Questions
Environmentalism and Moral Concern for Animals Many believe that we are in serious trouble today as...

Environmentalism and Moral Concern for Animals Many believe that we are in serious trouble today as human beings plunging headlong into a major climate crisis on planet earth. Our course eText on Environmental Ethics states the following: There is no denying that the global climate is changing, as the level of carbon dioxide in the atmosphere has increased during the past century. … Coastlines are crumbling as the climate changes and sea levels rise… storms are increasing in severity … the Arctic ice cap is melting… (MacKinnon, 427). But what’s causing these troubling changes? We are. MacKinnon again: Some skeptics dispute whether the changes are entirely man-made, but the vast majority of experts believe one of the major causes of climate change is the burning of fossil fuels … (MacKinnon, 428). And the human disregard for nature also means disregard for all species of animals that depend on livable natural habitats. Entire species today are threatened with imminent extinction. Writing in 2016, MacKinnon says “687 animal species are listed as either endangered or threatened.” That number has risen drastically since 2016, leading some scientists to conclude that we are in the midst of a global mass extinction of animal species. The following video links provide, in the first, a summary of a U.N. Climate Change Report from 2019, and, in the second, an explanation of the meaning of speciesism by Dr. Richard Ryder. After watching these short videos, please respond to the discussion questions listed below. U.N. Climate Change Report: LINK (Links to an external site.) Dr. Richard Ryder on the meaning of speciesism Link (Links to an external site.) Discussion Questions (please address both 1 and 2). [1] How does the hearing of this U.N. report on the climate crisis affect you, your values, your sense of the world and its future? What human beliefs or values today will more likely prevent needed changes in our way of life, methods of production, or government policies? And what beliefs or values will more likely lead to the kind of changes needed to address the climate crisis? [2] Do you think humans are biased against animals, as moral philosophers like Peter Singer express with the term speciesism, and do you think this speciesism is comparable to other human biases such as racism and sexism, as Dr. Ryder contends in the video?

Why or why not?

In: Economics

Program: Java Write a Java program using good programming principles that will aggregate the values from...

Program: Java


Write a Java program using good programming principles that will aggregate the values from several input files to calculate relevant percentages and write the values to an output file.

You have been tasked with reading in values from multiple files that contains different pieces of information by semester. The Department of Education (DOE) would like the aggregate values of performance and demographic information by academic year. A school year begins at the fall semester and concludes at the end of the summer semester the following year. Fall 2019 - Summer 2020 is considered one academic year.

Input Files

  • Input files named Fall2019Analytics.txt, Spring2020Analytics.txt, and Summer2020Analytics.txt have been placed in Canvas.   Each have the same layout but differ by semesters.
  • Each file contains several pieces of data by program - total enrollment, enrollment by gender, completion by gender, enrollment by ethnicity, completion by ethnicity, among other pieces of data.  
  • The program should read in the values from these input files, aggregate the data, and write the information to an output file that will be sent to Tallahassee.
  • From there, the DOE will use this output file as input to aggregate the data from other schools within the state of Florida.
  • It is important that this file is formatted in the proper sequence that the DOE needs - otherwise the college will be heavily fined and may lose accreditation.


These input files contain the data for three programs on campus:

Program code 3624
Program code 5651
Program code 6635

Input file layout (all integer values) by semester:

  • program number
  • total number of students enrolled in the program
  • total number of student completers in the program
  • total number of female students enrolled in the program
  • total number of male students enrolled in the program
  • total number of unknown/not reported gender students enrolled in the program
  • total number of female student completers in the program
  • total number of male student completers in the program
  • total number of unknown/not reported student completers in the program
  • total number of Asian students enrolled in the program
  • total number of Black students enrolled in the program
  • total number of Hispanic students enrolled in the program
  • total number of Multiracial students enrolled in the program
  • total number of Native American students enrolled in the program
  • total number of Native Hawaiian students enrolled in the program
  • total number of Unknown/not reported ethnicity students enrolled in the program
  • total number of White students enrolled in the program
  • total number of Asian student completers in the program
  • total number of Black student completers in the program
  • total number of Hispanic student completers in the program
  • total number of Multiracial student completers in the program
  • total number of Native American student completers in the program
  • total number of Native Hawaiian student completers in the program
  • total number of Unknown ethnicity student completers in the program
  • total number of White students completer in the program


Notes

  • Each value within the file for a program is separated by one space.
  • Each program code is on its own line in each file. There are three lines per file.
  • Use an array or arrayList to hold the values within each file.
  • Each semester should be coded within their own class.


Calculations

The following values must be calculated:

For each semester:
   - the percentage of students completers (total number of student completers / total number of students enrolled)

For each individual program code:
   - grand totals for each category (enrolled, completers, gender, and ethnicity)

Aggregate for all semesters:

   - the total number of students enrolled
   - the total number of student completers
   - the total number by gender
   - the total number by each ethnicity
   - the percentage of student completers (total completers / total enrolled)
   - the percentage of female completers (total number of female completers / total number of female enrolled)
   - the percentage of male completers
   - the percentage of each ethnicity


Output


The output for this project will be two-fold.   The output will be displayed in a Message dialog box and an output file.

