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:
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
Interconnected urban system
Specialized urban (economic) functions
Universal, generic functions that all cities provide
Cities as central place to which people travel, market areas from which people travel
II. Central place terminology
Central place functions
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
Defined in terms of minimum:
Low-order goods and services
High-order goods and services
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
Based on work by Christaller and Lösch
Featureless landscape (no roads, no barriers)
Uniform population distribution
Infinite plane (goes on forever—no boundary effects)
Behavioral assumptions (implied, but not explicitly stated in text)
Consumers shop at the closest place where a good is available
Consumers cannot not go beyond the range of the good
Firms’ market areas must equal or exceed threshold of the good
Hexagonal market areas
Hexagons because nonoverlapping circles leave some areas unserved
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
Other names for the game
New York City, 1842–45
National Association of Base Ball Players, 1857
Early professional baseball
Cincinnati Red Stockings, 1869
National Association of Professional Baseball Players (forerunner to the National League) was founded in 1871 with nine teams
Early league cities were central places, with large thresholds and market areas. Locations reflected the existing urban hierarchy.
World War II
Race and ethnic relations in baseball
Population shifts and team relocations
Range increases with TV, thresholds become more regionalized
Brooklyn Dodgers and New York Giants moved to West coast in 1957
Boston Braves moved to Milwaukee in 1953
St. Louis Browns became the Baltimore Orioles in 1954
Philadelphia Athletics moved to Kansas City in 1955
Washington Senators became the Minnesota Twins in 1961
Growth of the South attracts teams
Expansion in 1961
Southern California (Angels)
New York (Metropolitans, nicknamed the Mets)
Houston (Colt 45s, who later became the Astros)
San Diego (Padres)
Kansas City (Royals)
Seattle (Mariners) and Toronto (Blue Jays) in 1977
Colorado (Rockies) and Florida (Marlins) in 1993
Tampa Bay (Devil Rays) and Arizona (Diamondbacks) in 1998
Unfair competition issue: Media rights
Large versus small broadcast areas widen revenue and payroll disparities
New stadium issue
Relocation of Montreal Expos to Washington Nationals
Collective bargaining agreement
New wild card teams
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.
Nevertheless, you will see a tendency for somewhat regular spacing of major league cities.
You will also see that minor league cities are more numerous, more closely spaced, and have smaller market areas.
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.
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)
Number of Pizza Parlors
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.
Activity 2: Market Area Geography
2.1 Something like this:
2.2 There are fewer major than minor league teams (actually 30 major league teams versus 204 minor league teams, but don’t ask students to count them). Keep in mind that the blue layer is all teams, not just minor league teams. We did it that way because, otherwise, the minor league teams capture fans who are actually closer to major league cities.
2.3 Major league market areas are larger than minor league market areas.
2.4 Major league teams are farther apart than minor league teams.
2.5 Major league teams are in larger cities than minor league teams.
2.6 There are many good answers to this question. Here are a few samples:
a. There are four cities with two teams: New York, Los Angeles, Chicago, and San Francisco (the four largest metro areas in the U.S.). The GIS draws the boundaries based on the exact location of their stadiums, which is why the San Francisco Giants, on the west side of San Francisco Bay, lose the inland portion of northern California to the Oakland Athletics (A’s), who are on the eastern side of San Francisco Bay. In fact, the Giants moved to the Bay Area (from New York) before the A’s moved there (from Kansas City). The Giants probably have more loyal fans and a larger following in northern California than the A’s.
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.
Pre expansion, U.S.-only market area population
Post expansion, U.S. and Mexico market area population
San Diego Padres
Arizona Diamondbacks (Phoenix)
Texas Rangers (Dallas)
Monterrey, Mexico, with 80.6 million viewers!!!
Barriers into Latin America might include:
Problems with language for players off the field and with umpires on the field
Facilities and accommodations might not be up to standards expected by Major League players
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.
Local revenues might not cover expenses to run a Major League franchise, and local television revenues would likely be lower also
Television markets must be negotiated with international companies and governments
Bureaucratic delays with customs and immigration each time teams come and go
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.
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.
Concern for safety and security of professional baseball players
Here are the leagues and divisions of Major League Baseball, starting in 2013.
D. Discussion Questions Do you think taxpayers would help pay for new baseball stadiums in order to attract new teams or keep old ones?
What would you recommend to Major League Baseball to solve the problem of small-market teams that cannot afford expensive payrolls and therefore have difficulty in attracting or keeping the best players?
Link this activity to the idea of a culture region in Chapter 2 and discuss how sports teams create and sustain loyalty through regional identity and symbolism. Do sports affiliations arise from regional identification or do sports teams help to create those regional identities?
What are the effects of migration patterns on distorting the map of team allegiances? Do migrants bring their team affiliations with them or do they keep past loyalties? What affects the pace at which new residents bond with new teams versus maintaining their traditional loyalties?
