Custom Site Selection

INTRODUCTION

Purpose of Study

The purpose of this study is to find the most profitable location of any given retail store. A bakery was deemed an attractive market in Eau Claire due to the cheapness of the product that can benefit from college students on a tight budget and the attractiveness of a small local shop. Three sites were then ranked within Eau Claire to provide the best possible location for the bakery.

Scope of Study

The scope of the study was limited to Eau Claire, WI. However, to further analyze the trade area a comparison was ran against three other nearby cities--Menominee, Altoona and Osseo. All tools and analysis were limited to ESRI's Business Analyst. 

Sources and Methodology

First, to identify the most lucrative markets in Eau Claire, the demographics were analyzed. It is essential to locate the ideal customers and know if this customer base can support a business targeted toward this demographic. Next, the trade area for the product was analyzed and competitors were located to identify market saturation or if the product would have a firm hold on the market. Additionally, a gravity model comparing Eau Claire to Menominee, Altoona and Osseo was made to make further insights about the Eau Claire trade area. This was done using the gravity model. Finally, a ranking between the three most ideal sites within Eau Claire for a bakery was made.

CONCLUSIONS

Based on the demographics, a bakery could potentially have a strong market in Eau Claire, WI.
Not only could a bakery capitalize on a budget eatery, but also from the attention that is given to local shops in the area--downtown is a perfect example of this. Additionally, late-night bar customers could be drawn to the bakery in the downtown and Water Street sections of Eau Claire.

A bakery can appeal to these demographics because a bakery is a cheap little shop that can provide a positive local experience. The low per capita income at $23,887 and high college-aged population would indicate a large consumer base for cheap, on-the-go food. The ideal customer location performed in Business Analyst confirms this with the tracts surrounding campus, supporting the highest customer base.

There are no immediate competitors within the student housing area and in fact, there are no stores specifically designed as a stand-alone bakery. College residents do not have a place to eat for cheap or a quick pick-up eatery in close proximity to their location. Downtown residents and customers who are attracted to the expanding cultural scene of Eau Claire would be attracted to a local bakery and also do not have this option.

The gravity model indicated that most all Altoona citizens would travel to Eau Claire for a product while the product reach towards Menominee and Ossea is much smaller just at 8 miles. For this reason, targeting toward a local market would benefit this bakery.

RECOMMENDATIONS

Based on the conclusions and findings, the demographics indicate that there is a large consumer base for on-the-go cheap items targeted toward college students. A bakery allows for quick pick-up items as well as cheap take home goods that students are likely to purchase. It also allows for additional business from bar-goers looking for a late-night cheap snack option that Water Street food businesses typically benefit from. Additionally, Eau Claire citizens tend to appreciate and support local small shops that promote the culture of Eau Claire. For these reasons, a bakery would be a perfect market in the Eau Claire area. Since the target consumer is college students, the shop should be in close proximity to areas of college housing and the Water Street or downtown bars to benefit from other local shops and bars.

Since there are no bakeries along student housing, the bakery market is not saturated and allows for a controlling share of the customer base. Locations along Water Street would be an ideal site for a bakery. There are no competing bakeries and have limited options for budget eateries. The bakery could also see additional profits from bars and coffee shops. The second-best location would be downtown along the stretch of bars and other local shops. This area attracts many customers who like to experience the culture of Eau Claire and is only going to grow in popularity with the recent renovations and additional businesses.

Eau Claire products typically don't attract a large consumer base outside of the city itself as indicated by the gravity model. Therefore, the bakery should not try to appeal to outside customers, but rather develop a loyal local customer base. 

FINDINGS AND DISCUSSION

Demographics

Eau Claire is home to the University of Wisconsin-Eau Claire, where many students with a tight budget live in the same areas. From Water Street north a few blocks is where the majority lives, while downtown has recently experienced renovations that have made the area more popular. During the school session, eateries benefit from bar close, where there are few cheap options.

According to the tapestry segmentation, Bright Young Professionals make up 12%, in which these individuals are concerned about the environment and it impacts their purchasing decisions. This market also focuses on local experiences and eat out often. They are a loyal crowd if online ratings are positive. Furthermore, the Set to Impress demography who make up another 11% always have an eye out for a sale, have less income, and quick meals on the run are a reality of life.

