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The three missions of universities are education, research, and knowledge/technology transfer. At the micro‐level of the research and knowledge/technology transfer mission, we position researchers, as individuals who decided to pursue a scientific career in academia, with the PhD as the starting point. While existing literature acknowledges the supervisor's significance during this process from dependency to autonomy, this paper advocates for a closer examination of external factors such as the network, supervisor's experience, and work environment in idea generation. Ideas in this context encompass both curiosity‐driven and entrepreneurial concepts, often evolving from one to the other. Our research builds upon the theory of opportunity identification, drawing parallels between ideas and opportunities. The research asserts that PhD students primarily rely on their networks for idea generation due to limited prior knowledge and experience. Our findings underscore the dynamic interplay between PhD students, supervisors, and networks in the process of idea generation, advancing a comprehensive framework encapsulating the multifaceted influences on the trajectory from idea generation to execution in the context of PhD education. The framework is based on empirical evidence from a qualitative case study comprising 16 PhD students in a European H2020 project in the field of Photonics, illuminating the intricate relationship between supervisors' orientations (entrepreneurial or curiosity‐driven) and the types of ideas generated by PhD students. Practical implications highlight the need for tailored support and resources to foster independent research capabilities among PhD students, considering individual variations in supervisory support and networking opportunities. [ABSTRACT FROM AUTHOR]

We examine how hospital cost efficiency can improve because of knowledge spillover effects, arising from the experiences of members of a healthcare system. We identify two types of functional technology networks—that we term repository-type and workflow-type networks—which are defined by the adoption patterns of different types of electronic health record (EHR) systems application functions by hospitals in a health system. Additionally, we examine how structural features of these two network types—namely, network centrality and interconnectedness—impact such knowledge spillover effects. By analyzing seven years of panel data for 1,420 U.S. hospitals across 216 health systems, and data obtained from surveys of healthcare experts, we found that greater centrality of nodes in repository-type networks enhances the influence of partners' experiences on cost efficiency but has the opposite effect in workflow-type networks, while greater interconnectedness of workflow-type networks enhances the influence of partners' experiences on cost efficiency. Interestingly, we found the opposite effect in repository-type networks, where greater interconnectedness diminishes the influence of partners' experiences on cost efficiency. We discuss reasons for this surprising and counterintuitive finding. Overall, our results demonstrate that at least in healthcare settings where information technologies enable knowledge-sharing networks to be formed, benefits can accrue through knowledge spillover effects; moreover, variations across functional categories of technologies adopted in a network context can result in different technology-network structures with differential impacts on hospital cost efficiency because of their influence on knowledge spillover at both the hospital and system levels. Not only can these results explain mixed findings in the literature that has been dominated by a focus on cost efficiency outcomes dependent solely on the EHR adoption choices of individual hospitals, but they also provide the basis for guidelines for a network-based perspective of technology adoption. We discuss other possible settings to which our empirical findings can be reasonably generalized, including supply chain technologies and the Internet of Things. [ABSTRACT FROM AUTHOR]

Abstract With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants’ performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation.

We leverage the knowledge network representation of the Medical Subject Heading (MeSH) ontology to infer conceptual distances between roughly 30,000 distinct MeSH keywords — each being prescribed to particular knowledge domains — in order to quantify the origins of cross-domain biomedical convergence. Analysis of MeSH co-occurrence networks based upon 21.6 million research articles indexed by PubMed identifies three robust knowledge clusters: micro-level biological entities and structures; meso-level representations of systems, and diseases and diagnostics; and emergent macro-level biological and social phenomena. Analysis of cross-cluster dynamics shows how these domains integrated from the 1990s onward via technological and informatic capabilities — captured by MeSH belonging to the “Technology, Industry, and Agriculture” (J) and “Information Science” (L) branches — representing highly controllable, scalable and permutable research processes and invaluable imaging techniques for illuminating fundamental yet transformative structure–function–behavior questions. Our results indicate that 8.2% of biomedical research from 2000 to 2018 include MeSH terms from both the J and L MeSH branches, representing a 291% increase from 1980s levels. Article-level MeSH analysis further identifies the increasing prominence of cross-domain integration, and confirms a positive relationship between team size and topical diversity. Journal-level analysis reveals variable trends in topical diversity, suggesting that demand and appreciation for convergence science vary by scholarly community. Altogether, we develop a knowledge network framework that identifies the critical role of techno-informatic inputs as convergence bridges — or catalyzers of integration across distinct knowledge domains — as highlighted by the 1990s genomics revolution, and onward in contemporary brain, behavior and health science initiatives.

