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The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution.

The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples.

The simulation study shows that Bayes estimates based on γ prior with absence of prior information performs little better than the MLE with regard to both biases and mean squared errors. The Bayes credible intervals for reliability are also shorter length with competitive coverage percentages than the condence intervals. Further, the coverage probability is quite close to the nominal value in all sets of parameters when both sample sizes n and m increases.

The lifetime distributions used in reliability analysis as exponential, γ, lognormal and Weibull only exhibit monotonically increasing, decreasing or constant hazard rates. However, in many applications in reliability and survival analysis, the most realistic hazard rate is bathtub-shaped found in the Chen distribution. Therefore, the authors have studied the multicomponent stress-strength reliability under the Chen distribution by comparing the MLE and Bayes estimators.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

The purpose of this paper is to investigate the local feature of driven granular gases in event-driven molecular dynamic simulation, in order to achieve spatial profiles of local velocity distribution and granular temperature, and the local state with various coefficients of restitution.

Event-driven molecular dynamic simulation is performed to study a vibro-fluidized granular gas system. Triangular-wave vibration is adopted in the simulation. The authors focus on the steady state of a driven granular gas.

The simulation finds the local velocity distribution is asymmetric along vibration direction in this driven granular gas system, which agrees with the experimental results obtained in micro-gravity. A nonlinear spatial profile of the skewness of local velocity distribution in vibration direction is found in the simulation. Furthermore, it is found that the value of skewness increases with the system dissipation. It is also found that the two temperature components T+ and T− differ from each other. This shows breakdown of energy equipartition. The ratio between them drops exponentially along y direction in various coefficients of restitution. All results confirm that the bulk boundary effect relates to the dissipation properties of granular gases.

This is the first MD simulation that investigates the bulk boundary effect to the local velocity distribution. The spatial profiles of the skewness of local velocity distribution are also investigated when changing the coefficient of restitution to study the influence of the system dissipative nature.

The purpose of the paper is the construction of confidence intervals for the ratio of the values of process capability index C_pm for two processes. These confidence intervals can be used for comparing the capability of any pair of competitive processes.

Two methods for constructing confidence intervals for the ratio of the values of process capability index C_pm for two processes are proposed. The suggested techniques are based on a two-step approximation of the doubly non-central F distribution. Their performance is tested via simulation.

The performance of the suggested techniques seems to be rather satisfactory even for small samples, as illustrated through the use of simulated data.

The practical implication of the suggested techniques is that they can be implemented in real-world applications, since they can be used for comparing the capability of any pair of competitive processes.

The paper presents two new methods for constructing confidence intervals for the ratio of the values of process capability index C_pm for two processes.

The purpose of this paper is to develop an yield-based process capability index (PCI), C _py , to overcome the shortcomings of existing PCIs that limit their use and lead to inaccurate measures of quality conformance under a variety of common conditions.

–C _py is developed conceptually to flexibly and accurately reflect conformance and then used to numerically measure inaccuracies of C _pk .

–C _py overcomes many of the problems associated with existing PCIs, including C _pk . The degree of process distribution non-normality, level of quality (the sigma level), and whether the process is centered or shifted left or right affect the direction and size of process capability error produced by C _pk . The accuracy of C _pk can be greatly affected by process data that deviate even slightly from normality.

–C _py offers numerous advantages compared to existing PCIs. It accurately reflects process conformance regardless of the process distribution. It is applicable even if the process has multiple characteristics and with both variable and attribute data. Its calculation is relatively simple and the necessary data for it are likely already captured by most organizations.

The main contributions are the development of a new PCI, C _py ; a conceptual analysis of its advantages; and a numerical analysis of the improved accuracy of C _py as compared to C _pk for shifted and non-shifted process means for normal, nearly normal, and highly non-normal distributions over a range of process variability levels.

This paper aims to investigate the importance and prevalence of Guanxi in business interactions in network-based societies such as China, few studies have the phenomenon from a dyadic view. In a business dyad, one partner may not value Guanxi and take it as a template for actions as the other does.

The authors propose that such collective and asymmetric Guanxi orientation influence both the creation and distribution of relational rent in a Guanxi dyad. Furthermore, relationship-specific investments (RSIs) moderate the relationship between dyadic Guanxi orientation and relational rent creation and distribution.

Based on a matched sample of supplier-buyer dyads in China, the authors find that joint Guanxi orientation is positively related to joint pie creation, whereas Guanxi orientation imbalance has a positive effect on the pie distribution imbalance.

These results contribute to the literature by revealing how dyadic Guanxi dynamics and practices affect dyadic performance and providing managers with meaningful implications for dyadic Guanxi management.

Digital humanities research platform for biographies of Malaysia personalities (DHRP-BMP) was collaboratively developed by the Research Center for Chinese Cultural Subjectivity in Taiwan, the Federation of Heng Ann Association Malaysia, and the Malaysian Chinese Research Center of Universiti Malaya in this study. Using The Biographies of Malaysia Henghua Personalities as the main archival sources, DHRP-BMP adopted the Omeka S, which is a next-generation Web publishing platform for institutions interested in connecting digital cultural heritage collections with other resources online, as the basic development system of the platform, to develop the functions of close reading and distant reading both combined together as the foundation of its digital humanities tools.

