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Key core technology is the most important weapon of the country, and breaking through the “strangled” problem is one of the real problems that China’s emerging industries and enterprises must solve. Accurately identifying the “strangled” problem will help China accelerate the realization of high-level scientific and technological self-reliance and win the battle against key core technologies.

Combined with the characteristics of key core technologies, the key core technology evaluation system was constructed from four dimensions: technology innovation, technology radiation, technology economy and technology safety. We adopt the entropy TOPSIS method to evaluate the patents, and the patents with the top 5% scores are identified as key core technology patents. Then, this study identifies key core technology “strangled” problems in three dimensions: technology value advantage, competitive advantage and quantitative advantage.

Taking the patent data of the global new generation information technology industry from 2011 to 2023 as a sample, 178 moderately “strangled” technologies and 49 severely “strangled” technologies are selected. The study results are consistent with the current situation of the new generation information technology industry’s development, and verify the feasibility and reliability of the key core technology “strangled” problem identification model.

This study uses patent data to identify key core technologies and “Strangled” in the new generation information technology industry. It can provide a reference for relevant national departments and agencies, as well as universities and enterprises.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

To solve the problem that the traditional received signal strength indicator real-time location method does not test the attenuation characteristics of the electromagnetic wave transmission in the location area, which cannot guarantee the accuracy of the location, resulting in a large location error.

At present, the compressed sensing (CS) reconstruction algorithm can be roughly divided into the following two categories (Zhouzhou and Fubao, 2014; Lagunas et al., 2016): one is the greedy iterative algorithm proposed for combinatorial optimization problems, which includes matching pursuit algorithm (MP), positive cross matching tracking algorithm (OMP), greedy matching tracking algorithm, segmented orthogonal matching tracking algorithm (StOMP) and so on. The second kind is the convex optimization algorithm, which also called the optimization approximation method. The common method is the basic tracking algorithm, which uses the norm instead of the norm to solve the optimization problem. In this paper, based on the piecewise orthogonal MP algorithm, the improved StOMP reconstruction algorithm is obtained.

In this paper, the MP algorithm (OMP), the StOMP and the improved StOMP algorithm are used as simulation reconstruction algorithms to achieve the comparison of location performance. It can be seen that the estimated position of the target is very close to the original position of the target. It is concluded that the CS grid-based target stepwise location method in underground tunnel can accurately locate the target in such specific region.

In this paper, the offline fingerprint database in offline phase of location method is established and the measurement of the electromagnetic noise distribution in different localization areas is considered. Furthermore, the offline phase shares the work of the location process, which greatly reduces the algorithm complexity of the online phase location process and the power consumption of the reference node, meanwhile is easy to implement under the same conditions, as well as conforms to the location environment.

To understand the thermal insulation of four common structures of sleeping bags and factors influencing the thermal insulation as well as the thermal comfort of people who use four kinds of sleeping bag structures.

Four samples corresponding to four common sleeping bag structures were made and their thermal properties were investigated through a combination of objective instrument measurement and subjective human subject tests.

The porosity of the samples and the length of the interlining had a main impact on the thermal resistances of the four sleeping bag structures. The thermal sensation ratings and the thermal resistances had good consistency. There was a strong correlation between human physiological parameters and thermal sensation evaluation. The male and female have significant differences in thermal sensation of different structures of sleeping bags.

Instrument measurement and human subject tests were combined to study the thermal properties of sleeping bag structures, which had little attention in the past in research fields.

Cotton is one of the most common nature textile fiber that is widely used in clothing, bedding and decorative fields due to its comfort. However, the cellulosic cotton fiber has its own drawbacks. Cotton fiber belongs to flammable material with the limiting oxygen index (LOI) value about 18% that restricts its applications. Cotton fiber is easy to crease during the repeat wearing and laundering process that will influence the wearability. Therefore, it is very important to improve the flame retardancy and anticrease performance of cotton fabric.

In this study, flame retardant and anticrease multifunctional modifications of cotton fabric were conducted by one-step pad–dry–cure process using eco-friendly phytic acid and 1, 2, 3, 4-butanetetracarboxylic acid.

The results of limited oxygen index (LOI) values and vertical burning test indicate that the flame retardancy of modified cotton fabric was greatly improved. The LOI value of modified cotton fabric reached 30.8% when the usage of phytic acid was 12%. The crease recovery angle was over 250° of the modified cotton fabric revealing good anticrease performance.

This research provides a novel feasible cost-effective one-step method for the multifunctional modified cellulosic fiber using eco-friendly chemical agents.

The application of digital twins to optimise operations and supply chain management functions is a bourgeoning practice. Scholars have attempted to keep pace with this development initiating a fast-evolving research agenda. The purpose of this paper is to take stock of the emerging research stream identifying trends and capture the value potential of digital twins to the field of operations and supply chain management.

In this work we employ a bibliometric literature review supported by bibliographic coupling and keyword co-occurrence network analysis to examine current trends in the research field regarding the value-added potential of digital twin in operations and supply chain management.

The main findings of this work are the identification of four value clusters and one enabler cluster. Value clusters are comprised of articles that describe how the application of digital twin can enhance supply chain activities at the level of business processes as well as the level of supply chain capabilities. Value clusters of production flow management and product development operate at the business processes level and are maturing communities. The supply chain resilience and risk management value cluster operates at the capability level, it is just emerging, and is positioned at the periphery of the main network.

This is the first study that attempts to conceptualise digital twin as a dynamic capability and employs bibliometric and network analysis on the research stream of digital twin in operations and supply chain management to capture evolutionary trends, literature communities and value-creation dynamics in a digital-twin-enabled supply chain.

The purpose of this paper is to contextually theorise the different patterns of emerging multinational companies’ (EMNCs’) learning processes for innovation and the different influences of their technology-driven FDIs (TFDIs) on the processes.

A comparative case study method and process tracing technique are employed to investigate how and why firms’ learning processes for innovation took place, how and why the TFDIs emerged and influenced the firms’ learning processes in different ways.

The paper identifies two different patterns of learning process for innovation (Glider model vs Helicopter model) and two different roles of the case firms’ TFDIs (accelerator vs starter) in the different contexts of their learning processes. It is found that the capability building of the domestic wind energy industry has an important influence on the case of EMNCs’ learning processes and thus on the roles of their TFDIs.

The limitation of the paper lies in its small number of cases in a specific industry of a specific country. The two contextually identified learning models and roles of TFDIs may not be applied to other industries or other countries. Future research should investigate more cases in broader sectoral and geographic scope to test the models and also to identify new models.

For EMNCs, who wants to use the Helicopter model to rapidly gain production and innovation capability, cross-cultural management and integration management are crucial to practitioners. For emerging countries with ambitions to explore the global knowledge and technology pool, besides of the EMNC’s capability building, the capability building in the domestic industries should not be overlooked by policy makers.

The paper develops a dynamic and contextual analytical framework which helps to answer the important questions about how and under what context a TFDI emerges and influences firm’s learning process for innovation. It theorises the EMNCs’ learning process and TFDIs in the context of the development of the domestic industry. It strengthens the explanatory power of the learning-based view and adds new knowledge to the current FSA/CSA discourse in the international business literature.