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The context of this chapter is the use of data and advanced data analytics in a commercial setting. Privacy is considered as protection from vulnerability, whereby vulnerability is understood as the state of being exposed to the possibility of being harmed, either physically or emotionally, or in fundamental rights other than privacy. Therefore, privacy's policy instruments, in particular data protection law, could be seen as a means to reduce the risk of harm resulting from data use. Such harm is probabilistic and often uncertain, which, however, does not exclude analyzing costs and benefits of regulatory data protection policies. When balancing privacy protections and opportunities for knowledge gain, regulatory policy could be viewed as superior, when it expands the range of possible trade-offs between vulnerability protection and gaining socially beneficial knowledge.

This work empirically evaluates the effectiveness of the novel ontology-based access-control mechanism and the common password-protected access-control mechanism for social blogs. The paper aims to discuss these issues.

The ontology-based access-control scheme is designed to fit two characteristics of blog activities: social relationships and tags. A laboratory experiment is conducted to assess the perceived privacy benefit and perceived ease of use of the two mechanisms.

Analytical results indicate that, with the ontology-based access-control scheme, users perceive more privacy benefit than with the password-protected access-control scheme. The perceived ease of use with the ontology-based and password-protected access-control systems did not differ significantly.

Cross-boundary collaborations need an appropriate approach to control communication access. Further study is required to evaluate the ontology-based access-control scheme applied in cross-organizational and cross-departmental collaborations.

From a knowledge management perspective, blogs can store personal and organizational knowledge and experiences. The ontology-based access-control scheme encourages knowledge sharing for appropriate persons.

The new ontology-based access-control mechanism can help online users keep secrets from selected people to gain more privacy benefits than the existing password-protected access-control mechanism.

This paper advocates for banks to understand customers' online privacy concerns, use those insights to segment consumers and design tailored sales strategies to build a mutual relationship through a social exchange that produces a competitive advantage.

A qualitative study involving 30 in-depth interviews with Australian and Asian millennials residing in Australia was conducted using a grounded theory approach to explore privacy concerns of online banking and determine the efficacy of their banks' existing sales strategy and practice.

The study revealed differences in customer perceptions of trust, confidence, responsibility and exchange. Adopting a power-dependency paradigm within a social exchange theoretical framework and power distance belief of national culture theory, the authors identified four consumer segments: exemplar, empiric, elevator and exponent. The authors propose a tailored consumer-centered sales strategy of communication, control, consolidation and collaboration.

The paper contributes to the research in services marketing, sales strategy and banking in three ways: first, the authors demonstrate the importance of the social exchange theory and national culture as a premise to develop a competitive advantage; second, the authors propose an innovative set of consumer segments in regards to online privacy concerns; and, third, the authors introduce four sales strategies tailored to each of the four segments.

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 implementation of European data protection is a challenge for businesses and has imposed legal, technical and organizational changes for companies. This study aims to explore the benefits and challenges that companies operating in the information technology (IT) sector have experienced in applying the European data protection. Additionally, this study aims to explore whether the benefits and challenges faced by these companies were different considering their dimension and the state of implementation of the regulation.

This study adopts a quantitative methodology, based on a survey conducted with Portuguese IT companies. The survey is composed of 30 questions divided into three sections, namely, control data; assessment; and benefits and challenges. The survey was created on Google Drive and distributed among Portuguese IT companies between March and April of 2019. The data were analyzed using the Stata software using descriptive and inferential analysis techniques using the ANOVA one-way test.

A total of 286 responses were received. The main benefits identified by the application of European data protection include increased confidence and legal clarification. On the other hand, the main challenges include the execution of audits to systems and processes and the application of the right to erasure. The findings allow us to conclude that the state of implementation of the general data protection regulation (GDPR), and the type of company are discriminating factors in the perception of benefits and challenges.

This study has essentially practical implications. Based on the synthesis of the benefits and challenges posed by the adoption of European data protection, it is possible to assess the relative importance and impact of the benefits and challenges faced by companies in the IT sector. However, this study does not explore the type of challenges that are placed at each stage of the adoption of European data protection and does not take into account the specificities of the activities carried out by each of these companies.

The implementation of the GDPR is still in an initial phase. This study is pioneering in synthesizing the main benefits and challenges of its adoption considering the companies operating in the IT sector. Furthermore, this study explores the impact of the size of the company and the status of implementation of the GDPR on the perception of the established benefits and challenges.

This study serves two purposes: (1) to evaluate the effects of organizational ambidexterity by examining how the balanced and the combined sales–service configurations of chatbots differ in their abilities to enhance customer experience and patronage and (2) to apply information boundary theory to assess the contingent role that chatbot sales–service ambidexterity can play in adapting to customers' personalization–privacy paradox.

An online survey of artificial intelligence chatbots users was conducted, and a mixed-methods research design involving response surface analysis and polynomial regression was adopted to address the research aim.

The results of polynomial regressions on survey data from 507 online customers indicated that as the benefits of personalization decreased and the risk to privacy increased, the inherently negative (positive) effects of imbalanced (combined) chatbots' sales–service ambidexterity had an increasing (decreasing) influence on customer experience. Furthermore, customer experience fully mediated the association of chatbots' sales–service ambidexterity with customer patronage.

First, this study enriches the literature on frontline ambidexterity and extends it to the setting of human–machine interaction. Second, the study contributes to the literature on the personalization–privacy paradox by demonstrating the importance of frontline ambidexterity for adapting to customer concerns. Third, the study examines the conduit between artificial intelligence (AI) chatbots' ambidexterity and sales performance, thereby helping to reconcile the previously inconsistent evidence regarding this relationship.

