Developing IS-support for the Human Resources function

How can Information Systems effectively support Human Resources processes? So far, information systems are mainly applied within two areas of the Human Resources field: the attraction of qualified candidates over the Internet on the one hand and the support of administrative tasks such as applicant tracking, attendance tracking and payroll or compensation management on the other. However, there remains a big gap in-between: the decision support for the (pre-)selection of candidates and their matching with future team members as part of the desire to optimize the allocation of human resources within a company. Thus, despite the ubiquity of the corporate task of finding people with particular hard and soft skills within and across firm borders, a systematic IS-support for the team configuration process is scarce. Based on existing research we claim that an IS-supported approach for the systematic selection of individuals for jobs and the ad hoc configuration of teams needs to be able to describe the required complex individual and relational attributes capturing larger parts of the reality of human characteristics, e.g. skills, leadership styles and personality traits, to then make them available to a selection or proposal system. Therefore, the major challenge of this project is (1) the modelling of human as well as social capital as the main drivers of individual and corporate performance and (2) the design of an IS-supported decision support leveraging this underlying information.

As a consequence, within this project we aim at developing novel forms of E-HR, focusing on flexible partnership building including team configuration and of course the recruitment of new employees as a primary instance of partner matching. The three main objectives thus are: E-Recruiting, E-HR Recommender Systems, and Team configuration, trust, and traits:

1. E-Recruiting: Since 2003, our annual survey “Recruiting Trends” with the Top-1.000-companies in Germany and 1.000 SMEs has become a de facto standard on modern recruiting practises within German-speaking countries. This empirical work aims at understanding market trends valuable to both practitioners and researchers. We analyze IT-usage along the recruitment process, identify changes over time and discuss the implications of skill shortages for the mix of attraction, application and selection channels. Also, by testing underlying hypotheses, we derive recommendations for the optimization of the recruitment process. As this process is considered as a secondary process, quite similar to financial processes, there are synergies with our research within Cluster 1 of the E-Finance Lab. Since 2004, the Recruiting Trends surveys with firms are complemented by a survey with Internet job seekers thus providing us a means to reflect market trends form the perspective of both market sides.
   
   
2. E-HR Recommender Systems: The findings of the surveys on E-Recruitment practices show that searching for candidates is often only supported by methods that are not adequate to achieve a good matching quality between jobs and candidates such as Boolean search. We replaced this mechanism by an automated recommendation approach that exploits the advantages of collaborative filtering and hybrid methods for selecting individuals by using a probabilistic latent aspect model. The system suggests candidates that are similar to resumes previously selected for an identical job profile and thus makes Boolean search dispensable. In a next step, we aim to extend the recommender system from individual, competency-focused attributes to relational structures and interpersonal attributes.
   
   
3. Team configuration, trust, and traits: Beyond the selection of a candidate we aim to optimize the fit between the person in consideration and prospective team members. Thus, our research extends current knowledge in the field of CSCW and virtual work by considering the question of how information systems can contribute right at the beginning of virtual work in the design phase of the team. Therefore, we understand team configuration as a two-dimensional matching problem in which individuals need to be brought together (1) with tasks for which they posses the competencies to carry them out and (2) with other individuals with whom they are able to collaborate successfully. It is understood that multiple dimensions of human as well as social capital and especially of trust play an important role in the underlying decision process. Based on research in multiple fields we developed an approach permitting to establish successful virtual partnership based on a trust ontology and relational data model. Building on this research, we will extend the trust ontology to new relation types and complement it with research in the field of social network analysis in order to build a computational approach to workforce optimization.