The Message Dialog boxes:

Each percentage calculated should be displayed in percentage format with one decimal place.

A sample format (the values are not accurate, this is only for formatting purposes):

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate total number of student enrolled:       5555
Aggregate total number of student completers: 4444

Aggregate percentage of students completing for the academic year: 81.2%

Percentage of students completing Fall 2019:             76.9%
Percentage of students completing Spring 2020:        85.3%
Percentage of students completing Summer 2020:     84.1%

On the next dialog screen, display the following:

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate values for:

Female student completers:     88.8%
Male student completers:                        88.7%
Unknown/not reported completers:    89.1%

Asian completers:    90.1%
Black completers:                                        90.2%
Hispanic completers:                                 90.3%
Multiracial completers:                             90.4%
Native American completers:      90.5%
Native Hawaiian completers:                  90.6%
Unknown/Not Reported completers:   90.7%
White completers:                                       90.8%

Fall2019Analytics.txt: 3624 3729 2946 1774 1445 510 1442 1087 417 627 1021 939 216 47 15 122 742 572 977 735 181 39 11 84 3475651 4074 3585 1956 1977 141 1782 1731 72 413 927 893 314 56 37 395 1039 387 912 803 273 49 30 327 8046635 2116 1837 609 1058 449 582 1031 224 341 402 363 146 89 74 297 404 303 377 321 113 76 57 270 320

Spring2020Analytics.txt: 3624 3496 3102 1579 1238 679 1486 1017 599 703 1137 842 224 32 21 103 434 688 1007 774 221 30 21 101 2605651 3942 3711 1421 2213 308 2148 1349 214 443 739 804 310 46 37 173 1390 439 727 799 216 46 36 162 12866635 2101 1979 797 1273 31 752 1039 188 601 739 426 173 21 15 3 123 592 701 399 162 18 13 2 92

Summer2020Analytics.txt: 3624 2021 1983 771 1137 113 717 1083 183 307 526 601 211 27 4 13 332 297 506 600 208 26 4 13 3295651 3013 2883 1267 1393 353 1240 1297 346 226 402 373 102 16 13 17 1864 214 401 369 96 15 13 17 17586635 1731 1546 663 817 251 612 799 135 107 392 649 81 30 21 71 380 103 384 621 80 30 20 70 238

In: Computer Science

Program: Java Write a Java program using good programming principles that will aggregate the values from...

Program: Java


Write a Java program using good programming principles that will aggregate the values from several input files to calculate relevant percentages and write the values to an output file.

You have been tasked with reading in values from multiple files that contains different pieces of information by semester. The Department of Education (DOE) would like the aggregate values of performance and demographic information by academic year. A school year begins at the fall semester and concludes at the end of the summer semester the following year. Fall 2019 - Summer 2020 is considered one academic year.

Input Files

  • Input files named Fall2019Analytics.txt, Spring2020Analytics.txt, and Summer2020Analytics.txt have been placed in Canvas.   Each have the same layout but differ by semesters.
  • Each file contains several pieces of data by program - total enrollment, enrollment by gender, completion by gender, enrollment by ethnicity, completion by ethnicity, among other pieces of data.  
  • The program should read in the values from these input files, aggregate the data, and write the information to an output file that will be sent to Tallahassee.
  • From there, the DOE will use this output file as input to aggregate the data from other schools within the state of Florida.
  • It is important that this file is formatted in the proper sequence that the DOE needs - otherwise the college will be heavily fined and may lose accreditation.


These input files contain the data for three programs on campus:

Program code 3624
Program code 5651
Program code 6635

Input file layout (all integer values) by semester:

  • program number
  • total number of students enrolled in the program
  • total number of student completers in the program
  • total number of female students enrolled in the program
  • total number of male students enrolled in the program
  • total number of unknown/not reported gender students enrolled in the program
  • total number of female student completers in the program
  • total number of male student completers in the program
  • total number of unknown/not reported student completers in the program
  • total number of Asian students enrolled in the program
  • total number of Black students enrolled in the program
  • total number of Hispanic students enrolled in the program
  • total number of Multiracial students enrolled in the program
  • total number of Native American students enrolled in the program
  • total number of Native Hawaiian students enrolled in the program
  • total number of Unknown/not reported ethnicity students enrolled in the program
  • total number of White students enrolled in the program
  • total number of Asian student completers in the program
  • total number of Black student completers in the program
  • total number of Hispanic student completers in the program
  • total number of Multiracial student completers in the program
  • total number of Native American student completers in the program
  • total number of Native Hawaiian student completers in the program
  • total number of Unknown ethnicity student completers in the program
  • total number of White students completer in the program


Notes

  • Each value within the file for a program is separated by one space.
  • Each program code is on its own line in each file. There are three lines per file.
  • Use an array or arrayList to hold the values within each file.
  • Each semester should be coded within their own class.


