Review
Pharmacology & Pharmacy
Zhongxuan Ma, Kevin Augustijn, Iwan J. P. de Esch, Bart Bossink
Summary: This article conducts a bibliometric review to analyze the practices of university-industry collaborative research and development (UIC R&D) in the pharmaceutical sector over the past 30 years. The findings reveal the strategic alliance formation, organizational structure, and cultural norms in UIC R&D.
DRUG DISCOVERY TODAY
(2022)
Article
Information Science & Library Science
Manel Gonzalez-Pinero, Cristina Paez-Aviles, Esteve Juanola-Feliu, Josep Samitier
Summary: This paper explores how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by factors such as multidisciplinarity, knowledge base, and types of organizations involved. The study emphasizes the importance of stimulating various variables in collaborative research projects to benefit multidisciplinary consortia and accelerate the innovation process.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2021)
Article
Business
Juying Zeng, Zhenzhen Ning, Carlos Lassala, Samuel Ribeiro-Navarrete
Summary: This study utilizes social cooperation networks and multi-period DID to examine the impact of the innovative-city pilot policy on collaborative innovation in 26 cities in the Yangtze River Delta region from 2005 to 2020. The results show significant progress in collaborative innovation and an increase in cooperative intensity and control capability. However, the efficiency of R&D and technology transformation have not reached optimal levels, with transformation efficiency consistently lower than R&D efficiency. The pilot policy has a positive effect on improving innovation efficiency, with greater effects observed in provincial capital cities, particularly in Zhejiang province.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Yue Wu, Xin Gu, Zhenzhou Tu, Zhaobohan Zhang
Summary: Industry-university-research institute synergetic innovation (IUR-SI) is a contractual arrangement formed by the cooperation of enterprises, universities, and research institutes for the purpose of knowledge appreciation, sharing, and creation. This research analyzes the key factors influencing knowledge flow in the IUR-SI process and explores how to promote knowledge flow more effectively and efficiently. The results show that factors such as knowledge sharing ability, knowledge hiding coefficient, knowledge failure rate, trust relationship, and organizational distance have a significant impact on the overall knowledge stock of the system. Improving knowledge flow efficiency, the internal environment, and strengthening knowledge transfer and sharing are of great importance.
Article
Multidisciplinary Sciences
Xiaona Hou, Xiangxiao Gao, Shi Yin, Jianmin Li
Summary: Based on the current state of China's agricultural industry, this article proposes an integrated framework for the agricultural innovation ecosystem in developing countries. A dynamic simulation model is constructed to analyze the game process and factors influencing the agricultural innovation ecosystem. The results highlight the importance of industry-university-research collaboration and the implications of willingness to participate, cost of participation, and establishment of default fees for collaborative innovation within agricultural innovation ecosystems.
Review
Computer Science, Information Systems
Xin Chen, Guangxia Zhang
Summary: As university-industry collaborative innovation becomes a driving force for technological development, this study aims to fill the gap in scientometric analysis and visualization regarding research on individuals in this field. By using bibliometric indicators and visualization tools, the study analyzes the current progress and leading trends of university-industry collaborative innovation of individuals based on scientific publications from 2000 to 2022. The results reveal increasing academic interest, productive countries, emerging economies, and research focus areas, providing valuable insights for future research.
