Cadbury Chocolate: A Detailed Market Analysis in Shanghai

This case study assesses the market trends associated with Cadbury chocolate in Shanghai, China, covering the period from 1997 to 2017. It highlights the growth of the Chinese chocolate market due to the increasing popularity of Western foods and modern expressions of affection. The study examines Cadbury's volume and price figures, employing regression analyses to evaluate the data and identify potential issues with Cadbury's performance. The analysis includes considerations of price inelasticity, trend analysis, and the impact of seasonal indices on sales volume. The study reveals that while the overall trend in chocolate volume has been increasing, the price has remained relatively stable. It also identifies key months for sales and assesses the statistical significance of different regression models. The study concludes with recommendations for Cadbury to manage identified shortcomings and improve its market performance in Shanghai. Desklib is your go-to platform for accessing similar case studies and solved assignments.

Shanghai Chocolate Brands 1
SHANGHAI CHOCOLATE BRANDS ANALYSIS: CADBURY
By (Name)
The Name of the Class (Course)
Professor (Tutor)
The Name of the School (University)
The City and State where it is located
The Date

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Executive Summary
This study assesses the market trend associated with Cadbury chocolate in Shanghai,
China. The chocolate market in china has realized considerable growth over the past three
decades due to the increasing popularity of western foods and modern techniques of showcasing
affection. The drastic increment of chocolate manufacturing companies like Cadbury in the
Chinese market has significantly reformed the economy and society of China. The study
examines Cadbury volume and price figures for between 1997 and 2017. Regression analyses are
performed according to seven questions that are meant to evaluate the Cadbury Chocolate data.
The results for each analysis are used to identify potential issues with Cadbury performance in
the Shanghai chocolate market. Recommendations were then developed for Cadbury to manage
the various shortcomings identified during the assessment process.
Table of Content

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Executive Summary.........................................................................................................................2
Table of Content..............................................................................................................................3
Introduction......................................................................................................................................4
Cadbury Chocolate Assessment......................................................................................................6
Question 1....................................................................................................................................6
Question 2....................................................................................................................................7
Question 3....................................................................................................................................9
Question 4..................................................................................................................................11
Question 5..................................................................................................................................12
Durbin Watson Test...................................................................................................................14
Final Model to Adopt.................................................................................................................15
Conclusion/Recommendations......................................................................................................16
References......................................................................................................................................18
Appendices....................................................................................................................................18
Refined Model...........................................................................................................................18
Shanghai Chocolate Brands Analysis: Cadbury

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Introduction
The number of chocolate consumers in the Asian market has increased over the last five
years according to a report filed by the Organization for Economic Co-operation and
Development (OCED). Cadbury is one of the largest manufacturers of chocolate products across
the world with considerable market share in Europe. According to the OCED report, China is
considered the fastest growing market on a global scale for consumer services and products. The
continuous development of the Shanghai market is attributed to considerable industrial output,
capital investment, and sizable imports and exports. The Chinese government has put in place
fair trading policies that make the chocolate market accessible to both large-scale and small-scale
companies. Moreover, the government has encouraged the formation of consolidations as a way
to increase effectiveness in productivity and improve market competitiveness (Allen 2010).
Historically, the Chinese market proved quite profitable and conducive for the five
largest chocolate manufacturers that entered the economy in the late 1980s. Chocolate was
viewed as a great and exotic foreign product; it was readily accepted and appreciated by
consumers whose inexperience allowed them to prescribe the small level of credibility and
appreciation for different chocolate brands (Allen 2010). As such, all chocolate companies
enjoyed success in the Chinese market because people were more interested in the product as
opposed to the quality and brand. The considerably low cost of chocolate production and high
retail price ensured that any interested companies with sufficient startup capital were able to gain
entry into the Chinese market. Competitive advantage was none existence since all the different
chocolate companies were basically under the mercy of the Chinese regulatory and mercurial
economic environment. The success of the major chocolate brands was however determined by
experience, leadership capability, and management skills. The approach that was used by either

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one of these companies influenced how they were able to adapt to the emerging Chinese market
(Squicciarini & Swinnen 2016).
Statistical techniques such as trend and predictive analysis can be used to understand the
multi-billion dollar Chinese chocolate market that is projected to realize excess of $5 billion by
the end of 2023. The driving force in the Chinese chocolate market is the continuously growing
demand for foreign brands. The expanding networks of e-commerce platforms have also
facilitated the growth in chocolate demand. The greatest challenge however for chocolate brands
like Cadbury is poor supply chain infrastructure across all cities of china including Shanghai.
According to research 32% of all Chinese people living in Shanghai prefer foreign chocolate
brands while only 22% of the remaining population is willing to consume local brands. The top
tiers in the chocolate production and distribution industry are Hershey, Nestle, Kraft Foods,
Ferrerro, and Mar Inc because they produce high quality products and are trusted by consumers.
The increased purchasing power of the Yuan has created a critical import of premium chocolate
brands. The overall consumption of chocolate in China is considerably low compared to that
western countries, Japan, and Korea. The overall growth in the Chinese population presents
incredible opportunities for chocolate manufacturers (Squicciarini & Swinnen 2016).
The most commonly consumed type of chocolate is molded chocolate; it accounts for
40% of all forms of chocolate consumed in China. Forecasts in chocolate consumption in the
foreseeable future predict that molded chocolate will still be the preferred type for most Chinese
people. In close contention for the top spot in consumer preference is box assorted chocolates.
Cadbury produces a considerable amount of box assortment chocolates which are normally in
high demand during the winter season. Box assortments are considerably low cost to produce

