Search results

This paper aims to investigate the gear performance during meshing. The effects of line load, velocity and rough surfaces (kurtosis and skewness) on the lubrication characteristics and fatigue life of gears were analyzed.

In the mixed thermoelastohydrodynamic lubrication (TEHL) model, the distributions of pressure and film thickness are predicted using the Reynolds equation. The elastic–plastic rough contact model is used to calculate the contact force and area. To predict the fatigue life of the gears, the Dang–Van fatigue model is used to obtain the fatigue parameters under different line loads, velocities and rough surfaces.

The skewness of rough surfaces has a more significant effect on gear performance. In addition, according to fatigue parameters, it is found that when the load is too large, it leads to an increase in the probability of gear failure.

In this paper, a mixed TEHL model considering the effects of kurtosis and skewness is developed for the line contact to predict the mixed lubrication problem during gear meshing.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0356/

A tightly coupled global navigation satellite system (GNSS)-Vision-IMU-wheel odometer (GVIWO) system is proposed, which can realize robust positioning in extreme environments. The purpose of this study is to achieve adaptive initialization in complex environments, sensor anomaly detection and processing, and adaptive robust localization in extreme environments.

Adaptive initialization includes traditional dynamic and static initialization and extreme condition initialization. To deal with the unstable visual features in the state of excited motion, a method of wheel odometer assisted initialization is designed. According to the abnormal condition of the sensor, the anomaly detection and attenuation mechanism are designed to realize the accurate positioning of the sensor under abnormal condition.

Tight coupling optimization of GNSS signals, RGB+Depth Map cameras, inertial measurement units and wheel odometers ensures accurate positioning in both indoor and outdoor environments. Through open data sets and field validation experiments, the proposed tightly coupled system has strong adaptability, especially in extreme environments.

A new framework is proposed by integrating GNSS, visual, inertial measurement unit (IMU) and wheel odometer sensors to form an efficient positioning solution. An adaptive initialization method is proposed to enhance the robustness and real-time performance of the positioning system in complex and dynamic environments. A mechanism for detecting and attenuating sensor anomalies is designed, enabling quasideterministic positioning under sensor anomalies.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

This study aims to investigate the impact of the oil crash during the COVID-19 pandemic on the economy, energy and the environment in MENA countries, with and without fiscal policy, in a global context.

This study applies a Global Vector Autoregressive (GVAR) model for 47 countries from 2006Q1 to 2021Q3. The sign restriction method is used to identify the oil shocks originating from the COVID-19 crisis.

Empirical evidence shows that without fiscal interventions, MENA countries experienced a decline in output growth, energy consumption and CO₂ emissions due to lower oil prices caused by the COVID-19 pandemic. The impact of the oil price shock on inflation varied across the region. Economic growth and inflation rates in MENA countries turn positive when the member states implement expansionary fiscal measures to stimulate economic activities during the pandemic. Hence, fiscal policy played a crucial role in supporting the economy and preventing a severe recession during COVID-19 in the MENA region. However, expansionary fiscal measures increased energy consumption and air pollution.

The findings help policymakers better cope with the outbreak of deadly pandemics in the coming years. It improves our understanding of the role of fiscal policy in boosting economic efforts and reducing the adverse environmental impact of increased government spending.

This paper enhances the current body of literature by investigating how fiscal policies implemented by the MENA countries help mitigate the adverse economic effects of the COVID-19 crisis. Moreover, it enables us to analyze the impact of fiscal support on energy consumption and the environment during an oil shock influenced by global uncertainty, lockdowns, and supply chain disruptions.

For nearly 2 decades, the push-pull-mooring (PPM) model has been used frequently by scholars to explain consumers’ service switching intention and behavior. However, heterogeneity and incomparability between PPM model studies are prevalent issues: The chosen predictor variables, their categorization, their measurement, reported effect sizes, and effect directions vary considerably. By addressing these issues, the present meta-analytical review enables future researchers applying the PPM model to identify relevant variables and use valid measurements.

