slope, c is the constant, x is the dependent variable, y is the independent variable
and E is the error. Regression analysis has been able to establish the relationship
between the different factors by using a multiple regression tool.

4BUSINESS MARKETING
3.7 RELIABILITY AND VALIDITY
It has already been discussed that reliability and validity are important
components of research design. Reliability of the questionnaire has been measured
using test rated reliability where the questionnaire has been used to collect data from
different sets of respondents to check whether the results are similar or not. The
reliability of the collected data has been measured using cronbach’s alpha test which
measures the scale reliability and internal consistency of the collected data (Heale
and Twycross 2015). The value of alpha is expected to be greater than 0.6 for high
level of internal consistency. The validity of the questionnaire has been measured
using pilot testing where the questionnaire was sent to 10 respondents to gather
their opinion on the consumers. The validity of the data collected has been
measured using Bartlett test of sphericity and Kaiser Meyer Olkin test for sampling
adequacy. The KMO test is used to measure the adequacy of the sampling method
and the Bartlett test measures the proportion of variance among the data collected.
3.8 ETHICAL CONSIDERATION
The research has adhered to all the ethical guidelines of performing a
research. The respondents have been provided information regarding the purpose of
performing the research. The research has maintained the privacy and anonymity of
the respondents by withholding their personal data (Connelly 2014). The study has
also made sure that none of the data collected from the respondents has been
fabricated, falsified or plagiarised. The study has followed the data protection act of
1998 and data collected has been stored securely. The collected data has not been
used for any other purpose in the research. The study has also ensured that the
questionnaire does not consist of any discriminatory or offensive language that may
hurt the sentiment of any respondent.

5BUSINESS MARKETING
CHAPTER 4: FINDINGS AND ANALYSIS
4.1 INTRODUCTION
The current section has evaluated the data gathered using statistical tools and
techniques necessary to obtain relevant results. The reliability statistics and validity
test has been performed to analyse the quality of the data collected. Descriptive
statistics has been analysed to understand the mean response of the population in
each of the cases. The frequency charts has been examined to evaluate the
responses from each participant. The correlation and regression analysis measured
the relationship among the different elements to prove the hypothesis mentioned in
the literature review section. The chapter has also linked the results with the
literature review to form valid discussion in the research.
4.2 RELIABILITY AND VALIDITY
Cronbach’s alpha test has been used to measure the internal consistency of
the information gathered as it has the ability to quantify the responses into a range.
The Cronbach’s alpha value has a threshold of 0.7 and the value above 0.7 is
considered acceptable in applied research. The value of alpha is .807 which means
that the internal consistency and scale of the data gathered is significantly high. The
mean value of the responses collected shows a high value which means that similar
responses are obtained in majority of the cases. The item total statistics is used to
evaluate the internal consistency when one of the item is deleted. In this study, it can
be seen that the value of alpha decreases when one of the item is deleted. This
means that all the elements have high level of consistency.
The validity of the data gathered has been measured using Kaiser-Meyer-
Olkin Measure of Sampling Adequacy and Bartlett's Test of Sphericity. The value of
KMO is .798 which means that the sampling of the given data is highly adequate. On
the other hand, the value of Bartlett test is .000 which is less than the p value of .05.
This data implies that the data collected is significant and proportion of variance is
minimal in the research.
The reliability and validity analysis of the data gathered has shown positive
results. It is expected to derive results that are in accordance to the scope of
investigation. It also implies that results created are relevant and high accuracy and
precision.

6BUSINESS MARKETING
Reliability Statistics
Cronbach's Alpha N of Items
.807 6
Table 1: Reliability statistics
Source: (As created by author)
Item Statistics
Mea
n
Std.
Deviati
on
N
@5.Howfardoyouagreethatyoupreferlowpricesthroughoutt
h
3.30 1.648 100
@6.Howfardoyouagreethatyoupreferfrequentdiscountsthro
u
3.18 1.579 100
@7.Howfardoyouagreethatyourproductchoiceisinfluenced
b
3.86 1.436 100
@8.Howfardoyouagreethatyourstorechoiceisinfluencedby 3.76 1.272 100
@9.Howfardoyouagreethatyourpurchaseamountisinfluenc
ed
3.64 1.375 100
@10.Howfardoyouagreethatyourpurchasetimingisinfluenc
ed
3.75 1.410 100
Table 2: Item statistics
Source: (As created by author)
Item-Total Statistics
Scale
Mean
if
Item
Scale
Varian
ce if
Item
Correct
ed Item-
Total
Correlat
Cronbac
h's
Alpha if
Item

