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Knowledge transfer is considered the efficient way to improve regional innovation, but relatively little is known about how the innovation efficiency of scientific and technological (S&T) talents is affected by knowledge transfer within institutional environment, particularly, limited studies carried out regional differentiation analysis. Using panel data from 30 provinces in China between 2005 and 2017, this article empirically tests the influence of the institutional environment on knowledge transfer and analyses its impact between knowledge transfer and innovation efficiency of S&T talents in China. The results show knowledge transfer can significantly improve both the scientific and the economic innovation efficiency of S&T talents. Moreover, the effects of knowledge transfer on the innovation efficiency of S&T talents in eastern, central and western China had heterogeneity. Formal and informal institutions play mediating roles between knowledge transfer and innovation efficiency of S&T talents. This study contributes to the literature by constructing an econometric model with identified variables to test the impact of knowledge transfer on the innovation efficiency of S&T talents in China, in addition, the equation about knowledge transfer was explored. The research findings are valuable to regional governments and policymakers; our empirical evidence helps to develop more efficient strategy and policy planning. [ABSTRACT FROM AUTHOR]

The positive relationship between knowledge transfer and knowledge innovation is recognized by most scholars, while knowledge heterogeneity, as a knowledge situation of the enterprise organization, affects knowledge transfer within enterprise organizations. Therefore, as a state, knowledge transfer can be regarded as a result of knowledge heterogeneity, and it becomes the intermediary state between knowledge heterogeneity and knowledge innovation. The organizational structure of individuals within an enterprise organization may affect these three elements and their interrelationships. In this paper, data are collected by means of on-the-spot investigation and a network questionnaire for analysis. The results show that the microstructure state of the individual in the enterprise organization plays a moderating role for the first three elements. The lower that the micro-restriction of the individual is, the more favorable the knowledge heterogeneity is for the inverted U-shaped impact of knowledge transfer and knowledge innovation and the more favorable the occurrence of knowledge innovation. [ABSTRACT FROM AUTHOR]

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors. [ABSTRACT FROM AUTHOR]

This article explores the extent to which the regional higher education system (HES) influences the location of foreign research and development (R&D). To do so, we use a dataset with information on the location choices of new foreign R&D establishments within Spain from 2005 to 2013. Similarly, we use a multiple measure of the three university missions, distinguishing between research capacity training, scientific research, and technology transfer. We find that the probability of a foreign R&D establishment being located in a region is positively affected by the strength of the region's HES missions, and more specifically by the quality of its scientific research, while its research training capacity and knowledge transfer activities do not seem to play a significant role. Moreover, the strength of the research mission has a positive influence on the location choice of foreign units conducting research activities but is weak to explain the location of those performing development activities. JEL CLASSIFICATION F21; F23; O32 [ABSTRACT FROM AUTHOR]

Traditionally, extensive vehicle testing is applied to assure the robustness and safety of automotive systems. This approach is highly challenged by increasing system complexity. Formal verification lends a powerful framework for model-based safety assurance, but due to the mixed discrete–continuous behavior of automotive systems, traditional tools for discrete program verification are helpful but not sufficient. In academia, during the last two decades new approaches arose for the formal verification of such mixed discrete-continuous systems. However, the industry is not fully aware of this development, the tools are seldom tried and their applicability is not well examined. In a Ford–RWTH research alliance project, we aimed at evaluating the potential of knowledge and technology transfer in this area. This paper has two main objectives. Firstly, we want to report on the state-of-the-art in the above-mentioned academic development in a generally understandable form, targeted to interested potential users. Secondly, we want to share our observations after testing different available tools for their applicability and usability in the automotive sector and as a conclusion devise some recommendations. [ABSTRACT FROM AUTHOR]

Modern technology in the field of images led to the issue of information transfer speed. As a result, there was need to find new and rapid technology in application to reach good results. In this paper, we propose new transformations derived from Laguerre polynomials. The image is analyzed using new wavelets to remove the noise from the color image and to avoid the problem of large data and the difficulty of transferring this data to keep it from being lost. The image is compressed to reduce the space occupied by this huge data with the help of the MATLAB program. The obtained results show the efficiency of our proposed method. [ABSTRACT FROM AUTHOR]

Recommender system (RS) aims to predict user preferences based on automatic data acquisition, and those collected data assist in achieving the final decision. However, RS suffers from data sparsity issues over the newly launched system, and the lack of time to deal with the massive data is also a challenging factor. To acquire proper outcomes, cross-domain RS intends to transfer knowledge from the specific domain with quality enriched data to help recommendations to the target domains. The entities may or may not be overlapped, and it is common for the entities of two domains to be overlapped. These overlapping entities may show variations in their target domain, and avoiding these issues leads to distorted prediction outcomes over the cross-domain RS. To address these issues, this research concentrates on modeling and efficient cross-domain RS using the generative and discriminative adversarial network (CRS-GDAN) model for kernel-based transfer modeling. Domain specific is considered to handle the feature space of overlapped entities, and transfer computation is adopted to handle the overlapping and non-overlapping entity correlation among the domains. Based on the anticipated concept, knowledge transfer is achieved rigorously even in the case of overlapping entities, thus diminishing the data sparsity issues. The experimentation is performed using an available online dataset, and the model attains a 20% better outcome than other approaches. The outcomes specify that the knowledge transfer from source to destination target is advantageous even in overlapping issues. [ABSTRACT FROM AUTHOR]

SINCE MEDIEVAL TIMES, the impact of sugar production and consumption on European social, cultural, and economic development has been huge. The introduction of sugar cultivation entailed knowledge transfer and new technological requirements, such as the manufacture of sugar pots used to crystallise sugar, which is often the only archaeological evidence of its production and consumption. Sicily was one of the major sugar producers in medieval and post-medieval times, and many studies based on written sources are devoted to this phenomenon. However, the archaeological evidence seems comparatively scarce. This paper reviews the contexts and materials already known in Sicily, as well as research conducted under the EU-funded Marie Skłodowska-Curie SPotEU project. A typological classification based on sugar-pot shape and size is proposed here. This study allows the reconsideration of the archaeological evidence on the island and discusses changes in the design of sugar pots over phases, contexts and sites. [ABSTRACT FROM AUTHOR]

