Business Research Methods: Survey Instrument, Sampling Method, and Hypothesis Testing

This article discusses the survey instrument used to evaluate the differences between users and non-users of self-checkout counters in Singapore. It also covers the sampling method used for data collection, the importance of Cronbach's alpha coefficients, and hypothesis testing. Two case studies are included, one on Amazon Fresh and the other on entrepreneurship intention.

Business research methods

TABLE OF CONTENTS
PART ONE......................................................................................................................................2
1. Presenting the aim and research questions..............................................................................2
2. a. How the survey instrument is organised..............................................................................2
b. Presenting the concept measured for second section...............................................................2
c. Importance of Cronbach 𝛼 coefficients...................................................................................3
3. Sampling method for data collection.......................................................................................3
4. a. Evidence shows about demographic variable......................................................................3
b. Explanation of 4 from the report.............................................................................................3
c. Presenting the reason that all test results found to be significant............................................4
5. Conclusion and further research..............................................................................................4
PART TWO.....................................................................................................................................5
Case study 1:................................................................................................................................5
1. Frequency table for Take-up....................................................................................................5
2. Testing the RQ 1 hypothesis....................................................................................................5
3. Testing the RQ 2 hypothesis....................................................................................................5
4. General question......................................................................................................................5
Case study 2:................................................................................................................................6
1. Descriptive statistics for an entrepreneurship intention...........................................................6
2. Testing the hypothesis for average scores for entrepreneurship intention are significantly
different........................................................................................................................................6
3. Testing the university department has an effect on the average score for entrepreneurship
intention.......................................................................................................................................6
4. General question......................................................................................................................6
REFERENCES................................................................................................................................8

PART ONE
1. Presenting the aim and research questions
The aim of the research is to determine how the users and non-users of self-checkout
counters might be different within a retail industry. For that a study has performed for Singapore.
The research questions are as mentioned below:
Q1: Is there any difference between users and non-users of a self- -checkout counters within
Singapore?
Q2: Is there any difference between the users and non-users of self-checkout counters by
considering the characteristic under Singapore which include relative advantage, complexity,
reliability, compatibility and fun?
Q3: What is the differences between users and non-users of self-checkout counters in how
situational factors affect their intention to use the terminals?
2. a. How the survey instrument is organised
The survey instrument is organised into three different sections which includes:
 Demographic information of all the participants that helps to evaluate the information
pertaining to age, gender and educational qualification.
 Next is five point likert scale questions that identify the perception of self-checkout
counters by considering different dimensions.
 Last is based upon seven five point likert scale questions that identify the occurrence of
using self-checkout counters in different situations.
b. Presenting the concept measured for second section
The second section of survey instrument is all about comprises of five point likert scale
questions that helps to determine the perception of self-checkout counters. In this different
factors has also divided on which staffed cashier, ease of use, reliability and entertainment value

has used. This is further divided into different sub groups which involve relative advantage,
perceived complexity, Reliability and Fun. However, these dimensions are further measured in
the three item scaled that also reflected the goo level of consistency between each other.
c. Importance of Cronbach 𝛼 coefficients
The article uses Cronbach 𝛼 coefficients which in turn reflect the reliability coefficient
that also provides a methods of measuring internal consistency of test. This in turn reflected that
the term is used for determining the internal consistent and assess the reliability of a dataset as
well. Also, this represent how consisted the variables are in order to determine the results
effectually. It is essential to used Cronbach 𝛼 coefficients into a study in order to determine the
reliability between the variables and this determine how reliable the questionnaire is (Adeniran,
2019). That is why, if the value is average then there is a need to increase the reliability among
the variables and this in turn assist to generate a better results as well.
3. Sampling method for data collection
For the present study, non-probability sampling method has used in which convenience
sample has taken from the shoppers and residents within a residential suburb. This in turn helps
to make decision and make a comparison between the users and non-users within self-checkout
counters. This in turn shows that sampling helps to determine the perception of people regarding
the chosen research objectives.
4. a. Evidence shows about demographic variable
By applying chi-square test within the research article, it has been identified that there is
no association between the variables because the value of p is greater than the standard criteria
and this in turn shows that null hypothesis is accepted over other. That is why, it can be stated
that there is no difference in the use of self-checkout counters within different demographic
segments.
b. Explanation of 4 from the report
As per the age as a variable, the numeric term 4 indicated that there are four variables
used in the report and the association between other variables. This in turn reflect that there is no
association between the variables.

c. Presenting the reason that all test results found to be significant
All the test has applied and the results shows that there is a statistically significant
because the value of p shows the same. This in turn reflected that there is a moderate effect sizes
and this shows how important the results are. That is why, it can be stated that even having a
moderate effect size within the variables, the results shows that there is a statistically
significance between the variables.
5. Conclusion and further research
Through the research article, it has been analysed that author uses ‘recent’ word many
times and this in turn reflected that there were many studies that had already conducted on the
similar topic within last 2 to 5 years. That is why, the word ‘recent’ entails about the current
articles that reflected the research which is some how same to the present article. Also, the
research suggested that shoppers in the crowded condition perceiving the time pressure which is
less likely to use the self-checkout counters. Thus, in future when the same study has been
conducted then different test need to be applied which in turn help to determine the results in an
accurate manner.