7BUSINESS MARKETING
Delet
ed
Delete
d
ion Deleted
@5.Howfardoyouagreethatyoupreferlowprice
sthroughoutth
18.19 31.08
5
.282 .846
@6.Howfardoyouagreethatyoupreferfrequent
discountsthrou
18.31 33.20
6
.180 .863
@7.Howfardoyouagreethatyourproductchoic
eisinfluencedb
17.63 25.14
5
.818 .718
@8.Howfardoyouagreethatyourstorechoiceisi
nfluencedby
17.73 26.42
1
.836 .723
@9.Howfardoyouagreethatyourpurchaseamo
untisinfluenced
17.85 26.21
0
.773 .731
@10.Howfardoyouagreethatyourpurchasetim
ingisinfluenced
17.74 26.61
9
.713 .744
Table 3: Item-total Statistics
Source: (As created by author)
Scale Statistics
Mean Variance Std. Deviation N of Items
21.49 38.980 6.243 6
Table 4: Scale Statistics
Source: (As created by author)
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .798
Bartlett's Test of Sphericity Approx. Chi-Square 353.743
df 15
Sig. .000
Table 5: KMO and Bartlett's Test

8BUSINESS MARKETING
Source: (As created by author)
4.3 DESCRIPTIVE STATISTICS
The descriptive statistics examines the mean, standard deviation and kurtosis.
The average mean value of all the questions is 3.581 which means that majority of
the respondents have agreed to the research questions. The average standard
deviation of the data collected is 1.453 which means that the responses range from 5
to 2. It implies that there are few respondents that have disagreed to the research
questions. The kurtosis value measures the heaviness of the tail in the study and the
negative value determines that the distribution is platykurtic and the tails are lightly
distributed.
Descriptive Statistics
N Minim
um
Maxim
um
Mean Std.
Deviation
Kurtos
is
Statist
ic
Statisti
c
Statisti
c
Statist
ic
Statistic Statist
ic
@5.Howfardoyouag
reethatyoupreferlow
pricesthroughoutth
100 1 5 3.30 1.648 -1.550
@6.Howfardoyouag
reethatyoupreferfre
quentdiscountsthro
u
100 1 5 3.18 1.579 -1.613
@7.Howfardoyouag
reethatyourproductc
hoiceisinfluencedb
100 1 5 3.86 1.436 -.433
@8.Howfardoyouag
reethatyourstorecho
iceisinfluencedby
100 1 5 3.76 1.272 -.041
@9.Howfardoyouag
reethatyourpurchas
eamountisinfluence
d
100 1 5 3.64 1.375 -.743
@10.Howfardoyoua
greethatyourpurcha
setimingisinfluence
d
100 1 5 3.75 1.410 -.661
Valid N (listwise) 100 3.581 1.453
Table 6: Descriptive Statistics

9BUSINESS MARKETING
Source: (As created by author)
Descriptive Statistics
Kurtosis
Std. Error
@5.Howfardoyouagreethatyoupreferlowpricesthroughoutth .478
@6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou .478
@7.Howfardoyouagreethatyourproductchoiceisinfluencedb .478
@8.Howfardoyouagreethatyourstorechoiceisinfluencedby .478
@9.Howfardoyouagreethatyourpurchaseamountisinfluenced .478
@10.Howfardoyouagreethatyourpurchasetimingisinfluenced .478
Valid N (listwise)
Table 7: Descriptive Statistics
Source: (As created by author)
4.4 FREQUENCY RESPONSES
Image 1: Age

10BUSINESS MARKETING
Source: (As created by author)
The purpose of the question is examination of the age of the participants for
the current investigation. The results show that 42% of the participants belong to the
age group of 25-30 years, 26%% of the respondents belong to the age group of 35-
40 years, 18% belong to the age group of 18-24 years and the remaining
respondents belong to the age group of 40 and above. The frequency distribution
shows diversity among the respondents.
Image 2: Gender
Source: (As created by author)
The question aims to highlight the gender of the participants and the results
show that 51% are female, 40% are male and remaining preferred not to say. The
diversity in the gender can be used as a moderating variable in understanding the
difference in opinion between both the genders. The preferences and spending
characteristics may vary depending upon the gender.

