Technological Innovation Paths Research Articles

Research on the path of technological innovation and resource allocation optimization of state-owned enterprises from the perspective of ecological environment and biomechanics

In the evolving global landscape, competition among nations has increasingly centered on the allocation of innovation resources, which are crucial for enterprises to implement development strategies under supply-side reforms. The efficiency and rationality of resource allocation directly affect the innovation capacity and operational performance of enterprises. This paper examines the relationship between technological innovation and resource allocation in state-owned enterprises through the lens of the ecological environment, employing data from multiple sources and utilizing the Data Envelopment Analysis (DEA) model to assess resource allocation efficiency. The study reveals that the proportion of R&D personnel invested in enterprises in China increased significantly from 46.35% to 73.38%, while the proportion in research institutions and universities declined to 11.48% and 11.36%, respectively. These shifts underscore the growing dominance of state-owned enterprises in driving technological innovation. The findings highlight that aligning technological innovation mechanisms with ecological sustainability not only enhances innovation capabilities and competitiveness but also accelerates industrial development and contributes to the sustainable growth of the national economy.

Analysis of the influence and coupling effect of environmental regulation policy tools on industrial green and low-carbon transformation

Industrial green and low-carbon transformation plays a crucial role in China’s efforts to achieve its Carbon peaking and Carbon neutrality objectives. The implementation of environmental regulation policies is a key institutional framework that facilitates this transformation. Therefore, it is of great importance to explore the impact and interplay of these policies on industrial green and low-carbon transformation to foster high-quality economic development. This study categorizes environmental regulation policy instruments into three types: command-type, investment-type, and expense-type. Using industrial panel data from 30 provinces in China spanning the period from 1997 to 2021, both theoretical analysis and empirical testing are conducted to investigate the effects of these different policy instruments on industrial green and low-carbon transformation. The benchmark regression results show that the impact of command-type environmental regulation and investment-type environmental regulation on industrial green and low-carbon transformation shows an inverted U-shaped feature of rising first and then declining. The impact of cost-based environmental regulation on industrial green and low-carbon transformation shows a U-shaped feature of decreasing first and then increasing. The coupling of command-type environmental regulation and investment-type environmental regulation, command-type environmental regulation and expense-type environmental regulation, and the coupling of the three kinds of environmental regulation can promote industrial green and low-carbon transformation. The mechanism test results show that the impact of formal environmental regulation on industrial green and low-carbon transformation has a transmission mode of “formal environmental regulation–green technology innovation path–green and low-carbon transformation.”

Green Supply Chain Technology Innovation and Enterprise Synergy in the Context of Sustainable Development: Challenges and Strategie

This study explores the synergistic development between technological innovation and enterprises in green logistics supply chains from the sustainable development perspective. The study first introduces the latest progress of China's environmental policies and technological innovation and analyses the importance and necessity of green logistics supply chain management. Subsequently, through case studies and theoretical research, this paper discusses the policies and regulations of green supply chain management, collaborative management among enterprises, and the development path of technological innovation. It further analyses the contents of policies and regulations, enterprise collaboration management, and technological innovation in green logistics supply chain management. It proposes strategies and suggestions to solve problems by combining cases and theories. Finally, this study summarises the development status of green logistics supply chain management. It looks forward to future development trends, emphasizing that more enterprises should strengthen cooperation to jointly promote green logistics supply chains, environmental protection, and sustainable economic and social development.

The path of green finance to promote the realization of low-carbon economic transformation under the carbon peaking and carbon neutrality goals: Theoretical model and empirical analysis

