Stakeholder theory and management: Understanding longitudinal collaboration networks.

This paper explores the evolution of research collaboration networks in the 'stakeholder theory and management' (STM) discipline and identifies the longitudinal effect of co-authorship networks on research performance, i.e., research productivity and citation counts. Research articles totaling 6,127 records from 1989 to 2020 were harvested from the Web of Science Database and transformed into bibliometric data using Bibexcel, followed by applying social network analysis to compare and analyze scientific collaboration networks at the author, institution and country levels. This work maps the structure of these networks across three consecutive sub-periods (t1: 1989-1999; t2: 2000-2010; t3: 2011-2020) and explores the association between authors' social network properties and their research performance. The results show that authors collaboration network was fragmented all through the periods, however, with an increase in the number and size of cliques. Similar results were observed in the institutional collaboration network but with less fragmentation between institutions reflected by the increase in network density as time passed. The international collaboration had evolved from an uncondensed, fragmented and highly centralized network, to a highly dense and less fragmented network in t3. Moreover, a positive association was reported between authors' research performance and centrality and structural hole measures in t3 as opposed to ego-density, constraint and tie strength in t1. The findings can be used by policy makers to improve collaboration and develop research programs that can enhance several scientific fields. Central authors identified in the networks are better positioned to receive government funding, maximize research outputs and improve research community reputation. Viewed from a network's perspective, scientists can understand how collaborative relationships influence research performance and consider where to invest their decision and choices.

Exploring the psychometric properties of the Rainbow Model of Integrated Care measurement tool for care providers in Australia.

OBJECTIVE: To assess the reliability and validity of a shortened version of the Rainbow Model of Integrated Care (RMIC) measurement tool (MT). The original version of the measurement tool has been modified (shortened) for the Australian context. DESIGN: Validation of the psychometric properties of the RMIC-MT. SETTING: Healthcare providers providing services to a geographically defined rural area in New South Wales (NSW), Australia. PARTICIPANTS: A sample of 56 healthcare providers providing mental and physical healthcare. MAIN OUTCOME MEASURES: The psychometric properties of the tool were tested using principal component analysis for validity and Cronbach's alpha for reliability. RESULTS: The tool was shown to have good validity and reliability. The 35 items used in the shortened version of the tool were reduced to 29 items grouped into four dimensions: community-governance orientation, normative integration, functional integration and clinical-professional coordination. CONCLUSIONS: The shortened version of the RMIC-MT is a valid and reliable tool that evaluates integrated care from a healthcare provider's perspective in NSW, Australia. In order to assess the tool's appropriateness in an international context, future studies should focus on validating the tool in other healthcare settings.