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The development of digital technology has provided technical support to various industries. Specifically, Internet-based freight platforms can ensure the high-quality development of the logistics industry. Online freight platforms can use cargo transportation insurance to improve their service capabilities, promote their differentiated development, create products with platform characteristics and increase their core competitiveness.

This study uses a generalised linear model to fit the claim probability and claim intensity data and analyses freight insurance pricing based on the freight insurance claim data of a freight platform in China.

Considering traditional pricing risk factors, this study adds two risk factors to fit the claim probability data, that is, the purchase behaviour of freight insurance customers and road density. The two variables can significantly influence the claim probability, and the model fitting outcomes obtained with the logit connection function are excellent. In addition, this study examines the model results under various distribution types for the fitting of the claim intensity data. The fitting outcomes under a gamma distribution are superior to those under the other distribution types, as measured by the Akaike information criterion.

With actual data from an online freight platform in China, this study empirically proves that a generalised linear model is superior to traditional pricing methods for freight insurance. This study constructs a generalised linear pricing model considering the unique features of the freight industry and determines that the transportation distance, cargo weight and road density have a significant influence on the claim probability and claim intensity.

This article describes reliability analysis and failure cause determination in encapsulated semiconductor devices. Such devices were subjected to a destructive life test using temperature as an accelerating stress. Once the devices had failed, the failure data were statistically analysed with the aid of a digital computer. The failed devices were then decapsulated and failure causes were determined using different types of microscopy. The article gives detailed information about the tests and analysis mentioned above.

The purpose of this paper is to provide the current state of knowledge about the Flash Crash. It has been one of the remarkable events of the decade and its causes are still a matter of debate.

This paper reviews the literature since the early days to most recent findings, and critically compares the most important hypotheses about the possible causes of the crisis.

Among the causes of the Flash Crash, the literature has propsed the following: a large selling program triggering the sales wave, small but not negligible delays suffered by the exchange computers, the micro-structure of the financial markets, the price fall leading to margin cover and forced sales, some types of feedback loops leading to downward price spiral, stop-loss orders coupled with scarce liquidity that triggered price reduction. On its turn leading to further stop-loss activation, the use of Intermarket Sweep Orders, that is, orders that sacrificed search for the best price to speed of execution, and dumb algorithms.

The results of the previous section are condensed in a set of policy implications and recommendations.

The inverse Gaussian distribution arises quite naturally as a model for failure times brought on by a “steady” deterioration in quality. If the underlying “wear” process is one of Brownian motion with a positive drift at rate µ, with variance σ2 per unit time, the first passage time T to a barrier at a distance a from the origin has p.d.f. of inverse Gaussian type.

Wireless communication channel provides a wide area of applications in the field of communication, distributed sensor network and so on. The prominence of the wireless communication channel is because of its robust nature and the sustainability for the precise ranging and the localization. The precision and accuracy of the wireless communication channel largely depend on the localization. The development of the wireless communication channel with improved benefits needs the accurate channel model.

This paper characterizes the tangential path loss model in the WINNER based wireless communication channel model. The measurements taken in the WINNER channel model are compared with the tangential path loss characterized WINNER Channel model.

The model operates well over the varying antenna orientations, measurement condition and the propagation condition. The proposed tangential path loss model is performing well over the various outdoor scenarios.

The proposed characterization shows change in the small-scale parameters (SSP), such as power, delay, angle of arrival and angle of departure as well as the large-scale parameters (LSP), such as RMS delay spread, shadowing, path loss and Ricean factor associated with the model.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

In this paper, special emphasis is given to uncertainties in the evaluation of the structural behavior, looking for a better representation of the system characteristics and quantification of the significance of these uncertainties in structural design. The reliability analysis of reinforced concrete structures is performed taking into account the spatial variability of material properties. The finite element method is used to analyze reinforced concrete structures. A multidimensional non‐Gaussian stochastic field generation model (independent of the finite element mesh) is developed and used. The reliability analysis is carried out employing the first order reliability method. Numerical examples are presented to study how to generate correlated non‐Gaussian stochastic fields and determine the reliability of a reinforced concrete structure with respect to a limit state function.

Acceptance sampling can be both time‐consuming and destructive so that it is desirable to arrive at a sound lot disposition decision in a timely manner. Sequential sampling plans are attractive since they offer a lower average sample number than do matched single, double, or multiple sampling plans. Analogously, cumulative sum control charts offer the ability to detect moderate process shifts more rapidly than do Shewhart control charts applied to the same process. The inverse Gaussian distribution is flexible and is often the model of choice in accelerated life testing applications where early failure times predominate. Based on sequential probability ratio tests (SPRT), sequential sampling/ cumulative sum (CUSUM) plans provide timely, statistically based decisions. Presents SPRT and CUSUM results for the inverse Gaussian process mean. Also presents a simple goodness‐of‐fit test for the inverse Gaussian distribution which allows for model adequacy checking.

Cyber risk refers to risk affecting information and technology assets of a corporation or government institution. As cyber risk management become important, insurance is one possible solution. However, lack of data and severe information asymmetries increase the difficulties in pricing-related insurance products. In this chapter, we discuss first-party insurance that indemnifies the loss when the insured encounters virus attack and provide pricing model for the policy using copula methodology. Simulation results show that model risk may exist in the distribution of server downtime hours and is minor in the distribution of incident frequency and number of personal computers (PCs) infected.

The purpose of this paper is to both determine the effects of the nonlinearity on the wave dynamics and assess the temporal and spatial accuracy of five finite difference methods for the solution of the inviscid generalized regularized long-wave (GRLW) equation subject to initial Gaussian conditions.

Two implicit second- and fourth-order accurate finite difference methods and three Runge-Kutta procedures are introduced. The methods employ a new dependent variable which contains the wave amplitude and its second-order spatial derivative. Numerical experiments are reported for several temporal and spatial step sizes in order to assess their accuracy and the preservation of the first two invariants of the inviscid GRLW equation as functions of the spatial and temporal orders of accuracy, and thus determine the conditions under which grid-independent results are obtained.

It has been found that the steepening of the wave increase as the nonlinearity exponent is increased and that the accuracy of the fourth-order Runge-Kutta method is comparable to that of a second-order implicit procedure for time steps smaller than 100th, and that only the fourth-order compact method is almost grid-independent if the time step is on the order of 1,000th and more than 5,000 grid points are used, because of the initial steepening of the initial profile, wave breakup and solitary wave propagation.

This is the first study where an accuracy assessment of wave breakup of the inviscid GRLW equation subject to initial Gaussian conditions is reported.