What you see is what you get? Measuring companies' projected employer image attributes via companies' employment webpages

Theurer Christian, Schäpers Philipp, Tumasjan Andranik, Welpe Isabell, Lievens Filip

Abstract

Information on a company's employment webpage sends signals about the employer image the company intends to project to applicants. Nonetheless, we know little about the content of recruitment signals sent via company employment webpages. This study develops a method to measure companies’ projected employer image attributes based on their employment webpages. Specifically, we analyze companies’ projected employer image attributes by applying computer-aided text analysis (CATA) to the employment webpages of 461 Fortune 500 companies (i.e., more than 11,100 individual pages). Our results show that projected employer image attributes remain relatively stable over time. Moreover, we find relatively low levels of employer image differentiation between companies and between industries. Only a small group of companies (<20%) use distinct employer attribute signals to communicate their projected employer image. Finally, there is limited convergence between projected employer image attributes based on employment webpages and ratings on similar attributes on employer review websites. Generally, our results show that CATA is a viable method for assessing companies’ projected employer image in the context of employer image management and engineering.