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This paper aims to explore the key anchors of the National Innovation System shaping the nature of collaboration between academic high-performance computing centres (academic HPC centres) and small- to medium-sized enterprises (SMEs) working in the automotive and electronics sectors of the Danube region. With two main research questions, it discusses the importance of knowledge transfer and technology transfer for collaboration between University and Industry (U-I collaboration) in three groups of developmentally distinct countries: competitively advanced, competitively intermediate and competitively lagging. As main anchors of the innovation system, stable legal environment, exciting innovation policies and strong R&D funding are recognised.

A qualitative empirical study in 14 Danube region countries included 92 focus group participants, expert representatives of academic HPC centres and SMEs. The data were audio recorded, transcribed and analysed.

The findings show the main prerequisites of the framework conditions for efficient U-I collaboration evolve through a goal-oriented National Innovation Policy and developed and functioning legal environment supporting labour market and intellectual property (IP) protection and enforcement. Additionally, skilled people are needed to be able to operate with HPC, where it seems all the countries lack such skilled workforce. In competitively lagging countries, the high levels of brain drain exhibit strong impact to U-I collaboration.

Research into relationships between academic HPC centres and SMEs conducted was qualitative; therefore, limitations in terms of generalisation arise from it. On the other hand, the research is promising in terms of offering the guidance for policy makers who can use the findings when delivering innovation policy mix, adjusted to developmental level of own innovation ecosystem.

The study is among the pioneering work in U-I collaboration between academic HPC centres and SMEs from automotive and electronics industries in the Danube region. The research addresses the dynamics of collaboration and offers policy implications to strengthen the particular U-I collaboration.

本文旨在探究國家創新系統的主要支柱; 這些支柱決定了學術性的高速網路與計算中心 (註: 此為直譯) (以下簡稱學術高網算中心) 與於多瑙河地區的汽車製造業和電子產品行業內營運的中小型企業之間的合作性質。本文透過兩條主要的研究問題、去探討知識轉移和技術轉讓對大學與產業界之間的合作的重要性而這些產業是屬於在發展階段上三個明顯不同的國家組別裏的這三個組別是 競爭先進的、競爭性中級的和競爭落後的。穩定的法律環境、令人興奮的創新政策和強大的研究與開發資金被認為是創新系統的三個主要支柱。

研究人員在14個位於多瑙河地區的國家裏進行一個質性觀察研究研究涵蓋92個焦點小組參與者、來自學術高網算中心和中小型企業的專家代表。有關的數據被錄音繼而被轉寫下來最後被分析。

研究結果顯示效率高的大學產業界合作的框架條件的主要先決條件是透過一個以目標為導向的國家創新政策而逐漸形成繼而發展起來; 另外所需的條件是一個支援勞工市場、保障知識產權、並執行有關的法律的正常運作的法律環境。其次若想與學術高網算中心一起工作技術人才是必須的因學術高網算中心內的所有國家似乎欠缺技術勞動力。在落後於競爭對手的國家裏高度的人才外流對大學與產業界之間的合作會產生重大的影響。

由於研究採用的研究方法為質性研究法故研究結果、就普遍化的歸納而言是有其局限的。唯研究結果在實務方面有其作用因政策制定者在推行與科技進步與對策有關的策略時他們可把研究結果作為指引就其自身創新生態系統的發展水準而作出適當的調整。

本研究探討涉及學術高網算中心與於多瑙河地區的汽車製造業和電子產品行業內營運的中小型企業之間合作的大學產業界合作就此而言可說是開創性研究之一。本研究探究有關的大學產業界合作的變革動力並為政策制定者提供啟示以能強化有關的合作。

This paper aims to propose a framework that combines the triple helix model with competitive strategies concepts to capture and guide any innovation-led national development strategies.

This paper adopted a methodological framework based on existing methods and guidelines, the most commonly reported approach for developing a methodological framework. The review of fundamental approaches to achieving fast and sustained economic development, triple helix model and competitive strategies helped develop the methodological framework. The framework was validated and tested using the case studies approach on Korea, Taiwan and Singapore.

Kuwait aims to create an innovative environment to benefit from the innovation strategies anchored by the East Asian miracle economies and how they used the triple helix actors at different developmental stages. First, Kuwait’s research institutes and universities need to design interactive programs and activities with industry and community to help innovate solutions to current and prospective challenges. Second, the government needs to provide a competitive business environment and effective policies. Thirdly, the Kuwait industry must be encouraged to innovate and infuse modern technology practices.

