Chapter 9 Take Me Out to the Ball Game: Market Areas and the Urban Hierarchy A. Logistics

Chapter 9
Take Me Out to the Ball Game:
Market Areas and the Urban Hierarchy
A. Logistics
Students’ Time Requirements

Activity 1: Threshold of a Function 1 hour on the Internet for data collection (optional since instructor may provide data instead)

30–45 minutes for analysis

Activity 2: Market Area Geography 45–60 minutes

Activities 1 and 2 are completely stand-alone activities. They both tackle the concept of a market area but come at the idea from different angles. Activity 1 requires students to do original research to determine the minimum market size for a pizza restaurant in their city. Activity 2 is a Wiley Internet activity and asks students to compare market areas for major versus minor league baseball teams, to assess the effect of major league expansion on the size of the market areas of nearby cities, and to decide on a strategy for future major league expansion. Starting with the 4th edition, we have included questions on expansion into Latin America. Depending upon how much time you have allocated for this topic, you can assign either Activity 1 or Activity 2 or both.
Activity 1 is a genuine research experience for students, in that they must use the Internet to find a suitable data source for studying pizza restaurants, decide what constitutes a pizza restaurant, collect and manipulate the data, produce a graph on log-log paper and interpret the results.
You can reduce the time involved by partially or completely collecting the data yourself and asking the students to do only the analysis part of the activity. One good compromise is to list the specific towns and cities you want them to use for their state and give them the populations for those towns, but still require them to collect the number of pizza restaurants for those towns. The other benefit of giving the data to the students is that they can do the analysis in groups during class, no matter what the size of the class.
Regardless of who collects the data—students or instructor—there are certain pitfalls to watch out for. Yellow pages very often include listings for more than one city. The metro Phoenix phone book, for example, includes more than 50 place names. Care must be taken to match the population data to the phone book data. Don’t combine cities into metropolitan areas. Be careful to count only those pizza restaurants in your designated city.
Note also that yellow pages for smaller cities include outlying towns that should not be included as part of a single urban area. For instance, the yellow pages for Flagstaff, Arizona includes Page, Arizona, which is two hours to the north, and Cottonwood which is one hour south. Also, beware of double-counting pizza restaurants for chains of pizza restaurants. Individual outlets may be found in the alphabetical listing, in an advertisement, or in both places.
We have found Internet yellow pages to give uneven results. Tell your students to run a search on their hometown using several Web sites and use whichever finds the most complete and accurate list. I searched for pizza in the MSN Yellow Pages for Tempe, Arizona, and it found only six restaurants. It found two Papa Johns franchises but no Dominos or Pizza Huts, despite their being numerous outlets of both within the city limits. Meanwhile, yellowpages.com found 55, but somehow omitted the Dominos closest to campus. Infospace.com yielded at least 10 different categories, including by brand name; one category did have 54 entries. So it is important for students to test the search engine on a town they know well before proceeding with other towns. In Colorado, www.switchboard.com has been very accurate and a good source to use. It also lists the number of hits at the top, so students don’t need to count them by hand.
You might want to show your students a graph of the same data on regular (non-log) paper so they can see why log paper is necessary.
Activity 2 is extremely effective for structured group learning. For Question 2.12, students are asked to evaluate six cities as possible locations for a major league expansion team. You can ask teams of students to determine and justify their choices and then have a class discussion to try to arrive at two consensus choices. Alternatively, you can designate six teams and assign each team one of the six cities. Ask the teams to evaluate the strengths and weaknesses of their city as an expansion location. Remind them to consider strengths and weaknesses both in terms of the city itself as well as of the entire system of cities offering major league baseball. Is their city a viable market for major league baseball? Does the choice of their city as an expansion location undermine the viability of other cities in the system?

The new Latin America expansion questions in the 5th edition also provide a rich avenue for discussion. You may wish to preface Question 2.15 in particular to have them think about the complexities of expanding into lesser-developed countries that speak a different language. We could not devote the space to discuss these issues, but with some context from the instructor, students could discuss this scenario in great depth.

