Developing a strong knowledge of core business information sources will help prepare you for a successful career in business. If you take the time to learn how to search efficiently and effectively, to exercise discretion when using text and data, and to cite the sources you use, you will earn the respect and trust of your professional associates.
Complete the activity after the library instruction session.
Submit one report for the entire team. The report should be one Excel file with three sheets:
Upload your team report to your CCIP Blackboard site.
The name of the Excel file you upload to Blackboard should be Cohort_CompanyName
The Mergent Online database provides a company profile that is easy to locate and read.
Before you start researching, make sure you know:
A company profile will tell you the company's primary SIC and NAICS codes, as well as the industry name.
Image of the Mergent Online database with a red box around the Basic Search tab, a red box around the Company Search box, and a red box around the Go box, indicating that the researcher should click on the Basic Search tab, type the ticker symbol or company name into the Company Search box, and then click on the Go box.
Image of the Coca-Cola Company profile in the Mergent Online database with a red arrow pointing to the SIC and NAICS codes, and a red box around the Report Builder tab.
Classifying Companies By Industry (NAICS and SIC)
Most business databases list competitors based on NAICS and/or SIC codes; use the links below to find out more about these codification systems.
Activity: Search the NAICS and SIC databases for the same keyword and compare your results. (This does not need to be submitted.)
Interested in taking a deeper dive? Consider this article about using AI to overcome the shortcomings of traditional industry classification.
Kim, D., Kang, H., Bae, K., & Jeon, S. (2022). An artificial intelligence-enabled industry classification and its interpretation. Internet Research, 32(2), 406-424. https://doi.org/10.1108/INTR-05-2020-0299 (authentication with your Fordham Access IT username and password required)
Shortened Abstract: To overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).