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Perpetrators of technology-facilitated gender-based violence are taking advantage of increasingly automated and sophisticated privacy-invasive tools to carry out their abuse. Whether this be monitoring movements through stalkerware, using drones to nonconsensually film or harass, or manipulating and distributing intimate images online such as deepfakes and creepshots, invasions of privacy have become a significant form of gender-based violence. Accordingly, our normative and legal concepts of privacy must evolve to counter the harms arising from this misuse of new technology. Canada's Supreme Court recently addressed technology-facilitated violations of privacy in the context of voyeurism in R v Jarvis (2019) . The discussion of privacy in this decision appears to be a good first step toward a more equitable conceptualization of privacy protection. Building on existing privacy theories, this chapter examines what the reasoning in Jarvis might mean for “reasonable expectations of privacy” in other areas of law, and how this concept might be interpreted in response to gender-based technology-facilitated violence. The authors argue the courts in Canada and elsewhere must take the analysis in Jarvis further to fully realize a notion of privacy that protects the autonomy, dignity, and liberty of all.

The potential applications of information and communication technologies in the workplace are wide-ranging and, especially since the COVID-19 pandemic, have increasingly found their way into the field of electronic performance monitoring (EPM) of employees. This study aims to examine the influence of EPM on individual performance considering the aspects of privacy invasion, organizational trust and individual stress within an organization. Thus, important insights are generated for academia as well as business.

A theoretical framework was developed which conceptualizes perceived EPM as independent variable and individual performance as dependent variable. Moreover, the framework conceptualizes three mediator variables (privacy invasion, organizational trust and individual stress). Based on a large-scale survey (N = 1,119), nine hypotheses were tested that were derived from the developed framework.

The results indicate that perception of EPM significantly increases privacy invasion, reduces organizational trust, increases individual stress and ultimately reduces individual performance. Moreover, it was found that privacy invasion reduces organizational trust and that this lowered trust increases individual stress. Altogether, these findings suggest that the use of EPM by employers may be associated with significant negative consequences.

This research enriches the literature on digital transformation, as well as human–machine interaction, by adopting a multidimensional theoretical and empirical perspective regarding EPM in the workplace context, in which the influence of EPM perceptions on individual performance is examined under the influence of different aspects (privacy invasion, organizational trust and individual stress) not currently considered in this combination in the literature.

This study aims to propose an innovative model that integrates variables and examines the influence of internet usage expertise, perceived risk and attitude toward information control on privacy concerns (PC) and, consequently, in consumers’ willingness to disclose personal information online. The authors also propose to test the mediation role of trust between PCs and willingness to disclose information. Trust is not a predictor of PC but a causal mechanism – considering that the focus is to understand consumers’ attitudes and behavior regarding the virtual environment (not context-specific) (Martin, 2018).

The authors developed a survey questionnaire based on the constructs that compose the proposed model to collect data from 864 respondents. The survey questionnaire included the following scales: internet usage expertise from Ohanian (1990); perceived risk, attitude toward information control, trust and willingness to disclose personal information online from Malhotra et al. (2004); and PC from Castañeda and Montoro (2007). All items were measured on a Likert seven-point scale (1 = totally disagree; 7 = totally agree). To obtain Westin’s attitudinal categories toward privacy, respondents answered Westin’s three-item privacy index. For data analysis, the authors applied covariance-based structural equation modeling.

First, the proposed model explains the drivers of consumers’ disposition to provide personal information at a level that surpasses specific contexts (Martin, 2018), bringing the analysis to consumers’ level and considering their general perceptions toward data privacy. Second, the findings provide inputs to propose a better definition of Westin’s attitudinal categories toward privacy, which used to be defined only by individuals’ information privacy perception. Consumers’ perceptions about their abilities in using the internet, the risks, their beliefs toward information control and trust also help to delimitate and distinguish the fundamentalists, the pragmatics and the unconcerned.

Some limitations weigh the theoretical and practical implications of this study. The sample size of pragmatic and unconcerned respondents was substantially smaller than that of fundamentalists. It might be explained by applying Westin’s self-report index to classify the groups according to their score regarding PCs. Most individuals affirm having a great concern for their data privacy but still provide online information for the benefit of personalization – known as the privacy paradox (Zeng et al., 2021). It leads to another limitation of this research, given the lack of measures that classify respondents by considering their actual behavior toward privacy.