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because they combine different types of chocolates with varying taste (Squicciarini & Swinnen
2016).
Cadbury Chocolate Assessment
Question 1
From the chart on Cadbury volume (in tones) per year it is clear that between 1997 and
2017 the volume of chocolate distributed in Shanghai annually was between 6 and 10 tonnes.
Majority of the volume distributed by Cadbury between 1997 and 2007 was between 6 and 8
tonnes of chocolate. The period between 2007 and 2008 the lowest volume of Cadbury chocolate
rollout to the Shanghai market. The market them realizes an increment in overall volume of
chocolate produced between 2008 and 2017 with a majority of the annual volume being between
8 and 10 tonnes. The overall trend in the volume of chocolate realized into the Shanghai market
has being increasing steady between 1997 and 2017 with seasonal adjustments for increments
and decrements in demand for Cadbury chocolate. The price of 100g of Cadbury chocolate has
remained relatively the same ranging between 3 and 4 between the period 1997 and 2017.
Therefore, the average price of 100g of Cadbury chocolate is roughly 3.50. The fact that the
price of chocolate has remained relatively the small over a span of 20 years is an indication of
price inelasticity. This means that the price of 100g of Cadbury chocolate is not sensitive to the
volume of chocolate consumed in Shanghai between 1997 and 2017.

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1/1/1997
3/1/1998
5/1/1999
7/1/2000
9/1/2001
11/1/2002
1/1/2004
3/1/2005
5/1/2006
7/1/2007
9/1/2008
11/1/2009
1/1/2011
3/1/2012
5/1/2013
7/1/2014
9/1/2015
11/1/2016
0.00
2.00
4.00
6.00
8.00
10.00
12.00
Cadbury Volume (in Tonnes)
Volume (in Tonnes)
Quantity (in tonnes)
1/1/1997
2/1/1998
3/1/1999
4/1/2000
5/1/2001
6/1/2002
7/1/2003
8/1/2004
9/1/2005
10/1/2006
11/1/2007
12/1/2008
1/1/2010
2/1/2011
3/1/2012
4/1/2013
5/1/2014
6/1/2015
7/1/2016
8/1/2017
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
Cadbury Price per 100g
Price per 100g
pirce
Question 2
The regression model presented below where the trend is the independent variable and
the volume of Cadbury chocolate is the dependent variable is statistically significant based on p-
value acquired for the F statistic in the ANOVA table. According to the value of R squared it is
clear that only 32.9% of the change in the dependent variable can be explained by the
independent variable. This means that trend variable has a very small control over the volume of

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Cadbury chocolate distributed in the Shanghai market. This is in line with the results showcased
in the line chart for Cadbury Volume. From the graph it is clear that progression in time from
one month to the next (trend) has very little influence on the overall pattern of chocolate volume
in the Shanghai market. It is therefore correct to state that the regression model confirms the
behavior of Cadbury chocolate volume over the stipulated time interval of 20 years. The
regression model indicates that both coefficients are significant at an alpha level of 0.05. From
the model an increment in trend by one month will cause an increment in volume of Cadbury
chocolate by 0.005094 tonnes (Yan 2009). Lastly, when trend is equivalent to zero i.e. t=0, then
the amount of Cadbury chocolate volume is expected to be 7.193 tonnes. A scatter plot with
goodness of fit line is also provided to allow for a clear understand of the general trend in sales
movement with relation to time progressing from t=1,2…252.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.573649
R Square 0.329074
Adjusted R Square 0.32639
Standard Error 0.531187
Observations 252
ANOVA
df SS MS F Significance F
Regression 1 34.59819 34.59819 122.6192 1.88276E-23
Residual 250 70.53993 0.28216
Total 251 105.1381
CoefficientsStandard Error t Stat P-value Lower 95% Upper 95%Lower 95.0%Upper 95.0%
Intercept 7.193001 0.067123 107.1616 5.9E-211 7.060802585 7.3252 7.060803 7.3252
Trend 0.005094 0.00046 11.07335 1.88E-23 0.004187609 0.005999 0.004188 0.005999
Y=7.193001+0.005094(T)

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0 50 100 150 200 250 300
0.00
2.00
4.00
6.00
8.00
10.00
12.00
f(x) = 0.005093542386074 x + 7.19300113419339
R² = 0.329073695909975
Cadbury Volume
Cadbury Volume
Linear (Cadbury Volume)
Question 3
There are only three months in the year that recorded above average sales volume for
Cadbury chocolate. These three months in order of largest to smallest sales volume are
December, April, and May. The reason of the elevated sales figures in these periods of the year
can be attributed to special occasions and events celebrated in Shanghai china. Cold and rainy
season are commonly associated with higher chocolate consumption according to researcher; for
example December is one of the coldest months in the year in China.

