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MKF2121 Marketing Research Methods
创建日期：2024-06-18 14:51:12
所属分类：市场营销Marketing
标签： MKF2121
Marketing Research Methods

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MKF2121 Marketing Research Methods

Assignment 2: Marketing Research Analysis Report
The objective of this assignment is to give students the opportunity to practice solving real
marketing research problems with data.
Detailed instruction on how to complete the assignment is available in “Assignment 2 – Guide”
section of this document.
Here are some general requirements for the assignment.
1. The due date/time of the assignment is by 11:55 pm on May 24 (Friday of Week 12), 2024.
2. The assignment is individual work. Collaboration or consultation with anyone other than
the unit’s teaching staff is strictly prohibited
3. One copy is to be uploaded at the “Assignment 2 Submission” tab on the unit’s Moodle
site. In the rare event that unforeseen technical issues on Moodle prevent you from
completing the submission process, you should email the report to your chief examiner.
4. You need to first agree to the "plagiarism statement" above before you are allowed to
submit this assignment. Do NOT include cover sheets in your submission.
5. Submission format: PDF file. Maximum number of words is 2000 (±10%, and excluding
words and numbers that are part of your SPSS tables or references). The word count must
be included in the first page of your document. Exceeding the word count could result in a
penalty of up to 10% of your mark for the assignment
6. Please put any references you may have in the Appendix.
7. Students are required to keep a soft copy of their report until they get the marked report
back. It is also the student's responsibility to double check that the assignment has been
completely uploaded to the correct link on time and that it is the correct version. To
double check, go to the Moodle link where you submitted the assignment, download your
submitted file and check: 1) that the file is downloadable and can be opened using Adobe
Acrobat; and 2) that it is the file you intend to submit for grading
8. Please contact your lecturer if you have any further questions.
2
Assignment 2 - Guide
A marketing research analysis report communicates the result of a study to clients. The report is
usually commissioned by the manager at the end of the Market
Research Process to solve the Management Decision Problem (MDP)
and inform future decisions.
Suppose that you have been commissioned by the American
disposable diaper company Kimberly-Clark (makers of Huggies brand)
to draft a brief research report based on the questionnaire and data of Case 3.3 “Kimberly-Clark:
Competing Through Innovation” (henceforth, “the KC survey” and “the KC data.”). Kimberly-Clark
wants to get specific information from potential customers about their preferences and any
underlying market segments. They want to understand customer reactions to their new direct mail
(mailer) campaign. Please read the KC case and survey from the textbook (Pages 774-777) and
understand the MDP. You will be using the KC dataset to solve the MRP and report to the
manager.
Note that the survey collects customer awareness and perceptions for KC and different competing
fast-food chains in terms of multiple service and brand-related attributes. Below is the framework
of the research report –
1. Definition of the research problem
(a) Define the market research problem (MRP)
Based on the questionnaire provided, define a marketing research problem (MRP) with
components. The overall statement of the MRP should be “to identify and better understand the
key drivers/predictors of ____.” You need to fill in a blank with a customer attitude, belief or
behavioural variable that is measured by the KC survey. In addition to the overall statement, you
need to formulate at least two components for your MRP.
The MRP must be able to be addressed with the attached dataset collected with the KC
survey. In approaching this task, you should start by carefully reading through the accompanying
questionnaire and familiarize yourself with the SPSS dataset. Ask yourself the following questions:
what information has been collected from the target population? What are the variables that are
measured? How can KC make use of the information to improve their decision-making?
(b) Provide a brief justification for your MRP
Provide a brief explanation on how this research can help your client (i.e., why it is
important to understand the particular customer attitude or behaviour in this context). This
should be consistent with section 3 below where you discuss the managerial implication of your
findings. This could also include references from a background literature review. You may also
read the case to provide further justify your MRP given the background of the case.
3
2. Research approach and hypotheses
Come up with at least 5 comparative or relational research questions (RQ). Note that you
need to develop your own original RQs (i.e., you cannot the RQs used in mini-tasks or class
examples). Collectively, your RQs should cover ALL the components of your marketing research
problem proposed in the previous section. Note that because these RQs need to be “answerable”
by the KC dataset, they should only involve variables measured in the KC survey. This requires
you to be very familiar with each question in the questionnaire.
You can depict the research approach in the form of an Analytical Model. This section also
shows development of research approach and hypotheses, specification of information needed
and a data analysis plan. For each RQ,
• Clearly identify which component the RQ corresponds to.
• Clearly state both the null and alternative hypotheses, which are to be tested in the
data analysis section
• Clearly identify ALL the variables that you use to answer the research question and the
question in the questionnaire/dataset that measures this variable (to illustrate with a
hypothetical example, if the variable you use is “age of the respondent”, and it is
measured by question 15 in the accompanying questionnaire, you should include the
information in your report). If you use a recoded variable, describe the recoding (for
example., “young customers”: age <=30; “mature customers”: age > 30, etc)
• Name the statistical test you use to test the hypothesis (for example, “an independent-
samples t-test of the difference in loyalty between male and female”). If a multiple
regression is used to test several hypotheses simultaneously, name the dependent and
independent variables that will be included in the regression.
For this section, usage of bullet points and tables is required.
A list of the main statistical tests discussed in the lecture is provided below. Please note
that you are not required to use ALL the techniques (choose only what is appropriate for your
hypotheses). That being said, appropriate use of a variety of techniques or the usage of more
advanced techniques such as multiple regressions or cluster analysis is a necessity for high
marks for this section. Note that the statistical techniques used should be able to answer the
original research questions and generate relevant managerial insights.