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants' performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation. [ABSTRACT FROM AUTHOR]

In this article, we investigate the reasons behind the puzzling enthusiastic reception of a book about Finland's national development by Turkish nationalist intellectuals in the early Republic of Turkey. Published in Turkish in 1928, the developmental model laid out in Petrov's The Country of White Lilies resonated with the Turkish intelligentsia and has remained a popular book in Turkey throughout the twentieth century, and even today. First, we compare the fictionalized developmental model presented by Petrov in his book with Finnish development under the Russian Empire, before its independence in 1917. Second, we show that this reception was largely based on a comparison of Turkey and Finland's geopolitical positions in global imperial politics, and a constructed racial affinity between the two nations in the minds of Turkish readers. Third, we argue that this national developmental model served three ideological purposes; distancing the Turkish Republic from the Ottoman Empire, showing the developmental capacity of nations outside the linear and paternalistic developmental model proposed by Western European empires, and last, presenting a model that glosses over Ottoman-Turkish state violence and ethnic cleansing, as well as democratic processes, as irrelevant to considerations of progress and development. Finally, we discuss the implications of our study for re-evaluating the sociological literature on nation formation, largely taking its "model cases" (Krause 2021) from the Western European experience, through a more encompassing inter-imperial approach (Doyle 2014). [ABSTRACT FROM AUTHOR]

Innovation ambidexterity is important for firms, but their ability to develop both strategies simultaneously has been conventionally challenged. This challenge is caused by the heterogeneous demands of distinct capabilities and resources of exploratory and exploitative innovations. This paper thus investigates the interplay among internal and external collaborations, ambidextrous innovation, and absorptive capacity in small firms. Using a dataset of 228 Australian firms and applying the PLS‐SEM method, we find that supply chain networks influence only exploitative innovation, and knowledge‐oriented networks influence only exploratory innovation. However, employee engagement directly influences both exploratory and exploitative innovation. Absorptive capacity fully mediates the relationship between employee engagement and exploratory innovation and partially mediates the other relationships. The findings support the argument that balancing exploratory and exploitative innovation in firms is important instead of choosing one strategy over the other. It provides empirical evidence of employee engagement as a common antecedent of ambidextrous innovation and the differential effects of supply chain‐oriented and knowledge‐oriented networks. They will inform innovation strategy decisions of firms primarily on the need to broaden external networks and promote employee engagement in the innovation process and that the benefits of knowledge networks for exploratory innovation are realized fully through absorptive capacity. [ABSTRACT FROM AUTHOR]

Higher education institutes both foster the advancement of knowledge and address society's socioeconomic and environmental challenges. To fulfil these multiple missions requires significant changes to how the role of a researcher is perceived e.g. a researcher identity that is congruent with the objective of contributing to fundamental knowledge while also engaging with non-academic actors, broadly, and entrepreneurship, in particular. We argue that the early stages of an academic career—namely the PhD training trajectory—and the knowledge networks formed during this period have a major influence on the scientist's future capacity to develop an appropriate researcher role identity. We draw on knowledge network and identity theories to investigate how the knowledge networks (i.e. business, scientific and career knowledge networks) of PhD students promote changes to, reinforce or conflict with the perception of a researcher role identity. Our longitudinal qualitative network study includes PhD students and their supervisors funded by the H2020 FINESSE project. At the network level, we show that scientific knowledge is distributed equally throughout young academics' networks but that entrepreneurial (business) and career knowledge tend to be concentrated around certain individuals in these networks. On the PhD student level, we observe different pronunciations of the researcher role identity linked to students' interactions with their knowledge networks. We distinguish identity conflicts due to misalignment between ego and alters which leads to withdrawal from the network. Our findings have practical implications and suggest that universities and PhD student supervisors should support PhD students to develop a researcher identity which is in line with the individual PhD student's expectations. [ABSTRACT FROM AUTHOR]