Calculations

The following values must be calculated:

For each semester:
   - the percentage of students completers (total number of student completers / total number of students enrolled)

For each individual program code:
   - grand totals for each category (enrolled, completers, gender, and ethnicity)

Aggregate for all semesters:

   - the total number of students enrolled
   - the total number of student completers
   - the total number by gender
   - the total number by each ethnicity
   - the percentage of student completers (total completers / total enrolled)
   - the percentage of female completers (total number of female completers / total number of female enrolled)
   - the percentage of male completers
   - the percentage of each ethnicity


Output


The output for this project will be two-fold.   The output will be displayed in a Message dialog box and an output file.

The Message Dialog boxes:

Each percentage calculated should be displayed in percentage format with one decimal place.

A sample format (the values are not accurate, this is only for formatting purposes):

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate total number of student enrolled:       5555
Aggregate total number of student completers: 4444

Aggregate percentage of students completing for the academic year: 81.2%

Percentage of students completing Fall 2019:             76.9%
Percentage of students completing Spring 2020:        85.3%
Percentage of students completing Summer 2020:     84.1%

On the next dialog screen, display the following:

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate values for:

Female student completers:     88.8%
Male student completers:                        88.7%
Unknown/not reported completers:    89.1%

Asian completers:    90.1%
Black completers:                                        90.2%
Hispanic completers:                                 90.3%
Multiracial completers:                             90.4%
Native American completers:      90.5%
Native Hawaiian completers:                  90.6%
Unknown/Not Reported completers:   90.7%
White completers:                                       90.8%

Fall2019Analytics.txt: 3624 3729 2946 1774 1445 510 1442 1087 417 627 1021 939 216 47 15 122 742 572 977 735 181 39 11 84 3475651 4074 3585 1956 1977 141 1782 1731 72 413 927 893 314 56 37 395 1039 387 912 803 273 49 30 327 8046635 2116 1837 609 1058 449 582 1031 224 341 402 363 146 89 74 297 404 303 377 321 113 76 57 270 320

Spring2020Analytics.txt: 3624 3496 3102 1579 1238 679 1486 1017 599 703 1137 842 224 32 21 103 434 688 1007 774 221 30 21 101 2605651 3942 3711 1421 2213 308 2148 1349 214 443 739 804 310 46 37 173 1390 439 727 799 216 46 36 162 12866635 2101 1979 797 1273 31 752 1039 188 601 739 426 173 21 15 3 123 592 701 399 162 18 13 2 92

Summer2020Analytics.txt: 3624 2021 1983 771 1137 113 717 1083 183 307 526 601 211 27 4 13 332 297 506 600 208 26 4 13 3295651 3013 2883 1267 1393 353 1240 1297 346 226 402 373 102 16 13 17 1864 214 401 369 96 15 13 17 17586635 1731 1546 663 817 251 612 799 135 107 392 649 81 30 21 71 380 103 384 621 80 30 20 70 238

In: Computer Science

Program: Java Write a Java program using good programming principles that will aggregate the values from...

Program: Java


Write a Java program using good programming principles that will aggregate the values from several input files to calculate relevant percentages and write the values to an output file.

You have been tasked with reading in values from multiple files that contains different pieces of information by semester. The Department of Education (DOE) would like the aggregate values of performance and demographic information by academic year. A school year begins at the fall semester and concludes at the end of the summer semester the following year. Fall 2019 - Summer 2020 is considered one academic year.

Input Files

  • Input files named Fall2019Analytics.txt, Spring2020Analytics.txt, and Summer2020Analytics.txt have been placed in Canvas.   Each have the same layout but differ by semesters.
  • Each file contains several pieces of data by program - total enrollment, enrollment by gender, completion by gender, enrollment by ethnicity, completion by ethnicity, among other pieces of data.  
  • The program should read in the values from these input files, aggregate the data, and write the information to an output file that will be sent to Tallahassee.
  • From there, the DOE will use this output file as input to aggregate the data from other schools within the state of Florida.
  • It is important that this file is formatted in the proper sequence that the DOE needs - otherwise the college will be heavily fined and may lose accreditation.


These input files contain the data for three programs on campus:

Program code 3624
Program code 5651
Program code 6635

Input file layout (all integer values) by semester:

  • program number
  • total number of students enrolled in the program
  • total number of student completers in the program
  • total number of female students enrolled in the program
  • total number of male students enrolled in the program
  • total number of unknown/not reported gender students enrolled in the program
  • total number of female student completers in the program
  • total number of male student completers in the program
  • total number of unknown/not reported student completers in the program
  • total number of Asian students enrolled in the program
  • total number of Black students enrolled in the program
  • total number of Hispanic students enrolled in the program
  • total number of Multiracial students enrolled in the program
  • total number of Native American students enrolled in the program
  • total number of Native Hawaiian students enrolled in the program
  • total number of Unknown/not reported ethnicity students enrolled in the program
  • total number of White students enrolled in the program
  • total number of Asian student completers in the program
  • total number of Black student completers in the program
  • total number of Hispanic student completers in the program
  • total number of Multiracial student completers in the program
  • total number of Native American student completers in the program
  • total number of Native Hawaiian student completers in the program
  • total number of Unknown ethnicity student completers in the program
  • total number of White students completer in the program


Notes

  • Each value within the file for a program is separated by one space.
  • Each program code is on its own line in each file. There are three lines per file.
  • Use an array or arrayList to hold the values within each file.
  • Each semester should be coded within their own class.


