Isabella Seeber

Design principles for competence-based Recommender Systems

In this paper we analyze the principal preconditions and limitations for designing a competence-based Recommender System. In detail this analysis is contextualized in the ARISTOTELE European project. In the second part of the paper an architectural view is proposed taking in consideration the objective to propose standard and non-standard suggestions. This solution will permit to insert serendipity approaches into classical solutions.

Fostering adoption, acceptance, and assimilation in knowledge management system design

Designing information and communication technologies (ICT) for knowledge work is a primary challenge in research and practice of knowledge management. Knowledge workers supposedly organize and manage their workplaces, at least partly themselves, which needs to be considered when designing ICT for supporting their daily knowledge-intense activities. It is considered useful for designers of knowledge management systems (KMS) to look into the results of behavioral science in information systems concerning the adoption, acceptance and assimilation of ICT. Thus, this paper proposes a model that contributes to bridging the gap between design science and behavioral science in the domain of knowledge management. In this regard, widely recognized behavioral models that aim at explaining organizational and human behavior in conjunction with ICT are analyzed in order to extract important factors influencing the successful application of KMS with respect to the adoption by an organization or organizational unit, acceptance by individual knowledge workers, and assimilation into knowledge processes and practices. By combining, categorizing, and structuring these factors, we developed a comprehensive model to be taken into account in software design and evaluation processes from various perspectives. Moreover, we discuss a case example in which this model is applied to the design of a KMS.

Opening the Black Box of Team Processes and Emergent States: A Literature Review and Agenda for Research on Team Facilitation

The effects of facilitation on team outcomes have been in the focus of many studies. However, only a few quantitative studies investigate how teams evolve through team processes and emergent states. The goal of this review paper is to synthesize quantitative research studies to better understand the constructs of facilitation and to identify future avenues of facilitation research. We performed a structured literature review to identify relevant quantitative studies using the input-mediator-outcome model to group elicited constructs of facilitation. We found that most studies treat team processes and emergent states as a black box. We argue that we need to open this black box and include measures that allow for conceptualizing how human and automated facilitation affects team outcomes. Hence, we propose a research agenda, which enhances current models explaining team outcomes by a conceptualization and measurement of team processes and emergent states.

CoPrA: A tool for coding and measuring communication in teams

The analysis and assessment of team processes to inform facilitation for increased team effectiveness is a challenging task for organizations. Also, research has troubles to grasp the complexity of team effectiveness, which often results in treating team processes as a black box. This paper introduces a design artifact that is built upon the collaboration process analysis technique CoPrA. The technique strives to support the analysis of team processes by identifying behavior patterns, which crystalize as behavior patterns in the dynamic process of a team. The paper aims to contribute to behavioral research as it showcases a set of process metrics for the analysis of team communication. Furthermore, the paper aims to contribute to design-science research by providing an integrated tool for content analysis and process mining used primarily by researchers.

Convergence on Self - Generated vs. Crowdsourced Ideas in Crisis Response: Comparing Social Exchange Processes and Satisfaction with Process

Social media allow crowds to generate many ideas to swiftly respond to events like crises, public policy discourse, or online town hall meetings. This allows organizations and governments to harness the innovative power of the crowd. As part of this setting, teams that process crowd ideas must engage in social exchange processes to converge on a few promising ideas. Traditionally, teams work on self-generated ideas. However, in a crowdsourcing scenario, such as public participation in crisis response, teams may have to process crowd-generated ideas. To better understand this new practice, it is important to investigate how converging on crowdsourced ideas affects the social exchange processes of teams and resulting outcomes. We conducted a laboratory experiment in which small teams working in a crisis response setting converged on self-generated or crowdsourced ideas in an emergency response context. Our findings suggest that teams converging on selfgenerated ideas have better social exchange processes in terms of dominance and coordination. We found support that evaluation and coordination positively affect team member satisfaction under both experimental conditions. Implications for research and practice are discussed.

