Quantitative Analysis for Business: Expansion Location Analysis Report

This report presents a quantitative analysis focused on identifying the best locations for a business firm's expansion, considering economic factors such as inflation rates and purchasing power parity (PPP). The study utilizes secondary data from sources like the World Bank and OECD, employing statistical tools like mean, median, and standard deviation to analyze the data. The analysis compares PPP and inflation rates across multiple nations, including Finland, France, Hungary, Israel, Italy, and Slovenia. The findings reveal that Hungary, Israel, and Finland are the most favorable locations due to their higher PPP and, in the case of Hungary, a lower inflation rate. The report recommends these locations based on the assumption that the economic conditions within a nation are consistent across its cities, supporting the inference of sample data to other cities within the same country. The report concludes that economic data is crucial for business expansion, influencing investment decisions and ensuring market viability.

QUANTATIVE ANALYSIS FOR
BUSINESS

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................1
Strategies for gathering sample data............................................................................................1
Analysis of data...............................................................................................................................2
Recommendation.............................................................................................................................8
CONCLUSION................................................................................................................................9
Figure 1Mean value of PPP across all nations.................................................................................4
Figure 2Mean value of countries other then Hungary and Israel....................................................4
Figure 3Standard deviation of all nations........................................................................................5
Figure 4Standard deviation of nations other then Hungrary and Israel...........................................5
Figure 5Mean value of inflation rate across nations........................................................................7
Figure 6Standard deviation of nations inflation rate.......................................................................7
Table 1Analysis of data...................................................................................................................2
Table 2Inflation rate table across nations........................................................................................6

INTRODUCTION
Economy is one of the factor that people give due importance while selecting best location for commencing their business
operations. In the current report, detailed statistical analysis of inflation rate and purchase power parity is done. In this regard one of
the common tools of central tendency which are mean, median and mode are applied on data and results of same are interpreted in
systematic manner. On the basis of analysis of data results are obtained and recommendation is made at end of the report. In this way
by following systematic approach best option is selected for the business firm.
Strategies for gathering sample data
As per given case business firm wants to expand its business in three cities that are located in different nations of the world.
Main aim of the present research study is to identify best locations where firm can commence its operations. In the current report, by
using concept of purchase power parity best alternative is identified. In the present research study, secondary data will be collected
from different sources which may be World Bank website or any other website. Data related to purchase power parity will be used for
analysis purpose (Lee, Pham and Gu, 2013). This is because purchase power parity concept reflects the price that one have to pay for
purchasing same number of items across two nations in common currency like USD. By comparing purchase power parity of cities it
can be identified that in which cities cost of living is high. If in any city cost of living is high then in that case it is possible that
demand of the product may be less. From OECD website entire data will be gathered. It must be noted that OECD refers to
Organization for economic cooperation and development. Data related to inflation rate will also be collected from OECD website and
by applying excel software same will be analyzed in proper manner.
It is very important to determine quality of data before it is taken for analysis. This is because in data set there are lots of things
that are covered and all of them cannot be used for analysis purpose. Hence, it is important to determine quality of data. In the data set
that is downloaded from OECD some of the variables will be removed like year, indicators, subject and measure as well as frequency.
In order to structure inflation rate data some variables will be removed like year, indicator, subject and measurement. After
determining quality of data same will be used for analysis purpose.
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Structure of data needs to be determined before it is taken for analysis purpose. More data is well structured, analysis can be
done easily in effective manner. It can be observed that variables that one wants to analyze in data must be aligned to each other.
Thus, structure that is in data sheet is modified and in excel sheet only PPP and nation name is taken in to account. Plan for collection
of data and its implementation is given below.
Plan and its implementation Details
Collection of secondary data on purchase
power parity
Secondary data will be collected from OECD
website as mentioned above.
Gathering secondary data on inflation rate. Secondary data will be collected from OECD
website.
Analysis of data Excel software will be used for analysis of
data.
Charting of data Charts will be prepared in the report to give
visual presentation to facts.
Conclusion and recommendation In order to finally execute project conclusion
section will be prepared under which same
will be formed on the basis of results of
analysis of data.