Developing countries are trying to use science, technology and innovation as an effective strategy for achieving sustained economic growth. However, since each country has its unique conditions, learning from other success stories proved difficult if not structured in a framework designed to serve a specific purpose such as the one the authors propose in this paper.

This study analyses configurations of national culture as boundary conditions of countries’ national systems of innovation (NSI). Drawing from the NSI approach, we argue that culture’s role is that of a contingency factor shaping the relationship between investments in innovation and national innovation outputs.

We assessed the moderation effect of national culture through a systematic, two-stage approach using fuzzy-set Qualitative Comparative Analysis (fsQCA), which allows the analysis of changes induced by the moderator variables. Analyses were conducted with a diverse sample of 61 countries over a period spanning 12 years, from 2011 to 2022.

Findings reveal that investments in innovation, but not individual cultural dimensions, is a necessary condition for high innovation outputs. Furthermore, several configurations of cultural dimensions were identified as moderators of the relationship between investments in innovation and innovation outputs.

This study provides insights into cross-national innovation research by exposing the role of cultural configurations, rather than just individual cultural dimensions, as boundary conditions involved in the achievement of high levels of innovation.

This paper aims to depart from the national innovation system (NIS) arguments that countries' institutional arrangements and performance result from various complementary factors that generate innovative activities and products within economies.

To further explore these dimensions, the main objective of this paper is to address the determinants of global heterogeneity in the innovation outcomes of the nations. Thus, the research employs descriptive data analysis and multivariate regression models, using data from the Global Innovation Index (GII) to analyze innovation systems cross-regionally concerning institutional arrangements and performance. Since 2013, the GII, has annually measured and ranked the innovation inputs and outputs of more than a hundred countries based on a comprehensive and sophisticated approach and a multidimensional perspective.

The author found the empirical results remarkably interesting in many respects. The different indexes of innovation inputs affect the country's performance level, but not all show a statistically significant impact on innovation outputs. Institutions and infrastructure indexes do not affect the innovative performance of the economies. The main determinants of innovation performance worldwide are business sophistication, human capital & research (HC&R) and market sophistication. In short, the research presents an original contribution, mainly because it explores different views on NIS disparities worldwide, using complementary methodological strategies and based on comprehensive data on innovative inputs and outputs in the countries.

The findings add new evidence-based knowledge on the determinants of innovation performance in different realities, such as political, economic and administrative. These realities formulate innovation policies and implement them worldwide.

Farmers in rural areas are generally not well empowered with knowledge and innovations to solve their agricultural problems in spite of the growing presence of such knowledge resulting from research and innovation activities across the globe. This study aims to document approaches, impact and impediments of using village knowledge centers (VKCs) to transfer agricultural knowledge and innovations.

To achieve the objective of the study, a case study research design was used to investigate the impact of a selected VKC as institutional innovation in agricultural technology outreach and extension in rural Tanzania. Primary data was collected through semi-structured interviews, focus group discussions and observation methods. Besides, secondary sources such as reports were used to complement primary data during fieldwork.

The study reveals that various approaches are used by the VKC to transfer knowledge and innovation to farmers. The use of the multi-actor platform (MAP) to run the VKC ensures inclusive knowledge production and sharing among different actors. The findings also suggest that knowledge and innovation co-creation is constructed with various knowledge systems actors to enhance the use of research generated. Accordingly, the findings show that the university efforts are an important catalyst for integrated knowledge, technology and innovation systems in rural settings.

The present study reveals different limitations associated with the use of a single case study design. The single-case design provided researchers with little basis for generalisation of the study findings and conclusions. Aside from that, the use of a cross-sectional design did not help the researchers to validate the findings and conclusions. To address these limitations, the study recommends similar studies that will adopt different types of longitudinal design such as cohort and diary methods. Apart from this, a future study to investigate the tangible impact of VKC on knowledge and innovation transfer is recommended.

Considering the novelty of the MAP approach in Tanzania and the dearth of studies reporting on how the village knowledge center works and how effective it is, the present study provides insights on the approaches, impact and impediments.

This study aims to map and assess the conceptual development of the innovation ecosystem literature.

A bibliometric analysis was performed using the VOSviewer, RStudio software, Bibliometrix and Biblioshiny packages. To accomplish this, 367 publications published between 2006 and 2020 and indexed in the Web of Science and Scopus databases were assessed.