To explore the dual regulatory role of government subsidies in the aspect of industrial generic technology innovation, and given the factor of knowledge-ecological debugging, the subsidy pattern of industrial generic technology innovation is designed. Then, a modality model of knowledge niche based on Cobb-Douglas function and a knowledge-ecological debugging model based on an improved Lotka-Volterra model were constructed. Combining with qualitative and numerical examples, this paper analyzes the dual regulation mechanism of government about knowledge input and ecological interaction under decentralized and centralized decision-making. Fundings: through the knowledge ecological chain with multi-subject participation, the government subsidies are used to regulate the knowledge input of various organizations in the midst of industrial generic technological innovation and promote the interaction of knowledge ecology, and adjust the ecological positions of different knowledge, and boost the bidirectional flow, transfer and transformation of knowledge between different disciplines, and realize endogenous development. These are conducive to improving the efficiency of knowledge resource allocation in the technology innovation chain. It is expected to improve the effectiveness of industrial generic technology innovation. [ABSTRACT FROM AUTHOR]

Offsite construction, also known as industrialized/prefabricated construction, is an alternative approach to delivering construction projects, compared to the on-site stick-built/built-on-site construction approach. Today's offsite construction processes often use technology systems (e.g., digital design tools and automated machinery) to increase productivity and improve product quality. These systems operate collectively and rely on information generated in different operating environments. Therefore, information interoperability is critical to achieving overall construction efficiency and economics. This creates a need to study the impacts of information loss and transfer due to information interoperability, specifically for offsite construction processes. Given this, the paper uses a qualitative (case study) approach to document the offsite construction processes and the information requirements for each process. The efforts spent on information generation and transfer are taken as inputs for calculating the information loss and transfer impact using a quantitative (Monte Carlo simulation) approach. It contributes to the body of knowledge with (1) documentation of the current offsite construction processes based on wood panelized construction and the information requirements for all involved technology systems; (2) a case study approach that can be generically applied in other offsite construction companies to capture the information efficiency due to information interoperability; and (3) a generic simulation-based approach to measure the impacts of information loss and transfer between processes. As a result, the paper proposes phases of technology adoption and strategies for offsite construction companies. This research proposes some practical implications specifically for the offsite construction industry that intends to adopt new technology systems and/or evaluate the efficiency of information handling in their existing practice, through a case study. For example, offsite construction firms can develop their own evaluation metrics to assess the information loss and transfer before investing in new technology systems, by following a similar approach to this case study. This may include comparing different technology systems from the perspective of return on investment. The approach can also be used to evaluate existing technology systems and set a baseline/benchmark. This will help management to understand the potential losses in effort due to poor information interoperability and set targets for enhancing these systems. Lastly, the proposed phases of technology adoption and strategies can help the offsite construction industry to set targets for progressive technology transformation and serve as a reference for setting expectations from a business perspective. It also helps the company to identify the required talents and know-how in the technology transformation process. [ABSTRACT FROM AUTHOR]

Automatic modulation classification (AMC) based on deep learning (DL) is gaining increasing attention in dynamic spectrum access for 5G/6G wireless communications. However, inconsistent feature parameters between the training (source) and testing (target) data lead to performance degradation or even failure of existing DL-based AMC. The primary reason for this is the difficulty in obtaining sufficient labeled training data in the target domain. Therefore, we propose a novel cross-domain AMC algorithm based on multimodal information and transfer learning, utilizing abundant unlabeled target domain data. We achieve complementary gains by fusing multimodal information such as amplitude, phase, and spectrum, which are used to train a network. Additionally, we apply domain adversarial neural network technology from transfer learning to learn from a large number of unlabeled data samples in the target domain to address the issue of decreased accuracy in cross-domain AMC caused by differences in sampling rate, signal-to-noise ratio, and channel variations. Furthermore, we introduce class weight weighting and entropy weighting to solve the partial domain adaptation problem, considering that the target domain has fewer modulation signal classes than the source domain. Experimental results on two designed modulation datasets demonstrate improved performance gains, thus validating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Retinopathy, a prevalent disease causing visual impairment and sometimes blindness, affects many individuals in the population. Early detection and treatment of the disease can be facilitated by monitoring the retina using fundus imaging. Nonetheless, the limited availability of fundus images and the imbalanced datasets warrant the development of more precise and efficient algorithms to enhance diagnostic performance. This study presents a novel online knowledge distillation framework, called CLRD, which employs a collaborative learning approach for detecting retinopathy. By combining student models with varying scales and architectures, the CLRD framework extracts crucial pathological information from fundus images. The transfer of knowledge is accomplished by developing distortion information particular to fundus images, thereby enhancing model invariance. Our selection of student models includes the Transformer-based BEiT and the CNN-based ConvNeXt, which achieve accuracies of 98.77% and 96.88%, respectively. Furthermore, the proposed method has 5.69–23.13%, 5.37–23.73%, 5.74–23.17%, 11.24–45.21%, and 5.87–24.96% higher accuracy, precision, recall, specificity, and F1 score, respectively, compared to the advanced visual model. The results of our study indicate that the CLRD framework can effectively minimize generalization errors without compromising independent predictions made by student models, offering novel directions for further investigations into detecting retinopathy. [ABSTRACT FROM AUTHOR]

Purpose: The application of knowledge generated in universities is crucial for its dissemination outside of academic environments, particularly in industrial settings. Lack of familiarity with these channels and their features can lead to failure in achieving the ultimate goal of this communication. Therefore, the purpose of this research is to investigate the channels of knowledge flow between universities and industries. Method: This study employs a scientometric approach, utilizing co-word analysis and narrative review techniques. Using the narrative review approach, we conducted searches in the most important international databases, which served as the theoretical framework for this study. In the second stage of this research, a scientometric approach was employed to uncover the connections, key words, and the scientific map formed by the relationships between words. The co-word technique was utilized for this purpose. In this way, the query "(university AND industry AND (channel OR transfer OR spillovers OR flow OR dissemination))" was searched in the Topic field of the Web of Science database, which is known as one of the most reliable citation databases. The time span was from 1975 to November 27, 2022, and the search was performed in the Web of Science Core Collection, including the Science Citation Index Expanded (SCI-EXPANDED) from 1980 to the present, the Social Sciences Citation Index (SSCI) from 1980 to the present, the Arts & Humanities Citation Index (AHCI) from 1975 to the present, the Conference Proceedings Citation Index - Science (CPCI-S) from 1990 to the present, the Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH) from 1990 to the present, the Book Citation Index - Science (BKCI-S) from 2005 to the present, the Book Citation Index - Social Sciences & Humanities (BKCI-SSH) from 2005 to the present, and the Emerging Sources Citation Index (ESCI) from 2005 to the present. A total of 5178 documents were retrieved using this search strategy. To create a co-word map, the VOSviewer software was utilized. In order to generate an analyzable map, a threshold of at least 50 occurrences was applied, resulting in 86 words being entered for the analysis and creation of a co-occurrence map. Findings: Examining the flow of knowledge channels between universities and industries revealed that these channels may be formal, informal, or a combination of both. Also, the exchange of knowledge between the industry and the university can be intentional or incidental. This knowledge can be explicit or tacit. On the other hand, in channels for transferring knowledge, considerations such as commercialization, cost-benefit analysis, and financial return have also been taken into account. Furthermore, these channels and the transfer of knowledge between universities and industries are considered a form of social capital. Examining the relationship between industry and university from a scientometric perspective, and based on the co-occurrence map of words, it is evident that topics such as the performance and impact of cooperation, knowledge transfer, triple helix, industry, technology transfer, knowledge, entrepreneurship, and research and development are the most important concepts extracted. The scientific map and the formed clusters illustrate the significance of knowledge flow channels between industry and university researchers, highlighting the importance of cooperation in knowledge transfer. In total, four topic clusters have been identified in the co-word map. Conclusion: The channels between universities and industry have been the focus of various research studies, and the formation of thematic clusters further underscores this significance. The diversity among the channels indicates that a thorough analysis of the knowledge flow between the university and the industry requires the use of multiple indicators. [ABSTRACT FROM AUTHOR]