What would happen if a goods’ threshold (measured in miles) is larger than its range (also measured in miles)?
What kinds of goods or services would you expect to find in _____________ [insert a large city in your region] that would not be available in ______________ [insert a smaller city]?
Within a baseball market area, do you think attendance, TV viewing of games, and purchases of T-shirts would exhibit distance decay?
What other businesses besides sports franchises could we have used for this chapter to illustrate a two-level hierarchy? (daily and weekly newspapers, hub airports and airports served by regional airlines only, hospitals and doctors’ offices, etc.)
We instruct the students to split the distance evenly between each city pair in order to keep things simple at this level. Is this a realistic assumption? What would be a better assumption, and how might it be operationalized? (e.g., gravity model)
What might be a better way of estimating market areas for cities with two teams (NY, LA, Chicago)?
What would be required to make expansion into Latin America work?
Do you think Latin American expansion is a good idea?
What about including Cuban or Venezuelan teams? Would this be a problem?
Could Major League Baseball in Mexico help U.S. and Mexico with other foreign policy and cultural misunderstandings?
How could you use the data and scatter diagram in Activity 1 to estimate the threshold for pizza restaurants?
What would the scatter diagram for gasoline stations look like compared with that for pizza? How about for hospitals? Afghan restaurants? Major and minor league baseball teams?
How can the lessons of this chapter be applied to the placement of shopping centers?
In the latter half of the nineteenth century, as the railroads expanded across the Midwest and Great Plains, towns developed at stations along the rail lines in a linear fashion. In historical geography, this is known as the “mercantile model” of urban system development. How do you suppose this linear system would mesh with the hexagonal system of central place theory?
What effect do you think online shopping is having, if any, on the central place theory urban hierarchy?
What is the relationship between hierarchical diffusion (Chapter 3) and high-order goods (Chapter 9)? Give some examples of goods and services with large thresholds vs. goods and services that are simply at an early stage of diffusing hierarchically.
Given their location in the country’s third largest metropolitan area, what can possibly explain the Cubs’ failure to win a World Series in over a century? (Just kidding, this is a philosophical or possibly theological question!)
E. Question Bank 1. True/False In the urban hierarchy, small towns tend to house businesses with small thresholds.
2. True/False The locational choices of tertiary sector firms are driven by the same economic and geographic factors as for secondary sector firms.
3. True/False Low-order central places are more numerous than high-order central places.
4. True/False High-order central place functions are obtained on a frequent basis, they require small market areas to be profitable, and people are unwilling to travel far to obtain them.
5. True/False Minor league baseball cities are more numerous and more widely spaced than major league baseball cities.
6. True/False Major league baseball cities have a larger threshold than minor league baseball teams.
7. True/False Minor league baseball cities have a larger threshold than majorleague baseball teams.
8. True/False The number of pizza restaurants per city decreases with city size.
9. True/False. In the most recent baseball negotiations between owners and players, the large-market teams wanted more revenue sharing, while the small-market teams wanted no limit on a team’s player payroll.
10. True/False On the scatter diagram showing population (x-axis) versus the number of pizza restaurants (y-axis) for cities of different sizes, the dots for tourist destinations tended to be below the line of best fit.
11. True/False In central place theory, the hexagons represent market areas of central places.
12. True/False Major league baseball teams generally have a larger range than pizza places.
13. True/False There are no exceptions to the market areas drawn using the nearest-team rule (the same process you practiced doing on HGIA pp. 265–267).
14. True/False There is an extremely low number of exceptions to market area boundaries drawn using the nearest-team rule (the same process used to determine major and minor league baseball fan base areas).
15. Central place theory is concerned with cities as:
a. manufacturing centers
b. transportation centers
c. political capitals
* d. providers of goods and services
e. noneconomic entities
16. Which of the following is the highest-order central place function?
* b. are farther apart than low-order central places
c. are more numerous than low-order central places
d. have small trade areas for their goods and services
18. Low-order central place functions:
a. have large ranges and large thresholds
b. have small ranges but large thresholds
c. have large ranges but small thresholds
* d. have small ranges and small thresholds
19. The minimum area (or population) needed for a business to break even is called its:
* c. threshold
d. market area
20. Which was not one of the cities that the software considered for future expansion of major league baseball?
* c. Salt Lake City
d. Washington, D.C.
