3000 words +/- 10%Due: 30th May 11am
Question
The Research Methods module has now outlined different approaches to data
analysis, including a range of methods or techniques used by academics and
practitioners when conducting business research. We have learnt that there are
different choices to make in research and that the suitability of our analytical
techniques is determined by our assumptions and the current state of knowledge
around our research question. We have also learnt that no data is perfect, and all
methodologies and methods have merits and limitations.
In this assignment you are required to demonstrate your understanding of the
appropriateness and suitability of data analysis techniques, by justifying, applying
and critically evaluating one of the data analysis techniquesyou have learned on the
module to a given research topic and data set (see below).
Your work should be fully referenced, using appropriate literature sources, drawing
from module materials and core readings, and supplemented by your own wider
reading.
In completing your report, you should:
–
Use data from an approved source (i.e., the tutor designated transcripts or
dataset)
Show evidence of the application of your technique to reach your preliminary
results or findings
Critically review the relevance or suitability of the technique to the research
question
Students following the Mixed Methods pathway will be given a sample set of
interview transcripts and related survey data related to diversification of a local
business. Your overall research question will be set by your tutor, but you have some
scope to focus this further in accordance with your chosen method and data analysis
technique.
RQ: What diversification opportunity would best meet the needs of sunrise farm and
its current customers?
–
2 data sets, interview transcript & questionnaire results
Structure
Intro – 200 words
Approach
Initial assumptions or decisions
Main body – 1500 words
Guide to methods
o describe and justify data analysis technique
o explain assumptions or significant methodological decisions
made making reference to literature
results
o describe findings or results obtained from applying the technique
to the data
o include figures or tables to present results concisely
Critical Evaluation – 1000 words
discuss the suitability of chosen technique
give a critical account of its challenges or limitations in the context of
the research question
reflect on assumptions that were necessary to the analysis
mention any actions taken to address data quality
Recommendations and Conclusion – 300 words
briefly describe the actions or recommendations proposed in
response to the research question based on the results
possibly could include recommendations for further data gathering or
research
Guidance:
more of a focus on the evaluation of the method chosen rather than the
application
Structure
The recommended structure is given in the assessment briefing document. For Mixed
Methods students, you should take special care in the Results section not to get carried away
with the volume of data you have available. You are not supposed to analyse and write up
everything fully for this report. You simply need to demonstrate evidence of the application of
your technique, the type of results or findings your methodological techniques produce, and
account for their fit with the research question you have specified.
Things you may wish to include:
·
·
·
Graphs or tables of any significant patterns or relationships in the quantitative data.
Table of codes derived from or produced for coding of a transcript.
Excerpts or quotations from a coded transcript.
Remember, this is a methodological report, not a full research report. So it is not the purpose
of this report for you to conduct a full analysis of all the data in the dataset. You simply need
to show enough information to highlight the trends that have directed your approach or where
you would go next in your research project.
Suitable approaches would include one of:
·
·
·
·
A mixed-method or multi-method case study approach
A quantitative-led content analysis approach
A qualitative-led thematic analysis approach
A qualitative-led discourse analysis approach
Sunrise Farm Case Study notes:
–
–
20 years ago they diversified due to a competitive farming industry. They developed:
– Organic farm shop
– Partnered with a local butcher and restaurant that produced luxury yorkshire
cured hams and sausages which are manufactured from sunrise farm
ingredients and sold in the farm and butchers shop
– Opened a cafe – provided more cash flow and was an asset to the community
– Corn maze with car park and toilet block (summer only)
– Pick your own fruit (spring and summer only)
– They have looked at the potential to expand their production of luxury yorkshire
foods
– But they are mindful of the success of the organisation and the limit on
financial investment
The farm operates at a loss through winter but this is currently made up for by festive
sales in the shop and cafe
–
Investment in more food production would involve construction of another
building and additional variable costs to bring in outside ingredients which the
farm does not produce (e.g. spices, organic casings etc).
In winter there is the need for careful balance between staff costs and income
consider the potential for diversifying the farm into a major tourism attraction
versus an expansion of food production, the farm has taken on the role of
understanding their current customers; e.g. foot traffic, number of visitors, times
of day visiting (the data on vle)
–
They recognise the importance of their business to local residents
–
Summary of Key findings
(1) -Local people like to buy sweets snacks or biscuits, fresh organic farm meat, jam and
chutney.
