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This paper aims to investigate weight-climbing assistance strategy for the biomechanical design of passive knee-assisting exoskeleton (PKAExo) and evaluate a designed PKAExo which stores energy when the knee joint flexes and releases the energy to assist ascending when the knee joint extends.

The authors constructed theoretic modeling of human weight-climbing to analyze characteristics of knee angle and moment. They then conducted camera-based movement analysis, muscle strength and endurance tests and surface electromyography (sEMG) measures to verify the relationship of knee angle and moment with both stair height and load weight. Afterwards, the authors proposed an assistant strategy for passive knee assistance, then gave out designed PKAExo and conducted mechanical experiment to test the knee-assisting torque. Finally, the authors conducted comparison experiment based on measuring the sEMG signals of knee extensor to verify the assistance effect of the PKAExo for weight-climbing.

The knee extensor produces the maximum force during weight-climbing, and the muscle force provided by knee extensor has significant increasing rate along with the stair height. Thus, the assistance torque of PKAExo is designed to increase nonlinearly along with increasing knee angle. It stores energy when knee flexes and assists when knee extends. Both the mechanical experiment and comparison experiment have demonstrated that the PKAExo is able to provide nonlinear assistance torque for weight-climbing, thus decreasing the average maximum load of knee extensor by about 21 per cent, reducing muscle fatigue and enhancing wearer’s weight-climbing ability.

The authors construct theoretic maximum force model produced by knee extensor for weight-climbing in static situation and conduct a series of experiments to verify and revise the model, which is the fundamental reference for knee-assisting mechanism designed for weight-climbing. The authors have also provided and validated an assistant strategy and the mechanism based on the biomechanical analysis, which aims to translate wearer’s energy-providing mode form high load to mid-low load by storing energy when knee flexes and assisting when knee extends. The PKAExo decreases the maximum load of knee extensor, reduces muscle fatigue and helps people to easily climb with load.

There is intense competition and increasing globalisation in financial markets. Bank management must develop customer‐oriented strategies in order to compete successfully in the competitive retail banking environment. The longer a bank can retain a customer, the greater revenue and cost savings from that customer. China's accession to the World Trade Organisation (WTO) has resulted in the liberalisation and deregulation of China's financial services market. Chinese customers now have greater choices between domestic and foreign banks. This study aims to identify and analyse the factors that influence bank customers' switching behaviour in the Chinese retail banking industry.

The data for this analysis was obtained using a convenience sample of 421 bank customers in Jiaozuo City, Henan Province, China. The decision to switch banks is hypothesised to be a function of price, reputation, service quality, effective advertising competition, involuntary switching, distance, switching costs, distance, and demographic characteristics. Factor analysis and logistic regression are used to analyse the data and identify and rank the factors that impact on the bank switching behaviour of customers.

The research findings reveal that price, reputation, service quality, effective advertising, involuntary switching, distance, and switching costs impact on customers' bank switching behaviour. The findings also reveal that the young and high‐income groups are more likely to switch banks.

The results of this research allow service marketers and practitioners to develop and implement service marketing strategies to decrease customer defection rates, and in turn, increase bank profits. Furthermore, this research provides useful information for future researchers investigating customer switching behaviour in the retail banking industry.

This paper provides an empirical analysis of Chinese bank switching behaviour and provides a framework for future studies on the behaviour of bank customers.

An electrochemical method based on the open circuit potential (OCP) fluctuations was put forward. It can be used to optimize the alloy compositions for improving the corrosion resistance of rust layer.

The potential trends and potential fluctuations of carbon steels in seawater were separated by Hodrick–Prescott filter. The Spearman correlation coefficient and max information coefficient were used to explore the correlation of alloy compositions and potential fluctuations.

After long-term immersion, potential fluctuation resistance (PFR) can be used to characterize the corrosion resistance of metals and its rust layers. In the 1,500 to 2,500 h exposure period, Fe, C and S compositions have strong negative correlations, whereas PFR and P composition have weak negative correlations. Mn, Cu and Ti alloy compositions help the rust layer of carbon steels have higher PFRs. These elements that exhibit higher PFRs in this period have been confirmed to have the effect on improving the corrosion resistance of rust layer.

A new computing method for alloy composition optimization of carbon steels based on the OCP fluctuations was put forward. This method combines electrochemical monitoring with the long-term actual seawater environmental tests of various carbon steels.

This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.

This paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.

Results of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.

Corrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.

The purpose of this study aims to modify a self-mixing laser mouse as an extremely cost-effective displacement sensor to measure the mechanical oscillation of a commercial shaker and a nano-positioning stage.

