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Do LEGO® SERIOUS PLAY® (LSP) workshops result in improved experience of flow components as well as higher levels of creative output than traditional meetings (MEET)? This research studies the extent to which LSP, as a specialized material-mediated and process-oriented cocreative workshop setting, differs from MEET, a traditional workshop setting. Hypotheses for differences in individual flow components (autotelic behavior, happiness, balance), group flow components (equal participation, continuous communication) and creative output were developed and tested in a quasi-experimental comparison between LSP and MEET.

The study was conducted with 39 practitioners in six teams from various industries. In total, 164 observations were collected during two workshops using the Experience Sampling Method. The creative output was assessed by peer evaluations of all participants, followed by structural analysis and quantitative group comparisons.

The results show that two components of individual flow experience (autotelic behavior, happiness) were significantly higher in LSP, and one of the components of group flow experience (continuous communication) was, as expected, significantly lower. Regarding creative output, the LSP teams outperformed the MEET teams. The study suggests that a process-oriented setting that includes time for individuals to independently explore their ideas using a different kind of material in the presence of other participants has a significant influence on the team result.

LSP can improve the components of participants' flow experience to have an impact on the creative output of teams. In cocreative settings like LSP, teams benefit from a combination of alone time and high-quality collaborative activities using boundary objects and a clear process to share their ideas.

This is the first quasi-experimental study with management practitioners as participants to compare LSP with a traditional and widespread workshop approach in the context of flow experience and creative output.

Intraorganizational knowledge and information sharing are important steps toward more-accessible organizational knowledge. The aim of this study is to qualitatively explore factors that contribute to employees' motivations for sustaining intraorganizational knowledge-sharing behaviors and to examine the impact of these factors in a quantitative study with the Austrian Federal Ministry of Defense. This ministry faces a retirement wave in the next 5–10 years. Intraorganizational knowledge sharing before, during, and following this wave will play a decisive role for the organization in the near future.

An exploratory sequential mixed-methods study was conducted. The study design involved a qualitative study phase with expert interviews and stakeholder workshops (n = 9) and a quantitative study phase based on a cross-sectional online survey with an implicit association test on intraorganizational knowledge sharing (n = 59).

In the qualitative study phase, three main research topics regarding intraorganizational knowledge sharing were identified: employee attitude, organizational support, and specific relational aspects of knowledge transfer, such as reciprocal relationships among employees and opportunities for knowledge exchange. A hierarchical multiple regression analysis revealed that perceived organizational support was the only factor that was a significant predictor of motivation for engaging in knowledge sharing. We also analyzed the data for moderation effects and demonstrated that sociopsychological factors (e.g., the engagement or openness of colleagues to share their knowledge) further strengthened the positive relationship between employees' perceived support and personal willingness to share knowledge.

We conclude that an organizational culture that supports knowledge sharing within the organization is highly relevant for motivating employees to share their knowledge. Practitioners will also benefit from the insights of the various dimensions of employees' willingness to engage in knowledge-sharing behaviors to better design further interventions in organizations.

In accordance with an exploratory sequential mixed-methods approach, we followed a transdisciplinary process in which scientific and practical experiences and knowledge were integrated. For this purpose, interviews and workshops with experts and stakeholders in the organization were conducted. The qualitative findings were incorporated into a quantitative survey and an implicit association test for the employees of the organization. This approach demonstrates a different and more holistic approach to analyzing a real-world problem in the context of a governmental agency in order to investigate the multidimensional and complex topic of intraorganizational knowledge sharing.

The dynamics of modern life lead to societal changes that affect innovation systems. Entrepreneurship is an important driver for fostering adaptive capacities of innovation systems in such uncertain and complex environments. This study aims to gain a detailed understanding of how (innovative) entrepreneurship can promote innovation systems, leading to more sustainable societies. A particular focus is placed on migrant entrepreneurship in the digital economy, as a concrete implication of innovative entrepreneurship, and its role within the Austrian innovation system.

