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Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpose of this research is to explore the perceptions of the UK digital contact tracing app in the Black, Asian and Minority Ethnic (BAME) community in Leicester and how this can affect its deployment and implementation.

Data was collected through virtual focus groups in Leicester, UK. A total of 28 participants were recruited for the study. All participants are members of the BAME community, and data was thematically analysed with NVivo 11.

A majority of the participants were unwilling to download and use the app owing to legal and ethical concerns. A minority were willing to use the app based on the need to protect public health. There was a general understanding that lack of uptake will negatively affect the fight against COVID-19 in BAME communities and an acknowledgement of the need for the government to rebuild trust through transparency and development of regulatory safeguards to enhance privacy and prevent misuse.

To the best of the authors’ knowledge, the research makes original contributions being the first robust study conducted to explore perceptions of marginalised communities, particularly BAME which may be adversely impacted by the deployment of the app. By exploring community-based perceptions, this study further contributes to the emerging citizens’ perceptions on digital contact tracing which is crucial to the effectiveness and the development of an efficient, community-specific response to public attitudes towards the app. The findings can also help the development of responsible innovation approaches that balances the competing interests of digital health interventions with the needs and expectations of the BAME community in the UK.

Privacy is a sensitive issue in business because it involves how a platform uses consumer personal data. In terms of consumer rights, personal information needs to be protected in the privacy policy (PP). This study describes several aspects of the PP that consumers need to pay attention to, especially points prone to misuse of personal information.

This research used a taxonomy of consumer privacy concerns in e-commerce to reveal general and specific privacy concerns. The privacy calculus theory was also applied to explore consumer rationalization using (1) consumer knowledge about PP, (2) subjective perception, and (3) proximity to the PP features. Furthermore, the netnographic approach was used to combine the interrelation between technology and social construction. A sample of 378 young consumers in several major cities in Indonesia participated online and offline. Semi-structured interviews were also conducted to gain more in-depth comprehension.

The results showed that most young consumers have sufficient basic knowledge of the important points of PP. Furthermore, they tend not to read the PP because it is long and cumbersome, and therefore do not wish to expend much cognitive effort on it.

This study provides several results that can be utilized by policymakers or e-commerce companies to pay more attention to PPs for young groups. In addition, e-commerce companies can increase the knowledge of the privacy situation of Internet users in general.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0740

The chapter deliberates on research ethics and the unanticipated side effects that technological developments have brought in the past decades. It looks at data protection and privacy through the prism of ethics and focuses on the need for safeguarding the fundamental rights of the research participants in the new digital era. Acknowledging the benefits of data analytics for boosting scientific process, the chapter reflects on the main principles and specific research derogations, introduced by the EU General Data Protection Regulation. Further on, it discusses some of the most pressing ethics concerns, related to the use, reuse, and misuse of data; the distinction between publicly available and open data; ethics challenges in online recruitment of research participants; and the potential bias and representativeness problems of Big Data research. The chapter underscores that all challenges should be properly addressed at the outset of research design. Highlighting the power asymmetries between Big Data studies and individuals’ rights to data protection, human dignity, and respect for private and family life, the chapter argues that anonymization may be reasonable, yet not the ultimate ethics solution. It asserts that while anonymization techniques may protect individual data protection rights, the former may not be sufficient to prevent discrimination and stigmatization of entire groups of populations. Finally, the chapter suggests some approaches for ensuring ethics compliance in the digital era.

It is well‐known that the primary threat against misuse of private data about individuals is present within the organisation; proposes a system that uses intrusion detection system (IDS) technologies to help safeguard such private information. Current IDSs attempt to detect intrusions on a low level whereas the proposed privacy IDS (PIDS) attempts to detect intrusions on a higher level. Contains information about information privacy and privacy‐enhancing technologies, the role that a current IDS could play in a privacy system, and a framework for a privacy IDS. The system works by identifying anomalous behaviour and reacts by throttling access to the data and/or issuing reports. It is assumed that the private information is stored in a central networked repository. Uses the proposed PIDS on the border between this repository and the rest of the organisation to identify attempts to misuse such information. A practical prototype of the system needs to be implemented in order to determine and test the practical feasibility of the system. Provides a source of information and guidelines on how to implement a privacy IDS based on existing IDSs.

