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This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

This study investigates the impact of cultural distance on foreign box office performance of East Asian cinematic production in European markets. Predicated on two dimensions of a film's cultural specificity, namely content- and aesthetics-based components, this research advances current knowledge on the moderating effects of cultural specificity.

The authors compile a data set of 515 East Asian films released in European countries during the 2010–2018 period. Data are analyzed by hierarchical linear modeling.

Results show that cultural distance plays a negative role in affecting foreign box office performance and that aesthetics specificity of films weakens such a relationship, while content specificity of films can further strengthen the relationship.

The findings suggest that cultural specificity is a crucial element and a relevant marketing tool in the cross-country film trade. Film producers and distributors need to consider both distribution strategy and intercultural context in order to align effectively with differing cultural distance and specificity.

This study proposes a new categorization framework of cultural specificity and demonstrates the moderating roles of content and aesthetics specificity on the relationship between cultural distance and films' foreign box office performance. It offers implications for both theory and practice in global film marketing and trade.

The alignment precision of existing methods is limited by the precision of detecting element and worker’s experience, which the parallelism between ball screw and guide way is not guaranteed effectively. Thus, this paper aims to propose a method of detecting ball screw’s alignment error (BSAE) via monitoring the average vibration magnitude induced by rotational frequency of ball screw (VMRFBS).

In this study, the ball screw is simplified as a freely supported beam. A mathematical model of the effect of BSAE on the contact angle of the ball and screw is established. The change of contact angle has effect on the deformation and contact stiffness according to the Hertz contact theory. To improve the accuracy of the experimental results, the VMRFBS are analyzed by using average method, and the average values of the VMRFBS at different BSAEs are calculated by using the least squares method.

The experimental results show that the average VMRFBS increases with the increasing of BSAE under the BSAE from 0 to 0.2 mm, while the other conditions are unchanged.

This method provides an approach to monitor the BSAE and improve the alignment accuracy of machine tools and automation equipment, which has a certain guide for improving the alignment accuracy of ball screw.

With the rapid growth of the gig economy worldwide, gig workers’ perceived algorithmic control has been proven to have a crucial impact on the service performance, well-being and mental health of gig workers. However, the literature suggests that gig workers’ perceived algorithmic control may be a double-edged sword. The purpose of this research is to explore how the perceived algorithmic control of gig workers can accelerate thriving at work.

Based on the model of proactive motivation and work design literature, a three-wave survey was employed, yielding 281 completed responses. The structural equation modeling method was used to test the theoretical hypothesis.

The results indicate that gig workers’ perceived algorithmic control has positive and indirect effects on thriving at work through the mediating role of job crafting. In addition, job autonomy can moderate the mediated relationship; specifically, when job autonomy is high, this mediated relationship will be stronger.

The health and well-being of gig workers is a concern around the world. The findings provide insights for service platform enterprises and gig workers.

Perceived algorithmic control is critical to mental health and positive work experiences during a gig worker’s service process. However, the current literature focuses more on the negative aspects of algorithmic control. This paper provides a comprehensive research agenda for how to accelerate thriving at work for gig workers.

To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private capital's participation.

The new model is proposed by identifying the types of options private capital has in the OCR project, selecting the option model most suitable for private capital investment decisions, improving the valuation model through the triangular fuzzy numbers to take into account the uncertainty and flexibility, and demonstrating the feasibility of the calculation model through an actual OCR project case.

The new model can valuate OCR projects more accurately based on considering uncertainty and flexibility, compared with conventional methods that often underestimate the value of OCR projects.

The investment-income of OCR projects shall be re-valuated from the lens of real options, which could help reveal more real benefits beyond the capital growth of OCR projects, enable the government to attract private capital's investment in OCR, and alleviate government fiscal pressure.

The proposed OCR-oriented investment-income valuation model systematically analyzes the applicability of real option value (ROV) to OCR projects, innovatively integrates the ROV and the net present value (NPV) as expanded net present value (ENPV), and accurately evaluate real benefits in comparison with existing models. Furthermore, the newly proposed model holds the potential to be transferred to various social welfare projects as a tool to attract private capital's participation.

The purpose of this study is to examine the mediating role of career adaptability (CA) in the relationship between supervisor support (SS) and career satisfaction (CS).

Data were collected from 193 full-time employees working in private health-care institutions in Ankara, Turkey. The participants were asked to respond to a self-reported survey. Structural equation modeling was used to examine the hypothesized relationships between the research variables.

The results indicated that SS has a significant and positive effect on CS. It further reveals that CA mediates the effect of SS on CS.

As this study had a cross-sectional research design, causality could not be established between study variables.

CA ought to be considered by the managers and it ought to be advanced as it provides the employees fundamental instruments to deal with their career advancement efficiently.

The present study adds to the existing literature by providing additional evidence for the relationship among SS, CA and CS by examining a sample of health-care professionals.

Drawing on the self-cognitive theory, this study aims to propose a conceptual model that links customer mistreatment with different types of helping behaviors through the self-efficacy mechanism.

