Search Results (10)

The innovation cooperation network (ICN) drives innovation. However, how its network diversity affects local innovation needs further exploration. This paper examines the effects of ICN’s scale and functional diversity on local innovation. Employing the township-level co-invention network in Beijing, we analyze the evolution of the scale and functional diversity from 2010 to 2020, and explore their impacts, as well as the effects of their interaction, on local innovation. Moreover, the relationship between network and Jacobs’ diversity is further discussed. The results show that the township-level scale and functional diversity of the ICN in Beijing have increased by over 40%, accompanied by a transformation in the core–periphery distribution pattern. Both scale and functional diversity significantly contribute to local innovation, but manifest as inverted-U relationships, and they substitute for each other in promoting innovation. Furthermore, a substitution effect also exists between network and Jacobs’ diversity, though not robustly. Research highlights the role of scale and functional diversity in the ICN. It emphasizes that local governments need to conduct more precise management and adjustments in light of the heterogeneity of network connections in different scales and sectors within the ICN, in order to boost local innovation and foster regional development. Full article

Interdisciplinary research (IDR) is essential for addressing complex global challenges that surpass the capabilities of any single discipline. However, measuring interdisciplinarity remains challenging due to conceptual ambiguities and inconsistent methodologies. To overcome these challenges, we propose a deep learning approach that quantifies interdisciplinarity in scientific articles through semantic analysis of titles and abstracts. Utilizing the Semantic Scholar Open Research Corpus (S2ORC), we leveraged metadata field tags to categorize papers as either interdisciplinary or monodisciplinary, establishing the foundation for supervised learning in our model. Specifically, we preprocessed the textual data and employed a Text Convolutional Neural Network (Text CNN) architecture to identify semantic patterns indicative of interdisciplinarity. Our model achieved an F1 score of 0.82, surpassing baseline machine learning models. By directly analyzing semantic content and incorporating metadata for training, our method addresses the limitations of previous approaches that rely solely on bibliometric features such as citations and co-authorship. Furthermore, our large-scale analysis of 136 million abstracts revealed that approximately 25% of the literature within the specified disciplines is interdisciplinary. Additionally, we outline how our quantification method can be integrated into a TRIZ-based (Theory of Inventive Problem Solving) methodological framework for cross-disciplinary innovation, providing a foundation for systematic knowledge transfer and inventive problem solving across domains. Overall, this approach not only offers a scalable measurement of interdisciplinarity but also contributes to a framework for facilitating innovation through structured cross-domain knowledge integration. Full article

Resource management in agriculture is considered a pivotal issue because greenhouse farming and agriculture-related activities generate about 10–29% of all global greenhouse gas emissions. The problem of high greenhouse gas emissions is still unresolved due to the rapid expansion of arable land to meet global food demand. The purpose of this systematic literature review was to generate new perspectives and insights regarding the development of resource management and optimized environments in greenhouses, thereby lowering energy requirements and CO₂ emissions. This review sought to answer what technologies and inventions could be used to achieve zero greenhouse gas emissions through efficient energy-saving mechanisms while considering their technical and economic viability. The synthesis of the findings led to several themes which included energy-saving techniques for greenhouses, systems that reduced unfavorable external conditions and renewable energy systems. Other themes identified regarded energy storage systems, systems for managing conditions in greenhouses, carbon capture and storage, and factors influencing the performance of different technologies to enhance resource management and ensure zero carbon emissions. The findings also revealed various technologies used in the design of energy-saving techniques in greenhouses including proportional–integral–derivatives (PID), fuzzy, artificial neural networks, and other intelligent algorithms. Additionally, technologies that were a combination of these algorithms were also examined. The systems that reduced unfavorable external conditions included the use of insulation panels and intelligent shading systems. Greenhouse covers were also optimized by smart glass systems, sensors, Internet of Things (IoT), and Artificial Intelligence (AI) systems. Renewable energy systems included PV (solar) panels, wind turbines, and geothermal electricity. Some of the thermal energy storage systems widely studied in recent research included underground thermal energy storage (UTES) (for seasonal storage), phase-change materials (PCMs), and water tanks, which are used to address short-term shortages and peak loads. The adoption of the various technologies to achieve the above purposes was constrained by the fact that there was no isolated technology that could enable agricultural producers to achieve zero energy, zero emissions, and optimal resource utilization in the short term. Future research studies should establish whether it is economical for large agricultural companies to install smart glass systems and infrastructure for slow fertilizer release and carbon capture in greenhouse structures to offset the carbon footprint. Full article