The per capita income of $23,887 indicates that buyers are most likely looking for cheaper grocery items and 30% of the population aged 20-34 indicate the high college population that prefers on-the-go food that a bakery can provide.

Figure 1: Ideal Customer Location based on age and bakery expenses

Figure 1 shows the largest consumer market based on the 20-24 age group that spend their money on bakery items. This contains both the Water Street and the downtown tracts.\

Market Structure

Figure 2 shows all locations of nearby businesses that hold a bakery. Although there are three within 2 miles of the University of Wisconsin-Eau Claire, none are specifically a bakery and none are located along student housing.

Gravity Model

The gravity model is used to determine the distance from other cities that customers are willing to travel for a product. In this case the nearby city of Altoona, and Menominee and Osseo-both 24 miles away-were used. For Altoona, the gravity model indicated that customers 3 miles in this direction would travel to Eau Claire for a product. For both Menominee and Osseo, the gravity model indicated that customers 8 miles in those directions would travel to Eau Claire for a product. 

REFERENCES

All analysis used ESRI's Business Analyst.

Site Selection

INTRODUCTION

Purpose of Study

GIS is a powerful tool when examining site selections for businesses. Existing customer data, competitor locations, and demographic profiles give an accurate representation on the efficiency of existing stores and potential growth among the market. Using business analyst can provide specific ideal customer areas where a business is likely to succeed, the current popularity among all areas, and hot spot locations where a population is likely to support a business. In this project, an ideal customer area, market penetration, and hot spot analysis was performed to provide three potential Trader Joe's locations for growth in the Hennepin and Ramsey Counties in Minnesota. Finally, a ranking of the three prospective Trader Joe's was made using specific variables to give what is likely to be the most successful expansion of the franchise.

Scope of Study

All customer data was limited to simulated customer data from six Trader Joe's locations within Hennepin and Ramsey Counties in Minnesota. All demographic information and hot spot analysis used was from the ESRI geodatabase in Business Analyst.

Sources and Methodology

All demographic data and processes were performed using ESRI's Business Analyst. Ideal customer areas were based upon zip codes with above 20,000 total population and $45,000 household income. The market penetration used the number of customers divided by total population at the zip code level as well. The hot spot analysis gave total population by 1 square-mile areas. The final ranking system was based off total population, 2016 median household income, average spent per week by households at food stores $150+, and shopped at Trader Joe's in the past six months within a 1.5 mile buffer zone.

CONCLUSIONS

Central Minneapolis and St. Paul exibhit both a substantial population and disposable income. With the mean center of all customers located also in central Minneapolis, a Trader Joe's has the potential to benefit not only from nearby residents, but also surrounding customers who travel into central Minneapolis as well. There is a low market penetration in the Central Minneapolis area with plenty of potential customers and no nearby Trader Joe's sites. Additionally, in St. Paul, the customer base isn't fully exhausted and has no nearby store. The store rankings had the Southern Minneapolis ranked at number one, the Northwest Minneapolis location at number two, and the Northwest St. Paul site at three. This was based on population, income, customer tendencies, and road location.

RECOMMENDATIONS

There are enough potential consumers with disposable income to support business in central Minneapolis and St. Paul. Trader Joe's could also benefit from cross-traffic and the primary business district in central Minneapolis where any of the surrounding customers might be travelling into the heart of the city for other shops and events. Additionally, a Central Minneapolis location would boost the extremely low market penetration that exists in this area. Supported by the hot spot analysis, this area shows a healthy population for a large customer base that is currently not being taken advantage. The presitine site expansion for Trader Joe's is in the Southern Minneapolis where the current Trader Joe reach does not extend. Here, there is a high population with disposable income, that is likely to spend an above-average amount of income on household items such as groceries. The location at the intersection of interstates 35 and 94 also hold extra benefits from daily traffic. The proposed site offers ample room for parking and a moderate-to-small Trader Joe's, which would make sense for the seventh Trader Joe's in two counties.

FINDINGS AND DISCUSSION

As figure 1 shows, the ideal customer areas are around the heart of Minneapolis and east in St. Paul. There are plenty of residents in this area that have an above $45,000 salary and have over 20,000 people within the zip code. The mean center of all existing customers is actually focused in central Minneapolis as well.