-People from Yorkshire (except people from York) prefer Organic fruit, vegetables and
jam. (Data from Location*Purchase Intention Crosstabulation)
(2) Customers are satisfied with the parking area. Some people think that it is better to
keep the farm as it is, and some people think that the children’s playground needs to be
expanded. (Data from Interview)
Visitors with family or who with children want to see the improvements from facilities
and animals. (Data from Open-ended Question * Who with? Crosstabulation)
(3) Most consumers feel that organic products are more expensive. (Data from Interview)
(4) Some people come for the maze, they have kids with them, they think the
reward of free ice cream at the end is nice, it is a good marketing strategy
for the farm to make the maze a landmark of the farm.（Summarize from Interview)
(5) The consumption level of most people is between 20 pounds and 29.99 pounds, and
most of them are aged 25 to 34. (Data from Age* Spend Crosstabulation)
Basic statistics for questionnaire
Word Count Requirements
The word count for this assignment is 3000 words.
You must state on the front of your assignment the number of words used and this will
be checked.
The main text for this assignment must be word-processed in Arial, font 12, double
spacing, minimum 2cm margins all around.
You must observe the word count specified in this assignment brief. The School has
a policy of accepting variations to the recommended word count of plus or minus 10%.
What does this mean for you?
Markers will mark your work up to the word count maximum plus 10% and then will
stop marking; therefore all words which are in excess of the word count plus 10% will
not be marked.
Where your word count is more than 10% below that specified, it is likely that this will
result in a lack of analytical depth or relevant content, which will be reflected in the
mark assigned.
What is in the word count?
The word count includes:
–
the main text, including in-text reference citations and quotations.
The word count does not include:
–
Appendices. These may be used to include supporting data, which may be too
detailed or complex to include as a Table. They are not a device to incorporate
material, which would otherwise cause you to exceed the word limit.
Title page
Contents page
Abstract/executive summary
Tables, figures, legends
Reference lists
Acknowledgements
Page 2 of 6
Assessment Criteria
Please check the VLE for further assessment guidance that will help you demonstrate
achievement against the module-specific learning outcomes.
Generic marking criteria
G1: Argument
G2: Structure
G3: Use of sources
G4: Referencing
G5: Presentation
Module specific learning outcomes relevant to this assessment
S1: Critically examine the key characteristics of quantitative, qualitative, and mixedmethods research in business/management studies
S2: Identify and critically reflect on the underlying philosophies, theoretical principles,
methods, and techniques applicable to research in business/management
S3: Critically evaluate the strengths and weaknesses of different approaches to
research in business/management
S4: Identify and critically reflect on ethical, legal and safety issues involved in
conducting business/management research
S5 : Select, apply and critically evaluate research methodologies and methods for
specific business/management problems
Page 3 of 6
Summative Assessment
3000 Word Limit
The Research Methods module has now outlined different approaches to data
analysis, including a range of methods or techniques used by academics and
practitioners when conducting business research. We have learnt that there are
different choices to make in research and that the suitability of our analytical
techniques is determined by our assumptions and the current state of knowledge
around our research question. We have also learnt that no data is perfect, and all
methodologies and methods have merits and limitations.
In this assignment you are required to demonstrate your understanding of the
appropriateness and suitability of data analysis techniques, by justifying, applying and
critically evaluating one of the data analysis techniques you have learned on the
module to a given research topic and data set (see below).
Your work should be fully referenced, using appropriate literature sources, drawing
from module materials and core readings, and supplemented by your own wider
reading.
In completing your report, you should:
● Use data from an approved source (i.e., the tutor designated transcripts or
dataset)
● Show evidence of the application of your technique to reach your preliminary
results or findings
● Critically review the relevance or suitability of the technique to the research
question
Further guidance will be supplied to students on their specified question and data set
according to their subject specialist pathway. Students were allocated to their pathway
at the beginning of term according to their degree programme:
Advanced Quantitative Methods
● MSc Accounting and Financial Management
● MSc Management with Business Finance
Mixed Methods
● MSc Global Marketing
● MSc International Business
● MSc International Business and Strategic Management
● MSc International Strategic Management
● MSc Management
● MSc Corporate Sustainability with Environmental Management
Please note students are not permitted to choose a different pathway for the
assessment and must address the question for their allocated pathway.
Data Set
Students following the Mixed Methods pathway will be given a sample set of interview
transcripts and related survey data related to diversification of a local business. Your
Page 4 of 6
overall research question will be set by your tutor, but you have some scope to focus
this further in accordance with your chosen method and data analysis technique.
Students following the Advanced Quantitative Methods pathway will be given a sample
time series data set related to stock market performance. Your overall research
question will be set by your tutor, but you have some scope to focus this further in
accordance with your chosen company and data analysis technique.
Suggested structure:
Title
Introduction (approx. 200 words)
In your introduction you should describe the approach you are taking to the research
question, including any initial assumptions or decisions.
