How do your peers’ plans differ from your own, and what can you use from others’ plans that can improve or change your analysis approach?

Response to Aziri



In response to your peers, compare your plan to the others presented:

  • How do your peers’ plans differ from your own,
  • and what can you use from others’ plans that can improve or change your analysis approach?


The research problem would rely on deciding if the company should focus on targeting and attracting first-time buyers and identifying the tactics that the company should use to enhance their level of information on the entry-level hatch vehicles in order to increase the sales in this type of segment. Therefore, the potential analysis tools and methods that I will use to answer the research question would include measures of central tendency such as ordinal scale, mean, and mode (Sekaran, & Bougie, 2016). According to (Sekaran, & Bougie, 2016), these measures would help us to know the reaction of the participants towards the items in the questionnaire. Firstly, the questionnaires would use ordinal scale such as satisfaction ratings on a 5-point scale to determine the satisfaction of first-time buyers on entry-level hatch vehicles (Sekaran, & Bougie, 2016). Additionally, mean would provide me with a general picture of the data, while mode would help me to identify the phenomenon that is taking place frequently (Sekaran, & Bougie, 2016). Since I am planning to use data from Exhibit 6: Profile of Existing A-segment consumers in India which shows that the majority of the customers in the entry-level hatch are first time buyers, the mean would be used to give me a general picture of the data, in comparison to other types of segments (Mukherjee, Mathur, & Dhar, 2015). Also, in the Exhibit 8: Importance of different product attributes which would help me to identify the product attributes such as price, brand, reliability, word of mouth, styling, resale, the overall cost of ownership, fuel efficiency, convenience, dealer persuasion, promotional offers, or interior space, the mode would be used to determine how frequently customers are focusing on these types of attributes (Mukherjee et al., 2015). Moreover, the Exhibit 10: Motivation for A-segment cars purchased from Maruti Suzuki (%) would give me information on the motivation of purchasing entry-level hatch cars as the first vehicle, by using the mean measure of central tendency that would provide me with a general idea of the data (Mukherjee et al., 2015).

A study named “Impacts of Chronic Kidney Disease on the occupational performance of children and adolescents on hemodialysis” was conducted using central tendency measures. This study was done to recognize the influence of Chronic Kidney Disease on the occupational performance of children and adolescents on hemodialysis (Souza, Cardoso, Melo Kummer, Simoes e. Silva, & Ribiero Lage, 2019). Participants of the study involved children and adolescents with CKD that are currently going through hemodialysis treatment and the tools applied included identification questionnaire and semi-structured interviews by describing numerical variables as measures of central tendency and dispersion (Souza et al., 2019). I believe that this was the appropriate method to use because by recognizing these occupations, they could determine the practice of occupational therapy, by being able to use specific interventions and creating policies and guidelines (Souza et al., 2019).



With my research problem regarding marketing techniques based on the categories of cities, especially to attract middle-class Indians, as well as what these individuals value when purchasing a vehicle from Maruti Suzuki [MSIL], the following analysis tools and methods will be used. To begin, I’ll use the an ordinal scale using a rating system where 1 being the lowest and 10 being the highest for Exhibit 8 (Sekaran & Bougie, 2016). Since Exhibit 8 already uses a 1-10 scale, a different approach would be to use a bar chart under all categories like brand, reliability, interior space, etc (Mukherjee, Mathur, & Dhar, 2015, p. 12). This would be illustrated with clustered bars since the values don’t dip below a score of 5. This type of graph would give me an easier way to tally the median and mean of which features in which geographical location need to base its marketing.

Another method I plan to use will be more of a nominal scale (Sekaran & Bougie, 2016). A pie chart will easily help to show data percentages like Exhibit 7 since there are only 3 categories (Mukherjee, Mathur, & Dhar, 2015, p. 12). We can use the pie chart for MSIL specifically then utilize a histogram [interval scale] to include the other car companies to show the contrasting data.

Similar to the 2019 J.D. Power Vehicle Dependability Study conducted (2020), this particular study used a bar graph to rank to different car brands in 2019 based on issues which was a clear illustration as to how I would compare the ranking system in my top paragraph (J.D. Power, 2019). In a system where clear numbers and data are collected, the ordinal scale can be the best to use. With a pie chart, making the image easy for the average reader to understand along with bright colors can allow for up to 650% more engagement from social media consumers (Maryville University, 2019). I believe this study was appropriate because it’s charts and graphs outlined within its report has similar numeral data to mine and outlined that data for a typical middle-class American to look at and comprehend which is what I intend to do with my car research and the Indian middle-class.



INITIAL Discussion Post

The potential analysis tools and methods that I will use to review the research question will consist of descriptive and inferential statistics. This is because the research depends on quantitative data that will be collected from consumers of Maruti Suzuki. Descriptive statistics provide a researcher with an opportunity to summarize the collected data and find patterns (Van Elst, 2019). These patterns can then be used to answer the research question. This method of analysis provides absolute numbers and is beneficial when the research is limited to a sample. Descriptive analysis will be helpful for my research question since it will assist in finding absolute numbers to summarize the individual variables concerning Maruti Suzuki passenger cars sales. For instance, the frequency of the passenger cars in a particular area can be calculated and compared against the frequency of other car manufacturers to establish the difference.

Secondly, inferential statistics will be essential in answering my research question. According to Van Elst (2019), inferential statistics utilizes random data samples collected from a population. The data is then used to describe and make interpretations of the population. In this case, my sample data is will focus on the passenger cars in a particular region. This analytic tool is important in my research since it allows information gathered from a sample in a particular area to be used to make generalizations about other regions. It can be challenging to collect sales data from all the regions where the passenger cars have been sold. For instance, in my research, correlation can be calculated to determine the relationship between sales and consumer preferences.

An example of a business research study that implemented these methods is research conducted by Sulaiman and Baru. The research focuses on the influence of advertising on the purchasing behavior of consumers among various groups in Malaysia (Sulaiman & Baru, 2017). I do believe the methods were appropriate for the research study because the study was able to attain its objectives. More importantly, the methods allowed the researchers to provide the readers with invaluable information on how to structure advertising to meet consumer needs.

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