Starting from sites of yogic and Buddhist learning connecting Indonesia and India this article explores the politics, practices, transformation, dissemination and uses of knowledge on yoga and meditation in late colonial and postcolonial Indonesia, and their relation to moral geographies of Greater India. It follows, across (violent) regime changes, the trajectories of learning of a number of self-made experts and entrepreneurs in this field who were also involved in the postcolonial Buddhist reform movement in Indonesia: the Chinese Indonesians Souw Tjiang Poh (b.1929), better known, also as yoga guru, under his Buddhist name Yogamurti; and his meditation teacher, Tee Boan An (1923–2002), who, as Ashin Jinarakkhita, is more famous as motor behind the Buddhist reform movement in Indonesia from the 1950s onwards. Yogamurti's and Tee Boan An's histories of 'yogic' transformation reach back to 'alternative' spiritual reform trajectories of the Theosophical Society of late colonial times, and continue, across decolonization and the violent regime change of 1965, to those of the hippie trail of the 1970s. These spiritual and 'Indic' religious revivalist entrepreneurs provide alternative perspectives to the grand narratives of political history, yoga, 'Indian religion' or 'Greater India'. Across regime changes, their paths crossed and they exchanged knowledge, thereby changing and reshaping social hierarchies as they moved within an 'alternative present' in which spirituality seemed a way to move forward to 'alternative futures'. [ABSTRACT FROM AUTHOR]

Online reviews often contain considerable information redundancy. Understanding how to mine and identify valuable information is an important research topic. Based on knowledge-based theory and social network theory, this study discusses the impact of knowledge redundancy in online travel reviews on consumer purchase behaviour from the perspective of knowledge networks. By crawling 943,516 online reviews of 609 tourism products from Trip and Tuniu, we conduct an empirical analysis of the relationships among knowledge redundancy, knowledge diversity and consumer purchase behaviour. The results show that there is a U-shaped relationship between knowledge redundancy in online tourism reviews and consumer purchase behaviour, and knowledge diversity plays an intermediary role in the relationship between knowledge redundancy and consumer purchase behaviour. The results provide valuable and timely insights for the development of the online tourism industry. [ABSTRACT FROM AUTHOR]

Knowledge networks have become a critical factor in the development of innovation. However, most studies focus on the innovation benefits derived from network embedding, and there are fewer studies on firms' knowledge networks from the perspective of feature attributes. This study analyzes the direct and interactive effects of knowledge diversity and the combination of knowledge potential on innovation performance. The research also explores how the complementarity of ambidextrous learning affects the relationship between knowledge networks and innovation performance. The empirical analysis is based on panel data from 116 firms in China's automotive manufacturing industry from 2010-2018. The results processed by the fixed effects negative binomial regression model indicate that the combinatorial potential of knowledge has an inverted U-shaped relationship with firm innovation performance, and knowledge diversity has a positive effect on firm innovation performance. There is an interactive effect between knowledge combination potential and knowledge diversity, and their mutual coordination improves firm innovation performance. The complementarity of ambidextrous learning significantly and positively moderates the positive relationship between the combination potential of knowledge and firm innovation performance. [ABSTRACT FROM AUTHOR]

This paper investigates the centrality of knowledge management as an enabler of economic development opportunities in the Niger Delta region. Given the developmental challenges facing the Niger Delta region, it is imperative that knowledge management should be harnessed as a tool for development. From the prism of PIND and leveraging a qualitative and descriptive approach, this study adopts focus group discussions and in‐depth interviews to affirm that knowledge management is an effective tool for fostering economic development. Results reveal that while information on development is not readily available to the citizens of the region, as well as a low level of awareness of developmental initiatives within local communities, the study contends that in order to stimulate economic development in the Niger Delta region, a robust knowledge management framework that takes cognisance of the innate needs of the people through citizen engagement must be instituted. Also to be considered is the literacy level, the medium of communication and the physical terrain of the region, which makes it challenging to extend developmental activities to all corners of the Niger Delta. The study, therefore, recommends the use of social media to improve information dissemination and the formation of knowledge clusters facilitated by ICT to expand the scope of operations in all local communities in the region. [ABSTRACT FROM AUTHOR]

Theoretical constructs, such as the information gap theory and compression progress theory, seek to explain how humans practice curiosity. According to the former, curiosity is the drive to acquire information missing from our understanding of the world. According to the latter, curiosity is the drive to construct parsimonious mental world models. To complement the densification and simplification processes inherent to these frameworks, we propose the conformational change theory, wherein we posit that curiosity builds mental models with marked conceptual flexibility. We formalize curiosity as a knowledge-network-building process to investigate each theoretical account for individuals and collectives. In knowledge networks, gaps can be identified as topological cavities, compression progress can be quantified using network compressibility, and flexibility can be measured as the number of conformational degrees of freedom. We find that curiosity fills gaps and constructs increasingly compressible and flexible knowledge networks. Across individuals and collectives, we determine the contexts in which each account is explanatory, clarifying their complementary and distinct contributions. Our findings offer a novel networks-based perspective that harmonizes with (and compels an expansion of) the traditional taxonomy of curiosity. [ABSTRACT FROM AUTHOR]

