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As logistics talents in both Taiwan and Hong Kong are expanding their work area to Greater China, it is best to understand the competencies that logistics talents should possess. With this in mind, this study takes Mainland China, Hong Kong and Taiwan as the study scope, as well as logistics teaching and research experts and scholars as the study objects. The research findings can not only serve as informative references for universities intent on cultivating logistics talents, but as well as enhance the scope of both Taiwan and Hong Kong talents’ competence that can pave the way to the development of the logistics business in Greater China.

A total of 478 Americans participated in an online survey. Each participant was asked to answer questions about a company randomly assigned from one of 36 companies representing six industries.

This study aims to explain how corporate social responsibility (CSR) and negative corporate ability (CA) associations lead to negative word-of-mouth (WOM) intentions in non-crisis situations. Specifically, this study investigates the mediating roles of revenge and avoidance motives in the relationship between negative CSR and CA associations and the intention to generate negative WOM.

The findings indicate that negative CSR associations have a greater effect on WOM than negative CA associations. Moreover, negative CSR associations stimulate the revenge motive, resulting in stronger intentions to spread negative information, while negative CA associations lead to the avoidance motive, resulting in weaker intentions to spread negative information.

Unlike most previous studies that focused on crises, this study examines how negative CA and CSR associations influence negative WOM in non-crisis situations, shedding light on the roles of motives including the revenge and avoidance. The research fills a gap in the existing literature by demonstrating that negative CSR associations have a greater impact on negative WOM intentions than negative CA associations in non-crisis situations.

Informed by Mihaly Csikszentmihalyi’s systems view of creativity and Chad Borkenhagen’s conceptualization of open source cooking, this study explored how a group of extraordinary pastry chef used Instagram to openly express creativity, disseminate knowledge and reveal culinary secrets. The subsequent impacts of such actions were also assessed.

A qualitatively driven mixed-method approach was conducted using a nested mixed-method design. A total of 2,456 Instagram posts were visually analyzed alongside a series of interviews with elite pastry chefs over a two-year period.

Analysis distilled three themes that delineated how elite pastry chefs express creativity and share knowledge mindfully, ethically and altruistically on Instagram. The findings also converged to form a new theoretical model, “systems view of culinary creative sharing,” which accounts for the multifaceted considerations of culinary knowledge sharing on social media.

Findings converged to form a systems view of culinary knowledge sharing. This is peculiarly useful for scholars who are interested in developing a greater understanding about “where and how” creative ideas and knowledge originate, disseminate and receive corroborations in the contemporary digital era.

This study highlighted that a new praxis of open sharing looms large in the culinary profession. This praxis symbolizes a movement away from the traditional mindset of safeguarding culinary secrets and toward a more transparent and open philosophy toward knowledge sharing in the culinary community.

The Yangtze River Delta (YRD) has become the world’s most important container-export area in the world because of the huge growth of container volume from China. Shanghai, the gateway of the YRD, handles most of the cargoes. But the nature of river port has restricted its development, which forced China to built the Yangshan deepwater port to act as the mega hub in the region. In response to the emergence of the YRD and Yangshan, two traditionally transshipment centers in the region, Busan and Kaohsiung, have implemented strategies to in response to the emergence of YRD and Yangshan. This paper analyzes Busan’s and Kaohsiung’s strategies and tries to forecast the development of these ports. Research result shows Busan is aggressive and ambitious but that Kaohsiung has little chance of becoming the mega-hub in the region.

The purpose of this paper is to examine and explore the factors that drive users to gift through social network services (SNS).

A questionnaire method was applied to collect data from the sample of the WeChat users who have used mini-program. This paper employed the partial least squares method and used SmartPLS2.0 to analysis sample data, which examined the validity as well as reliability of the sample and further tested the hypotheses by the path coefficients.

The empirical results showed that pleasure, social relationship maintenance, convenience and comprehensiveness are significantly related to SNS gifting behavior, and conscientiousness moderates the relationship between intention and behavior in the context of SNS gifting. However, this study cannot find the effect of symbolic representation, impersonality and gift reciprocity motivations.

Theoretically, this study perfects the research of SNS gifting on the lack of exploring characteristics of comprehensiveness. Practically, this paper lends insights on how SNS providers attract users to adopt gifting.

SNS gifting lacks a complete and effective promotion strategy, resulting in a small number of users as well as low profit. Besides, prior studies have focused on tradition gifting and online gifting. Little research talks about gifting on SNS phenomena, and thus it is necessary to perfect the theory of SNS gifting.

Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout.

In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out.

For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm.

The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

This paper aims to examine the precision loss of ball screw raceway under different operating conditions and geometry parameters.

Based on a new coefficient K’ introduced especially for ball screws to reflect the actual contact condition, the modified Archard theory is applied to ball screws to obtain wear volume of the ball-screw contacts. Thus, the axial precision loss can be defined as the ratio of the wear volume to the contact area. Meanwhile, a novel running bench and a precision-measuring system of ball screws are conducted. Precision variation is obtained and analyzed during the whole life running test, which agrees well with the theoretical values calculated in this paper.

