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This study discusses the protection of traditional villages and understand the role, policy environment and characteristics of traditional village protection. This study also constructs an analytical framework of “historical timing - policy orientation” to study the development process and policy evolution of traditional village protection in China.

This study selects the policy documents related to traditional village protection since 1980 as the research samples to explore the origin and evolution of traditional village protection in China. Then, the paper systematically combs the temporal evolution of the policy theme and orientation at each stage, which would provide a reference direction for the protection and development of traditional villages.

The interpretation of traditional village protection and its institutional background can be divided into three stages: relying on the protection system of historical and cultural towns and villages (1982–2012) and the stage of construction and improvement of traditional villages protection system (2012–2017). After 2017, traditional village protection entered a new rural revitalization journey.

This study is limited to: documents issued from 1982 to the end of 2022; Central Committee of the Communist Party of China, the State Council, and central ministries and administrations directly governing the protection of traditional villages; policies that can directly reflect the central government’s attitude towards protecting traditional villages; and excluding the documents for some particular regions and particular problems.

This study fulfills as the guidance of traditional village protection and development in different periods.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Public reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study explores the public attitudes and emotions toward educational robots through online reviews on Weibo and Twitter by using text mining methods.

Our study applied topic modeling to reveal latent topics about educational robots through online reviews on Weibo and Twitter. The similarities and differences in preferences for educational robots among public on different platforms were analyzed. An enhanced sentiment classification model based on three-way decision was designed to evaluate the public emotions about educational robots.

For Weibo users, positive topics tend to the characteristics, functions and globalization of educational robots. In contrast, negative topics are professional quality, social crisis and emotion experience. For Twitter users, positive topics are education curricula, social interaction and education supporting. The negative topics are teaching ability, humanistic care and emotion experience. The proposed sentiment classification model combines the advantages of deep learning and traditional machine learning, which improves the classification performance with the help of the three-way decision. The experiments show that the performance of the proposed sentiment classification model is better than other six well-known models.

Different from previous studies about attitudes analysis of educational robots, our study enriched this research field in the perspective of data-driven. Our findings also provide reliable insights and tools for the design, development and management of educational robots, which is of great significance for facilitating artificial intelligence in education.

This paper aims to try to develop new, environmentally friendly and efficient lubricating additives; study the compatibility of carbon-based additives with different base oils [Polyalphaolefin (PAO)-3, PAO-20 and NPE-2]; and explore the lubrication mechanism.

Oleylamine modified carbon nanoparticles (CNPs-OA) were prepared and the dispersion stability of CNPs-OA in PAO-3, PAO-20 and NPE-2 base oils was investigated by transmission electron microscopy, Fourier transform infrared, thermogravimetric analysis, energy dispersive spectroscopy and X-ray photoelectron spectroscopy. Universal Mechanical Tester (UMT) platform was used to carry out experiments on the effects of different additive concentrations on the lubricating properties of base oil.

The mean friction coefficient of PAO-3, PAO-20 and NPE-2 reduced by 32.8%, 10.1% and 11.4% when the adding concentration of CNPs-OA was 1.5, 2.0 and 0.5 Wt.%, respectively. Generally, The CNPs-OA exhibited the best friction-reducing and anti-wear performance in PAO-3.

The agglomeration phenomenon of carbon nanoparticles as lubricating additive was improved by surface modification, and the lubricating effect of carbon nanoparticles in three synthetic aviation lubricating base oils was compared.

Corrosion is a major concern for many industries that use metals as structural or functional materials, and the use of corrosion inhibitors is a widely accepted strategy to protect metals from deterioration in corrosive environments. Moreover, the toxic nature, non-biodegradability and price of most conventional corrosion inhibitors have encouraged the application of greener and more sustainable options, with natural and synthetic drugs being major actors. Hence, this paper aims to stress the capability of natural and synthetic drugs as manageable and sustainable, environmentally friendly solutions to the problem of metal corrosion.

In this review, the recent developments in the use of natural and synthetic drugs as corrosion inhibitors are explored in detail to highlight the key advancements and drawbacks towards the advantageous utilization of drugs as corrosion inhibitors.

Corrosion is a critical issue in numerous modern applications, and conventional strategies of corrosion inhibition include the use of toxic and environmentally harmful chemicals. As greener alternatives, natural compounds like plant extracts, essential oils and biopolymers, as well as synthetic drugs, are highlighted in this review. In addition, the advantages and disadvantages of these compounds, as well as their effectiveness in preventing corrosion, are discussed in the review.

This survey stresses on the most recent abilities of natural and synthetic drugs as viable and sustainable, environmentally friendly solutions to the problem of metal corrosion, thus expanding the general knowledge of green corrosion inhibitors.

The objective of this research is to methodically categorize the various types of Open Government Data (OGD) stakeholders, and to elucidate the intricate network relationships among OGD stakeholders, along with the underlying mechanisms that shape their formation.

To comprehend the collaboration mechanism of stakeholders in the OGD ecosystem, the authors constructed an OGD multi-stakeholder relationship network by using data from the Shandong Province Data Application Innovation and Entrepreneurship Competition. Based on the structural social capital theory and exponential random graph model (ERGM), an analytical framework was established to explore the formation mechanism of the collaborative network of OGD multi-stakeholder.

The results indicate that multi-stakeholder collaboration among government, enterprises and the public is crucial for achieving OGD goals. Organizing OGD competitions serves as an effective mechanism for solidifying and maintaining relationships among OGD stakeholder groups. Degree centrality and structural parameters reveal a Matthew effect within the connection process of the OGD ecosystem's collaborative network. Additionally, there is evidence of agglomeration and transferability within the network's structure.