Figure 1: Ideal customer (greater than 20,000 population/greater than $45,000 income) areas

While Figure 1 focuses on growth and expansion, a lot can be learned from existing customer information and current market penetration within zip codes as shown by Figure 2. Two apparent details can be gained from this report in regard to the ideal customer areas. The first being that central Minneapolis has the lowest market penetration, meaning that for the given population, there are very few customers who are able to shop at a Trader Joe's. The second being that there is a very large population of customers by the St. Paul area, but both Trader Joe's are located at a substantial distance from this region. Additionally, although the market penetration is higher than central Minneapolis, St. Paul's customer base hasn't been completely exhausted.

Figure 2: Market Penetration for existing customers of Trader Joe's

While analyzing customer data may be helpful at the zip code level, a hot spot analysis, as Figure 3 shows, can provide data and better represent patterns by categorizing by distance, such as the 1.5-mile divisions below. The three prospective Trader Joe sites all reside in high population areas and show not only that a substantial population resides to support that Trader Joe's, but that it also wouldn't take away business from other Trader Joe's sites.

Figure 3: Hot spot analysis categorized by 1.5 miles

Finally, Figure 4 ranks the prospective sites given the existing customer data, demographic information, and overall site location. The southern Minneapolis location was ranked the best potential site for Trader Joe's expansion. Here, there is a high population, disposable income, and above-average amount of income spent on household goods. This specific location is also at an advantage because it's along the intersection of interstates 35 and 94. The next best option is Northwest Minneapolis where the location benefits just slightly less from population and income, but is in a less favorable road location and budgeting for household items. Finally, the third-ranked location resides in Northwest St. Paul, where a higher current market penetration, lower population and income dictates a less favorable location to its Minneapolis counterparts.

Figure 4: Ranking of Prospective sites using customer data, demographic information, and additional factors

Figure 5 shows aerial imagery of the exact location of the best-ranked expansion for Trader Joe's according to Google Imagery. Updated information shows, however, that the building has been torn down in place of a garden and lawn space, which would reduce initial demolition costs. The lot would have to be remodeled to provide ample parking and the store would be limited to a moderate-to-small Trader Joe's. However, with six nearby locations in the two counties, this space would be of adequate size.

Figure 5: Google imagery of the top-ranked expansion site of Trader Joe's

REFERENCES

All fictional customer data was obtained from Dr. Ryan Weichelt in the Business Geographics course offered at the University of Wisconsin-Eau Claire
Analysis was performed using Business Analyst on ESRI's ArcMap.

Real Estate Analysis

INTRODUCTION

This specific study demonstrates the ability to examine the spatial features as well as specific field-related features to provide an accurate analysis. An important function of real estate is location; the location of a house within a city or country will largely determine its asking price. Spatial analysis in real estate can provide a target consumer, and important factors in determining a fair asking-price such as its connection to the local economy, distance from recreation and entertainment, the safety of the neighborhood, and ward-specific codes.

CASE STUDY

The house actually listed for sale and chosen for analysis was 303 Garfield Avenue, located in the 3rd Ward of Eau Claire, Wisconsin. Our analysis was broken into three scopes: the house, the neighborhood, and the city. For the features of the house and a reference asking price, Zillow.com was used.

303 Garfield Avenue

For the house, a regression analysis was performed using Eviews which accounted for the number of bedrooms and bathrooms, lot size, square footage of property, and an indicator of quality of the interior. These dependent variables possesed an R-squared value of 0.91 (on a scale of 0.0-1.0) which gives the strength of correlation between the above variables listed and our output, the final asking price. The program used the following equation to give an output asking-price:

13670 - 12,001.12  BDRMS + 3627.851 BATHRMS + 2.738 LOTSIZE + 90.45 SQFT + 12,956.05 CHIMNEY=Price

With the correct information for 303 Garfield plugged in, the equation is as follows:

13670 - 12,001.12(3) + 3627.851(1.5) + 2.738(10,018) + 90.45(2,048) + 12,956(1) = $208,735.66

Figure 1 shows some of the property-specific features as listed: 3 bedroms, 1.5 bath, fireplace with chimney, large dining room, vintage hardwood flooring, cherry caninets, granite countertops, newly painted interior, ladscaped garden, 2-car garage, 2,048sqft-unfinished basement, 3rd-floor office/workspace.

Figure 1: A peak into 303 Garfield Avenue, Eau Claire, WI

3rd Ward

The 3rd Ward is a highly-respected neighborhood that is located along the University of Wisconsin-Eau Claire campus. Figure 2 shows this ward's owner profile, where almost all of the surrounding houses are comprised of single family residential. 

