BACKGROUND: Big data offers new opportunities to enhance healthcare practice. While researchers have shown increasing interest to use them, little is known about what drives research impact. We explored predictors of research impact, across three major sources of healthcare big data derived from the government and the private sector. METHODS: This study was based on a mixed methods approach. Using quantitative analysis, we first clustered peer-reviewed original research that used data from government sources derived through the Veterans Health Administration (VHA), and private sources of data from IBM MarketScan and Optum, using social network analysis. We analyzed a battery of research impact measures as a function of the data sources. Other main predictors were topic clusters and authors’ social influence. Additionally, we conducted key informant interviews (KII) with a purposive sample of high impact researchers who have knowledge of the data. We then compiled findings of KIIs into two case studies to provide a rich understanding of drivers of research impact. RESULTS: Analysis of 1,907 peer-reviewed publications using VHA, IBM MarketScan and Optum found that the overall research enterprise was highly dynamic and growing over time. With less than 4 years of observation, research productivity, use of machine learning (ML), natural language processing (NLP), and the Journal Impact Factor showed substantial growth. Studies that used ML and NLP, however, showed limited visibility. After adjustments, VHA studies had generally higher impact (10% and 27% higher annualized Google citation rates) compared to MarketScan and Optum (p<0.001 for both). Analysis of co-authorship networks showed that no single social actor, either a community of scientists or institutions, was dominating. Other key opportunities to achieve high impact based on KIIs include methodological innovations, under-studied populations and predictive modeling based on rich clinical data. CONCLUSIONS: Big data for purposes of research analytics has grown within the three data sources studied between 2013 and 2016. Despite important challenges, the research community is reacting favorably to the opportunities offered both by big data and advanced analytic methods. Big data may be a logical and cost-efficient choice to emulate research initiatives where RCTs are not possible.

Open innovation that Henry Chesbrough introduced in 2003 promotes the usage of the input of outsiders to strengthen internal innovation processes and the search for outside commercialization opportunities for what is developed internally. Open innovation has enabled both academics and practitioners to design innovation strategies based on the reality of our connected world. Although the literature has identified and explored a variety of benefits and costs, to the best of our knowledge, no study has reviewed the benefits and costs of open innovation in terms of their importance for strategic performance. To conduct such a study, we need to take into account two main issues. First, the number of benefits and costs of open innovation are multifold; so, to have a comprehensive comparison, a large number of benefits and costs must be compared. Second, to have a fair comparison, benefits and costs must be compared in terms of different performance criteria, including financial and non-financial. Concerning the issues above, we will face a complex process of exploring benefits and costs. In this regard, we use multiple criterion decision-making (MCDM) methods that have shown promising solutions to complex exploratory problems. In particular, we present how using a stochastic multi-criteria clustering algorithm that is one of the recently introduced MCDM methods can bring promising results when it comes to exploring the strategic importance of benefits and costs of open innovation. Since there is no comprehensive understanding of the nature of the benefits and costs of open innovation, the proposed model aims to cluster them into hierarchical groups to help researchers identify the most crucial benefits and costs concerning different dimensions of performance. In addition, the model is able to deal with uncertainties related to technical parameters such as criteria weights and preference thresholds. We apply the model in the context of open innovation for universities concerning their research collaboration with industries. An online survey was conducted to collect experts' opinions on the open-innovation benefits and costs of university-industry research collaboration, given different performance dimensions. The results obtained through the cluster analysis specify that university researchers collaborate with industry mainly because of knowledge-related and research-related reasons rather than economic reasons. This research also indicates that the most important benefits of university-industry research collaboration for universities are implementing the learnings, increased know-how, accessing specialized infrastructures, accessing a greater idea and knowledge base, sensing and seizing new technological trends, and keeping the employees engaged. In addition, the results show that the most important costs are the lack of necessary resources to monitor activities between university and industry, an increased resistance to change among employees, conflict of interest (different missions), an increased employees' tendency to avoid using the knowledge that they do not create themselves, paying time costs associated with bureaucracy rules, and loss of focus. The research's findings enable researchers to analyze open innovation's related issues for universities more effectively and define their research projects on these issues in line with the priorities of universities.

