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This chapter delves into how smart city innovations positively affect workforce efficiency, residents’ quality of life (QoL), and the delivery of services, particularly within the dynamic context of smart cities: innovation, development, transformation, and prosperity. It discusses the role of technologies like cyber-physical systems, the Internet of Things, and intelligent transport systems in creating efficient, sustainable urban spaces that benefit the workforce and the broader community. The chapter highlights strategies for improving urban environments, ensuring workforce well-being, and fostering sustainable growth by examining the interplay between these technologies and urban living. The narrative emphasizes the necessity of ongoing innovation, policy support, and workforce adaptation, underscoring the importance of tailoring smart city initiatives to regional needs for maximal impact on employee performance, QoL, and service delivery. Additionally, it introduces a comprehensive framework designed to guide the development of next-generation smart cities. This framework integrates advanced technologies for optimized urban management and service provision, directly linking to enhanced employee performance through improved urban infrastructure and services. The strategic application of this framework aims to elevate economic prosperity and societal well-being, ensuring workforce efficiency is central to the urban development agenda. The enhanced employee performance, catalyzed by smart city innovations, is pivotal in driving economic vibrancy, social inclusivity, and environmental sustainability, shaping the future of urban development. This analysis will offer valuable insights for smart cities research and development in the Gulf Region, suggesting pathways for implementing these concepts to address the region’s urbanization and development challenges.

This paper aims to conduct an in-depth analysis of the shortcomings of apps’ privacy policies and to propose improvement and optimization strategies, which are of great significance for establishing a transparent and responsible privacy protection framework that ensures compliant collection and use of users’ information and effective protection of their privacy.

This paper obtained privacy policy texts for 100 shopping apps through Web crawlers and manual downloads. Based on the perspective of perceived usefulness, thematic analysis is conducted through the latent Dirichlet allocation topic model and comparison with existing policies. Based on the perspective of perceived ease of use, readability analysis is conducted through content analysis and formula calculation.

The apps privacy policies can be divided into seven themes. The authors benchmark these seven topics with the Personal Information Protection Law of the People’s Republic of China, the E-Commerce Law of the People’s Republic of China and the General Data Protection Regulation. It is found that there are omissions in the information collection and use and juvenile protection of the existing apps. Through the indicators’ readability analysis and calculation, it is found that the existing apps privacy policies have good performance in the readability indicators such as naming method, frame directory and so on. However, text personalization and text readability need to be improved and optimized.

At the theoretical level, this paper constructs a model from the dual perception perspectives of perceived usefulness and perceived ease of use and analyses the apps’ privacy policy texts at a fine-grained level. At the practical level, based on large-scale apps’ privacy policy text data, this paper conducts multi-dimensional research from theme analysis, authoritative law benchmarking analysis, content analysis and text readability calculation and analysis. At the same time, this paper identifies the current problems of apps’ privacy policies and puts forward countermeasure suggestions for their content improvement and optimization.

Financial market sustainability is gaining attention as investors and stakeholders become more aware of environmental, social and governance issues, pushing demand for responsible and ethical investment practices. Therefore, this study aims to investigate the impact of carbon (CO2) emissions from three sources, oil, gas and coal, on the stock market sustainability via effective government policies.

The eight countries belong to two different regions of world: Asian economies such as Pakistan, India, Malaysia and China, and OECD economies such as Germany, France, the UK and the USA are selected as a sample of the study. The 22-year data from 2000 to 2022 are collected from the DataStream and the World Bank data portal for the specified countries. The generalized methods of movement (GMM) and wavelet are used as the econometric tool for the analysis.

Our findings show that the CO2 emission from coal and gas significantly negatively impacts stock market sustainability, but CO2 emission from oil positively impacts stock market sustainability. Moreover, all the emerging Asian economies’ CO2 emissions from coal and gas have a much greater significant negative impact on the stock market sustainability than the OECD countries due to the critical situation. However, the government’s effective policies have a positive significant moderating impact between them, reducing the effect of CO2 emission on the stock market.