11BUSINESS MARKETING
Image 3: Monthly Income
Source: (As created by author)
The present questions examines the monthly income of the respondents. The
results show that 38% of the respondents have an annual income between 25,001 to
35,000 GBP, 28% have an annual income between 15,001 to 25000 GBP, 17% have
an annual income of less than 15,000 GBP and 17% have an annual income of
greater than 35,000 GBP. This shows that the disposable income of the consumers
are relatively on the higher side in United Kingdom. However, it would be interesting
to analyse the buying behaviour based on the income level of each participant
segment.

12BUSINESS MARKETING
Image 4: Age
Source: (As created by author)
The question shed light on the most preferable retail supermarket among the
sample population. The results are quite shocking as 44% of the respondents have
preferred ALDI over other industry giants. Tesco has been preferred by 32% of the
respondents and has given competition to ALDI but the remaining two organisations
have shown shocking results and have received only 12% of votes. This clearly
implies that the buying behaviour of the consumers have changed and they are
preferring to purchase products from ADLI over the big three.

13BUSINESS MARKETING
Image 5: Everyday Low Pricing
Source: (As created by author)
The question examines the preferences of the consumers in respect to
everyday low pricing. The results showed that 36% have strongly agreed to the
question, 20% have agreed to the question. On the contrary, 26% have strongly
disagreed to the question and 10% have disagreed to the question. This shows that
56% of the respondents prefer Everyday low pricing in comparison to the high low
pricing strategy.

14BUSINESS MARKETING
Image 6: High Low pricing strategy
Source: (As created by author)
The question examines the preferences of the consumers in respect to high
low pricing strategy. The results showed that 34% have strongly agreed to the
question, 13% have agreed to the question. On the contrary, 19% have strongly
disagreed to the question and 25% have disagreed to the question. This shows that
47% of the respondents prefer high low pricing in comparison to the everyday low
pricing strategy.

15BUSINESS MARKETING
Image 7: Age
Source: (As created by author)
The question investigates whether the products choices of customers are
affected by the price offered. It can be seen that 49% of the respondents have
strongly agreed to the question and 22% have agreed to the question. On the
contrary, 13% have strongly disagreed to the question and 8% have disagreed to the
question. The result is as expected and have parity with the literature and shows that
71% customers choose products based on the price offered.
Image 8: Store choice
Source: (As created by author)
The given question examines the impact of price of the products on the store
choices. The results show that 32% of the respondents have strongly agreed to the
question and 41% have agreed to the question. On the contrary, 10% have strongly
disagreed to the question and 9% have disagreed to the question. This shows that
73% of the respondents chooses their supermarket retail brand based on the price
offered. However, among these there are cherry pickers that purchase products

16BUSINESS MARKETING
when there are price incentives but this study has not been able to differentiate
them.
Image 9: purchase amount
Source: (As created by author)
The given question examines the impact of price of the products on purchase
amount. The results show that 36% of the respondents have strongly agreed to the
question and 26% have agreed to the question. On the contrary, 12% have strongly
disagreed to the question and 10% have disagreed to the question. This shows that
in 62% of the consumers’ purchase amount is affected by the price of the product.