Main Body (approx. 1500 words)
In this section you should justify your data analysis technique and show evidence of
your application of this technique to the data. You may wish to include;
Guide to Methods
Describe and justify the data analysis technique you are using. You might wish to
explain your assumptions or significant methodological decisions you have made with
reference to relevant academic literature.
Results
Describe the findings or results you have obtained from applying the technique to the
data. You may wish to include figures or tables to present your results concisely.
Detailed workings or full results can be included in the appendices.
Critical Evaluation and Reflection (approx. 1000 words)
In this section you should discuss the suitability of your technique and give a critical
account of its challenges or limitations in the context of the research question. You
may wish to reflect upon assumptions that were necessary to your analysis or actions
you took to address data quality.
Recommendations and Conclusion (approx. 300 words)
Briefly describe the actions or recommendations you would propose in response to
the research question on the basis of your results. This might include
recommendations for further data gathering or research.
References
In this section you should list your references in Harvard style. This section does not
contribute towards your word count.
Appendices
Page 5 of 6
In this section (if necessary) you should provide evidence to demonstrate the
application of your technique, such as data tables, coding protocols or other relevant
documentation. This section does not contribute towards your word count
END OF ASSESSMENT
Page 6 of 6
Interview 1 (Female Aged 60 years)
1. Connection to the farm
(1) Started coming here with my mother
(2) Organic
2. Reasons to visit
(1) Fruit picking, fun
(2) Quite close to here
(3) Good lifestyle
3. Attitudes towards the facilities
（1）Easy to park, footpaths was easy to walk
（2）Maze is big enough for buses too so hasn’t affected weekly parking
4. Attitudes towards future development
(1) Hope it would stay as it is, think it is a ‘green belt’
(2) Might be good to have a children’s playground near the maze
Interview 2 (children aged under 5 years)
1. Connection to the farm
(1) Come here when I feel a bit lonely
2. Reasons to visit
(1) Come here when I feel a bit lonely
(2) Buy from the organic shop and have a drink in the café occasionally
3. Attitudes towards the facilities
(1) Good experience with really do cater for children
(2) A bit expensive
4. Attitudes towards future development
(1) Expand the children’s playground
(2) Have a water feature
(3) Discounts for regular customers
Interview 3 (Local Councillor)
1. Connection to the farm
(1) A local councillor
(2) George and Jane told me they were going to build an organic farm shop
2. Reasons to visit
(1) The shop, the café and the maze
3. Attitudes towards the facilities
(1) The café is wonderful
(2) Food fresh, menu depending on the seasons
(3) A bit expensive
4. Attitudes towards future development
(1) wouldn’t want Sunrise Farm to get any bigger
(2) Concentrate on the maze, a small zoo with farm animal
(3) Have a hostel type place or tents
Interview 4 (Teenager at Local School)
1. Connection to the farm
(1) Have a job at Sunrise Farm
2. Reasons to visit
(1) Had heard of Sunrise Farm but never visited
(2) My mum came here for a cup of tea with her neighbour occasionally to the
café
3. Attitudes towards the facilities
(1) A bit expensive
(2) Really nothing for the teenagers
(3) It would be good fun for holiday
4. Attitudes towards future development
(1) come here full time and go to the college for training in the kitchen one day a
week
Interview 5 (Young Couple with no children)
1. Connection to the farm
(1) Never thought about it
2. Reasons to visit
(1) First came here with a friend from work
3. Attitudes towards the facilities
(1) Lots of parking and it is well signposted off the main road (good parking
area)
(2) Good café, comfortable
(3) Fresh food
(4) New bike sheds
(5) A bit expensive
4. Attitudes towards future development
(1) Promote Sunrise Farm to people
Interview 6 Local Resident who has not visited (empty nester)
1. Connection to the farm
(1) lived in this area all life
2. Reasons to visit
(1) Never been to Sunrise Farm
3. Attitudes towards the facilities
(1) Fresh fruit
(2) Good café
(3) People are kind
4. Attitudes towards future development
(1) Offer a bus for all the older people around here
Interview 7 (Fruit Picker)
1. Connection to the farm
(1) The staff from the farm are the same every year and they remember you
2. Reasons to visit
(1) Visit Sunrise Farm to pick raspberries and strawberries
3. Attitudes towards the facilities
(1) Fresh fruit
(2) A bit expensive
(3) Plenty of parking, and lots of buckets to put your berries in
4. Attitudes towards future development
(1) Don’t change anything about the raspberry & strawberry picking
(2) Open vegetables for picking
Interview 8 Annual Family Visitor (children aged 10-15 years)
1. Connection to the farm
(1) Used to live around here, both me and my husband went to school around
here
2. Reasons to visit
(1) Always buy our Christmas tree and some Sunrise jam from here
(2) Went around the maze in summer
3. Attitudes towards the facilities
(1) Free ice cream
(2) Good experience
(3) A bit expensive
(4) Nothing for teenagers
(5) Good drinks
(6) Fruit picking is funny
4. Attitudes towards future development
(1) Sent me a reminder
(2) Love it the way it is
Interview 9 (International Student at York University)
1. Connection to the farm
(1) Only been living in the area for a year
2. Reasons to visit
(1) Hadn’t heard of Sunrise Farm until do these interviews
3. Attitudes towards the facilities
(1) Willing to buy organic food
(2) Want to visit maze
(3) Don’t like the idea of fruit-picking
(4) Visiting traditional places
(5) Going shopping in the old parts of York
4. Attitudes towards future development
(1) Making the place into a bigger tourist attraction
Frequencies
Notes
Output Created
14-MAY-2023 23:24:02
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics are based on all
cases with valid data.