Article
Business
Zhuo-Yue Zhu, Hong -Ming Xie, Liang Chen
Summary: The ICT industry is characterized by globalized innovation activities, modular product forms, and intelligent technologies. ICT has greatly contributed to the development of the global digital economy. However, there have been concerns and questions about the global innovation model of ICT companies, leading to a need for a systematic review and summary of ICT industry innovation. Using qualitative and quantitative methods, this research analyzes the literature on ICT industry innovation published in top journals to provide guidance for future academic research and practice in ICT industry innovation.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Article
Business
Arman Y. Aksoy, Davide Pulizzotto, Catherine Beaudry
Summary: This study fills the gap between technological relatedness and university research commercialisation by examining the effect of patent portfolio composition on university research commercialisation. The results show a positive association between related diversification and the number of licences generating income, but no association for unrelated diversification. Furthermore, technological proximity follows an inverted-U shaped association with the number of licences generating income, but this effect is observed only for smaller universities. Therefore, policymakers should consider measures to bridge the cognitive gap between universities and industries in order to promote innovation and regional economic growth.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Business
Shaopeng Zhang, Xiaohong Wang
Summary: This study utilized super-efficiency data envelopment analysis method to investigate the impact of innovative city pilot policy on the knowledge innovation efficiency and knowledge transformation efficiency of industry-university-research knowledge flow. The results showed a significantly positive influence of the policy on both efficiencies. Furthermore, innovation cooperation dependence and innovation financial support partially mediated the effects of the policy on the efficiencies.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Business
Ao Zan, Yanhong Yao, Huanhuan Chen
Summary: This study explores the evolutionary stable strategy of university-industry collaborative innovation based on evolutionary game theory, finding that agent coupling degree, group size, and government policies all play significant roles in the stable evolution of university-industry collaborative innovation.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2021)
Article
Business
Aiting Xu, Keyang Qiu, Yuhan Zhu
Summary: This paper examines the innovation inequality of enterprises, universities, and scientific research institutions in China using various measures, and explores the contributions of intra-subject and inter-subject factors to the inequality. The study finds that despite some decline, the innovation inequality of the three subjects has remained relatively high in China over the past decade, with a tendency to frequently rebound. Additionally, the inequality in different innovation circles in northern, southern, and western regions show distinct development trends post 2006. The relationship between the subjects is identified as a key factor affecting the innovation inequality, with heterogeneities observed in research shortage, industry delay, and insufficiency in Industry University Research.
JOURNAL OF BUSINESS RESEARCH
(2023)
Article
Energy & Fuels
Wuyin Yan, Hui Liu, Baijun Han
Summary: This research collected photovoltaic patents from the perspective of Industry-University-Research collaborative innovation and examined the evolution of the collaborative innovation network from 2000 to 2019. Social Network Analysis (SNA) was used to analyze the characteristics of patent holders and the overall network, including network size and degree, network density, and network degree centrality. SNA results showed significant increases in network size and degree over time, while network density became sparser as PV technology developed and the number of core network members increased. Universities and research institutions demonstrated a clustering role in leading innovations and discipline construction. The leading knowledge domain studied by the industry, university, and research institutions was H01L, followed by F24J and F24S. Two noteworthy knowledge domains, H02J and H02S, related to control and regulation of power systems. This analysis provides insights into energy subjects and knowledge domains in collaborative innovations and education.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Management
Wenju Niu, Houcai Shen
Summary: This paper investigates whether manufacturers with differentiated absorptive capacity will invest in uncertain process innovation under knowledge spillovers. Game-theoretic models with bilateral investment, unilateral investment, and no-investment are developed to analyze the equilibrium outcomes. The study reveals that the intensity of knowledge spillovers plays a crucial role in manufacturers' investment decisions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Economics
Leticia de Castro Peixoto, Ricardo Rodrigues Barbosa, Adriana Ferreira de Faria
Summary: This study examines the process of knowledge creation and management in a geographic region, focusing on knowledge flow through university-industry-government collaboration. By integrating theories of knowledge management, the triple helix model, and regional knowledge, a framework is established to stimulate knowledge production and innovation in geographic regions. Collaboration and interaction among players are emphasized to consolidate synergy in the knowledge production chain for promoting innovation and sustainable development in the knowledge economy.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2022)
Article
Business
Ye Xu, Jie Zhu, Changqi Tao
Summary: This study proposes and elaborates on the concept of technical potential energy based on field theory in the context of industry-university-research institution (IUR) collaborative innovation. The driving mechanism of technical potential energy on different stages is analyzed and verified, showing varying effects. The research demonstrates that technical potential energy promotes the establishment of IUR collaborative innovation alliances in the preparation stage, drives technical innovation synergy in the operation stage, and stimulates technical spillover effect in the extension stage.
