Market Research Case Study: Pulse Motors' PEV0 for City Commuters

This case study examines the market research conducted for Pulse Motors' Personal Electric Vehicle Zero (PEV0), an electric motorbike targeting city commuters aged 18-35 traveling 10 miles or less. The research employs a quantitative approach to understand consumer attitudes, behaviors, and needs related to cycle-based commuting and electric vehicles. It justifies the selection of quantitative research and probability sampling methods. The study defines the research population, explores the merits of various sampling frames, and proposes city commuters as the target sample. It details the selection of probability sampling, explaining its advantages. The assignment also discusses various sampling methods within the chosen approach, recommending simple random sampling and provides an implementation plan, including potential problems and mitigation strategies.

Running head: MARKET RESEARCH
MARKET RESEARCH

MARKET RESEARCH 2
Table of Contents
Main research orientations and justify proposed one.............................................................3
Main research orientations.......................................................................................... 3
Justify the proposed one and decision guide subsequent actions............................................3
Explanation of research population and merits of alternative sampling frames and justification of
selected one............................................................................................................... 4
Define the research population.................................................................................... 4
Merits of alternative sampling frames............................................................................5
Suggest appropriate one and justify choice......................................................................7
Main sampling approaches, propose adopted one with justification...........................................7
Main sampling approaches......................................................................................... 7
Selection of one sampling approach and justify the decision................................................7
Various sampling methods of adopted approach, propose one with justification...........................9
Various sampling techniques of the adopted approach........................................................9
Selection of one sampling method of the adopted approach and justify the recommendation......10
Implementation plan of specific approach, potential problems and strategies to mitigate problems. .11
Implementation plan of Probability sampling process approach:.........................................11
Identifying potential problems of Probability Sampling....................................................11
Identifying potential problems of simple random probability sampling method.......................11
Strategies to mitigate the potential problems..................................................................13
References.............................................................................................................. 14

MARKET RESEARCH 3
Main research orientations and justify proposed one
Main research orientations
Quantitative research is implemented for quantifying the attitudes, opinions, behaviours, as
well as, other variables along with, creates the generalization from the higher population. The
goal in the quantitative investigation is to comprehend the association between dependent and
independent variables in the population. A big benefit of using this approach is that outcomes
are reliable, valid as well as, generalizable to a higher population (Lee, et. al., 2016).
Qualitative research facilitates valuable information for using product designing such as data
regarding patterns of behaviours, needs of the user, as well as, application of cases.
Qualitative analysis emphasizes less on statistical measurements being gathered, and more
about the nuances of what could be identified in a certain knowledge. This enables the
evidence to provide a higher level of realism that will offer more ways to develop
perspectives from during the analysis (Aslam, Balamurali, and Jun, 2019).
Justify the proposed one and decision guide subsequent actions
In the context of this research, quantitative research would be used by the market research
manager of Pulse Motors to address attitudes, behaviours as well as, needs of consumer about
cycle-based commuting and to assess whole perceptions about EVs. This research orientation
is selected to use randomized samples.
It is identified that if research respondents believe that research is intended to attain a
particular outcome, then their personal prejudice will affect the data distribution. The facts
presented through the survey are partial realities, or contradictions that could be used to
manipulate the research. Therefore, the quantitative method is highly important when
undertaking to test a particular hypothesis in a broad demographic group (Aslam, 2018).
This method uses a random information-gathering procedure. In certain conditions, it
excludes prejudice from occurring. It also offers benefits in the evidence that information can