Syntax
FREQUENCIES
VARIABLES=Q4 Q6 Q11
Q12 Q8 Openquestion
/ORDER=ANALYSIS.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Statistics
How many
Who with?
N
people
Age
Spend
Transport
Openquestion
Valid
59
59
59
59
59
41
Missing
0
0
0
0
0
18
Frequency Table
Who with?
Cumulative
Valid
Frequency
Percent
Valid Percent
Percent
Here with family
27
45.8
45.8
45.8
Here with children
10
16.9
16.9
62.7
alone
5
8.5
8.5
71.2
Here with friends
7
11.9
11.9
83.1
Here with family, Here
7
11.9
11.9
94.9
1
1.7
1.7
96.6
2
3.4
3.4
100.0
59
100.0
100.0
with children
Here with friends, Here
with children
Here with family, Here
with friends, Here with
children
Total
How many people
Cumulative
Valid
Frequency
Percent
Valid Percent
Percent
0
5
8.5
8.5
8.5
1
7
11.9
11.9
20.3
2
10
16.9
16.9
37.3
3
12
20.3
20.3
57.6
4
12
20.3
20.3
78.0
5
5
8.5
8.5
86.4
Over 5
8
13.6
13.6
100.0
Total
59
100.0
100.0
Age
Cumulative
Valid
Frequency
Percent
Valid Percent
Percent
18-24
3
5.1
5.1
5.1
25-34
16
27.1
27.1
32.2
35-44
23
39.0
39.0
71.2
45-54
11
18.6
18.6
89.8
55-64
4
6.8
6.8
96.6
Over 65
2
3.4
3.4
100.0
Total
59
100.0
100.0
Spend
Cumulative
Valid
Frequency
Percent
Valid Percent
Percent
£0-9.99
1
1.7
1.7
1.7
£10-19.99
4
6.8
6.8
8.5
£20-29.99
13
22.0
22.0
30.5
£30-39.99
5
8.5
8.5
39.0
£40-49.99
6
10.2
10.2
49.2
£50-59.99
8
13.6
13.6
62.7
£60-69.99
6
10.2
10.2
72.9
£70-79.99
5
8.5
8.5
81.4
£80-89.99
3
5.1
5.1
86.4
£90-99.99
3
5.1
5.1
91.5
Over £100
5
8.5
8.5
100.0
Total
59
100.0
100.0
Transport
Cumulative
Valid
Frequency
Percent
Valid Percent
Car
53
89.8
89.8
89.8
Bus
3
5.1
5.1
94.9
Bicycle
2
3.4
3.4
98.3
Walk
1
1.7
1.7
100.0
Total
59
100.0
100.0
Openquestion
Percent
Cumulative
Valid
Missing
Frequency
Percent
Valid Percent
Food-related
4
6.8
9.8
9.8
Environment
3
5.1
7.3
17.1
Facilities
10
16.9
24.4
41.5
Animals
11
18.6
26.8
68.3
More shop options
4
6.8
9.8
78.0
Kids
2
3.4
4.9
82.9
Cafe
3
5.1
7.3
90.2
Crafts
4
6.8
9.8
100.0
Total
41
69.5
100.0
System
18
30.5
59
100.0
Total
Percent
MULT RESPONSE GROUPS=$Do (cafe pickfruit shop maze (1))
/FREQUENCIES=$Do.
Multiple Response
Notes
Output Created
14-MAY-2023 23:25:26
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each table
are based on all the cases
with valid data in the
specified range(s) for all
variables in each table.