17BUSINESS MARKETING
Image 10: Purchase timing
Source: (As created by author)
The given question examines the impact of price of the products on purchase
timing. The results show that 42% of the respondents have strongly agreed to the
question and 26% have agreed to the question. On the contrary, 12% have strongly
disagreed to the question and 11% have disagreed to the question. This shows that
68% of the respondents choose their purchase timing based on the price offered.
4.5 CORRELATION ANALYSIS
The relationship between all the elements have been found to be relevant and
significant at .01 confidence interval. The correlation analysis shows that there is a
strong correlation between product choices and store choices. The value is 0.8
which means that the degree of association is strong and directly proportion.
Moreover, the relationship is bidirectional in nature where choice of store determines
the product to be purchased. Similarly, the product choice dictates the stores to be
visited. The relationship between consumers preferring everyday low pricing and the
high low pricing strategy shows that negative relationship with a value of -.269. This
means that there is a strong negative relationship between the preferences of ELDP
and Hi-Lo strategy. This is because of the fact that consumers preferring ELDP
would not choose Hi-Lo strategy and vice versa. This means that the consumers of
ALDI will not make purchases in Tesco or Sainsbury’s. Similarly, the consumers of

18BUSINESS MARKETING
Tesco will not make purchase from ALDI unless other moderating factors affect their
behaviour. The relationship between purchase amount and product choice have
strong positive correlation between them and the relationship bidirectional. This
means that consumers choose their products based on their overall purchase
amount. This defines the disposable income of the consumers.
Correlations
@5.Howfa
rdoyouagr
eethatyou
preferlowp
ricesthrou
ghoutth
@7.Howfa
rdoyouagr
eethatyour
productch
oiceisinflu
encedb
@8.Howfa
rdoyouagr
eethatyour
storechoic
eisinfluenc
edby
@5.Howfardoyouag
reethatyoupreferlow
pricesthroughoutth
Pearson
Correlation
1 .419** .357**
Sig. (2-tailed) .000 .000
N 100 100 100
@7.Howfardoyouag
reethatyourproductc
hoiceisinfluencedb
Pearson
Correlation
.419** 1 .800**
Sig. (2-tailed) .000 .000
N 100 100 100
@8.Howfardoyouag
reethatyourstorecho
iceisinfluencedby
Pearson
Correlation
.357** .800** 1
Sig. (2-tailed) .000 .000
N 100 100 100
@9.Howfardoyouag
reethatyourpurchas
eamountisinfluence
d
Pearson
Correlation
.351** .850** .753**
Sig. (2-tailed) .000 .000 .000
N 100 100 100
@10.Howfardoyoua
greethatyourpurcha
setimingisinfluence
d
Pearson
Correlation
.324** .646** .715**
Sig. (2-tailed) .001 .000 .000
N 100 100 100
@6.Howfardoyouag
reethatyoupreferfre
quentdiscountsthro
u
Pearson
Correlation
-.269** .198* .328**
Sig. (2-tailed) .007 .048 .001
N 100 100 100
Table 8: Correlation
Source: (As created by author)

19BUSINESS MARKETING
Correlations
@9.Howfar
doyouagre
ethatyourp
urchaseam
ountisinflue
nced
@10.Howf
ardoyouagr
eethatyour
purchaseti
mingisinflu
enced
@6.Howfar
doyouagre
ethatyoupr
eferfreque
ntdiscounts
throu
@5.Howfardoyouagr
eethatyoupreferlowp
ricesthroughoutth
Pearson
Correlation
.351** .324** -.269**
Sig. (2-tailed) .000 .001 .007
N 100 100 100
@7.Howfardoyouagr
eethatyourproductch
oiceisinfluencedb
Pearson
Correlation
.850** .646** .198*
Sig. (2-tailed) .000 .000 .048
N 100 100 100
@8.Howfardoyouagr
eethatyourstorechoic
eisinfluencedby
Pearson
Correlation
.753** .715** .328**
Sig. (2-tailed) .000 .000 .001
N 100 100 100
@9.Howfardoyouagr
eethatyourpurchase
amountisinfluenced
Pearson
Correlation
1 .584** .240*
Sig. (2-tailed) .000 .016
N 100 100 100
@10.Howfardoyoua
greethatyourpurchas
etimingisinfluenced
Pearson
Correlation
.584** 1 .320**
Sig. (2-tailed) .000 .001
N 100 100 100
@6.Howfardoyouagr
eethatyoupreferfrequ
entdiscountsthrou
Pearson
Correlation
.240* .320** 1
Sig. (2-tailed) .016 .001
N 100 100 100
Table 9: Correlation
Source: (As created by author)
4.6 REGRESSION ANALYSIS
4.6.1 EVERY DAY LOW PRICING STRATEGY IMPACT ON PRODUCT CHOICE
The value of Multiple R is .419 which shows moderate correlation between
product choice and ELDP. The value of R square is .176 which implies that the