Based on 148 empirical studies employing the PPM model, the variables used to predict consumers’ service switching intention and behavior, their frequency of use, their categorization into push, pull, and mooring factors, and their measurement are assessed. The effect sizes and directions of the relationships between these variables and consumers’ service switching intention and behavior are analyzed using meta-analytic structural equation modeling. Additionally, the predictive capacity of this model and the influence of moderators are assessed.

Among the 148 empirical studies, 382 different independent variables were used. The three most frequently used and distinctly categorized independent variables are dissatisfaction (push), alternative attractiveness (pull), and switching costs (mooring). Overall, 152 unique sources were cited to measure these variables and the dependent variables. Dissatisfaction and alternative attractiveness increase switching intention, which positively affects switching behavior, while switching costs decrease switching intention. The model explains 30% of the variance in switching intention and 31% of the variance in switching behavior.

This study provides the first meta-analytical review of the PPM model to guide future research systematically.

This chapter aims to explore the potential for virtual reality (VR) technology to revolutionise human resource management (HRM) procedures. The comprehensive plan for integrating VR into HRM will positively impact various aspects such as recruitment, training, performance evaluation and employee engagement. This chapter provides practical insights and recommendations for organisations embracing this groundbreaking technology. It explores the design considerations, implementation techniques and potential impact of VR-based HRM programmes.

This article analyses the existing retail and distribution legal framework in which Internet companies operate, focusing on data breaches and other issues of relevance to these companies. In order to identify who should be responsible for the largest share of improving people's quality of life, this study takes into account the perspectives of both consumers and businesses (or service provider). The author states that where there is a high probability of a security or privacy breach and the customer suffers moderate to severe damage, the burden of proof may shift to the corporation. However, the customer's obligation is conditioned by factors such as the customer's risk tolerance, the customer's losses and the efficiency of the security investment.

The author suggests that the decentralized nature of blockchain, information sharing, immutability and smart contracting capabilities have the potential to disrupt established business models and social norms. Challenges related to trust, customs oversight and payments are discussed, as well as the process of creating the framework for electronic commerce. As part of this research, the author has taken into consideration the increasing popularity of Internet shopping.

The author demonstrates that due to the worldwide reach of the internet and the fast advancement of computer technology, the economies of the globe have grown increasingly linked. Even though e-commerce has been growing rapidly in recent years due to innovations in both technology and international retail and distribution forms, it still confronts a number of challenges.

In e-commerce that makes use of blockchain technology, there are significant costs associated with transferring data formats, a lack of consensus and limited emissivity in the flow of law and information. Reduced costs and associated negative externalities would be tremendously beneficial for both private enterprise and forward-thinking public policy.

This paper examines the potential liability concerns that may arise in the context of electronic transactions should a breach of security or privacy occur, as the author shows from a practical standpoint. Computers, mobile devices, tablets, sensors, smart meters and even autos are just some of the many channels via which data may be sent. It is conceivable for data flows in e-commerce, cloud and the Internet of Things to follow a regular pattern. This may endanger the confidentiality or security of the data. These have evolved into a significant barrier that web stores must overcome.

The author argues that resolving disputes related to the processing of electronic transactions is crucial to the growth of e-commerce businesses since customer happiness is directly correlated with business success.

The current study aims to explore the three dimensions of paternalistic leadership (i.e. moral leadership, benevolent leadership and authoritarian leadership) and their dual pathways of positive and negative influences on employees’ organizational citizenship behavior through the two aspects of trust (i.e. cognitive and affective trust).

Given that trust is pertinent in any human relationship, especially in Asian countries where bonding plays an important role, the current study investigated the relationship of each leadership style within paternalistic leadership on employees’ cognitive and affective trust in their leaders, employees’ organizational citizenship behavior and the processes involved. The current study employed a cross-sectional multilevel approach with 435 employees from 85 workgroups participating in the study.

As hypothesized, benevolent and moral leadership styles (but not the authoritarian leadership style) had a positive effect on employees’ cognitive and affective trust in their leaders and on employees’ organizational citizenship behavior. Cognitive and affective trust also mediated the relationships of benevolent and moral leadership styles with organizational citizenship behavior.

The study’s findings urge practitioners and human resources personnel to be aware of the dual effects that a paternalistic leader has on employees. To be specific, benevolent and moral leadership styles are conducive to employees’ work outcomes, whereas the authoritarian leadership style has a non-significant role in employees’ work outcomes.

