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Bolted joint is the most important connection method in aircraft composite/metal stacked connections due to its large load transfer capacity and high manufacturing reliability. Aircraft components are subjected to complex hybrid variable loads during service, and the mechanical properties of composite/metal bolted joint directly affect the overall safety of aircraft structures. Research on composite/metal bolted joint and their mechanical properties has also become a topic of general interests. This article reviews the current research status of aeronautical composite/metal bolted joint and its mechanical properties and looks forward to future research directions.

This article reviews the research progress on static strength failure and fatigue failure of composite/metal bolted joint, focusing on exploring failure analysis and prediction methods from the perspective of the theoretical models. At the same time, the influence and correlation mechanism of hole-making quality and assembly accuracy on the mechanical properties of their connections are summarized from the hole-making processes and damage of composite/metal stacked structures.

The progressive damage analysis method can accurately analyze and predict the static strength failure of composite/metal stacked bolted joint structures by establishing a stress analysis model combined with composite material performance degradation schemes and failure criteria. The use of mature metal material fatigue cumulative damage models and composite material fatigue progressive damage analysis methods can effectively predict the fatigue of composite/metal bolted joints. The geometric errors such as aperture accuracy and holes perpendicularity have the most significant impact on the connection performance, and their mechanical responses mainly include ultimate strength, bearing stiffness, secondary bending effect and fatigue life.

Current research on the theoretical prediction of the mechanical properties of composite/metal bolted joints is mainly based on ideal fits with no gaps or uniform gaps in the thickness direction, without considering the hole shape characteristics generated by stacked drilling. At the same time, the service performance evaluation of composite/metal stacked bolted joints structures is currently limited to static strength and fatigue failure tests of the sample-level components and needs to be improved and verified in higher complexity structures. At the same time, it also needs to be extended to the mechanical performance research under more complex forms of the external loads in more environments.

The mechanical performance of the connection structure directly affects the overall structural safety of the aircraft. Many scholars actively explore the theoretical prediction methods for static strength and fatigue failure of composite/metal bolted joints as well as the impact of hole-making accuracy on their mechanical properties. This article provides an original overview of the current research status of aeronautical composite/metal bolted joint and its mechanical properties, with a focus on exploring the failure analysis and prediction methods from the perspective of theoretical models for static strength and fatigue failure of composite/metal bolt joints and looks forward to future research directions.

The purpose of this paper is to investigate the effects of political connections on the association between firms' business strategy and their tax aggressiveness in an emerging economy such as China.

The authors study a large sample of Chinese public firms from 2011 to 2017 using a panel regression model. In addition, a change analysis, an instrument variable test and alternative measures/samples are implemented as robustness tests.

Firms adopting innovative business strategy are more tax aggressive overall. However, innovative firms with political connections are less tax aggressive compared to those without political connections.

This paper contributes to the understanding of firms' tax behaviors in an emerging economy setting. It suggests that there are costs associated with political connections, such as foregone tax saving opportunities, which are understudies in the prior literature.

The purpose of this review is to conduct a bibliometric analysis of financial fraud exploiting the elderly by mapping its evolution, identifying major metrics and discussing directions for future research.

A bibliometric analysis was conducted, based on 434 articles retrieved from the Web of Science that represent the academic literature on the topic from 1995 to the first quarter of 2024. This paper analyses the antecedents of financial fraud exploiting the elderly, the publication trends and the most prolific countries, institutions, journals, research areas and authors. Bibliometric analyses based on co-citation and co-words explore the intellectual structure of the topic. A bibliographic coupling analysis reveals the hottest research trends in this field.

A significant increase in the number of publications in recent years shows the importance gained by this research stream. The bibliometric analysis identifies four clusters throughout the literature: differentiation of types of elder abuse; protection of the elderly from fraud; cognitive and decision-making capacity in ageing; and factors influencing fraud victimization of the eldest. The most recent research lines identified through bibliographic coupling focused on the contextual and personal antecedents of financial exploitation of the elderly, as well as the possible impact of interventions. Several key research gaps and additional suggestions for further studies, as well as action lines for the financial authorities and economic agents, are outlined.

This paper contributes to knowledge about financial fraud exploiting the elderly synthesizing the existing literature, stressing that the banking industry has to deal with such financial fraud in the context of a growing relevance of the silver economy.

This paper examines the relationship between transport connectivity and regional economic development in China. It develops measurements appropriate for transport connectivity based on a set of evaluation models. This model is used to analyze the logistic connectivity of China’s 31 provinces by focusing on 11 variables, including some new factors (Density of road network, Density of railway network, Number of Internet Users) not used in previous studies, over the 13-year period from 2002 to 2014. Using panel data regression analysis, the empirical results show a statistically significant and positive impact of transport connectivity (factors like Density of road network, Density of railway network and Number of Internet Users) on economic development in China. In particular, the Number of internet users is a key factor reflecting information connectivity in all the variables. Comparative analysis regarding economic development is conducted to benchmark between coastal provinces and interior provinces. Like most previous research, this study yields the same finding of higher impact of transport connectivity on economic development in eastern provinces than in western provinces. This study suggests that decentralized decision-making will be significantly more efficient for analyzing regional infrastructure development. It also shows that the influence of transport connectivity on economic development is dependent on a certain developmental stage. This suggests that an economic region should adopt different development strategies for transport connectivity during different stages of development.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

With the help of a quasi-natural experiment on Chinese policies, this study aims to understand the actual contribution of Smart City (SC) policies to the development of information and communications technology (ICT) in different cities. It also discusses the social and digital differences that such policies may generate, with a particular focus on the potential for exacerbating urban inequalities.

