Response A
1) What is the APA format reference entry for the article?
Dlamini, Mfundo, and Brian Barnard. 2020. “Customer expectation, satisfaction and loyalty: A
study of grocery retail sector in south africa.” IUP Journal of Marketing Management 19 (3): 7–62.
2) What are the research questions? Are they looking for a difference, an association, or apredictive relationship?
Dlamini and Barnard (2020) asked two research questions to assist them with understanding satisfaction and outcome from a customer’s point of view. The research questions asked are:
1. What are the factors that impact customer satisfaction?
2. To what extent does customer satisfaction determine customer loyalty?
The first research question attempts to determine the association between customer satisfaction and customer loyalty. The second research question tries to determine if a predictive relationship exists. It tries to predict how much customer satisfaction impacts customer loyalty.
3) Describe the Research Design. Do you feel that this choice was appropriate and why? What are the strengths and weaknesses of the design?’
Dlamini and Barnard (2020) took a quantitative approach to their study. The design they utilize incorporates regression analysis and focuses on correlation and linear regression. It aims at assessing the dependence between the independent and dependent variables being assessed. Surveys are used to collect data, and the survey method is acknowledged as a weakness of the study. They note that geographic challenges and not conveying information appropriately can skew the results of the study.
4) Who are the participants, and how were they selected? Describe both the target population and the sample. If possible, indicate the response rate achieved by the researchers.
Two hundred and eighty samples were collected, which exceeds the 150 researchers would have liked to receive, at a minimum. Dlamini and Barnard (2020) discuss using the snowball method. Sedgwick (2013) states that this method is prone to selection bias. This method is effective, however, when it is difficult to get participants from a specific population, such as that of consumers. Dlamini and Barnard (2020) were specifically targeting individuals that were over 18 and either employed, retired, or student.
5) What are the variable(s) and their measurement scales?
a. Identify key Independent Variables and the level of measurement (Nominal,
Ordinal, Scale)
There were several independent variables in this study, including expectations, store atmosphere, service, promotion, and convenience. Each are measured on an ordinal scale.
b. Identify key Dependent Variables and the level of measurement (Nominal,
Ordinal, Scale)
There are 2 dependent variables. They are customer satisfaction and customer loyalty. These are also measured on an ordinal scale.
6) Are there measurement Reliability and Validity studies?
a. How would you know the measurements are reliable? What does the study report?
(Remember, reliability is about non-sampling error).
Reliability it not only discussed as something that can impact a customer’s experience. It is also used with Cronbach’s alpha to test whether the items used in the study are acceptable.
b. How do you know the measurements of the variables are valid? What does the study
report?
Dlamini and Barnard (2020) reported that 55 responses were removed because they did not pass reliability and correlation tests. Of the initial 318 responses, 263 were used. This is 83% of the initial participant size.
c. Briefly describe the procedures.
Dlamini and Barnard (2020) discussed the use of Cronbach’s alpha in order to determine reliability and validity. Results came down to whether items scored α >= 7. The items that did not scrore α >= 7 were removed from the study.
7) What statistical tests were used? Identify each test used. State why that statistic was chosen
(e.g., “the t-test was chosen because the researchers were comparing two group means).
Report the result, the p value, and how it was interpreted.
Several tests were used, including Cronbach’s alpha, multiple regression, and correlation analysis. Cronbach’s alpha was chosen to determine reliability. Additionally, multiple regression analysis was used to identify relationships between dependent and independent variables. Multiple regression analysis looked at the relationships between IVs like store atmosphere and service, as well as the relationships between customer satisfaction and customer loyalty.
With correlation analysis, the highest sig. value is .006, which is much lower than .05. This means that there was a statistically significant correlation between the variables loyalty, satisfaction, expectations, atmosphere, phyfet, service, promotion, and convenience. Some of these were as low as .000, indicating a very statistically significant correlation.
An interesting test in the study is the correlation test between promotion and satisfaction between individuals of different sex. The results showed that for females, the Sig. (2-tailed) value was .100, indicating that a statistically significant correlation was not present. However, males had a Sig. (2-tailed) score of .036, indicating that a significant correlation existed between the 2 variables. These results are interesting because they insinuate that different sexes view this differently.
8) Summarize how the results were interpreted.
In this study, researchers looked at retail grocery stores in South Africa and looked at whether there was a relationship between customer satisfaction and customer loyalty. The results show that 4 of the 6 proposed hypotheses were not supported. Hypotheses regarding customer expectations impact customer satisfaction and customer satisfaction impacts customer loyalty were supported.