This paper proposes a new method to analyze technical development directions of a company using knowledge persistence-based main path analysis and co-inventor network analysis. Main path analysis is used for identifying internal technical knowledge flows and inheritances over time within a company, and knowledge persistence-based main path analysis can well identify major knowledge streams of each sub-domain within a relatively small knowledge network generated by one company without omission of significant inventions. A co-inventor network analysis is used for identifying key inventors who can be represented as the major technical capabilities of a company. The method is a meaningful attempt in that it applies knowledge persistence-based main path analysis to analyzing a company’s internal technical development and combines the two approaches to provide the information on both base technical capabilities and new technical characteristics. To test the method, this paper conducted an empirical study of Samsung Electronics. The results show that the method generated major knowledge flows and identified key inventors of Samsung Electronics. In particular, the method can identify the base technical knowledge as the ‘backbone’ and newly injected knowledge as ‘fresh blood’ for forecasting future technical development. Based on the identified clue information, this paper forecasted the potential future technologies for each sub-domain of Samsung Electronics with technical keywords and descriptions. Full article

Latinx seasonal farmworkers are essential workers and are at elevated risk for SARS-CoV-2 in the United States. Risk factors for SARS-CoV-2 are unique to this population and include crowded living conditions, isolated social networks, and exploitative working environments. The circumstances and cultural values of Latinx seasonal farmworkers pose a unique challenge to public health authorities working to contain the spread of SARS-CoV-2. This community is in dire need of urgent public health research to identify opportunities to prevent SARS-CoV-2 transmission: social network methods could be the solution. Using previously collected and new information provided by a team of experts, this commentary provides a brief description of Latinx seasonal farmworker disparities that affect tracking and treating SARS-CoV-2 in this important group, the challenges introduced by SARS-CoV-2, and how social network approaches learned from other infectious disease prevention strategies can address these disparities. Full article

The process of agricultural robot design is a complex system requiring the cooperation and integration of agricultural, machinery, automation, and information technology. These demands create great challenges for the innovative design of agricultural robots. Meanwhile, more than 95% of the latest inventions and creations in the world are recorded in the patent literature. In order to make effective use of the information and data resources of patents, shorten the design cycle, and provide knowledge for the designers, according to the operation’s objectives, an agricultural robot technology knowledge graph (TKG) was established for innovative designs. By analyzing the patent information, a patent IPC co-classification network (IPCNet) for adaptive design process recognition was put forward to meet the requirements of the different operation objectives and operation links. Through the extraction of the technology keywords and efficacy keywords, based on the word co-occurrence network (WCONet), a technology–efficacy map (TEM) was constructed. Through the integration of the adaptive design process and the TEM, the agricultural robot design TKG was constructed for determining technological recommendations for agricultural robot design. The case of the citrus picking robot design was realized to implement the design process. With the technology recommendation results, the moving system, body, and end-effector for the citrus picking robot were designed to verify the results of the recommendation. Full article

Knowledge creation involves social and collaborative processes with local and extra-local partners. The space of knowledge flows functions as a system of networks where knowledge is transmitted around different alignments of agents in distant places. Scholars argue that the concept of urban resilience combines local and extra-local competencies to develop an inter-city system, this is a major strategy for cities to mitigate and adapt to climate change and economic recession. Little attention has been given to the role of networks in co-invention and few empirical studies have been conducted. This article provides insights into the structure of inter-city networks of co-invention by examining the relative importance of the network compared with spatial proximity in biotechnology co-patenting across 150 American cities from 1983 to 2013. Results show that the U.S. inter-city structure gradually becomes more explicit, apparent, and identifiable in the network-based system. Network proximity better defines the biotechnology co-patenting relationships among the U.S. cities compared with spatial proximity. The current inter-city networks of co-invention are mostly regional, with some national but few local ties. This structure provides a way to develop mitigation and adaptation policies for climate disasters or economic recessions. Full article

