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The purpose of this paper is to investigate the influence of trust and perceived risk on investment willingness considering the bidirectional relationship between trust and perceived risk in peer-to-peer (P2P) lending.

Data were collected from a leading Chinese P2P platform, PPDAI.com. In total, 328 valid responses were received and analyzed using structural equation modeling (SEM).

The results show that the influence of trust on investment willingness is significant, whereas that of perceived risk is insignificant. The results also indicate that platform reputation has a positive effect on trust, and the quality of alternatives is positively associated with perceived risk. In addition, the bidirectional perspective should be preferred to cope with the bidirectional relationship between trust and perceived risk in P2P lending.

This study extends existing research on the influence of trust and perceived risk on investment willingness from a bidirectional perspective, which has not been addressed in the P2P lending context. In addition, this research enriches the current literature about trust and perceived risk by providing more evidence that the relationship between trust and perceived risk is bidirectional and thus the bidirectional model should be preferred. For practice, the study suggests that managers can earn trust and reduce the perceived risk of lenders by continuously providing high-quality products, services and enhancing platform reputation, ultimately improving their investment willingness.

A tension leg platform (TLP) is a vertically moored, floating structure which is normally used for offshore oil/gas production. However, these types of structures can be damaged by vibration responses that are too large. The purpose of this paper is to consider the influence of the external waves on oceanic structures.

A mathematical model of an ocean environment was constructed, in which wave‐induced flow fields cause structural surge motion, then solutions to the mathematical model were analytically derived.

The Takagi‐Sugeno (T‐S) fuzzy model is employed in the approximation of the oceanic structure. The stability analysis of the TLP system is carried out using the Lyapunov direct method.

The dependence of the wave‐induced flow field and its resonant frequency on the wave characteristics and the structural properties of the platform, which include width, thickness and mass, can be drawn using a parametric approach.

Mathematical modeling is applied to find the wave‐induced displacement due to the surge motion. The vibration of the mechanical motion of the platform structure caused by wave force is also discussed.

This study aims to apply a systematic statistical approach, including several plot indexes, to diagnose the goodness of fit of a logistic regression model, and then to detect the outliers and influential observations of the data from experimental data.

The proposed statistical approach is applied to analyze some experimental data on internal solitary wave propagation.

A suitable logistic regression model in which the relationship between the response variable and the explanatory variables is found. The problem of multicollinearity is tested. It was found that certain observations would not have the problem of multicollinearity. The P‐values for both the Pearson and deviance χ² tests are greater than 0.05. However, the Pearson χ² value is larger than the degrees of freedom. This finding indicates that although this model fits the data, it has a slight overdispersion. After three outliers and influential observations (cases 11, 27, and 49) are removed from the data, and the remaining observations are refitted the goodness‐of‐fit of the revised model to the data is improved.

A comparison of the four predictive powers: R², max‐rescaled R², the Somers' D, and the concordance index c, shows that the revised model has better predictive abilities than the original model.

The goodness‐of‐fit and prediction ability of the revised logistic regression model are more appropriate than those of the original model.

This study seeks to develop a systematic means of identifying regression models using a complex regression model with a statistical method.

As a widely adopted statistical scheme for analyzing multifactor data, regression analysis provides a conceptually simple algorithm for examining functional relationships among variables. This investigation assesses the proposed relationship using a sample of data in regression analysis and then estimates the fit using statistics. Furthermore, several algorithms and added variable plots are presented to obtain an appropriate regression model and the relationship between response variables y, p and explanatory variables x₀,x₁,x₂, … ,x_p.

The proposed statistical scheme is demonstrated by the analysis of experimental data on internal waves, in which the results can well illustrate what has been investigated in laboratory experiment and may be applicable to the naturally occurring reflection of internal waves from sloping bottoms.

In previous studies, field observations of internal waves were carried out. Owing to the limit of stationary measurement in situ, sufficient experiment data were not easily obtained. On the other hand, data collected by laboratory experiments express more information on wave mechanism, such as energy dissipation, mixing efficiency, and stratification thickness in a stratified layer fluid system. In present study, the authors supply valuable experiment data and analytic method, which will be a great contribution to the geophysical fluid dynamics. The results illustrate well what has been investigated in laboratory experiment and may be applicable to the naturally occurring reflection of internal waves from sloping bottoms.

More recently, it has been proposed that internal wave mixing may contribute significantly to internal mixing in the ocean and hence has an important influence on world climatic changes. Based on the statistical algorithm and regression model, the reduction in internal wave energy can be predicted on a sloping bottom due to frictional effect. Since, interaction between internal waves and uniform slopes has occurred in an estuary, a lake or in the ocean, the results available in this paper would benefit future study on internal wave hydrodynamics.

Lightweight apps such as WeChat mini programs (WMPs) are an emerging mobile channel (m-channel) touchpoint that have gained remarkable popularity among consumers. Despite the focus of migration research on traditional m-channel touchpoints (e.g. native apps and mobile websites), but few researchers have examined why consumers switch from native to lightweight apps. Drawing on the push-pull-mooring framework, this study aims to identify the key factors influencing consumers' switching related to lightweight apps.

The data were collected using a questionnaire survey of 416 WMP consumers and the proposed model was analyzed through structural equation modeling.

The results show that the push effect, specifically, high privacy concern, nudges consumers away from native apps, whereas the pull effects, including relative ease of use, convenience of access and exit and socially-oriented interaction, entice consumers to lightweight apps. Further, consumer switching intention is influenced by habit and perceived technology control, both of which reflect the mooring effects. Switching intention also stands as an important precedent of actual behavior.