In 2020, China proposed the Carbon Peaking and Carbon Neutrality Goals, promoting low-carbon economy and the related green financial market environment. The introduction of relevant policies means that China's green financial service system is undergoing transformation. This is not only a manifestation of China's active commitment to environmental protection obligations, but also a major responsibility for China to actively respond to global climate change. It also directly puts forward higher requirements for China to accelerate the implementation of low-carbon economic transformation. Based on the panel data of 30 provinces (cities) from 2006 to 2020, this article realistically uses panel data information as the most fundamental basis, and adopts the Mediating Effect and GMM model to empirically analyze and verify the implementation path of green finance to assist in the low-carbon transformation of the economy. The study found that green finance could assist in the low-carbon transformation of the economy: there are paths of green finance →upgrading industrial structure → GDP carbon emission intensity and green finance →technological innovation→ GDP carbon emission intensity. Heterogeneity analysis showed that, in high-carbon emission areas, the upgrading of industrial structure has played a negative mediating effect in the process of green finance assisting in the low-carbon transformation of the economy. In addition, both the technological innovation paths in high-carbon emission areas and the upgrading industrial structure and technological innovation path in low-carbon emission areas have played a positive mediating effect in the process of green finance assisting in the low-carbon transformation of the economy. The research in this article enriches and develops the theory of finance and economic growth, providing a reference basis for achieving the Carbon Peaking and Carbon Neutrality Goals and coping with the difficulties encountered in the low-carbon transformation of the economy. It is of positive significance in the field of low-carbon development.

Unlocking the carbon emission efficiency improvement path of technological innovation: a perspective on industrial restructuring and R&D element flows.

Technological innovation is regarded as an important means to improve carbon efficiency. However, there is no consensus on this view. Meanwhile, few studies have considered how technological innovation affects carbon efficiency. To this end, this study investigates the influencing mechanism and effects of technological innovation on carbon emission efficiency from the perspectives of industrial restructuring and R&D element flow. It establishes the influencing and mechanism model and then deeply studies the impact and paths of technological innovation on carbon emission efficiency, using panel data from 30 provinces in 1999-2020. Results show that (1) technological innovation improves carbon emission efficiency. (2) Regional differences in the impact effects of technological innovation are evident, with a greater contribution to carbon emission efficiency in eastern region. (3) Innovation improves carbon efficiency through two paths: advanced industrial structure and industrial structure rationalization. (4) The moderating effect demonstrates that the technological innovation's influence is gradually enhanced with the interregional mobility of R&D personnel and capital. Hence, decision-makers should correctly guide the orderly flow of R&D factors and further improve the carbon emission reduction effect by increasing innovation support and helping optimize the industrial structure.

Research on technology innovation path of Intelligent Manufacturing enterprises-Based on qualitative comparative analysis of fuzzy sets under TOE framework.

Intelligent manufacturing enterprises play a crucial role in the modern industrial system and are key to high-quality economic development. However, most current research on intelligent manufacturing technology innovation focuses on single variables, lacking a comprehensive analysis from a linkage grouping perspective. This paper constructs an analytical framework for the technology innovation path of intelligent manufacturing enterprises from three dimensions: technology level, organization level, and environment level. Six antecedent variables are selected: R&D investment, digital transformation, human capital structure, profitability, government support, and competitive position. Using the fuzzy sets of qualitative comparative analysis (fsQCA) methodology, the paper examines the technological innovation paths of intelligent manufacturing enterprises in China. The research indicates that no single antecedent variable is necessary for high technological innovation; instead, the innovation path results from the synergistic effect of multiple conditions. The study identifies three paths leading to high technological innovation in intelligent manufacturing:"Government and Human Resource driven types," "Environmental-Organizational linkage types,"and"Organizational Resilience dominant types." This analysis provides reference suggestions for enterprises to adopt suitable development strategies based on their competitive positions.

The Commercial Application Scenario and Development Path of Intelligent Manufacturing and New Energy Integration

This paper deeply discusses the commercial application scenarios and development paths of the integration of intelligent manufacturing and new energy. By summarizing the basic knowledge of intelligent manufacturing and new energy, the importance and motivation of the integration of the two are highlighted. This paper analyzes the application status of intelligent manufacturing and new energy in automobile manufacturing, construction industry and energy Internet, and puts forward the path of technological innovation, policy promotion, business model innovation and social cooperation for the future development. At the same time, the research points out the technical challenges, policy challenges, business model challenges and social collaboration challenges faced by the integration of intelligent manufacturing and new energy, and provides specific countermeasures for each challenge. Finally, the paper summarizes the results and prospects the future developments.