Free access to scientific data, knowledge and technology transfer has become more and more important in science, at universities, governmental institutes, and in our society in general. In an interdisciplinary project initialised by palynologists at the University of Vienna and the Austrian Agency for Health and Food Safety Ltd (AGES), the world's most comprehensive database PalDat has been expanded by more than 2000 datasets from the PONET database, comprising high resolution light microscopy (LM) micrographs of hydrated pollen. The main aim of this fusion of knowledge was to share digital data in a secure way and to ensure users of various disciplines free access to reliable pollen data. The project was finally completed in 2021. In the course of the expansion, additional data entry fields regarding LM description have been added, and new features, such as a search function for orders and families, have been implemented in the new version 3.4 of PalDat. A global online submission and publication tool for palynological data to PalDat, including review and editorial process, assures easy knowledge transfer and facilitates a continually increasing number of datasets and taxa contributed from scientists all over the world. The free accessible online pollen database PalDat is maintained by members of the Division of Structural and Functional Botany (University of Vienna). [ABSTRACT FROM AUTHOR]

Aspects of 2nd‐ to 5th‐century ce Roman production technology and knowledge transfer in southern Austria (known as Noricum) were examined. With no evidence for workshops identified in the study area, 44 grey ware bowls from two sites at Aguntum and Lavant were studied macroscopically, and combined with optical microscopy, X‐ray powder diffraction, prompt gamma activation, neutron activation and scanning electron microscopy, in order to understand whether one (large) workshop supplied these bowls, or whether the bowls were produced by several (small) workshops nearby. Combined with information from the geological background, the results were used to tentatively indicate the production location. The results indicate that the grey ware bowls from Aguntum and Lavant were produced by local workshops nearby. The bowls were manufactured with similar clay sources, tempered with crushed calcite‐marble rocks from the Tauern Window, their surface smoothed and burnished, and fired between 800 and 850°C in a reducing atmosphere of an open fire. This is taken to suggest that Roman potters, who were located at Aguntum and Lavant, shared strategies of raw materials selection, paste preparation, finishing and firing, and transferred technological knowledge through time. [ABSTRACT FROM AUTHOR]

While a significant body of research has emphasized the contribution of knowledge spillover to the economic growth of a region, the distinction between knowledge types has not received the attention it deserves. Market-mediated technology transfer, compared with pure knowledge spillover, is mediated by market mechanisms that stimulate chances to identify potential partners, alleviating the spatial restraints between them. This research explores the mutual uncertainties of licensor and licensee in transferring market-mediated technology and seeks to capture the geographic incidence at prefecture-levels across China. It also tests whether the intensity of market competition imposes constraints on the licensor's decision concerning technology transfer. The results corroborate that geographical distance still serves as a heavy toll between licensor and licensee. However, spatial proximity does not always support technology diffusion in cases where the licensors are associated with the dissipation effect among the proximate partners. The results challenge the common notion in the literature that an agglomeration effect is associated with knowledge spillover, reflecting the dynamic nature of market-oriented knowledge transfer. The contribution of this work will broaden understanding of the relationship between international/local technology diffusion and regional innovative capacity. [ABSTRACT FROM AUTHOR]

Within the university-industry ecosystem, improvement and innovation of technology transfer involve implementing appropriate dynamic capabilities. To answer the question—What are the micro-foundations of dynamic capabilities in university technology transfer?—this study investigates in-depth organizational-level dynamic capabilities in transferring university-based knowledge to business and society. Two qualitative case studies were deployed at organizational entities at Vrije Universiteit Amsterdam: the Industry Alliance Office, and the Demonstrator Lab. These two organizations stimulate science- and business-oriented university technology transfer. In this context, the micro-foundations of the dynamic capabilities "sensing", "seizing" and "reconfiguring" are identified and discussed. For "sensing", which is the university's ability to explore the opportunities in the ecosystem, the micro-foundations are "selecting internal competency" and "sensing external partners". For "seizing", which supports universities in managing complementarity with industry and society, micro-foundations include "resource co-allocation" and "collaborative business model". The micro-foundations of "reconfiguring", through which universities maintain evolutionary fitness in the innovation ecosystem, are "strategic renewal", "establishing a university technology transfer-friendly environment", and "asset orchestration". This study provides researchers with a better understanding of how dynamic capabilities facilitate university technology transfer. Industrial practitioners and policymakers can consider the suggestions of the present study when pursuing collaboration with universities. [ABSTRACT FROM AUTHOR]

Technology transfer is a conscious knowledge transfer and diffusion, which can promote the coordinated configuration and balanced development of technological innovation elements in geographical space. From the perspective of "space of flow", the technology transfer network is constructed. Utilizing patent technology transaction data from 2018, this study analyzes the agglomeration differentiation and spatial polarization patterns of technology transfer from network nodes, network layers, and network partition in Guangdong–Hong Kong–Macao Greater Bay Area. The conclusions are as follows: (1) The agglomeration of technology transfer is remarkable in the network, showing "two poles and two strong" as well as proximity advantages; Shenzhen and Guangzhou have become spatial poles within the network. (2) The Matthew effect is prominent and technology transfer at the spatial level is largely caused by core node interactions, while core‐edge hierarchical transmission mechanisms and geographical proximity contact characteristics are gradually developing. (3) Differences in roles between the plates are pronounced, and there is an agglomeration effect within a plate and between plates, as well as clear spillover effects. [ABSTRACT FROM AUTHOR]