MARKET RESEARCH 4
then be applied statistically to the general population being researched. There is a chance of
failure to recognize but reliable results would be usually obtained by this approach
(Moerkens, et. al., 2018).
Investigators will gather information in real-time situations by using quantitative research
procedure therefore, statistical assessment can take place almost simultaneously.
Moreover, surveys are used to offer immediate responses from a data-centred method that is
beneficial. Fewer delays in obtaining certain tools make it possible to identify correlations
that lead to a reliable conclusion. The use of quantitative analysis helps researchers to collect
data quickly. Quantitative analysis does not require that processes be isolated or that variables
be defined to obtain results. Therefore, implementation is a transparent process (Aslam,
2018).
The quantitative approach will permit a larger sample size for the company’s market research
manager. If a researcher will have the opportunity to test a larger sample size for the
hypothesis, then it is significant to draw a specific conclusion that would be reliable. The new
data obtained from this work makes more credibility to a result as a statistical study had more
scope to analyse. Larger samples make outliers in the study and less prone to negatively
influence outcomes that a company’s market research manager wants to perform fairly and
accurately (Wu, et. al., 2017).
Explanation of research population and merits of alternative sampling frames and
justification of selected one
Define the research population
In general, a research population is a broad set of people or artefacts which is the central
focus of a research question. Therefore, an investigator is depending on sampling tools. Often
known as the well-defined study population is set of individuals and artefacts considered to
have different traits (Wang, et. al., 2019). In research, the subject matter or system where a

MARKET RESEARCH 5
sample is extracted is a sampling frame. This is a list related to those in a population that
could be sampled, which can involve individuals, families, or organizations (Aslam and Ali,
2019).
Attribute Attribute
categories
Frequency
Age 18-22 15
23-27 13
28-32 12
33-35 10
Travelling 5-10 miles 12
15-20 miles 0
25-30 miles 0
Types of travellers Urban 50
Rural 0
Sub-Urban 0
Merits of alternative sampling frames
Low cost for sampling
When information would be gathered for population as a whole, cost would be very higher.
Moreover, sample is relatively small percentage of the population. Therefore, when data is
obtained for population sample that is major advantages in terms of declining cost (Moser
and Korstjens, 2018).
Scope of sampling is higher
Researchers are concerned to generalizing the results. It will be inefficient to research whole
population for achieving generalizations. Moreover, some populations are wider as not to be
able to quantify their attributes. The population would have shifted before analysis would
be complete. However, the sampling method allows for generalizations by analysing
variables within a moderately small proportion about population (de Macêdo, et. al., 2019).
Minimum time consuming

MARKET RESEARCH 6
The application of sampling will take less time for the company’s market research manager
of Pulse Motors. It takes less time than the technique of censusing. In the context
of tabulation and analysis, the sample would take far less time as compared to the population
(Aslam, et. al., 2018).
Organization of convenience
It is identified that some organizational issues are involved with sampling. Because the
sample is of limited scale and there is no need for extensive services. Thus, sampling is
competitive in terms of resources. The sample study requires less area and less instruments.
The correctness of data is higher
To draw samples as well as, measured the appropriate descriptive statistics, stability of
collected sample value could be estimated. Moreover, sample demonstrates population that is
taken from it. It permits for higher extent about accuracy because of small field of operations.
Besides, it is possible to perform the fieldwork carefully. Ultimately, the findings of sampling
experiments would be specific enough (Wu and Chen, 2019).
Appropriate in limited resources
There could be restricted available resources in an organization. It is not feasible to explore
the universe. By sampling, the population can be adequately identified. In the case of limited
resources, the application of sampling is an effective technique when carrying out marketing
research (Balamurali, Jeyadurga, and Usha, 2016).
Rigorous and thorough data
Measurements or findings in sample research are created of a small amount. Therefore,
comprehensive and detailed data is gathered (Die, et. al., 2016).
Better rapport
A successful investigation study involves a good relationship between the investigator and
the participants. When the research population is higher, the question of the