You need to consider a number of issues in deciding which technique to choose for a
particular test. For example, certain techniques are only appropriate for interval-scaled data, while
others can be used for both interval- and ordinal-scaled data. Similarly, some techniques only
allow for comparison between two groups, while others allow you to compare the differences
between multiple groups.
List of the main statistical techniques
1. T‐tests (one sample/independent samples/paired samples) can be used to test for
differences between means of subgroups/variables.
4
2. Chi‐square test of association can be used to test the (non-linear) association between two
categorically scaled variables.
3. Chi-square test of proportions can be used to test for sample representativeness.
4. Analysis of variance (ANOVA) can be used to see whether there are any differences across
the categories of the non‐metric variables with respect to any of the metric variables.
5. Correlation analysis measures the degree to which there is a linear association between
two interval or ratio scaled variables.
6. Multiple regression can be used to explain the variation in dependent variables (outcome
or effect variables) using other metric variables as independent variables (predictors),
and/or test for differences across groups (using dummy variables).
7. Cluster analysis to identify key market segments
3. Key Descriptive/Summary Statistics
First, briefly describe the data based on the information you have. Consider the following
questions as you work on this section. Answers to these questions will provide a general
description of how the data was collected for your survey sample. This serves as an introduction of
the sample data to the manager.
a) What is the target population?
b) What is the sample size? (Here, assume that the sample is representative of the
population)
c) Broadly speaking, what kind of information has been gathered with the questionnaire (e.g.,
target population’s attitudes and behaviour towards what? What demographic information
is collected)
For EACH of your variables chosen in Section 2, provide appropriate descriptive statistics. These
could include frequency bar-charts/histograms or descriptive tables.
• In case you want to include a bar chart/histogram, you may just include the plot
directly for each variable (i.e., the SPSS frequency table is NOT required)
• You can also choose descriptive tables for describing metric variables.
• For the re-coded variables in these RQs, provide this information for the re-coded
version (i.e., not the source variable from which the re-coded variable is derived)
• If you have missing values in your variables (for e.g., values such as “99”), you can
find these out from Variable View of the SPSS dataset. You may wish to recode
missing/extreme values as missing on SPSS.
• You can choose to represent these descriptive tables/figures in-text or create a
separate appendix at the end of the document.
5
4. Statistical Analysis Results (25%)
You are required to report the results of your statistical tests. This includes both the SPSS output
as well as the interpretation of the test/regression/segmentation analyses.
• Clearly state the outcome of each statistical analysis and what it means in plain English.
The outcome of each statistical analyses should be part of the main text.
• Make sure that the output tables are properly labelled and clearly indicate which analyses
it tests.
Examples for including SPSS output
Table 1. Comparing the difference between 2007 and 2011
revenue (H1)
Paired Samples Test
Paired Differences
t df Sig. (2-tailed) Mean
Std.
Deviation
Std. Error
Mean
95% Confidence Interval of
the Difference
Lower Upper
Pair 1 Firm revenue in 2011 – Firm
revenue in 2007
.53 .77 .10 .32 .74 5.15 60 .001
Please provide all SPSS statistical output from which you have derived your results—including any
steps in data cleaning, recoding and data description. This includes your handling of missing
values. Failure to comply could result in 40% reduction in your final mark for this assignment.
5. Discussions of the managerial implication of your main findings (10%)
Discuss the managerial implication of your main findings. For example, if you do find that
customer satisfaction varies by income, how could your client use this information for its business
decision making? This discussion should be based on the specific questions you proposed. This
serves as a justification for your proposed research questions. Note that the managerial
implication needs to be broadly consistent with the justification of MRP in section 1.
Appendices: (optional)
Background literature or references
Descriptive characteristics (see instructions for Section 3)
Note: All text (main text + appendices), barring SPSS output (tables or figures) and background
literature references, is counted towards document word count.
Number the tables
Indicate which hypothesis
is being tested
6
Marking criteria
1. Problem definition (15% of assignment overall mark)
• Is the marketing research problem clearly defined and well thought-out?
• Is the justification sensible and appropriate?
2. Research approach and hypotheses (25% of assignment overall mark)
• Do the RQs provide a good coverage of the MRP components? Are they well thought-out?
• Are the constructs, variables and questionnaire questions correctly identified?
• Are appropriate statistical tests chosen to test the hypotheses?
• Is all the information available – either in main text or appendices?
3. Key Descriptive/Summary statistics (15% of assignment overall mark)
• Are all relevant variables described?
• Are the descriptive statistics appropriate to the measurement scales of the variables?
• If any recoding is performed to create new variables or for cleaning missing values, has this
been appropriately described?
4. Statistical Analysis Results (25% of assignment overall mark)
• Are the statistical techniques correctly executed?
• Are the results correctly interpreted?
• Are all the SPSS output available?
5. Discussion of Managerial Implications (10% of assignment overall mark)
• Is the discussion of findings correct and sensible?
• Is the discussion of managerial implication sensible and broadly consistent with section 1?
6. Quality of writing and communication (10% of assignment overall mark)
• clearly explained; writing is cogent, lucid and flows naturally
• appropriate use of bullet points and tables
• proper formatting of document
• reads like a report, not a record of a Q&A session
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