Under the influence of the COVID-19 pandemic, there is an accelerated transition from the traditional form of knowledge transfer to online learning. Our study of 344 automotive students showed that the success of this transition depends on the readiness to introduce special digital tools for organizing knowledge and conducting practical forms of classes. In this regard, a modern digital form of organizing and transferring knowledge to automotive service engineers in the form of virtual laboratories was developed and presented in the article. The work scenarios, functionality, and minimum technical requirements of virtual laboratories as software systems are described and reviewed in the paper. The rationale for the effectiveness of the application, based on the results of using 109 university students in training practice, is presented as a result of the research. An analysis of the distributions of the student survey results and their training progress revealed differences at the p = 0.05 significance level. This confirmed the hypothesis that the use of methods for teaching engineers special disciplines and language skills using VR technologies is much more effective than the traditional one. An increase in students' interest in learning was revealed, and their performance improved markedly. This proves that the immersive nature of VR technology makes it possible to better assimilate the studied material, increase the level of motivation of future car service specialists, and also allow the organization of the transfer of knowledge online. The very process of knowledge transfer becomes the point of acquiring new digital competencies necessary for high-tech industries. [ABSTRACT FROM AUTHOR]

Background: The age of information has given rise to the demand for higher education institutions (HEIs) to produce graduates capable of producing innovation and ultimately contribute to improving the South African (SA) economy. Objectives: The objective of this study is to determine whether graduates who enter the business environment demonstrate the knowledge and capability to produce business innovation through knowledge and skills acquired in HEIs. Method: An online questionnaire, was used to collect data from 69 of the 100 participants from the South African Business Innovation Community (Innovation Summit) (SABIC) and the Innovation, Sustainability and Visionary Leadership Group (ISVL). The demography ranged from company representatives, government representatives, entrepreneurs, academics, etc. Data were collected were analysed through inferential statistical analysis with the support from Statistical Package for Social Sciences (SPSS). Results: Based on the findings, an equal distribution exists between seldom and often, which indicates tension about whether graduates seldomly demonstrated the ability to produce effective business innovation or whether they often demonstrated the ability to produce business innovation. Conclusion: Higher education institutions play a vital role in preparing graduates for the world of work by transferring knowledge. It is therefore significant for HEI's to transfer knowledge and skills that improve graduates' capability to innovate, think critically and solve complex problems and contribute to the SA economy. Contribution: Given the state of youth unemployment there is a need for universities to produce graduates capable of effective innovation. This article focused on determining whether graduates possess the knowledge and capability to produce business innovation from the knowledge and skills transferred by HEIs. [ABSTRACT FROM AUTHOR]

The populations of Afro‐Palearctic migratory landbirds (breeding in Europe and overwintering in Africa) are declining and conservation efforts to halt or reverse their decline have failed to meet their targets. Yet, most studies and conservation measures focus on migratory landbirds' breeding grounds, whereas knowledge about threats, drivers of their decline and conservation actions in their nonbreeding grounds, where they spend most of their annual cycle, is largely limited. Here, we provide a four‐step roadmap to integrate research, policy and actions for conserving Afro‐Palearctic migratory landbirds at a flyway scale: (1) assessing and monitoring population trends and defining priority species accordingly; (2) maximizing tracking data to identify important areas for the conservation of priority species; (3) conducting ground‐based studies on the nonbreeding grounds to identify conservation challenges; (4) implementing conservation measures, for the benefit of both the avifauna and the local human communities. Alongside these steps, international conventions may facilitate new collaborations across range‐states and institutions to engage diverse stakeholders and involve local communities, with particular emphasis on evidence‐based policymaking, law enforcement in addition to capacity strengthening and knowledge transfer of new technologies. This four‐step roadmap provides guidance for future work on Afro‐Palearctic migratory landbirds and will ultimately contribute to their conservation. [ABSTRACT FROM AUTHOR]

How do global value chains (GVCs) affect a firm's innovation impact? Working as international communities, GVCs are rich in knowledge and resource interchange. The prior literature has focused on knowledge absorbing or internal knowledge transfer within firms for in-house innovation. However, scant research has focused on promoting innovation across interfirm networks in a GVC context. This article develops a new concept of interfirm transformative capacity as a firm's ability to transfer developed technology knowledge across time, space, and firm networks. In this article, we explore three mechanisms of interfirm transformative capacity in GVCs: 1) choosing knowledge intermediaries, 2) transmitting and maintaining knowledge over time and space, and 3) reactivating and synthesizing knowledge. We predict that engagement in a lead firm's GVC, structural holes, and network centrality will affect a focal firm's innovation impact as a result of interfirm transformative capacity. Integrator suppliers have higher innovation impacts than modular suppliers. To test these three mechanisms, we build a novel dataset from a five-year panel of Apple suppliers and their patent impacts. The results support our hypotheses related to the mechanisms of interfirm transformative capacity. Our theoretical elaboration and empirical findings have significant implications for innovation policy within, and governance of, GVCs. [ABSTRACT FROM AUTHOR]

Silicon Fen (SF) is a cluster of high-tech firms located around the University of Cambridge (UoC) in the UK. This article, for the first time, investigates the technological bonds between SF firms and UoC based on patent analysis covering the period of 1999–2021. We provide a short history of SF, highlighting its early formation and growth, and the role of spin-off firms on its evolution. We employ joint patents generated by UoC and various business sectors of SF to calculate the values of technological collaboration strength (TCS). It is found that the majority of joint patents (61%) are generated by the Pharma/Biotech sector of SF with the highest value of TCS (16.45 × 10−3). Moreover, the patent's economic values across various business disciplines in SF are calculated based on the total counts of citations. Our observations suggest that senior university academics making spin-off firms in a business cluster around their university can effectively facilitate university–firm technological collaboration. Furthermore, the relatively strong technological bond between UoC and the Pharma/Biotech sector of SF is confirmed to be influenced by the collaboration of the university with its own spin-off firms rather than large independent firms in SF. The outcomes of this research contribute to the knowledge of the collaboration between a main research university and a cluster of firms located in its geographical proximity. [ABSTRACT FROM AUTHOR]

Convolutional Neural Network (CNN) has been proved excellent for hyperspectral image(HSI) classification on the basis of large training set. However, the lack of available samples degrades the performance of CNNs in practical HSI classification. Although transfer learning is a typical strategy to address the issue of limited training samples, such methods tend to reload source model's feature extractors directly ignoring their generalization. Furthermore, most existing adaptive transfer learning algorithms pay attention to spectral features of HSI while the obvious difference between RGB image and HSI's spatial features is overlooked. In this paper, the proposed method can solve the mentioned problems to some extent. Firstly, the proposed adaptive heterogeneous transfer (AHT) can measure their transferability and find appropriate solution to transfer knowledge. It computes feature extractors' transferability based on feature maps and influences the learning process of target model through backpropagation, therefore, target model is prone to receive knowledge from feature extractors with high generalization. Secondly, the proposed method lays emphasis on HSI's spatial features. It adopts the methodology of spatial attention and calculates the regularization loss based on spatial features. Experiments were conducted on two widely used HSI datasets. The results demonstrate the method's effectiveness when few samples are available. [ABSTRACT FROM AUTHOR]