INTERNATIONAL ENTREPRENEURSHIP AND MANAGEMENT JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Ursula Addison
Summary: Goal reasoning is an essential functionality for artificial systems to manage and execute goals in complex and changing environments. This survey investigates motivated agents that simulate human integrated-self, exploring the potential benefits of internal motivations in goal reasoning. By evaluating different systems, the study concludes the potential advantages of motives, mental simulation, and emotion in the goal reasoning paradigm.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Haoran Fu, Chundong Wang, Jiaqi Sun, Yumeng Zhao, Hao Lin, Junqing Sun, Baixue Zhang
Summary: Although natural language processing has shown strong performance, it is vulnerable to adversarial examples. Current methods for English are not suitable for Chinese due to the differences in language structure. This paper proposes a new algorithm called WordIllusion for generating Chinese adversarial texts and verifies its effectiveness.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Beatriz Garcia-Martinez, Patricia Fernandez-Sotos, Jorge J. Ricarte, Eva M. Sanchez-Morla, Roberto Sanchez-Reolid, Roberto Rodriguez-Jimenez, Antonio Fernandez-Caballero
Summary: This study aims to detect auditory hallucinations (AH) in schizophrenia patients using a wireless EEG device. The results show that AH is mainly activated in the right frontal locations, while the left hemisphere demonstrates stronger activation during hallucination-free periods. Additionally, a decrease in spectral power during hallucination episodes compared to non-hallucination periods is observed.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Shivant Kathusing, Natalie Samhan, Jan Treur
Summary: This paper introduces a fifth-order adaptive self-modelling network model to describe the role of epigenetics in the development of anxiety disorders and suggests a possible epigenetics-based therapeutic method.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Yanru Jiang, Rick Dale, Hongjing Lu
Summary: This study investigates the integration of large-language models and recurrent neural networks into a hybrid cognitive model for solving natural language tasks. The findings highlight the crucial role of global knowledge in adapting to new learning tasks, while having only local knowledge significantly reduces system transferability.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
configuration Viacheslav Wolfengagen, Larisa Ismailova, Sergey Kosikov, Igor Slieptsov, Sebastian Dohrn, Alexander Marenkov, Vladislav Zaytsev
Summary: This paper proposes a configuration-based approach to knowledge extraction, which enhances the expressive power of semantic networks. By representing functions as objects, the central issues of nodes and links in knowledge-based systems are addressed. The model is applicable to representing morphing and considers objects as processes, aligning with current ideas in computing. The concept of information channels for process transformations is introduced. The potential for generating displaced concepts and their morph families is demonstrated.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Leibovici Anat, Raizman Reut, Itzhaki Nofar, Tik Niv, Sapir Maayan, Tsarfaty Galia, Livny Abigail
Summary: Traditionally, neuroimaging studies have focused on brain activation in frontal-parietal regions for fluid intelligence. However, recent evidence suggests the involvement of the cerebellum in higher cognitive function. This study investigates the role of the cerebellum in processing fluid intelligence and provides evidence through task brain activation and network analysis.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Leticia Berto, Leonardo Rossi, Eric Rohmer, Paula Costa, Ricardo Gudwin, Alexandre Simoes, Esther Colombini
Summary: Integrating robots into daily life is becoming a reality, and bridging the gap between human developmental theories and robotics applications is crucial. This research focuses on the early stages of human development from 0 to 2 years old and aims to simulate motor and cognitive growth in robots through progressive experiments.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Alice Plebe, Henrik Svensson, Sara Mahmoud, Mauro Da Lio
Summary: This article reviews the research on autonomous driving influenced by cognitive science, neuroscience, and psychology, proposing the potential advantages of human driving ability for developing autonomous vehicles and discussing the methods of applying human thinking process to autonomous driving.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Md Ehtesham-Ul-Haque, Jacob D'Rozario, Rudaiba Adnin, Farhan Tanvir Utshaw, Fabiha Tasneem, Israt Jahan Shefa, A. B. M. Alim Al Islam
Summary: This paper aims to explore emotion generation, particularly for general-purpose conversations. Based on the Cognitive Appraisal Theory, a novel method to calculate informative variables for evaluating emotion-generating events and six primary emotions is proposed. The implementation of EmoBot, an emotional chatbot, demonstrates its ability to generate more accurate emotional and semantic responses compared to traditional chatbots.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Simon Jerome Han, Keith J. Ransom, Andrew Perfors, Charles Kemp
Summary: This study applies GPT-3.5 and GPT-4 models to explore the differences between human and machine intelligence in the context of property induction. The results show that GPT-4 performs qualitatively similar to humans in most cases, with the exception of premise non-monotonicity. This research provides interesting comparisons and two large datasets for future studies.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Vincent Frey, Julian Martinez
Summary: This study proposes a trust dynamics model based on a multi-agent reinforcement learning algorithm, aiming to quantitatively understand the characteristics and behavior of interpersonal trust, and explore the relationship between trust and agent performance.
COGNITIVE SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Hamit Basgol, Inci Ayhan, Emre Ugur
Summary: This study investigates the mechanism behind event segmentation, the process of dividing experiences into discrete units. The researchers propose a computational model inspired by event segmentation theory and predictive processing, which successfully produces human-like event boundaries and representations.
COGNITIVE SYSTEMS RESEARCH
(2024)