Knowledge construction can be facilitated through different types of social interactive environment. A knowledge network environment (KN) develops a knowledge-centered network visualizing the structure of collective knowledge. A social network environment (SN) creates a people-centered network visualizing the social relationships among people. Considering the connectedness of knowledge and people, this study moves the conversation forward by introducing an integrated environment of both knowledge- and people-centered network, a social knowledge network environment (SKN). The study aimed at comparing the three types of environments and investigated their effect on collaborative knowledge construction processes and individual learning outcomes. The quasi-experiment results indicated that these three environments differed in their effects on learners' knowledge construction levels, the sequential patterns, as well as individual learning outcomes. Learners in SN had a highest rate of social interaction than the learners in the other environments. KN learners had a higher rate of allocentric elaboration than SN learners. SKN learners showed a higher level of surface and elaborative application, reflection, and knowledge construction outcomes than KN and SN learners. The different roles of social interactions were further discussed across three environments. [ABSTRACT FROM AUTHOR]

Copyright of Research Papers of the Wroclaw University of Economics / Prace Naukowe Uniwersytetu Ekonomicznego we Wroclawiu is the property of Uniwersytet Ekonomiczny we Wroclawiu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We develop a quantitative framework for understanding the class of wicked problems that emerge at the intersections of natural, social, and technological complex systems. Wicked problems reflect our incomplete understanding of interdependent global systems and the systemic risk they pose; such problems escape solutions because they are often ill-defined, and thus mis-identified and under-appreciated by communities of problem-solvers. While there are well-documented benefits to tackling boundary-crossing problems from various viewpoints, the integration of diverse approaches can nevertheless contribute confusion around the collective understanding of the core concepts and feasible solutions. We explore this paradox by analyzing the development of both scholarly (social) and topical (cognitive) communities — two facets of knowledge production studies here that contribute towards the evolution of knowledge in and around a problem, termed a knowledge trajectory — associated with three wicked problems: deforestation, invasive species, and wildlife trade. We posit that saturation in the dynamics of social and cognitive diversity growth is an indicator of reduced uncertainty in the evolution of the comprehensive knowledge trajectory emerging around each wicked problem. Informed by comprehensive bibliometric data capturing both social and cognitive dimensions of each problem domain, we thereby develop a framework that assesses the stability of knowledge trajectory dynamics as an indicator of wickedness associated with conceptual and solution uncertainty. As such, our results identify wildlife trade as a wicked problem that may be difficult to address given recent instability in its knowledge trajectory.

Ornamental plants play a fundamental role in diverse applications, from cut flower production to landscape design and space decoration. The ornamental industry, which is part of horticulture, has experienced significant advances and mobilizes billions of dollars in the global economy, being also a totally globalized market. In recent years, this industry has implemented advanced production strategies, from genetic improvement to sustainability and supply chain, promoting scientific research in various areas. However, the dispersion of knowledge has hindered the integration of the various research networks. Therefore, this article seeks to provide an overview of the scientific production in the cut flower sector, establishing a reference line for researchers, using bibliometrics as a tool to identify trends and the scientific structure of this area of knowledge. The results revealed that worldwide since 1983 there have been 975 articles focused on this productive system, gene rated in more than 69 countries by 2750 authors who published their research in 160 academic journals. Relevant research topics that are already developed and those that need a more intense and integrated research focus on the knowledge already generated were also identified.

