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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.

The purpose of this study is to ascertain service quality (halal values, assurance, meal quality, reliability, security, system and traceability) and perceived risks (financial, quality, environment, social, time, psychology and health) and its influence on satisfaction, as well as trust concerning online halal food delivery system (OHFDS).

This study uses quantitative methodology, through an online survey, by using purposive sampling across a sample size of 423 respondents. The analysis of data was conducted using SmartPLS.

The results of the findings indicate that assurance and halal values have an influence on satisfaction, as well as trust; nonetheless, only reliability has an impact on satisfaction. On the other hand, perceived health and financial risks have negative influence on trust and satisfaction toward OHFDS. In addition, perceived psychological and financial risks are found to have negative impacts on trust of OHFDS.

The theoretical value of this study is the testing of perceived service quality and risks concerning OHFDS in the same model, thereby contributing to a deeper understanding of its impact on trust and satisfaction toward the online food service delivery industry. The results of this study may appear as a starting point for researchers who wish to conduct further studies on the same topic.

This study suggests that the service providers need to boost their efforts in establishing high quality service and, simultaneously, reduce perceived risks, to develop satisfaction and trust toward OHFDS.

The long-term consequence of the business's achievement is that it makes it simpler for customers to have confidence in, be satisfied with and recommend the service providers to others.

A number of research investigations have been conducted among Muslims, specifically in the Asian region, which have yielded crucial data regarding consumer behavior toward halal products, such as food and tourism. This study, nonetheless, remains close with other studies on halal food, except that it adds together the knowledge of perceived quality and risks, as to gain a deeper understanding of the experience customers have on food, through online service delivery.

This study aims to develop a measurement model of the halal supply chain resilience (HSCRES) index, which represents the capability of the supply chain (SC) to handle disruption caused by halal risks. A case study is conducted to apply the HSCRES index in the halal chicken SC in Yogyakarta, Indonesia, to test the proposed methodology.

A literature synthesis was conducted to establish the main capability and vulnerability factors and their relevant indicators. The indicators were validated using the confirmatory factor analysis approach. Then, applying an analytical hierarchy process involving ten experts – practitioners and academicians – the weight of each indicator was obtained. A survey of 20 employees of slaughterhouses, 35 sellers and 100 consumers was conducted to obtain the value of each indicator. Finally, the HSCRES index was calculated by comparing the total weighted capability value to vulnerability.

The results revealed that the resilience of halal chicken SC in Yogyakarta is at a good level, with an index of 3.459, and “halal team” is the most significant indicator. The findings also revealed several capabilities that need improvement, including dedicated halal facilities, employees’ halal competence and halal regulation. However, the lack of a halal certification board, lack of management commitment and packaging contamination were found as vulnerability indicators that need to be reduced.

The case of this study is limited to the halal chicken SC in Yogyakarta, Indonesia. As a consequence, the obtained results are limited to a specific context. The application of this method to different areas and objects enables the establishment of different capability and vulnerability indicators.

The halal resilience measurement model offers a comprehensive understanding of the strengths and weaknesses of the HSC. The findings can help stakeholders improve preparedness for halal risks, deal with halal risks better and recover more quickly. Measuring the HSCRES index can be particularly useful for policymakers in developing evidence-based strategies to increase HSCRES.

The current study is the first to define and classify the contributing halal resilience attributes and also to calculate the halal resilience index.

Reactive power in radial distribution networks (RDN) leads to detrimental effects like power factor degradation, voltage profile alterations and increased power losses, ultimately impacting network stability. This paper aims to present a novel two-phase optimization approach to address the challenging task of locating, sizing and determining the optimal number of capacitors in RDNs.

The first step of the proposed methodology is using a hybrid technique that combines the loss sensitivity factors (LSF) with voltage sensitivity factors (VSF) to identify network nodes requiring capacitor installation efficiently. The second step uses an external approximation technique to optimize the size and number of capacitors for each identified node, achieving significant power loss reductions.

The effectiveness of this new approach is evaluated on two RDNs: 33- and 69-bus. Simulations on these test systems demonstrate the effectiveness of the proposed approach, reducing total power loss by 34.7% in the first case and 35.3% in the second. The method’s robustness compared to other approaches further highlights its potential for practical implementation in RDNs, contributing to improved network stability and efficient power distribution.

This paper presents a novel, efficient and robust approach to determining the optimal number, location and size of an RDN capacitor. The problem is addressed through a new formulation with modified constraints. The method consists of two stages: initially, a hybrid LSF–VSF method identifies potential capacitor locations, followed by an external approximation-based mixed-integer nonlinear programming (MINLP) solver to optimize capacitor numbers and sizes. The proposed methodology is applied to the widely used 33-bus and 69-bus RDN test systems. Comparative analysis with existing methods highlights the proposed approach’s effectiveness. Key contributions of this study include the following: Proposes a new problem formulation with modified constraints. Proposes a novel two-stage framework for optimally locating and sizing capacitors in RDNs. Introduces a hybrid LSF–VSF algorithm to identify promising capacitor locations efficiently. Using an external approximation-based MINLP for optimal sizing. Demonstrates the effectiveness of the proposed approach through rigorous testing on standard benchmark systems. Provides a comprehensive comparative analysis against state-of-the-art methods, highlighting the proposed approach’s superior performance.