This paper proposes an English-Chinese machine translation research method based on transfer learning. First, it expounds the theory of neural machine translation and transfer learning and related technologies. Neural machine translation is discussed, the advantages and disadvantages of various models are introduced, and the transformer neural machine translation model framework is selected. For low-resource Chinese-English parallel corpus and Tibetan-Chinese parallel corpus, 30 million Chinese-English parallel corpora, 100,000 Chinese-English low-resource parallel corpora, and 100,000 Tibetan-Chinese parallel corpora were used to pretrain the transformer machine translation architecture. The decoders are all composed of 6 identical hidden layers, the initialization of the model parameters is done by the transformer uniform distribution, and the model training uses Adam as the optimizer. In the model transfer part, the parameters with the better effect of the pretrained model are transferred to the low-resource Chinese-English and Tibetan-Chinese machine translation model training, so as to achieve the purpose of knowledge transfer. The results show that the model transfer learning of low-resource Chinese-English parallel corpus improves the translation system's translation by 3.97 BLEU values compared with the translation system without transfer learning at 0.34 BLEU values. Model transfer learning on low-resource Tibetan-Chinese parallel corpus increases the BLEU value by 2.64 BLEU compared to the translation system without transfer learning. The neural machine translation system that uses BPE technology for preprocessing plus model transfer learning is compared to the translation system that only performs transfer learning and shows an improved 0.26 BLEU value.It is verified that the transfer learning method proposed in this paper has a certain improvement in the effect of low-resource Chinese-English and Tibetan-Chinese neural machine translation models. [ABSTRACT FROM AUTHOR]

This study seeks to address the issue of the development factors influencing technological entrepreneurship capabilities of enterprises during the COVID-19 epidemic crisis. This research is particularly relevant in light of the leading role given to innovation and science-oriented technology companies in the economic and epidemiological crisis. This study aims to analyze the impact of the changing environment on the predictors of technological entrepreneurship, assess their impact by the management practice and establish a causal relationship between the used variables. The paper draws on foreign literature review, covering fundamental theoretical fields in international management literature, to develop an integrated research framework. Based on a differentiated approach, the collaborative framework emphasizes a range of network processes and attributes, their interactions and moderating managerial relationships related to their impact on companies' technological entrepreneurship capabilities and their contribution to business outcomes. The study was conducted by means of four-wave research. The factors of models included in the correlation analysis are management functions and demand for new technology. Results show that there is a weak positive relationship between management functions and manager's technological preferences. These findings show that during COVID-19, firms changed their management practices using digitalization to respond to the pandemic. Additionally, it shows that managers moved towards employing new technologies as a strategic response to the crisis. The results showed a mutual, two-way relationship between the demand for new technology and managers from the planning area, high level scientifically and managers with managerial functions, a quick diffusion of technological innovations and managers with the motivating function, a short lifecycle of products and processes and managers from the short lifecycle of products and processes. Taking into consideration that technology entrepreneurship and innovation are facets of the innovative entrepreneur sector, the need for a holistic approach is needed to support their development during the international economic crisis. The next practical implication derived from the crisis may hinder the ability of entrepreneurs to discover new opportunities for technology development. Moreover, an epidemic shock such as COVID-19 may have an impact on technology entrepreneurial opportunities. This article presents a new look at the theory of management by using the implementation role of predictors of the growth of technological entrepreneurship during the epidemic crisis. In addition, the article obviously contributes to the technology entrepreneurship literature by providing an empirical study that advances a new perspective on the process of developing new technologies in the period of crisis. [ABSTRACT FROM AUTHOR]

The filter feature selection algorithm is habitually used as an effective way to reduce the computational cost of data analysis by selecting and implementing only a subset of original features into the study. Mutual information (MI) is a popular measurement adopted to quantify the dependence among features. MI-based greedy forward methods (MIGFMs) have been widely applied to escape from computational complexity and exhaustion of high-dimensional data. However, most MIGFMs are parametric methods that necessitate proper preset parameters and stopping criteria. Improper parameters may lead to ignorance of better results. This paper proposes a novel nonparametric feature selection method based on mutual information and mixed-integer linear programming (MILP). By forming a mutual information network, we transform the feature selection problem into a maximum flow problem, which can be solved with the Gurobi solver in a reasonable time. The proposed method attempts to prevent negligence on obtaining a superior feature subset while keeping the computational cost in an affordable range. Analytical comparison of the proposed method with six feature selection methods reveals significantly better results compared to MIGFMs, considering classification accuracy. [ABSTRACT FROM AUTHOR]

The implementation of the innovative city pilot policy (ICPP) is conducive to promoting the urban industry–university–research collaborative innovation, but there is no clear answer to how industry–university–research knowledge flow is affected by the policy. Based on the knowledge flow process divided into the knowledge creation stage and knowledge transfer stage, this paper uses the two-stage Data Envelopment Analysis (DEA) model to measure the dual efficiency of urban industry–university–research knowledge creation and knowledge transfer. And the paper also adopts the spatial difference-in-difference (SDID) model to study the impact mechanism of ICPP on the knowledge flow dual efficiency. The results show that there are positive spatial spillover effect of the knowledge creation efficiency (KCE) and knowledge transfer efficiency (KTE). And the effects of ICPP on industry–university–research KCE and KTE are both manifested as the promoting impact. Furthermore, ICPP has a significantly positive impact on the urban innovation atmosphere (UIA), and UIA plays a partial mediating role in the impact mechanism of ICPP on KCE and complete mediating role in the relationship of ICPP and KTE. [ABSTRACT FROM AUTHOR]

The papers in this special section focus on the ability to integrate evolving incubator models into the organization. Management and organizational science focusing on the complex process of R&D that leads to the subsequent commercialization has come a long way since the days of post-World War II industrial and research laboratories. In this context, the evolution of the incubator can be retraced from the foundational research in the 1950s and 1960s of Researchon-Research—that explored the R&D process in a number of settings to derive and test theories of organization behavior. Since then, we have seen a concentration of research and practice that have spanned a burgeoning range of incubators models and entities that, in some manner, exist to play a role to support and harness new technology-based start-ups. For more than half a century, these third-party entities in the entrepreneurial ecosystem have spread from the United States to Europe and are a well-established worldwide phenomenon. Business incubators have been largely viewed as an essential means to facilitating the process of knowledge transfer and tech-based commercialization through the provision of office infrastructure, laboratories and equipment, business support services, mentoring, and access to entrepreneurial finance and specialist networks for the founders of these embryonic start-ups. [ABSTRACT FROM AUTHOR]

