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This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Co-working spaces bundle all real estate services into a package and leverage shared economy trend to create new opportunities for growth. This sector is anticipated to expand significantly due to changes in mobility and office design driven by the development of remote or hybrid work settings. The current study attempts to identify key motivating factors for users in emerging economies in choosing co-working spaces.

Using analytic hierarchy process (AHP) methodology and the self-determination theory framework, a total of 4 criteria-level factors, along with 13 sub-criteria level factors were identified as key motivators for adapting to co-working spaces.

The study highlights a few factors and their relative importance, which could help firms/organizations to start or offer co-working spaces within emerging economies.

The study contributes to literature by advancing the understanding of key motivators for users of co-working spaces within the ambits of emerging economies. In the process, the authors enlist a few factors vis-à-vis their relative importance, which could help firms/organizations to start or offer co-working spaces within emerging markets.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This paper aims to realize an in-situ quality inspection system rapidly for new injection molding (IM) tasks via transfer learning (TL) approach and automation technology.

The proposed in-situ quality inspection system consists of an injection machine, USB camera, programmable logic controller and personal computer, interconnected via OPC or USB communication interfaces. This configuration enables seamless automation of the IM process, real-time quality inspection and automated decision-making. In addition, a MobileNet-based deep learning (DL) model is proposed for quality inspection of injection parts, fine-tuned using the TL approach.

Using the TL approach, the MobileNet-based DL model demonstrates exceptional performance, achieving validation accuracy of 99.1% with the utilization of merely 50 images per category. Its detection speed and accuracy surpass those of DenseNet121-based, VGG16-based, ResNet50-based and Xception-based convolutional neural networks. Further evaluation using a random data set of 120 images, as assessed through the confusion matrix, attests to an accuracy rate of 96.67%.

The proposed MobileNet-based DL model achieves higher accuracy with less resource consumption using the TL approach. It is integrated with automation technologies to build the in-situ quality inspection system of injection parts, which improves the cost-efficiency by facilitating the acquisition and labeling of task-specific images, enabling automatic defect detection and decision-making online, thus holding profound significance for the IM industry and its pursuit of enhanced quality inspection measures.

China's Belt and Road Initiative (BRI) is the most ambitious investment strategy for infrastructural development belonging to the significant potential for stimulating regional economic growth in Asia, Europe and Africa. This study aims to investigate the impact of infrastructure on spurring inward foreign direct investment (FDI) within the purview of human capital, GDP per capita, foreign aid, trade, domestic investment, population and institutional quality in BRI countries.

In doing so, the authors analyze panel data from 2000 to 2019 within the framework of the system generalized method of movement (GMM) approach for 66 BRI countries from Europe, Asia, Africa and the Middle East.

The investigated results demonstrate that aggregate and disaggregate infrastructure indices, e.g. transport, telecommunications, financial and energy infrastructures, are the driving forces in attracting foreign direct investment (FDI) in the BRI countries. In addition, control variables (i.e. institutional quality, human capital, trade, domestic investment, foreign aid and GDP per capita) play an essential role in spurring FDI inflows.

The authors’ study uniquely investigates both the pre- (2000–2012) and post- (2013–2019) BRI scenarios using the aggregate and disaggregate infrastructural components from the perspectives of full and clustered sample regions, such as Asia, Europe, Africa and the Middle East. The study provides several policy implications.

This study aims to examine newcomers experiencing maladjustment due to cognitive diversity, specifically, how maladjustment affects their turnover intentions; the mediating role of reported workplace bullying; and the buffering effect of perceived inclusive practices in the hospitality sector.

The authors collected time-lagged data from 403 respondents and analyzed the data through hierarchical regression analyses using statistical package for the social sciences (SPSS) 25.0.

Role ambiguity, low self-efficacy and social exclusion could each lead to newcomers’ reported workplace bullying (NRB). Perceived inclusive practices buffered the impacts of role ambiguity and social exclusion. NRB negatively mediated the relationships between role ambiguity and NRB; and social exclusion and NRB.

Hospitality practitioners should specify work procedures to minimize role ambiguities and record service processes to correct mistakes, reward veterans who help newcomers improve self-efficacy, invite newcomers to develop inclusive practices and review employee comments on third-party platforms to understand factors responsible for turnover intention.

This study contextualized cognitive diversity into newcomers’ maladjustment-bullying-turnover model in China’s hospitality industry. It highlighted the buffering effect of perceived inclusive practices in the relationships between maladjustment and reported bullying and turnover intentions among newcomers and confirmed the important role of self-efficacy in addressing adverse work events.

The purpose of this study is to test the impact of time and price sensitivity on consumer satisfaction and purchase intention on online-to-offline (O2O) takeout platforms and explore the moderating effect of purchase preference on time sensitivity and satisfaction, as well as price sensitivity and satisfaction, in order to guide market pricing.

A structural equation model (SEM) of customer purchase intention was constructed, and the relationships between the variables (time sensitivity, price sensitivity, satisfaction and purchase intention) were examined. The completed questionnaires of 349 respondents were collected from the Questionnaire Star platform in China. The research model and hypotheses were then tested. Analytic hierarchy procedure was used to determine the moderating effect of purchase preference. Finally, the study proposes a pricing strategy for customer-active selective services.

Satisfaction positively influences purchase intention, and price sensitivity significantly increases satisfaction and further increases purchase intention; however, time sensitivity negatively affects satisfaction. Specifically, purchase preference has strongly moderated the relationship between time, price sensitivity and satisfaction. In addition, the findings show that when purchase preference is high, the effect of price sensitivity on satisfaction is stronger, suggesting the importance of purchase preference in strengthening purchase intentions. The research work recommends a pricing strategy involving value-added pricing primarily for time-sensitive customers, which can help build a high-end brand image and reduce price competition. Reduced pricing is mainly for price-sensitive customers, which is conducive to stimulating consumption within a specific time. This pricing strategy is important for adjusting market sensitivity and flexibility.

This research provides new ideas for related disciplines and guidance for the differentiated pricing and promotion of takeout platforms, as well as a theoretical basis for the diversified development of takeout platforms, improvement of personalized service quality and enhancement of customer stickiness. This study fills gaps in the existing literature on the moderating effect of purchase preference on time sensitivity and satisfaction and price sensitivity and satisfaction.

This paper aims to explore financial anxiety and generalized anxiety as the serial mediators linking perceived organizational support (POS) to career commitment.

Data were collected from 388 managerial and nonmanagerial employees in diverse service areas, such as restaurants, airlines and hotels in Turkey. The direct and mediating effects were tested via the PROCESS macro.

Financial anxiety partly mediates the impact of POS on career commitment. The findings further reveal that financial anxiety and generalized anxiety serially mediate the effect of POS on career commitment.

Management should work with mentors to provide employees with psychosocial support during the COVID-19 pandemic. When employees perceive that the firm really cares about them and values their contribution during these challenging days, they display lower anxiety and higher career commitment. Management should also retain employees who are high on career commitment because such employees possess a sense of calling and are unlikely to quit. These implications may not be considered new. However, management would need such employees concerning the firm’s performance recovery after COVID-19.

Workers in the service industries suffer from financial and generalized anxieties and display reduced career commitment during COVID-19. However, little is known about the antecedents and outcomes of financial anxiety among hospitality and tourism workers. More importantly, no empirical piece has tested these anxiety variables as the mediators linking POS to career commitment in the pertinent literature so far.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.