MARKET RESEARCH 7
relationship arises. But realistic samples allow the investigator to develop sufficient
rapport with the participants (Aslam, Azam, and Jun, 2016).
Suggest appropriate one and justify choice
In the context of this research, city commuters would be selected as a sample size from the
UK population whose age is between 18-35 years as well as, traveling 10 miles or less (per
journey) is addressed as target population for this product. This sampling frame is selected to
effectively address the attitudes, behaviours, and needs of consumers about cycle-based
commuting together with, assessing the whole perceptions about EVs.
Main sampling approaches, propose adopted one with justification
Main sampling approaches
Probability Sampling is a technique of sampling in which, samples through a greater
population are collected using a strategy relied on probability theory. In the context of the
probability sample, the participant will be chosen using random choice. Simple random
sampling, cluster sampling, stratified sampling, systematic random sampling, as well
as, multi-stage sampling are kinds of probability sampling techniques (Larral, et. al., 2018).
Non-probability sampling is characterized as method of sampling wherein the investigator
chooses samples relied on the researcher's personal judgment instead of a random choice.
This method is less robust. This technique of sampling is highly dependent on the
competence of investigators. There are several kinds of non-likely sampling techniques like
quota sampling, convenience sampling, self-selection sampling, purposive sampling as well
as, snowball sampling (Samman, et. al., 2016).
Selection of one sampling approach and justify the decision
To choose a sample for addressing attitudes, behaviours, and needs of consumers about
cycle-based commuting, probability sampling method would be selected by market research
manager of Pulse Motors. Probability sampling will facilitate the chances of acquiring sample

MARKET RESEARCH 8
that is accurately representative related to general population. Using probability sampling, the
researcher will determine sample sizes that would use in statistical methods, such as
confidence intervals as well as error margins to evaluate the findings (Afshari and
Sadeghpour Gildeh, 2017).
This method is adopted due to the following reasons:
Involves a lesser extent of judgment
When distributing the amount to an element in the population, an individual identifies it in a
random pattern that enables the probability sampling method more productive and reliable.
Cost-Effective
When the task of allocating random figures to larger population items would be over, the
phase would be half-finished. This method largely saves time as well as, expense. From that
process, the researcher will choose any number of samples (Yen, et. al., 2018).
Comparatively simpler way of sampling
Probability sampling will not require any lengthy and difficult process. And this is a much
simpler way to analyse (Afshari and Sadeghpour Gildeh, 2018).
A sample representative of the population
Probability Sampling employs random amounts to make sure the samples are as
unpredictable as the population itself (Lima, et. al., 2017).
Can be performed even though non- technical individuals
Random number allocation can be performed by any form of the individual after a
presentation, as it would not require any extensive, complicated, and critical procedure.
Minimum time consuming
This method is one that is quick and fast. This will take minimum time to finish. The saved
time would be applied for evaluating as well as interpreting.

MARKET RESEARCH 9
Various sampling methods of adopted approach, propose one with justification
Various sampling techniques of the adopted approach
Simple Random Sampling
Simple random sampling is considered as method of distributing the random amount to
population items as well as choosing any of them using some particular action. This method
would offer a more objective evaluation, as the researcher excludes successive items (Wang
and Wu, 2019).
Stratified Random Sampling
When choosing a small number of items from a broad group of items (population) to be
analysed, the researcher wants to ensure that samples collected appropriately reflect the
population. The amount of small Dataset Review matches with population features depends
primarily on the sampling approach chosen. One way to choose samples through the
population is by categorizing the entire population into small strata comprising of
components with some common features and then picking some number of samples
through each of them to be proportionate to the amount of the stratum. This sampling
approach is termed as Stratified Random Sampling, which is a kind of probability sampling
(Veerakumari and Suganya, 2018).
Systematic Random Sampling
Researchers can use systematic random sampling because the simple random sampling
requires more judgment as well as stratified random sampling requires a difficult process of
classifying the information into various groups. Researchers can also assume that this
approach is the combination of two approaches (Simple Random Sampling and Stratified
Random Sampling) (Chandler, et. al., 2019).
Cluster Sampling