Describes how the Office of Strategic Crime Assessments (OSCA) and the Victoria Police Computer Crime Investigation Squad conducted the 1997 Computer Crime and Security Survey in order to establish some reliable base‐line information regarding the extent of computer‐related crime in Australia today. A representative sample of over 300 Australian companies was surveyed. Of the respondents, 37 per cent had experienced some form of intrusion or other unauthorised use of computer systems in the last 12 months. Nearly 90 per cent of those that had experienced computer‐related incidents had been subjected to attacks from sources internal to their own organisation. Over 60 per cent were subjected to intrusions from external sources (meaning that a significant number of companies had been subjected to attacks from both employees and outsiders). States that the results of this study empirically support many elements of the anecdotal evidence and highlights a number of issues for Australian law enforcement.

General Data Protection Regulation (GDPR) of the European Union (EU) was passed to protect data privacy. Though the GDPR intended to address issues related to data privacy in the EU, it created an extra-territorial effect through Articles 3, 45 and 46. Extra-territorial effect refers to the application or the effect of local laws and regulations in another country. Lawmakers around the globe passed or intensified their efforts to pass laws to have personal data privacy covered so that they meet the adequacy requirement under Articles 45–46 of GDPR while providing comprehensive legislation locally. This study aims to analyze the Malaysian and Saudi Arabian legislation on health data privacy and their adequacy in meeting GDPR data privacy protection requirements.

The research used a systematic literature review, legal content analysis and comparative analysis to critically analyze the health data protection in Malaysia and Saudi Arabia in comparison with GDPR and to see the adequacy of health data protection that could meet the requirement of EU data transfer requirement.

The finding suggested that the private sector is better regulated in Malaysia than the public sector. Saudi Arabia has some general laws to cover health data privacy in both public and private sector organizations until the newly passed data protection law is implemented in 2024. The finding also suggested that the Personal Data Protection Act 2010 of Malaysia and the Personal Data Protection Law 2022 of Saudi Arabia could be considered “adequate” under GDPR.

The research would be able to identify the key principles that could identify the adequacy of the laws about health data in Malaysia and Saudi Arabia as there is a dearth of literature in this area. This will help to propose suggestions to improve the laws concerning health data protection so that various stakeholders can benefit from it.

The purpose of this study is to explore the negative consequences of human resource analytics applications using the privacy calculus approach.

By using the existing literature and privacy calculus theory, a theoretical model has been developed. This model helps to examine the benefits and risks associated with HR analytics applications. The theoretical model was validated using the partial least square structural equation modeling (PLS-SEM) technique with 315 respondents from different organizations.

HR analytics provides multiple benefits to employees and organizations. But employee privacy may be compromised due to unauthorized access to employee data. There are also security concerns about the uncontrolled use of these applications. Tracking employees without their consent increases the risk. The study suggests that appropriate regulation is necessary for using HR analytics.

This study is based on cross-sectional data from a specific region. A longitudinal study would have provided more comprehensive results. This study considers five predictors, including other boundary conditions that could enhance the model’s explanative power. Also, data from other countries could improve the proposed model.

The proposed model is useful for HR practitioners and other policymakers in organizations. Appropriate regulations are important for HR analytics applications. The study also highlights various employee privacy and security-related issues emerging from HR analytics applications. The study also discusses the role of leadership support for the appropriate usage of HR analytics.

Only a few research studies have explored the issues of HR analytics and its consequences. The proposed theoretical model is the first to consider the negative consequence of HR analytics through privacy calculus theory. In this perspective, the research is considered to be novel.