• A digital twin-assisted dual transfer method was proposed with information and model adaptation for bearing fault diagnosis. • DTa-DT aims to simultaneously synthesize information transfer and model transfer for domain transfer error minimization. • DTd-IT method was proposed to information transfer with low distribution difference of twin data adapted. • DAd-MT method, composed of DBTN, was proposed to model transfer with feature distribution difference of domain-model adapted. • Experiments and ablation study verified that the proposed DTa-DT method can be well applied to small sample learning. Rolling bearing fault diagnosis is of great importance to the safety management of mechanical equipment. The scarcity of labelled fault data makes it difficult to adequately perform the training process of intelligent diagnosis models, and this will result in these intelligent models not being effectively and widely used in practice. Although some recent studies have verified that the addition of dynamic model response to the training process will greatly improve the ability of the model with low cost and high efficiency, it is still stuck in poor effect caused by large information distribution difference between dynamic model response and real measured data. Focusing on this issue, a digital twin-assisted dual transfer (DTa-DT) method with information and model adaptation was proposed for rolling bearing fault diagnosis. Different from the traditional digital-analogue driven transfer methods, the proposed DTa-DT aims to simultaneously synthesize data information transfer and feature model transfer together with domain transfer error minimization. In particular, it should be noted that the DTa-DT architecture consists of a dual transfer learning process, including digital twin-driven information transfer (DTd-IT) and digital-analogue-driven model transfer (DAd-MT), where the information is collaborated with the model to improve the integrated transfer diagnosis effect under sampling. On one aspect, with the employment of bearing dynamic model responses, DTd-IT is innovatively designed to establish the transfer of dynamic information and measured information. The information distribution difference between these twin data and real measured data is effetely adjusted with the introduced actual inference components, where the twin data with low information distribution difference can be well fusion generated by the information transfer digital twin (ITDT) model. On the other aspect, considering the truth that there are still small sample cases of real measured data and information distribution differences will affect the quality of the twin data, a digital-analogue driven model transfer (DAd-MT) method is further proposed, where the deep branch transfer network (DBTN) model with improved convolutional neural network (CNN) is used to achieve an accurate fault diagnosis effect with the help of digital twin data. Experiments and wear analysis verified that the proposed DTa-DT can significantly reduce the distribution difference between the dynamic model response and the real measured data, thus achieving low-cost and efficient rolling bearing transfer diagnosis compared to other ten state-of-the-art deep learning models. It can be predicted that the proposed dual transfer architecture provides more opportunities for the practical application of intelligent fault diagnosis under small sample sizes. [ABSTRACT FROM AUTHOR]

• Materials and the production process are flexible in adhesive technology. • Technological knowledge transfer is flexible across genders and ages. • Technological flexibility minimizes the risk of production problems. • Single compound archaeological adhesives are likely exceptions, not typical cases. This study explores traditional adhesives using an ethnobiological approach within a multisocioecological context in Zambia. Through semi-structured interviews, videotaped demonstrations, and herbarium collections, we investigated the traditional adhesives people know and use, the flexibility of production processes, resource usage, and knowledge transmission in adhesive production. Our findings reveal flexibility in adhesive production systems. People use a wide range of organic and inorganic materials in their adhesive recipes. Recipes are flexible, demonstrating the ability to adapt to changes and substitute materials as needed to achieve the desired end product. Additionally, our study reveals a variety of redundant pathways for knowledge transmission typically confined within individual population groups. These include same-sex vertical transmission and distinct learning spaces and processes. Also, we identified material procurement zones showing that people are prepared to travel 70 km for ingredients. We use our findings to review the archaeology and we discuss the identification of archaeological adhesives, the functional roles of adhesive materials, adhesive storage, and the sustained human interaction with species from families such as Euphorbiaceae and Apiade. Our findings underscore the diversity and adaptability of traditional adhesive production and suggest that further research on adhesives would reveal similar diversity within the archaeological record. [ABSTRACT FROM AUTHOR]

The interest of this article is the presentation of the findings of the relationship found between knowledge transfer and information and communication technologies, of the SMEs of the tourism sector of the Department of Caldas. The study is based on the application of a knowledge management valuation model to 61 operating companies of the tourism sector in the Department of Caldas. Based on a qualitative research, with a descriptive approach (use of surveys), exploratory (use of observation and documentary review) and correlational (multivariate analysis). Regarding the use of ICT, it is a palpable fact, the progress of SMEs in the tourism sector of the Department of Caldas in the use of this resource as a basis for the sale of services, products and the transfer of knowledge inside and outside the companies, which can be seen in the different portals and mobile applications that these companies have. It is concluded that there is a positive and significant correlation between knowledge transfer and information and communication technologies. It is hoped that these results will lead to strategies that allow the improvement of these companies. [ABSTRACT FROM AUTHOR]

Objective of the study: This study aimed to investigate how collaboration between actors in the innovation ecosystem is related to the transfer of knowledge between institutions. Methodology/Approach: The study units were the innovation hubs of the Federal Institutes of Education, Science and Technology in Brazil accredited by Embrapii. The methodological approach of the research was qualitative; the method employed was the multiple-case study; the data collection was conducted through semistructured interviews with representatives from academia, company, government, and society; and the results were obtained via content analysis. Originality/Relevance: Based on the findings of this research, it was possible to elaborate an analytical model to relate the level of collaboration and transfer of knowledge between agents of the innovation ecosystem. Main Results: The main results indicated that the collaboration between the actors was related to the transfer of knowledge through the creation and expansion of the established partnerships as well as the management of the facilitators and difficulty of this relationship. Theoretical/Methodological Contributions: The theoretical contribution was the proposition of an integrated analytical model of collaborative relations and knowledge transfer between members of the innovation ecosystem. Management/Social Contributions: The managerial contribution of the study was the identification of key aspects to improve the collaborative relationship between the actors of the innovation and knowledge transfer ecosystem. The social contribution consists of the possibility of collaboration expansion and knowledge transfer by enhancing the facilitating factors and minimizing the difficulties identified in the researched innovation ecosystems. [ABSTRACT FROM AUTHOR]