Copyright of NovaRUA Revista Universitaria de Administracion is the property of NovaRUA Revista Universitaria de Administracion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Business Law Journal / Administração de Empresas em Revista is the property of Administracao de Empresas em Revista and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Journal of Law & International Relations / Relações Internacionais no Mundo is the property of Relacoes Internacionais no Mundo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study seeks to investigate firm-level innovation, exploring whether social relationships located in knowledge networks influence the transfer of university knowledge to Ghanaian firms. Firms’ informal relationships with universities have been under-researched in developing economies. The extant literature suggests that informal relationships in the context of economies with advanced regional and national innovation systems have a positive association with firm level innovation performance. The research project employs a cross-sectional survey of 245 firms in Ghana. The aim of the project is to explore the influence of informal mechanisms of university knowledge transfer on firm level innovation performance in Ghana. The study adopts a structural model with partial least squares as an analytical technique. The findings reveal that to deliver positive results in a firm’s innovation performance by informal means, a well-coordinated social system to attract research knowledge from all aspects of the university system is required. The research project’s implications for Ghana’s innovation system include a need to be aware of the impact of corruption and lack of intellectual property rights on the efficacy informal knowledge transfer.

Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task and requires the application of natural language processing methodology. In this article, we implement and evaluate multiple machine learning models for coding energy knowledge in free‐text responses of German K‐12 students to items in formative science assessments which were conducted during synchronous online learning sessions. Dataset: The dataset we collected for this purpose consists of German constructed responses from 38 different items dealing with aspects of energy such as manifestation and transformation. The units and items were implemented with the help of project‐based pedagogy and evidence‐centered design, and the responses were coded for seven core ideas concerning the manifestation and transformation of energy. The data was collected from students in seventh, eighth and ninth grade. Methodology: We train various transformer‐ and feature‐based models and compare their ability to recognize the respective ideas in students' writing. Moreover, as domain knowledge and its development can be formally modeled through knowledge networks, we evaluate how well the detection of the ideas within responses translated into accurate co‐occurrence‐based knowledge networks. Finally, in terms of the descriptive accuracy of our models, we inspect what features played a role for which prediction outcome and if the models pick up on undesired shortcuts. In addition to this, we analyze how much the models match human coders in what evidence within responses they consider important for their coding decisions. Results: A model based on a modified GBERT‐large can achieve the overall most promising results, although descriptive accuracy varies much more than predictive accuracy for the different ideas assessed. For reasons of comparability, we also evaluate the same machine learning architecture using the SciEntsBank 3‐Way benchmark with an English RoBERTa‐large model, where it achieves state‐of‐the‐art results in two out of three evaluation categories. Lay Description: What is already known about this topic?: Formative assessments are needed to test and monitor the development of learners' knowledge throughout a unit to provide them with appropriate automated feedback.Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge.Assessing constructed responses in an automated fashion is a widely researched topic, but the problem is far from solved and most of the work focuses on predicting holistic scores or grades.To allow for a more fine‐grained and analytic assessment of learners' knowledge, systems which go beyond predicting simple grades are required.To guarantee that models are stable and make their predictions for the correct reasons, methods for explaining the models are required. What this papers adds?: A core topic in physics education is the concept of energy.We implement and evaluate multiple systems based on natural language processing technology for assessing learners' conceptual knowledge about energy physics using transformer language models as well as feature‐based approaches.The systems assess students' knowledge about various forms of energy, indicators for the same and the transformation of energy from form into another.As our systems are based on machine learning methodology, we introduce a novel German short answer dataset for training them to detect the respective knowledge elements within students' free‐text responses.We evaluate the performance of these systems using this dataset as well as the well‐established SciEntsBand‐3‐Way dataset and manage to achieve, to our best knowledge, new state‐of‐the‐art results for the latter.Moreover, we apply methodology for explaining model predictions to assess whether predictions are carried out for the correct reasons. Implications for practice and/or policy: It is indeed possible to assess constructed responses for the demonstrated knowledge about energy physics in an analytic fashion using natural language processing.Transformer language models can outperform more specialized feature‐based approaches for this task in terms of predictive and descriptive accuracy.Co‐occurrences of different concepts within the same responses can lead models to learn undesired shortcuts which make them unstable. [ABSTRACT FROM AUTHOR]

Copyright of Tecnura is the property of Tecnura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Despite its recent growth in popularity since the COVID-19 pandemic, One Health* can be traced back to the colonial period when it was used to control the health of local communities and their animals while exploiting natural resources. At present, it is necessary to move away from this asymmetrical colonialist view and develop more inclusive perspectives. Local communities have their own knowledge with a holistic vision of health involving humans, animals and the environment. Their viewpoint is nevertheless rarely taken into consideration within the scientific approach to health. To fill this gap, the humanities and social sciences can be used to revive this local knowledge and to initiate a dialogue with scientific knowledge. More crucially, to effectively put One Health into practice, researchers must call into question their own practices, reflect on what constitutes science and rethink the way of producing knowledge, all the while acknowledging the different ways of understanding the world and diseases. This means opening up to other forms of knowledge and epistemologies and networking them.