Factor analysis is the most used tool in organizational research and its widespread use in scale validations contribute to decision-making in management. However, standard factor analysis is not always applied correctly mainly due to the misuse of ordinal data as interval data and the inadequacy of the former for classical factor analysis. The purpose of this paper is to present and apply the Bayesian factor analysis for mixed data (BFAMD) in the context of empirical using the Bayesian paradigm for the construction of scales.

Ignoring the categorical nature of some variables often used in management studies, as the popular Likert scale, may result in a model with false accuracy and possibly biased estimates. To address this issue, Quinn (2004) proposed a Bayesian factor analysis model for mixed data, which is capable of modeling ordinal (qualitative measure) and continuous data (quantitative measure) jointly and allows the inclusion of qualitative information through prior distributions for the parameters’ model. This model, adopted here, presents considering advantages and allows the estimation of the posterior distribution for the latent variables estimated, making the process of inference easier.

The results show that BFAMD is an effective approach for scale validation in management studies making both exploratory and confirmatory analyses possible for the estimated factors and also allowing the analysts to insert a priori information regardless of the sample size, either by using the credible intervals for Factor Loadings or by conducting specific hypotheses tests. The flexibility of the Bayesian approach presented is counterbalanced by the fact that the main estimates used in factor analysis as uniqueness and communalities commonly lose their usual interpretation due to the choice of using prior distributions.

Considering that the development of scales through factor analysis aims to contribute to appropriate decision-making in management and the increasing misuse of ordinal scales as interval in organizational studies, this proposal seems to be effective for mixed data analyses. The findings found here are not intended to be conclusive or limiting but offer a useful starting point from which further theoretical and empirical research of Bayesian factor analysis can be built.

Introduction: As Internet usage increases, so does widespread concern about surveillance and privacy. While most of the research primarily focuses on a particular digital setting, these problems cut beyond national boundaries and impact economies everywhere.

Purpose: This study critically analyses the Data Protection Bill 2019’s effectiveness within the context of surveillance and privacy in India’s digital economy. Investigating critical provisions of the bill, comparing it to international privacy laws and standards, and identifying potential gaps and weaknesses, this study provides insights into the bill’s ability to protect personal data and limit surveillance practices.

Methodology: The chapter is based on secondary sources of data, including academic articles, government reports, and news articles on the topics of surveillance, privacy, and the Data Protection Bill 2019 in India, involving content and critical discourse analyses.

Findings: The Data Protection Bill 2019 evaluation reveals a set of provisions with the overarching intent to safeguard citizens’ privacy worldwide and curtail undue surveillance practices exercised by both governmental bodies and private enterprises. Intricately delineates the entitlements of individuals concerning their data, encompassing vital aspects such as the right to access, rectify, and erase their data, the bill mandates stringent adherence to the principle of explicit consent when collecting and processing personal data.

Nevertheless, a comprehensive analysis also reveals several gaps and constraints inherent in the bill’s framework. One such area is the inclusion of exemptions for governmental entities, an aspect that raises international concerns regarding potential disparities in data protection practices.

This chapter explores young individuals’ attitude toward protection of personal data. Specifically, the discussion focuses on the General Data Protection Regulation (GDPR) and the introduction of a property right over personal data. To this end, a total of 10 in-depth interviews were conducted with both Albanian and Italian college students. Transcribed data from the interviews were analyzed through thematic analysis. Four main themes emerged from the interviews: (i) distrust toward the way personal data are used online, (ii) no change in behavior after the introduction of GDPR, (iii) limited knowledge regarding terms and conditions of websites, and (iv) individual desire for more control over his/her data. In light of the research findings, the present contribution highlights that, despite the GDPR enhances individuals’ data protection and rights, there is an intention–behavior gap that has been labeled in the literature as “privacy paradox.” Furthermore, findings reveal that treating personal data as a property right has pros and cons.