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Row Labels Average of Volume in Tonnes (Y) SI
Jan 7.809294286 99.64223
Feb 7.785166667 99.33437
Mar 7.733938571 98.68073
Apr 8.14674619 103.9479
May 7.845840476 100.1085
Jun 7.685702381 98.06526
Jul 7.753168571 98.92609
Aug 7.422657143 94.70895
Sep 7.617944762 97.20071
Oct 7.60966619 97.09508
Nov 7.777627619 99.23818
Dec 8.860258095 113.0519
Grand Total 7.837334246
The regression model below has two independent variables Trend (T) and Seasonal Index
(SI). The addition of the extra variable has made the model more reliable because 61.12% of the
change in the dependent variable (sales volume of Cadbury chocolate) can be explained by the
independent variables (Sarstedt & Mooi 2014). By adding the seasonal index variable to the
previous model the applicability and reliability of the regression model has been increased
considerable. As a result, this new model is more appropriate to use compared to the previous
model generated in question 2. It is however, important to note that in this model the Y-intercept
is not statistically significant at an alpha level of 0.05. Due to this simple and critical issue one
would forego this model because it proposes that the inclusion of B0 (Y-intercept) in the model
is unnecessary. Nevertheless, the model is correct in assuming that B0 is irrelevant because the
sales volume of Cadbury chocolate can never be negative at T=0 and SI=0 (Seber & Lee 2012).

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SUMMARY OUTPUT
Regression Statistics
Multiple R 0.783747
R Square 0.61426
Adjusted R Square 0.611161
Standard Error 0.403579
Observations 252
ANOVA
df SS MS F Significance F
Regression 2 64.58209 32.29105 198.2559 3.12E-52
Residual 249 40.55603 0.162876
Total 251 105.1381
CoefficientsStandard Error t Stat P-value Lower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept -0.5461 0.572668 -0.9536 0.341211 -1.67399 0.581794 -1.67399 0.581794
Trend (X1) 0.005041 0.00035 14.42288 1.09E-34 0.004352 0.005729 0.004352 0.005729
Seasonal Index (X2) 0.077458 0.005709 13.56801 9.11E-32 0.066214 0.088701 0.066214 0.088701
Y=0.005041(T)+0.077458(SI)-0.5461
Question 4
In this regression model there are three independent variables and a single dependent
variable. One of the three independent variables is a dummy variable that assumes a value of 1
for periods when “Whooping Cow Disease” was observed and a value of 0 if the disease was not
recorded amongst daily cattle. The addition of the dummy variable has increased the reliability
and dependability of the model since 70.85% of the change in dependent variable can be
explained by the independent variables. All the coefficients are significant at alpha=0.05 expect
for the Y-intercept (B0) (Montgomery, Peck & Vining 2015). Nevertheless, the overall model is
significant and therefore, it would be more preferable in prediction analysis compared to the
model obtained in question 3. However, due to the fact that it has a coefficient that is

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insignificant at alpha= 5% it is less preferable when compared to the model generated in question
2. It is clear that the present of the disease in the daily cattle will cause a decrement in Sales
volume for Cadbury chocolate by 0.9481 tonnes.
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.843784
R Square 0.711972
Adjusted R Square 0.708488
Standard Error 0.349439
Observations 252
ANOVA
df SS MS F Significance F
Regression 3 74.85541 24.9518 204.3426 9.9377E-67
Residual 248 30.28271 0.122108
Total 251 105.1381
CoefficientsStandard Error t Stat P-value Lower 95% Upper 95%Lower 95.0%Upper 95.0%
Intercept -0.50095 0.49587 -1.01024 0.313364 -1.4776031 0.475705 -1.4776 0.475705
Trend (X1) 0.005041 0.000303 16.65745 2.54E-42 0.00444478 0.005637 0.004445 0.005637
Seasonal Index (X2) 0.077458 0.004943 15.67013 6.21E-39 0.06772205 0.087193 0.067722 0.087193
Disease (X3) -0.94811 0.103365 -9.17242 1.85E-17 -1.1516977 -0.74453 -1.1517 -0.74453
Y=0.005041(T)+0.077458(SI)-0.94811(D)-0.50095
Question 5
This final regression model is statistically significant and has 13 independent variables;
where 10 of those independent variables are price variables for Cadbury and competitor
chocolate and ice cream brands. The new model has higher level of dependability and reliability
compared to the previous three models (Golberg & Cho 2010). 79.07% of the change in the
dependent variable can be explained by the independent variables. In this model like in the