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By distinguishing between core business service and value-added service in mobile payment applications, this paper aims to incorporate point mechanisms (point rewarding and point exchanging) into these two separated roles of services to understand user loyalty formation. Specifically, this study aims to examine the mediating role of need satisfaction and perceived value in the relationships between point mechanisms and user loyalty.

Drawing upon self-determination theory and perceived value lens, this study develops a theoretical model that examines the mediation effects of multiple psychological outcomes on the relationships between point mechanisms (point rewarding and point exchanging) and user loyalty in the context of mobile payment. Data were collected from 731 users of a leading mobile payment application in China through an online survey. Structural equation modeling was used to analyze the hypothesized relationships.

Empirical results suggest that point rewarding enhances users’ need satisfaction of core service, whereas point exchanging increases users' perceived value of additional value-added service. Results also reveal that need satisfaction and perceived value mediate the relationships between point mechanisms (i.e. point rewarding and point exchanging) and user loyalty. In sum, the findings enhance our understanding of user loyalty formation from a dual channeling perspective.

This study informs the managers of mobile payment applications on how to build user loyalty by enhancing users' experience of core business service and value-added service through point mechanism implementation.

This study highlights the importance of both core business service and value-added service in mobile payment applications and provides new insights into the effects of point mechanisms on user loyalty by considering different service routes. Additionally, this study uncovers the mediation mechanisms of users' need satisfaction of core service and users' perceived value of additional value-added service on the two service routes, which further enrich our understanding regarding the user loyalty formation of mobile payment applications.

The purpose of this paper is to research the induced flashover laws of different insulation materials under electrostatic electromagnetic pulse, and the induced flashover characteristics of different electrode structures are further explored.

According to standard IEC 61000–4-2, an experimental system of electrostatic electromagnetic pulse flashover for insulation materials is established. The induction flashover laws of polytetrafluoroethylene, epoxy resin and polymethyl methacrylate surface-mounted finger electrodes under the different intensity of electrostatic electromagnetic pulse are researched. The influence of the finger electrode, needle–needle electrode and needle–plate electrode on insulation flashover was compared. Secondary electron emission avalanche (SEEA) and field superposition theory are used to analyze the experimental results of electrostatic electromagnetic pulse induced flashover.

The larger the dielectric strength of insulation materials, the more difficult flashover occurs on the surface. The field superposition enhances collision ionization between electrons and gas molecules, which leads to the insulation materials surface induced flashover easily by electrostatic electromagnetic pulse. The sharper the electrode shapes on the insulation materials surface, the stronger the electric field intensity at the cathode triple junction, more initial electrons are excited to form the discharge channel, which easily leads to flashover on the surface of the insulating material.

The proposed field superposition combined with the SEEA method provides a new study perspective and enables a more rational, comprehensive analysis of electrostatic electromagnetic pulse induced flashover of insulation materials. The work of this paper can provide a reference for the safety protection of spacecraft in orbit under a strong electromagnetic field environment, increase the service life of spacecraft and improve the reliability of spacecraft’s safe operation in orbit. It provides a basis for the selection of insulation materials for equipment under the different intensities of the external electromagnetic environment.

The authors explicitly evaluate the dynamic impact of five most concerned supply chain disruption scenarios, including: (1) a short-term shortage and price jump of corn supply in hog farms; (2) a shortage of market hogs to packing facilities; (3) disruption in breeding stock adjustments; (4) disruption in pork import; and (5) a combination of scenario (1)–(4).

The agricultural supply chain experienced tremendous disruptions from the COVID-19 pandemic. To evaluate the impact of disruptions, the authors employ a system dynamics model of hog market to simulate and project the impact of COVID-19 on China hog production and pork consumption. In the model the authors explicitly characterize the cyclical pattern of hog market. The hog cycle model is calibrated using market data from 2018–2019 to represent the market situation during an ongoing African swine fever.

The authors find that the impacts of supply chain disruption are generally short-lived. Market hog transportation disruption has immediate impact on price and consumption. But the impact is smoothed out in six months. Delay in import shipment temporarily reduces consumption and raises hog price. A temporary increase of corn price or delay in breeding stock acquisition does not produce significant impact on national hog market as a whole, despite mass media coverage on certain severely affected regions.

This is the first evaluation of short-term supply chain disruption on China hog market from COVID-19. The authors employ a system dynamics model of hog markets with an international trade component. The model allows for monthly time step analysis and projection of the COVID-19 impact over a five-year period. The results and discussion have far-reaching implications for agricultural markets around the world.

The purpose of this paper is to analyze the extent to which weather index‐based insurances can contribute to reducing shortfall risks of revenues of a representative average farm that produces corn or wheat in the North China Plain (NCP). The geographical basis risk is quantified to analyze the spatial dependency of weather patterns between established weather stations in the area and locations where the local weather patterns are unknown.

Data are based on the Statistical Yearbook of China and the Chinese Meteorological Administration. Methods of insurance valuation are burn analysis and index value simulation. Risk reduction is measured non‐parametrically and parametrically by the change of the standard deviation and the value at risk of revenues. The geographical basis risk is quantified by setting up a decorrelation function.

Results suggest significant differences in the potential risk reduction between corn and wheat when using insurance based on a precipitation index. The spatial analysis suggests a potential to expand the insurance around a reference weather station up to community level.

Findings are limited by a weak database in China and, in particular, by the unavailability of individual farm data. Moreover, the low density of weather stations currently limits the examination of the approach in a broader context.

The risk reduction potential of the proposed insurance is encouraging. From a policy point of view, the approach used here can support the adjustment of insurers towards different crops.

This paper is believed to be the first that investigates a weather index‐based insurance designed for an average farm in the NCP and the quantification of geographical basis risk.

The purpose of this study is to use visual and inertial sensors to achieve real-time location. How to provide an accurate location has become a popular research topic in the field of indoor navigation. Although the complementarity of vision and inertia has been widely applied in indoor navigation, many problems remain, such as inertial sensor deviation calibration, unsynchronized visual and inertial data acquisition and large amount of stored data.

First, this study demonstrates that the vanishing point (VP) evaluation function improves the precision of extraction, and the nearest ground corner point (NGCP) of the adjacent frame is estimated by pre-integrating the inertial sensor. The Sequential Similarity Detection Algorithm (SSDA) and Random Sample Consensus (RANSAC) algorithms are adopted to accurately match the adjacent NGCP in the estimated region of interest. Second, the model of visual pose is established by using the parameters of the camera itself, VP and NGCP. The model of inertial pose is established by pre-integrating. Third, location is calculated by fusing the model of vision and inertia.

In this paper, a novel method is proposed to fuse visual and inertial sensor to locate indoor environment. The authors describe the building of an embedded hardware platform to the best of their knowledge and compare the result with a mature method and POSAV310.

This paper proposes a VP evaluation function that is used to extract the most advantages in the intersection of a plurality of parallel lines. To improve the extraction speed of adjacent frame, the authors first proposed fusing the NGCP of the current frame and the calibrated pre-integration to estimate the NGCP of the next frame. The visual pose model was established using extinction VP and NGCP, calibration of inertial sensor. This theory offers the linear processing equation of gyroscope and accelerometer by the model of visual and inertial pose.