Syntax
MULT RESPONSE
GROUPS=$Do (cafe
pickfruit shop maze (1))
/FREQUENCIES=$Do.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Case Summary
Cases
Valid
N
$Doa
Missing
Percent
59
N
100.0%
Total
Percent
0
0.0%
N
Percent
59
a. Dichotomy group tabulated at value 1.
$Do Frequencies
Responses
N
$Doa
Percent
Percent of
Cases
Cafe
49
32.0%
83.1%
Pickfruit
30
19.6%
50.8%
Shop
53
34.6%
89.8%
Maze
21
13.7%
35.6%
153
100.0%
259.3%
Total
a. Dichotomy group tabulated at value 1.
DESCRIPTIVES VARIABLES=Q4 Q6 Q11 Q12 Q8 Openquestion
/STATISTICS=MEAN STDDEV MIN MAX.
Descriptives
100.0%
Notes
Output Created
14-MAY-2023 23:26:35
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User defined missing
values are treated as
missing.
Cases Used
All non-missing data are
used.
Syntax
DESCRIPTIVES
VARIABLES=Q4 Q6 Q11
Q12 Q8 Openquestion
/STATISTICS=MEAN
STDDEV MIN MAX.
Resources
Processor Time
00:00:00.02
Elapsed Time
00:00:00.00
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Who with?
59
1.00
7.00
2.4576
1.74516
How many people
59
.00
6.00
3.1186
1.79160
Age
59
1.00
6.00
3.0508
1.12071
Spend
59
1.00
11.00
5.7627
2.79987
Transport
59
1.00
4.00
1.1695
.56179
Openquestion
41
1.00
8.00
4.1220
2.00244
Valid N (listwise)
41
CORRELATIONS
/VARIABLES=Q11 Q12
/PRINT=TWOTAIL NOSIG FULL
/MISSING=PAIRWISE.
Correlations
Notes
Output Created
14-MAY-2023 23:27:11
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each pair of
variables are based on all
the cases with valid data
for that pair.
Syntax
CORRELATIONS
/VARIABLES=Q11 Q12
/PRINT=TWOTAIL
NOSIG FULL
/MISSING=PAIRWISE.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.01
Correlations
Age
Age
Pearson Correlation
Spend
1
Sig. (2-tailed)
N
Spend
-.002
.991
59
59
Pearson Correlation
-.002
1
Sig. (2-tailed)
.991
N
59
59
CORRELATIONS
/VARIABLES=Q11 Q12 Q4 Q6 Q8 Openquestion
/PRINT=TWOTAIL NOSIG FULL
/MISSING=PAIRWISE.
Correlations
Notes
Output Created
14-MAY-2023 23:27:45
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each pair of
variables are based on all
the cases with valid data
for that pair.
Syntax
CORRELATIONS
/VARIABLES=Q11 Q12
Q4 Q6 Q8 Openquestion
/PRINT=TWOTAIL
NOSIG FULL
/MISSING=PAIRWISE.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Correlations
How many
Age
Age
Pearson Correlation
Spend
1
-.153
-.201
.991
.247
.128
59
59
59
59
Pearson Correlation
-.002
1
.040
.322*
Sig. (2-tailed)
.991
.762
.013
N
N
Who with?
59
59
59
59
Pearson Correlation
-.153
.040
1
.054
Sig. (2-tailed)
.247
.762
59
59
59
59
Pearson Correlation
-.201
.322*
.054
1
Sig. (2-tailed)
.128
.013
.684
59
59
59
59
Pearson Correlation
.096
-.314*
.131
-.020
Sig. (2-tailed)
.471
.016
.324
.879
59
59
59
59
Pearson Correlation
.208
-.165
.144
-.151
Sig. (2-tailed)
.191
.301
.368
.347
41
41
41
41
N
How many people
N
Transport
N
Openquestion
people
-.002
Sig. (2-tailed)
Spend
Who with?
N
.684
Correlations
Transport
Age
Pearson Correlation
.096
.208
Sig. (2-tailed)
.471
.191
59
41
Pearson Correlation
-.314*
-.165
Sig. (2-tailed)
.016
.301
59
41
Pearson Correlation
.131
.144
Sig. (2-tailed)
.324
.368
59
41
Pearson Correlation
-.020
-.151
Sig. (2-tailed)
.879
.347
N
59
41
Pearson Correlation
1
.279
N
Spend
N
Who with?
N
How many people
Transport
Openquestion
Sig. (2-tailed)
N
Openquestion
.077
59
41
Pearson Correlation
.279
1
Sig. (2-tailed)
.077
N
41
41
*. Correlation is significant at the 0.05 level (2-tailed).