Figure 2: 3rd Ward of Eau Claire, WI

Although the 3rd Ward comprises campus, it's away from roudy college student-rentals and duplexes and has strict code enforcement to maintain a respected exterior aesthetic. An active police force also patrols the neighborhood to maintain its distance from the problems that college students may bring. The safety of this neighborhood compared to other wards is shown below in Figure 3.

Figure 3: Crime reports from Jan-March 2017 in Eau Claire, WI

Finally, this neighborhood falls into the Lakeshore Elementary School District, which holds above-average academic scores compared to the rest of the state.

Eau Claire

When looking at Eau Claire itself, real estate is rapidly taken off the market with the city expanding and absorbing into the nearby Altoona. Eau Claire's growth has also given way to an increased availability in entertainment and recreation as well. The 3rd Ward is situated between Water Street (Eau Claire's infamous bar scene where many college students frequent) and the downtown bars (featuring a more laid-back experience and live music). In all, there are 29 bars located 1 mile away from 303 Garfield and an additional 26 in 2 miles--10 of which offer live music. 

Phoenix Park (located less than a mile away) is a beautiful park along the confluence of the Eau Claire and Chippewa Rivers that hosts music in the park, the farmers' market, and is a great starting point for a tube ride down the river. Owen Park (also less than a mile away) hosts free music and movies during the summer. Demmler, Kappus, and Wilson parks are located within the 3rd Ward and hold a community garden, basketball courts, socccer fields, and playgrounds. 

Additionally, there are 7 county parks in total and over 30 miles of biking trails offering ample opportunity to enjoy the scenic outdoors Eau Claire provides. The Eau Claire and Chippewa Rivers provide excellent fishing as well as Lake Altoona, Lake Hallie, and further out Lake Wissota.

CONCLUSION

Our final listing price for 303 Garfield was $208,735.66 well below its $220,000 price tag listed on Zillow and the $267,000 3rd ward-average asking price. With it's proximity to the University of Wisconsin-Eau Claire, the safety of the 3rd ward, and the location in the heart of Eau Claire itself, the target consumer would be a middle to upper-class family associated with the university and/or interested in the community.

We stuck with the regression analysis output of $208,735.66 because Eau Claire is an expanding city with houses rapidly being sold. The below-Zillow price and average 3rd Ward-price would hopefully drive up interest and start a bidding war for the property. Our asking price would be considered a fair asking price for the house features itself, but is undervalued due to its location and the consumer-flooded market. The strategy here would be to flood the number of initial bids and encourage a consumer to overpay in the midst of a bidding war.

Coffee Customer Base and Competitors in San Francisco, California

EXECUTIVE SUMMARY

Purpose and Methodology

The purpose of this study is to analyze the customer base for the coffee and doughnut shops given to combine efforts and maximize potential earnings. Trade areas based on customer base and drive and walk times for customers are provided along with all competitors in the area.

For each business, a mean center of their respective customers is calculated from the customer data provided. Using business analyst, all known coffee shops in the San Francisco area are then plotted. Finally, trade zones were established for each store first based on customer location and then on customer drive and walk distance. A business report was then produced for the customer location trade zones, where a Spending Potential Index (SPI) which is household-based and represents the amount spent for a product or service relative to a national average of 100 was then produced for bakery and cereal items. This report also gave total population and average age.

Findings and Conclusions

While there isn't an abundance of intersecting customers between stores, Store 2 possesses some customers who drift north into Store 1's area. There is a much greater clustering of customers around Store 1 compared to that of Store 2, perhaps because of the vast number of competitors located in the northeast portion of San Francisco as shown by Figure 2. Overall, there are far fewer coffee competitors located in the southern section of San Francisco.

Store 2 has a much larger customer radius where 80% of the customer base nearly reach twice as far as Store 1 in some locations. The business report for these customer trade zones showed a much higher SPI along all three of Store 2's trade zones. This indicates that consumers here are more likely to spend their money on bakery items and would be beneficial to a producer to locate themselves here. The total population was also much higher ,indicating a larger potential market for consumers who are located nearby to existing customers. The average age for Store 2 was also higher, only intensifying the probability that more people in the area would drink coffee.

