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This study aims to explain the market-oriented transformation dilemma of Chinese urban investment and development companies (UIDCs; also known as local government investment and financing companies) and objectively evaluate their transformation efficiency from both static and dynamic perspectives. The results of the research provide methodological bases for improving the transformation efficiency of UIDCs, thus pointing out the direction for the rational planning of their transformation path.

This study takes Chinese UIDCs in market transformation during 2015–2019 as the research object and uses principal component analysis to screen the index system for measuring the efficiency of market transformation. It then uses a three-stage data envelopment analysis model and the Malmquist productivity index to evaluate the market transformation efficiency of these companies during 2015–2019 and comprehensively analyzes the influence of external environmental factors on the market transformation of Chinese UIDCs.

Research results show that the transformation efficiency of Chinese UIDCs is low and slow overall and that large spatial and temporal differences exist. The transformation efficiency of UIDCs located in eastern China is higher than that of UIDCs in central and western China. The higher the external environmental factors of regional GDP, local debt service pressure and credit rating, the more likely they are to cause input redundancy in the transformation process of Chinese UIDCs, which is not conducive to their market-oriented transformation. In addition, the higher the urbanization rate, the more effective it is to improve the efficiency of market-oriented transformation of UIDCs. If the influence of environmental factors is stripped away, both the overall efficiency value and pure technical efficiency value of market-oriented transformation of Chinese UIDCs will increase while the scale efficiency value becomes smaller.

This research measures the transformation efficiency of Chinese UIDCs and comprehensively analyzes the influence of external environmental factors on their market-oriented transformation. The goal is to enrich the study of the market-oriented transformation efficiency evaluation index system of Chinese UIDCs at the theoretical level and provide important reference values for improving the efficiency of market-oriented transformation of Chinese UIDCs at the practical level.

Based on social cognitive theory, this study aims to explore the influence of supervisor bottom-line mentality (SBLM) on employee knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior). The study first investigates the role of an ethical decision-making mechanism (moral disengagement) in mediating this relationship. In addition, it considers the possible boundary conditions to supplement research on the influence of SBLM in the knowledge management field.

The authors collected 256 data points from employees across three stages using convenience sampling. The authors then tested the proposed hypothesis using hierarchical regression and bootstrap methods.

The results demonstrated that SBLM promotes employees’ moral disengagement, leading to more knowledge territorial behavior and knowledge sabotage behavior. Furthermore, high power distance orientation among employees exacerbates the ill effects of SBLM according to the first stage of a moderated mediation model. Employees with such an orientation are more likely to respond to a SBLM by exhibiting a higher level of moral disengagement, thus increasing their knowledge territorial behavior and knowledge sabotage behavior.

Research on the influence of SBLM in the knowledge management field is limited. This study not only clarifies the relationships between SBLM and two types of knowledge behavior (knowledge territorial behavior and knowledge sabotage behavior) but also enriches the research on the antecedents of these two types of knowledge behavior.

Based on the cognitive appraisal theory of emotion and social comparison theory, this study explores the mediating mechanism and boundary conditions of supervisor bottom-line mentality on employee presenteeism.

Using hierarchical regression and bootstrapping, we test the hypothesized relationships with three-stage data from 265 full-time employees in China.

Supervisor bottom-line mentality has a significant positive influence on employee presenteeism. Workplace fear of missing out plays a mediating role between supervisor bottom-line mentality and employee presenteeism. Employees’ status-striving motivation positively moderates the influence of supervisor bottom-line mentality on employees’ workplace fear of missing out and enhances the mediating effect of workplace fear of missing out.

Presenteeism can be detrimental to employees’ health, and ultimately leads to a decrease in organizational productivity. Research conclusions warn companies to be vigilant about supervisors’ bottom-line mentalities and to strengthen employee health management.

This study explains when and how supervisor bottom-line mentality affects employee health, contributing to the literature on the antecedents of presenteeism and enriching the research on supervisor bottom-line mentalities and employee and organizational outcomes. This study clarifies the emotional mechanisms and boundary conditions of supervisor bottom-line mentality affecting presenteeism.

The objective to achieve economic growth and sustainable development (SD) within the maritime industry has ever since been the ultimate goal of the International Maritime Organization and its stakeholders. Coupled with this effect, the United Nations organization has also mandated all its bodies to adopt sustainable working policies and practices towards the achievement of SD in its 2030 Agenda. From the standpoint of an emerging economy, this study aims to examine green maritime practices adopted by maritime authorities towards the achievement of SD in the maritime industry of Ghana. The proposed conceptual model of this study supports the natural resource-based view theory advocated by Hart (1995).

The dataset of this study was gathered using semi-structured questionnaires. A total of 635 valid responses were received as feedback which were tested and analyzed using partial least square structural equation modelling. The rationale for the adoption of this analytical tool is its resilient ability to handle a relatively small quantity of datasets. It is also suitable for empirical studies involving model development and at the early stage of theory development.