21. Sometimes, estimating market areas by assigning areas to their nearest center will create some unrealistic market areas. This occurred in our case study, in which an existing team was estimated to have an unrealistically small market area population of 3.9 million. Which team was it?
a. Baltimore Orioles
b. Texas Rangers
c. Seattle Mariners
d. St. Louis Cardinals
* e. San Francisco Giants
22. In 1900, professional baseball teams were found in which regions of the United States?
* a. Northeast
b. Northeast and Midwest
c. Northeast, Midwest, and West Coast
d. Northeast, Midwest, West Coast, Texas, and Florida
e. throughout the United States
23. Compared with the East Coast, major and minor league baseball teams in the Great Plains are:
a. more densely spaced
* b. less densely spaced
c. spaced about the same
24. In central place theory, market areas are presumed to resemble:
* d. hexagons
25. A system of cities consisting of various levels, with few cities at the top level and increasingly more settlements on each lower level, is known as an:
26. Urban-economic geographers refer to a city or town that provides goods and services to the surrounding population as a ________ place.
* d. central
27. Using a scatter diagram of population (x-axis) versus the number of pizza restaurants (y-axis) for cities of different sizes, we were able to estimate the ____________ of a pizza restaurant.
* a. threshold
d. central place function
e. market area radius
28. Central place theory is concerned with cities as:
a. manufacturing centers
b. transportation centers
c. political capitals
* d. providers of goods and services
e. noneconomic entities
29. Which of the following is the highest-order central place function?
a. neighborhood bank
b. gas station
c. grocery store
* d. rare blood disease specialists
e. family doctor
A-level central place
B-level central place
C-level central place
30. In the diagram above, a shopper located at the * is likely to shop for its lowest-order goods at the closest town of type:
* b. B
d. cannot be determined
31. The higher-order central places are type:
* c. C
d. cannot be determined
32. The maximum distance a customer is willing to travel to purchase an item is known as the:
d. market area
33. Why is the ratio of residents/pizza place higher in urban than rural areas? Choose two. (Credit will be granted only if you choose both correct answers and only those two answers.)
a. Major pizza franchises have agreed to limit their stores in an effort to charge higher prices to urban consumers.
*b. In urban areas consumers have a wider variety of options for eating out.
*c. Urban customers have higher expectations in terms of quality and décor.
d. because there is always room for a new pizza place in the urban market
34. Low-order goods and services are provided by:
a. small towns
b. medium-sized cities
c. large cities
*d. all of the above
35. High-order goods and services are provided by:
a. small towns
b. medium-sized cities
*c. large cities
d. all of the above
36. Which of the following is the lowest-order central place function?
*a. gas station
c. shopping mall
d. Porsche dealership
e. furniture store
37. How do the number of major league teams compare to the number of minor league teams?
a. There are more major league teams.
*b. There are more minor league teams.
c. There is no noticeable difference in the number of teams.
38. How does the size of the market areas of major league teams compare to the size of the market areas of minor league teams?
*a. Major league market areas are bigger.
b. Minor league market areas are bigger.
c. There is no noticeable difference in the size of the market areas.
39. How does the spacing of major league teams compare to the spacing of minor league teams?
*a. Major league teams are farther apart.
b. Minor league teams are farther apart.
c. There is no noticeable difference in the spacing of the teams.
40. How does the size of the host cities of major league teams compare to the size of the host cities of minor league teams?
*a. Major league teams tend to be in larger cities.
b. Minor league teams tend to be in larger cities.
c. There is no noticeable difference in the size of the host cities.
41. If you collected the pizza data properly, constructed the log-log graph properly, and drew your line of best fit properly, the line would intercept the x-axis at approximately:
*a. 1,000–2,000 persons
b. 100–200 persons
c. 10,000–20,000 persons
d. 10–20 pizza restaurants
e. 100–200 pizza restaurants
f. 1,000–2,000 pizza restaurants
42. In Activity 1 of Chapter 9, we were able to use the x-axis intercept in the log-log scatter diagram to estimate the ____________ of a pizza restaurant.
d. central place function
e. market area radius
43. In the graph in Activity 1 of Chapter 9, what did the axes measure?
a. X measured population, Y measured number of pizza restaurants
b. X measured number of pizza restaurants, Y measured population
*c. X measured the log of the population, Y measured the log of the number of pizza restaurants
d. X measured the log of the number of pizza restaurants, Y measured the log of the population
44. The logarithm of a number is:
a. the number times itself
b. the number in base 10
*c. the power to which you would have to raise 10 to get the number
d. the number divided by 10
e. the power to which you would have to raise the number to get 10
45. The log of 100 is:
46. If we had used a regular x-y scatter graph for Chapter 9, Activity 1 rather than a log-log graph, one of two undesirable outcomes would have happened. (You must choose both correct answers to get credit.)
*a. To make the point for the largest city that would fit on the graph, many of the points for the smaller towns would have been squished together in the bottom-left corner of the graph.
*b. To make the points for the smaller cities legible, it would be nearly impossible to fit the largest cities on the same graph on a normal-sized piece of paper.
c. The line of best fit would not have been a straight line.
d. We would have needed to draw two different points for each city.