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Despite the significant growth of inter-institutional research collaboration, there has been a disparity of partnerships between universities with different history, missions and identities. In competition for limited resources, inter-institutional collaborations among Predominantly White Institutions (PWIs) and research-intensive universities appear more frequent and better supported than between PWIs and Historically Black Colleges and Universities (HBCUs) or other minority-serving institutions (MSIs). Developing grant funding strategies is one way to enhance collaboration between faculty at HBCUs/MSIs and faculty at PWIs and improve pathways for success among traditionally underrepresented groups. The Institute for Critical Technology and Applied Science (ICTAS) at Virginia Tech, a research-intensive PWI, launched a unique seed funding program, the ICTAS Diversity and Inclusion Seed Investment (ICTAS DandI Investment), in 2016 to build direct faculty-to-faculty research partnerships between faculty at Virginia Tech and faculty at various HBCUs/MSIs. With the rarity of such initiatives and recognizing the primacy of the topic, this doctoral study was defined in the context of the ICTAS DandI Investment to investigate the little-understood phenomenon of research collaboration between faculty at HBCUs/MSIs and faculty at PWIs. The study informed by several bodies of literature including social psychology, inter-organizational relationships, and ethics and moral philosophy. A qualitative multiple case study approach was employed to explore factors that influence the sustainability of collaboration considering the perspectives of faculty in the context of the ICTAS DandI Investment. The ICTAS DandI Investment-related reports as well as survey and interview data were collected from 15 faculty members representing eight collaborative teams, across Virginia Tech and six different HBCUs. The findings indicate that potential collaboration and sustainability of partnerships rely on dynamic interactions between three dimensions in temporal context: Structure, broader institutional and contextual elements, Diversity, similarities and differences between team members' characteristics, abilities, and identities, and Relation, interactions and exchanges between collaborators and their outputs in doing collaboration. The study shows ICTAS has been successful in facilitating fruitful collaborations among faculty participants at different institutions. Based on the findings in this study I recommend that forging and maintaining long-term relationships of collaborative teams across HBCUs and PWIs need attention to the importance of capacity building over time and broader organizational and administrative factors such as support structure and credit allocation. Further, I recommend that administrators and policymakers to develop similar programs as a strategy for broadening participation and enhancing diversity, equity, and inclusion, not merely as a means for enhancing research productivity. / Doctor of Philosophy / Research collaborations between faculty members have become a common practice in higher education. The number of research collaborations across institutions, inter-institutional research collaborations, has increased significantly over the last few decades. However, there has been a disparity of partnerships between universities with different history, missions and identities. Collaborations among elite universities and Predominantly White Institutions (PWIs) appear better supported and far more common than collaborations between Historically Black Colleges and Universities (HBCUs) or other minority-serving institutions (MSIs) and PWIs. Considering the rarity of faculty collaboration across HBCUs/MSIs and PWIs and the lack of research studies on the process and dynamics of faculty collaboration, this dissertation study aimed to enhance the understanding of research collaboration between faculty at HBCUs/MSIs and PWIs. The study was defined in the context of a seed funding program, the ICTAS Diversity and Inclusion Seed Investment Program (ICTAS DandI Investment) at Virginia Tech. The program aims to facilitate research partnerships between faculty at Virginia Tech, a PWI, and faculty at HBCUs/MSIs. The general phenomenon of interest was faculty research collaboration across HBCUs/MSIs and PWIs. The dissertation specifically investigated factors that facilitate sustainable collaboration between faculty at HBCUs/MSIs and a PWI, primarily through understating faculty experiences with collaboration. In this study, sustainability has been characterized as continued working relationship between faculty at Virginia Tech and faculty at HBCUs/MSIs beyond the funding period, when they first received support through the ICTAS DandI Investment. Fifteen faculty members representing eight collaborative teams, across Virginia Tech and six different HBCUs, participated in this study. The primary sources of data were individual interviews and survey questionnaires. The data analysis and comparison across different teams indicated several factors essential to sustainable inter-institutional faculty collaboration. The factors were further aggregated to three broader dimensions: Structure, broader institutional and contextual elements; Diversity, similarities and differences between team members' characteristics, abilities, and identities; and Relation, interactions and exchanges between collaborators and their outputs in doing collaboration. In addition, the findings indicated that time plays an essential role in team processes. Based on the findings in this study, I recommend that forging and maintaining long-term relationships of collaborative teams across HBCUs and PWIs need attention to the importance of capacity building over time and broader organizational and administrative factors such as support structure and credit allocation. Further, I recommend that administrators and policymakers to develop similar programs as a strategy for broadening participation and enhancing diversity, equity, and inclusion, not merely as a means for enhancing research productivity.