The results demonstrate a rise in research during 2016, with almost 30% of publications concentrated in only six journals. The co-citation analysis presented four clusters: case studies, business and innovation ecosystems (platform approach), open innovation and national and regional innovation systems (territorial approach). We proposed a theoretical framework based on two approaches in the innovation ecosystem literature based on co-citation analysis: platform, which has its roots in the literature on strategy, and territory, grounded in research on economic geography literature.

One of the limitations of the study is that only articles published in journals were analyzed, leaving out of the sample those published in congresses, books and other sources.

This paper contributes to the literature by presenting and clarifying the different conceptual trajectories of research in innovation ecosystems. We also proposed an analytical framework based on the two main approaches to innovation ecosystems – platform and territory. This framework presents the critical elements of managing innovation ecosystems from both perspectives.

This work aims to analyze the university–industry interaction in innovation ecosystems. The problem under study addresses how agents can operate in university–industry interactions to enhance the connections, specifically in the aspect of operational mechanisms of an innovation ecosystem.

The study is qualitative, applied through grounded theory approach, cross-sectional and multiple sources of evidence – semi-structured interviews were conducted. An explanatory conceptual model was subsequently compared with the literature and validated with specialists.

The results showed that the university–industry interaction is influenced by several factors, such as networking, legal support, facilitating agents, management practices. Despite this, some other factors were identified for the improvement of U–I relationships, such as: strengthening of triple helix, greater legal certainty and encouragement of open innovation.

The small sample size and the heterogeneity among the universities interviewed did not allow full saturation to occur. In spite of that, a significant level of saturation with respect to the challenges and barriers was observed.

This work has a direct dialogue with researchers, managers and actors involved in university–industry interaction with regard to increasing the capacity for creation and dissemination of knowledge among organizations, educational institutions, government and companies.

By adopting a grounded theory approach, a detailed research agenda addresses research needs in two main areas: activities that precede the interaction between universities and companies, and the organization and management of the consequences of collaborative relationships.

The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

The purpose of this study is to examine the effects of banking innovations (INNs) on customer experience (EXP), satisfaction (SAT) and loyalty (LOY).

The author evaluated the data using a structural equation method-artificial neural network (SEM-ANN) method. The author’s results show the presence of relationship between INN, EXP, SAT and LOY. In this study, the node layers of ANNs add an input layer, hidden layers and an output layer. Each “node” acts as an artificial neuron that communicates with others. The ANN model takes the variables from the SEM analysis as input neurons.

The author observed the significant effects between INN, EXP, SAT and LOY using the normalised importance generated by the multilayer perceptron used in the feed-forward back propagation of the ANN methodology. In this study, the ANN model can predict LOY through service innovation, with a forecast accuracy of 77.6%.

By applying neural network modelling, this research helps us understand how service innovation affects customer behaviour. For the first time, the author examined service innovations' direct and indirect impact on loyalty through EXP and SAT. The author made a significant conceptual contribution by using a non-compensatory model of ANNs to circumvent the limitations of linear models.

This study aims to elucidate institutional analysis as an effective approach to investigating and designing the multilevel policymaking system of online social networks (OSN) for achieving a participatory model.

The institutional mapping approach has been used to analyze Iran’s OSN multilevel policymaking system. A combination of two matrices, including institutions-institutions and institutions-functions, was used to perform the institutional mapping. Two main steps were taken to draw the mentioned matrices. First, a review of related studies in Iran’s OSN policymaking system was conducted and the policy functions mentioned in these studies were identified and categorized using the meta-synthesis. Second, based on analyzing two policy documents of Iran’s OSN, institutions and their interactions were identified and policy functions were allocated to institutions.

Based on the results, the most important policy functions in the current OSN policymaking system in Iran are support, regulatory, monitoring and evaluation, business environment development, culture building and promotion, organizing licenses and permissions, policymaking and legislation. Also, the results show that there are shortcomings in this system, some of the most important of which are lack of transparency in regulatory, little work in culture building and promotion, neglect of the training of specialized human resources and research and development, slow development of the business environment and neglecting the role of nongovernmental organizations in policymaking.

By examining and analyzing how different institutions operate within a multilevel policymaking system, the policymaking process and its overall effectiveness can be enhanced. This analysis helps identify any inconsistencies, overlaps or conflicts in the roles and policies of these institutions, leading to a better understanding of how a multilevel policymaking system is organized.