This kind of laser mouse, mostly consisting of a pair of vertical cavity surface emitting lasers, two photodiodes and an integrated signal processing unit, is capable of directly giving the x-axis and y-axis components of the measured vibrating displacement. Based on the laser self-mixing interference, the velocity of the object is coded into the Doppler frequency shift of the feedback light, which allows accurate determination of the vibration of the object.

A commercial shaker has been used to provide standard harmonic oscillation to test the displacement sensor. Within a vibrating frequency range of 110 Hz, the experimental results show that the micrometer scale resolution has been achieved at the velocity of up to 2 m/s, which is much improved compared with the image-based optical mouse. Furthermore, the measurements of the two dimensional displacement of a nano-positioning stage are performed as well. The minimum measurable velocity limit for this sensor has been discussed in detail, and the relative measurement error can be greatly reduced by appropriate selection of the modulation frequency of the triangular injection current.

These results demonstrate the feasibility of this device for the industrial vibration sensing applications.

The purpose of this paper is to empirically explore the mechanisms through which Chinese National Science Parks' (NSPs) services facilitate returnee entrepreneurs' (REs) acquisition of resources for their new ventures. Resource acquisition is crucial for new ventures, but it inevitably leads to significant costs increase. Although the NSPs offer various services to REs to reduce these costs, they still struggle to find the right mix of services.

From the transaction cost's perspective, an exploratory multiple-case study was conducted with data collected from six NSPs in China.

The results reveal that four types of NSP services (mentoring and training, social event, promotion of REs and accreditation of resource holders (RHs)) have both individual and joint effects on reducing REs' resource acquisition costs. Specifically, the “accreditation of RHs” service directly helps REs reduce search costs. The combination of “accreditation of RHs”, “promotion of REs” and “social event” services help REs and RHs to establish guanxi. Further, guanxi, working along with the “mentoring and training” service, helps REs to reduce contracting, monitoring and enforcement costs.

This study is among the first to explore the matching mechanisms between science parks’ services and entrepreneurs' cost reduction. This helps reconcile the inconsistent findings on science parks' effect by explaining why some NSPs are able to provide strong support to REs while others are less successful. In addition, the findings are useful for NSPs to develop the right mix of tailored services for REs. Finally, REs will find this study useful to evaluate which NSP is a more suitable location for their new ventures.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

The purpose of this study is to construct a scale that is contextually suitable for measuring early childhood leadership in China.

Following a standard scale development procedure, both qualitative and quantitative research approaches were addressed. Qualitative data was collected from 21 semistructured interviews with formal and informal teacher leaders in Xiamen City, China. Using survey data of 120 respondents and 305 respondents, an exploratory factor analysis was conducted twice to determine the underlying factorial structure of the scale. A further sample of 317 respondents were used to test the latent structure and validity of the scale using confirmatory factor analysis.

Based on the results from reliability and validity tests, this study indicates that the scale demonstrates sound psychometric properties. A three-factor model was determined, including staff management and development, peer learning and support and communication with parents.

The scale is the first of its kind for measuring early childhood leadership in China.

This study aims to apply the elaboration likelihood model to explore when, how and why robotic services increase customer engagement.

A field survey and two experiments were conducted to examine the proposed theoretical framework.

The robots’ proactive behavior encouraged customers to trust and engage with them. The influence of this behavior on customer engagement increased for highly interaction-oriented customers or when the reputations of companies were poor.

The findings can inform the efficient management of customer–robot interactions and thus support firms’ relationship marketing objectives.

The literature on robotic services has recognized that robots should be proactive to ensure positive customer experiences, but few studies have explored the relational outcomes of proactive robotic services. The authors’ in-depth empirical examination thus extends research into the role these services can play in fostering customer engagement.

The purpose of this study is to examine the effects of executives’ overseas education and work experience on enterprise digital as executives’ overseas background is critical to the development of enterprises. It also explored the mediating role of enterprise digital transformation on the relationship between executives’ overseas background and enterprise growth.

Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges for the period 2018–2020 were analyzed using regression analysis and bootstrapping to verify hypothesized relationships.

Executives’ overseas study and work experience both enhanced enterprise digital transformation significantly, thus improving enterprise growth. The level of employee education moderated the mediating role proposed in the theoretical model. Moreover, the promoting effect of executives’ overseas background on enterprise digital transformation was more significant for non-state-owned enterprises and those in eastern China.

The findings provide reference for the formulation and optimization of companies’ human resource structure and have implications on the improvement of enterprise digital transformation and enterprise growth.

This study explored the factors influencing enterprise digital transformation at the microlevel of corporate human capital, thereby providing microlevel empirical evidence for research on the factors influencing enterprise digital transformation. Its findings shed light on the mechanism and context under which executives with overseas backgrounds may enhance enterprise digital transformation and growth.