Calculations

The following values must be calculated:

For each semester:
   - the percentage of students completers (total number of student completers / total number of students enrolled)

For each individual program code:
   - grand totals for each category (enrolled, completers, gender, and ethnicity)

Aggregate for all semesters:

   - the total number of students enrolled
   - the total number of student completers
   - the total number by gender
   - the total number by each ethnicity
   - the percentage of student completers (total completers / total enrolled)
   - the percentage of female completers (total number of female completers / total number of female enrolled)
   - the percentage of male completers
   - the percentage of each ethnicity


Output


The output for this project will be two-fold.   The output will be displayed in a Message dialog box and an output file.

The Message Dialog boxes:

Each percentage calculated should be displayed in percentage format with one decimal place.

A sample format (the values are not accurate, this is only for formatting purposes):

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate total number of student enrolled:       5555
Aggregate total number of student completers: 4444

Aggregate percentage of students completing for the academic year: 81.2%

Percentage of students completing Fall 2019:             76.9%
Percentage of students completing Spring 2020:        85.3%
Percentage of students completing Summer 2020:     84.1%

On the next dialog screen, display the following:

Santa Fe College
Academic Year 2019 - 2020
Program codes: 3624, 5651, and 6635

Aggregate values for:

Female student completers:     88.8%
Male student completers:                        88.7%
Unknown/not reported completers:    89.1%

Asian completers:    90.1%
Black completers:                                        90.2%
Hispanic completers:                                 90.3%
Multiracial completers:                             90.4%
Native American completers:      90.5%
Native Hawaiian completers:                  90.6%
Unknown/Not Reported completers:   90.7%
White completers:                                       90.8%

Fall2019Analytics.txt: 3624 3729 2946 1774 1445 510 1442 1087 417 627 1021 939 216 47 15 122 742 572 977 735 181 39 11 84 3475651 4074 3585 1956 1977 141 1782 1731 72 413 927 893 314 56 37 395 1039 387 912 803 273 49 30 327 8046635 2116 1837 609 1058 449 582 1031 224 341 402 363 146 89 74 297 404 303 377 321 113 76 57 270 320

Spring2020Analytics.txt: 3624 3496 3102 1579 1238 679 1486 1017 599 703 1137 842 224 32 21 103 434 688 1007 774 221 30 21 101 2605651 3942 3711 1421 2213 308 2148 1349 214 443 739 804 310 46 37 173 1390 439 727 799 216 46 36 162 12866635 2101 1979 797 1273 31 752 1039 188 601 739 426 173 21 15 3 123 592 701 399 162 18 13 2 92

Summer2020Analytics.txt: 3624 2021 1983 771 1137 113 717 1083 183 307 526 601 211 27 4 13 332 297 506 600 208 26 4 13 3295651 3013 2883 1267 1393 353 1240 1297 346 226 402 373 102 16 13 17 1864 214 401 369 96 15 13 17 17586635 1731 1546 663 817 251 612 799 135 107 392 649 81 30 21 71 380 103 384 621 80 30 20 70 238

In: Computer Science

David Stern, Commissioner of the National Basketball Association (NBA), scanned the arena from his courtside seat...