The findings of the study are as follows; firstly, quality maritime education and training directly and significantly influence green maritime transport (GMT), clean ocean and maritime resource conservation (COMRC), green port operations and services (GPOS), SD and waste management and treatment systems (WMTS). Secondly, GMT, COMRC, GPOS and WMTS have a direct significant influence on SD. Lastly, GMT, COMRC, GPOS and WMTS partially mediate the relationship between quality maritime education and training and SD.

This study proposes a conceptual model that attempts to explain to maritime authorities and stakeholders that although the adoption of green maritime practices significantly influences SD, yet, it may be insufficient without quality maritime education and training provided to maritime professionals. Hence, emphasizing that all maritime personnel receive quality maritime education and training to enhance the long-term achievement of SD in the maritime industry. It also attempts to prove and suggest to maritime authorities how they can collectively integrate both onshore and offshore green maritime practices to achieve SD.

The originality of this study shows in testing a conceptual model that affirms that, achieving SD in the maritime industry is dependent on quality maritime education and training received by maritime personnel, hence, demonstrating the significant role of maritime training institutions towards the maritime industry and the achievement of SD.

The teenager community is the most affected community by cybercrime in the COVID-19 era. Increasing social networks and facilitating teenager access to the Internet have increased the probability of cybercrimes. On the other hand, entertainment such as mobile and computer games is top-rated among teenagers. Teenagers' tendency to cybercrime may be influenced by individual, parent, social, economic and political factors. Studying the impact of social networks, mobile games and parents' religious attitudes on teenagers' tendency to cybercrimes in the COVID-19 era is the primary goal of this paper.

The outbreak of COVID-19 caused a considerable change in the world and the lifestyle of all people. Information and Communication Technology (ICT) was also affected by the special conditions of this virus. Changes in ICT and rapid access to it have empowered individuals and organizations, and people have increased civic participation and interaction through ICT. However, the outbreak of COVID-19 has created new challenges for the government and citizens and may cause new crimes. Cybercrime is a type of crime that occurs in a cyber environment. These crimes range from invasions of privacy to crimes in which the offender vaguely paralyzes the macroeconomic. In this research, 265 students of high schools and universities are used for collecting data by utilizing a survey. Measuring actions have been done in all surveys employing a Likert scale. The causal pattern is assessed through a constructional equation modeling procedure to study the scheme's validity and reliability.

The outcomes have indicated that social networks have no significant relationship with teenagers' tendency to cybercrimes in the COVID-19 era. Mobile games have a mild effect on teenagers' tendency to cybercrimes in the COVID-19 era, and parents' religious attitudes significantly impact teenagers' tendency to cybercrimes in the COVID-19 era.

Current research also has some restrictions that must be noticed in assessing the outcomes. First, sample research was selected from high schools and universities in one city. So, the size of the model is small, and the generalization of results is limited. Second, this research may have ignored other variables that affect the tendency of teenagers' to cybercrime. Future researchers intend to investigate the parents' upbringing system's impact on teenager's trend to cybercrime in the COVID-19 era. Future research can also examine practical factors such as parental upbringing, attitudes toward technology development and virtual addiction in the COVID-19 era.

In this study, teenagers' tendency to cybercrimes in the COVID-19 era is investigated, and a procedure is applied depending on a practical occasion. This article's offered sample provides a perfect framework for influencing parents' social networks, mobile games and religious attitudes on teenagers' tendency to cybercrimes in the COVID-19 era.

As two essential styles of firm decision-making, the relationships among effectuation logic, causation logic and firm performance are unclear. It is helpful to deepen the understanding of reasoning theory and the process of decision-making. The purpose of this paper is to explore the relationship between effectuation logic, causation logic and firm performance.

Based on 31 independent empirical studies (including 11,600 samples) published by predecessors, meta-analysis is used to systematically integrate the impact of two decision-making styles on firm performance and explore the potential factors affecting their relationship.

The results show a positive correlation between two decision-making styles and firm performance and the influence of effectuation decision-making style in firm performance is slightly stronger. However, the application environment is different: in the emerging market, the causation decision-making style is more effective for firm performance management. When the firm chooses the effectuation decision-making style, it is more effective for performance management in the emerging market. In addition, the industry type, firm performance evaluation tools, national development level and firm scale and firm age can significantly moderate the impact of two decision-making styles on firm performance.

Both decision-making logics are possible ways for firm to success. Still, the future needs to dig deeper into the black box that can unlock the decision-making styles to achieve firm performance or competitive advantage based on other factors of the decision-behavior-outcome business model, more longitudinal data and experiments.

To the best of the authors’ knowledge, this is the first study to explore the impact of decision-making styles (effectuation logic and causation logic) on firm performance using a meta-analysis.