The revolutionary advancement of technology in the past decade brought the attention of academics and management practitioners to ways of improving innovative capabilities of organizations. Advice-seeking relationships have an essential role in the knowledge production of modern-day organizations as they enable actors to acquire information, professional support and knowledge elements that they can recombine to form new knowledge. This paper conceptualizes advice-seeking behaviour as part of an inherently complex social world that can best be captured by a multiplex approach to organizational network research. It investigates how different layers of interpersonal relationships in the workplace may contribute to the appearance of advice-seeking interactions. This study examines the cases of three knowledge-intensive organizations and applies binary logistic regression to shed light on the yet invisible relational foundations of workplace collaboration. Implications for Central European audience: Central European countries attempt to improve their economic competitiveness by attracting knowledge-intensive companies as well as incentivizing innovation and digital transformation. Knowledge-intensive firms, such as business service centres or information and communication technology companies, are significant contributors to the economic output of countries such as the Czech Republic, Hungary and Poland. Recommendations derived from the results of this paper provide insights into the leadership of knowledge-intensive companies regarding creation of organizational environments that foster knowledge sharing and innovation. Measures that promote interpersonal trust, visibility of expertise and boundary-spanning behaviour are recommended. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramifications, in order to analyze its growth. The study was developed under the bibliometric approach and considered the period 1990–2019. The steps followed were (i) Identification and selection of keyword terms in three methodological layers by a panel of experts. (ii) Design and application of an algorithm to identify these selected keywords in titles, abstracts, and keywords using terms in Web of Science to contrast them. (iii) Performing data processing based on the Journals of the Journal Citation Report during 2020. Knowing the evolution of a field of knowledge such as AI from a bibliometric study and subsequently establishing the ramifications of new research streams is in itself a relevant finding. Addressing a broad field of knowledge as AI from a multidisciplinary approach given the convergence it generates with other disciplines and specialties is of high strategic value for decision makers such as governments, academics, scientists, and entrepreneurs. [ABSTRACT FROM AUTHOR]

The effects of climate change are instigating a discourse shift towards net-zero emissions agriculture. However, a sectoral silo paradigm of policy design is incompatible with a systems approach to address complex global environmental challenges. This study introduces a social cartography approach that amalgamates network theory with a nexus perspective to identify social relation changes in the making. The study examines the role of an advisor-led initiative promoting the discourse of climate-smart farming in Scotland and identifies the impacts upon farmer knowledge networks. The social cartography comprises of a survey, farm meeting observations, and social network analysis of the agriculture, climate change, and energy (ACE) policyscape. As a visualization method, the social cartography provides a conceptual compass to navigate social relation changes of farmer knowledge networks amidst discursive transition. The results demonstrate that the advisor-led initiative acts an intermediary of discursive transition by introducing new knowledge frames and practices of farming that facilitate network shifts. However, voluntary measures fall short of instigating cross-sectoral interplay to actualize transformation towards systems integration. Furthermore, the study presents policy design elements to chart a new frontier of integrated agrifood and energy systems governance in Scotland. • Innovative policyscape approach to agrifood systems transformation. • Novel ACE nexus concept: agriculture, climate change, energy policy intersection. • Role of advisors as intermediaries in farmer knowledge networks. • Social processes and properties for discourse transition. • Policy design elements for integrated agrifood and energy systems governance. [ABSTRACT FROM AUTHOR]

Today we live in a global network of knowledge–as shown recently by the worldwide interactive research on Covid-19. Nevertheless, knowledge is distributed differently around the world and is perceived and valued differently in different cultures. This also applies to different strata within societies. The fact of a global world of knowledge and its horizontally and vertically different perception, interpretation and usage raises several problems. These can be explained above all by the sociogenesis of the global knowledge world and its fundamental lines and moments of development. Even a brief look at history shows that knowledge has been and is exchanged from earliest times till nowadays. This fact in turn raises questions and problems that we want to address systematically. What is "knowledge"? Sciences? Arts and crafts? When, by whom, in what form was knowledge disseminated? What is knowledge transfer? Exchange? Is it a mere transport, a deliberate exchange, or a kind of silent appropriation of foreign knowledge? In the following, some of these questions will be dealt with systematically. The historical material as well overarching question is the exchange of knowledge in Eurasia and here specifically the transfer and exchange of knowledge between Europe and China. After a preliminary clarification of terms and questions, the transfer of knowledge between Europe and China from the earliest times up to the Yuan Dynasty will be surveyed. Subsequently, the basic concepts and questions can be discussed and sharpened for further research. An outlook on the historical phase of a deliberate transfer and finally exchange of knowledge between China and Europe since the early modern period concludes the study. The aim of this work is not primarily to describe the historical course of individual exchange processes, but to clarify questions and problems for future empirical studies regarding the research landscape. [ABSTRACT FROM AUTHOR]