This study is among the first theoretical explorations of consumer switching across m-channel touchpoints in the context of mobile commerce. For information system practice, these findings provide new insights for both incumbent providers and newcomers on how to retain existing shoppers as well as attract potential shoppers effectively.

This study aims to investigate the influence mechanism of expatriates' cultural intelligence (CQ) on expatriate effectiveness (task performance and premature return intention), identifying work engagement as a mediator and cultural distance as a boundary condition.

Drawing on the conservation of resource theory and the person–environment fit (P–E fit) theory, a moderated mediation model is built. Working with a sample of 303 international construction expatriates collected by snowball sampling, the hypotheses are tested by using the structural equation model analysis.

Work engagement partially mediates the relationship between expatriates' CQ and task performance, as well as fully mediates the relationship between expatriates' CQ and premature return intention. Cultural distance moderates the positive relationship between CQ and work engagement, as well as moderates the mediating effects of work engagement.

The impacts of potential moderators (e.g. work–family conflict and organizational culture) on the relationship between CQ and expatriate effectiveness have not been considered in this study.

This study is useful for international construction firms to optimize the allocation of human resources.

This study contributes to the expatriate literature by adding empirical evidence to explain the influence mechanism of expatriates' CQ on expatriate effectiveness.

The growing rate of desertification in Northwestern China and Mongolia that is occurring as a result of the conflict between economic development and natural conservation has been demonstrated in many studies. There have, for example, been some large studies using variations in bi‐weekly normalized difference vegetation index (NDVI) satellite images as a parameter for evaluating the vegetation dynamics in these areas. The purpose of this paper is to identify multi‐temporal variation in vegetated and non‐vegetated areas in remotely sensed satellite images to assess the status of desertification in East Asia.

Spatial data derived from these satellite images are applied to evaluate vegetation dynamics on a regional level, to identify the areas most vulnerable to desertification.

Analytical results indicate that the desert areas in East Asia are primarily distributed over Southern Mongolia, Central and Western Inner Mongolia, and Western China (the Taklimakan Desert). These desert areas expanded from 2000 to 2002, shrunk in 2003, then expanded again from 2003 to 2005. The areas most at risk for desertification are principally distributed in Southeastern Mongolia, and Eastern Inner Mongolia.

Simulation results based on data for deserts distributed throughout Northwestern China and Mongolia indicate that the proposed fuzzy model‐based method would be helpful for assessing and monitoring desertification. These analytical results will help administrators refine planning processes, define the boundaries of protected areas, and facilitate decisions for prioritizing areas for desertification protection.

This paper aims to explore the damage mechanism of a lubricating film on the worn surface of solid self-lubricating composites under different loads.

By comparing the actual stress with the strength, it is possible to determine the approximate wear state of the lubricating film. To prove the validity of the mathematical model that can predict the initiation of micro cracks or even the failure of the lubricating film, M50-5 Wt.% Ag self-lubricating composites (MA) was prepared. Tribological tests of the composites against Si₃N₄ ceramic balls were conducted at room temperature from 2 to 8 N. The electron probe microanalysis images of the lubricating film verify the wear state of the lubricating film.

The study found that the back edge of the contact area is the most vulnerable to destruction. The tensile stress and the equivalent shear stress have a positive correlation with load and friction coefficient. When the load is 4 N, an intact lubricating film covers the worn surface because the tensile stress and the equivalent shear stress are below the tensile strength and the shear strength, respectively; under other working conditions, the lubricating film is destroyed.

This paper has certain theoretical guidance for the study of tribological properties of solid self-lubricating composites. Moreover, this mathematical model is appropriate to be applied for the other composites.

The purpose of this paper is to investigate the influence rule and mechanism of three degrees of freedom film thickness disturbance on the transient performance of spiral groove, upstream pumping spiral groove dry gas seal (UP-SDGS) and double-row spiral groove dry gas seal (DR-SDGS).

The transient performance of spiral groove, UP-SDGS and DR-SDGS are obtained by solving the transient Reynolds equation under different axial and angular disturbance coefficients. The transient and steady performance of the above-mentioned DGSs are compared and analyzed.

The film thickness disturbance has a remarkable impact on the sealing performance of DGS with different structures and the calculation deviations of the leakage rate of the UP-DGS will increase significantly if the film thickness disturbance is ignored. The axial and angular disturbance jointly affect the film thickness distribution of DGS, but there is no significant interaction between them on the transient sealing performance.

The influence mechanism of axial disturbance and angular disturbance on the transient performance of typical SDGSs behavior has been explained by theory. Considering small and large disturbance, the interaction between axial disturbance and angular disturbance on the transient performance have been studied.

The purpose of this paper is to examine the strategic technology outsourcing of corporate ventures from an integrated perspective.

The proposed model argues that technology sourcing modes are jointly determined by the technological regime, industry‐specific factors and resource‐based view (RBV), as well as firm‐specific factors. Four Taiwanese top publicly traded pharmaceutical companies dedicated to biotechnology are studied.

This paper demonstrates that firms most likely to outsource technology are characterized by the following technological regime factors: reliant on external sources of innovation, tight IPR protection, path independent from the existing technology trajectory, less complexity, easy to codify and having resource‐based (RB) factors: irrelevant to the core competence, weak complementary assets, and autonomous innovation.

Current approaches generally focus on technology sourcing with a single strategic theory. New venture managers can apply the list of four industry‐specific factors and three firm‐specific factors of sourcing technologies to determine the appropriate sourcing modes (internal vs internal).

There has been little research on how technology sourcing can be done from a holistic, strategic angle. This paper demonstrates that technology sourcing strategy could be properly done by integrating multi‐levels, industry, firm and governance factors in a coordinated plan.