Brainstorming is Just the Beginning: Effects of Convergence Techniques on Satisfaction, Perceived Usefulness of Moderation, and Shared Understanding in Teams

Much research exists regarding (computer-supported) idea generation, yet little is known about how teams can be facilitated to efficiently converge on a set of ideas. Convergence is a critical activity in collaborative problem-solving and decision-making as teams need to focus their cognitive resources on the most promising ideas resulting from a brainstorming activity. This paper investigates the effects of facilitation on team outcomes to foster our understanding of convergence. We tested three facilitated convergence techniques, Self Sifter, Fast Focus, and Treasure Hunt that offer different levels of procedural structuring and discussion allowances. An experiment with 138 subjects in 34 teams showed significant improvements in satisfaction with process and product after convergence. Self Sifter and Treasure Hunt outperformed Fast Focus in terms of shared understanding, while Fast Focus and Treasure Hunt outperformed Self Sifter in terms of usefulness of moderation. Our findings contribute to a better understanding of how teams can benefit from facilitated convergence techniques.

Social Meets Structure: Revealing Team Collaboration Activities and Effects in Enterprise Social Networks

Enterprise social networks (ESNs) are increasingly added to organizational IT infrastructures for more inclusive, open, and “social” communication. Many organizations recognize the potential benefits that ESNs can offer for improved team collaboration. Albeit there is extensive research testing the effects of general IT support on teams, it is still poorly understood what activities teams perform to realize the ESN’s potentials and to foster team collaboration. Drawing on our revelatory case study, we contribute to addressing this research gap by exploring this special case of an organization that uses an ESN for all work-related matters. Our findings describe four effects of team collaboration emerging from ESNsupported social and structure activities. Social activities emphasize interactions on the relationships among team members, whereas structure activities emphasize interactions on objects, including content and processes. We explain tensions within the effects of (1) unified, collective, yet relevant communication, (2) visible, active, yet controlled participation, (3) formalized, guiding, yet flexible processes, and (4) reusable, yet maturing information objects with team states, challenges and responses identified in team collaboration.

The Choice Is Yours: The Role of Cognitive Processes for IT-Supported Idea Selection

The selection of good ideas out of hundreds or even thousands has proven to be the next big challenge for organizations that conduct open idea contests for innovation. Cognitive load and attention loss hinder crowds to effectively run their idea selection process. Facilitation techniques for the reduction and clarification of ideas could help with such problems, but have not yet been researched in crowd settings that are prevalent in idea contests. This research-in-progress paper aims to contribute to this research gap by investigating IT-supported selection techniques that differ in terms of selection direction and selection type. A laboratory experiment using eye-tracking will investigate variations in selection type and selection direction. Moreover, the experiment will test the effects on the decision-making process and the number and quality of ideas in a filtered set. Findings will provide explanations why certain mechanisms work for idea selection. Potential implications for theory and practice are discussed.

How to Achieve Better Knowledge Utilization with Knowledge Externalization Mechanisms in Social Intranets

Organizations rely on employees to externalize their tacit knowledge in order to effectively conduct knowledge-intensive work processes. Tacit knowledge externalization is particularly important in times of digital transformation where product and service innovation cycles become shorter and require creative, quick decision-making. Our understanding of mechanisms that constitute tacit knowledge externalization and how this relates to knowledge use is, however, limited. This paper contributes towards closing this gap by testing whether the suggested mechanisms of content generation, storytelling, organizational communication, professional collaboration, and practice demonstration are associated with knowledge use when supported by corporate social media. The implications for research and practice are discussed.

The More the Merrier? The Effects of Community Feedback on Idea Quality in Innovation Contests

Innovation contests represent a novel and popular approach for organizations to leverage the creativity of the crowd for organizational innovations. In this approach, ideators present their initial ideas to a global community of potential users, and solicit their feedback for idea improvement or refinement. However, it is not clear which types of feedback lead to the development of better ideas and which contingent factors moderate these relationships. In this study, we examine the role of community feedback on idea development in online innovation contests, by using feedback intervention theory to develop a set of hypotheses relating community feedback and idea quality, and then testing those hypotheses using data from ZEISS VR ONE innovation contest. Our analysis suggest that task information feedback does lead to improvement in idea quality, while task learning and task motivation feedback does not, and the number of users providing feedback moderate the relationship between feedback and idea quality. Implications of our findings for theory and practice are discussed.