20BUSINESS MARKETING
goodness of fit of the model is low but is acceptable in practical studies. This also
signifies that 17.6% of the characteristics of product choice can be described by
ELDP. Durbin Watson test shows that there is no first order autocorrelation between
the variables. The F value in the study is .000 which is less than the p value so the
null hypothesis can be rejected and there is significant relationship between the two.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .419a .176 .167 1.310 1.827
a. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
b. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 35.848 1 35.848 20.888 .000b
Residual 168.192 98 1.716
Total 204.040 99
a. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
b. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.655 .294 9.021 .000
@5.Howfardoyouagreetha
tyoupreferlowpricesthroug
houtth
.365 .080 .419 4.570 .000
a. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
4.6.2 EVERY DAY LOW PRICING STRATEGY IMPACT ON STORE CHOICE
The value of Multiple R is .357 which shows moderate correlation between
store choice and ELDP. The value of R square is .128 which implies that the
goodness of fit of the model is low but is acceptable in practical studies. This also
signifies that 12.8% of the characteristics of store choice can be described by ELDP.
Durbin Watson test shows that there is no first order autocorrelation between the

21BUSINESS MARKETING
variables. The F value in the study is .000 which is less than the p value so the null
hypothesis can be rejected and there is significant relationship between the two.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
Durbin-Watson
1 .357a .128 .119 1.194 1.814
a. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
b. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 20.467 1 20.467 14.350 .000b
Residual 139.773 98 1.426
Total 160.240 99
a. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby
b. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.850 .268 10.620 .000
@5.Howfardoyouagreetha
tyoupreferlowpricesthroug
houtth
.276 .073 .357 3.788 .000
a. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby
4.6.3 EVERY DAY LOW PRICING STRATEGY IMPACT ON PURCHASE AMOUNT
The value of Multiple R is .351 which shows moderate correlation between
purchase amount and ELDP. The value of R square is .123 which implies that the
goodness of fit of the model is low but is acceptable in practical studies. This also
signifies that 12.3% of the characteristics of purchase amount can be described by
ELDP. Durbin Watson test shows that there is no first order autocorrelation between

22BUSINESS MARKETING
the variables. The F value in the study is .000 which is less than the p value so the
null hypothesis can be rejected and there is significant relationship between the two.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .351a .123 .114 1.293 1.372
a. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
b. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 23.083 1 23.083 13.797 .000b
Residual 163.957 98 1.673
Total 187.040 99
a. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
b. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.673 .291 9.199 .000
@5.Howfardoyouagreetha
tyoupreferlowpricesthroug
houtth
.293 .079 .351 3.714 .000
a. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
4.6.4 EVERY DAY LOW PRICING STRATEGY IMPACT ON PURCHASE TIMING
The value of Multiple R is .324 which shows moderate correlation between
purchase timing and ELDP. The value of R square is .105 which implies that the
goodness of fit of the model is low but is acceptable in practical studies. This also
signifies that 10.5% of the characteristics of purchase timing can be described by
ELDP. Durbin Watson test shows that there is no first order autocorrelation between

23BUSINESS MARKETING
the variables. The F value in the study is .000 which is less than the p value so the
null hypothesis can be rejected and there is significant relationship between the two
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .324a .105 .096 1.341 1.545
a. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
b. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 20.633 1 20.633 11.481 .001b
Residual 176.117 98 1.797
Total 196.750 99
a. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced
b. Predictors: (Constant), @5.Howfardoyouagreethatyoupreferlowpricesthroughoutth
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.836 .301 9.416 .000
@5.Howfardoyouagreetha
tyoupreferlowpricesthroug
houtth
.277 .082 .324 3.388 .001
a. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced
4.6.5 HIGH LOW PRICING STRATEGY IMPACT ON PRODUCT CHOICE
This model is significant as the F value is .048 and hi-lo strategy explains
3.9% of the characteristics of product choice.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .198a .039 .030 1.414 1.784