The results of the first-stage development are introduced in this study, and a case study of qualitative analysis is provided to describe the research process by a humanist scholar who used DHRP-BMP to discover the character relationships and contexts hidden in The Biographies of Malaysia Henghua Personalities.

Close reading provided by DHRP-BMP was able to support humanities scholars on comprehending full text contents through a user-friendly reading interface while distant reading developed in DHRP-BMP could assist humanities scholars on interpreting texts from a rather macro perspective through text analysis, with the functions such as keyword search, geographic information and social networks analysis for humanities scholars to master on the character relationships and geographic distribution from personality biographies, thus accelerating their text interpretation efficiency and uncovering the hidden context.

At present, a digital humanities research platform with real-time characters’ relationships analysis tool that can automatically generate visualized character relationship graphs based on Chinese named entity recognition (CNER) and character relationship identification technologies to effectively assist humanities scholars in interpreting characters’ relationships for digital humanities research is still lacking so far. This study thus presents the DHRP-BMP that offers the key features that can automatically identify characters’ names and characters’ relationships from personality biographies and provide a user-friendly visualization interface of characters’ relationships for supporting digital humanities research, so that humanities scholars could more efficiently and accurately explore characters’ relationships from the analyzed texts to explore complicated characters’ relationships and find out useful research findings.

The purpose of this paper is to evaluate the ozone risk introduced by the mixing air-supply mode, displacement air-supply mode and personalized air-supply mode, respectively, in commercial aircraft cabins.

In this study, a computational fluid dynamics (CFD) model of aircraft cabin has been built to study the distribution of ozone mass fraction and the ozone surface deposition rate on passenger’s face and clothes under the three different air-supply modes, respectively. The distribution of ozone mass fraction has been obtained by calculating the mass concentration of ozone in different location. The ozone surface deposition rate on passenger’s face and clothes has been calculated according to the mechanism of the reactions between ozone and squalene, which is the primary reactant in human sebum.

By comparing the three air-supply modes, it was considered that the mixing air-supply mode made lower ozone concentration and ozone surface deposition risk in most area, but this was because of the thin air distribution in cabin. The displacement air-supply mode made an uneven distribution of ozone concentration and increased absorbing ozone risk in the breathing zone. The personalized air-supply mode was proper for avoiding ozone harm and making a comfortable air environment. The air supply from the inlet on seat back could not increase the ozone surface deposition risk on passenger’s face.

This paper provides the qualitative and quantitative analysis for ozone risk to the passengers under the different air-supply modes. Findings can provide some suggestions for the designers to optimize the air-supply mode of air distribution system for reducing passengers’ discomfort caused by high-altitude ozone introduction, such as breathing in too much ozone.

The purpose of this paper is to split loan customers to different credit ratings to ensure the results that show that customers with lower credit ratings have higher loss rates, and the number of customers that satisfies the bell-shaped distribution. Hence, the number of credit ratings, the distribution of the rated obligors among ratings can achieve a meaningful differentiation of risk, which can avoid the loan pricing confusion.

The authors introduce a multi-objective programming to establish the credit rating model. Objective function 1 minimizes the absolute difference between the obligor number proportion and perfect client proportion, following a standard normal distribution. Objective function 2 minimizes the total difference of the deviation between two adjacent credit ratings’ loss rates. This study combines the two objective functions to ensure the obligor number distribution and the monotonicity of the loss rate, and applies genetic algorithm to solve the model.

This study’s analysis is based on data from 6,155 enterprises, provided by a Chinese bank and Prosper P2P loan data. The empirical results reveal that the proposed approach can ensure the balance between both criteria and avoid undue concentration of obligors in particular grades.

The proposed credit model could help building a reasonable credit rating system, which is the prerequisite of loan pricing; thus, inaccurate credit rating can cause incorrect loss rate estimates and loan pricing.

In September 2019, Booking.com changed from the smiley-based scoring system (2.5–10) to the purely 10-point evaluation system (1–10). The smiley-based service evaluation is based on the multi-dimensional (M-D) system, whereas the purely 10-point service evaluation is based on the single-dimensional (S-D) system. This paper aims to focus on how a change in review posting policies impacts service evaluations regarding review generation and distribution.

The authors exploit the natural experiment using Booking.com when the site changed its scoring system from a multidimensional smiley-based service evaluation system to an S-D scoring system. The authors collected online reviews posted on two travel agencies (Booking.com and Priceline.com) between September 2019 and October 2020. A quasi-experimental approach, Difference-in-Differences, was used to isolate the impacts of the new scoring system from the impacts of the change in the service evaluation environment, i.e. COVID-19.

The change in the scoring system considerably alters review distributions by decreasing the portion of positive reviews but increasing the portion of highly positive reviews. Using the theory of emotion work (Hochschild, 1979, 2001), DID is also the reason that the former M-D smiley-based system could have underrated, highly positive reviews of services. Using the information transfer theory (Belkin, 1984), the authors reason the asymmetric transfer of information when users consume reviews from the older (M-D) system but are required to generate reviews on a newer (S-D) system.

The findings would provide online review platform management with a deeper understanding of the consequences of changes in service evaluations when the scoring system is changed.

Though the change in the scoring system would affect how customers evaluate the services of hotels, the causal impacts of switching to the new S-D scoring system have not yet been thoroughly covered by prior hospitality and service evaluation literature, which this research aspires to do.