CROSSTABS
/TABLES=Q4 BY Openquestion
/FORMAT=AVALUE TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Crosstabs
Notes
Output Created
14-MAY-2023 23:30:56
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each table
are based on all the cases
with valid data in the
specified range(s) for all
variables in each table.
Syntax
CROSSTABS
/TABLES=Q4 BY
Openquestion
/FORMAT=AVALUE
TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Dimensions Requested
2
Cells Available
524245
Case Processing Summary
Cases
Valid
N
Who with? *
Missing
Percent
41
N
Total
Percent
69.5%
18
N
Percent
30.5%
59
100.0%
Openquestion
Who with? * Openquestion Crosstabulation
Count
Openquestion
Who with?
Food-related
Environment
Facilities
Animals
Here with family
1
3
6
6
Here with children
0
0
2
3
alone
2
0
0
1
Here with friends
0
0
1
0
Here with family, Here
1
0
1
1
4
3
10
11
with children
Total
Who with? * Openquestion Crosstabulation
Count
Openquestion
More shop
options
Who with?
Kids
Cafe
Crafts
Here with family
3
0
0
2
Here with children
0
1
1
0
alone
0
0
0
1
Here with friends
1
1
1
1
Here with family, Here with
0
0
1
0
4
2
3
4
children
Total
Who with? * Openquestion Crosstabulation
Count
Total
Who with?
Here with family
21
Here with children
7
alone
4
Here with friends
5
Here with family, Here with children
4
Total
41
CROSSTABS
/TABLES=Openquestion BY Q4
/FORMAT=AVALUE TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Crosstabs
Notes
Output Created
14-MAY-2023 23:31:33
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each table
are based on all the cases
with valid data in the
specified range(s) for all
variables in each table.
Syntax
CROSSTABS
/TABLES=Openquestion
BY Q4
/FORMAT=AVALUE
TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Resources
Processor Time
00:00:00.00
Elapsed Time
00:00:00.00
Dimensions Requested
2
Cells Available
524245
Case Processing Summary
Cases
Valid
N
Openquestion * Who
Missing
Percent
41
N
69.5%
Total
Percent
18
N
30.5%
Percent
59
100.0%
with?
Openquestion * Who with? Crosstabulation
Count
Who with?
Openquestion
Total
Here with
Here with
family
children
Here with
alone
friends
Food-related
1
0
2
0
Environment
3
0
0
0
Facilities
6
2
0
1
Animals
6
3
1
0
More shop options
3
0
0
1
Kids
0
1
0
1
Cafe
0
1
0
1
Crafts
2
0
1
1
21
7
4
5
Openquestion * Who with? Crosstabulation
Count
Who with?
Total
Here with family, Here
with children
Openquestion
Food-related
1
4
Environment
0
3
Facilities
1
10
Animals
1
11
More shop options
0
4
Kids
0
2
Cafe
1
3
Crafts
0
4
4
41
Total
CROSSTABS
/TABLES=Q4 BY Q12
/FORMAT=AVALUE TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Crosstabs
Notes
Output Created
14-MAY-2023 23:32:19
Comments
Input
Data
C:\Users\asus\Desktop\Q
uestionnaire.sav
Active Dataset
数据集1
Filter
Weight
Split File
N of Rows in Working
59
Data File
Missing Value Handling
Definition of Missing
User-defined missing
values are treated as
missing.
Cases Used
Statistics for each table
are based on all the cases
with valid data in the
specified range(s) for all
variables in each table.
Syntax
CROSSTABS
/TABLES=Q4 BY Q12
/FORMAT=AVALUE
TABLES
/CELLS=COUNT
/COUNT ROUND CELL.
Resources
Processor Time
00:00:00.02
Elapsed Time
00:00:00.00
Dimensions Requested
2
Cells Available
524245
Case Processing Summary
Cases
Valid
N
Who with? * Spend
Missing
Percent
59
N
100.0%
Total
Percent
0
N
0.0%
Percent
59
100.0%
£10-19.99
£20-29.99
£30-39.99
Who with? * Spend Crosstabulation
Count
Spend
£0-9.99
Who with?
Here with family
1
1
6
3
Here with children
0
1
3
1
alone
0
0
1
0
Here with friends
0
2
1
0
Here with family, Here
0
0
1
1
0
0
0
0
0
0
1
0
1
4
13
5
with children
Here with friends, Here
with children
Here with family, Here
with friends, Here with
children
Total
Who with? * Spend Crosstabulation
Count
Spend
£40-49.99
Who with?
