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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.

Metaverse is a virtual application spawned by digital technology that is becoming increasingly relevant to our lives. However, for the opportunities created and challenges posed by the metaverse, its important elements and future evolution trend remain largely unknown. Thus, this paper aims to understand the current status of metaverse research and its future research directions.

Based on the analysis of the literature data on the metaverse both in English and Chinese using Latent Dirichlet allocation (LDA) topic modeling and bibliometrics, this study discussed the related research and development trend of the metaverse. The authors first defined the concept of the metaverse and analyzed 1,378 English articles from seven publishers and 590 Chinese articles from the CNKI database. Following that, the authors summarized three important themes from the current studies: virtual world, metaverse technologies and metaverse applications. Finally, a framework of future directions on metaverse research was proposed.

The review found that during the rapid development of the metaverse, opportunities and challenges coexisted. In the virtual world, metaverse technologies drive the implementation of application scenarios, and in turn, applications promote the improvement of technologies. The interrelationship between technology and application lays the foundation for the development of the metaverse. Future metaverse research will generate different research directions.

This review provides a valuable, systematic perspective for individuals who want to understand the metaverse. The conceptual framework on metaverse research proposed in this paper offers a comparison of literature analysis from domestic and international perspectives and brings new insights into the development of the metaverse.

This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.

This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.

The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.

The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533

In response to food supply constraints resulting from coronavirus disease 2019 (COVID-19) restrictions, in the year 2020, the project developed automated household Aquaponics units to guarantee food self-sufficiency. However, the automated aquaponics solution did not fully comply with data privacy and portability best practices to protect the data of household owners. The purpose of this study is to develop a data privacy and portability layer on top of the previously developed automated Aquaponics units.

Design Science Research (DSR) is the research method implemented in this study.

General Data Protection and Privacy Regulations (GDPR)-inspired principles empowering data subjects including data minimisation, purpose limitation, storage limitation as well as integrity and confidentiality can be implemented in a federated learning (FL) architecture using Pinecone Matrix home servers and edge devices.

The literature reviewed for this study demonstrates that the GDPR right to data portability can have a positive impact on data protection by giving individuals more control over their own data. This is achieved by allowing data subjects to obtain their personal information from a data controller in a format that makes it simple to reuse it in another context and to transmit this information freely to any other data controller of their choice. Data portability is not strictly governed or enforced by data protection laws in the developing world, such as Zimbabwe's Data Protection Act of 2021.

Privacy requirements can be implemented in end-point technology such as smartphones, microcontrollers and single board computer clusters enabling data subjects to be incentivised whilst unlocking the value of their own data in the process fostering competition among data controllers and processors.

The use of end-to-end encryption with Matrix Pinecone on edge endpoints and fog servers, as well as the practical implementation of data portability, are currently not adequately covered in the literature. The study acts as a springboard for a future conversation on the topic.

Blockchain technology is provoking significant disruptions, thereby affecting supply chain management. This study endeavoured to advance research regarding blockchain-based supply chain traceability by identifying the opportunities and limitations that accompany the adoption of public blockchains. Therefore, the purpose of the study is to contribute to contemporary supply chain research by an assessment of blockchain technology and its linkages to traceability.

This paper is conceptual. The authors summarised the relevant literature on the concepts of supply chain traceability, conceptualised key elements exclusive to the public blockchain and highlighted opportunities and limitations in implementing traceability using blockchains.

Incompatibilities were identified between general traceability and the public blockchain. However, when embracing the blockchain's privacy model, the blockchains can support information exchange in supply chains where vulnerability towards third parties, the confidentiality of information, or the privacy of participants are concerns. Furthermore, the public blockchain can support areas of supply chains where institutional interest is lacking.

This is one of the first papers in an international supply chain management journal to critically analyse the intersection of specific blockchain characteristics and supply chain traceability requirements. The authors thereby add to the discussion of designs for a disintermediated, peer-to-peer models and guide researchers and practitioners alike in exploring the application of disruptive change from blockchain technologies. By setting focus on the privacy model, the paper identifies the potential application and future research approaches to exploit the elementary strength of the blockchain.

In today’s digitized environment, information privacy has become a prime concern for everybody. The purpose of this paper is to provide an understanding of information privacy concern arising because of the application of computer-based information system in the various domains (E-Governance, E-Commerce, E-Health, E-Banking and E-Finance), and at different levels, i.e. individual, group, organizational and societal.