Heart rate estimation from ballistocardiogram signals processing via low-cost telemedicine architectures: a comparative performance evaluation.

Medical devices (MDs) have been designed for monitoring the parameters of patients in many sectors. Nonetheless, despite being high-performing and reliable, they often turn out to be expensive and intrusive. In addition, MDs are almost exclusively used in controlled, hospital-based environments. Paving a path of technological innovation in the clinical field, a very active line of research is currently dealing with the possibility to rely on non-medical-graded low-cost devices, to develop unattended telemedicine (TM) solutions aimed at non-invasively gathering data, signals, and images. In this article, a TM solution is proposed for monitoring the heart rate (HR) of patients during sleep. A remote patient monitoring system (RPMS) featuring a smart belt equipped with pressure sensors for ballistocardiogram (BCG) signals sampling was deployed. A field trial was then conducted over a 2-month period on 24 volunteers, who also agreed to wear a finger pulse oximeter capable of producing a photoplethysmography (PPG) signal as the gold standard, to examine the feasibility of the solution via the estimation of HR values from the collected BCG signals. For this purpose, two of the highest-performing approaches for HR estimation from BCG signals, one algorithmic and the other based on a convolutional neural network (CNN), were retrieved from the literature and updated for a TM-related use case. Finally, HR estimation performances were assessed in terms of patient-wise mean absolute error (MAE). Results retrieved from the literature (controlled environment) outperformed those achieved in the experimentation (TM environment) by 29% (MAE = 4.24 vs. 5.46, algorithmic approach) and 52% (MAE = 2.32 vs. 3.54, CNN-based approach), respectively. Nonetheless, a low packet loss ratio, restrained elaboration time of the collected biomedical big data, low-cost deployment, and positive feedback from the users, demonstrate the robustness, reliability, and applicability of the proposed TM solution. In light of this, further steps will be planned to fulfill new targets, such as evaluation of respiratory rate (RR), and pattern assessment of the movement of the participants overnight.

Research on the development path of integration of rural sports culture and sports tourism in the context of big data

Abstract In the context of rural revitalization strategy, sports and culture industry, with its wide coverage and strong inclusiveness, has become an important grip to boost rural revitalization. The development of sports tourism industry needs to rely on innovation drive. China’s sports tourism industry has stepped into the stage of high-quality development from traditional rough development. Under the strategy of rural revitalization, the issue of the significant impact of innovation on sports tourism development is addressed. This paper uses case studies and other methods to analyze the policy background of rural revitalization and sports industry development in conjunction with the promotion and application of big data today, and elaborates the value implication and role mechanism of sports industry to promote rural revitalization. At the same time, it explores the mechanism of the integration development of rural sports culture and sports tourism from four different perspectives: factor-driven, goal-oriented, resource-oriented and sports segment-guided. Finally, the “technology-fund-talent-synergy” innovation mechanism is constructed, and through the analysis of the difficulties faced by the development path of integration of rural sports culture and sports tourism, several suggestions are put forward to realize the development path of integration of rural sports and tourism. It proposes a driving path of technological innovation, capital innovation, talent innovation and collaborative innovation, and provides theoretical support for the high-quality development of sports tourism industry.

Machine Learning Based Industrial Engineering With 6G Technology

The "Ubiquitous Wireless Intelligence" concept of 6G opens up a variety of technological innovation paths, some of which are aided by machine learning and artificial intelligence, the two topics on which this work focuses. However, this advancement in ICT comes at a time when people are more driven than ever to use digital inclusion to reduce social and economic inequality while also giving the UN Sustainable Development Goals priority (SDGs). The document is divided into four sections: what 6G offers, the gaps and technical hurdles now present, the role of machine learning in many aspects, and finally the difficulties associated with incorporating AI/ML For the first time, a brand-new theoretical framework, denoted as 6GIIoE, was developed for the 6G-enabled IIoE system. This paper presents the vision of future 6G wireless correspondence and its network design. We talk about the emerging advances such as artificial intelligence, terahertz correspondences, optical wireless innovation, free space optic organization, blockchain, three dimensional networking, quantum correspondences, automated ethereal vehicle, without cell correspondences, integration of wireless information and energy move, integration of sensing and correspondence, integration of access-backhaul networks, dynamic organization slicing, holographic beamforming, and enormous information examination that can help the 6G design improvement in guaranteeing the QoS. We present the normal applications with the prerequisites and the potential innovations for 6Gcorrespondence. We likewise outline the potential difficulties and research headings to arrive at this objective.