9) Identify specific limitations of the research.
Dlamini and Barnard (2020) describe four limitations of the research. These limitations include bias in the data gathered, inability to gather additional information due to the instrument used, failure to measure variable quality, and the notion that frequency was not covered with the promotion variable. There will always be limitations in research. It is important that researchers are transparent with presenting this information because it helps other researchers studying the same topic identify research gaps that they may or may not want to close.
10) State the purpose of the scatter plot diagram.
The purpose of the scatter plot diagram in this study was to identify if a linear relationship existed between customer satisfaction and several other variables, including store atmosphere and convenience. None was discovered. When customer relationship and customer satisfaction were assessed, a linear relationship was present. This shows us that customer satisfaction can impact customer loyalty.
References
Dlamini, Mfundo, and Brian Barnard. 2020. “Customer expectation, satisfaction and loyalty: A
study of grocery retail sector in south africa.” IUP Journal of Marketing Management 19 (3): 7–62.
Sedgwick, Philip. 2013. “Snowball Sampling.” BMJ : British Medical Journal (Online)347
(December). https://doi.org/10.1136/bmj.f7511.
Response B
- What is the APA format reference entry for the article?
Zhou, Y., Ahmad, Z., Alsuhabi, H., Yusuf, M., Alkhairy, I., & Sharawy, A. M. (2021). Impact of YouTube advertising on sales with regression analysis and statistical modeling: Usefulness of online media in business. Computational Intelligence and Neuroscience, 2021, 9863155. https://doi.org/10.1155/2021/9863155
- What are the research questions? Are they looking for a difference, an association, or a predictive relationship?
According to Zhou et al. (2021), the study seeks to determine the efficacy of YouTube as an advertising platform and its impact on the sales of a company. The authors are looking for an association between the usage of YouTube as an advertising tool and its impact on a company’s sales. However, Zhou et al. (2021) stated that the regression analysis is used to “predict and forecast” as well as “establish a causal relationship between X and Y” (p.2). Therefore, the authors may also be looking to identify a predictive relationship between the efficacy of YouTube as an advertising tool and the impact on sales of a company.
- Describe the Research Design. Do you feel that this choice was appropriate and why? What are the strengths and weaknesses of the design?
Zhou et al. (2021) uses a quantitative approach and employed a Simple Linear Regression Analysis (SLRA). The topic provided is relatively complex since there are multiple factors involved when it comes to advertising, especially on YouTube. The use of this statistical method may not be as robust to provide a comprehensive understanding of the research topic. Therefore, I believe there is an opportunity for the author to utilize the multiple linear regression analysis instead.
- Who are the participants and how were they selected? Describe both the target population and the sample. If possible, indicate the response rate achieved by the researchers.
None are readily available in this study and requires one to reach out to the authors for those details.
-
What are the variable(s) and their measurement scales?
- Independent Variable: YouTube advertising; scale
- Dependent Variable: sales of a company; scale
- Are there measurement Reliability and Validity studies?
None were explicitly stated in this study.
- What statistical tests were used? Identify each test used. State why that statistic was chosen (e.g., “the t-test was chosen because the researchers were comparing two group means). Report the result, the p value, and how it was interpreted.
The two statistical tests used for this study was the t-test and the f-test. According to Zhou et al. (2021, the value of the t-statistic shows how far the CE is from zero and based on the results, the p value is < .05 and the authors determined the null hypothesis would be rejected. For the f-test, it was used to determine the impact of YouTube advertising on sales (Zhou et al., 2021, p. 3). Therefore, the value of f-statistic is 99.18 which is significantly far from zero, indicating that there is a positive impact of YouTube advertising on sales Zhou et al., 2021).
- Summarize how the results were interpreted.
Overall, the tests from the research determined that there was a positive correlation between YouTube advertising and sales performance and profit. This suggests the efficacy of YouTube as a strategy for increasing sales and profits.
- Identify specific limitations of the research.
While the article was interesting, it lacked available data to learn more about the population and the sample retrieved. Unfortunately, one would have to reach out to the author to obtain that information. No explicit mention of limitations was made by the authors. However, the lack of details concerning the population and sample represents an inherent limitation in itself. Consequently, acknowledging this limitation should have been part of the authors’ responsibility when conducting and reporting this study
