[SOLVED] Past Paper: Time Series Analysis

The provided document is a time series analysis table with data ranging from 4.0 to 8.7. The table consists of multiple columns representing different variables, such as 'Time' (in months), 'Value', 'Period', 'Total', 'Solved', and 'Total'. Each row corresponds to a specific time period, and the values in each column represent the corresponding data point for that period. This data is likely used for analyzing trends and patterns over time.

Quantitative Analysis
for Marketing
Management

Table of Contents
INTRODUCTION...........................................................................................................................3
RECOMMENDATION...................................................................................................................7
REFERENCES................................................................................................................................9
Appendix 1.....................................................................................................................................10

INTRODUCTION
Quantitative analysis is an essential aspect that deal with the concept which assists in
taking a note of numerical values to a variable. This model is further aimed at the develop in-
depth knowledge of the behaviour of consisted variables. Corrugated paper sales(CPS) is well
known as paper manufacturer company which is situated in Manchester UK. They are supplying
paper products to various merchants and packaging companies for so many years. For better
understanding of their products quality and customer perceptions, CPS wants to conducts a
survey over the existing customers of the company. The data is being collected from taking 200
samples of purchasing managers from firm buying from CPS. For instant satisfaction with CPS,
the results would be helpful in making decision about whether strategic alliance or partnership is
suitable for expanding their business in various marketplaces (Dekker and et. al., (2013).
According to the mentioned information about CPS products that this company is
providing re-cycle able environment friendly packing materials. Goods are more versatile and
cost efficient techniques to transport, protect and secure wide range of items. After purchased by
West Bromwich-based CBS packaging group they have relocated their business operations by
setting long term base in a 27000 Sq. ft. The main part of the company to sell paper products to
two primary market segment such as magazine sector and book publishing company. CPS wants
to create better understanding of customer characteristics and relationships among their
perception of CPS. In order to formulate this level of knowledge under this condition, a research
of existing customers of the firm. The information is gather from 200 respondents from firms
purchasing from CPS (Tayur, Ganeshan and Magazine, (2012). There are two types of data collection
research is being done. These are mentioned underneath:
(a): The first types of data reflect characteristics of the respondents which consists of information
like:
 Size of the customers
 Length of the purchase relationship
(b): The second type of data was based on the perception of CPS's performance over 13
attributes.
Research survey is the most common method of gathering data regarding population of
interest. There are various types of survey and modes to deal with them. Basically, two of the
main features of survey:
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Questionnaire: It is complete set of research questions those are categorise into closed
ended and open-ended. It aims to define a better characteristics of customers. This would include
an understanding of traits or behaviours such as asking respondents to examine their age group
of total size (Kotler, (2015).
Sampling: For this particular research a total of 200 samples is been taken in to
consideration. One of the major strength of sampling is to make accurate estimate of total
populations characteristics that can be collected form customers those are using products of CPS.
There are certain issues which is associated with the management of CPS.
Research hypothesis:
It is a formal statement of expected relationships among more than two variables under a
given case. This would assist in translating research issues and objectives into a simple
prediction of expected outcomes (Anderson and et. al., (2018). Mainly two types of research
hypothesis are being used. Such as:
 Null Hypothesis (H o): It is statistical hypothesis which is used for interpretation of
numerical outcomes. There are significance impacts on the independent factors on the
dependent factors.
 Alternative Hypothesis(H1): There is no any significant impacts on the independent
factors on the dependent factors (Sheth, (2011).
Customers characteristics:
There are five main characteristics of analysing responding company that would reflect
main aspects of customers. This would consist of some specific variables those are being
associated with the company. The total duration of time a particular customer has been buying
production from CPS are analyse accordingly (Moutinho and Hutcheson, (2011). Type of client, their
size based on total number of employees and customer region from where they used to purchase
products.
Statistics
Q3 - Customer
Size
Q9 - Complaint
Resolution
ID Q2 - Customer
Type
N Valid 200 200 200 200
Missing 0 0 0 0
Mean .51 5.367 100.50 .50
5