David Stern, Commissioner of the National Basketball Association (NBA), scanned the arena from his courtside seat at the sold out Toyota Center in Houston, TX during the 2004 Western Conference Playoffs game between the Houston Rockets and the Los Angeles Lakers. The video commercials and fan-response prompts he viewed on the high-tech scoreboard reminded him of how far technology had progressed since he first took the helm of the league in 1984. The NBA’s tremendous growth that stemmed from increased revenue opportunities through state-of-the-art facilities had begun to taper off since there was only one team left in the league that had yet to move into a modern arena. Now, the NBA leadership team spent much of its time pondering ways to offer fans alternative options to experience the NBA using cell phones, video games, and other innovative media channels of communication. While Stern contemplated how the league would continue to benefit from new technological advances, he noticed fans waving pictures of Yao Ming, a 7-foot 6-inch player from China. Stern’s global vision of the NBA was slowly coming to fruition through the recent influx of international players and the NBA’s initiatives to broadcast and market games internationally, yet he believed there was a much greater potential to be realized. Stern still had a few months to prepare for the annual Board of Governors meeting. In front of the NBA’s owners, Stern would deliver a “state-of-the-league” address and unveil a plan for confronting the league’s challenges and systematizing recommended changes across the league’s 30 teams. While the league was healthy on most fronts, team owners were recently alarmed after receiving reports indicating that revenues were down even though overall attendance had increased during the 2003- 04 season. Additionally, the league had just withstood several public relations disasters involving a few high-profile players and was facing the perception from many fans that the quality of play had diminished. Stern reflected on the competing demands and wondered how to prioritize and sort them out. The following morning, Stern would meet with Russ Granik, Deputy Commissioner and COO, and Adam Silver, President and CEO of NBA Entertainment, to begin thinking through a strategy. Just as Stern turned to Granik to remind him of the meeting, the crowd erupted as Yao Ming scored a last second shot to send the game into overtime. By 2003, the NBA had grown to include 29 teams, and had plans to expand to 30 teams in 2004.8 Each team was independently owned, either by an individual or by an ownership group. The NBA’s league office intended to work “for” the owners and was primarily responsible for operating the league.9 Revenue and costs for the league were largely driven by collective individual team activity. In 2002, 41% of the league’s revenue came from each team’s gate receipts, 45% from the league’s television contract with national television networks to broadcast NBA basketball games, and 12% from other sources including sponsorships, licensing partnerships, concessions, and preseason promoter fees.10 Of the league’s costs, over 63% were due to player salaries, which had escalated significantly over time (see Exhibit 1).11 The remainder of the league’s costs was split evenly among team basketball operations, promotions, arena rentals, and general & administrative costs.12 The league office was funded by 6% of each team’s gate receipts, and all other gate receipts were kept by each individual team.13 All national revenue—including licensing and national TV deals—was split evenly amongst all 29 teams.14 However, each team retained any local television revenue it generated.15 Over the years, the league had implemented a number of measures to control costs and distribute money equitably across the league. These measures were captured in a collective bargaining agreement (CBA), which is negotiated between the owners and players. In 2004 the league had a salary cap in place that attempted to “cap” the amount of money that each team spent on player salaries, generally at 55% of Basketball-Related Income (BRI, or the sum of gate receipts and national television revenue).16 However, there were numerous exceptions that enabled teams to exceed the cap in order to retain players. Although the league had numerous sources of revenues and costs, there were a handful of critical factors that drove the financial success of the NBA. The overriding factor, according to senior league management, was the quality of play and the excitement generated over the 82-game regular season and the post-season playoffs. Granik noted that “the key to this league is the public perception of our product, the quality of the games being played on the court, the level of competition between the teams, and the expertise of the athletes involved.”17 Mike Bantom, Senior Vice President of Player Development, summed up the league’s critical success factor as “exciting, competitive basketball games that would effectively compete against other entertainment options for the consumer.”18 Others tied the success of each team to its respective win-loss record. Bob Criqui, the league’s SVP of Finance, noted that “even more importantly than the win-loss record, a team must inspire hope among its fans. If a team’s fans believe that the team will be successful, the fans will actively cheer for the team, and come to watch the team’s games.”19 All mentioned that it was difficult to quantify or measure this critical success factor, but agreed that the excitement of the game translated into strong attendance, TV ratings, and scoring averages. Exhibits 2 and 3 present recent attendance levels and TV ratings for the league. Another success factor often cited by league executives was the image of its players, both on and off the court. Granik noted that “how people perceive our players is certainly an issue for us.” NBA League Office Overview The NBA league office, headquartered in New York City and Secaucus, NJ, consisted of five main entities—NBA League Operations, NBA Entertainment, NBA International, the WNBA, and the NBDL—which all reported to the Commissioner’s Office, led by Stern. Exhibit 5 presents the NBA organizational structure. NBA League Operations, headed by Granik, governed the basketball side of the league, including game scheduling and officiating, and oversaw league administrative duties, such as finance, human resources, and security. Other divisions, such as Player Development, worked