£50-59.99
£60-69.99
£70-79.99
Here with family
3
2
3
2
Here with children
0
2
1
2
alone
1
1
0
0
Here with friends
2
0
0
1
Here with family, Here with
0
3
2
0
0
0
0
0
0
0
0
0
6
8
6
5
children
Here with friends, Here with
children
Here with family, Here with
friends, Here with children
Total
Who with? * Spend Crosstabulation
Count
Spend
£80-89.99
Who with?
£90-99.99
Over £100
Here with family
0
3
3
27
Here with children
0
0
0
10
alone
2
0
0
5
Here with friends
0
0
1
7
Here with family, Here with
0
0
0
7
1
0
0
1
0
0
1
2
3
3
5
59
children
Here with friends, Here with
children
Here with family, Here with
friends, Here with children
Total
SET Small=0.0001 THREADS=AUTO Printback=On DIGITGROUPING=No LEADZERO=No.
SET Printback=On.
SET Small=0.0001 THREADS=AUTO DIGITGROUPING=No LEADZERO=No.
Sunrise facilities
Comment
facilities
to
the
Parking Area
Parking area is big,
Improvement area
Respondent Type
NO
Regular Customer to
convenient, and plenty
the Café: Female
Aged 60 years, Fruit
picker
Maze
-Free ice cream award
is amazing
-A
good
-Maybe
idea
for
build
a
big
playground for children
Regular Customer to
the Café: Female
children
Aged 60 years,
-No advertisement to
Occasional Family
tell people
Visitor to the Cafe
-Funny
(children aged under 5
years), Local
Councillor, Teenager
at Local School, Fruit
picker, Annual Family
Visitor (children aged
10-15 years)
Sunrise Farm
– Keep it, don’t want
No
Occasional Family
Visitor to the Cafe
change anymore
(children aged under 5
years), Local
Councillor, Annual
Family Visitor (children
aged 10-15 years)
-Not for teenager, feel
-Do some promotion
Teenager at Local
bored
– Provide bus service for
School, Young Couple
-It has a great café
old people
with no children, Local
– Make the place into a
Resident who has not
bigger tourist attraction
visited (empty nester),
Fruit picker,
International Student
at York University
Shopping
– It is a real Christmas
No
Annual Family Visitor
shop
(children aged 10-15
– lots of decorations and
years)
lights
and
presents,
Christmas trees
Cafe
– A little expensive
Occasional Family
– Cafe menu depending
Visitor to the Cafe
on the seasons, food is
(children aged under 5
years), Local
organic and fresh
–
It
has
a
Councillor, Teenager
good
community
at Local School, Young
– It has a big open fire,
Couple with no
which make people feel
children
comfortable
Organic product
– The price is little
– Do some discounts
Regular Customer to
expensive
the Café: Female
– The food is fresh,
Aged 60 years,
healthy and taste good
Occasional Family
– It has fresh jam
Visitor to the Cafe
(children aged under 5
years), Young Couple
with no children, Fruit
picker, International
Student at York
University
Fruit pick
– It is very funny
– Open vegetables to
Regular Customer to
– The fruit is very fresh
pick
the Café: Female
– The most beautiful
Aged 60 years, Local
fruit and the farm is
Resident who has not
organised
visited (empty nester),
Fruit picker
Distance
Long distance
– Offer bus service
Young Couple with no
children, Local
Resident who has not
visited (empty nester),
International Student
at York University
STUDENT EXAMINATION NUMBERS
Y3873557
Y3879511
Y _______________
Y _______________
Y _______________
Module No:
MAN00112M
Module Title:
Research Methods
Module Tutor:
Dr Matthew Holmes
Dr Ziyun Fan
Professor Sonal Choudhary
Dr Danson Kimani
Dr Shenghua Shi
Essay Title:
Summative Assessment B – Summer Term
Sunrise Farms Group Project
Group Number
Group 62
Word Count:
1
TITLE
Table of Contents
Chapter
Subsection
Page Number
Chapter 1: Introduction
Chapter 2: Guide to
Methods
2.1 Mixed Methods Techniques
2.2 Qualitative Analysis Techniques
2.3 Quantitative Analysis Techniques
Chapter 3: Results
3.1 Thematic Coding of Interview
Transcripts
3.2 Pearson Chi-Square Analysis of
Survey Data
Chapter 4: Evaluation and Reflection
Chapter 5: Conclusions
References
Appendix
Chapter 1: Introduction
Chapter 2: Guide to Methods
2.1 Mixed Methods Techniques
As practical business research, this research is underpinned by a pragmatic
standpoint tying together subjective and objective perspectives, allowing both
viewpoints to generate a bigger picture (Saunders et al., 2019). To best assess the
needs of Sunrise Farm and it’s customers this essay will utilise a convergent mixed
2
methods research design to simultaneously conduct both qualitative and quantitative
data analysis of equivalent status (Denscombe, 2021). This converging parallel
research design will allow for comparison between the two different strands of data,
which together can be used to interpret the needs of Sunrise Farm customers
(Harvard Catalyst, 2023). This approach best applies to the research question as
both the interview transcript and customer survey data carry equal weighting and can
be understood independently before drawing the findings into a comparative and
concluding picture. Mixed methods analysis is a practical tool allowing for a more
complete study able to utilise both fact and meaning. Quantitative and qualitative
research operate in separate paradigms, however, the combination of the two is
beneficial for understanding consumer behaviour (Bell et al., 2019). The available
data utilised in this mixed methods analysis will not be sampled due to the scale of
information available.
