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 SCHOOL OF BUSINESS HO CHI MINH CITY CAMPUS -*** - *** END-MODULE ASSIGNMENT Module: Using Data to Build Business Code: BSS004-1.S2 THE KENTUCKY MILK CASE Student: NGUYỄN THỊ KHÁNH VÂN FOR EXAMINERS ONLY Grade (in number): Student ID: 2145519082 ……………… Cohort: K60BF-C Grade (in words): Semester: II ……………… Academic year: 2022-2023 Headteacher: Nguyen Thu Hang Examiner Submission date: 19th July 2023 (Signature & Fullname) ……………… Student’s signature: Examiner (Signature & Fullname) Nguyễn Thị Khánh Vân ……………… Ho Chi Minh City, July 2023 UNIVERSITY OF BEDFORDSHIRE FOREIGN TRADE UNIVERSITY SCHOOL OF BUSINESS HO CHI MINH CITY CAMPUS -*** - *** 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 Semester: II Academic year: 2022-2023 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 endmodule 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 TABLE OF CONTENTS STATEMENT OF AUTHORSHIP LIST OF ABBREVIATIONS LIST OF TABLES LIST OF FIGURES INTRODUCTION CHAPTER MARKET SHARE CHAPTER INCUMBENCY RATES CHAPTER BID LEVELS AND DISPERSION CHAPTER PRICE VERSUS COST/ DISTANCE CHAPTER BID SEQUENCE 10 CHAPTER COMPARISON OF AVERAGE WINNING BID PRICES 12 CONCLUSION 14 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 Name of table Page Table Data of Trauth and Meyer in tri-county market Table Data of districts and the same vendors .6 Table 3.Standard deviation of WWBID of Trauth and Meyer Table Correlation of three milk Table Comparison of the mean of winning bid prices……………………….……………12 LIST OF FIGURES Name of figures Page Figure The box and whisker chart below shows the data about Trauth and Meyer in Tricounty by using “Market share” Figure 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 Figure 3.1 The bar graph shows the standard deviation of WWBID of Trauth and Meyer during the time from 1983 to 1991 Figure 3.2 The bar graph shows the standard deviation of LFWBID of Trauth and Meyer during the time from 1983 to 1991 Figure 3.3 The bar graph shows the standard deviation of LFCBID of Trauth and Meyer during the time from 1983 to 1991 Figure 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 The bar chart shows the average winning bid price for three milk from 1983 to 1991 13 INTRODUCTION 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 : Few sellers and high concentration Only a few day-ies control all or nearlv all of the milk business in the market Homogeneous products The products sold are essentially the same from the standpoint of the buyer (i.e., the school district) 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.) 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.) Document continues below Discover more Using data to from: build pratice Trường Đại học… 119 documents Go to course Ftubanedited-2 - 15 cuối kì Using data to build pratice None Anh Prism - Tai lieu thuc hanh tieng anh Using data to build pratice None Final assigment Using data to build… Using data to build pratice None CHỦ-ĐỀ-9 -GIAO34 THOA-SÓNG Using data to build pratice Rock Crawling oooo None Using data to build pratice None Quy định viết tiểu CHAPTER MARKET SHARE luận -… Using data to build pratice Table Data of Trauth and Meyer in tri-county market Figure 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 *** None CHAPTER INCUMBENCY RATES Table Data of districts and the same vendors Figure The line chart below shows the districts and the same vendors in the surrounding market and tricounty 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 *** Table 3.2 Standard deviation of LFWBID CHAPTER 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 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 1984 1985 1986 1983 1987 1988 1989 1991 1990 1991 0,005 0,004 0,005 0,005 0,009 0,004 0,005 TRI-COUNTY 0,014 0,005 theSURROUND above argument and data 0,014 analysis, 0,013 we see that the winning of three0,008 milk is 0,008 Trauth and 0,014 0,011 0,010 bid 0,011 0,007 Meyer in both tri-county and surrounding market in each year.Based on Table 3.Standard deviation of WWBID of Trauth and Meyer Figure 3.1 The bar graph shows the standard deviation of WWBID of Trauth and Meyer during the time from 1983 to 1991 Figure 3.2 The bar graph shows the standard deviation of LFWBID of Trauth and Meyer during the time from 1983 to 1991 Table 3.3 Standard diviation of LFCBID TRI-COUNTY SURROUND 1983 0,02 1984 0,00779 0,0153 1985 0,01 0,02 1986 0,01 0,01 1987 0,01 0,01 1988 0,01 1989 0,01 0,01 1990 0,01 1991 0,01 0,01 Figure 3.3 The bar graph shows the standard deviation of LFCBID of Trauth and Meyer Based on signal communication we can see that the winning bids and dispersions of during thethe time fromof1983 to 1991 three milk not have the same pattern in surrounding and tri-county market In addition, the 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 *** CHAPTER 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 Correlation of three milk TRI-COUNTY SURROUND WWBID 0,0937 0,5491 LFWBID 0,0707 0,5233 LFCBID 0,1294 0,5054 Figure The bar chart shows the price versus cost/ distance of three milk in tri-county market and surrounding market 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 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 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 Figure 5.1 The bid sequence of WWBID Figure 5.2 The bid sequence of LFWBID 10 Figure 5.3 The bid sequence of LFCBID Based on the chart above, we can plot and compare the bidding of dairy in tricounty 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 *** CHAPTER 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 Table Comparison of the mean of winning bid prices WWBID LFWBID LFCBID SURROUND 0,1359 0,1280 0,1283 TRI-COUNTY 0,1370 0,1301 0,1309 Figure The bar chart shows the average winning bid price for three milk from 1983 to 1991 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 13 CONCLUSION 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 14 More from: Using data to build pratice Trường Đại học… 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