Brain–computer interfaces and 3d design manufacturing in a postdigital scenario

The paper describes the results of seven-year experimental research between manufacturing processes of product design and the BCI - Brain–Computer Interfaces field, afferent to neuroscience. From analyzing a postdigital scenario and the emergence of a series of case studies, the essay proposes theoretical-applicative research that develops new cooperation between BCI and object-oriented 3d printing technologies.From a humanistic perspective, the paper identifies the postdigital scenario as a conjunction plane between the constant bio-technological acceleration and digital culture. In the interaction of BCI with the Internet of Things, the contribution illustrates the meaning of the primary brain frequencies and some wearable devices able to detect them. The essay then describes the rise in the last decade of a series of design experiences on the borderline between design and neuroscience, highlighting how these technological hybridizations can lead to the singularization of objects.The final part carries out its path of technological innovation into practice through the experimentation of two processes: Alpha and Flows. The most operative part of the process investigates the interaction between different brain waves and software, the BCI's connection with the subjects, and the 3d printing of the results. Both experimental phases implement hybrid manufacturing processes, involving citizens in a process of scientific awareness through direct interaction with the artifacts created.By showing the expressive possibilities and touchpoints between neuroscience and design, the contribution tries to be a tangible manifestation of a design culture that integrates different scientific knowledge and skills. The conclusions place the adoption of BCIs within a conscious digital design aimed at a double outcome: on the one hand, bringing citizens closer to neuroscience issues, and on the other, activating transdisciplinary processes towards a hybrid production.

Collaborative elicitation process for sustainable manufacturing: A novel evolution model of green technology innovation path selection of manufacturing enterprises under environmental regulation.

Due to promote manufacturing enterprises to carry out green technology innovation practice smoothly, achieve the goal of energy conservation and emission reduction, and win green competitive advantage, this paper first divides the green technology innovation path into two types, namely internal independent R&D of green technology (IIGT) and external green technology introduction (EGTI), and analyzes the operation mechanism of these two types of paths. Secondly, a two-agent game model of different types of environmental regulation tools on the choice of green technology innovation path of manufacturing enterprises is constructed. To be sure, the manufacturing enterprises include the leader enterprise A and the follower enterprise B. It is assumed that the two groups of manufacturing enterprises produce the same products or provide the same services in the natural state without considering other influencing factors. Finally, stability analysis and numerical simulation are employed to compare and analyze the heterogeneous effects of different environmental regulation tools on the path selection of green technology innovation in manufacturing enterprises.The simulation shows that when the government adopts or does not adopt environmental regulation means, the system, leader enterprise A and follower enterprise B will eventually choose the path of IIGT or EGTI respectively after a long-term evolution process. However, the effects of subsidy for green technology innovation and carbon tax rate on the path selection of green technology innovation are different among the three parties. Specifically, when the government adopts the means of subsidy for green technology innovation, the leader enterprise A will actively choose the the path of IIGT earlier than the follower enterprise B. On the contrary, when the government adopts the means of carbon tax, the leader enterprise A will actively choose the the path of IIGT later than the follower enterprise B. The research of this paper is helpful to explore the green and sustainable development mode of China’s manufacturing industry under the dual constraints of environment and resources, and provides decision support for the relevant national departments to make relevant policies.

