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Part 1
1. Aim and Research questions
The main aim of the research article is to identify a systematic examination of users and non-users of self-checkout counters. The researcher has drawn many assumptions to check out the examination centres for both users. The self-service checkouts have many beneficial elements that are discussed in detail with their limitations. The effectiveness of the examination system in practical use is also defined in brief.
Research questions
Q1: What are the coefficients and elements used for this research article?
Q2: Which factors are measured in this research article?
Q3: How many items are required to form each factor?
2. Survey instrument
a) Survey instrument for this research article is used as a questionnaire form where the primary sources are used to collect the data through a survey in the google form. As opined by Bell et al. (2022), the answers are collected in a qualitative way, and then it was converted into numerical to use software (SPSS) to analyse the dataset. Firstly, the data was collected through a survey where questionnaires are prepared with the objective to collect the ideas and knowledge related to the research article. Then the responses are recorded and later it is analysed.
b) There are two elements that are used to acquire information from the technology and take up. In this, the responses were ascertained with variables 1 and 0 (Beugelsdijk et al. 2020). It was subdivided into four categories, agree, disagree, bly agree and neutral.
c) Cronbach's alpha is used to ensure the internal consistency of a research article. The standard value for this alpha is stated at 0.90, less value from this can be referred to as dimensional to the researched data.
3. Data collection
A “simple random sampling method” is used for this research article. In this method, the researcher randomly selects a sample from the group to represent the whole dataset. As per the view of Chang et al. (2020), it is difficult to describe each element from a long and huge dataset; this is why random sampling methods are used to classify a group. It is a simple sampling trick used by the researchers to examine the easy assumptions from the overall dataset. The responses were random and independent and give evidence from the collect dataset by using the abovementioned instrument.
4. Findings
a) From the results that are incurred from the above-used methods states that there is no evidence that shows the demographic variables have no effective segment with self-checkout counters. As per the author Eden et al. (2020), demographic elements are stated as age, gender, qualification, and other living standards. It is clearly reflected that the outcomes will imply negative results as they are no relation between demographic variables to checkout counters.
b) The variable 4 in this equation refers to an element that has one and more categories in a contingency table. It is calculated by subtracting the expected frequency from the expected frequency.
c) The main reason is that due to any change the significant result may change its interface but the size tells hope the importance it is for the researcher to get an accurate statistical result. 0.5 is the medium-size effect where the t-test reflects the change.
5. Conclusion
Based on this recent study it can be concluded that the research must use other test methods to analyze the whole dataset of the above-mentioned article. The suitable method and research techniques have been chosen to get effective results from the variables. Testing of hypothesis shows theresults that can be effective for examining the self-checkout counters
Part 2
Case study 1: Amazon Fresh
1. Frequency table
From the analysis, the variable “Ease and comfort with mobile technology” shows a cumulative percentage of 52.9 for the people who have agreed with this implementation. The Consideration of shopping at Amazon Fresh the frequency is evaluated at 36.8. The table also shows valid percentages where both the variable shows effective results for amazon fresh.
Figure 1: frequency distribution
(Source: self-created)
2. Appropriate hypothesis test RQ1
From requirement 1, it can be stated that more than 50% of the people do shopping from amazon fresh. From the t-test analysis, it can be stated that people use the technology to buy products from amazon fresh (Hassel and Sieker 2022).
Figure 2: one sample test
(Source: self-created)
3. Appropriate hypothesis test on RQ2
Requirement 2 states that the people who are agreeing in with the proportion of using mobile technology in buying products from amazon fresh can be reflected in the hypothesis test. 0.36 people use mobile technology to buy products whereas 0.36 does not use this technology.
Figure 3: T-test
(Source: self-created)
4. Reasons for an appropriate hypothesis test
Conducting a hypothesis for a test to show the effectiveness of the research article is important because it shows “data from the sample is statistically significant or not” (Lo et al. 2020). Compression with a simple method of statistics cannot represent significant responses but using t-tests can bring clear results for the research users.