This study advocated strong implications for policymakers, governments and investors.

Effective government policies can protect the environment and make business operations suitable, leading to market financial stability. This study advocated strong implications for policymakers, governments and investors.

This study provides fresh evidence of the government’s effective role to control the carbon environment that provide the sustainability to the organizations with respect to OECD and emerging economy.

Blockchain (BC) has recently gained attention from educational organizations as a reliable and trustworthy technology for storing crucial data. This study aims to explore the factors that influence the students’ intention to use BC to host an automated reward system that is based on objective criteria of students’ performance and activities. Predefined smart contracts would guarantee unbiased judgements and fair rewards.

A mixed method approach is used. Based on an iterative rounds of Delphi approach along with a comprehensive literature review, this research proposed an extended Unified Theory of Acceptance and Use of Technology model. The model hypotheses relate performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), perceived innovativeness (PI), trust (TR), perceived security and privacy (S&P), complexity (CX) and enjoyment (EN) to students behavioural intention to use the reward system. The study tests the hypotheses using survey data from 138 students who are familiar with BC technology and its applications. The data analysis is performed using partial least squares-structural equation modelling method.

The analysis revealed that PE, EE, PI, TR and EN positively affect students’ intention to use the BC rewarding system, while CX negatively impacts it. Conversely, FC and, interestingly, S&P, which showed a significant influence on trust, were found to be insignificant in influencing students’ intention to use the system.

This study significantly contributes to the educational technology field by addressing research gaps regarding the adoption and acceptance of BC technology in academia. Firstly, it proposes a basic form of a student reward system. Secondly, it introduces an empirically validated model of students’ adoption, pinpointing factors influencing their readiness to embrace a BC reward system and providing practical implementation insights.

Cement plays a significant part in concrete, and with the increasing demand for concrete, cement output varies day by day, allowing production to carbon dioxide emissions. As well as marble processing creates stone slurry and solid discards. These are often dumped irresponsibly on open land, polluting the soil. This improper disposal of marble waste is a major environmental concern. This study aims to propose a sustainable solution for reusing this waste material as a concrete additive.

A total of 135 concrete cubes of size 150 × 150 × 150 mm, 54 concrete cylinders of size 150 mm dia. and 300 mm height and 54 concrete beams of size 150 × 150 × 700 mm were cast. The replacement was 0%, 2.5%, 5%, 7.5%, 10%, 12.5%, 15%, 17.5% and 20% by weight of cement with marble dust to create M30 concrete with a water-cement ratio of 0.45. The test was performed to find the compressive strength (CS), flexural strength (FS) and split tensile strength. Also, durability tests like rapid chloride penetration test (RCPT), acid attack, ultrasonic pulse velocity (UPV) and water permeability test were performed.

After 7 and 28 days of curing, it was found that replacing 5% of cement with marble powder led to an initial strength improvement of up to 25% for both curing periods. However, further increases in marble dust resulted in an inconsistent decrease in strength for all the mixtures. Also, durability properties like acid attack test, water permeability test and RCPT, showed good performance at the optimum percentage of waste marble powder (WMP) as cement replacement. The microscopic analysis revealed a denser pore structure at lower WMP replacement levels, likely due to the powder filling in gaps.

This study reveals that by substituting 5% (optimum) of cement with WMP, there was CS improvement up to 8.4% and 17% for both 7 and 28 days of curing. WMP is typically finer than cement particles and fills the voids in the concrete more effectively, resulting best performance at optimum percentage against RCPT, UPV, acid attack and water permeability.

Advancements in enhancing regional port connectivity are crucial to fostering global maritime transport. The objective of this paper is to explore the complex relationship between infrastructure connectivity and the regional port of Thailand, specifically within the Regional Comprehensive Economic Partnership (RCEP).