closely with NBA teams to promote best practices and to ensure that teams adhered to league guidelines. NBA Entertainment, led by Silver, housed all revenue-generating properties at the league level, including the NBA Store and NBA TV. NBA International consisted of satellite offices situated to maximize revenue and marketing opportunities abroad. Similar to NBA League Operations, the WNBA and the NBDL offices served as governing bodies for their respective leagues. WNBA In the fall of 1996, the NBA launched the Women’s National Basketball Association (WNBA) as a wholly-owned subsidiary of the league so that the eight WNBA teams would be collectively owned by the NBA’s 29 owners, unlike NBA teams which were franchised individually to owners. Eight inaugural teams would begin play during the summer season of 1997 in the following NBA team cities: Charlotte, Cleveland, Houston, New York, Los Angeles, Phoenix, Sacramento and Utah. Although the WNBA league office managed many aspects of WNBA team operations such as negotiating player contracts and disbursing player salaries, the affiliated NBA teams were responsible for using existing resources and/or hiring employees to fulfill the league’s mandated operational and sales requirements. Within four years, the WNBA had expanded to 16 teams, all of which were affiliated with existing NBA teams. After the 2002 season, the league decided to shift WNBA team ownership from the NBA to each affiliated team. At this point, NBA owners were given the option to purchase and gain full control of their corresponding WNBA team. All the owners accepted the league’s offer with the exception of those in Portland, Orlando, Utah, and Miami. Subsequently, two of the teams relocated to other cities with owners who wanted a WNBA team, while the other two teams dissolved. Beginning in the 2004 season, the WNBA consisted of 13 teams. National Basketball Development League (NBDL) In the fall of 2001, the NBDL, a minor league wholly-owned by the NBA, became the league’s official training ground for team staff, officials, and players who met the minimum 20 year age requirement. The NBDL tipped off with teams in Asheville, NC; Charleston, SC; Columbus, GA; Fayetteville, NC; Greenville, SC, Huntsville, AL; Mobile, AL; and Roanoke, VA. NBA Board of Governors Major strategic decisions for the league were approved by the NBA’s Board of Governors. The Board of Governors comprised the owners of all 30 NBA teams, each of whom controlled a vote. David Stern was the Chairman of the Board, and the Board met twice annually. As the league became increasingly successful, the nature of the Board of Governors changed as team ownership changed hands. New owners such as Howard Schultz (Owner of the Seattle Supersonics and Chairman of Starbucks Coffee), Mark Cuban (Owner of the Dallas Mavericks and co-founder of Broadcast.com and current CEO of HDNet), and Joe and Gavin Maloof (Owners of the Sacramento Kings and Co-CEOs of Maloof Sports and Entertainment) began to take a more proactive approach to the management of their teams and their role on the Board of Governors. As Silver explained, “the biggest difference with the current Board of Governors is that we have much more substantive discussions about the business decisions of the league, which David actually encourages. We still have a ‘strong commissioner model’, we just have a much more active board. We now have owners on the board who spent $10 million on their team, and owners who have spent $300 million on their team. There is clearly going to be a difference in the demands from these two different sets of owners with regards to the direction of the league.” National Basketball Players Association (NBPA) The NBPA was the NBA players’ union that negotiated the Collective Bargaining Agreement (CBA) with the NBA. The CBA defined the rules of interaction between the players and the league on multiple fronts, including player compensation, conduct and appearances. As such, the NBA’s major product improvement and development recommendations were typically subject to approval by the NBPA, whose interests were not always aligned with the league’s and team owners. For instance, the league’s attempt to impose a harder player salary cap for purposes of increasing competitiveness across teams was met by extreme opposition from the NBPA during the 1998 collective bargaining period. This dispute, among others, ended after the longest ever NBA lock-out (strike). Consequently, the league suffered considerable financial losses from having to cut the regular season from 82 to 50 games and sustained substantial brand damage from negative media coverage. The NBPA provided its own set of programs and services to the players and, on occasion, would join forces with the NBA’s Player Development department to administer certain programs. All NBA league-mandated programs and appearances in which players participated were negotiated as part of the CBA. Superstar Turnover Much of the NBA’s popularity in the 1980s and 1990s was built on a handful of superstars. The NBA encouraged this by actively promoting its superstars, and turning their burgeoning popularity into booming ratings and attendance figures. Michael Jordan of the Chicago Bulls – perhaps the game’s greatest player and certainly its most popular player – joined the league in 1984 and continued playing until 199827 , after which returned to the league for 2 more seasons with the Washington Wizards in 2001-2003. The contests between Magic Johnson’s Los Angeles Lakers and Larry Bird’s Boston Celtics in the 1980s became one of sports’ greatest rivalries, as these two teams combined to win 8 of 10 NBA titles during the decade. Other charismatic superstars – such as Charles Barkley, Isiah Thomas, Julius “Dr. J” Erving, Dominique Wilkins, and Hakeem Olajuwon – propelled the NBA and created an exciting identity for the league. However, as these superstars began to retire in the early 1990s, the league struggled to identify comparable superstars to capture fans’ imagination in the same way. Fans constantly searched for the “next Jordan”, and throughout the 1990s players like Harold Miner, Jerry Stackhouse, Grant Hill and Vince Carter attempted to fill Jordan’s shoes only to fail. Although the NBA had its stars in the late1990s and early 2000s—including Shaquille O’Neal, Tim Duncan, Kevin Garnett, Kobe Bryant, Tracy McGrady, Allen Iverson and Jason Kidd—many fans were unable to connect to these players in the same way as the superstars of the 80s and