PC emerges as an important predictor of consumer trust and willingness to disclose their data online, and trust also influences this disposition. Managers need to implement actions that effectively reduce consumers’ concerns about privacy and increase their trust in the company – e.g. adopting a clear and transparent policy on how the data collected is stored, treated, protected and used to benefit the consumer. Regarding the perception of risk, if managers convince consumers that the data collected on the internet is protected, they tend to be less concerned about privacy.

The results suggest different aspects influencing the willingness to disclose personal information online, including different responses considering consumers’ PCs. Through their policies and legislation, the authors understand that governments must be attentive to this aspect, establishing regulations that protect consumers’ data in the virtual environment. In addition to regulatory policies, education campaigns can be carried out for both consumers and managers to raise the discussion about privacy and the availability of information in the online environment, demonstrating the importance of protecting personal data to benefit the government, consumers and organizations.

Although there is increasing research on consumers’ privacy, studies have not considered their attitudinal classifications – high, moderate and low concern – as moderators of willingness to disclose information online. Researchers have also increased attention to the antecedents of PCs and disclosure of information but overlooked possible mechanisms that explain the relationship between them.

The purpose of the present article is to highlight the role of Artificial Intelligence (AI) and Robotics in the tourism industry. The various technologies being integrated to improve the service and customer experience in tourism. The expected changes and challenges in tourism in the future are focused in this paper.

A systematic study on the emerging technologies of AI and Robotics applied in the tourism sector is presented in the form of a viewpoint.

AI certainly enhances tourism experiential services however cannot surpass the human touch which is an essential determinant of experiential tourism. AI acts as an effective complementary dimension to the future of tourism. With the emergence of artificial travel intelligence, it is simpler to make travel arrangements. AI offers travel services that are automated, customized and insightful. AI allows travelers to learn about their behaviors, interests to inclinations and provide a personalized experience. Gone are the days to consult a travel agent, meet him physically and indulge in an endless chain of troubling phone calls to inquire about travel arrangements.

Tourism marketing to see a positive and improved change that will enhance the tourists’ overall experience due to the application of AI and Robotics. New emerging technologies like chatbots, virtual reality, language translators, etc. can be effectively applied in Travel, Tourism & Hospitality industry.

The present viewpoint discusses the application and role of AI and Robotics with the help of relevant industry examples and theory. The present paper highlights the different technologies being used and will be used in the future.

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 at investigating the extent of SysTrust’s framework (principles and criteria) as an internal control approach for assuring the reliability of accounting information system (AIS) were being implemented in Jordanian business organizations.

The study is based on primary data collected through a structured questionnaire from 239 out of 328 shareholdings companies. The survey units were the shareholding companies in Jordan, and the single key respondents approach was adopted. The extents of SysTrust principles were also measured. Previously validated instruments were used where required. The data were analysed using t-test and ANOVA.

The results indicated that the extent of SysTrust being implemented could be considered to be moderate at this stage. This implies that there are some variations among business organizations in terms of their level of implementing of SysTrust principles and criteria. The results also showed that the extent of SysTrust principles being implemented was varied among business organizations based on their business sector. However, there were not found varied due to their size of business and a length of time in business (experience).

This study is only conducted in Jordan as a developing country. Although Jordan is a valid indicator of prevalent factors in the wider MENA region and developing countries, the lack of external validity of this research means that any generalization of the research findings should be made with caution. Future research can be orientated to other national and cultural settings and compared with the results of this study.

The study provides evidence of the need for management to recognize the importance of the implementation of SysTrust principles and criteria as an internal control for assuring the reliability of AIS within their organizations and be aware which of these principles are appropriate to their size and industry sector.

The findings would be valuable for academic researchers, managers and professional accounting to acquire a better undemanding of the current status of the implementation of the SysTrust principles (i.e., availability, security, integrity processing, confidentiality, and privacy) as an internal control method for assuring the reliability of AIS by testing the phenomenon in Jordan as a developing country.

Coronavirus Disease 2019 (COVID-19) necessitated the need for “Hospital-at-home” improvisations that involve wearable technology to classify patients within households before visiting health institutions. Do-It-Yourself wearable devices allow for the collection of health data leading to the detection and/or prediction of the prevalence of the disease. The sensitive nature of health data requires safeguards to ensure patients’ privacy is not violated. The previous work utilized Hyperledger Fabric to verify transmitted data within Smart Homes, allowing for the possible implementation of legal restrictions through smart contracts in the future. This study aims to explore privacy-enhancing authentication schemes that are operated by multiple credential issuers and capable of integration into the Hyperledger ecosystem.