PART TWO
Case study 1:
1. Frequency table for Take-up
In accordance with the binomial test (as attached in table 1 under appendix), it has been
identified that out of 87 respondents, 32 of them are stated no they do not prefer to buy the
products from Amazon. Whereas 55 of them stated that they prefer to buy the product from
Amazon. Overall, it can be stated that majority of the people are agree to buy the products from
Amazon.
2. Testing the RQ 1 hypothesis
With the help of table 2 under appendix, it has been identified that there is an alternative
hypothesis accepted over null because the value of p is lower than 0.05 and this shows that the
proportion of people who consider shopping at Amazon Fresh greater than 50%. Further, it is
also analysed that there is a weak association between the variables because the value of phi-
coefficient and cramer’s V is low and this in turn shows that the chances of fluctuation is
minimum.
3. Testing the RQ 2 hypothesis
Through the table 3, attached in binomial test, it has been identified that the value of p is
lower than 0.05 and this shows that the proportion of people who consider shopping at Amazon
Fresh different between those who are comfortable with mobile technology. Therefore, it can be
analysed that with the value of take up, there is a difference identified between the groups and
this shows the value will be affected positively.
4. General question
In the present research, only hypothesis testing is used instead of comparing the sample
statistics because it provide accurate results which indicate whether null or alternative hypothesis
has accepted (Renau and et.al., 2020). Therefore, sample statistics has not used for the current
situation in order to explain the association between the variables.

Case study 2:
1. Descriptive statistics for an entrepreneurship intention
Through the descriptive statistics (attached in the table 4 under appendix) it has been
identified that 60 respondents stated that there is no entrepreneurial module required for the
entrepreneurship. Whereas 74 of them stated that there is a need of entrepreneurship module.
Hence, it can be stated that average of them stated that the entrepreneurship module is required.
2. Testing the hypothesis for average scores for entrepreneurship intention are significantly
different
As per the independent sample t test (attached in the table 5) it has been identified that
there is a significant difference between the values and this in turn shows that the average scores
for entrepreneurship intention are significantly different. Also, it can be identified that under the
test of normality, where Shapiro Wilk reflected that there is no difference between the variables
and this shows that average score for an entrepreneurship intention is different.
3. Testing the university department has an effect on the average score for entrepreneurship
intention
With the help of table 6, by applying anova test, it can be identified that there is null
hypothesis accepted because the value of p is greater than the standard criteria and this in turn
shows that the entrepreneurial intention is not related with the University department. This in
turn shows that 46 of GSBL department shows the entrepreneurship intention where as 44 CDM
and CASS students followed the same. Therefore, the university department has no effect on the
average score for entrepreneurship intention.
4. General question
The concept of p-value in the hypothesis testing is describe how likely the researcher
have found a specific set of observation when the hypothesis has tested. This in turn assist to
determine whether there is a need to reject or accept the hypothesis in an appropriate manner.
The importance of using the p value to test the hypothesis and analyse the relationship between
the variables (Greenland, 2019). Also, it is used when the inferential tests has applied in a dataset
in order to examine the result in an effective manner. The major limitation of using p value in the

test includes that it is mainly interpreted incorrect manner and this in turn indicated how
incompatible the data are with a specific statistical model which in turn assist to affect the
results. It mainly measures the compatibility of the data and this is in turn assist to affect the
results.

REFERENCES
Books and Journals
Greenland, S., 2019. Valid p-values behave exactly as they should: Some misleading criticisms
of p-values and their resolution with s-values. The American Statistician. 73(sup1).
pp.106-114.
Adeniran, A.O., 2019. Application of Likert scale’s type and Cronbach’s alpha analysis in an
airport perception study. Scholar Journal of Applied Sciences and Research. 2(4). pp.1-5.
Renau, Q. and et.al., 2020, September. Exploratory landscape analysis is strongly sensitive to the
sampling strategy. In International Conference on Parallel Problem Solving from
Nature (pp. 139-153). Springer, Cham.

APPENDIX
Table 1: Frequency statistics
Table 2: hypothesis test for RQ1
Table 3: Hypothesis test for RQ2

Table 4: Descriptive statistics

Table 5: Independent sample t test
Table 6: Anova test