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Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.

This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration (GCI), while investigating the moderating mechanisms of big data development and social capital.

Following hierarchical linear regression analysis, the authors examine hypothesized relationships by combining survey data from 206 Chinese manufacturers with secondary data.

The results show that relationship trust positively affects non-coercive influence strategy, while its impact on coercive influence strategy is insignificant. Non-coercive influence strategy has an inverted U-shaped impact on GCI. Furthermore, big data development flattens the inverted U-shaped relationship between non-coercive influence strategy and GCI. Conversely, social capital steepens the inverted U-shaped relationship between non-coercive influence strategy and GCI.

This study sheds light on managers on how to involve customers in GCI through friendly strategies that favor the involvement of customers and the willingness to develop environmentally friendly initiatives.

Although GCI has received widespread attention, how it can be enhanced remains unclear. These findings provide novel insights into the emerging GCI literature and complement social exchange theory.

This study aims to study the formation mechanism of micro-arc oxidation (MAO) coating on AZ31 magnesium alloy and how the annealing process affects its corrosion resistance.

This study involved immersion experiments, electrochemical experiments and slow strain rate tensile experiments, along with scanning electron microscopy, optical microscopy observation and X-ray diffraction analysis.

The findings suggest that annealing treatment can refine the grain size of AZ31 magnesium alloy to an average of 6.9 µm at 300°C. The change in grain size leads to a change in conductivity, which affects the performance of MAO coatings. The MAO coating obtained by annealing the substrate at 300°C has smaller pores and porosity, resulting in better adhesion and wear resistance.

The coating acts as a barrier to prevent corrosive substances from entering the substrate. However, the smaller pores and porosity reduce the channels for the corrosive solution to pass through the coating. When the coating cracks or falls off, the corrosive medium and substrate come into direct contact. Smaller and uniform grains have better corrosion resistance.

Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

Despite the growing interest in enhancing mass customization capability (MCC), firms still have little knowledge of dealing with the superimposed challenges of increased market uncertainty and supply chain disruptions. Based on the dynamic capability view, this study focuses on the impacts of frequent sensing and reconfiguring processes on MCC and the mediating roles of proactive and reactive supply chain resilience (SCR).

We collected survey data from 277 manufacturing firms and conducted a structural equation model to test hypotheses.

The results reveal that although its direct effect on MCC is insignificant, sensing process improves MCC indirectly via reactive SCR. Our findings also show that reconfiguring process enhances MCC both directly and indirectly via reactive SCR.

This study provides theoretical and practical insights into how to combine dynamic capability and SCR to strengthen MCC.

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

Business model design (BMD) is essential for firms to interact with stakeholders and gain competitive advantages in a changeable business environment. The advances in digital technologies create plenty of opportunities for the transformation of BMD. However, the effect of digital-based BMD on firm performance and the underlying mechanisms are unclear. Based on dynamic capability theory, this paper aims to introduce a framework elaborating on how digital-based novelty- and efficiency-centered BMD impact firm performance.

To examine the hypotheses, the authors collect data from 277 Chinese manufacturing firms and use hierarchical regression analysis to process the data.

The results indicate that ambidextrous innovation partially mediates the impacts of digital-based novelty- and efficiency-centered BMD on firm performance. Interorganizational learning only strengthens the impact of digital-based efficiency-centered BMD on ambidextrous innovation.

This study reveals the impacts of two distinct digital-based BMD on firm performance and uncovers the underlying mechanisms, which enrich the BMD literature and provide a deeper understanding of B2B marketing.

Infrastructure financialization plays a critical role in infrastructure development and urban growth around the world. However, on the one hand, the existing research on the infrastructure financialization focuses on qualitative and lacks quantitative country-specific studies. On the other hand, the spatial heterogeneity and influencing factors of infrastructure financialization are ignored. This study takes China as a typical case to identify and analyze the spatial characteristics, development process and impact factors of infrastructure financialization.

To assess the development and characteristics of infrastructure financialization in China, this study constructs an evaluation index of infrastructure financialization based on the infrastructure financialization ratio (IFR). This study then analyzes the evolution process and spatial pattern of China's infrastructure financialization through the spatial analysis method. Furthermore, this study identifies and quantitatively analyzes the influencing factors of infrastructure financialization based on the spatial Dubin model. Finally, this study offers a policy suggestion as a governance response.

The results demonstrate that infrastructure financialization effectively promotes the development of infrastructure in China. Second, there are significant spatial differences in China’s infrastructure financialization. Third, many factors affect infrastructure financialization, with government participation having the greatest impact. In addition, over-financialization of infrastructure has the potential to lead to government debt risks, which is a critical challenge the Chinese Government must address. Finally, this study suggests that infrastructure financialization requires more detailed, tailored,and place-specific policy interventions by the government.

This study not only contributes to enriching the knowledge body of global financialization theory but also helps optimize infrastructure investment and financing policies in China and provides peer reference for other developing countries.

This study aims to investigate the process of developing loyalty in the Chinese mobile health community from the information seeking perspective.

A covariance-based structural equation model was developed to explore the mobile health community loyalty development process from information seeking perspective and tested with LISREL 9.30 for the 191 mobile health platform user samples.

The empirical results demonstrate that the information seeking perspective offers an interesting explanation for the mobile health community loyalty development process. All hypotheses in the proposed research model are supported except the relationship between privacy and trust. The two types of mobile health community loyalty—attitudal loyalty and behavioral loyalty are explained with 58 and 37% variance.

This paper has brought out the information seeking perspective in the loyalty formation process in mobile health community and identified several important constructs for this perspective for the loyalty formation process including information quality, communication with doctors and communication with patients.

The increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.

This study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.

The primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.

Our study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.

This study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.