Hiring your Next Superstar: An R Package to Expedite the Hiring Process
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Mentor Information
Dr. Alon Friedman
Description
With an overload of applications received by employers, hiring talent has remained the top concern for CEOs as the influx of applications has resulted in outsourcing the hiring process to foreign countries increasing the cost of hiring while decreasing the quality. To expedite this process for in-home employers as well as shorten the response time to applicants, I have developed a shiny app accessible through my R package named hiringLetter. Shiny apps are interactive web applications allowing users to make choices to see results straight from R. My presentation will explain the development and execution process of my hireLetter function to allow a hiring committee to interactively set qualifications to filter candidates for a position. The default qualifications available in the hire function are age, work experience, and current role. The output is dynamically filtered tables of accepted and rejected individuals with customized acceptance and rejection letter templates. The results of this package indicate the usefulness of expanding this package to include a wider variety of qualifications and more customization in templates. This presentation employs R to first bring awareness to the hiring issue at large and provide a starting app to benefit research in the hiring field.
Hiring your Next Superstar: An R Package to Expedite the Hiring Process
With an overload of applications received by employers, hiring talent has remained the top concern for CEOs as the influx of applications has resulted in outsourcing the hiring process to foreign countries increasing the cost of hiring while decreasing the quality. To expedite this process for in-home employers as well as shorten the response time to applicants, I have developed a shiny app accessible through my R package named hiringLetter. Shiny apps are interactive web applications allowing users to make choices to see results straight from R. My presentation will explain the development and execution process of my hireLetter function to allow a hiring committee to interactively set qualifications to filter candidates for a position. The default qualifications available in the hire function are age, work experience, and current role. The output is dynamically filtered tables of accepted and rejected individuals with customized acceptance and rejection letter templates. The results of this package indicate the usefulness of expanding this package to include a wider variety of qualifications and more customization in templates. This presentation employs R to first bring awareness to the hiring issue at large and provide a starting app to benefit research in the hiring field.