To achieve this, the study employs a principal component analysis (PCA) to develop an ICT development indicator system. It then employs a difference-in-differences (DID) model to analyze panel data from 209 Chinese cities over the period from 2007 to 2019, examining the impact of SC policies on ICT development across various urban settings.

Our findings show that SC policies have significantly contributed to the enhancement of ICT development, especially in ICT usage. However, SC policies may inadvertently reinforce developmental disparities among cities. Compared to less developed areas, the benefits of SC policies are more pronounced in economically booming cities. This is likely due to the agglomeration of the ICT industry and the strong allure of developed urban centers for high-caliber talent.

This study contributes to the related literature by explaining the role of SC policies in driving ICT development and by focusing on the often-overlooked impact of SC policies on urban inequality. These findings can provide guidance to policymakers on the need to recognize and address existing urban inequalities.

Inventory accumulation is a major problem for any organization, as it not only occupies the valuable storage space, but it also blocks the company's capital, leaving the owners with less cash to run the company's business. Aggregation of inventory in any organization contributes to inventory carrying cost; it affects labor productivity, increases equipment expenses and creates a loss of opportunity associated with it. Therefore, it is essential for any organization to come up with a solution to deal with the stockpile of inventory.

This research aims to examine the potential causes of inventory aggregation in an organization. First, the potential factors for the build-up of inventory are identified from survey data collection, such as questionnaire approach and discussion with industry experts, and then weights are assigned to attributes to study the effects for these factors. After the identification of probable causes, they are analyzed through a multi-criterion decision-making (MCDM) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) to prioritize the severity of these causes toward the accumulation of inventory and take corrective actions to prevent their disruptive effect on the business.

The top three causes identified from the TOPSIS analysis are sales and forecasting error, defects and quality related issues and communication gap between departments. Firstly, we focus on these major contributors and prioritize them using the TOPSIS analysis. Then, we proceed further toward other factors. The main reasons identified for the accumulation of inventory are (1) forecasting error, (2) bulk purchase, (3) data entry error, (4) communication gaps, (5) quality-related issues, (6) product category not traceable and (7) wrong material being procured.

To carry out the data analysis in this research paper, first survey data collection is done. Then, discussions with managers and executives in the particular domain are carried out, and weights are assigned to the attributes and the criteria to study the effects of the identified factors. After that root cause analysis (RCA) is performed to get to the genesis of the problem and to take necessary corrective action, for carrying out this study, a total of seven potential causes were identified and the contribution of these seven causes on five attributes or criteria, i.e. quantity (in tons), holding and carrying cost, effect on labor productivity, loss of opportunity cost and storage space were studied.

This research paper is the author’s original work, and all the analyses carried out are from the discussion with experts in the field and through the in-depth analysis carried out. This research aims to examine the potential causes of the accumulation of inventory in organizations and their contribution toward factors like inventory carrying cost, labor productivity, and opportunity loss and excessive storage space have been analyzed. This research provides great value to the readers in the respective domain.

The wavelet neural network (WNN) has the drawbacks of slow convergence speed and easy falling into local optima in data prediction. Although the artificial bee colony (ABC) algorithm has strong global optimization ability and fast convergence speed, it also has the drawbacks of slow speed while finding the optimal solution and weak optimization ability in the later stage.

This article uses an ABC algorithm to optimize the WNN and establishes an ABC-WNN analysis model. Based on the example of the Jinan Yuhan underground tunnel project, the deformation of the surrounding rock of the double-arch tunnel crossing the fault fracture zone is predicted and analyzed, and the analysis results are compared with the actual detection amount.

The comparison results show that the predicted values of the ABC-WNN model have a high degree of fitting with the actual engineering data, with a maximum relative error of only 4.73%. On this basis, the results show that the statistical features of ABC-WNN are the lowest, with the errors at 0.566 and 0.573, compared with the single back propagation (BP) neural network model and WNN model. Therefore, it can be derived that the ABC-WNN model has higher prediction accuracy, better computational stability and faster convergence speed for deformation.

This article uses firstly the ABC-WNN for the deformation analysis of double-arch tunnels. This attempt laid the foundation for artificial intelligence prediction in deformation analysis of multi-arch tunnels and small clearance tunnels. It can provide a new and effective way for deformation prediction in similar projects.

With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

Enterprise social media (ESM) are expressive spaces where users exchange emotional workplace communication. While some studies have explored how positive emotions may be contagious, little research explored the notion that negative communication may accumulate on enterprise social media. This study explores perceived negativity bias and its correlates in the context of ESM.

This study relies on survey data collected from 599 employees of a global organization. The response rate was 18.7%. Structural equation modeling was used to test the hypotheses.

The results contribute to research on ESM by demonstrating that perceived negativity bias is positively related to feelings of accountability and negatively associated with social support. Furthermore, the results indicate that unmet communication expectations on ESM can have implications for perceived social support beyond online contexts and accountability through perceived negativity bias.

The findings demonstrate how employees' unmet expectations about ESM use increase feelings that a digital environment is disproportionately negative, which may create an “unsafe” space for employees and a fear of being held accountable for their contributions. This study highlights how the Expectation-Disconfirmation Theory provides a fruitful framework for studying enterprise social technologies.

This study suggests that work is not merely a rational endeavor, and that emotions and personal feelings (including negative ones) may shape workplace communication on ESM. We contribute to research on ESM use by using the Expectation-Disconfirmation Theory as a lens to study antecedents and implications of perceived negativity bias.