Special Issues 2019

"Skills and competences in maritime logistics: managerial and organizational emerging issues for human resources"

The Call for Abstracts is available here.

Abstracts submission deadline: 15.2.2019 extended! 5.3.2019. Full papers submission deadline: 15.5.2019. Abstracts and full papers will undergo double blind review.

The Special Issue will be published in Septembre 2019.


"Studying organizations: identity, pluralism and change"

The proposal has a strong and direct connection with the annual Workshop of Researchers in the Organizational Field.

The Call for Papers is available here.

Full papers submission deadline: 15.4.2019. Full papers will undergo double blind review.

The Special Issue will be published in May 2019.

Appearance or reality? Monitoring of employer branding in public network space: the Glassdoor case.

On issue: 

To what extent does Employer Branding (EB) express the real-life company working environment or merely constitutes a well-orchestrated organizational image? After reconstructing its significance and impact on the managing of the human resource cycle (recruitment, commitment, and retention) this study describes three ways of monitoring EB: internal, professional and public control. They each make use of a variety of tools in order to assess the extent to which the appearance of the employer corresponds to an authentic reality. Then, there is a presentation of the features and critical issues of a case of public EB control: Glassdoor.com. More specifically, this is followed by descriptions of the structure, services and critical implications of the crowdsourcing-based platform of Glassdoor.com (retaliatory, improper, frivolous and illusionistic utilizations). Implications which may affect the platform’s validity as a monitoring tool of EB. The article ends with several considerations regarding the use of the site as a research-tool. Research sources: literature reviews, Glassdoor-site analysis, specialized web-journals, social-media, studies that used Glassdoor for research purposes. Method: theoretical and empirical data-processing.