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In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

In this article, the authors try to determine why and under what conditions consumers intend to buy green and what the consequences are. Relying on theories of reasoned action and theory of planned behaviour (TPB), the authors offer that the green purchase intention (GPI) is impressed by environmental and personality components. Provide statements about the determinants and key implications of such market identification.

This research investigates the role of trust and social capital in shaping consumer behaviour in collaborative consumption (CC) platforms. By integrating system quality, social referral and shared goals, this study aims to develop a comprehensive framework that explains how these factors influence social trust, self-efficacy and ultimately drive consumers' intention to adopt CC.

The recognition of housing as an essential requirement in enhancing the quality of life of an individual has increasingly captivated scholars’ interest, particularly within the context of sustainability. However, the identification of suitable attributes of sustainable housing to be prioritized encountered challenges due to a lack of effective approach in addressing uncertainties and stakeholders’ interests. This study attempts to identify critical attributes of sustainable housing in rural areas and explore their interrelationships.

Six dimensions and 54 criteria are proposed and validated using the expert linguistic preferences through the Fuzzy Delphi Method. The Fuzzy Decision-Making Trial Evaluation Laboratory is also applied to determine the interrelationship between those attributes.

The result demonstrates that economic benefits strongly impacted social implications for sustainable housing. The top criteria, including government participation, reduced life cycle cost, environmental protection and local authorities’ participation, are considered to assist housing stakeholders for better sustainable practices.

To the best of the authors’ knowledge, this is one of the first studies addressing the interrelationship among sustainable housing attributes through linguistic preferences in the context of rural areas.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

The aerodynamic load caused by high-speed train operation may lead to severe vibration of the pedestrian bridge, thus causing great safety hazards. Therefore, this study aims to investigate the aerodynamic loading characteristics of a pedestrian bridge when a high-speed train passes over the bridge, as well as to evaluate the vibration response of the aerodynamic loads on the bridge structure.

High-speed trains are operated at three different speeds. The aerodynamic pressure load characteristics of high-speed trains crossing a pedestrian bridge are investigated by combining a nonconstant numerical simulation method with a dynamic modeling test method, and the vibration response of the bridge is analyzed.

The results show that when a high-speed train passes through the pedestrian bridge, the pedestrian bridge interferes with the attenuation of the pressure around the train, so that the pressure spreads along the bridge bottom, and the maximum positive and negative pressure peaks appear in the center area of the bridge bottom, while the pressure fluctuations in the bridge entrance and exit areas are smaller and change more slowly, and the pressure attenuation of the bridge bottom perpendicular to the direction of the train’s operation is faster. In addition, the pressure fluctuation generated by the high-speed train will lead to a larger vertical response of the bridge structure in the mid-span position, and the main vibration frequency of the bridge structure ranges from 8 to 10 Hz, and the maximum value of the vertical deformation amplitude is located in the mid-span region of the bridge.

This paper analyzes the flow field distribution around the train and at the bottom of the bridge for the evolution of the flow field when the train passes through the bridge at high speed, and conducts a finite element dynamic analysis of the bridge structure to calculate the vibration response of the bridge when the train passes through at high speed, and to evaluate the comfort of the passengers passing through the high-speed railroad bridge.

Based on traditional Chinese filial piety, this article examines the impacts and mechanisms of the two-dimensional filial piety concept “Qinqin – Zunzun” on gender wages in China via China Family Panel Studies (CFPS) conducted in 2014 and 2018.

This article construct regression models to examine the relationship between filial piety concepts and wages. Also, it uses unconditional quantile regression and decomposition to explore the impact of filial piety concepts on the wage gap.

It is found that: (1) The effects of two-dimensional filial piety are heterogeneous in terms of gender. Specifically, authoritarian filial piety significantly suppresses individual wages and has a stronger suppressive effect on women’s wages, whereas affinity filial piety significantly enhances individual wages without gender heterogeneity; (2) Parents' time support in the intergenerational exchange model is a crucial mechanism by which filial piety affects wages, exhibiting significant gender heterogeneity; (3) Regarding wage distribution, authoritarian filial piety mainly widens the gender income gap in the low and middle income-groups, while affinity filial piety narrows the gender wage gap by “raising the floor”, with its converging effect being most significant in the middle and high-income groups. This article deepens the understanding of the gender wage gap and intergenerational income mobility, providing policy references for better utilizing the social governance function of culture.

The article deepens the understanding and mechanisms of the gender wage gap and inter-generational income mobility, providing policy reference for better utilizing the social governance function of culture.

Based on stakeholder theory, this study aims to examine the impact of family firm succession on corporate philanthropy while considering the potential role of the clan cultural context, industry context, and the stage of succession.

Data were based on a sample of 7,502 firm-year observations from listed family firms in China’s A-share markets between 2007 and 2018. Several Tobit models are used for analysing the data. Difference-in-difference regression method and propensity score matching method are used for robustness tests.

Family firms undergoing succession tend to spend more on corporate philanthropy compared to non-succession counterparts. This effect is more pronounced among polluting industry firms and weaker in regions with strong clan cultures and after the process of succession is complete.

This study sheds new light on the relationship between inter-generational succession and corporate philanthropy. By considering the moderating effect of the clan cultural context, industry context, and the stage of succession, this study further advances the understanding of the role of corporate philanthropy in managing family firm succession.

Organizational commitment could influence nurses’ turnover intention, but we know little about how effort recognition may enhance all three aspects of nurses’ organizational commitment and consequently reduce their turnover intention. This study adopts the self-affirmation theory to examine how the number of effort recognitions received by a nurse may impact the normative, continuance and affective aspects of their organizational commitment and their turnover intention.

We collected two-wave data from the survey responses of 481 nurses in a large medical center in Taiwan between June and August, 2017 and between January and February, 2018 as well as counting the number of times their efforts were recognized as excellent by using patient/family performance appraisal forms in 2016. Bivariate correlation was used to test the hypotheses.

We found that effort recognition is positively associated with nurses’ normative organizational commitment but not with their continuance or affective commitment. The three aspects of organizational commitment are negatively associated with turnover intention.

Nurse managers who hope to reduce nurses’ turnover intention could consider adequately recognizing nurses’ outstanding performance.

The present study is the first to employ the self-affirmation theory to examine the impact of effort recognition on the three aspects of organizational commitment and turnover intention.

This study aims to investigate the impact of several constructs on young customers’ consumption of solar energy appliances in an emerging market by extending the theory of planned behavior (TPB).

This study collected primary data from 885 young customers in an emerging market, that is, Vietnam. Subsequently, this study used partial least squares structural equation modeling to investigate the relationships between examined variables.

The results indicated that personal innovativeness, environmental knowledge and renewable energy knowledge significantly improved attitudes toward solar energy appliances. In addition, purchasing intention is promoted by subjective norms and perceived behavioral control. Contradictorily, the perceived functional risk is a significant barrier to purchasing intention. It also negatively moderates two associations: attitude and purchasing intention, attitude and positive word-of-mouth. Despite being proven to influence word-of-mouth positively, attitude has no significant impact on purchasing intention.

These findings suggested several implications for enterprises, technology providers and policymakers to develop renewable energy appliance consumption.