Construction and Path Analysis of Enterprise Green Technology Innovation Model Using Data Mining

With the rapid increase of resource consumption and ecological protection demand, the economic growth model of China has also changed to focus on efficiency and quality. In the future, the circular economic model will be the main direction of sustainable development. According to the analysis of international development trends, green consumption has become the development trend of the times. Some developing countries also put forward the concept of green trade in the process of trade. It results in a severe living environment and challenges for some Chinese enterprises. For this challenge, China should grasp the economic development trend and change the business model by adopting the green technology innovation model. It will reduce consumption and pollution, improve efficiency, and, also, build the enterprise green technology innovation model to greatly improve the production efficiency and resource utilization of the enterprises. This paper uses data mining technology to establish a mathematical model of cluster analysis. It describes the process of enterprise technological innovation in detail and analyzes the power source of enterprise technological innovation and several commonly used models. Through this model, the enterprise technological innovation ability can be comprehensively improved. It focuses on the analysis of the enterprise green technology innovation path based on data mining. It analyzes the enterprise green technology innovation path from the points of reducing transaction costs and improving the allocation efficiency of innovation elements. According to this path, the enterprise transaction costs can be reduced to a certain extent and the allocation efficiency of enterprise elements can also be realized.

Characteristics and evolution path of technological innovation in the Guangdong-Hong Kong-Macao Greater Bay Area

Characteristics and evolution path of technological innovation in the Guangdong-Hong Kong-Macao Greater Bay Area

Reprint of: Basic considerations for a digital twin of biointelligent systems: Applying technical design patterns to biological systems

Biointelligence is one of the most noted technological innovation paths. In the future, biological and technical systems are expected to interact and learn from each other to optimally solve a given production task. Therefore, a data driven monitoring of both the biological and technical system is just as essential as ensuring interoperability between different manufacturing systems and across enterprise boundaries. In this context, the Digital Twin concept is a promising approach for physical production environments. However, in order to transfer the concept to a biological subsystem of a production process several hurdles have to be taken. Among others, these include the hitherto distinct interpretation of the concept in the life sciences and the corresponding pre-structuring of living systems. In this paper we present basic considerations for a transfer of the asset administration shell and the RAMI4.0 architecture to biological subsystems. We develop the fundamentals of an integrated scalable model which will ensure the interoperability of biointelligent manufacturing systems. As such, the paper is to be understood as a contribution to clarification between approaches from production research and the life sciences. Its primary aim is to initiate a scientific discourse across disciplinary boundaries.

Green technology innovation path based on blockchain algorithm

The core of green technological innovation is to protect the ecology. The innovative introduction of ecological concepts into the existing ecosystem can ensure the sustainable development and progress of society. This paper mainly studies the path analysis of green technology innovation based on blockchain algorithm. Aiming at the high latency and low efficiency of pbft algorithm in green technology innovation, a low latency consensus algorithm ipbft based on an alternative voting mechanism is proposed. Explore the influencing factors of domestic realization of green technology innovation, clarify the reasons that hinder green technology innovation and give reasonable strategies to help domestic green technology innovation work to be carried out faster and better. This article compares the ipbft algorithm with the improved consensus algorithms cpbft, vpbft and pbft in recent years. Experimental results show that the consensus delay of the ipbft algorithm is much lower than that of the other three algorithms, and the average delay of the ipbft single consensus is only about 370ms. In different transaction volume and different node number throughput performance tests, the ipbft throughput in these two tests is better than the other three algorithms. In the view switching phase, the ipbft algorithm also takes less time than the other three algorithms. The above results show that the ipbft algorithm has lower consensus delay and higher throughput, which can reduce network communication overhead and save system transmission energy consumption. It can ensure the security and authenticity of information in the green technology innovation based on blockchain, and reduce system overhead.