This paper utilised fuzzy logic in exploratory factor analysis and introduced a new factor based on shipping networks, port operations, trade and emerging innovations. This can enhance the regional port and facilitate infrastructure connectivity in the RCEP. The results of this study have been successfully applied in specific contexts involving port authorities and private shipping companies.

The study’s findings indicate key factors for enhancing regional ports in Thailand. These factors include integrating connectivity, creating spare hubs, addressing service issues, optimising logistics and supply chains, considering market components and leveraging the digital market. These factors are also crucial for promoting infrastructure connectivity within the RCEP framework.

This research presents a strategic framework for enhancing regional ports in Thailand and improving international infrastructure. This is the first attempt to examine the influence of infrastructure connectivity on regional ports by applying fuzzy exploratory factor analysis to modernise infrastructure, which is key to unlocking the region’s maritime potential.

This study aims to examine the cutting performance of a coated carbide tool during the boring of 1Cr17Ni2 martensitic stainless steel, with a focus on how the tool’s structural parameters, particularly the nose radius, affect the wear patterns, wear volume and lifetime of the cutting tool, and related mechanisms.

A full factorial boring experiment with three factors at two levels was conducted to analyze systematically the impact of cutting parameters on the tool wear behavior. The evolution of tool wear over the machining time was recorded, and the influences of the cutting parameters and nose radius on wear behavior of the tool were examined.

The results show that higher cutting parameters lead to significant wear or plastic deformation at the tool nose. When the cutting depth is less than the nose radius, the tool wear tends to be minimized. Larger nose radius tools have weaker chip-breaking but greater strength and wear resistance. Higher cutting parameters reduce wear for the tools with larger nose radius, maintaining their integrity. Wear mechanisms are primarily abrasive, adhesive and diffusion wear. Furthermore, the full-factorial analysis of variance revealed that for the tool with r_ε = 0.4 mm and 0.8 mm, the factors contributing the most to tool wear were cutting speed (38.76%) and cutting depth (86.43%), respectively.

This study is of great significance for selection of cutting tools and cutting parameters for boring 1Cr17Ni2 martensitic stainless-steel parts.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0266/

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

In this paper, the authors aim to study the relationship between hydrogen embrittlement (HE) susceptibility and cathodic current density applied on the X70 steel girth welds.

The HE susceptibility of X70 steel girth welds were investigated through slow strain rate tensile test and observed and analyzed by optical microscope and scanning electron microscope methods.

The results show that HE susceptibility of X70 girth weld was basically unchanged with increasing of ion concentration while gradually increased and maintain at a specific value with the increase of cathodic current density. As for same ion content, a dense calcareous deposit layer generated on the sample surface in soil simulation solution with Ca2+ and Mg2+ resulted a decreased HE susceptibility while the porous calcareous deposit layer resulted a increased HE susceptibility.

A logistic regression model was established to describe the correlation between HE index and the cathodic current density.

This study aims to understand how product attributes (object stimuli), social influences (social-psychological stimuli) and internal factors (internal stimuli) contribute to Chinese Generation Z’s purchase intentions (responses) for new Chinese style apparel (NCSA) through NCSA attitudes (cognitive state) and cultural pride (affective state) based on the stimulus-organism-response (S-O-R) model.

Data were collected from 989 respondents aged between 18 and 29 years through self-administrated questionnaires via a professional survey panel, Credamo, in China. Data were analyzed using structural equation modeling.

Results showed that among the seven stimuli, NCSA’s design, online social networking communities, cultural identity and personal norms significantly influenced Generation Z’s purchase intentions through both NCSA attitudes and cultural pride. Further, NCSA’s cultural connotations and celebrity influences elicited purchase intentions merely through the affective state – cultural pride. In contrast, NCSA’s functionality did not have a significant influence on NCSA attitudes and adversely affected cultural pride.

This study fills the research gap and extends the application of the S-O-R model within the NCSA context. The findings of this study shed light on the practical implications for marketers, brands and policymakers with regard to a better understanding of Chinese Generation Z’s NCSA consumption.