(Tiểu luận) end module assignmentmodule using data to build business the kentucky milk case

The line chart below shows the districts and the same vendors in the surrounding market and tri-county market in the same period from 1983 to 1991 6Figure 3.1 The bar graph shows the sta

UNIVERSITY OF BEDFORDSHIRE FOREIGN TRADE UNIVERSITY

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-*** -END-MODULE ASSIGNMENT

Module: Using Data to Build Business

Code: BSS004-1.S2 THE KENTUCKY MILK CASE

Student: NGUYỄN THỊ KHÁNH VÂN

Student ID: 2145519082

Cohort: K60BF-C

Semester: II

Academic year: 2022-2023

Headteacher: Nguyen Thu Hang

Submission date: 19th July 2023

Student’s signature:

Nguyễn Thị Khánh Vân

FOR EXAMINERS ONLY

Grade (in number):

………

Grade (in words):

………

Examiner 1

(Signature & Fullname)

………

Examiner 2

(Signature & Fullname)

………

Ho Chi Minh City, July 2023

UNIVERSITY OF BEDFORDSHIRE FOREIGN TRADE UNIVERSITY

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-*** -END-MODULE ASSIGNMENT

Module: Using Data to Build Business

Code: BSS004-1.S2 THE KENTUCKY MILK CASE

Student’s fullname: NGUYỄN THỊ KHÁNH VÂN Student ID: 2145519082

Cohort: K60BF-C

Lecturer: Assoc Prof Dr Nguyen Thu Hang

Ho Chi Minh City, July 2023

STATEMENT OF AUTHORSHIP

Except where reference is made in the text of the end-module assignment, this assignment contains no material published elsewhere or extracted in whole or in part from an assignment which I have submitted or qualified for or been awarded another degree or diploma

No other person’s work has been used without due acknowledgements in the end-module assignment

This end-module assignment has not been submitted for the eveluation of any other modules or the award of any degree or diploma in other tertiary institutions

Ho Chi Minh City, 19th July 2022

Nguyen Thi Khanh Van

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TABLE OF CONTENTS

STATEMENT OF AUTHORSHIP 1

LIST OF ABBREVIATIONS 3

LIST OF TABLES 3

LIST OF FIGURES 3

INTRODUCTION 4

CHAPTER 1 MARKET SHARE 5

CHAPTER 2 INCUMBENCY RATES 6

CHAPTER 3 BID LEVELS AND DISPERSION 7

CHAPTER 4 PRICE VERSUS COST/ DISTANCE 9

CHAPTER 5 BID SEQUENCE 10

CHAPTER 6 COMPARISON OF AVERAGE WINNING BID PRICES 12

CONCLUSION 14

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LIST OF ABBREVIATIONS

Abbreviation Meaning

WWBID Winning bid price of whole white milk

LFWBID Winning bid price of low-fat white milk

LFCBID Winning bid price of low-fat chocolate milk

LIST OF TABLES

Table 1 Data of Trauth and Meyer in tri-county market 5

Table 2 Data of districts and the same vendors 6

Table 3.Standard deviation of WWBID of Trauth and Meyer 7

Table 4 Correlation of three milk 9

Table 6 Comparison of the mean of winning bid prices……….………12

LIST OF FIGURES Name of figures Page Figure 1 The box and whisker chart below shows the data about Trauth and Meyer in Tri-county by using “Market share” 5

Figure 1 The line chart below shows the districts and the same vendors in the surrounding market and tri-county market in the same period from 1983 to 1991 6 Figure 3.1 The bar graph shows the standard deviation of WWBID of Trauth and Meyer during the time from 1983 to 1991 7

Figure 3.2 The bar graph shows the standard deviation of LFWBID of Trauth and Meyer during the time from 1983 to 1991 8

Figure 3.3 The bar graph shows the standard deviation of LFCBID of Trauth and Meyer during the time from 1983 to 1991 9

Figure 4 The bar chart shows the price versus cost/ distance of three milk in tri-county market and surrounding market 10

