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The purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.

A smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.

The main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.

The hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

Purpose – In order to explore how gender and sexual politics are played out in everyday practice within both the extreme right and jihadi-Salafist movements online, this chapter analyzes the content of two women’s only forums: The Women’s Forum on Stormfront.org and Women Dawah, a Turkish language pro-IS group chat on Telegram.

Methodology – The Women’s Forum and the Women Dawah data sets were analyzed using structural topic modeling to uncover the differences and similarities in salient topics between White Nationalist and Islamic State women-only forums.

Findings – The cross-ideological and multi-linguistic thematic analysis suggests that the safety of online spaces enables women to be more active, and serves digital support network for like-minding individuals. It also highlights that religion and ideology, whilst interwoven throughout posts on both platforms, they were more explicitly discussed within Women Dawah data.

Originality/Value – This research uses a unique data set which was collected over one year to conduct a cross-ideological and multi-linguistic thematic analysis, a relatively uncommon approach.

Blockchain technology, renowned for its decentralization, security, reliability, and data integrity, has the potential to revolutionize businesses globally. However, its full potential remains unrealized due to adoption barriers, necessitating further studies to address these challenges. Identifying these barriers is crucial for businesses and practitioners to effectively tackle them. This systematic review analyzed 70 eligible studies out of 1944 gathered from various databases to understand and identify common blockchain adoption barriers. The Technology–Organization–Environment (TOE) framework was the most popular theory used in these studies. Despite differences in variable definitions, financial constraints, lack of stakeholder collaboration and coordination, and social influences like resistance to change and negative perceptions emerged as the top three barriers. The supply chain domain had the highest number of studies on blockchain adoption. Notably, there was a significant increase in studies addressing blockchain adoption in 2023, comprising 34.2% of the total reviewed studies. This review provides a comprehensive overview of identified barriers, serving as a valuable foundation for future research. Understanding these challenges allows researchers to design targeted studies aimed at developing solutions, strategies, and innovations to overcome obstacles hindering blockchain adoption.

This paper introduces a solution for employing intrusion detection technology across organisational boundaries by using knowledge grid technology.

Employment of intrusion detection technology is currently limited to inside organisation deployments. By setting up communities, which maintain trust relationships between network nodes anywhere in the internet, security event data, structured into a common XML‐based format, can be exchanged in a secure and reliable manner.

A modular architecture has been developed which provides functionality to integrate different audit data generating applications and share knowledge about incidents, vulnerabilities and countermeasures from all over the internet. A security policy, based on the Chinese Wall Security Policy, ensures the protection of information inserted into the network.

The solution is currently in a preliminary stage, providing the description of the design only. Implementation as well as evaluation is under development.

Trusting communities everywhere in the internet will be brought into being so that people may establish trust relationships between each other. Participants may decide themselves whom they trust as a source for security‐related information rather than depending on centralised approaches.

No approach is known combining the two technologies – intrusion detection and grid – as described in this paper. The decentralised, peer‐to‐peer based grid approach together with the introduction of trust relationships and communities results in a new way of thinking about distributing security audit data.

The potential measurements in NaCl solutions of varying concentrations carried out separately on galvanised steel and aluminised steel, each coupled galvanically with mild steel, have shown continuous rise of potential with increase in the concentration of NaCl in both the cases. For the aluminised steel‐mild steel couple, the protective potential of −760 mV is reached close to the NaCl concentration of 2%, while the potential in the case of galvanised steel‐mild steel couple has always been above the protective potential, right from the beginning, within the concentration range of NaCl (upto 3%) studied. The current and potential measurements in 0.1% NaCl solution have shown that the resistance of the surface film on aluminised steel grows from 1.037 ×103 ohm to 5.500×103 ohm within the test duration ranging from 20 hours to 100 hours and that on the galvanised steel increases from 0.90×103 ohm to 2.307×103 ohm within the test span ranging from 30 hours to 100 hours. The low current found to have been associated with the aluminised steel‐mild steel couple is not sufficient to bring the potential at the required protective level for the protection, while about 4 times higher current measured in the galvanised‐mild steel couple helps it in attaining the protective potential.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.

This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.

The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.

While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.

Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.

Blockchain technology (BT) presents a decentralized approach that has promising potentials to alleviate many of the long-lasting risks and inefficiencies in trade finance (TF) and supply chain finance (SCF) operations, providing international traders greater access to working capital. Despite this, the actual adoption of the technology and related issues in this space has remained under-researched. This paper examines the state of the practice to identify the main drivers and inhibitors faced by TF/SCF parties in their BT adoption efforts.

This exploratory study applies a multi-stakeholder perspective and a mixed-methods approach using semi-structured interviews with practitioners in various stages of BT implementation in TF/SCF initiatives across North America, Europe and Asia. The study then determines the priority of the identified factors using the Bayesian best-worst method (BWM).

The findings show that while the discussion has focused on the technological drivers of BT adoption for TF/SCF, practitioners rely more on non-technological factors such as peer adoption and fostering innovation. The findings also reveal how practitioners address common BT issues, including scalability and interoperability.

The study offers insights into important requirements for realizing the full benefits of BT in support of TF and SCF from an extended technology-organization-environment (TOE) perspective. On a more general level, it highlights what is required to transform this industry toward digitization.

Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.

A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.

The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.

The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.

The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.