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Background Inter-organizational partnerships and collaborations, used here interchangeably, have growing prominence across the health sector. Successful partnerships have received extensive study. However, especially for partnerships including nonprofit partners, limited attention has been given to negative factors that contribute to struggling partnerships, including failed partnerships, and/or impede potential partnerships, including unexplored and undeveloped potential partnerships. This study aimed to explore these across diverse examples of struggling and potential partnerships considered otherwise worthwhile in principle, according to leaders and managers—in 13 countries across Asia-Pacific, EU+, North America—from diverse roles and settings across the health sector. It also aimed to explore success factors they said contributed to successful partnerships. Methods Interviews were conducted with 70 practitioners in 13 countries and a wide range of roles and nonprofit, industry, and government settings, including research institutions, across the health sector. Interviews covered their examples of struggling, potential, and successful partnerships; and, factors. Interview data were analyzed inductively, employing thematic network analysis. Comments underlying themes were reviewed regarding the participants concerned to note range (e.g., regions). Results Key findings included: (1) the many negative factors and success factors identified as themes; (2) their occurrence across diverse contexts, including different regions and institutional sectors (i.e., nonprofit, industry, government); (3) the complementarity of negative factors and success factors, with each set placing different emphasis on certain topics and negative factors both broadening the overall range of topics and contributing more to literature; (4) the occurrence of most negative factors with both struggling and potential partnerships. The 255 partnerships and potential partnerships discussed included nonprofit (190/255), industry (112/255), and/or government (140/255) partners. Many spanned two different institutional sectors (147/255); 86/255 spanned one; 20/255 spanned three. Conclusions The findings suggest three takeaways for practitioners: (1) factors used to consider partnerships should reflect factors from struggling partnerships and/or potential partnerships, plus successful partnerships; (2) negative factors can highlight opportunities to advance partnerships, individually and systematically; (3) practitioners should consider developing frameworks of factors from literature and experience to facilitate judicious consideration of partnerships and inform approaches, lessons drawn, and potential partnerships sought. Struggling and potential partnerships merit scholarly attention.
Background Inter-organizational partnerships and collaborations, used here interchangeably, have growing prominence across the health sector. Successful partnerships have received extensive study. However, especially for partnerships including nonprofit partners, limited attention has been given to negative factors that contribute to struggling partnerships, including failed partnerships, and/or impede potential partnerships, including unexplored and undeveloped potential partnerships. This study aimed to explore these across diverse examples of struggling and potential partnerships considered otherwise worthwhile in principle, according to leaders and managers—in 13 countries across Asia-Pacific, EU+, North America—from diverse roles and settings across the health sector. It also aimed to explore success factors they said contributed to successful partnerships. Methods Interviews were conducted with 70 practitioners in 13 countries and a wide range of roles and nonprofit, industry, and government settings, including research institutions, across the health sector. Interviews covered their examples of struggling, potential, and successful partnerships; and, factors. Interview data were analyzed inductively, employing thematic network analysis. Comments underlying themes were reviewed regarding the participants concerned to note range (e.g., regions). Results Key findings included: (1) the many negative factors and success factors identified as themes; (2) their occurrence across diverse contexts, including different regions and institutional sectors (i.e., nonprofit, industry, government); (3) the complementarity of negative factors and success factors, with each set placing different emphasis on certain topics and negative factors both broadening the overall range of topics and contributing more to literature; (4) the occurrence of most negative factors with both struggling and potential partnerships. The 255 partnerships and potential partnerships discussed included nonprofit (190/255), industry (112/255), and/or government (140/255) partners. Many spanned two different institutional sectors (147/255); 86/255 spanned one; 20/255 spanned three. Conclusions The findings suggest three takeaways for practitioners: (1) factors used to consider partnerships should reflect factors from struggling partnerships and/or potential partnerships, plus successful partnerships; (2) negative factors can highlight opportunities to advance partnerships, individually and systematically; (3) practitioners should consider developing frameworks of factors from literature and experience to facilitate judicious consideration of partnerships and inform approaches, lessons drawn, and potential partnerships sought. Struggling and potential partnerships merit scholarly attention.
Introduction: the use of bibliometric analyses is useful to gain insight into the development, trends, and impact of scholarly output on artificial intelligence (AI) in several fields.Objective: to characterize the worldwide scholarly output on AI in Scopus in the period 2013-2022.Method: a descriptive observational bibliometric study was carried out. The study population consisted of the 776,961 documents identified using SciVal. The following variables were studied: number of documents (Ndoc), year of publication, annual variation rate (AVR) of the scholarly output, type of document, source, number of citations (Ncit), field-weighted citation impact (FWCI), author(s), author-level h-index, institution, country, type of collaboration, and keyphrases.Results: the scholarly output showed a steady quantitative increase during the period studied, with a positive AVR. Conference papers (68.5%) and articles (26.5%) were the main types of documents. Neurocomputing led the list of sources in both Ndoc (12,989) and Ncit (351,837). The highest FWCI (3.02) corresponded to Proceedings – IEEE International Conference on Robotics and Automation. China, the United States and India were the countries with the highest Ndoc by year of publication. Institutional collaboration was the most common (46.7%) type of collaboration. The most prominent keyphrases were: Robot, Artificial Intelligence, Deep Learning, Convolutional Neural Network and Robotics. Conclusions: the scholarly production analyzed is characterized by its constant quantitative growth and is mostly represented by conference papers. Productivity and impact indicators based on citations show remarkable results. The science produced was led by China, and scientific collaboration played a relevant role.
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