24BUSINESS MARKETING
a. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
b. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 8.032 1 8.032 4.016 .048b
Residual 196.008 98 2.000
Total 204.040 99
a. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
b. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 3.286 .319 10.291 .000
@6.Howfardoyouagreetha
tyoupreferfrequentdiscoun
tsthrou
.180 .090 .198 2.004 .048
a. Dependent Variable: @7.Howfardoyouagreethatyourproductchoiceisinfluencedb
4.6.6 HIGH LOW PRICING STRATEGY IMPACT ON STORE CHOICE
This model is significant as the F value is .001 and hi-lo strategy explains
10.8% of the characteristics of store choice.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .328a .108 .099 1.208 1.806
a. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
b. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby

25BUSINESS MARKETING
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 17.291 1 17.291 11.854 .001b
Residual 142.949 98 1.459
Total 160.240 99
a. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby
b. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.918 .273 10.701 .000
@6.Howfardoyouagreetha
tyoupreferfrequentdiscoun
tsthrou
.265 .077 .328 3.443 .001
a. Dependent Variable: @8.Howfardoyouagreethatyourstorechoiceisinfluencedby
4.6.7 HIGH LOW PRICING STRATEGY IMPACT ON PURCHASE AMOUNT
This model is significant as the F value is .016 and hi-lo strategy explains
5.7% of the characteristics of purchase amount.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .240a .057 .048 1.341 1.353
a. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
b. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 10.740 1 10.740 5.970 .016b
Residual 176.300 98 1.799
Total 187.040 99

26BUSINESS MARKETING
a. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
b. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.977 .303 9.829 .000
@6.Howfardoyouagreetha
tyoupreferfrequentdiscoun
tsthrou
.209 .085 .240 2.443 .016
a. Dependent Variable: @9.Howfardoyouagreethatyourpurchaseamountisinfluenced
4.6.8 HIGH LOW PRICING STRATEGY IMPACT ON PURCHASE TIMING
This model is significant as the F value is .001 and hi-lo strategy explains
10.2% of the characteristics of purchase timing.
Model Summaryb
Mode
l
R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-
Watson
1 .320a .102 .093 1.342 1.710
a. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
b. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1 Regression 20.142 1 20.142 11.177 .001b
Residual 176.608 98 1.802
Total 196.750 99
a. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced
b. Predictors: (Constant), @6.Howfardoyouagreethatyoupreferfrequentdiscountsthrou
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.841 .303 9.374 .000
@6.Howfardoyouagreetha
tyoupreferfrequentdiscoun
.286 .085 .320 3.343 .001

27BUSINESS MARKETING
tsthrou
a. Dependent Variable: @10.Howfardoyouagreethatyourpurchasetimingisinfluenced

28BUSINESS MARKETING
CHAPTER 5: CONCLUSION
5.1 CONCLUSION
The final chapter of thesis paper aims to summarise the overall research
process and findings. This chapter has critically linked the findings to the objectives
to gain suitable insights. It has already been stated that the grocery retail market in
United Kingdom is highly saturated in nature and organisations spend significant
amount of their resources to develop the ideal price strategy for their products to
gain competitive advantage over the other organisations in the same operating
market. Even though various strategies and theories have been discussed,
consumer purchase intention and pricing is a multi-faced phenomenon. This means
that there was a lack of standardisation in measuring and conceptualisation the
strategies and theories. Moreover, Aldi has been able to gain competitive advantage
in the market due to their unique strategy and the study aims to take this case into
account to analyse the pricing strategies and the way it has impacted to the
purchase intention of the consumers. The research has used 100 consumers in the
retail industry in the United Kingdom and quantitative survey has been used to
create significant results. The investigation has presented following findings:
The results are quite shocking as 44% of the respondents have preferred
ALDI over other industry giants. Tesco has been preferred by 32% of the
respondents and has given competition to ALDI but the remaining two
organisations have shown shocking results and have received only 12% of
votes. This clearly shows that ALDI has been able to increase their share in
the market.
The correlation analysis shows that there is a strong correlation between
product choices and store choices. The value is 0.8 which means that the
degree of association is strong and directly proportion. Moreover, the
relationship is bidirectional in nature where choice of store determines the
product to be purchased.
Similarly, the product choice dictates the stores to be visited. The relationship
between consumers preferring everyday low pricing and the high low pricing
strategy shows that negative relationship with a value of -.269. This means
that there is a strong negative relationship between the preferences of ELDP