Given the economic squeeze world over, search for what we call frugal grassroots innovations in Honey Bee Network, has become even more urgent and relevant in the recent years. And, to shape this search, models and concepts like open innovation, reverse innovation (GE, Market-Relevant Design: Making ECGs Available Across India, 2009); (Govindarajan, Reverse Innovation: a Playbook, 2012); (Govindarajan and Ramamurti. Global Strategy Journal, 1: 191–205, 2011); (Govindarajan and Euchner, Res. Technol. Manage, 55: 13–17, 2012, Govindrajan and Trimble, 40(5), 5–11, 2012), embedded innovation (Simanis and Hart, Innovation from the Inside Out, MIT Sloan Management Review, 2009), extremely affordable, low-cost, frugal innovation (Honey Bee Network, 1989–2016, Gupta, 2000); (Gupta AK, How Local Knowledge can Boost Scientific Studies, 2007); (Gupta AK, Indian Hidden hotebd of invention, 2009a; Gupta AK, http://anilg.sristi.org/harnessing-stimulus-forpromoting- innovations-and-entrepreneurship/, 2009b) etc., have emerged over time. We wish to trace the evolution of the Open Innovation Theory (Urban and Von Hippel, Manag. Sci. 34(5), 569–582, 1988) in the context of the Honey Bee Network working on such ideas for over 26 years. The idea is to study the different strands of relationships between knowledge providers and seekers which make the system truly reciprocal, responsible and responsive. When systems become open, search cost for inclusive innovation will automatically come down and the knowledge system will also become more symmetrical and inclusive. Inclusive innovation for social development implies that new solutions should help in dealing with one or more of the five factors of exclusion: spatial, seasonal, sectoral, skill and social. These should also be accessible, affordable, available and adaptable to varying and differentiated user endowments and needs, besides being circular. One has to understand the interaction between natural, social, ethical and intellectual capital, situated in the institutional context of innovations: at, from, for and with grassroots level communities for defining inclusivity in the innovation ecosystem. A company or a community, when in need of an innovative solution to a local problem, may seek it from outside, develop it inside, or co-create/contract it out. The nature of reciprocity between knowledge and innovation exchange partners may have different types of asymmetries (Bansemir and Neyer 2009). Different ethical principle enunciated in the Honey Bee Network may or may not be followed. The discourse on open innovation has been biased in the favour of corporates seeking ideas form outside rather than sharing their own innovation/knowledge as a public good or commons, or even at low cost with less-advantaged industry actors. In this paper, we reflect on such biases that companies and scholars have developed and propose a framework to temper it. The need for such a correction becomes even more important when various kind of climatic, institutional and market risks are making socio-economic systems more fragile and vulnerable to various uncertainties and fluctuations.
Coping with risks is significantly related to malleability of innovations. The process of evolving and nurturing innovations may have a bearing on their eventual adaptability to user. We argue that when both technology platform and application domains are known well, the incubation model works. Generally, through this process, incremental innovation grows better. But, when both are unknown or are ambiguous, sanctuary model works better. In incubators, the chaos is outside and the order is inside. In sanctuary, it is the opposite. It is not very surprising that sanctuary nurtures innovation which is more suited to fluctuating climate and market-uncertain environments.
Innovations don’t have relevance only at artefactual level. One can learn at metaphorical, heuristic and gestalt levels too. Building bridges between formal and informal knowledge systems poses a unique challenge in designing reciprocal and responsible open innovation platforms? This paper pleads for more reciprocal, respectful and responsible exchanges of knowledge between formal and informal sector adding value to the contributions of grassroots green innovators. Full article

The purpose of this study is to examine how the collaboration structure among inventors in an R and D organization affects its capability to create impactful innovations. Specifically, this study is focused on examining whether a certain type of network mechanism found in collaboration among inventors contributes more to enhancing the future impacts of collaboration outputs, which is represented by the forward citations of their patents. To this end, co-invention networks for R and D organizations are constructed from an inventor-patent database, and the three structural patterns are measured by using network analytic constructs, namely, structural holes, strength of ties, and centralization. The results show that the presence of structural holes and strong ties are positively associated with the increasing forward citations, and that decentralized collaboration has also a positive impact. The findings offer support for both structural hole and network closure perspectives on social capital, which have been considered contradictive in the literature. Full article

This work aimed to identify and address the main challenges associated with fabricating large samples of carbon foams composed of interwoven networks of carbon nanofibers. Solutions to two difficulties related with the process of fabricating carbon foams, maximum foam size and catalyst cost, were developed. First, a simple physical method was invented to scale-up the constrained formation of fibrous nanostructures process (CoFFiN) to fabricate relatively large foams. Specifically, a gas deflector system capable of maintaining conditions supportive of carbon nanofiber foam growth throughout a relatively large mold was developed. ANSYS CFX models were used to simulate the gas flow paths with and without deflectors; the data generated proved to be a very useful tool for the deflector design. Second, a simple method for selectively leaching the Pd catalyst material trapped in the foam during growth was successfully tested. Multiple techniques, including scanning electron microscopy, surface area measurements, and mechanical testing, were employed to characterize the foams generated in this study. All results confirmed that the larger foam samples preserve the basic characteristics: their interwoven nanofiber microstructure forms a low-density tridimensional solid with viscoelastic behavior. Fiber growth mechanisms are also discussed. Larger samples of mechanically-robust carbon nanofiber foams will enable the use of these materials as strain sensors, shock absorbers, selective absorbents for environmental remediation and electrodes for energy storage devices, among other applications. Full article