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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.

Although many conventional level-set approaches can be used for segmenting images containing factors such as noise and intensity inhomogeneities, they still can impact the accuracy of the results seriously. To solve this problem, a level-set method for fast image segmentation based on pre-fitting and bilateral filtering is proposed.

Firstly, an improved bilateral filter was investigated for image preprocessing. Secondly, by computing the local average intensity of the preprocessed enhanced picture, two local pre-fitting functions were defined. Thirdly, a new level-set energy functional was defined. Finally, a new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level-set function in a smooth state.

The experimental results demonstrate that the proposed model has an excellent segmentation capability for images with noise and intensity inhomogeneities and has different degrees of performance improvement compared with the mainstream models.

(C1) An improved bilateral filter was investigated and integrated into the model. (C2) Proposing two local pre-fitting functions by computing the local average intensity of the preprocessed enhanced image. (C3) Proposing a new level-set energy functional. (C4) A new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level set function in a smooth state. (C5) Analyzing and comparing the performance of the proposed model with other similar models.

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 chapter explores the landscape of higher education in Singapore as the nation positions itself to emerge stronger after the pandemic. A focus on three major issues facing higher education − digital transformation, job readiness of graduates, and access to quality education, describes education-based initiatives for addressing these challenges in Singapore. Local autonomous universities are woven into the tapestry of sustainable growth and development within Singapore’s economy. Connections between the development of education-based initiatives are made to illustrate how these institutions of continuous learning are positioning for relevance considering current developments and to suggest some areas for enhancement for promoting lifelong learning opportunities for all.

This study explores how the battle against the COVID-19 pandemic highlights the tourism industry's vulnerabilities and consequently leads to a paradigm shift towards adaptability, digitalization, diversification and closer collaboration with governmental and international entities. It encompasses a diverse range of industry involved parties, examining the responses and adaptations of various tourism entities to the pandemic's challenges. Through qualitative data analysis, including network analysis and word clouds, this study furnishes viable strategies that emphasize cultural sensitivity, environmental stewardship, technological integration, conservation-focused tourism and public–private partnerships. The study identifies key forthcoming challenges, including the standardization of environmental impact assessments, the promotion of eco-certifications, responsible tourism initiatives and the ethical treatment of wildlife, which will shape the future trajectory of sustainable tourism.

The tourism sector has realised an increasing need to transition towards sustainability. As the sector comprises a high number of entrepreneurs and small- and medium-sized enterprises, it faces specific limitations, which include, amongst others, knowledge transfer, skills and technology, financial and policy support, customer acceptance, and cultural taboos. To overcome these limitations, the sector thrives on encouraging interaction between ecosystem participants. One of the strategies to encourage interaction between ecosystem participants is the application of coopetition strategies. Coopetition strategies combine the advantages of cooperation and competition to generate value and achieve fruitful collaboration. However, their implementation is still limited. The purpose of this chapter is to examine the potential and practice of coopetition strategies among SMEs in addressing sustainability issues. Therefore, the study explored 10 European reusable cup-sharing schemes based on their level of applying coopetition. In doing that, the study aims to understand the supporting characteristics of existing cup schemes. It seeks to develop a framework for different levels of coopetition in achieving sustainability in the tourism and hospitality sector.

This chapter investigates the relationship between sustainable human resource (HR) practices and employee intentions to engage in sustainable behavior within an eco-friendly hotel. Specifically, we examine the influence of internal sustainability orientation, supervisory support, training, and rewards, as well as the mediating role of employees' knowledge of the resort's sustainability practices.

Due to increasing socio-ecological concerns, manufacturers are paying ample attention to the strategic decision-making for enhancing customer satisfaction considering Industry 4.0 requirements. Customers' preferences are being considered vital into the decisions related to sustainable supplier selection for building competitive gain. Thus, the objective of this study is to develop a real-case-based empirical approach for evaluating performance of suppliers based on customers' feedback, an area not explored much in literature. The novelty of current study lies in the development of an integrated supplier evaluation and selection model involving three phases: (1) identifying sustainable criteria according to Industry 4.0 requirement through customers' feedback, (2) calculating relative scores of criteria using Z-numbers and (3) determining evaluation weights of suppliers using fuzzy-TOPSIS. The contribution of the study lies in effective validation of the model by considering the case of a manufacturing firm, which aids the firm in evaluating performance of suppliers based on customers' socio-ecological expectations while considering reliable information provided by decision-makers (DMs).

Intellectual capital (IC) and venture capital (VC) play an important role in enterprise development. While the literature has investigated the relationship between IC and the profitability of companies, the relationship among IC, VC and enterprise value (EV) is still not well understood.

Drawing insights from the literature, we develop a few testable hypotheses about the relationships among IC, VC and EV. Using the panel data of companies listed in the Chinese stock market from 2009 to 2019, we employ fixed-effects regression models to test these hypotheses.

We find that IC has a significant positive effect on long-term EV. VC is found to have a positive direct effect on long-term EV but has a negative direct effect when its moderating effect with IC is considered. To explain this finding, we develop a simple economic model and provide an over-investment perspective.

We believe this paper can shed light on pro-venture investment policies in China, as well as provide indications for similar policies around the world.