The empirical analysis made use of the original data of three hotels located in southern China. The authors tested the hypotheses with a three-wave survey of a sample of 430 frontline workers in 95 groups.

Customer mistreatment may reduce employees’ self-efficacy, which has both positive and negative effects depending on the type of helping. Moreover, the coworkers’ supporting climate buffered the influence of self-efficacy on autonomous and dependent helping.

The authors resolve the ambiguity surrounding customer mistreatment-helping and self-efficacy-helping relations. Thus, the authors extend the knowledge on the influence of customer mistreatment and self-efficacy on helping behaviors by establishing that both positive and negative effects may exist depending on the type of helping. Moreover, this study identifies the predictive role of self-efficacy in autonomous and dependent helping.

The authors develop a framework to build an early warning mechanism in detecting financial deterioration of Chinese companies. Many studies in the financial distress and bankruptcy prediction literature rarely do they examine the impact of pre-processing financial indicators on the prediction performance. The purpose of this paper is to address this shortcoming.

The proposed framework is evaluated by using both original and discretized data, and a least absolute shrinkage and selection operator (LASSO) selection technique for choosing an appropriate subset of financial ratios for improved predictive performance. The financial ratios are then analyzed by five different data mining techniques. Managerial insights, using data from Chinese companies, are revealed by the methodology employed.

The prediction accuracy increases after we discretized the continuous variables of financial ratios. A better prediction performance can be achieved by including fewer, but relatively more significant variables. Random forest has the highest overall performance following closely by SVM and neural network.

The contribution of this study is fourfold. First, the authors add to the literature on defaults by showing variable discretization to be an essential pre-processing step to improve the prediction performance for classification problems. Second, the authors demonstrate that machine learning approaches can achieve better performance than traditional statistical methods in classification tasks. Third, the authors provide the evidence for the adoption of C5.0 over other methods because rules generated with C5.0 provide managerial insights for managers. Finally, the authors demonstrate the effectiveness of the LASSO technique for identifying the most important financial ratios from each category, enabling one to build better predictive models.

A low-level controller is critical to the overall performance of multirotor unmanned aerial vehicles. The purpose of this paper is to propose a nonlinear low-level angular velocity controller for multirotor unmanned aerial vehicles in various operating conditions (e.g. different speed and different mode).

To tackle the above challenge, the authors have designed a nonlinear low-level controller taking the actuator dynamics into account. The authors first build the actuator subsystem by combining the actuator dynamics with the angular velocity dynamics model. Then, a recursive low-level controller is developed by designing a high-gain observer to estimate unmeasurable states. Furthermore, a detailed stability analysis is given with the Lyapunov theory.

Simulation tests and real-world flying experiments are provided to validate the proposed approach. In particular, we illustrate the performance of the proposed controller using violent random command test, attitude mode flight and high-speed flight of up to 18.7 m/s in real world. Compared with the classical method used in PX4 autopilot and the estimation-based incremental nonlinear dynamic inversion method, experimental results show that the proposed method can further reduce the control error.

Low-level control of multirotor UAVs is challenging due to the complex dynamic characteristics of UAVs and the diversity of tasks. Although some progress has been made, the performance of existing methods will deteriorate as operating conditions change due to the disregard for the electromechanical characteristics of the actuator.

To solve the low-level angular velocity control problem in various operating conditions of multirotor UAVs, this paper proposes a nonlinear low-level angular velocity controller which takes the actuator dynamics into account.

The purpose of this study is to explore how government subsidies influence technology innovation in new-energy enterprises in the new era of Industry 4.0. Specifically, this study investigates the mediating effect of digital transformation and the moderating effect of a top management team (TMT) with digital experience.

Using a sample of 225 listed new-energy companies, with annual information, patent data, and financial data for the years 2010–2020, this study employs panel fixed effect regression models to obtain the results.

This study finds strong evidence that government subsidies promote the technology innovation of new-energy enterprises, and digital transformation partially mediates the effect of government subsidies on technology innovation. In addition, a TMT's digital experience moderates the effect of government subsidies on digital transformation, but has no significant moderating effect on the relationship between digital transformation and technology innovation. Further analysis shows that subsidies make a sustained contribution to both digital transformation and technological innovation over the next two years. The digital subsidies have a stronger role in promoting digital transformation and further technological innovation through digital transformation.

The Chinese government needs to continue to intermittently increase subsidies for new-energy enterprises, and focus on guiding enterprises' digital transformation. Chinese new-energy enterprises should pay attention to the importance of having TMTs with digital experience, make full use of government subsidies, actively implement digital transformation, and improve their innovation levels.

A new conceptual framework is proposed to examine the relationships between government subsidies, digital transformation, a TMT's digital experience, and technology innovation. This paper provides an important theoretical basis and practical reference for improving the technology innovation ability of Chinese new-energy enterprises, and the high-quality development of renewable energy in the context of Industry 4.0.