Analysis of data
Table 1Analysis of data
Year Nation PPP Nation PPP Nation PPP Nation PPP Nation PPP Nation PPP
2008 FIN 0.912125 FRA
0.88187
4 HUN 131.0054 ISL 114.527 ITA
0.78369
4 SVN 0.633789
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2009 FIN 0.895402 FRA
0.86190
8 HUN 127.5337 ISL 121.8263 ITA
0.77037
6 SVN 0.644683
2010 FIN 0.89881 FRA
0.85305
1 HUN 126.1768 ISL 132.6351 ITA
0.77169
8 SVN 0.63672
2011 FIN 0.898068 FRA
0.84136
1 HUN 124.2718 ISL 135.152 ITA
0.75868
7 SVN 0.62397
2012 FIN 0.908495 FRA
0.84430
1 HUN 125.6236 ISL 136.9677 ITA
0.74773
1 SVN 0.606793
2013 FIN 0.905357 FRA
0.81164
3 HUN 124.9794 ISL 137.0226 ITA
0.73729
9 SVN 0.590407
2014 FIN 0.906302 FRA
0.80496
2 HUN 128.8078 ISL 138.3401 ITA
0.73509
4 SVN 0.584135
2015 FIN 0.904435 FRA 0.79981 HUN 130.6587 ISL 140.339 ITA
0.72725
7 SVN 0.584748
2016 FIN 0.904823 FRA
0.80350
1 HUN 133.6346 ISL 140.9739 ITA
0.72319
8 SVN 0.585688
Mean 0.903757
0.83360
1 128.0769 133.0871
0.75055
9 0.610104
Median 0.904823
0.84136
1 127.5337 136.9677
0.74773
1 0.606793
Mode #N/A #N/A #N/A #N/A #N/A #N/A
STDEV 0.005359
0.02965
4 3.175307 9.004746
0.02155
9 0.024924
Interpretation
On analysis of data it can be observed that mean value of purchase power parity in case of Finland is 0.90 and standard
deviation is only 0.005 followed by same for France is 0.83 and standard deviation is 0.02. It can be said that purchase power parity of
France is fluctuating at fast rate then Finland. Moreover, PPP in case of Finland is higher than France. Island and Hungary purchase
power parity is much higher than Italy and Slovenia. It can be observed that PPP value in case of Hungary is 128 and same for Israel is
133. Standard deviation for Hungary is 3.17 and same for Israel is 9.00 (Purchasing power parities, 2017). This reflects that purchase
power parity deviate at fast rate in Israel then Hungary. Mean value of Italy is 0.75 and same for Slovenia is very low 0.61. It can be
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said that purchase power parity in case of Slovenia is lower than Italy. Standard deviation value is slightly different in case of both
nations. It can be observed that in case of Italy standard deviation valued at 0.021 and same for Slovenia is 0.024. This reflects that
mean value is different in case of both nations but rate of fluctuation is same. Hence, it can be said that purchase power parity value is
high in case of Hungary and Island then other nations that are in the table given above. All these facts can be seen from charts given
below.
FIN FRA HUN ISL ITA SVN
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
0.90 0.83
128.08 133.09
0.75 0.61
Mean
Figure 1Mean value of PPP across all nations
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FIN FRA ITA SVN
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00 0.90
0.83
0.75
0.61
Mean
Figure 2mean value of countries other than Hungary and Israel
FIN FRA HUN ISL ITA SVN
0.00
2.00
4.00
6.00
8.00
10.00
0.01 0.03
3.18
9.00
0.02 0.02
STDEV
Figure 3Standard deviation of all nations
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FIN FRA ITA SVN
0.00
0.01
0.02
0.03
0.04
0.01
0.03
0.02
0.02
STDEV
Figure 4Standard deviation of nations other than Hungary and Israel
All these images are clearly reflecting that apart from Hungary and Israel standard deviation is high in case of Finland.