early 90s. Was it just a matter of time until these players blossomed into the same types of superstars as those of the days of old, or did the existence of these new players require a different approach for the league? Negative Off-the-Court Image of NBA Players The league suffered incalculable damage to its image during a 6-month long work stoppage (better known as a “lockout”) of the players that eliminated 32 games from the 1998-99 NBA season as a result of contentious negotiations between the league office and the NBPA. After the lockout was finally settled, many felt the NBA as a whole had lost. Utah Jazz guard Jeff Hornacek said “I wouldn't blame the fans if they didn't come back…neither side is coming out of this thing looking good.”1 All in all, players lost $500 million in salaries, the NBA’s important corporate partners lost significant revenues (Nike reported a 50% drop in fiscal second quarter earnings and a 15% drop in revenues in December of 1998) (Motley Fool), and the NBA’s goodwill amongst fans and the general public was at an all-time low. As one fan stated in a Detroit News article in March 2000, “I hate the NBA and I'm not really a Pistons fan anymore. I'm sick and tired of the bitching players and owners. They're a bunch of big millionaire babies and I'm not going to pay to see them” (Detroit News). Other critical source for this section: The NBA continued to face image problems in 2003, when an ESPN poll revealed that the number one “problem” with the NBA, as perceived by its fans, was “player off-court behavior.” 39 A summary of the poll is presented in Exhibit 10. There were certainly a number of negative off-court incidents involving NBA players in the late 1990s and early 2000s that couldn’t be ignored, including: • All-Star Latrell Sprewell choking and threatening his coach, P.J. Carlesimo, during a practice in December 1997.40 • A scathing 1998 Sports Illustrated article revealing the significant number of paternity suits and out-of-wedlock births among professional athletes. The article mentioned several NBA superstars by name, including Larry Johnson, who was supporting five children by four women, and Shawn Kemp (drafted shortly after his high school graduation), who had fathered seven children out-of-wedlock. Other players highlighted in the article included NBA superstars Patrick Ewing, Juwan Howard, Scottie Pippen, Jason Kidd, Stephon Marbury, Hakeem Olajuwon and Gary Payton, Larry Bird, and Isiah Thomas. Kobe Bryant—three-time NBA champion and mega-superstar, high school draftee, married father with a young daughter—was arrested and charged with the sexual assault of a young woman at a hotel in Colorado during the 2003 off-season. In 2004, David Stern openly discussed plans to expand the league to Europe, noting that “it is not out of the realm of possibility that the NBA could have teams in Milan, Munich, Barcelona and London within a decade.” Many in the league office were excited at the possibility of brand-new revenue sources overseas—including international gate receipts, increased sponsorship and merchandising revenue from international companies and consumers, and a new source of television rights fees (or potentially broadcast-related revenues from NBA TV international telecasts). To many this expansion only seemed natural, and in some cases necessary. Stern noted “90% of our buildings are full at any given NBA game in the U.S…90%! Expansion overseas is the only way to grow this revenue source.” There was already cross-fertilization between the two markets, such as the increased number of international NBA superstars and the burgeoning popularity of NBA players and games in European and Asian markets. The NBA was already working on “seeding” these markets by holding exhibition games in international markets like China and Russia and expanding the presence of NBA TV, which was already in 30 countries in early 2004. Another open question was the future of the NBDL. While initially launched as a “training ground” for team staff, officials and players, many saw the opportunity to transform the NBDL into a true “minor league” for the NBA, which would operate similar to the minor leagues in Major League Baseball. Under this system, each NBDL would “belong” to one or two NBA teams, and the NBA team would have the ability to send a player down to their minor league team, or call them up when they needed a player, all the time retaining their contractual rights. Many saw this as an attractive option in order to handle the increasing number of high school and international players into the league. Upcoming Collective Bargaining Agreement Discussions Looming in the distance was a new collective bargaining agreement (CBA) to be negotiated with the NBPA. The current CBA was scheduled to expire after the 2004-2005 season, and all parties wanted to avoid a repeat of the lockout of 1999. Issues on the table included the percentage of revenues to be allocated to players and owners, the salary cap, the luxury tax, a potential age limit or a NBDL minor league, and any other issue that would have a direct impact on players. One NBA team president noted that one of the most important issues for the league going forward was “to find labor peace without bloodshed, so everyone is a little better off and teams have a chance to make money.” Decisions, Decisions Tomorrow, Stern, Granik and Silver would meet to begin planning for the upcoming gathering of the Board of Governors, where they would present the league’s strategic plan and the organizational requirements to support these strategic goals. As such, the three needed to discuss the competing priorities of the league’s stakeholders, and determine whose issues were most important to the future of the league. On the one hand, the trio would have to grapple with the serious issues that were undermining the league’s short-term vitality with certain segments of its fans. They would also have to address the concerns of the league’s ownership group and players association. Finally, Stern was eager to build consensus for his growth agenda. But how would the owners react to this proposal? How would this translate into the upcoming Collective Bargaining Agreement negotiations with the NBPA? And what systemic organizational changes were required to ensure that these recommendations would take root and sustain themselves across all 30 teams in the league? -------------------------------------------------------------------------------------------------------------------