The authors performed an in-depth analysis of different research articles related to information privacy concerns and elements affecting those at certain level of applications. The primary sources of literature were articles retrieved from online databases. Various online journal and scholarly articles were searched in detail to locate information privacy-related articles.

The authors have carried out a detailed literature review to identify the different levels where the privacy is a big challenging task. This paper provides insights whether information privacy concern may obstruct in the successful dispersal and adoption of different applications in various application domains. Consumers’ attitude towards information privacy concerns have enlightened and addressed at individual levels in numerous domains. Privacy concerns at the individual level, as suggested by our analysis, seem to have been sufficiently addressed or addressed. However, information privacy concerns at other levels – group, organizational and societal levels – need the attention of researchers.

In this paper, the authors have posited that it will help the researchers to more focus at group level privacy perspective in the information privacy era.

The purpose of this paper is to improve the understanding of cloud service users’ privacy concerns, which are anticipated to considerably hinder cloud service market growth. The researchers have explored privacy concerns from dimensions that were identified as relevant in the cloud context.

Content analysis was used to identify privacy problems that were most often raised in previous cloud research. Multidimensional developmental theory (MDT) was used to build a conceptual model of cloud privacy concerns. Literature review was made to identify the privacy-related constructs used to measure privacy concerns in previous cloud research.

The paper provides systematization of recent cloud privacy research, proposal of a conceptual model of cloud privacy concerns, identification of measuring instruments that were used to measure privacy concerns in previous cloud research and identification of categories of problems that need to be addressed in future cloud research.

This paper has identified the categories of privacy problems and dimensions that have not yet been measured in the cloud context, to the best of the authors’ knowledge. Their simultaneous examination could clarify the effects of different dimensions on the privacy concerns of cloud users. The conceptual model of cloud privacy concerns will allow cloud service providers to focus on key cloud problems affecting users’ privacy concerns and use the most appropriate privacy protection communication and preservation approaches.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

This study investigates perceptions of the use of online tracking, a passive data collection method relying on the automated recording of participant actions on desktop and mobile devices, for studying information behavior. It scrutinizes folk theories of tracking, the concerns tracking raises among the potential participants and design mechanisms that can be used to alleviate these concerns.

This study uses focus groups composed of university students (n = 13) to conduct an in-depth investigation of tracking perceptions in the context of information behavior research. Each focus group addresses three thematic blocks: (1) views on online tracking as a research technique, (2) concerns that influence participants' willingness to be tracked and (3) design mechanisms via which tracking-related concerns can be alleviated. To facilitate the discussion, each focus group combines open questions with card-sorting tasks. The results are analyzed using a combination of deductive content analysis and constant comparison analysis, with the main coding categories corresponding to the thematic blocks listed above.

The study finds that perceptions of tracking are influenced by recent data-related scandals (e.g. Cambridge Analytica), which have amplified negative attitudes toward tracking, which is viewed as a surveillance tool used by corporations and governments. This study also confirms the contextual nature of tracking-related concerns, which vary depending on the activities and content that are tracked. In terms of mechanisms used to address these concerns, this study highlights the importance of transparency-based mechanisms, particularly explanations dealing with the aims and methods of data collection, followed by privacy- and control-based mechanisms.

The study conducts a detailed examination of tracking perceptions and discusses how this research method can be used to increase engagement and empower participants involved in information behavior research.

This article advocates that privacy literacy research and praxis mobilize people toward changing the technological and social conditions that discipline subjects toward advancing institutional, rather than community, goals.

This article analyzes theory and prior work on datafication, privacy, data literacy, privacy literacy and critical literacy to provide a vision for future privacy literacy research and praxis.

This article (1) explains why privacy is a valuable rallying point around which people can resist datafication, (2) locates privacy literacy within data literacy, (3) identifies three ways that current research and praxis have conceptualized privacy literacy (i.e. as knowledge, as a process of critical thinking and as a practice of enacting information flows) and offers a shared purpose to animate privacy literacy research and praxis toward social change and (4) explains how critical literacy can help privacy literacy scholars and practitioners orient their research and praxis toward changing the conditions that create privacy concerns.

This article uniquely synthesizes existing scholarship on data literacy, privacy literacy and critical literacy to provide a vision for how privacy literacy research and praxis can go beyond improving individual understanding and toward enacting social change.