Table 2Inflation rate table across nations
2008 FIN
98.5483
8 FRA 103.9245 HUN
87.8749
2 ISL
80.0671
5 ITA
105.069
8 SVN
91.5670
2
2009 FIN
90.3777
8 FRA 91.00896 HUN
90.2690
8 ISL
86.5974
7 ITA
96.4671
2 SVN 88.3737
2010 FIN 100 FRA 100 HUN 100 ISL 100 ITA 100 SVN 100
2011 FIN
114.584
5 FRA 112.61 HUN
109.005
5 ISL
117.064
7 ITA
111.316
3 SVN
108.426
5
2012 FIN
119.268
3 FRA 118.3885 HUN
118.493
6 ISL
127.296
9 ITA
127.161
3 SVN
117.503
9
2013 FIN
118.643
2 FRA 119.2559 HUN 112.031 ISL
127.418
5 ITA
126.692
6 SVN
120.093
3
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2014 FIN
116.584
7 FRA 117.4947 HUN
104.386
1 ISL
125.700
6 ITA
122.948
1 SVN
118.400
5
2015 FIN
109.567
2 FRA 111.8966 HUN
96.4673
2 ISL
118.756
8 ITA
114.346
6 SVN
110.463
7
2016 FIN
105.494
9 FRA 108.7996 HUN
92.8358
3 ISL
115.345
1 ITA
108.186
2 SVN
105.344
6
Mean
108.118
8 109.2643
101.262
6
110.916
4
112.465
3
106.685
9
Median
109.567
2 111.8966 100
117.064
7
111.316
3
108.426
5
Mode #N/A #N/A #N/A #N/A #N/A #N/A
STDEV
10.1844
6 9.46546
10.4777
2
17.8197
7
11.2775
6 11.5203
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FIN FRA HUN ISL ITA SVN
94
96
98
100
102
104
106
108
110
112
114
108 109
101
111 112
107
Mean
Figure 5Mean value of inflation rate across nations
FIN FRA HUN ISL ITA SVN
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
10.18 9.47 10.48
17.82
11.28 11.52
STDEV
Figure 6Standard deviation of nation’s inflation rate
Interpretation
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Facts are clearly indicating that inflation rate is low in case of Hungary relative to other nations of the world. Same for Finland
is 108, France 109, Israel is 111. For Italy inflation rate is 112 and same for Slovenia is 107. It can be said that inflation rate is much
higher in Italy and France as well as Finland. Standard deviation is high in case of Israel which is 17.82 followed by 11.28 in case of
Italy, 11.52 in case of Slovenia (Inflation, 2017). Inflation rate is very low in case of France which is 9.47. It can be said that there is
high fluctuation in inflation rate in the nations like Israel, Italy and Slovenia.
Recommendation
On the basis of analysis of figures it is recommended that firm must commence its operations in cities that are located in
Hungary, Israel and Finland. This is because purchase power parity is high in these nations in comparison to other nations that are
analyzed in present study. There is high purchase power parity which means that purchasing power of people living in these cities
located in these nations is also high. This signaled that there may be huge consumption of fuel cell technology machines and oil.
While selecting any city for business it is also very important to consider inflation rate. It can be observed that inflation rate is very
low in city of Hungary and due to this reason it is one of the preferred choice for investment purpose ( Stern, 2010). However, in case
of Israel inflation rate is high and in Finland it is at moderate level in comparison to other nations. It can be said that high inflation rate
in Israel may be matter of concern but purchasing power is also high in the mentioned nation and due to this reason it cannot be
ignored as available option. In case of city of Finland there is moderate inflation rate and due to this reason it is taken as third best
choice for opening a business. Remaining locations cannot be taken as preferred choice because purchasing power of people in
relevant cities is very low and inflation rate is high. Thus, already purchasing capacity is less and high inflation rate will mount
pressure on people and due to this reason situation will be out of control. Thus, if firm launch its product in the market then in that
case may face huge loss in the business because people will have less spending capacity and due to high inflation rate their spending
on relevant product will further decline. Due to all these reasons cities located in Hungary, Israel and Finland are selected as best
alternatives for opening of new business.
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Results of sample data can be inferred to all cites of specific nation because all cities are operating in similar economic
environment and due to this reason big difference cannot be observed in purchasing power of the people. It must be noted that people
receive compensation according to cost of living of city. Hence, big variation does not come across people spending capacity in cities
that are located in same nation. Thus, it can be said that results that are obtained on single city can be obtained in other cities of same
nation. Hence, it can be assumed that sample data can be inferred to all cities that are located in specific nation.
CONCLUSION
On the basis of above discussion it is concluded that there is significant importance of the economic data for the business
firms. This is because when firm intends to open business in any nation it is very important for it to ensure that there are ample
opportunities in same and people will be prepared to make purchase. Thus, it is necessary to gather data related to economy of nation
in relation to purchase power parity and inflation rate etc. It is also concluded that while preparing business expansion policy it is very
important to evaluate number of nations and specific one must be picked up to ensure that country which is selected is best place to do
business.
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