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This thesis investigates the integration of Artificial Intelligence (AI) in the recruitment processes of Small and Medium Enterprises (SMEs), highlighting both the opportunities and challenges of such technologies. It examines the potential benefits of AI in recruitment, including increased efficiency and unbiased decision-making, as well as challenges such as data privacy concerns. Through qualitative research and interviews with HR professionals, the study not only explores the current landscape of AI in recruitment but also proposes a comprehensive implementation plan for SMEs. This plan is designed to help SMEs navigate the complexities of adopting AI technologies, ensuring they can effectively leverage AI tools to enhance their recruitment outcomes and overcome the barriers to implementation.
Candidate experience management is gaining in importance: The recruiter experience study in 2018 revealed that 63% of the recruiters questioned throughout Germany considered optimizing the candidate experience to be one of the top priorities for future actions.
Why is that? It is becoming increasingly difficult for companies to recruit top talents. Because of demographic changes, the workforce supply is declining and the competition among firms is growing.
What does that mean for companies? Firms need to counter-tactics and ensure that talented people stay in the application process instead of opting for the competition. The goal is to attract talented individuals and ultimately win them over for the corporation.
How can companies successfully manage it? To be successful as an employer, it is well worth optimizing contact points along the application process and providing the best possible experience for candidates. Ideally, this can also help to strengthen the employer brand.
Literature, including previous findings, as well as insights about the collaborating company Marc Cain provide a baseline. A qualitative research examines how different candidates Marc Cain recently hired perceive the candidate journey and its resulting candidate experience.
For this purpose, interviews are conducted along the established candidate journey model of Athanas and Wald. The aim of this work is to answer the overall research question of the title:
Optimizing the Candidate Experience at Marc Cain GmbH –
Can this Investment sustainably strengthen the Employer Brand?
The research indicates that essential attributes for candidates during the application process are transparency, communication, authenticity, a personal approach, and feedback. Moreover, it shows that Marc Cain does not have a bad status quo or starting point, but regarding future developments does have the potential for optimization.
How exactly Marc Cain can counter this shortage of talent through an improved candidate experience, and how the employer brand benefits from it, is examined in the following work. Further, recommendations for action are meant to express direct suggestions for the company.
This thesis deals with the marketing of today and its benefits for companies and universities. The focus is on the recruitment of students at universities through the business platform LinkedIn. The tools offered by LinkedIn will be presented and the purpose for which they are beneficial will be determined. Surveys are used to clarify questions about the use of social networks for different activities. In addition, it will be worked out why students choose a university and how LinkedIn fosters this. These findings are then translated into marketing measures for the HFU Business School in Villingen-Schwenningen.
The presented thesis studies Artificial Intelligence-based tools which are currently used in recruiting. The guiding research questions ask which ethical implications exist when using different so-called robot recruiting tools, and how these implications apply to the German healthcare sector. The analysis is based on a comprehensive literature review. First, an overview over eight different tools is given, then they are analyzed regarding their ethical implications. Finally, the practical example of the healthcare sector in Germany is discussed. The eight tools are considered in regard to the specific need of larger hospitals. The thesis shows that when applying artificial intelligence-based tools, severe ethical concerns, mostly on the questions of non-discrimination, data security and integrity of an organization, can arise. Because of that, the thesis recommends that human resource managers should be very careful when applying Artificial Intelligence-based tools.