How to Identify Unique Region Industries: Location Quotient, Cultural Marginalization, & More
Many business owners and investors use metrics such as business performance to assess other businesses. It helps them identify valuable investment opportunities, prospects, and potential business partners.
However, there is another way to do it while understanding specific industries and getting actionable insights.
Have you ever heard of terms such as location quotient, industry concentration, and cultural marginalization? Understanding these terms can help you identify unique region industries, no matter which nation or geo-location you choose.
Below you can find everything you need to know about them.
What is industry concentration?
Industry concentration is often cited by experts interested in discovering the level of development in certain regions. The term can be misleading, and you can quickly end up thinking that it stands for a specific industry size within a region compared to other industries.
Industry concentration definition outlines this term in an easy-to-understand way:
“Industry concentration is the concentration of employment in a regional industry compared to national metrics.”
Whether you want to assess the strength or weaknesses of a specific urban, rural, or region with noticeable cultural marginalization, industry concentration can help you do it. How do you calculate the industry concentration, though? That’s where the location quotient comes in.
How is location quotient connected to industry concentration?
The location quotient is a metric that clearly shows the concentration of employment in a specific regional industry in relation to state-wide, national, or continent metrics. It tells you which industries are the most competitive in a particular region and which communities are prevalent in those industries.
To paint the picture, let’s take the US as an example where the entire US is at the national level, and states are considered as regions. Let’s say that you are interested in the IT industry. The chances are that the location quotient for the IT sector will be highest in California because the IT industry supports over 1.18 million jobs across the state.
However, if you take the automotive industry, California is no longer relevant, as the location quotient for the automotive industry is highest in Michigan, as the auto industry in this state supports over 500,000 jobs.
To better understand the local quotient, you need to see the formula.
Local quotient formula
You can calculate the local quotient by dividing local concentration by national concentration.
Local concentration is calculated by dividing local industry employment by the local all-industry employment.
National concentration is calculated by dividing national industry employment by national all-industry employment.
Finally, you can use the same local quotient formula for demographic groups, competencies, and occupations. For instance, you can identify regions with the above nation’s average cultural marginalization.
Where to get the data to calculate the location quotient
You can get all the data you need yourself. Most official government and state portals have public employment databases you can easily access. Some are more structured than others. In any case, be ready for a lot of copy-pasting and spreadsheet editing. While this is a viable way of getting the data, it’s time-consuming.
The more efficient way would be to purchase the data from data providers. Data providers offer ready-to-use firmographic data sets, which are regularly updated and screened for errors. It will save you a ton of time and give you instant access to in-depth reports for all companies operating in a specific region.
How to interpret location quotient
Interpreting the results of your location quotient mathematical calculations is easy. The results can be either greater or lower than 1. If the location quotient is greater than 1, the local industry has a greater share of the local area employment than nationwide employment. In case you get a number lower than 1, the local industry has a lower share of the local area employment compared to nationwide employment.
However, you need to be careful when interpreting results. For instance, an LQ lower than 1 doesn’t necessarily indicate that the industry in a specific region lacks a competitive advantage.
Take the export and import industries, for example. Export industries often have a very high location quotient, while import industries have a low location quotient. Lower LQ can also indicate that cultural marginalization is high within a region. If you decide to expand into this region, you’ll have to devise a proper strategy. For instance, you will need a strong inclusion policy, support, and adequate training and education.
Why is location quotient important?
Location quotient has found many use cases. Businesses often use it to identify export and import-oriented industries in a specific region and quickly gauge a region to identify the emerging export industries with a high competitive advantage.
States often use it to assess local economies, discover which industries make it unique, and identify sectors that can potentially cause economic instability in a region.
The location quotient is crucial because it tells you exactly which industries tend to prosper in an economy. If you are focused on specific markets in target regions, you can use this information to make informed investment decisions.
The location quotient can help you identify emerging competitive businesses in a target location. This information can help you choose the best business partners – or you can better target your sales and marketing strategies to address the needs of emerging companies.
Conclusion
Identifying unique region industries is straightforward when you have access to actionable data. Thanks to firmographic data, you can assess every company in a specific region and calculate the location quotient. You will also be able to spot cultural marginalization and identify communities that provide valuable expansion or investment opportunities.