This study contributes to the understanding regarding the formation mechanism of OGD stakeholders. The findings have implications for developing multi-stakeholder relationship networks of OGD and driving OGD initiatives.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2023-0284

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

In the context of open innovation, more and more enterprises are leveraging innovation networks to drive disruptive innovation performance, but there is no consensus on the relationship between network embeddedness and enterprise disruptive innovation performance. This paper aims to systematically explore the relationship between them.

This paper constructs a multi-level network embeddedness model and uses 58 independent studies as samples to explore the relationship between multi-level network embeddedness and enterprise disruptive innovation performance by meta-analysis.

First, network embeddedness at the enterprise and regional levels will promote the improvement of disruptive innovation performance. Although industrial relationship embeddedness will promote the improvement of disruptive innovation performance, its structural embeddedness will bring negative effects. Second, in terms of mediating effect, policy-oriented support will promote the relationship between network embeddedness and disruptive innovation performance at the enterprise and industry levels. Compared with large enterprises, small- and medium-sized enterprises will have more advantages in the performance of multi-level network embedding and disruptive innovation performance. Under the subjective performance measurement method, the promotion effect of multi-level network embedding is more prominent.

This study enriches the theoretical research of network embeddedness and disruptive innovation and provides management enlightenment for the network embeddedness strategy of enterprise disruptive innovation. Limited by data samples and article length, future research can further expand literature samples to test the stability of variable relationships and test the moderating effects of more internal and external factors.

First, it constructs a theoretical analysis model of “point-line-surface” multi-level network embedding and disruptive innovation performance of enterprises and expands the theoretical analysis framework of network embedding and disruptive innovation performance. The second is to explore the influence mechanism of multi-level network embeddedness and enterprise disruptive innovation performance. Third, it deepens the theoretical understanding of the moderating variables of the impact of network embeddedness and enterprise disruptive innovation performance.

Personal thermal management by controlling the radiation energies of both the body and the sun can be used in all environments and contributes to sustainability components with the advantages of energy saving, low chemical usage and comfort enhancements under dynamic conditions. In this study, passive radiative heating nanocomposite films were produced using sodium alginate as the matrix and zinc oxide (ZnO) and aluminum oxide (Al₂O₃) nanoparticles as nanofillers having far infrared radiation reflecting, hence passive heating functions.

Nanocomposite film solutions were prepared by stirring sodium alginate powder, deionized water, ZnO and Al₂O₃ nanoparticles (20% wt of matrix polymer) with surfactant using magnetic and ultrasonic stirrers in turn. Films produced within Petri dishes after drying at room temperature were analyzed by FT-IR, UV-VIS-NIR spectroscopy and SEM for chemical, radiation management and morphological characteristics, respectively. Emissivity values giving idea about the heating performances of the films were determined with an IR camera and a hotplate system. Moreover, direct heating performances were measured by the hotplate system including a far-infrared lamp.

Results showed that the emissivity of the films increased by approximately 18% and 16% with ZnO and Al₂O₃ nanoparticles, respectively. Moreover, NaAlg–Al₂O₃ nanocomposite film exhibited passive radiative heating performance of 3.58 °C, higher than the heating performance of NaAlg–ZnO nanocomposite film which is 2.97 °C when compared to the reference NaAlg film. These results indicate that both NaAlg–ZnO and especially NaAlg–Al₂O₃ nanocomposite films have excellent far-infrared emission and absorption properties ensuring a significant heating effect.

In addition to other clothing types, the heating performance obtained with the produced nanocomposite structures may be applied to different types of cosmetic/medical applications (beauty mask, wound dresses, etc.) enabling skincare/healing with the advantage of the sodium alginate matrix.

In the context of constructing an integrated national strategic system, collaborative innovation among enterprises is the current social focus. Therefore, in order to find the interest relationship between multiple game subjects, to explore the influencing factors of collaborative innovation of civil-military integration enterprises. This paper constructs a collaborative innovation mechanism for military–civilian integration involving four game subjects (military enterprises, private enterprises, local governments, and science and technology intermediaries). It aims to solve and reveal the evolutionary game relationship among the four parties.

To explore the mechanism of military–civilian collaborative innovation involving four players, this study employs game theory and constructs an evolutionary game model for collaborative innovation with the participation of military enterprises, civilian enterprises, local governments, and technology intermediaries. The model reveals the evolutionary game patterns among these four entities, analyzes the impact of various parameters on the evolutionary process of the game system, and numerical simulation is used to show these changes more specifically.

The research findings demonstrate that active government subsidies promote cooperation throughout the system. Moreover, increasing the input-output ratio of research and development (R&D), the rate of technological spillovers, and the R&D investment of civilian enterprises all facilitate the tendency toward cooperation within the system. However, when the government chooses to actively provide subsidies, increasing R&D investment in military enterprises may hinder the tendency toward cooperation. Furthermore, central transfer payments, government punishment from the central government, and an increase in the information conversion rate of technology intermediaries may suppress the rate of cooperation within the system.

Most of the previous studies on the collaborative innovation of military–civilian integration have been tripartite game models between military enterprises, private enterprises, and local governments. In contrast, this study adds science and technology intermediaries on this basis, reveals the evolution mechanism of collaborative innovation of civil-military integration enterprises from the perspective of four-party participation, and analyzes the factors influencing the cooperation of the whole system. The conclusion of this study not only enriches the collaborative innovation evolution mechanism of military–civilian integration enterprises from the perspective of multiple agents but also provides practical guidance for the innovation-driven development of military–civilian integration enterprises.