Case study 2: Entrepreneurship intention
1. Descriptive statistics
There are a total of 87 students of which 55 have opted to study for an entrepreneurship module and 32 students have not opted for the module. From the chi-square test, it can be concluded that the significance level is less than 0.5, which represents both positive and negative factors. As per the view of Angelica and Sijabat (2022), it shows lees efficient values, but the value is less than 0.5. Through the descriptive statistics, the median value for the student who doesn't opt for the study is valued at 21.0 whereas for the students who have opted for the study the median value is 22.0.
2. Average scores for entrepreneurship intention
Independent t-tests of the entrepreneurship intention are significantly different assumptions where the p-value is obtained at 0.09 which is more than 0.01. As per the author Peprah et al. (2022), this shows the null hypothesis is accepted where both the variables are different to each other. The df value is obtained at 132.00 and the p-value is more than 0.01 shows there is no relationship between the two variables.
3. Effect on the average score for entrepreneurship intention
The university department has an effect on the average score for entrepreneurship intention by enabling a mean value of 2.279 and a p-value of 1.460. This increased value shows the average score is more in GSBL and less in CDM. As per the view of Nielsen et al. (2020), the average score represents the minimum value where the intentions can be changed by adding more hypotheses. From the results, it can be stated that the effect on these dos does not have any linked relationship among variables.
4. Concept of the p-value in hypothesis testing with limitations
P-value helps to decide to accept or reject the value of the null hypothesis. Less value implies ber evidence in accepting the hypothesis, where the higher value represents the rejected norms of the null hypothesis. As mentioned by Lu et al. (2022), the probability of testing results is obtained by assuming that the null hypothesis is correct. The values can be replicable if are obtained low, this shows they are calculated as per the statistical techniques. The value between 0-1 shows accuracy to the p-value to represent the tests of the stated hypothesis.
Limitations of p-value in hypothesis testing
Results can be deviated from
Rejection of null hypothesis
Not appropriate for scientific and business calculations
Testing is unreliable in nature
References
Angelica, B.K. and Sijabat, R., 2022. IMPACT OF CSR, LEADER IMAGE, AND INNOVATION ON AMAZON CONSUMER PURCHASING DECISION. TRANSAKSI, 14(1), pp.28-41.
Bell, E., Harley, B. and Bryman, A., 2022. Business research methods. Oxford university press.
Beugelsdijk, S., Ambos, B. and Nell, P.C., 2020. Conceptualizing and measuring distance in international business research: Recurring questions and best practice guidelines. In Research methods in international business (pp. 449-498). Palgrave Macmillan, Cham.
Chang, S.J., Witteloostuijn, A.V. and Eden, L., 2020. Common method variance in international business research. In Research methods in international business (pp. 385-398). Palgrave Macmillan, Cham.
Eden, L., Nielsen, B.B. and Verbeke, A., 2020. Research methods in international business. Palgrave Macmillan.
Hassel, A. and Sieker, F., 2022. The platform effect: How Amazon changed work in logistics in Germany, the United States and the United Kingdom. European Journal of Industrial Relations, p.09596801221082456.
Lo, F.Y., Rey-Martí, A. and Botella-Carrubi, D., 2020. Research methods in business: Quantitative and qualitative comparative analysis. Journal of Business Research, 115, pp.221-224.
Lu, L., Neale, N., Line, N.D. and Bonn, M., 2022. Improving data quality using Amazon mechanical Turk through platform setup. Cornell Hospitality Quarterly, 63(2), pp.231-246.
Nielsen, B.B., Eden, L. and Verbeke, A., 2020. Research methods in international business: Challenges and advances. Research methods in international business, pp.3-41.
Peprah, A.A., Giachetti, C., Larsen, M.M. and Rajwani, T.S., 2022. How business models evolve in weak institutional environments: the case of Jumia, the Amazon. com of Africa. Organization Science, 33(1), pp.431-463.
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