In order to develop a shared system understanding from a scientific and practical perspective, transdisciplinary multistage system modeling was applied. The transdisciplinary discourse involved 14 experts, and several system models were iteratively co-created during the course of the research.

The main result demonstrates the interrelationship between the innovation system and migrant entrepreneurship in the digital economy, which includes six core reinforcing loops: (1) the mindsets of entrepreneurs, (2) the role of international collaboration, (3) the role of entrepreneurial education, the financial sphere in regard to (4) government and (5) private funding, as well as (6) the impact of formal procedures.

The authors present and discuss the relational dynamics of this complex phenomenon as well as the applied transdisciplinary approach, with the aim of identifying a potential way to improve the sustainable impact of (migrant) entrepreneurship considering the case of the Austrian innovation system.

One of the currently debated changes in scientific practice is the implementation of data sharing requirements for peer-reviewed publication to increase transparency and intersubjective verifiability of results. However, it seems that data sharing is a not fully adopted behavior among researchers. The theory of planned behavior was repeatedly applied to explain drivers of data sharing from the perspective of data donors (researchers). However, data sharing can be viewed from another perspective as well: survey participants. The research questions (RQs) for this study were as follows: 1 Does data sharing increase participant's nonresponse? 2 Does data sharing influence participant's response behavior? The purpose of this paper is to address these issues.

To answer the RQs, a mixed methods approach was applied, consisting of a qualitative prestudy and a quantitative survey including an experimental component. The latter was a two-group setup with an intervention group (A) and a control group (B). A list-based recruiting of members of the Medical Faculty of the University of Freiburg was applied for 15 days. For exploratory data analysis of dropouts and nonresponse, we used Fisher's exact tests and binary logistic regressions.

In sum, we recorded 197 cases for Group A and 198 cases for Group B. We found no systematic group differences regarding response bias or dropout. Furthermore, we gained insights into the experiences our sample made with data sharing: half of our sample already requested data of other researchers or shared data on request of other researchers. Data repositories, however, were used less frequently: 28% of our respondents used data from repositories and 19% stored data in a repository.

To the authors’ knowledge, their study is the first study that includes researchers as survey subjects investigating the effect of data sharing on their response patterns.

There is a lack of theoretical and empirical studies regarding concepts of social sustainability based on social infrastructure. The idea of understanding this paper is that quality social infrastructure leads to the general quality of people’s life in the built environment and that is rounded up to social sustainability. This paper aims to integrate these concepts into the network, hereinafter referred to as a social sustainability model.

The methodology used in this paper is desk research. The authors follow methodological steps in the building of conceptual network: setting up a research problem; choice of databases; reviewing the literature and categorizing the selected data; identifying and default conceptual definition; integrating the concepts; synthesis and making it all make sense; and assembly and validating the concept. Through that, a large volume of bibliographic materials was scanned, and a limited number of documents have been reviewed and critiqued. The documents have been selected from varied disciplines, including social infrastructure, quality of life, social sustainability, urban sociology, housing policy as among the articles.

The result is the model which represents the links between social infrastructure (utility equipment, public infrastructure, vital objects and fundamentals) and further between factors inside quality of life structure (users, quality of life, reflections). The result is the model which representing the links between social infrastructure (utility equipment, public infrastructure, vital objects and fundamentals) and further between factors inside well-being structure (users, quality of life, reflections).

There is a potential risk of errors arising from the use of assumptions, limited desk reviews and data from secondary resources.

The authors portray the development of social sustainability model. Within this model, the authors can critically observe all levels within the existing built environment: user responses to the built environment, their satisfaction, social inclusion, health, etc. Within this model, they can observe the links between existing research, their frequency, capture, direction and not least to determine which areas have not been explored and where the lacks of research are. The conclusion outlines the framework and its main concepts of social sustainability based on social infrastructure and well-being, including their theoretical premises and components.