COVID-19, an infectious disease first identified in China, has resulted in an ongoing pandemic all over the world. Most of the countries have been experiencing a difficult period during the fighting of this pandemic. The purpose of this study is to explore the effect of privacy concerns and cultural differences on public opinion related to the pandemic. The authors conducted a comparative analysis of public opinion in the US and in China as a case study, in order to determine the results.

National policies on important issues faced during the COVID-19 pandemic in the US and in China were examined through a comparative analysis. The authors used text clustering and visualization to mine public opinion on two popular social media platforms, Twitter and Weibo. From the perspectives of concern for privacy and of national culture, this study combines qualitative and quantitative analysis to discover the acceptance level of national policies by the public in the two countries.

The anti-pandemic policies and measures of the US and China reflect the different characteristics of their respective political systems and national cultures. When considering the culture of the US, it is hard to establish and enforce a rigorous regulation on either mask wearing in public or home quarantine on the national level. The opinions of US people are diverse, regarding national COVID-19 policies, but they are rather unified on privacy issues. On the other hand, Chinese people show a high acceptance of national policies based on their mask-wearing customs and their culture of collectivism.

Prior studies have paid insufficient attention to the ways in which user privacy and cultural difference affect public opinion on national policies between the US and China. This case study that compares public opinion on current and topical issues which are closely bound up with public life shows originality, as it innovatively provides a cross-cultural perspective on the research of public opinion dissemination during emergencies by considering the ongoing COVID-19 pandemic.

The purpose of this paper is to take a novel approach to help users better understand and be more aware of what third parties are learning about them as they browse the web.

The approach the authors take is to personalize the awareness by using JavaScript embedded in a web page to examine portions of a user's web‐browser history in order to ascertain web sites that the user has visited. The authors then personalize information reported to the user about what third‐party sites are tracking the user's behavior along with demographic information these sites may be inferring from these visited sites and the user's geographic location.

It was found that 63 percent of users agreed with a statement of concern for third parties monitoring activities, about half of the respondents agreed with a concern for knowledge about a user's location and a little more than half agreed to concern about inference of demographic information. It was found that females are more concerned about these issues than males. In terms of possible actions, a majority of users report using an ad blocker tool and even more delete cookies at least some amount of time. Using an opt‐out mechanism or removing browser history is done by less than 20 percent of users. Despite expressing more concern for information known by third parties, females are not significantly more likely to take actions that may limit what is leaked to these third parties. A contributor to this discrepancy is that females were much less likely to know their settings for many of the actions, indicating less familiarity with them.

Web privacy is an important social issue so helping users to better understand tracking of their actions, along with what actions can be taken to limit tracking, is important.

The paper takes an original approach to helping users understand what third parties learn about them and follows up that approach with a survey of user attitudes and actions on this important topic.

The purpose of this paper is to analyse the current state of research on the integration of blockchain and building information modelling (BIM) in the Architecture, Engineering, Construction and Operations (AECO) industry as a means of identifying gaps between the existing paradigm and practical applications for determining future research directions and improving the industry. The study aims to provide clear guidance on areas that need attention for further research and funding and to draw academic attention to factors beyond the technical dimension.

A mixed-method systematic review is used, considering multiple literature types and using a sociotechnical perspective-based framework that covers three dimensions (technic, process and context) and three research elements (why, what and how). Data are retrieved and analysed from the Web of Science and Scopus databases for the 2017–2023 period.

While blockchain has the potential to address security, traceability and transparency and complement the system by integrating supporting applications, significant gaps still exist between these potentials and widespread industry adoption. Current limitations and further research needs are identified, including designing fully integrated prototypes, empirical research to identify operational processes, testing and analysing operational-level models or applications and developing and applying a technology acceptance model for the integration paradigm. Previous research lacks contextual settings, real-world tests or empirical investigations and is primarily conceptual.

This paper provides a comprehensive, critical systematic review of the integration of blockchain with BIM in the construction industry, using a sociotechnical perspective-based framework which can be applied in future reviews. The study provides insight into the current state and future opportunities for policymakers and practitioners in the AECO industry to prepare for the transition in this disruptive paradigm. It also provides a phased plan along with a clear direction for the transition to more advanced applications.

The purpose of this paper is to identify the factors influencing the citizens to use robots that would improve the quality of life of the citizens.

With the help of different adoption theories and models and with the support of background studies, some hypotheses have been formulated and a conceptual model has been developed with the consideration of the impact of artificial intelligence regulation (IAR) that controls the use of robots as a moderator. The model has been validated and the hypotheses have been tested by statistical analysis with the help of survey works involving consideration of feedbacks from 503 usable respondents.

The study reveals that the use of robots by the citizens would appreciably increase if government imposes strict artificial intelligence (AI) regulatory control concerning the use of robots, and in that case, it appears that the use of robots would improve the quality of life of the citizens.

The duly validated model would help the authority to appropriately nurse and nurture the factors such as ethical dilemma, perceived risks and control beliefs for enhancing the intention of the citizens to use robots for many purposes including domestic usage in the context of appropriate restrictions imposed through AI regulation. Such use of robots would eventually improve the quality of life.

There are a few studies covering analysis of IAR as a moderator on the linkages of the predictors with the intention of the citizens to use robots. In this context, this study is claimed to have offered a novel contribution.