29BUSINESS MARKETING
and Hi-Lo strategy. This is because of the fact that consumers preferring
ELDP would not choose Hi-Lo strategy and vice versa. This means that the
consumers of ALDI will not make purchases in Tesco or Sainsbury’s.
Similarly, the consumers of Tesco will not make purchase from ALDI unless
other moderating factors affect their behaviour.
The regression analysis shows that both the pricing strategies impacts the
product choices, store choices, purchase timing and purchase amount.
However, the impact is greater in case of the ELDP which can be understood
from the models developing using regression analysis.
5.2 RECOMMENDATION
The research has proposed the following recommendations based on the
objective in the research:
ELDP pricing is more appropriate for the consumers in United Kingdom due to
the change in buying behaviours of the consumers. The consumers have
become more sensitive to price changes so ELDP is more appropriate when
compared to Hi-Lo pricing strategy.
ALDI has become the primary choice of the majority of the consumers in UK
so other companies will have to develop backward integration and develop
their private labelled brand to provide low prices constantly. This provides
sustainable competitive advantage throughout the year.
ELDP should be used by heavy discounters and customer value based pricing
is the key to implementing pricing strategy suitable to current needs of the
consumers.
ALDI can use competitor based pricing to improve their market share due to
the current economic recession in the United Kingdom market.
5.3 FUTURE SCOPE OF THE STUDY AND RESEARCH LIMITATION
The major limitation of the study is that sample size is relatively smaller and
the sampling error is 10%. Moreover, the study uses a single research design and a
mixed method design would have provided a better result. On the other hand, the
study has mainly focused on ELDP and Hi-Lo pricing strategies and further study
can be performed to analyse the competitor oriented pricing, cost based pricing and

30BUSINESS MARKETING
customer value based pricing. The research has also used ALDI as the main case so
there may be differences between discounters and other major organisations.
REFERENCES
Choy, L.T., 2014. The strengths and weaknesses of research methodology:
Comparison and complimentary between qualitative and quantitative
approaches. IOSR Journal of Humanities and Social Science, 19(4), pp.99-104.
Connelly, L.M., 2014. Ethical considerations in research studies. Medsurg
Nursing, 23(1), pp.54-56.
Cook, D.A. and Reed, D.A., 2015. Appraising the quality of medical education
research methods: the medical education research study quality instrument and the
Newcastle–Ottawa scale-education. Academic Medicine, 90(8), pp.1067-1076.
Creswell, J.W. and Poth, C.N., 2017. Qualitative inquiry and research design:
Choosing among five approaches. Sage publications.
Heale, R. and Twycross, A., 2015. Validity and reliability in quantitative
studies. Evidence-based nursing, 18(3), pp.66-67.
Ioannidis, J.P., Greenland, S., Hlatky, M.A., Khoury, M.J., Macleod, M.R., Moher, D.,
Schulz, K.F. and Tibshirani, R., 2014. Increasing value and reducing waste in
research design, conduct, and analysis. The Lancet, 383(9912), pp.166-175.
Jishan, S.T., Rashu, R.I., Haque, N. and Rahman, R.M., 2015. Improving accuracy
of students’ final grade prediction model using optimal equal width binning and
synthetic minority over-sampling technique. Decision Analytics, 2(1), p.1.
Meyers, L.S., Gamst, G. and Guarino, A.J., 2016. Applied multivariate research:
Design and interpretation. Sage publications.
Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood,
K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed
method implementation research. Administration and policy in mental health and
mental health services research, 42(5), pp.533-544.
Saunders, M.N., Lewis, P., Thornhill, A. and Bristow, A., 2015. Understanding
research philosophy and approaches to theory development.