In the NSF summer workshops, our collaborative learning expert, Susan Ledlow, used Activity 2 to demonstrate different collaborative learning structures. Follow our links to a description of these structures. The ones she thought were best for each question were:

2.1 Write-Pair-Share

2.2–2.5 Pairs Check

2.6 Round Robin Brainstorm, Discuss, Write

2.7 Numbered Heads Together

2.8–2.9 Group Problem Solving with Roles

2.10 Write-Pair-Check

2.11 “Custom-designed Structure” in pairs

1. Brainstorm the criteria needed to make the decision.

2. Think individually about which two teams you would select.

3. Write your justifications.

4. Compare your choices and justifications with your partner’s.

5. Rank the top two choices.

6. Present your choices and defend them to the class, if called upon.

B. Lesson Plan
I. Urban functions

1. 
   Interconnected urban system
   
2. 
   Specialized urban (economic) functions
   
   1. 
      Automotive
      
   2. 
      Aerospace
      
   3. 
      Entertainment
      
   4. 
      Government
      
   5. 
      Tourism
      
3. 
   Universal, generic functions that all cities provide
   
4. 
   Cities as central place to which people travel, market areas from which people travel
   

II. Central place terminology

1. 
   Central place functions
   
   1. 
      Function has an order based on how specialized they are, how large a market area is needed, and how far people are willing to travel
      
2. 
   Threshold
   
   1. 
      Defined in terms of minimum:
      
      1. 
         Sales
         
      2. 
         Population
         
      3. 
         Area
         
      4. 
         Distance
         
3. 
   Range
   
4. 
   Urban hierarchy
   
   1. 
      Low-order goods and services
      
   2. 
      High-order goods and services
      
   3. 
      Number of types of goods and services is a function of population size
      

III. Introduce Activity 1. In class, go over instructions for collecting the data, completing the scatter diagram, and drawing the best-fitting line (see Logistics). If you are providing the data, start Activity 1 in class. They can finish at home if necessary.

IV. Discussion of Activity 1 results and applications
V. Central place theory

1. 
   Based on work by Christaller and Lösch
   
2. 
   Geographic assumptions
   
   1. 
      Featureless landscape (no roads, no barriers)
      
   2. 
      Uniform population distribution
      
   3. 
      Infinite plane (goes on forever—no boundary effects)
      
3. 
   Behavioral assumptions (implied, but not explicitly stated in text)
   
   1. 
      Consumers shop at the closest place where a good is available
      
   2. 
      Consumers cannot not go beyond the range of the good
      
   3. 
      Firms’ market areas must equal or exceed threshold of the good
      
4. 
   Hexagonal market areas
   
   1. 
      Hexagons because nonoverlapping circles leave some areas unserved
      
   2. 
      Any higher-order central place must also offer all lower-order functions, which means that the there is both a small hexagon and a large hexagon centered on each higher-order central place
      

VI. Background on baseball case study

1. 
   Origins
   
   1. 
      Disputed origin
      
   2. 
      Other names for the game
      
   3. 
      New York City, 1842–45
      
   4. 
      National Association of Base Ball Players, 1857
      
2. 
   Early professional baseball
   
   1. 
      Cincinnati Red Stockings, 1869
      
   2. 
      National Association of Professional Baseball Players (forerunner to the National League) was founded in 1871 with nine teams
      
   3. 
      Early league cities were central places, with large thresholds and market areas. Locations reflected the existing urban hierarchy.
      