In this study, we investigated the effects of foreign direct investment (FDI) spillovers on firm production and technical efficiency in Indonesia's manufacturing sector from 2010 to 2015. We scrutinized three different channels of horizontal spillover, namely, demonstration, technology adoption, and competition channels. We also captured the heterogeneous effect of firms by categorizing them based on their technological intensity (low, medium, or high). Using time-varying stochastic production frontier analysis, we found that manufacturing firms in each technological group benefit from FDI, either from productivity improvement or technical efficiency improvement. High-technology firms mainly benefit from FDI due to their high technological absorption capability. Meanwhile, medium-high and medium-low tech firms increase productivity through the demonstration effect and the technology adoption channel, despite underperforming in technical efficiency. Finally, low-tech firms, which primarily employ unskilled workers, suffer from large inefficiency. We found that increased FDI, combined with improvements in technology absorption capacity, can help revitalize the productivity of low-tech firms. FDI, firm size, and access to foreign inputs all support production effects but have no direct positive impact on firms' technical efficiency. The results of this study suggest that the government should ensure that domestic firms can absorb the technical capability of a foreign presence. Open innovation can help strengthen foreign–domestic linkages to contribute to growth through the transfer of knowledge, skills, and technologies. [ABSTRACT FROM AUTHOR]

Knowledge has become the most important factor of production with the emergence of the knowledge economy. We use the system GMM estimation method to analyze how cross-national knowledge transfer (CNKT) impacts the total factor productivity (TFP) of China's 31 provinces and evolution of China's ability to absorb foreign knowledge. We also examine the possible intermediary effects of foreign direct investment (FDI), outward FDI, import trade, export trade, and direct technology spillovers between CNKT and TFP. We find that: (1) CNKT improves China's TFP and positively impacts FDI, import trade, export trade, and direct technology spillover; It shows that CNKT not only helps to improve China's TFP, but also provides innovative knowledge reserve for the absorption of international technology spillovers. (2) The improvement in the domestic infrastructure construction level, R&D capacity, human capital, economic development and openness has obvious absorption effect on CNKT, which is conducive to the absorption and utilisation of international advanced knowledge. (3) FDI, import trade, and direct technology spillover play a partial mediating role between CNKT and TFP, and the intermediary effect of import trade technology spillover is the strongest. [ABSTRACT FROM AUTHOR]

To solve the difficulty associated with radar signal classification in the case of few-shot signals, we propose an adaptive focus loss algorithm based on transfer learning. Firstly, we trained a one-dimensional convolutional neural network (CNN) with radar signals of three intra-pulse modulation types in the source domain, which were effortlessly obtained and had sufficient samples. Then, we transferred the knowledge obtained by the convolutional layer to nine types of few-shot complex intra-pulse modulation classification tasks in the target domain. We propose an adaptive focal loss function based on the focal loss function, which can estimate the parameters based on the ratio of hard samples to easy samples in the data set. Compared with other existing algorithms, our proposed algorithm makes good use of transfer learning to transfer the acquired prior knowledge to new domains, allowing the CNN model to converge quickly and achieve good recognition performance in case of insufficient samples. The improvement based on the focal loss function allows the model to focus on the hard samples while estimating the focusing parameter adaptively instead of tediously repeating experiments. The experimental results show that the proposed algorithm had the best recognition rate at different sample sizes with an average recognition rate improvement of 4.8%, and the average recognition rate was better than 90% for different signal-to-noise ratios (SNRs). In addition, upon comparing the training processes of different models, the proposed method could converge with the least number of generations and the shortest time under the same experimental conditions. [ABSTRACT FROM AUTHOR]

Since medieval times, sugar production and consumption has had a huge impact on European social, cultural, and economic development. The introduction of sugar cultivation entailed knowledge transfer and new technological requirements, such as the manufacture of sugar pots used to crystallise sugar, which requires a specific design, and thermal and mechanical properties. This paper presents part of the results of the SPotEU project, funded under the Marie Skłodowska-Curie Actions, which explores the development and impact of sugar production in western Europe through the study of sugar pot manufacture from an interdisciplinary perspective, integrating archaeological and historical research with material science and material culture approaches. This paper focuses on sugar pots from Sicily, one of the main regions for sugar production in Western Europe in the 11–16th centuries A.D. Sugar pots were assessed from technological and performance points of view, aided by instrumental analysis (petrography, SEM, XRF, XRD, mechanical, and thermal property tests). The archaeological and analytical results are presented, revealing different centres of sugar pot production on the island, and specific choices in the design of the vessels and their properties. This allows us to discuss how craftspeople locally adapted their ceramic-making traditions to face the new product demands from the sugar production industry in the Mediterranean. [ABSTRACT FROM AUTHOR]

The term ʺknowledge transferʺ is currently often used and is not limited to the commercial sphere. We undrestand technology transfer as the transfer of research and development results into practice. From a narrower point of view, technology transfer can be understood as the successful use of technologies developed by one entity to meet the needs of other entities. The process of technology transfer is quite complex and therefore i tis necessary to take severeal steps in order to successfully commercialize the technology. Success, but also failure, thus also depends on the correct and effective application of intellectual property, which is a key aspect of technology and knowledge transfer. Intellectual property law provides adequate protection for the unique results ofcrative intellectual activity and results with commercial potential. [ABSTRACT FROM AUTHOR]

The main aim of the article is to fill the gap concerning the recognition of constructs of programme management supporting open innovations. Current knowledge on this subject is mainly limited to identifying success factors of open innovation and programme management. In the current literature, there are few publications indicating the use of the programme as a tool supporting innovation. In order to fill the identified knowledge gap, common factors of programme success and open innovations were compared and assessed successively. A quantitative study was conducted on an international group of experts, including 578 experts in programme management. As a result of applying cluster analysis and operationalising the obtained results, four programme constructs supporting open innovations were dimensioned, such as cooperation with the environment, transfer of knowledge and technology, organisational maturity, and ensuring and maintaining implementation capacity. Moreover, the discussion and the research revealed that the impact and scope of the structured approach to programme management not only allow for the implementation of the assumed outcomes and benefits at the strategic level, but also influence the shaping and adjustment of the whole organisation. [ABSTRACT FROM AUTHOR]

Desorptive capacity is the organisational ability to transfer internal knowledge to external actors to obtain competitive advantage. We distinguish two forms of desorptive capacity to investigate how organisations active in emerging technology domains explore and exploit opportunities to match internally developed technology to external needs. We also focus on management innovation – the ability to create or revise organisational structures or processes – as a potential antecedent of desorptive capacity. From a study of 84 synthetic biology organisations we found that explorative and exploitative desorptive capacity mediate the relationship between management innovation and external technology commercialisation. The study provides empirical evidence of the existence and interdependence of different managerial and organisational processes required for external technology commercialisation. We underscore how organisations can valorise technological assets strategically through management innovation and by achieving a fit between internal practices and the technological base of potential technology adopters. [ABSTRACT FROM AUTHOR]

