Purpose: This paper aims to explore the relationships between participants’ perceived benefits of sharing knowledge privately, within a group or with the general public within an organisational knowledge network. The quality and quantity of knowledge shared are explored in relation to the level of knowledge sharing visibility (both content and participants’ profiles).Design/methodology/approach: A research framework of perceived benefits of knowledge sharing is designed; survey and content analysis are used to explore influences of perceived benefits on the quantity and quality of knowledge shared by participants for each level of knowledge sharing within an organisation. The research model is empirically tested using a questionnaire survey with 205 participants and content analysis of their contributions in a high-tech corporate group. This study uses the partial least squares path-modelling method to explore relationships between constructs of the research model.Findings: The current research results show that intrinsic benefits are more influential than extrinsic benefits for private knowledge sharing, while extrinsic rewards play an important role at the public knowledge sharing within organisations. In addition, results indicate that both the quality and quantity of knowledge sharing at the group-level knowledge sharing are significantly higher than at the private and the public levels.Practical implications: Contemporary knowledge management systems are developed by integrating communication channels in different visibility levels of knowledge exchange. Managers of knowledge management systems are advised to use the research outcome for developing incentive strategies in different levels.Originality/value: In contrast to previous studies that focus on only one level of knowledge sharing, this paper explores relationships between perceived benefits of knowledge sharing with the quantity and quality of shared knowledge for three distinct levels of knowledge sharing.

Identifying the diverse and often competing values of citizens, and resolving the consequent public value conflicts, are of significant importance for inclusive and integrated urban development. Scholars have highlighted that relational, value-laden urban space gives rise to many diverse conflicts that vary both spatially and temporally. Although notions of public value conflicts have been conceived in theory, there are few empirical studies that identify such values and their conflicts in urban space. Building on public value theory and using a case-study mixed-methods approach, this paper proposes a new approach to empirically investigate public value conflicts in urban space. Using unstructured participatory data of 4528 citizen contributions from a Public Participation Geographic Information Systems in Hamburg, Germany, natural language processing and spatial clustering techniques are used to identify areas of potential value conflicts. Four expert interviews assess and interpret these quantitative findings. By integrating quantitative assessments with the qualitative findings of the interviews, we identify 19 general public values and nine archetypical conflicts. On the basis of these results, this paper proposes a new conceptual model of ‘Public Value Spheres’ that extends the understanding of public value conflicts and helps to further account for the value-laden nature of urban space.

Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. Additionally, a rigorous methodology is missing that enables the development of both theoretical and empirical models for supporting policy formulation and evaluation with respect to a specific policy problem. In this article, the authors propose a methodology targeting these gaps for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the conceptual framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model.