Recommendations for Combining Efforts

Based on the previous conclusions, it would be far more beneficial to open up a singular store at Store 2's location for the following reasons:

• Wider consumer base
• Far less competition
• More willingness to spend money on bakery items
• Higher potential customer base

Closing Store 1 would run the risk of losing existing customers; However, by combining stores, the new store will have a chance at attracting more customers. It would also most likely not be possible to pay utilities for multiple stores and transport fresh bakery or coffee every day daily from store-to-store.

Contents

EXECUTIVE SUMMARY

Purpose and Methodology

Findings and Conclusions

Recommendations for Combining Efforts

INTRODUCTION

Purpose of study

Scope of study

Sources and Methodology

CONCLUSIONS

RECOMMENDATIONS

FINDINGS & DISCUSSION

REFERENCES

INTRODUCTION

Purpose of Study

The purpose of this study is to analyze the customer base for the coffee and doughnut shops given to combine efforts and maximize potential earnings. Trade areas based on customer base and drive and walk times for customers are provided along with all competitors in the area.

Scope of Study

All customer data was limited to what was provided by both stores and all competitors in the San Francisco area was limited to the database held in Business Analyst.

Sources and Methodology

All mapping was done on ArcMap which was used to perform the mean center function. All customer base data, customer location trade zones, customer drive and walk trade zones, competitors, and the business report was produced using Business Analyst.

CONCLUSIONS

While there isn't an abundance of intersecting customers between stores, Store 2 possesses some customers who drift north into Store 1's area. There is a much greater clustering of customers around Store 1 compared to that of Store 2, perhaps because of the vast number of competitors located in the northeast portion of San Francisco as shown by Figure 2. Overall, there are far fewer coffee competitors located in the southern section of San Francisco.

Store 2 has a much larger customer radius where 80% of the customer base nearly reach twice as far as Store 1 in some locations. The business report for these customer trade zones showed a much higher SPI along all three of Store 2's trade zones. This indicates that consumers here are more likely to spend their money on bakery items and would be beneficial to a producer to locate themselves here. The total population was also much higher ,indicating a larger potential market for consumers who are located nearby to existing customers. The average age for Store 2 was also higher, only intensifying the probability that more people in the area would drink coffee.

RECOMMENDATIONS

Based on the previous conclusions, it would be far more beneficial to open up a singular store at Store 2's location for the following reasons:

• Wider consumer base
• Far less competition
• More willingness to spend money on bakery items
• Higher potential customer base

Closing Store 1 would run the risk of losing existing customers; However, by combining stores, the new store will have a chance at attracting more customers. It would also most likely not be possible to pay utilities for multiple stores and transport fresh bakery or coffee every day daily from store-to-store.

FINDINGS AND DISCUSSION

Figure 1 shows customer locations for both business, including the mean center of customers for each. Store 1 has a greater clustering of customers located nearby and can be represented by the mean center located fairly close to the actual location of the store. Store 2 has a broader customer base and is less clustered with the mean center drifting somewhat north toward Store 1. For the most part, Store 1's customers are located fairly near to the northern side of San Francisco, whereas Store 2 has customers drifting north and mixing with Store 1's area.

Figure 1

Figure 2 then shows both store's customer base as one and plots all coffee competitors in the San Francisco area. There is a great clustering of competitors in the northeast and disperses gradually moving away from the clustering. There are far fewer coffee shops in the southern part of San Francisco.

Figure 2

Figure 3 establishes trade areas for each store based on customer data provided. Store 1 has a much smaller radius of customers and a greater clustering of customers located nearby to the store. Store 2 has a much larger customer radius and a far greater dispersion along the San Francisco area. The trade zones do not intersect, meaning that 80% of each store's customers are not located in the same region in San Francisco.

Figure 3

After these trade zones were established, Business Analyst produced a report for each zone. The focus was then placed on bakery and cereal products where a Spending Potential Index (SPI) which is household-based and represents the amount spent for a product or service relative to a national average of 100, was produced. For trade area 1 the SPI was 130, 151, and 148 for its 40, 60, and 80% customer zones, respectively. For trade area 2 the SPI was 142, 151, and 152 for its 40, 60, and 80% customer zones. Another key statistic was total population and average age for each 80% customer zone for each store. For Store 1, the total population was 136,356 compared to Store 2's much larger 160,365. For Store 1, the average age was 37, compared to that of Store 2's 40-year-old average age.

