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The purpose of this paper is to solve the problem that mobile robots are still based on reactive collision avoidance in unknown dynamic environments leading to a lack of interaction with obstacles and limiting the comprehensive performance of mobile robots. A dynamic window approach with multiple interaction strategies (DWA-MIS) is proposed to solve this problem.

The algorithm firstly classifies the moving obstacle movement intention, based on which a rule function is designed to incorporate positive incentives to motivate the robot to make correct avoidance actions. Then, the evaluation mechanism is improved by considering the time cost and future information of the environment to increase the motion states. Finally, the optimal objective function is designed based on genetic algorithm to adapt to different environments with time-varying multiparameter optimization.

Faced with obstacles in different states, the mobile robot can choose a suitable interaction strategy, which solves the limitations of the original DWA evaluation function and avoids the defects of reactive collision avoidance. Simulation results show that the algorithm can efficiently adapt to unknown dynamic environments, has less path length and iterations and has a high comprehensive performance.

A DWA-MIS is proposed, which increases the interaction capability between mobile robots and obstacles by improving the evaluation function mechanism and broadens the navigation strategy of DWA at a lower computational cost. After real machine verification, the algorithm has a high comprehensive performance based on real environment and provides a new idea for local path planning methods.

In recent years, with the steady growth of China’s economy and world’s vacation market, and powered by the growing and significant large demands of Chinese overseas travel, an emergent trend of international development by major Chinese tourism groups has attracted notice by scholars and practitioners and this is obvious especially in the private sector. With this as the background, this paper aims to explore how China’s leading tourism companies expand their business internationally through a case study approach.

Recently, the concept of financial technology (FinTech) has attracted extensive attention from international organisations and regulators, in particular, how to achieve a “win–win” situation between financial institutions' FinTech innovation and effective regulation has become a hot topic. This study purposes to explore the evolutionary game relationship between FinTech innovation and regulation by constructing both static and dynamic earmarking game models.

A simulation experiment was conducted using primary data obtained from a commercial bank in China.

The results of the theoretical analysis of evolutionary game models were consistent with the corresponding simulation results, proving the validity of the proposed evolutionary game models. It was also found that the dynamic earmarking game model was more stable and effective than the static earmarking game model in promoting FinTech innovation and regulation. Furthermore, when the regulators utilised a dynamic earmarking mechanism, the evolutionary path of financial institutions and regulators' behaviour strategies took the shape of a spiral and eventually converged to a central point, indicating the existence of an evolutionary stable strategy and Nash equilibrium. Finally, because the behaviour strategies of financial institutions were mainly influenced by the regulators' policies, the regulators were inspired to adjust the corresponding regulation policies on FinTech innovation.

This study bridges the knowledge gap in the existing literature on financial innovation and regulation, in particular by establishing evolutionary game models from the perspective of financial earmarking policies. Also, the case study for simulation experiments can gain a more intuitive insight into FinTech innovation and financial earmarking policies.

The rapid growth of emerging market firms (EMFs) has been a topic of interest for the past two decades, especially in China. However, few studies have discussed how and why EMFs can impel the upgrading of their capabilities to quickly win competitive advantages in the global market. In this context, the purpose of this paper is to unravel the implausible upgrading phenomenon from the perspective of technological proximity.

This paper adopts a single case study, specifically that of a leading Chinese e-bike firm, with a special focus on the dynamic nature of the capability upgrading process and underlying mechanisms.

The results show that taking advantage of technological proximity is an important way for EMFs to climb the ladder of capability upgrading. The stage-based process reveals how capability upgrading is achieved through elaborate actions related to technological proximity. Furthermore, this study finds three learning mechanisms behind the technological proximity, which enable firms to successfully upgrade to higher levels of capabilities. In particular, the trigger role played by contextual conditions in guiding firms' capability upgrading is highlighted and characterized.

This study enriches traditional capability upgrading literature from a technological proximity perspective, especially the traditional static upgrading research related to EMFs. The authors also contribute to the conceptualization of technological proximity. However, the research setting is China's e-bike industry; therefore, the study's generalizability to other emerging markets and industries may be limited.

The results show that it is important to recognize the value of the transfer and sharing of technology between proximal industries for local governments. Also, appropriate policies should be developed to break down the technology barriers between these industries. Moreover, rather than catching up with the superior technologies of multinational corporations in advanced countries, focusing on products with high technological proximity in local or regional areas may be more helpful for EMFs' upgrading.

This paper investigates the capability upgrading process and mechanisms in EMFs, particularly with respect to the role played by technological proximity.

The purpose of this paper is to explore the features of health misinformation on social media sites (SMSs). The primary goal of the study is to investigate the salient features of health misinformation and to develop a tool of features to help users and social media companies identify health misinformation.

Empirical data include 1,168 pieces of health information that were collected from WeChat, a dominant SMS in China, and the obtained data were analyzed through a process of open coding, axial coding and selective coding. Then chi-square test and analysis of variance (ANOVA) were adopted to identify salient features of health misinformation.

The findings show that the features of health misinformation on SMSs involve surface features, semantic features and source features, and there are significant differences in the features of health misinformation between different topics. In addition, the list of features was developed to identify health misinformation on SMSs.

This study raises awareness of the key features of health misinformation on SMSs. It develops a list of features to help users distinguish health misinformation as well as help social media companies filter health misinformation.