This study explores the underlying research topics regarding CRISPR based on the LDA model and figures out trends in knowledge transfer from science to technology in this area over the latest 10 years. We collected publications on CRISPR between 2011 and 2020 from the Web of Science, and traced all the patents citing them from lens.org. 15,904 articles and 18,985 patents in total are downloaded and analyzed. The LDA model was applied to identify underlying research topics in related research. In addition, some indicators were introduced to measure the knowledge transfer from research topics of scientific publications to IPC-4 classes of patents. The emerging research topics on CRISPR were identified and their evolution over time displayed. Furthermore, a big picture of knowledge transition from research topics to technological classes of patents was presented. We found that for all topics on CRISPR, the average first transition year, the ratio of articles cited by patents, the NPR transition rate are respectively 1.08, 15.57%, and 1.19, extremely shorter and more intensive than those of general fields. Moreover, the transition patterns are different among research topics. Our research is limited to publications retrieved from the Web of Science and their citing patents indexed in lens.org. A limitation inherent with LDA analysis is in the manual interpretation and labeling of "topics". Our study provides good references for policy-makers on allocating scientific resources and regulating financial budgets to face challenges related to the transformative technology of CRISPR. The LDA model here is applied to topic identification in the area of transformative researches for the first time, as exemplified on CRISPR. Additionally, the dataset of all citing patents in this area helps to provide a full picture to detect the knowledge transition between S&T. [ABSTRACT FROM AUTHOR]

Manufacturing services collaboration (MSC) is crucial to the industrial internet platform in determining the proper integration of multiple functionality unique services for a complex manufacturing process. As a critical enabler for resolving MSC, evolutionary algorithm (EA) plays an essential role in enhancing the efficiency of MSC optimization. However, EA solvers are generally executed from scratch and suffer from a high computational burden. Inspired by transfer learning, researchers have considered performing knowledge extraction across distinct problem instances to promote the problem-solving efficiency, giving rise to the evolutionary multi-task optimization (EMTO) paradigm. The appearance of EMTO brings an emerging knowledge-aware search paradigm that supports the online learning and exploitation of optimization experiences during the course of evolution process, thereby accelerating the search efficiency. In spite of competence in continuous problems, EMTO has received little visibility in the field of combinatorial optimization, particularly, MSC problem, let alone an experimental comparison of state-of-the-art EMTO approaches in the context of MSC. To fill in this void, this article explores the suitability of versatile EMTO solvers for addressing MSC and provides insights into the behavior of various knowledge transfer techniques in multi-task MSC environments. To our knowledge, this study is the first attempt that investigates the scalability of EMTO on MSC problems and the systematic evaluation of their performances. Our results unveil the intrinsic characteristics of distinct transfer techniques to MSC in different scenarios, along with a deep analysis of the abilities for EMTO alternatives on resolving MSC. [ABSTRACT FROM AUTHOR]

• Donor funding schemes in water supply mainly focus on constructing centralized water systems. • Donor funding schemes usually entail technology transfer without enhancing local experts' capacity for for maintenance & repair i. • Strong reliance on imported spare parts, experts' knowledge, and engineering services for maintenance & repair. • Reliance on imported technologies enhance export markets for donor countries' technological products. In many African countries, international donor funding schemes contribute significantly to financing water infrastructures, especially for constructing new networks and water plants and upgrading existing ones. However, little is known about how these financial arrangements shape infrastructure maintenance and repair. This article explores the politics of tied water aid to show how international donors' technology transfer schemes and their associated funding conditionalities shape water infrastructure maintenance and repair. Empirically, this study builds on a qualitative study of the cities of Accra (Ghana) and Dar es Salaam (Tanzania), where the maintenance and repair of water infrastructures have been a persistent challenge. The article shows that the compulsory adoption of foreign technologies embedded in donors' funding schemes limits local capacity to properly maintain and repair water infrastructure. As maintenance and repair increasingly depend on imported expert knowledge, spare parts, and engineering services, donors' funding schemes undermine effective maintenance and repair in both cities. We argue that to make transferred water technologies work sustainably in recipient countries, funding schemes need to anticipate maintenance and repair by incorporating local capacity building and knowledge transfer to reduce import dependence. [ABSTRACT FROM AUTHOR]

Public higher education institutions (universities) in developing countries are making great strides regarding action geared to the valorization of research results oriented toward transferring knowledge and technologies to society and the market. Such valorization implies huge challenges for research staff in these institutions as well as for the body of directors and the whole administrative team. The current research arose from the lack of specialized knowledge on the topic of this particular area of valorization in developing countries such as Colombia. The article delves into the experience of the University of Cauca, located in the southwest Colombian city of Popayan, concerning the valorization of research results aimed at transferring knowledge and technologies from research groups to the business sector and to public organizations. As of 2018, in its research system the university boasted 160 registered research groups. Selected for the study were those with the highest scientific readiness level, featuring important research results from the execution of science, technology and innovation projects backed by external financing and within the last 10 years. Characterization of the research results was carried out based on international references (such as the Technology Readiness Level, TRL) and on the particularities reported in the various results generated by the research groups selected. The case study concludes in putting forward a route for the valorization and transfer of knowledge and technologies associated with results from higher education institution research within the contexts of developing countries and regions with a low-to-non-existent business presence. [ABSTRACT FROM AUTHOR]

In light of the diversified relationship between universities and TLOs, this presentation will introduce the ideal form of Shinshu TLO, which collaborates with regional universities, and its efforts to collaborate with other organizations as an external wide-area TLO and to develop professional human resources. [ABSTRACT FROM AUTHOR]

Farmers demand more precision farming technology and specific information is consumed in the adoption process, which could not only depend on how efficiently the information flows among farmers. It is assumed that the sources of information are inputs in the production processes and could have an impact on the decision to adopt precision farming technology, after controlling for farmer and farm business characteristics. Accordingly, the objective of this research was to evaluate the effects of nine information sources used by cotton farmers of 12 U.S. producer states on the adoption of yield monitor with GPS, grid soil sampling, zone soil sampling, aerial photos, and soil survey maps. The scientific utility of this research lies on the quantitative data from the Southern Cotton Precision Farming Survey analysed using statistical methods such as univariate, bivariate and multivariate probit regressions. The statistical results indicated that information from dealers, consultants, university publications, and university events were the most common information sources used when searching for precision farming information with positive and significant effects on the adoption of precision farming technology. The presented findings from this comprehensive analysis can assist organizations in selecting information sources, and on planning communications and partnerships strategies fostering technology transfer. [ABSTRACT FROM AUTHOR]