Median 1.00 5.400 100.50 .50
Mode 1 5.8 1a 0a
Std. Deviation .501 1.2100 57.879 .501
Variance .251 1.464 3350.000 .251
Sum 102 1073.5 20100 100
Percentiles
25 .00 4.500 50.25 .00
50 1.00 5.400 100.50 .50
75 1.00 6.200 150.75 1.00
a. Multiple modes exist. The smallest value is shown
Q3 - Customer Size
Frequency Percent Valid Percent Cumulative
Percent
Valid
Small (0 to 499) 98 49.0 49.0 49.0
Large (500+) 102 51.0 51.0 100.0
Total 200 100.0 100.0
Q2 - Customer Type
Frequency Percent Valid Percent Cumulative
Percent
Valid
Magazine 100 50.0 50.0 50.0
Books 100 50.0 50.0 100.0
Total 200 100.0 100.0
The above analyse is based on customer characteristic those are regularly buying the
products of CPS company. Customer size is in small range are having 49 % and from large
100%. Whereas type of customers is collected 50% from magazine and 100% out of books.
Variables Entered/Removed
Model Variables Entered Variables
Removed
Method
6

1
Q8 - Technical
Support, Q13 -
Competitive
Pricing, Q9 -
Complaint
Resolution, Q19 -
Satisfaction, Q14
- Warranty &
Claims
. Enter
a. Dependent Variable: Q6 - Product Quality
b. All requested variables entered.
Model Summary
Model R
R
Square
Adjusted
R
Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change F Change df1 df2
Sig. F
Change
1 .655a .429 .414 1.0584 .429 29.154 5 194 .000
a. Predictors: (Constant), Q8 - Technical Support, Q13 - Competitive Pricing, Q9 - Complaint Resolution, Q19 -
Satisfaction, Q14 - Warranty & Claims
At 95% significant level there is not any changes seen over the depended factors. It
means the null hypothesis will be rejected.
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 163.301 5 32.660 29.154 .000b
Residual 217.332 194 1.120
Total 380.633 199
a. Dependent Variable: Q6 - Product Quality
b. Predictors: (Constant), Q8 - Technical Support, Q13 - Competitive Pricing, Q9 - Complaint Resolution,
Q19 - Satisfaction, Q14 - Warranty & Claims
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
95.0%
Confidence
Interval for B
B
Std.
Error Beta
Lower
Bound
Upper
Bound
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1 (Constant) 7.040 .831 8.475 .000 5.402 8.679
Q19 -
Satisfaction
.698 .081 .626 8.658 .000 .539 .857
Q14 -
Warranty &
Claims
-.064 .160 -.040 -.397 .692 -.379 .252
Q13 -
Competitive
Pricing
-.260 .050 -.297 -5.210 .000 -.358 -.162
Q9 -
Complaint
Resolution
-.345 .078 -.302 -4.429 .000 -.499 -.192
Q8 -
Technical
Support
.010 .083 .012 .121 .904 -.154 .174
a. Dependent Variable: Q6 - Product Quality
RECOMMENDATION
After analysing various aspects of CPS company performance, it has been found that plenty
of customers those are less than 1 year of attachment with the company thinks that products of
CPS are not perfect. The results are also not able to delivery much effective results to the
researches. This would surely make company to think in order to control their losses by make
joint venture with the other paper industry which is having better market position. It has been
seen that there are two of the main variables such as independent and dependent variables. In a
research design, the most crucial disturbing variables which make impacts over the company are
have been controlled by using appropriate tools and techniques (Peterson and Kim, (2013).
This will make huge impacts on the CPS industry by considering discerned sectors as
dummy variables in multiple regression analysis for total 200 research samples size. The overall
regression model, customer’s characteristics can easily be determining by using appropriate
evaluation of final outcomes collected during the research survey. Recognising the appropriate
research methods limitation that are embedded in this specific research which is being collected
as empirical evidence that lends to support both hypotheses.
It has been suggested that every aspect those are affecting the performance and profitability
of CPS business would need to be resolve by coordinating their operations with the other
company. Forecasting the future is much more difficult task as a researcher it is more predicated
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to attempt some predication regarding the CPS business operation. Price would be key part in
any business planning which would assists management to make their valuable contribution in
order to increase their market share as well as their future performances. Few crucial vital
recommendations that would be helpful the company to make their marketing strategies. For this
purpose, they need to do certain changes in the product quality and services. The customer
complain resolution should be done in more fast and effective manner. Maximum focus will be
given to advertising their products. This will lead to create better market position to attain future
aims and objectives (Delbufalo, (2012).
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REFERENCE
Books and Journals:
Dekker, R & et. al., (2013). Reverse logistics: quantitative models for closed-loop supply chains.
Springer Science & Business Media.
Tayur, S., Ganeshan, R., & Magazine, M. (Eds.). (2012). Quantitative models for supply chain
management (Vol. 17). Springer Science & Business Media.
Kotler, P. (2015). Framework for marketing management. Pearson Education India.
Anderson, D. R &. et. al., (2018). An Introduction to Management Science: Quantitative
Approach. Cengage learning.
Sheth, J. N. (Ed.). (2011). Models of buyer behavior: conceptual, quantitative, and empirical.
Marketing Classics Press.
Moutinho, L., & Hutcheson, G. D. (Eds.). (2011). The SAGE dictionary of quantitative
management research. Sage.
Peterson, R. A., & Kim, Y. (2013). On the relationship between coefficient alpha and composite
reliability. Journal of Applied Psychology, 98(1), 194.
Delbufalo, E. (2012). Outcomes of inter-organizational trust in supply chain relationships: a
systematic literature review and a meta-analysis of the empirical evidence. Supply Chain
Management: An International Journal, 17(4), 377-402.
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Appendix 1
Statistical analysis:
Statistics
Q3 - Customer
Size
Q9 - Complaint
Resolution
N Valid 200 200
Missing 0 0
Mean .51 5.367
Median 1.00 5.400
Mode 1 5.8
Std. Deviation .501 1.2100
Variance .251 1.464
Sum 102 1073.5
Q3 - Customer Size
Frequency Percent Valid Percent Cumulative
Percent
Valid
Small (0 to 499) 98 49.0 49.0 49.0
Large (500+) 102 51.0 51.0 100.0
Total 200 100.0 100.0
Q9 - Complaint Resolution
Frequency Percent Valid Percent Cumulative
Percent
Valid 1.5 1 .5 .5 .5
2.6 3 1.5 1.5 2.0
3.0 1 .5 .5 2.5
3.1 1 .5 .5 3.0
3.2 2 1.0 1.0 4.0
3.3 1 .5 .5 4.5
3.4 2 1.0 1.0 5.5
3.5 1 .5 .5 6.0
3.6 1 .5 .5 6.5
3.7 4 2.0 2.0 8.5
11

