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Technology transfer (TT) from universities to manufacturing firms is important for enhancing innovation performance (IP) and ultimately improving competitiveness. However, TT is hampered by bureaucracy, inertia, inefficiency, cognitive dissonance, and low research and development activity. The purpose of this study is to examine the relationship between TT from universities to manufacturing firms and their IP. This study was conducted based on Megnigbeto's (2018) triple helix game theory. A mixed-method approach was used. The independent variable was TT, measured in terms of technology spillover, networking, and the presence of accelerators and incubators within a firm's locality. The dependent variable was IP, measured through innovation output and innovation efficiency. This study used an explanatory sequential research design. The target population was manufacturing firms in Kenya, identified using a multi-stage sampling strategy. Primary data were collected using semi-structured questionnaires, interview schedules, and checklists. Linear regressions, hierarchical multiple moderated regressions, structural equation modeling, and partial least squares were used to test the hypotheses. The results indicate that TT from universities significantly influences IP in manufacturing firms. Universities are important intermediaries of TT in manufacturing firms in Kenya because of their improved IP and competitiveness. Universities should create dynamic linkages with industries and adopt an engaged learning approach in their programs to create greater and more unique values for enhanced competitiveness and sustainable development. [ABSTRACT FROM AUTHOR]

Demand for solving systemic problems has resulted in the need for new forms of innovation. Accordingly, the concept of innovation ecosystem has emerged. Ecosystems are intrinsically more fluid than networks, which set ups the need to understand and orchestrate the internal dynamics of innovation ecosystem in order to have successful innovation outcomes. The dynamics of ecosystems, however, is not well understood. In this paper the dynamics of innovation ecosystems has been studied by applying the methodology of system dynamics. The purpose of the study is to support the creation of innovation ecosystems and the orchestration of existing ecosystems so that they could be more successful. Key factors generating dynamics in innovation ecosystems were identified. They form the elements of the system dynamics model of innovation ecosystems. The causal loop structure between the model elements indicates how the key factors of dynamics influence the outcome of ecosystem. [ABSTRACT FROM AUTHOR]

This study aims to show how activity theory in the socio-technical systems paradigm can assist in understanding and managing system innovation. We conceptualize sociotechnical systems to address societal needs as activity systems and system innovations as transformations of such systems. Transformations result from resolving contradictions that develop due to technical and social change within and between the activities carried out by various agencies to fulfill societal needs. Along this line, the explanation of system innovations focuses on identifying emerging contradictions, resolution initiatives, and their outcomes, whereas the governance of system innovations can be carried out by interactively developing policies through successive interventions to resolve contradictions. We demonstrate the employment of activity theory to understand the transformation of the recorded music socio-technical system towards streaming, as well as to facilitate the management of the transition of the olive oil-producing sector at the regional level towards a circular economy through the adoption of innovative waste-processing technology. [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]

With the continuous development of the computer field, the Internet has become the main way of education in today's era. The development of computer technology and big data has brought innovation and opportunities to the teaching mode of ideological and political courses in colleges and universities. Due to the dynamic change of big data, there are many difficulties in the establishment of ideological and political course models in colleges and universities. This paper studies the innovation of ideological and political course modes in colleges and universities on the network platform under the background of big data. This paper mainly compares the traditional teaching mode and explores the formal modeling method of network platform education. The discrete dynamic modeling technology of the complex system is used to model the formal process of online education. Then, it carries out nonlinear prediction modeling for the operation efficiency and traffic change of the network platform under the big data environment and uses dynamic modeling to predict the learning effect of college students' ideological and political course mode. The results show that the formal method of education under dynamic modeling can improve the defects of traditional teaching and give full play to the advantages of network platform teaching. Improving the teaching mode of network platform can improve students' learning efficiency. Finally, in the dynamic model prediction, the problem of big data affecting the model results is improved, and the accuracy of the prediction model is improved. [ABSTRACT FROM AUTHOR]

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate data resources and rich and reliable educational technology means for online public mental health education in colleges and universities. This paper comprehensively uses a variety of methods such as qualitative and quantitative analysis, case and empirical analysis, literature analysis, and artificial intelligence technology. Artificial intelligence technology has been closely integrated with online public mental health education in colleges and universities. The model systematically analyzes the optimization methods of artificial intelligence technology methods for the online public mental health education system in colleges and universities, and constructs an innovation system for online public mental health education in colleges and universities. Based on the comprehensive analysis of artificial intelligence and public health in colleges and universities, this paper further proposes the application of artificial intelligence technology in online public mental health education in colleges and universities. On this basis, the model conducts an in-depth analysis of artificial intelligence technology and the online public mental health innovation system. The model supports the development of ideological and political teaching in colleges and universities through various forms such as idea innovation, path innovation, carrier innovation, and mechanism innovation. [ABSTRACT FROM AUTHOR]

As a distributed computing technology, cloud computing has the characteristics of fast processing speed, large-capacity data processing, and high overall efficiency. With the continuous development of communication technology today, cloud computing technology has begun to be applied in various industries and has promoted the development and progress of the industry. As an important part of college education, ideological and political education in colleges and universities is also constantly developing. The integration of cloud computing and ideological and political education is the main trend in the future. At present, the application research of cloud computing and wireless communication technology in the ideological and political education of colleges and universities has obtained some results, but there are still some problems. Therefore, the research on innovative methods of ideological and political education is extremely important. At present, under the attention of all walks of life, scholars have strengthened the research on new paths of ideological and political education in colleges and universities, and they are also constantly experimenting with innovative methods. In this context, this paper studies the current situation of ideological and political education in colleges and universities through questionnaire surveys and analyzes the innovative mode of ideological and political education in colleges and universities in the context of cloud computing through the K-means clustering algorithm model. [ABSTRACT FROM AUTHOR]