Figure 4 shows another trade area for both stores, this time based on customer drive and walk distance. Store 1 has a fairly square shape, meaning that from all directions from the store, it is accessed with the same difficulty. The radius is also slightly larger than Store 2, meaning that it's slightly harder to access, but not significantly.

Figure 4

REFERENCES

ESRI, ArcMap, Business Analyst.

Population and Cultural Analysis of Jacksonville, Florida

EXECUTIVE SUMMARY

Purpose and Methodology

The purpose of this study is to analyze Jacksonville, Florida’s population structure and the overall cultural and service sectors of the city. This information can then be used for BK Investments to make a geographically-informed decision on which businesses or industries in which to invest.

All data was obtained from the US Census Bureau from estimates of 2015 population data. Population data obtained was then transferred to Microsoft Excel to produce a population pyramid for population analysis. For calculated dependency ratios, percent Hispanic/White, location quotients, and percent of service industries, data for Jacksonville, Duval, Florida, and the US was observed from the US Census Bureau website and calculated.

Findings and Conclusions

Based on the findings of the population structure and cultural and service sectors of Jacksonville, FL, the following conclusions can be made:

• The high percentage in the finance industry in Jacksonville’s economy compared to the state and national average suggest there are a vast number of competitive financial firms in the area
• The population structure as indicated by Figures 1 and 2, show a clustering population at the 20-30 range and an echo beginning to form with newborn babies
• Although nationally, the Hispanic population is rising and Florida has a higher-than-average Hispanic population compared to the US, Jacksonville itself is under half the national average
• Although Florida is known for retiree migration, Jacksonville again finds itself the exception with a below state and national average in the elderly dependency ratio.

Recommendations for Business Investment

After considering the findings and conclusions drawn on Jacksonville, FL, the following recommendations can be made for an informed business investment:

• Successful businesses of the same industry tend to cluster in one area, and the staggering percentage of financial firms in Jacksonville provides a good selection of profitable firms to invest money
• Investing in financial firms, compared to the baby industry, has a far greater capacity of earning higher profits
• Perhaps with a large population of 20-30 year-olds and a high percentage of people working in the financial sector, an investment in high-end retail companies that sell professional clothing would be a worthwhile investment
• With an echo-effect of newborn babies, a less risky and slightly less profitable investment could be made in the baby-related industries such as toy companies, diaper providers, and daycares
• Capitalizing on a rising Hispanic population, especially true to Florida, does not seem wise for the city of Jacksonville and related businesses should be avoided
• Capitalizing on the cycle of elderly migrants to Florida should also be avoided in Jacksonville due to its below-average statistics in the elderly population.

INTRODUCTION

Purpose of Study

The purpose of this study is to analyze Jacksonville, Florida’s population structure and the overall cultural and service sectors of the city. This information can then be used for BK Investments to make a geographically-informed decision on which businesses or industries in which to invest. 

Scope of Study

This study investigates:

• population structure of Jacksonville
• dependency ratios for the youth and elderly
• total Hispanic and White populations
• economic service sectors

and compares this data to its county (Duval), the state of Florida, and to the US.

The scope of this study was limited to US Census Data estimates for the year of 2015, which typically held an accuracy of 98-99%. Due to time constraints, ethnic data for the cultural sector was only collected for Hispanic and White populations. For similar reasons, only six categories were used to analyze the economic service sectors. 

Sources and Methodology

All data was obtained from the US Census Bureau from estimates of 2015 population data. Population data obtained was then transferred to Microsoft Excel to produce a population pyramid for population analysis. Percentages of total male and female numbers for age categories were made into a diverging horizontal bar graph. For calculated dependency ratios, percent Hispanic/White, location quotients, and percent of service industries, data for Jacksonville, Duval, Florida, and the US was observed from the US Census Bureau website and calculated.

To find total population, dependency ratios, and percentage of Hispanic/White populations found in Figure 2, the number for each was divided by the total number of that region. For example, the total population of ages 0-14 for Florida (166,002) would be divided by the total population of Jacksonville (846,951) to produce a percentage of population aged 0-14 in Jacksonville (19.6). The same was done for the county, state and nation data.

To calculate the location quotients in Figure 3, the data for each category in Jacksonville, Duval, and Florida was each separately divided by the nation’s data for that category. The same methodology was used for Figure 4 to find location quotients of service sectors.  