Figure 5.1 The bid sequence of WWBID 11

Figure 5.2 The bid sequence of LFWBID 11

Figure 5.3 The bid sequence of LFCBID 12

Figure 6 The bar chart shows the average winning bid price for three milk from 1983 to 1991 13

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In business, to be able to make an important decision affecting the development and operation

of a company, it must be based on actual data related to that company, then calculate and analyze a reasonable way to draw conclusions In addition, data analysis is also used in many other fields of work, carrying many great responsibilities, which can affect the whole economy and the development of a country

There are many types of data for us to analyze and learn, but in this report, I will analyze The Kentucky Milk Case's data on this report about milk companies' collusion with the government to supply milk to schools in the Kentucky area

Based on background information These are some basic features that show the environmrent may be collusion :

1 Few sellers and high concentration Only a few day-ies control all or nearlv all of the milk business in the market

2 Homogeneous products The products sold are

es-sentially the same from the standpoint of the buyer (i.e., the school district)

3 Inelastic demand Demand is relatively insensitive to price (Note: The quantity of milk required by a school district is preeminent determined by school

enrollment, not price.)

4 Similar costs The dairies bidding for the milk contracts face similar cost conditions (Noie: Approximately 60% of a dairy's production cost is raw milk, which is federally regulated Meyer and Trauth are dairies of similar size, and both bought their raw milk from the same supplier.)

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CHAPTER 1 MARKET SHARE

Table 1 Data of Trauth and Meyer in tri-county market

Figure 1 The box and whisker chart below shows the data about Trauth and Meyer in Tri-county by using

“Market share”.

According to the "market share" method, we divide the total number of half-pints supplied to the market by the number of milk half-pints purchased by the dairy through an entire school year This approach reveals the proof of collusion showing nearly equal market shares over time for the analyzed dairies

The previously mentioned indicators indicate that the data of Trauth and Meyer are similar between the years of 1983 and 1991 Meyer will decrease while Trauth's data rises, and vice versa We can see from the horizontal axis of the graph above that Trauth and Meyer planned

so they could alternate getting milk supplies for the tri-county market's schools

In summary, using the "market share" method, we are able to quickly analyze the data and determine how Trauth and Meyer differ in order to make comparisons between the two

values In conclusion, using the "market share" method, it is simple to look into the data and determine between Trauth and Meyer in order to make comparisons between the two values above

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CHAPTER 2 INCUMBENCY RATES

Table 2 Data of districts and the same vendors

Figure 2 The line chart below shows the districts and the same vendors in the surrounding market and tri-county market in the same period from 1983 to 1991

"Incumbency rates" is the next method that is helpful in our examination of the level competition or shortage of The fact that the same dairy supplier controls the same school systems year after year is a telling evidence of the "incumbency rate" approach If the percentage of education organizations gained by the same vendor as the previous year reaches 70%, then collusive behavior may have taken place

Using the aforementioned methodology, we can observe that the tri-county market consistently achieved 70%, whilst the surrounding area's incumbency rates only did so once

in 1986 Except for 1988, the tri-county reached exactly 70% over the years 1983 to 1991 Thus, we can clearly see that the tri-county market was open to bids during the period from

1983 to 1991

6

CHAPTER 3 BID LEVELS AND DISPERSION

Normally, when bidding, bidders are not allowed to disclose their prices to other investors to show fairness But when bidding, vendors communicate about their bids and tend to submit bids in close proximity to one another in an attempt to make the bidding appear competitive The telltale sign of bids is when bids are submitted at relatively high more than the bids which are submitted at or near marginal cost

1983 1984 1985 1986 1987 1988 1989 1990 1991 TRI-COUNTY 0,012 0,006 0,005 0,005 0,007 0,006 0,008 0,006 0,006 SURROUND 0,016 0,015 0,015 0,012 0,012 0,013 0,007 0,010 0,007

1983 1984 1985 1986 1987 1988 1989 1990 1991 TRI-COUNTY 0,014 0,005 0,005 0,004 0,005 0,005 0,009 0,004 0,005 SURROUND 0,014 0,014 0,013 0,011 0,010 0,011 0,008 0,008 0,007

Figure 3.1 The bar graph shows the standard deviation of WWBID of Trauth and Meyer during the time from

1983 to 1991.