MARKET RESEARCH 10
Population is categorized into groups as well as, subgroups that are somewhat close to one
another and some of two sampling techniques are used: census with one and few of
population groups and randomly pick more subsets and take a sample of them. Area sampling
(clusters are a type of geographical area) is a method of cluster sampling which is often used.
Cluster sampling creates error if the groups are not homogeneous (Wang and Wu, 2019).
Selection of one sampling method of the adopted approach and justify the recommendation
In order to address whole perceptions about EVs, sample would be selected by market
research manager of Pulse Motors by using a simple random sampling method. Following are
the reasons for selecting this method:
Involves a lesser degree of judgment
When distributing the random amount to an item in population, an individual identifies the
amount in random sequence, indicating that procedure is impartial because it would not
require the decision of an individual performing to sampling (Afshari and Sadeghpour
Gildeh, 2018).
Costs less money
If the process of allocating a random number to specific population items is completed, the
phase is half completed. This method significantly saves expenses and time as well as its
efficiency assures researchers do not need to invest huge money on the sampling method
itself. From that process, the researcher will take any number of samples (Yen, et. al., 2018).
Can be concluded in shorter time duration
It is an easy and quick procedure. It takes minimum time to complete. The time saved
would be applied for evaluating and interpreting (Lima, et. al., 2017).
Can be done even by non- technical persons too

MARKET RESEARCH 11
A random amount of allocation can be performed by any sort of individuals after a review, as
it would not require any extensive, complex as well as, critical procedure (Samman, et. al.,
2016).
Comparatively easier way of sampling
Probability sampling would not require any extensive and difficult procedure. Therefore, it is
a much simpler mode to sample (Larral, et. al., 2018).
Better chances that the sample represents the whole population
Simple random sampling utilizes random figures to ensure samples differ as much as the
population itself (Aslam, Azam, and Jun, 2016).
Implementation plan of specific approach, potential problems and strategies to mitigate
problems
Implementation plan of Probability sampling process approach:
 Define a suitable sampling method depend on study question(s) and goals.
 Selecting the most suitable sampling process and choosing the samples.
 The appropriate sample size is determined.
 Testing if the sample is representative of the sample size (Lima, et. al., 2017).
Identifying potential problems of Probability Sampling
 Probability sampling technique is more difficult as compared to non- probability
sampling technique.
 This sampling method takes more time.
 A high amount of money is required for this sampling method (Veerakumari and
Suganya, 2018).
Identifying potential problems of simple random probability sampling method
It can require a sample size that is too large.

MARKET RESEARCH 12
Simple random sampling performs better if a small percentage of total population is handled.
For such component, drawing titles from the hat comprises 10 percent of the overall
population in the example used in the introduction. Larger groups need a more
comprehensive frame for the gathered data so it can be precise. If investigators use a minimal
framework, then the sampling error would increase dramatically, making the data
ineffectively useless. It seems that there is minimal scope for the total size of a sample (Wang
and Wu, 2019).
It can be a time-consuming process to conduct this research.
To complete the research, investigators should include each person or scenario chosen via the
random sampling method. If the sample size is large then this research procedure may take a
considerable amount of time to accomplish. They need to avoid interacting with people in
communities to have the information reliable as people constantly change their responses
when they need to get along with others and feel offended when their answers are different. It
indicates that this technique requires a one-on-one communication approach that needs a
significant amount of planning for each stage (Lima, et. al., 2017).
It depends on the research work’s quality that is performed by the researcher
This drawback also arises in simple random sampling technique, since the researcher's skills
are required for the collection of data. When the study needs particular investigators to
conduct a personal interview with participants, then the data quality depends on the ability to
execute the study structure. Interviewees who struggle to adhere to a template or who may
not have the ability to analyse the specific responses may build knowledge gaps that could
become a distortion of the overall population. Simple random sampling would encounter the
same cumulative drawback as any other type of study encounter: weak implementation of the
process will often result in lesser details (Chandler, et. al., 2019).