As China has pressed ahead with rural revitalization in recent years, its rural financial sector has also developed rapidly and the financial environment has been greatly improved. But compared with urban areas, the rural financial sector makes rather limited contributions to rural economic development for a variety of reasons, including single types of service providers, narrow coverage, and lack of services and products. The underdevelopment of the rural financial system is closely related to the characteristics of its target customers and the economic system. The deficient rural financial credit system, the low level of IT application, the difficulty in data collection and integration, and the insufficient collateral of farmers pose high costs and huge risks for financial institutions when providing credit and other financial services.

In the present case, fintech and financial innovation complement each other: The application of fintech makes innovation possible, and the need for financial development fuels the development of fintech. Leveraging fintech and new business models, MYbank has overcome the main obstacles in the development of rural finance to provide convenient financial services for farmers and rural MSEs. Fintech is the abbreviation of “financial technology.” It can be understood as the combination of finance and technology for easier understanding, but it is more than that. Fintech refers to the innovation of traditional financial products and services with various technologies to improve efficiency and reduce operating costs. The emergence and development of fintech have led to the creation of new business models, applications, and processes, which have triggered major changes in financial markets, financial institutions, and the ways financial services are delivered, and are reshaping the financial landscapes of countries and even the world.

There are three major problems in the development of rural finance: difficult access to data, difficult risk management, and difficult market penetration. In order to gradually remove the obstacles and guarantee sustainable business development, MYbank has created three new business models with the power of fintech: digital inclusive finance at the county level, industrial finance, and platform finance. With these models, MYbank is searching for a “Chinese solution” to the worldwide problem of rural inclusive finance.

This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational efficiency through wear image analysis.

Using a data set of scanning electron microscopy images from an internal combustion engine, the authors used AlexNet as the feature extraction algorithm and the J48 decision tree algorithm for feature selection and compared 15 ML classifiers from the lazy-, Bayes and tree-based families.

From the analyzed ML classifiers, instance-based k-nearest neighbor emerged as the optimal algorithm with a 95% classification accuracy against testing data. This surpassed individually trained convolutional neural networks’ (CNNs) and closely approached ensemble deep learning (DL) techniques’ accuracy.

The proposed approach simplifies the process, enhances efficiency and improves interpretability compared to more complex CNNs and ensemble DL techniques.

This paper investigates the vibration compaction mechanism and evaluates the impact of vibration frequencies on the stability of coarse-grained soil, aiming to optimize the subgrade filling process.

This study examines the vibratory compaction behavior of coarse-grained soils through indoor vibration tests and discrete element simulations. Focusing on angular gravel (breccias) of varying sizes, the simulations were calibrated using parameters such as Young’s modulus, restitution and friction coefficients. The analysis highlights how particle shape influences compaction, revealing mesoscopic mechanisms that drive macroscopic compaction outcomes.

This study investigates the influence of vibration frequency on the compaction behavior of coarse-grained soils using discrete element simulation. By analyzing particle contact and motion, the mesoscopic mechanisms driving compaction are explored. The study establishes a positive linear correlation between contact force anisotropy (Cv) and deformation, demonstrating that higher anisotropy leads to greater structural disruption. Additionally, the increase in sliding contact percentage (SCP) at higher frequencies indicates instability in the skeletal structure, driven by uneven contact force distribution. These findings reveal how frequency-induced stress concentration affects the stability and deformation of the soil skeleton.

This research explores the effect of various vibration frequencies on the compaction behavior of coarse-grained soils, examining microscopic interactions to reveal their impact on soil stability and deformation.

The precise and sensitive methods for authentication and differentiation of natural and synthetic indigo dyes are required for assurance of textile safety and public health. This study aims to develop a fast and simple method to distinguish natural indigo from synthetic one.

A static headspace gas chromatography-mass spectrometry (GC-MS) method was developed for identification of natural and synthetic indigo samples. Natural indigo samples prepared from three different plants and synthetic indigo samples from three famous manufacturers in China, were involved in this study, along with some nonindigo blue samples (such as direct blue, active blue and neutral blue). The yarns and fabrics dyed with natural and synthetic indigo were also analyzed by the GC-MS method.

High levels of aniline (21.87%–71.59%) or N-methylaniline (25.26%–38.73%) were detected only in synthetic indigo samples (1 g) using the static headspace GC-MS method. The yarns and fabrics dyed with the synthetic indigo were also detected with residual aniline (0.47%–14.86%) or N-methylaniline (6.59%–40.93%).

The results clearly demonstrated that aniline or N-methylaniline can be used a diagnostic marker for distinguishing natural indigo from synthetic indigo. The proposed static headspace GC-MS method is a rapid, simple and convenient approach for differentiation of natural and synthetic indigo, as well as for the yarns and fabrics dyed with synthetic indigo.