Theoretically, this study contributes to the academic discourse on health misinformation on SMSs by exploring the features of health misinformation. Methodologically, the paper serves to enrich the literature around health misinformation and SMSs that have hitherto mostly drawn data from health websites.

In the face of fierce international competition for those participating in global value chains (GVCs), upgrading has been a central concern of emerging market firms (EMFs) that are trying to occupy higher value-added positions. However, although the innovation capabilities (ICs) have been generally considered critical to upgrading in GVCs, few studies have examined how IC is built up and then applied to the EMF upgrading process over time. To this end, the purpose of this paper is to investigate why and how EMFs can upgrade in GVCs through the development of their IC.

This paper adopts a multiple-case study of three supplier firms in China and their IC development processes, with a special focus on the nature of the firm-level upgrading in GVCs.

The results generate a process model of EMFs upgrading with respect to the development of IC. The model reveals how IC is built up through the firms' underlying systematic innovation activities, which enable firms to successfully upgrade within GVCs. In particular, the role played by contextual vulnerability in guiding firms to develop the appropriate IC, and the corresponding upgrading, is highlighted.

This study contributes to the micro-foundation in GVCs literature, especially the traditional static upgrading research of EMFs. The authors also contribute to existing IC development research. Meanwhile, the study focuses on the upgrading of three Chinese firms in the phone and LED industries. The generalizability to other emerging markets and industries may therefore be limited.

The study results show that EMFs could initially develop endogenous IC that focuses on process innovation as a means to establish a foundation for further upgrading. In addition, firms need to improve their ability to accurately sense contextual changes. As such, it would be valuable to understand their positions and characteristics within GVCs.

This paper investigates a process model of upgrading in GVCs through IC development in EMFs. This study also adds a dynamic micro-foundation to existing, rather macro and static GVCs studies.

Vehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.

This paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.

Experiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.

To reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.

This paper aims to optimize the weighing control system and compensate weighing error for weighing control system of coal mine paste-filling weighing control system.

The process of the paste-filling weighing control system is analyzed and the mathematical model of the paste-filling material weight is established. Then, the back-propagation (BP) neural network is used to optimize the control system and compensate the weighing error.

Without the BP neural network, the weighing error of the paste-filling control system is more than 3 per cent, whereas after optimization with the BP neural network, the weighing error is less than 1 per cent. With the simulation results, it is seen that the weighing error of the paste-filling control system decreases and the accuracy of the weighing control system improves and optimizes.

The method can be further used to improve the control precision of the coal mine paste-filling system.

The purpose of the study is to explore how technological capability and exogenous pressure interactively influence business model (BM) dynamics over time in new technology-based ventures.

The study adopts a longitudinal case study of the BM innovations of a Chinese financial technology venture. The structural approach and temporal bracket are used to analyze and theorize the data.

The findings indicate that distinct contextual changes impel a firm to refine or abandon existing BMs over time. In different stages, the antecedents interactively influence BM dynamics with three successive patterns, namely pressure dominance, parallel influence and hybrid influence. While both antecedents trigger changes during the initiation and implementation of new BMs, they also serve as the filter and the enabler, respectively, during the ideation and integration of BMs.

The study inductively develops three propositions regarding the relationship between BM dynamics and its antecedents, which is based on the data collected from one single firm. Future research should test the propositions in other domains and take more cross-level antecedents into consideration.

The study contributes to the nascent research stream of BM dynamics by offering in-depth insights into the interaction of internal and external antecedents and by linking the differentiated roles of antecedents to the BM innovation process. The research offers some practical implications for new technology-based ventures seeking to develop BMs in a fast-changing environment.

This paper aims to clarify the size and morphology of transition metal dichalcogenides has an impact on lubrication performance of Cu-based composites. This study is intended to show that Cu-based electrical contact materials containing Nb_0.91Ti0.09Se₂ have better electrical and tribological properties than those containing NbSe₂. The tribological properties of Cu-based with different Ti-dopped NbSe₂ content were also discussed.

The NbSe₂ and Nb_0.91Ti_0.09Se₂ particles were fabricated by thermal solid state reaction method. The powder metallurgy technique was used to fabricate composites with varying Nb_0.91Ti_0.09Se₂ mass fraction. The phase composition of Cu-based composites was identified by X-ray diffraction, and the morphology of NbSe₂/Nb_0.91Ti_0.09Se₂ and the worn surface of composites were characterized by scanning electron microscopy and transmission electron microscopy. In addition, the tribological properties of composites were appraised using a ball-on-disk multi-functional tribometer. The data of friction coefficient and resistivity were analyzed and the corresponding conclusion was drawn.

In comparison with the pure copper, Cu-based composites containing Nb_0.91Ti_0.09Se₂/NbSe₂ had a lower friction coefficient, illustrating the Nb_0.91Ti_0.09Se₂ with nano-size particles prepared in this work is a perfect choice for the fabrication of excellent electrical contact composites. Compared to composites with NbSe₂, composites containing Nb_0.91Ti_0.09Se₂ have better tribological and electrical properties.

Because of the use of thermal solid state reaction method, the size of NbSe₂ and Nb_0.91Ti_0.09Se₂ is relatively large. Therefore, the fabrication of finer particles of Nb_0.91Ti_0.09Se₂ is encouraged.

In this paper, the authors discuss the tribological and electrical properties of Cu-based composites, and the value of optimum obtained as Nb_0.91Ti_0.09Se₂ content is 15 Wt.%.