CONCLUSIONS

Based on the findings of the population structure and cultural and service sectors of Jacksonville, FL, the following conclusions can be made:

• The high percentage in the finance industry in Jacksonville’s economy compared to the state and national average suggest there are a vast number of competitive financial firms in the area
• The population structure as indicated by Figures 1 and 2, show a clustering population at the 20-30 range and an echo beginning to form with newborn babies
• Although nationally, the Hispanic population is rising and Florida has a higher-than-average Hispanic population compared to the US, Jacksonville itself is under half the national average
• Although Florida is known for retiree migration, Jacksonville again finds itself the exception with a below state and national average in the elderly dependency ratio.

RECOMMENDATIONS

After considering the findings and conclusions drawn on Jacksonville, FL, the following recommendations can be made for an informed business investment:

• Successful businesses of the same industry tend to cluster in one area, and the staggering percentage of financial firms in Jacksonville provides a good selection of profitable firms to invest money
• Investing in financial firms, compared to the baby industry, has a far greater capacity of earning higher profits
• Perhaps with a large population of 20-30 year-olds and a high percentage of people working in the financial sector, an investment in high-end retail companies that sell professional clothing would be a worthwhile investment
• With an echo-effect of newborn babies, a less risky and slightly less profitable investment could be made in the baby-related industries such as toy companies, diaper providers, and daycares
• Capitalizing on a rising Hispanic population, especially true to Florida, does not seem wise for the city of Jacksonville and related businesses should be avoided
• Capitalizing on the cycle of elderly migrants to Florida should also be avoided in Jacksonville due to its below-average statistics in the elderly population.

FINDINGS AND DISCUSSION

The findings of this study are presented into two categories:

• The population structure
• The cultural and service sectors.

The first of which will present a population pyramid and the following, calculated dependency ratios and location quotients. Discussions for each will follow each figure.

Population Structure

From the data gathered from the US Census Bureau, Figure 1 shows the resulting population pyramid representing the overall population structure of Jacksonville, Florida.

Figure 1

Jacksonville, like the rest of the nation, exhibits a larger population than expected around the 50-65 range because of the baby boomers—a result of returning troops from World War II.  Beyond that, a clear uprising of population exists at the 20-30 range. From 10-20, the population then drastically decreases, but then again begins increasing at the under 5 range. This can be viewed as an echo effect from the large population of 20-30 year-olds who are in the prime age of reproduction. The number of newborn babies in the next couple of years would be expected to grow as the echo effect comes full cycle.

Cultural and Service Sectors

To further understand the population of Jacksonville, Florida, additional cultural data was collected and shown in Figure 2. Cultural data includes total population, dependency ratios for the youth and elderly, and Hispanic and White population numbers for Jacksonville, its county (Duval), state (Florida), and the US.

Figure 2

As indicated above, the dependency ratio for both the youth and elderly falls below the US average. Similarly, the total ethnic populations of Hispanics and Whites also falls below the nation’s average. Although Florida itself holds a reputation for and tallies well above the US average for elderly citizens and Hispanic population, the city of Jacksonville is an exception to the state average. Differently from the Florida average, Jacksonville holds a higher dependency ratio for the youth. Finally, with a well-below state and national average for Hispanic and White population, other ethnicities such as African American, Asian, or Native American are likely to reside in Jacksonville.

To better envision Jacksonville, Duval, and Florida compared to the nation’s average, Figure 3 shows the location quotient compared to that of the US average for youth and elderly dependency ratios and Hispanic and White population numbers.

Figure 3

Just as the discussion following Figure 2 stated, the youth dependency ratio for Jacksonville is considerably higher than that of Florida, and the elderly dependency ratio and Hispanic/White populations are well under Florida’s average, as well as the nation’s average. Now that the population and cultural data of Jacksonville has been examined, an economic understanding should be made before investment.

Figure 4 gives an economic understanding of Jacksonville by evaluating the percentage of total industry for six major industries and compares it to the state of Florida and the US average by obtaining a location quotient.

Figure 4

As shown by Figure 4, for the most part Jacksonville’s percentage of industry remains fairly consistent with Florida’s and the US percentage besides the finance industry. With a staggering 1.76 location quotient compared to the US, Jacksonville has a well-above average percentage in the finance sector. 

REFERENCES

Data Access and Dissemination Systems (DADS). "American FactFinder." U.S. Census Bureau.

Accessed February 07, 2017. http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml.