Stefan Thalmann

Virtualizing face-2-face trainings for training senior professionals: a comparative case study on financial auditors

Traditionally, professional learning for senior professionals is organized around face-2-face trainings. Virtual trainings seem to offer an opportunity to reduce costs related to travel and travel time. In this paper we present a comparative case study that investigates the differences between traditional face-2-face trainings in physical reality, and virtual trainings via WebEx. Our goal is to identify how the way of communication impacts interaction between trainees, between trainees and trainers, and how it impacts interruptions. We present qualitative results from observations and interviews of three cases in different setups (traditional classroom, web-based with all participants co-located, web-based with all participants at different locations) and with overall 25 training participants and three trainers. The study is set within one of the Big Four global auditing companies, with advanced senior auditors as learning cohort.

Balancing Knowledge Protection and Sharing to Create Digital Innovations

The creation of digital innovations requires active participation and knowledge sharing on behalf of all collaboration partners in inter-organisational settings. However, while the participants collaborate, they also have their own interests and as they are competitors in many cases, they have to protect their competitive knowledge. Collaboration thus requires balancing of knowledge sharing and protection on both the organizational and individual level. This paper reviews literature from several domains to assess how the balancing act is scoped and what kind of measures to achieve this balance prior research has identified. The balancing act is examined on the channel, partner and artefact levels. The paper identifies the balancing act as decisions made over the course of the collaboration both by the organizations as a whole, and by individuals on concrete knowledge artefacts in their daily work. Implications from the point of view of creating digital innovation are presented.

Localizing Knowledge in Networks of SMEs—Implication of Proximities on the IT Support

The concentration of knowledge development around the economy’s big players and into few regions leads to rising inequalities of knowledge distribution. Due to shorter innovation cycles, more and more knowledge is ephemeral. To stay competitive, both trends force organizations to absorb increasingly more distant knowledge faster and with less opportunities of reuse. This situation is particularly challenging for small and medium-sized enterprises (SMEs) with their limited resources. Joining networks focused on the acquisition of external knowledge and is one promising solution for SMEs. So far, there is little research on strategies that facilitate localization of knowledge, particularly in networks of SMEs. In this paper, therefore, we first identified the phases of localizing external knowledge, followed by an investigation on the role of proximities during the localization process and the potential for supportive IT.

Reconciling digital transformation and knowledge protection: a research agenda

Abstract Digital transformation revolutionises the way people work not only in office settings but also in physical work settings such as manufacturing or construction. New ways of combining digital and physical innovations and intensified inter-organisational collaborations are key characteristics for success. Knowledge sharing becomes increasingly important, but its inter-organisational nature and the blurring of organisational boundaries create new challenges for the protection of knowledge. Existing research on knowledge protection mostly focuses on single organisations or on dyadic relationships. Complex sharing arrangements and especially sharing in networks has received little attention so far. This paper presents a literature review, integrating the perspectives of the base domains of knowledge, strategy, innovation, and information security management with the goal to identify knowledge protection requirements in the era of digital transformation. Five avenues for future research on knowledge protection to support organisations coping with challenges imposed by digital transformation are presented.

Open Innovation in the Big Data Era with the MOVING Platform: An Integrated Working and Training Approach for Data-savvy Information Professionals

The MOVING platform enables its users to improve their information literacy by training how to exploit data mining methods in their daily research tasks. Its novel integrated working and training environment supports the education of data-savvy information professionals and allows them to address the big data and open innovation challenges.

AFEL - Analytics for Everyday Learning.

The goal of AFEL is to develop, pilot and evaluate methods and applications, which advance informal/collective learning as it surfaces implicitly in online social environments. The project is following a multi-disciplinary, industry-driven approach to the analysis and understanding of learner data in order to personalize, accelerate and improve informal learning processes. Learning Analytics and Educational Data Mining traditionally relate to the analysis and exploration of data coming from learning environments, especially to understand learners behaviours. However, studies have for a long time demonstrated that learning activities happen outside of formal educational platforms, also. This includes informal and collective learning usually associated, as a side effect, with other (social) environments and activities. Relying on real data from a commercially available platform, the aim of AFEL is to provide and validate the technological grounding and tools for exploiting learning analytics on such learning activities. This will be achieved in relation to cognitive models of learning and collaboration, which are necessary to the understanding of loosely defined learning processes in online social environments. Applying the skills available in the consortium to a concrete set of live, industrial online social environments, AFEL will tackle the main challenges of informal learning analytics through 1) developing the tools and techniques necessary to capture information about learning activities from (not necessarily educational) online social environments; 2) creating methods for the analysis of such informal learning data, based on combining feature engineering and visual analytics with cognitive models of learning and collaboration; and 3) demonstrating the potential of the approach in improving the understanding of informal learning, and the way it is better supported; 4) evaluate all the former items in real world large scale applications and platforms.