Basic considerations for a digital twin of biointelligent systems: Applying technical design patterns to biological systems

Biointelligence is one of the most noted technological innovation paths. In the future, biological and technical systems are expected to interact and learn from each other to optimally solve a given production task. Therefore, a data driven monitoring of both the biological and technical system is just as essential as ensuring interoperability between different manufacturing systems and across enterprise boundaries. In this context, the Digital Twin concept is a promising approach for physical production environments. However, in order to transfer the concept to a biological subsystem of a production process several hurdles have to be taken. Among others, these include the hitherto distinct interpretation of the concept in the life sciences and the corresponding pre-structuring of living systems. In this paper we present basic considerations for a transfer of the asset administration shell and the RAMI4.0 architecture to biological subsystems. We develop the fundamentals of an integrated scalable model which will ensure the interoperability of biointelligent manufacturing systems. As such, the paper is to be understood as a contribution to clarification between approaches from production research and the life sciences. Its primary aim is to initiate a scientific discourse across disciplinary boundaries.

Industrial districts and the fourth industrial revolution

Purpose This paper aims to explore if firms located in industrial districts (IDs) have different adoption paths concerning Industry 4.0 technologies and get different results with respect to other similar firms located outside IDs. Design/methodology/approach The study is based on a quantitative analysis related to an original data set of 206 Italian manufacturing firms specializing in made in Italy industries and adopting Industry 4.0 technologies. A case study of a district firm is also presented to explain the rationale of investment strategies and results obtained. Findings The analysis shows that there are differences between district and non-district firms when Industry 4.0 technology investments are concerned (higher investment rate in big data/cloud and augmented reality for district firms than non-district ones). In contrast to a breakthrough view of the fourth industrial revolution, the study suggests that 4.0 technologies emphasize the peculiarities and competitiveness factors typical of the district model in terms of customization and flexibility. There are differences in the motivations of adoption (product diversification for district firms vs productivity enhancement for non-district firms) and in the results achieved. Originality/value The paper is one of the first attempts to empirically explore the technological innovation paths related to Industry 4.0 within IDs, therefore, contributing to the debate on the possible evolution of the district model

The cultivation mechanism of green technology innovation in manufacturing industry: From the perspective of ecological niche

Abstract Green technology innovation is the strategy adopted by the manufacturing industry in implementing green innovation. Choosing the right green technology innovation path is crucial to the development of green innovation in manufacturing industry. From the perspective of niche theory, the paper constructs the green technology innovation trend indicators of manufacturing industry, and builds a multi-layer comprehensive evaluation model by using cloud model tools. Taking the green technology of manufacturing industry in Jiangsu Province as an example, the empirical analysis reveals that from 2012 to 2016, Jiangsu Province manufactures. The ecostate value of green technology innovation has been continuously improving, while the ecorole value has fluctuated. The comprehensive niche score has gradually boosted, indicating that the overall development trend of manufacturing green technology innovation capability in Jiangsu Province goes well. When advancing the level of innovation and formulating green technology innovation capability promotion strategies, macro-control and supervision for Jiangsu Province’s manufacturing green technologies should be emphasized, environmental management optimized, stimulation of green innovative talents strengthened, and green technology R&D and service centers intensified. Create a symbiotic environment, increase cooperation between enterprises, and the government, build a green innovation and cultivation mechanism for manufacturing, and facilitate sustainable development with creative approaches in Jiangsu Province.

Sustainable Technology Innovation Path Recognition: An Evaluation of Patent Risk of International Trade

Patent protection is a critical aspect of sustainable technology innovation, which is currently facing the challenge of patent risk. This study aimed to help enterprises prevent and avoid patent risk in a global view of technology innovation, and to propose a systematic evaluation model for patent risk. By combining the entropy method with the analytic hierarchy process (AHP), this study constructed an analytic hierarchy model of patent risk. Some indexes in the model were selected based on the summary of prior literature, and other indexes were selected according to experts’ communication, which helped us to generalize the patent risk as comprehensively as possible. The AHP evaluation results determined the weight and relative materiality for each risk factor, which were contained in a criteria layer and a sub-criteria layer. The entropy method integrated the evaluation weights of different experts’ opinions. By dividing the risk factors into three categories, namely “high”, “medium”, or “low”, according to the priority degree, the risk priority ranking was obtained. Suggestions are discussed regarding support for enterprises in dealing with patent risk that may occur during international trade or other commercial activities.