This study explores the way in which network structure (network integration), network context (resource munificence and stability), and network governance mode relate to network effectiveness. The model by Provan and Milward (Provan, Keith G., and H. Brinton Milward. 1995. A preliminary theory of interorganizational network effectiveness: A comparative study of four community mental health systems. Administrative Science Quarterly 40 (1):1–33) on the effectiveness of designed and goal-directed interorganizational networks is extended and tested on the basis of 39 crime prevention networks (Safety Houses) in the Netherlands. Ten cases were subjected to in-depth analysis through documentation reviews, interviews, observations, and a survey among network participants. In the other 29 cases semistructured interviews were conducted with the network managers. The data for all 39 cases were analyzed with crisp-set Qualitative Comparative Analysis. The results revealed two different configurations for network effectiveness. Effective networks are centrally integrated networks that have been in existence for at least 3 years (age) and which show a high degree of stability. In addition, they either have considerable resources at their disposal or they have been set up with a network administrative organization. The results confirm core insights from Provan and Milward’s earlier study but also show that administrative resources can serve as a substitute for financial resources (and vice versa). The article concludes with suggestions for the further development of a configurational theory of network effectiveness.

Due to the COVID-19 pandemic, emergency healthcare workers have come under even more pressure than before, threatening the workers’ mental health and the continuity of care delivered by their teams. This study aims to investigate what conditions increase individual and team resilience, referring to the ability to “bounce back” from stressful situations. We also assess whether team resilience is the sum of the individual resilience of team members, or whether other conditions enhance team resilience and thus continuity of care, despite limited individual resilience. We collected survey data from 129 emergency healthcare team members in the Netherlands to examine to what extent transformational leadership and team familiarity influence the level of team resilience, either directly or mediated by individual resilience, accounting for psychological characteristics and social support. The results show two distinct pathways to enhance team resilience, directly by familiarizing team members with each other and by mobilizing family support, and indirectly but with a much weaker effect, by encouraging team members’ individual resilience through transformational leadership and staffing optimistic team members with high levels of self-efficacy.

This experimental study examines user involvement in the co‐design stage of public sector innovations in relation to citizen acceptance of these innovations. We analyze 603 citizen evaluations of 12 co‐designed innovation prototypes. Results show that involving a few users can benefit many citizens. Partially co‐designed innovation prototypes, with users co‐defining the problem but professionals developing the solution, are perceived by citizens to be of higher quality than prototypes developed by professionals only, resulting in greater innovation acceptance in terms of perceived usefulness and ease of use. However, for fully co‐designed innovation prototypes, we do not find these positive results.

Background: The success of eHealth relies on interorganizational collaboration (IOC) throughout the development, evaluation, and implementation phases of eHealth deployment. This IOC is complex, as it involves a diversity of organizations from different sectors, such as technological, academic, health care, and governmental organizations, collaborating to deploy eHealth. Between these organizations, organizational boundaries, defined as the demarcation of an organization from its environment, arise. When these boundaries are perceived as aligned and enable complementarity, IOC is facilitated. By contrast, misalignment of organizational boundaries can hinder IOC. A dialogical learning mechanism, defined as a learning process that occurs when boundaries hinder IOC, can support learning how to navigate such boundaries. However, it is difficult to determine whether and when organizational boundaries facilitate or hinder IOC, and which dialogical learning mechanisms can be used to address these challenges during eHealth deployment. Previous literature presents the barriers and facilitators of IOC during eHealth deployment only for subsets of organizations or specific phases, leaving their generic versus phase specific applicability uncharted. Objective: This scoping review aims to identify whether, and under what circumstances, organizational boundaries facilitate or hinder IOC during the development, evaluation, and implementation of eHealth. Methods: A scoping review was conducted using searches in the PubMed, PsycINFO, CINAHL, and Web of Science databases. Articles were eligible for inclusion if they were empirical studies written in English or Dutch and contained findings on factors influencing IOC during the development, evaluation, or implementation phases of eHealth deployment. The search yielded 11,867 articles, of which 16 met the inclusion criteria. Open and axial coding of the extracted findings was performed to identify organizational boundaries and dialogical learning mechanisms that hindered or facilitated IOC during eHealth deployment. Results: In each phase, different organizational boundaries either hindered or facilitated IOC. The dialogical learning mechanism identification was crucial for enhancing IOC and was supported by training or by establishing IOC from previous relationships. Additionally, the learning mechanism coordination improved IOC and depended on the involvement of boundary spanners (ie, individuals who span organizational boundaries) and the use of boundary objects (ie, objects which help bridge different social worlds). Furthermore, the mechanism reflection, fostered through open and frequent communication, facilitated IOC. The dialogical learning mechanism transformation did not influence IOC during any phase of eHealth deployment. Conclusions: IOC in eHealth deployment is a dynamic process that depends on the dialogical learning mechanisms identification, coordination, and reflection to navigate organizational boundaries. This review is the first to present organizational boundaries and dialogical learning mechanisms that influence IOC across the different phases of eHealth deployment. However, further research that explicitly considers these phases is needed to deepen the understanding of IOC in eHealth deployment.