• We revealed the influence of network embeddedness and knowledge stock on collaboration dynamics. • We identify graphlet degree distribution to expand the measurement of local network embeddedness. • We extract fine-grained knowledge elements to feature knowledge stock. • Organizations with more partners and annular graphlets are less likely to collaborate. • An assignee with broader knowledge, lower knowledge network transitivity, or superior knowledge combinatorial capability tends to seek new collaborators. Science, technology, and innovation are becoming increasingly collaborative, prompting concerted efforts to understand and measure the factors influencing these collaborations. This study aims to explore the driving factors and underlying mechanisms of collaboration dynamics based on patent data. Multilayer longitudinal networks are constructed to scrutinize interactions among organizations as well as the embedding of their knowledge elements in the network fabric. We then analyze the structures and characteristics of collaboration and knowledge networks from global and local perspectives, in which process topological indicators and graphlets are used to feature each organization's collaborative patterns and knowledge stock. Knowledge elements are extracted to present the core concepts of patents, overcoming the limitations of predefined categorizations, such as IPC, when representing technological content and context. By performing a longitudinal analysis using a stochastic actor-oriented model, we integrate network structures, node characteristics, and different dimensions of proximity to model collaboration dynamics and reveal the driving factors behind them. An empirical study in the field of lithography finds that organizations with a larger number of partners or a higher number of annular graphlets in their collaboration networks are less likely to collaborate with others. If an assignee has a more extensive range of knowledge elements and demonstrates a higher capability for knowledge combination, or if its local knowledge network exhibits weaker connectivity, its propensity to seek new collaborators increases. Both cognitive and organizational proximity play important roles in fostering collaboration. [ABSTRACT FROM AUTHOR]

• Exposing the knowledge networks' robustness from aspects of structure and function. • Unveiling the possible damage of targeted attacks to knowledge networks. • Conceptualizing the knowledge element and measuring it by patent-related indicators. • Clarifying the diverse importance of knowledge elements in maintaining robustness. A new framework is proposed to comprehensively explore the robustness (structure and function) of knowledge networks under different targeted attacks. Results show that (1) recalculated-based attacks cause greater damage than initial-based attacks. Meanwhile, a higher price is needed to destroy the structure than disrupt the function of the knowledge network. (2) Maintaining the structure of the knowledge network not only depends on the position that high-degree knowledge elements occupy in the maximal connected subgraph and their upper limit of combinatorial value but also relies on the reducing requirement of new knowledge elements caused by local search and connections. (3) Embedding more knowledge elements that are involved in multiple knowledge domains with medium-degree distribution can consolidate the knowledge network's structure. With regard to enhancing network efficiency, highly relevant knowledge elements create an inverted U-shape influence, while diverse knowledge elements continuously exert positive effects. [ABSTRACT FROM AUTHOR]

This study seeks to investigate firm-level innovation, exploring whether social relationships located in knowledge networks influence the transfer of university knowledge to Ghanaian firms. Firms' informal relationships with universities have been under-researched in developing economies. The extant literature suggests that informal relationships in the context of economies with advanced regional and national innovation systems have a positive association with firm level innovation performance. The research project employs a cross-sectional survey of 245 firms in Ghana. The aim of the project is to explore the influence of informal mechanisms of university knowledge transfer on firm level innovation performance in Ghana. The study adopts a structural model with partial least squares as an analytical technique. The findings reveal that to deliver positive results in a firm's innovation performance by informal means, a well-coordinated social system to attract research knowledge from all aspects of the university system is required. The research project's implications for Ghana's innovation system include a need to be aware of the impact of corruption and lack of intellectual property rights on the efficacy informal knowledge transfer. [ABSTRACT FROM AUTHOR]