Balancing economic development with social challenges such as gender inequality has become critical in the current times. Structural barriers persist as obstacles to women's professional opportunities despite evolving gender roles in the modern era. This chapter investigates the ‘motherhood penalty’, which is a concept couched in sociology and describes the disadvantages that working mothers face including lower wages and fewer opportunities of career advancement. This chapter explores economic, physical and mental health impacts of this penalty and sheds light on its detrimental effects on women's well-being and organisational success. Potentially, virtual reality (VR) technology is a solution through which working mothers can alleviate stress and improve well-being. In this chapter, existing literature on the motherhood penalty has been reviewed, and the innovative use of VR in workplace settings has been examined. There is limited research on the nexus between VR, motherhood penalty and working mothers' well-being, and therefore, this chapter seeks to provide a comprehensive overview of this intersection and proposes VR as a tool to mitigate the motherhood penalty, promoting gender equality and enhancing overall workplace well-being. Future research should explore VR's long-term benefits and ensure inclusive applications for diverse demographic groups.

This study addresses the growing challenges of food security, livelihood generation and sustainable urban living in the context of increasing urbanization in developing countries. As urban populations are projected to rise significantly in the coming decades, urban agriculture emerges as a potential solution to support dietary needs and economic empowerment. However, urban farming practices in developing countries face unique socio-economic, cultural and technological challenges compared to developed nations. This paper aims to analyze global urban agriculture practices, examine success stories from developed countries and propose an adaptable, inclusive urban agriculture model tailored to developing countries.

The research systematically reviews global urban agriculture practices, emphasizing successful implementations in developed nations. The research highlights gaps and areas of opportunity by comparing these practices with the unique socio-economic and cultural contexts of developing countries. Focus group interviews were conducted among urban farmers from India to finalize the key variables of urban agriculture in developing countries. The second phase involves the construction of a context-specific model for developing countries and proposing interventions. A comparative method is devised to identify developed country’s urban agricultural practices and policies to derive an optimal urban agricultural model for developing countries.

The findings from the study reveal that in developed countries, urban agriculture is motivated by the urge to become self-sustainable and to maintain a connection with the community shaped by different socio-economic, environmental and technological factors. In developing countries, the prime motive is to generate a secondary income source and ensure food security. Still, they face limited technological access, insufficient policy support and socio-cultural barriers. Technology-supported urban agricultural infrastructure and support from the government and other stakeholders would be a potential solution in developing countries to implement successful integrative solutions. To support this, adaptive policies in urban agriculture are required to bridge the gap in the current system.

This research offers practical implications for policymakers, urban planners and agricultural stakeholders in developing countries. It emphasizes the importance of designing policies that address resource constraints, such as land availability and financial access and promote sustainable farming techniques. The study recommends creating supportive frameworks to empower urban farmers, including subsidies, training programs and efficient market mechanisms. Integrating urban farming into city planning can foster green spaces, enhance food security and drive economic development. These actionable recommendations aim to facilitate the growth of urban agriculture as a sustainable and inclusive practice in developing countries.

Participation and social cohesiveness aspects of urban agriculture provide beneficial food accessibility with the concept of food for all, ensuring socio-cultural equality in accessing quality food. This study highlights the role of urban agriculture in addressing socio-economic inequalities, particularly in developing countries. By engaging communities in sustainable farming practices, urban agriculture can create collaborative networks, promote healthier lifestyles and improve access to fresh produce. The study also underscores the importance of empowering urban populations through targeted interventions in urban farming. These social implications reinforce the value of urban agriculture in enhancing the overall quality of urban life.

This study makes a unique contribution by focusing on the contextual adaptation of urban agriculture models for developing countries. While urban farming has been extensively studied in developed nations, limited research addresses developing regions’ specific challenges and opportunities. By proposing a comprehensive and inclusive model that bridges socio-economic and cultural gaps, this research provides a novel framework for integrating urban farming into the urban planning and policy landscape of developing countries. The originality lies in its comparative approach, leveraging global best practices while tailoring solutions to local contexts, thereby advancing the discourse on sustainable urban agriculture.