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As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

The purpose of this study is to understand user perceptions and misconceptions regarding security tools. Security and privacy-preserving tools (for brevity, the authors term them as “security tools” in this paper, unless otherwise specified) are designed to protect the security and privacy of people in the digital environment. However, inappropriate use of these tools can lead to unexpected consequences that are preventable. Hence, it is significant to examine why users do not understand the security tools.

The authors conducted a qualitative study with 40 participants in the USA to investigate the prevalent misconceptions of people regarding security tools, their perceptions of data access and the corresponding impact on their usage behavior and data protection strategies.

While security vulnerabilities are often rooted in people’s internet usage behavior, this study examined user’s mental models of the internet and unpacked how the misconceptions about security tools relate to those mental models.

Based on the findings, this study offers recommendations highlighting the design aspects of security tools that need careful attention from researchers and industry practitioners, to alleviate users’ misconceptions and provide them with accurate conceptual models toward the desired use of security tools.

Cyber-attacks that generate technical disruptions in organisational operations and damage the reputation of organisations have become all too common in the contemporary organisation. This paper explores the reputation repair strategies undertaken by organisations in the event of becoming victims of cyber-attacks.

For developing the authors’ contribution in the context of the Internet service providers' industry, the authors draw on a qualitative case study of TalkTalk, a British telecommunications company providing business to business (B2B) and business to customer (B2C) Internet services, which was a victim of a “significant and sustained” cyber-attack in October 2015. Data for the enquiry is sourced from publicly available archival documents such as newspaper articles, press releases, podcasts and parliamentary hearings on the TalkTalk cyber-attack.

The findings suggest a dynamic interplay of technical and rhetorical responses in dealing with cyber-attacks. This plays out in the form of marshalling communication and mortification techniques, bolstering image and riding on leader reputation, which serially combine to strategically orchestrate reputational repair and stigma erasure in the event of a cyber-attack.

Analysing a prototypical case of an organisation in dire straits following a cyber-attack, the paper provides a systematic characterisation of the setting-in-motion of strategic responses to manage, revamp and ameliorate damaged reputation during cyber-attacks, which tend to negatively shape the evaluative perceptions of the organisation's salient audience.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.

This study aims to argue that user’s continued use behavior is contingent upon two perceptions (i.e. the app and the provider). This study examines the moderating effects of user’s perceptions of apps and providers on the effects of security and privacy concerns and investigate whether assurance mechanisms decrease such concerns.

This study conducts a scenario-based survey with 694 mobile cloud computing (MCC) app users to understand their perceptions and behaviors.

This study finds that while perceived value of data transfer to the cloud moderates the effects of security and privacy concerns on continued use behavior, trust only moderates the effect of privacy concerns. This study also finds that perceived effectiveness of security and privacy intervention impacts privacy concerns but does not decrease security concerns.

Prior mobile app studies mainly focused on mobile apps and did not investigate the perceptions of app providers along with app features in the same study. Furthermore, International Organization for Standardization 27018 certification and privacy policy notification are the interventions that exhibit data assurance mechanisms. However, it is unknown whether these interventions are able to decrease users’ security and privacy concerns after using MCC apps.

The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

Consumers frequently use electronic payments (e-payment) as their first step into formal financial services. The advancement of information and communication technology, on the other hand, has resulted in several achievements for human civilization, altering people’s lives, behaviors and societal measures. This study’s main aim is to investigate issues and identify the factors that are likely to influence customers’ acceptance of implementing e-payment in the Kingdom of Bahrain.

A quantitative research approach was adopted to test the influence of e-payment data security, trust, ease of use, usefulness and accessibility on customers’ acceptance of the service. A questionnaire survey was electronically administered to a purposive sample, and 531 responses were returned, achieving the required sample size for the study. Descriptive statistics analysis was used to ascertain data validity and consistency, and regression analysis was used to test the model’s hypotheses.

The findings of this study demonstrated a high influence of the mentioned factors on the e-payment acceptance of the customers in the Kingdom of Bahrain. The main recommendations are to increase the adoption of e-payment; focus highly on the security factor in e-payment adoption; create a trustworthy e-payment service; strive to make the e-payment services more user-friendly; increase the longevity of the e-payment services by focusing on usefulness; and make e-payment services more accessible.

This study’s potential contribution is to identify the factors that influence e-payment acceptance by customers in Bahrain and draw attention to issues to be considered in adopting new e-payment services.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

The purpose of this study is to explore a theoretical model using the unified theory of acceptance and use of technology framework by adding Islamic compliance (IC) and security assurance to build antecedents of intention to use Islamic internet-only banks (IIOBs) in Muslim youth.

This study involved 262 Muslim youths from several Islamic communities in Indonesia. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). Moreover, PLS techniques such as the variance accounted for (VAF) were used to verify the statistical analysis of findings.

The findings show that effort expectancy (EE) and online social influences (OSI) strongly correlate with the intention to use IIOBs. In addition, user reviews (online reviews) are proven to form a solid social influence and impact consumer decision-making. Finally, IC and security assurance are still critical factors in the IIOBs acceptance.

Practically, IIOB providers need to strengthen information about performance, accessibility, security and benefits when running service applications. Providers must show their strengths and advantages compared to the traditional banks in various service lines. Besides, providers are expected to be more careful regarding IC applications in their products and services.

This study considers the effects of OSI, EE, security and IC as the unique characteristics of Muslim youth in using the IIOBs. In particular, the significance of IC and OSIs provides a valid picture of the pathways of acceptance creation towards IIOBs.