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the above argument and data analysis, we see that the winning bid of three milk is Trauth and Meyer in both tri-county and surrounding market in each year.Based on

Table 3.Standard deviation of WWBID of Trauth and Meyer

Table 3.2 Standard deviation of LFWBID

Figure 3.2 The bar graph shows the standard deviation of LFWBID of Trauth and Meyer during the time from 1983 to 1991

1983 1984 1985 1986 1987 1988 1989 1990 1991 TRI-COUNTY 0 0,00779 0,01 0,01 0,01 0 0,01 0 0,01 SURROUND 0,02 0,0153 0,02 0,01 0,01 0,01 0,01 0,01 0,01

Based on the signal of communication we can see that the winning bids and dispersions of three milk do not have the same pattern in surrounding and tri-county market In addition, the

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Table 3.3 Standard diviation of LFCBID

Figure 3.3 The bar graph shows the standard deviation of LFCBID of Trauth and Meyer during the time from 1983 to 1991

surrounding market data shows extremely uniformity in the first years from 1984 to 1988 and this number is always larger than the tri-county data

From this, it can be seen that Trauth and Meyer approved the bids for the three types of milk

in the tri-county and surrounding market

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CHAPTER 4 PRICE VERSUS COST/ DISTANCE

Usually, when bidding, the bid price of milk should be highly correlated with the raw milk cost If lack of a relationship between bid price of milk and the raw milk cost, there will be a collusion

Table 4 Correlation of three milk

As clearly seen from the bar chart, the tri-county market shows a very low than the figures of surrounding market So, the bid price did not correlate to the raw milk While in the

9 Figure 4 The bar chart shows the price versus cost/ distance of three milk in tri-county market and surrounding market

surrounding market, based on raw milk costs and distance, the milk price when the bidding was much higher than in the tri-county market, which is a suitable price for investors to compete with together But in tri-county it is the opposite, the same price of raw milk but investors forced the price to the lowest possible level to be able to win the bid

In conclusion, the bid prices in tri-county did not increase as normal so there have a collusion the bid prices with the price of raw milk in tri-county

***

CHAPTER 5 BID SEQUENCE

If the bid prices are constant or slightly increasing patterns of sequential bids in a market where a single dairy wins year by year is considered another indication of collusive behavior The line chart below shows the price patterns of sequential bids in three types of milk

10 Figure 5.1 The bid sequence of WWBID

Figure 5.2 The bid sequence of LFWBID

Based on the chart above, we can plot and compare the bidding of dairy in tri-county market and surrounding market from 1983 to 1991 Based on the chart, the bid prices of types of milk in tri-county market was slightly rose while the figure for surrounding market was a sharply fluctuated As a result, there is a sign of collusion

11 Figure 5.3 The bid sequence of LFCBID

CHAPTER 6 COMPARISON OF AVERAGE WINNING BID PRICES

The theory given that winning prices in the “rigged” will be significantly higher than the mean price in competitive market for each year

WWBID LFWBID LFCBID SURROUND 0,1359 0,1280 0,1283 TRI-COUNTY 0,1370 0,1301 0,1309

Thanks to the theory and bar chart, we can obviously see that the mean of winning bid prices for tri-county market in three milk are always higher than the same figure in surrounding market Thus, tri-county market obviously a rigged market

12

Table 6 Comparison of the mean of winning bid prices

Figure 6 The bar chart shows the average winning bid price for three milk from 1983 to 1991

13

After finishing this course and this report, I was able to know more knowledge about data processing It sounds strange, but in every aspect of our lives, we also need to use data to be able to make a decision, the most accurate answer for a certain task that we need to solve

Thanks to the formulas, data processing cases that I have learned, I was able to solve the problems posed in The Kentucky Milk Case, from which I was able to draw conclusions about the information contractor and understand what is bid communication, how to process data to find out the phenomenon of bid collusion, etc

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