3.8 1 .5 .5 9.0
3.9 4 2.0 2.0 11.0
4.0 8 4.0 4.0 15.0
4.1 6 3.0 3.0 18.0
4.2 6 3.0 3.0 21.0
4.3 4 2.0 2.0 23.0
4.4 3 1.5 1.5 24.5
4.5 3 1.5 1.5 26.0
4.6 4 2.0 2.0 28.0
4.7 7 3.5 3.5 31.5
4.8 6 3.0 3.0 34.5
4.9 5 2.5 2.5 37.0
5.0 3 1.5 1.5 38.5
5.1 5 2.5 2.5 41.0
5.2 5 2.5 2.5 43.5
5.3 8 4.0 4.0 47.5
5.4 7 3.5 3.5 51.0
5.5 7 3.5 3.5 54.5
5.6 5 2.5 2.5 57.0
5.7 5 2.5 2.5 59.5
5.8 12 6.0 6.0 65.5
5.9 6 3.0 3.0 68.5
6.0 3 1.5 1.5 70.0
6.1 7 3.5 3.5 73.5
6.2 5 2.5 2.5 76.0
6.3 5 2.5 2.5 78.5
6.4 6 3.0 3.0 81.5
6.5 1 .5 .5 82.0
6.6 6 3.0 3.0 85.0
6.7 4 2.0 2.0 87.0
6.8 3 1.5 1.5 88.5
6.9 6 3.0 3.0 91.5
7.0 2 1.0 1.0 92.5
7.1 3 1.5 1.5 94.0
7.2 3 1.5 1.5 95.5
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7.3 1 .5 .5 96.0
7.4 1 .5 .5 96.5
7.5 1 .5 .5 97.0
7.6 1 .5 .5 97.5
7.7 1 .5 .5 98.0
7.8 2 1.0 1.0 99.0
8.3 1 .5 .5 99.5
8.7 1 .5 .5 100.0
Total 200 100.0 100.0
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