1.What is the case about?

2.What are the important events that occurred in the case?

3.What can we learn from reading the case?

4.What advice do you have for the leaders in the case and/or company in the case?

In: Operations Management

During 2022, its first year of operations as a delivery service, Marigold Corp. entered into the...

During 2022, its first year of operations as a delivery service, Marigold Corp. entered into the following transactions.

1. Issued shares of common stock to investors in exchange for $120,000 in cash.
2. Borrowed $53,000 by issuing bonds.
3. Purchased delivery trucks for $51,000 cash.
4. Received $17,000 from customers for services performed.
5. Purchased supplies for $6,200 on account.
6. Paid rent of $5,800.
7. Performed services on account for $10,900.
8. Paid salaries of $26,600.
9. Paid a dividend of $10,200 to shareholders.


Using the following tabular analysis, show the effect of each transaction on the accounting equation. Put explanations for changes to Stockholders’ Equity in the far right column. (If a transaction causes a decrease in Assets, Liabilities or Stockholders' Equity, place a negative sign (or parentheses) in front of the amount entered for the particular Asset, Liability or Equity item that was reduced, see Illustration 3-4 for example.)

Assets

=

Liabilities

+

Stockholders’ Equity

Cash + Accounts
Receivable
+

Supplies

+ Equipment = Accounts
Payable
+

Bonds
Payable

+ Common
Stock
+

Retained Earnings

Revenues Expenses

Dividends

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(6)

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(7)

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eTextbook and Media

In: Accounting

BENEFIT ENROLLMENT PERIOD Background Information: You work for Baxter Company and need to announce the benefit...

BENEFIT ENROLLMENT PERIOD

Background Information:

You work for Baxter Company and need to announce the benefit enrollment period.
Based on last year’s enrollment period, you are concerned about the attitude of employees. They don’t seem to realize that changes to health, dental, and life insurance programs can be made only once a year, during the month of May.

You’ll need to let your audience know that most of the benefit program is unchanged. However, dental coverage is a little different; two carriers (Quality Care and Health Alliance) now offer a dental coverage option. Employees can also increase coverage in life insurance for their family members, and health coverage will now include both a basic plan and a prudent buyer plan. You do not have to describe these changes; just encourage employees to read about them in an email to be sent in early April---see instructions for the exact date.

Your boss, Jonathon, asks you to schedule and announce a day early in April when representatives from Human Resources will be available to answer employee questions about the changes. He suggests these question-and-answer sessions be held in the East Lounge, and each session should be held at different times of the day: Dental insurance changes from 8:30 to10:30 a.m., Health insurance changes from 1 to 3 p.m., and Life insurance changes from 3 to 5 p.m.

Your Task:

Write an informational memo report to your employees announcing changes to their benefit coverage and the enrollment deadline. This is important because employees may make changes to their benefits only during this period. The deadline for changes is May 31.

First, read the attached file.

Second, prepare this message as an informational memo report, addressed to All Employees and sent from you, the Benefits Choice Manager. Date the informational report, and be sure to include a useful subject line; useful subject lines capture the essence of the report's content. Refer to the Guffey text for review.

Third, pick the meeting date (and use facts given regarding times ) in the case. You can refer to The Gregg Reference Manual for proper presentation of timeframes when using a.m. and p.m. in your message. Also, be sure to mention the location given in the case. When listing the times for each meeting, you will create a 3-item bulleted list; use bullets for each benefit to be discussed. You must figure out the best way to present this bulleted list.

Next, you must follow the Standard Memo Report Procedure document (and its supplement) for layout/format of your informational report. In this message, you will not use major or subsection breaks or continuation page headings. That is, it will be a maximum one page in length. Also, note that business reports contain no formal salutation and no complimentary close. Furthermore, your name and job title are typed as the content of the FROM: header near the top of the page; and your job title belongs on the same line as your typed name.

Finally, the opening paragraph [Introductory section] of your report will clarify for the reader exactly what content is coming in the discussion section of the report. The [Discussion section] will contain the facts you wish to present to your readers and will be from 1 - 4 paragraphs in length---in this case, shorter is better. Be sure to indicate the highlights of the coming changes that will be contained in an email to be sent on April 5. Your final paragraph [Closing section] will contain information about what the reader must do with the information. In this case, the action will be an invitation to attend one or more of the informational sessions at the times and in the location specified. Additionally, you will tell your employees what action to take if they cannot make it to the meetings they wish to attend.

Shown below is a model of how your finished report might look: [The model shows a one-paragraph introductory section, a two-paragraph discussion section, and a one-paragraph closing section; Your final report may vary based on the amount of information written in the discussion section.] You should be able to fit all of the necessary information on one page.

TO:          All Employees

FROM:      Your Name, Your Job Title

DATE:      March 27, 2013

SUBJECT: XXXXXXXXXXXXXXXXXXXXXXXXXX (all uppercase)                  *****Make sure you create a useful subject line---one that captures the essence of the report's content*****

             (Triple space here)

              (The paragraphs are single spaced)

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             (Double space here)

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Name this Word document Benefit Choice Your First Name Your Last Name. Submit.

In: Operations Management

In what ways have each of the following affected the costs of health care in the...

In what ways have each of the following affected the costs of health care in the U.S.?

- The health insurance industry -

Advances in medical technology -

Changes in U.S. demographics -

Government support for health care -

Consumer expectations

In: Nursing

What are the risk factors for heart problems that a person can and cannot control? What...

What are the risk factors for heart problems that a person can and cannot control? What is the difference between "control" and "management" of a risk factor? How do you encourage people to make necessary changes to their lifestyle

In: Nursing

Draw the Solow diagram for the General Solow Model and clearly indicate the steady state.

Draw the Solow diagram for the General Solow Model and clearly indicate the steady state. Starting from the original each time, draw in any changes and indicate any change in k~* and y~* if there is a decrease in n.

In: Economics