{"id":6632,"date":"2020-10-26T02:54:26","date_gmt":"2020-10-26T02:54:26","guid":{"rendered":"https:\/\/data-science.gotoauthority.com\/2020\/10\/26\/mcdonalds-expansion-strategy-analysis-in-nyc\/"},"modified":"2020-10-26T02:54:26","modified_gmt":"2020-10-26T02:54:26","slug":"mcdonalds-expansion-strategy-analysis-in-nyc","status":"publish","type":"post","link":"https:\/\/wealthrevelation.com\/data-science\/2020\/10\/26\/mcdonalds-expansion-strategy-analysis-in-nyc\/","title":{"rendered":"McDonald’s Expansion Strategy Analysis in NYC"},"content":{"rendered":"
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\"\"\"\"<\/figure>\n<\/div>\n

Link to GitHub Repository<\/a><\/p>\n

Introduction<\/h2>\n

McDonald\u2019s is the backbone of America\u2019s fast-food industry, generating about $7.84bn across more than 13,800 restaurants in the United States. It is no mistake that their expansion strategy has benefitted them greatly. In high density urban areas such as New York City, it is especially imperative that their strategy is adaptive to the dynamic environment. In New York City, McDonald\u2019s restaurants are as common as pigeons; setting the fast-food giant the focus of this exploratory data analysis project.<\/p>\n

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Focus Question<\/h3>\n

How does McDonald\u2019s choose their restaurant location? What are the factors that play into it?<\/p>\n

Initial Analysis<\/h3>\n

To get an understanding of McDonald’s location strategy, first it helps to know where their chains are actually located. Utilizing the longitude, latitude, city, and state variables from a Kaggle dataset for McDonald\u2019s locations in the United States, here is the result.<\/p>\n

\"\"\"\"
Screenshot of McDonald’s Manhattan locations from R Shiny App<\/figcaption><\/figure>\n

The first noticeable detail is how close each restaurant is to one another, a trend that occurs in every borough. But taking a closer look reveals more interesting insights. Restaurants are commonly located near transit centers such as bus stops and subway stations.<\/p>\n

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But wait, there’s more!<\/p>\n

– Ronald M. Popeil<\/cite>\n<\/p><\/blockquote>\n<\/div>\n<\/div>\n

After some more inspection, every McDonald\u2019s is also suspiciously near a park, playground or school. In the following set of maps, the blue circle markers represent schools.<\/p>\n

This makes sense when you look at the demographics they serve. McDonald’s is a family and budget friendly restaurant chain mainly targeting families and lower income individuals, which includes students. However, not every cluster of schools or parks has a McDonald\u2019s located in it. So, what are the prerequisites?<\/p>\n

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New Angle<\/h3>\n

What makes one set of park, playground, or school locations more attractive than others?<\/p>\n

    \n
  1. population density?<\/li>\n
  2. economic status of the surrounding area?<\/li>\n<\/ol>\n

    The economic status associated with the area each restaurant is found in sounds more interesting. Utilizing zip codes and income information extracted from a Kaggle dataset on the US household income statistics by geographic location, this new angle can be tackled. Since New York City has 176 unique zip codes designated for major neighborhoods in the city this works.<\/p>\n

    New Driving Question<\/h3>\n

    Does the average household income level of a zip code determine the amount of McDonald\u2019s within it?<\/p>\n

    \n

    Results<\/h2>\n

    Zip codes that contain X amount of McDonald\u2019s restaurant(s) have an average household income of:<\/p>\n

      \n
    • 1 restaurant: $76,323<\/li>\n
    • 2 restaurants: $67,307<\/li>\n
    • 3 restaurants: $72,680<\/li>\n
    • 4 restaurants: $69,450<\/li>\n
    • 5 restaurants: $53,434<\/li>\n<\/ul>\n
      \"\"\"\"<\/figure>\n

      What does this show?<\/h4>\n

      McDonald\u2019s targets neighborhoods where the household income level is between $50,000 and $77,000. McDonald’s are more frequent in areas that are close to the median household income in New York City, for instance the four bullet point above. <\/p>\n

      This data makes sense when thinking about who McDonald’s targets, take for example some of their menu items:<\/p>\n

        \n
      • The $1 $2 $3 Dollar Menu<\/li>\n
      • Happy Meals for kids<\/li>\n<\/ul>\n
        \n

        Next Steps<\/h2>\n

        This is just the tip of the iceberg for McDonald’s location strategy in New York City. Moving forward I want to further explore sub filters McDonald’s potentially uses for settling within their desired neighborhood. Specifically, I want to look at high traffic areas with the help of a heat map, and measure the average influx\/outflux of people in them. This might offer some explanation as to why the 10010 zip code in Manhattan has five McDonald’s restaurants within it. <\/p>\n

        \"\"\"\"<\/figure>\n

        Thank you for taking the time to read this blog post! Any feedback and\/or praise is welcome! Happy analyzing.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

        https:\/\/nycdatascience.com\/blog\/student-works\/mcdonalds-expansion-strategy-analysis-in-nyc\/<\/p>\n","protected":false},"author":0,"featured_media":6633,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[2],"tags":[],"_links":{"self":[{"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/posts\/6632"}],"collection":[{"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/comments?post=6632"}],"version-history":[{"count":0,"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/posts\/6632\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/media\/6633"}],"wp:attachment":[{"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/media?parent=6632"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/categories?post=6632"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wealthrevelation.com\/data-science\/wp-json\/wp\/v2\/tags?post=6632"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}