   4. 
      National pastime
      
   5. 
      World War II
      
3. 
   Race and ethnic relations in baseball
   
4. 
   Population shifts and team relocations
   
   1. 
      Range increases with TV, thresholds become more regionalized
      
   2. 
      Brooklyn Dodgers and New York Giants moved to West coast in 1957
      
   3. 
      Boston Braves moved to Milwaukee in 1953
      
   4. 
      St. Louis Browns became the Baltimore Orioles in 1954
      
   5. 
      Philadelphia Athletics moved to Kansas City in 1955
      
   6. 
      Washington Senators became the Minnesota Twins in 1961
      
   7. 
      Growth of the South attracts teams
      
5. 
   Expansion in 1961
   
   1. 
      Southern California (Angels)
      
   2. 
      Washington (Senators)
      
   3. 
      New York (Metropolitans, nicknamed the Mets)
      
   4. 
      Houston (Colt 45s, who later became the Astros)
      
   5. 
      San Diego (Padres)
      
   6. 
      Montreal (Expos)
      
   7. 
      Seattle (Pilots)
      
   8. 
      Kansas City (Royals)
      
6. 
   Free agency
   
7. 
   Further expansion
   
   1. 
      Seattle (Mariners) and Toronto (Blue Jays) in 1977
      
   2. 
      Colorado (Rockies) and Florida (Marlins) in 1993
      
   3. 
      Tampa Bay (Devil Rays) and Arizona (Diamondbacks) in 1998
      
8. 
   Unfair competition issue: Media rights
   
   1. 
      Large versus small broadcast areas widen revenue and payroll disparities
      
   2. 
      Luxury tax
      
   3. 
      Merchandise sales
      
   4. 
      New stadium issue
      
   5. 
      Contraction
      
   6. 
      Relocation of Montreal Expos to Washington Nationals
      
   7. 
      Collective bargaining agreement
      
      1. 
         New wild card teams
         
      2. 
         minimum salaries
         
      3. 
         lottery for draft
         

9. Baseball is central place theory in action!
VII. Introduce or do Activity 2—apply central place theory to the real world

1. Definition of Thiessen polygon—the area closer to a given central point than to any other central point

a. How to make Thiessen polygons

1. Using a light-colored pencil, draw straight lines connecting neighboring cities.

2. Find the halfway point between two cities.

3. With a darker pencil, draw a perpendicular line at the halfway point.

4. Repeat for all lines emanating from the city.

5. Erase overlapping lines.

2. Baseball market areas will not be so perfectly shaped and spaced.

1. 
   Nevertheless, you will see a tendency for somewhat regular spacing of major league cities.
   
2. 
   You will also see that minor league cities are more numerous, more closely spaced, and have smaller market areas.
   
3. 
   You will see major distortions of the ideal central place pattern due to coastlines and uneven population densities. Thus, the deviations from the theoretical expectations are explainable.
   

VIII. Discussion

C. Answer Key
Activity 1: Threshold of a Function

1.1 Table for Arizona (with a few extra cities)

Table for Colorado (with a few extra cities)

Population	Number of Pizza Parlors	Town
739	1	San Luis
1206	2	Fowler
4286	1	Rocky Ford
5409	7	Gunnison
6784	3	Rifle
7568	1	La Junta
7960	9	Alamosa
9078	2	Trinidad
12344	5	Montrose
13922	13	Durango
41986	26	Grand Jct.
71093	16	Longmont
76930	16	Greeley
94673	37	Boulder
102121	26	Pueblo
360890	107	CO Springs
554636	178	Denver

1.2 Log-log scatter diagram for Arizona

1.2 Log scatter for Colorado (note this is an old graph—current graph in book has an x-axis that goes to 10,000,000)

1.3 Common mistakes in drawing the line of best fit are to (1) connect the dots, (2) force it through the origin, (3) draw a curved line, (4) draw it in too close to one side of the scatter diagram. If you force the line through the origin, you presume a threshold of 1,000. This figure may or may not be the actual threshold. In Arizona, for example, the line of best fit does, in fact, come quite close to the origin for a threshold population close to 1,000.

1.4 In the Arizona example, our line of best fit crosses the x-axis somewhere around 1,200–1,400 persons.
Note: This number is lower than the average number of persons per pizza restaurant for each city (2,538), or the average for the total number of restaurants divided by the total number of people for all of the cities combined (3,825).
There are two possible explanations for this fact. First, the graphical method yields a minimum population base. This is different from an average population base that you would get by dividing persons by pizza restaurants. The fact that the minimum is smaller suggests that many pizza restaurants are making excess profits due to larger market areas than they absolutely need to stay in business.
A second reason why the intercept is so low is that pizza restaurants in small towns are supported by much more than just the town’s population. Pizzas are being sold to people in the surrounding region, people who are not being counted in the city’s size. For instance, in our Arizona data, the pizza restaurant in Springerville (pop. 1,802) draws hundreds of customers from the surrounding countryside that is closer to Springerville than any other town with a pizza restaurant. By this interpretation, the threshold being calculated is not truly the number of potential customers, but the minimum town size. You can use this point to discuss what variables besides population could be used to measure the market threshold. Possibilities include distance, area, actual customers, or potential customers.
1.5 A city below the best-fit line has fewer pizza restaurants than expected given its population size (it would therefore be a good candidate for new restaurant location).
1.6 The cities well below the best-fit line are candidates for new pizza restaurants because they appear to be under served. Such cities, with more persons per restaurant, in theory, could provide enough customers to make a new restaurant profitable. Students should pick the top three or four candidates and list the actual versus expected number of pizza restaurants. This fulfills the question based on our graph relationship. However, students should discuss specific place characteristics about these potential sites. Possible discussion points would be:

a. Always beware of direct comparisons between towns of roughly the same size when one is a stand-alone central place serving a large rural hinterland and the other is a suburb of a larger metropolitan area. You would expect fewer in the suburban town because there are more options in adjacent cities.

b. A savvy site manager will not automatically eliminate a town that is above the line. Although its population number may be low, there may be a large surrounding rural population that could support a pizza restaurant or there are a large number of tourists who are not included in the permanent population count. A town may be a college town, where high student population could support more restaurants than expected. Alternatively, it could be a major stopover point on interstate travel that serves a large transient market. Good site managers have an accurate demographic and socioeconomic profile of their customers, and they relate this to the characteristics of resident population in the city, the number and characteristics of tourists, and the pizza restaurant’s potential to attract customers from the surrounding region.

c. A site selection manager, however, should use the graph with care as there could be other explanations for why the number of persons per restaurant is so high. Perhaps there are many other competing restaurants serving Mexican, Greek, or Chinese food. Perhaps the town is very poor, and its population cannot afford to dine out. It may be populated by an ethnic or social group that dislikes pizza, or alternatively, the town may be “dry” and so people who like beer with their pizza go elsewhere.

b. The Philadelphia Phillies’ market area is a long narrow strip that splits south central Pennsylvania with the Baltimore Orioles. While there are certainly Orioles fans in southern PA, many are loyal Phillies fans due to in-state allegiance.

c. Northwestern New York is allocated by the GIS to Toronto, but most families in this area rooted for the Yankees 50 years before the Toronto Blue Jays were even formed. Also, U.S. residents are more likely to root for a U.S. than a Canadian team.

d. Migration can play a major role in determining team loyalties. In Arizona, for example, many residents are recent migrants to the state from the Midwest, the East and Texas. As a result, it is not uncommon for a sizable share of the crowd at an Arizona Cardinals’ games (football) to cheer for the opposition, especially if it’s the Chicago Bears, New York Giants or the Dallas Cowboys—three cities that have supplied many of the migrants to the state. In baseball, there are many Cubs fans in Phoenix.

e. Team success can also play a role. Had the Cardinals even had one winning season in their 10 years in Arizona, local fans might start have shifted their allegiances from their home region teams to the local team. Likewise, with the recent success of the Cleveland Indians, the boundaries between their fans and those of the Detroit Tigers or Cincinnati Reds might shift away from Cleveland (that is, Cleveland’s market area might expand at their expense).

f. The market area of the Pittsburgh Pirates extends too far to the south. West Virginia is economically linked to Pittsburgh through coal and steel, but people in the western parts of North Carolina and Virginia are unlikely to root for a “yankee” (lowercase y) team like the Pirates. They are probably more closely aligned with the Atlanta Braves in the South.

g. By the same token, Atlanta captures an even larger market area than shown, because for years the Atlanta Braves were the only non-Texan team representing the South.

h. Many fans in Montana and Idaho, far from any “local” team, became Braves fans because Turner Broadcasting was once the only channel showing baseball regularly.
Generally speaking, the strong regional loyalties found in places like Texas, New England, and the South outweigh distances in determining fan allegiances.
2.7 Population density in the upper plains is extremely low. As a result, a large area is needed to supply fans and an adequate TV revenue base. In addition, large metro areas are farther apart in the Great Plains than elsewhere in the nation.

2.8 Before the Arizona Diamondbacks (located in Phoenix) were added, the Colorado Rockies (located in Denver) captured an enormous market area in the West. Phoenix was one of the largest cities without a major league team, and nearby Tucson helped to beef-up potential attendance figures and television audiences. In addition, metropolitan Phoenix is one of the fastest growing cities in the country, although this information is not on the map.
Tampa, while not quite as populous as Phoenix, has a number of good-sized cities nearby, such as Jacksonville, Orlando, and Tallahassee. Another advantage for Tampa is that it will take fans only from two teams with large market areas: the Atlanta Braves and Florida (Miami) Marlins. Tampa also is located in a region with high rates of projected population growth.
Phoenix and Tampa share two other advantages. First, both areas are tourist destinations and vacation Meccas, which can add to the fan base. Second, both cities have a long tradition of hosting spring training (the Cactus League in Arizona and the Grapefruit League in Florida), and thus their populations are familiar with major league baseball.
2.9 Cities negatively affected by Phoenix expansion Change in Market Area Pop.
San Diego Padres From 11.8 to 5.5 = –6.3

Colorado (Denver) Rockies From 11.5 to 10.3 = –1.2

Texas Rangers From 16.6 to 15.7 = –0.9

Los Angeles (Anaheim) Angels From 7.7 to 7.1 = –0.6

Cities negatively affected by Tampa expansion Change in Market Area Pop.
Miami Marlins From 16.1 to 6.4 = –9.7

Atlanta Braves From 33.7 to 30.2 = –3.5

2.10 Teams with smallest market area populations, according to the nearest distance rule:

San Francisco Giants 3.9 million

Baltimore Orioles 4.5 million

Chicago White Sox 4.8 million

Pittsburgh Pirates 5.3 million

San Diego Padres 5.5 million

Cleveland Indians 5.5 million
2.11 Orioles market area went from 19.7 million to 4.5 million (according to the nearest distance rule).
2.12 This is clearly a subjective question with no absolutely right or wrong answers. Below are the pros and cons of the six cities.
Buffalo. Buffalo captures 4.9 million people, 4.5 million of which would be reallocated to Buffalo from the Toronto area. The addition of Buffalo would have the advantage of reallocating the Toronto Blue Jays market area to very near the Canadian border. Toronto, with a base of 15.6 million fans, can afford to lose some.
Indianapolis. Indianapolis captures a viable market area population of 4.8 million, but it is not without negative impacts. The already weak south side of Chicago White Sox drops from 4.8 million to a very marginal 3.9 million. If northern Indiana deserts the White Sox for an Indianapolis team, this would have negative effects on the White Sox, which already have trouble competing with the more popular north-side Chicago Cubs (although their 2005 World Series win will certainly gain more fans). The Cincinnati Reds are the biggest losers to Indianapolis, sacrificing 3.2 million of their fans, but they would still have a healthy 10.8 million-person market area. St. Louis also drops from 9.5 million to 9.1.

Memphis Memphis is a very defensible answer. Memphis would capture 9.2 million in its market area, and all surrounding teams are left with at least 6.0 million. The biggest impact is on the St. Louis Cardinals, who lose 3.5 million but retain a respectable 6.0 million. Memphis is also a good choice because the Braves dominate the southern states, so there is room for expansion in the south.
New Orleans New Orleans is also a solid choice. Their market area would contain 7.3 million, and all surrounding teams would continue to capture at least 9.4 million. New Orleans also has a large tourist/convention trade that would help bolster ticket sales, and again is a southern city where little competition exists for Atlanta.
Portland Of the six candidate cities, Portland’s market area would be the third-smallest at 5.9 million people. While there is a lot of unserved territory in the West, Portland remains a troublesome choice because it is so close to Seattle. While the GIS shows Seattle as having 20.3 million in its market area, and continuing to attract 15.0 million even if Portland were to get a team, in fact it is questionable how many fans they actually get from western Canada and the mountain west states. San Francisco falls to 3.8 million, the lowest of all teams, but that too is unrealistic because the GIS allocates most of the Bay Area population to Oakland on the basis that most areas are slightly closer to Oakland. But the San Francisco Giants arrived there first, and San Francisco is the lead city, and it just isn’t true that most people root for the A’s over the Giants because they are a few miles closer to Oakland than San Francisco.
San Antonio San Antonio appears to be a good choice. The market size of 7.4 million is large, neighboring Houston and Dallas (Texas Rangers) are still strong (11.7 and 14.6 respectively), it is a southern city, Texas has a huge baseball tradition, and San Antonio has cultural links to Hispanic south Texas and the Rio Grande Valley that Dallas or Houston do not. Furthermore, they could expect a large following from northern Mexico. Houston does take a big hit, however, losing 6.3 million fans.
In sum, most likely choices: 1) Memphis, 2) New Orleans, 3) San Antonio, 4) Portland. Of course, students should argue their case, so instructors should weigh the logic of their argument accordingly.
2.13