The focus of this paper is on cross-region R&D collaboration funded by the 5th EU Framework Programme (FP5). The objective is to measure distance, institutional, language and technological barrier effects that may hamper collaborative activities between European regions. Particular emphasis is laid on measuring discrepancies between two types of collaborative R&D activities, those generating output in terms of scientific publications and those that do not. The study area is composed of 255 NUTS-2 regions that cover the pre-2007 member states of the European Union (excluding Malta and Cyprus) as well as Norway and Switzerland. We employ a negative binomial spatial interaction model specification to address the research question, along with an eigenvector spatial filtering technique suggested by Fischer and Griffith (2008) to account for the presence of network autocorrelation in the origin-destination cooperation data. The study provides evidence that the role of geographic distance as collaborative deterrent is significantly lower if collaborations generate scientific output. Institutional barriers do not play a significant role for collaborations with scientific output. Language and technological barriers are smaller but the estimates indicate no significant discrepancies between the two types of collaborative R&D activities that are in focus of this study. (authors' abstract) / Series: Working Papers in Regional Science

This dissertation endeavours to address an identified gap in literature concerning the relationship between New Zealand and the European Union (EU) in the field of research, science and technology (RS&T). Examination of the partnership begins with the creation of the Science and Technological Cooperation (STC) Arrangement in 1991 and comes to a close in 2008, following the Arrangement’s ‘upgrade’ to an STC Agreement on 16 July. During this time, the intensification of the EU’s activities in RS&T is evident. The Seventh Framework Programme (FP7) currently constitutes the most internationalised Programme to date. Identifying the complementary nature of New Zealand and EU research priorities thus suggests that now, more than ever, the New Zealand research community stands to gain from participation within such an inclusive venture. Aiming to assess the current status of New Zealand-EU research collaboration, the research identifies a number of recurring themes, both positive and negative, that influence the nature of the RS&T relationship. These themes focus on problems concerning visibility within the EU, geographical isolation from this important market, an absence of targeted domestic funding for New Zealand-EU RS&T collaboration and the unwieldy bureaucratic process of the Framework Programme. The research also determines the importance of both ‘official’ and ‘informal’ mechanisms’ in combating the outlined collaborative bottlenecks. Taking these themes into account, the thesis ultimately looks to provide recommendations concerning the future of New Zealand-EU engagement in this field.

Um effektiv auf neue Marktgegebenheiten reagieren zu können, versuchen Industrieunternehmen ihre internen Geschäftsabläufe schlank und effizient zu halten. Dies stößt jedoch an Grenzen, wenn tradierte Unternehmens-IT im Zuge der digitalen Transformation mit neuen Geschäfts- und Bedienfähigkeiten ausgestattet werden soll. Die Integration von Systemen und Daten sowie die prozessuale Steuerung einer sich neu ordnenden IT-Landschaft verlangt nach neuen Konzepten, die die Besonderheit von kooperativen Wertschöpfungsprozessen berücksichtigen. Der Beitrag stellt die Anwendung der Action Design Research für die Konzeption, Entwicklung, Einführung und Auswertung einer IT-Applikation innerhalb eines Anwendungsfalls der Montageplanung der Automobilproduktion heraus. Dazu wird der Ansatz der Conversational Workflows, ein für die Zusammenarbeit in wissensintensiven, kooperativen Industrieprozessen entwickelter Applikationsaufbau, zur Lösung der Problemstellung herangezogen. Mit Hilfe eines auf den Anwendungsfall angepassten Ablaufs der Action Design Research werden in zwei partizipativen ADR-Zyklen sowohl eine MVP-Version als auch eine produktive Variante einer Web-Applikation für die Materialmodulbereitstellung entwickelt und im Praxissystem erlebbar gemacht. Im Ergebnis konnte sich das Konzept der Conversational Workflows als geeignet herausstellen und lässt zusätzlich Raum für kontinuierliche Weiterentwicklungen. Auf methodischer Seite hat sich gezeigt, dass eine Ergänzung der konzeptionellen ADR-Phasen um Design Thinking zu einer verbesserten Artefaktentwicklung beitragen kann.

This paper describes the background, objectives and methods of my doctoral research concerned with the support of the initiation of research collaboration with the help of information and communication technologies. The research is based on the assumption that providing more information about potential partners would lead to better-grounded decisions about collaboration. The purpose of this research is also to support and utilize Open Research. To address these aims, I suggest the design and creation of an ePortfolio that will aggregate information from the Internet, particularly Web 2.0 applications.

Eine evidenzbasierte Gestaltung von Studium und Lehre, wie sie heute normativ eingefordert wird, bedarf des integrierten Zusammenwirkens von Qualitätsmanagement und Hochschuldidaktik – aber gibt es dieses in der Praxis? Mit Blick auf die allgemeine Befundlage, aber auch anhand einer eigenen empirischen Untersuchung zeigt der Beitrag diesbezüglich auf, dass Qualitätsmanagement und Hochschuldidaktik als weitgehend desintegrierte Funktionsbereiche wahrgenommen werden und Evidenzbasierung in der Praxis folglich keinen sehr hohen Stellenwert genießt. Ausgehend von einer Ursachenanalyse wird auf die dysfunktionalen, aber auch auf die funktionalen Auswirkungen dieser Separierung aufmerksam gemacht.

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