2.2 Qualitative Analysis Techniques
2.3 Quantitative Analysis Techniques
Chapter 3: Results
3.1 Thematic Coding of Interview Transcripts
Thematic analysis is the chosen qualitative data analysis technique used for
the analysis of the interviews conducted for this research. And as Williams and
Moser (2019) discuss, once the researcher provides a theme with a code, the object
is to arrange things in a systematic order, to make something part of a system or
classification which then permits data to be grouped and relinked in order to
consolidate meaning and explanation (Lincoln and Guba 1985, p.21). In the case of
the Sunrise Farm research, the objective is to discover ‘What diversification
opportunity would best meet the needs of Sunrise Farm and its current customers?’.
This research objective can be used to group and refine themes that emerge in the
thematic analysis of the interview transcripts into 5 key codes which capture both the
3
needs of the customers and their views on possible diversification opportunities:
community, affordability, enjoyment, accessibility and transport, and future
development. A full table of coding for these 5 codes is available in the appendices
of this report which details the code, a definition of the code and quotations from the
various interview transcripts. The transcripts frequently referred to the sense of
community, friendship and inclusivity that they value at Sunrise Farm, with comments
such as “He is part of the family now” (Interview 1). These comments often refer to
the positive interpersonal connections with farm staff and other customers at the
farm, generating significant value and proving to be an important motivator for
customers’ visits; therefore, coded as “Code 1: Community”. The affordability of the
products and services, reported as “Code 2: Affordability”, emerged as a key need
for the customers of Sunrise Farm; with comments consistently referring to products
and services with the words “price” (Interview 7), “budget” (Interview 2), “expensive”
(Interview 2), “costs” (Interview 5). “Code 3: Enjoyment”, captures the need for family
fun and enjoyment in the customers’ experience at Sunrise Farm. Customers often
used words such as “fun” (Interview 8) (Interview 2) and “laughed” (interview 8)
when describing their experiences at the farm. The ability to have a good time was
an important factor in customers’ decisions to visit the farm. “Code 4: Accessibility
and Transport”, focuses on the need for easy access to the facilities for all
customers. Frequently, comments such as “well sign-posted” (Interview 5) and
“parking” (Interview 7) (Interview 1) (Interview 3) referred to transport, and other
comments referred to accessibility such as “room in the shop” (Interview 2). Lastly,
comments related to the expansion of Sunrise Farm into a theme park were coded
as “Code 5: Expansion”. This theme captures the customers’ opinions about the
potential of Sunrise Farm to become a theme park. Comments such as “they need
to…” (Interview 5) and “It would be a complete change of organisation” (Interview 3)
indicate that customers have specific ideas about how Sunrise Farm can evolve. At
the same time, comments such as “I would hope it would stay as it is” (Interview 1)
indicate that customers have a deep emotional connection with the farm and want it
to continue to offer the same experiences in the future without developing into a
theme park. Overall, the 5 key themes identified in this study strongly suggest that
participants appreciate the community-driven approach to business and its
long-standing traditional practices. The overall sentiment from the coding is that
customers ‘needs’ in the current and future development of the farm are affordable,
4
easily accessible facilities and products that provide enjoyment for the whole family
through community-driven attractions and services. Participants expressed a strong
desire that the farm remains a farm shop and café with seasonal attractions, and not
become a theme park in the future.
3.2 Pearson Chi-Square Analysis of Survey Data
As detailed previously, the quantitative statistical analysis chosen for this
study is the Pearson Chi-square test. The hypothesis formulated for this research,
that the chi-square test aims to investigate is: “If the age group is related to the
product category, then we would expect to see a significant association between
these variables because different age groups may have different preferences and
needs for different types of products”. And therefore the null-hypothesis is that
“There is no significant association between age group and product category, and
any observed differences are due to chance”. The results tables of the chi-square
test revealed no significant association between the variables of age category and
products purchased. An ‘alpha-value’, or ‘p-value’ of p
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