Design Science Research is the methodology that was used in this study. An architecture for ABC-privacy was developed and evaluated.

While the privacy-by-design architecture enhances data privacy through edge and fog computing architecture, there is a need to provide an additional privacy layer that limits the amount of data that patients disclose. Selective disclosure of credentials limits the number of information patients or devices divulge.

The evaluation of this study identified Coconut as the most suitable attribute-based credentials scheme for the Smart Homes Patients and Health Wearables use case Coconut user-centric architecture Hyperledger integration multi-party threshold authorities public and private attributes re-randomization and unlinkable revelation of selective attribute revelations.

This chapter focusses on the ethical issues raised by different types of surveillance and the varied ways in which surveillance can be covert. Three case studies are presented which highlight different types of surveillance and different ethical concerns. The first case concerns the use of undercover police to infiltrate political activist groups over a 40-year period in the UK. The second case study examines a joint operation by US and Australian law enforcement agencies: the FBI’s operation Trojan Shield and the AFP’s Operation Ironside. This involved distributing encrypted phone handsets to serious criminal organisations which included a ‘backdoor’ secretly sending encrypted copies of all messages to law enforcement. The third case study analyses the use of emotional artificial intelligence systems in educational digital learning platforms for children where technology companies collect, store and use intrusive personal data in an opaque manner. The authors discuss similarities and differences in the ethical questions raised by these cases, for example, the involvement of the state versus private corporations, the kinds of information gathered and how it is used.

This study aims to explore US hotel guests’ privacy concerns with a twofold aim as follows: to investigate the privacy categories, themes and attributes most commonly discussed by guests in their reviews and to examine the influence of cultural proximity on privacy concerns.

This study combined automated text analytics with content analysis. The database consisted of 68,000 hotel reviews written by US guests lodged in different types of hotels in five European cities. Linguistic Inquiry Word Count, Leximancer and SPSS software were used for data analysis. Automated text analytics and a validated privacy dictionary were used to investigate the reviews by exploring the categories, themes and attributes of privacy concerns. Content analysis was used to analyze the narratives and select representative snippets.

The findings revealed various categories, themes and concepts related to privacy concerns. The two most commonly discussed categories were privacy restriction and outcome state. The main themes discussed in association with privacy were “room,” “hotel,” “breakfast” and several concepts within each of these themes were identified. Furthermore, US guests showed the lowest levels of privacy concerns when staying at American hotel chains as opposed to non-American chains or independent hotels, highlighting the role of cultural proximity in privacy concerns.

Hotel managers can benefit from the results by improving their understanding of hotel and service attributes mostly associated with privacy concerns. Specific suggestions are provided to hoteliers on how to increase guests’ privacy and on how to manage issues related to cultural distance with guests.

This study contributes to the hospitality literature by investigating a neglected issue: on-site hotel guests’ privacy concerns. Using an unobtrusive method of data collection and text analytics, this study offers valuable insights into the categories of privacy, the most recurrent themes in hotel guests’ reviews and the potential relationship between cultural proximity and privacy concerns.

The purpose of this study is to empirically investigate the relationship between a set of functional and social–psychological barriers and bank customers’ intention to fully adopt digital payment methods (DPMs).

The data were collected via an online questionnaire sent to two samples of Swedish bank customers, namely, adopters-accepters (i.e. young bank customers) and adopters-resisters (i.e. a group opposing a cashless society). Hypotheses were tested by applying an ordinal regression model.

Regarding the adopters-accepters, privacy and access barriers can be obstacles to the full adoption of DPMs. The adopters-resisters perceived all five studied barriers as significant, though only the impersonalisation barrier seemed to matter when the barriers were related to their intention to fully adopt DPMs. Moreover, the results suggest that barriers have a stronger negative effect on the intention to fully adopt among those with extensive experience of DPMs.

Based on the barriers affecting the intention of particular groups of bank customers to adopt DPMs, banks could implement customised measures to promote the ongoing development of digital financial services.

In this under-researched area, this study provides empirical knowledge of the influence of various barriers on the intention of bank customers characterised as adopters-accepters and adopters-resisters to fully adopt DPMs.