Team	Pre expansion, U.S.-only market area population	Post expansion, U.S. and Mexico market area population
San Diego Padres	5.5	7.3
Arizona Diamondbacks (Phoenix)	9.0	11.4
Houston Astros	18.0	16.3
Texas Rangers (Dallas)	15.7	15.6

14. 
    Monterrey, Mexico, with 80.6 million viewers!!!
    

14. 
    Barriers into Latin America might include:
    

1. 
   Problems with language for players off the field and with umpires on the field
   
2. 
   Facilities and accommodations might not be up to standards expected by Major League players
   
3. 
   Although the numbers in the market area are large, their purchasing power is much lower. Few fans in these countries could pay $30 to go see a baseball game. Admission fees would need to be very low to attract fans, thereby lowering profits.
   
4. 
   Local revenues might not cover expenses to run a Major League franchise, and local television revenues would likely be lower also
   
5. 
   Television markets must be negotiated with international companies and governments
   
6. 
   Bureaucratic delays with customs and immigration each time teams come and go
   
7. 
   Cuba is a special case—the U.S. still bans citizens from visiting there. No expansion to Havana would likely occur with Fidel Castro still in power.
   
8. 
   Local teams would likely generate tourism, but overall they might capture fewer fans from outside the market area to go to the stadium than would a U.S. city.
   
9. 
   Concern for safety and security of professional baseball players
   

Here are the leagues and divisions of Major League Baseball, starting in 2013.

American League	National League
East Division Baltimore Orioles Boston Red Sox New York Yankees Toronto Blue Jays Tampa Bay Rays	East Division Atlanta Braves Miami Marlins New York Mets Philadelphia Phillies Washington Nationals
Central Division Chicago White Sox Cleveland Indians Detroit Tigers Kansas City Royals Minnesota Twins (Minneapolis)	Central Division Chicago Cubs Cincinnati Reds Milwaukee Brewers Pittsburgh Pirates St. Louis Cardinals
West Division Los Angeles Angels Oakland Athletics Seattle Mariners Texas Rangers (Dallas–Ft. Worth) Houston Astros	West Division Arizona Diamondbacks (Phoenix) Colorado Rockies (Denver) Los Angeles Dodgers San Diego Padres San Francisco Giants

Directory: secondary -> SEC%20-%20CULTURAL%20STUDIES -> AP%20HUMAN%20GEOGRAPHY%2015 -> AP%20HUMAN%20GEOGRAPHY%20CO -> AP%20HG%20Tsts -> H%20Geog%20in%20Action
H%20Geog%20in%20Action -> Chapter 13 Breaking Up Is Hard to Do: Nations, States, and Nation-States A. Logistics
H%20Geog%20in%20Action -> Chapter 3 Tracking the aids epidemic in the United States: Diffusion Through Space and Time A. Logistics
secondary -> The state of ict/Computing delivery in Key Stage 3 and 4
secondary -> Application for Art Elective Programme (aep) Centre (2016)
AP%20HG%20Tsts -> Contemporary Human Geography, 2e (Rubenstein) Chapter 11 Industry
secondary -> Secondary Bibliography a resource of secondary sources for all acpa poets Table of Contents
secondary -> Liquefied Natural Gas: Implications for the Evolving Global Energy Market a light at the end of the pipeline
secondary -> Flooding might affect sediment