For a given rotational speed, the increasing rate of the precision loss rate is high at low axial load and then becomes small with the increasing axial load, whereas for a given axial load, the precision loss rate is proportional to the rotational speed. Besides, the precision loss rate is reduced with the increasing contact angle between a ball and the screw raceway, and is proportional to the helix angle when the angle changes from 1 to 10 degrees.

The rotational speed used in this experiment is low and the ball screw is of no-load type, although results calculated by the model and Wei’s model seem close when the axial load is high, whether the model built in the paper is applicable to the condition of high rotational speed and preload still needs to be verified in the future work.

This study provides an accurate model to predict the precision loss of the screw raceway and estimate the remaining life of ball screws, which is significant for better performance of ball screws as well as the computer numerical control machine tools.

Previous studies on the wear of ball screws mainly focused on the drag torque analysis and mechanical efficiency estimation, and the experiment to verify their theoretical analysis was almost all limited to the test of drag torque or axial rigidity, which is neither sufficient nor persuasive. However, in this paper, the authors proposed a comprehensive wear prediction model which combines the modified Archard wear theory, Hertz contact theory and kinematic theory of ball screws. To the best of the authors’ knowledge, this kind of study has never been reported in the literature. In addition, for the lack of the test bench and high cost of the experiment, the whole life operation test, which is designed and conducted to confirm the model in this paper, has never been reported in literature either.

Guided by the cognitive-affective system theory of personality (CAPS), this study aims to investigate the parallel mediating effects of cognitive and affective cynicism on the relationship between illegitimate tasks and employees’ adaptive performance. It also proposes growth need strength as a moderating variable for relationships between illegitimate tasks and employees’ adaptive performance.

Using a time-lagged design, data were gathered from 330 frontline hotel employees in China.

The authors found that the presence of illegitimate tasks is negatively associated with employees’ adaptive performance, this relationship being mediated by cognitive and affective cynicism. Growth need strength weakens the negative impacts of cognitive and affective cynicism on employees’ adaptive performance. In addition, the indirect effect of illegitimate tasks on employees’ adaptive performance via cognitive and affective cynicism is stronger for employees with lower levels of growth need strength.

Hotel managers must heed the negative impact of illegitimate tasks. Furthermore, they should underscore the importance of promoting a harmonious and positive organizational culture and atmosphere. Naturally, hotel managers must also establish effective communication with employees, assisting them in fostering a desire for excellence in their work.

This study provides valuable insights for the hospitality industry by investigating how illegitimate tasks hold sway over hotel employees’ adaptive performance. The study uses a moderated dual-path model to uncover the mechanisms behind this impact and the influence of boundary conditions, thereby expanding the understanding of the topic.

This paper aims to study the influence of different reinforcement methods on crack monitoring characteristics of eddy current array sensors, and the sensors with two different reinforcement methods, SUS304 reinforcement and permalloy reinforcement, are proposed.

First, the finite element model of the sensor is established to analyze the influence of the reinforcement plate’s electromagnetic parameters on the crack identification sensitivity. Then, the crack monitoring accuracy test of sensors with two reinforcement methods is carried out. Finally, the fatigue crack monitoring experiments with bolt tightening torques of 45 and 63 N · m are carried out, respectively.

In this study, it is found that the crack identification sensitivity of the sensor can be improved by increasing the relative permeability of the reinforcement plate. The crack monitoring accuracy of the sensors with two different reinforcement methods is about 1 mm. And the crack identification sensitivity of the sensor reinforced by permalloy reinforcement plate is significantly higher than that of the sensor reinforced by SUS304 reinforcement plate.

The sensor reinforced by reinforcement plate can work normally under the squeezing action of the bolt, and the crack monitoring sensitivity of the sensor can be significantly improved by using the reinforcement plate with high relative permeability.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is difficult to diagnose accurately due to its heterogeneous clinical manifestations. Comprehensive models combining different big data approaches (e.g. neuroimaging, genetics, eye tracking, etc.) may offer the opportunity to characterize ASD from multiple distinct perspectives. This paper aims to provide an overview of a novel diagnostic approach for ASD classification and stratification based on these big data approaches.

Multiple types of data were collected and recorded for three consecutive years, including clinical assessment, neuroimaging, gene mutation and expression and response signal data. The authors propose to establish a classification model for predicting ASD clinical diagnostic status by integrating the various data types. Furthermore, the authors suggest a data-driven approach to stratify ASD into subtypes based on genetic and genomic data.

By utilizing complementary information from different types of ASD patient data, the proposed integration model has the potential to achieve better prediction performance than models focusing on only one data type. The use of unsupervised clustering for the gene-based data-driven stratification will enable identification of more homogeneous subtypes. The authors anticipate that such stratification will facilitate a more consistent and personalized ASD diagnostic tool.

This study aims to utilize a more comprehensive investigation of ASD-related data types than prior investigations, including proposing longitudinal data collection and a storage scheme covering diverse populations. Furthermore, this study offers two novel diagnostic models that focus on case-control status prediction and ASD subtype stratification, which have been under-explored in the prior literature.