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PurposeThe purpose of this paper is twofold: first, the relationship between crowding perceptions (i.e. employees’ perceptions of insufficient personal space due to offices’ physical constraints) and deviant workplace behaviors (DWBs) directed at both the organization as a whole (DWB-O) and individuals (DWB-I); and second, privacy invasion from supervisors and peers as a mediator.Design/methodology/approachData were collected from 299 respondents working in open-plan offices at four medium-to-large sized IT-based companies. Drawing on conservation of resources theory, the paper suggests that under crowding conditions employees can perceive the physical workspace as a space-related resource that is threatened leading them to engage in DWBs out of a conservation strategy.FindingsStructural equation modeling results significantly supported main effects of employees’ crowding perceptions on the two types of DWBs, with privacy invasion from supervisors and peers as full mediator.Research limitations/implicationsThe study could suffer from mono-method/source bias, and specificities of the studied IT-based companies and their work can raise concerns about the generalizability of the results.Practical implicationsThe findings indicate that a proper physical office arrangement can be a useful tool for managers in combating employee DWB.Originality/valueTo date, the origin of workplace deviance has mainly been investigated in terms of the psychosocial work environment; however, the physical labor conditions (i.e. the layout of buildings, furniture, workspace, air conditioning, workplace density, etc.) have received little systematic attention.

Teeming with chatrooms, online discussion groups, and blogs, the Internet offers previously unimagined opportunities for personal expression and communication. But there's a dark side to the story. A trail of information fragments about us is forever preserved on the Internet, instantly available in a Google search. A permanent chronicle of our private lives-often of dubious reliability and sometimes totally false-will follow us wherever we go, accessible to friends, strangers, dates, employers, neighbors, relatives, and anyone else who cares to look. This engrossing book, brimming with amazing examples of gossip, slander, and rumor on the Internet, explores the profound implications of the online collision between free speech and privacy. Daniel Solove, an authority on information privacy law, offers a fascinating account of how the Internet is transforming gossip, the way we shame others, and our ability to protect our own reputations. Focusing on blogs, Internet communities, cybermobs, and other current trends, he shows that, ironically, the unconstrained flow of information on the Internet may impede opportunities for self-development and freedom. Long-standing notions of privacy need review, the author contends: unless we establish a balance between privacy and free speech, we may discover that the freedom of the Internet makes us less free.

Purpose This study explored reactions to location sensing technologies (LSTs) which enable organizations to track the location and movements of employees, even off-site. In particular, we examined the relationships among two monitoring characteristics (i.e., purpose and control), perceptions of privacy invasion, and monitoring fairness. Design/Methodology/Approach This study employed a 2 (purpose) × 2 (control) factorial design using 208 college students. Study hypotheses were tested using hierarchical regression. Findings The ability to control the location sensing device was related to monitoring fairness via privacy invasion, but no support was found for monitoring purpose. Implications The results underscore the importance of giving employees a sense of control over monitoring and providing them with \"protected spaces\" where monitoring can be avoided. Originality/Value This study offers the first examination of attitudes toward location sensing technologies.

With the proliferation and ubiquity of information and communication technologies (ICTs), it is becoming imperative for individuals to constantly engage with these technologies in order to get work accomplished.Academic literature, popular press, and anecdotal evidence suggest that ICTs are responsible for increased stress levels in individuals (known as technostress). However, despite the influence of stress on health costs and productivity, it is not very clear which characteristics of ICTs create stress. We draw from IS and stress research to build and test a model of technostress. The person-environment fit model is used as a theoretical lens. The research model proposes that certain technology characteristics — like usability (usefulness, complexity, and reliability), intrusiveness (presenteeism, anonymity), and dynamism (pace of change) — are related to Stressors (work overload, role ambiguity, invasion of privacy, work-home conflict, and job insecurity). Field data from 661 working professionals was obtained and analyzed. The results clearly suggest the prevalence oftechnostress and the hypotheses from the model are generally supported. Work overload and role ambiguity are found to be the two most dominant Stressors, whereas intrusive technology characteristics are found to be the dominant predictors of Stressors. The results open up new avenues for research by highlighting the incidence oftechnostress in organizations and possible interventions to alleviate it.

Character recognition is one of the steps in the number plate recognition system. Character recognition is done to get text character data. The method used is YOLOv3 (You Only Look Once), and Darknet-53 is used as a feature extractor. In this study, the data used were number plate images derived from the extraction and cropping of motorized vehicle videos that had been taken using cellphones and cameras. Testing is done with two different models, namely the model obtained with additional preprocessing data and the model obtained without any preprocessing data. Data preprocessing is done to improve the quality of the number plate image. Testing is done on an uninterrupted number plate image dataset and a number plate image dataset with interference and a reduction of color intensity (brightness) in the image. For the model obtained from the data without preprocessing, the highest number plate recognition accuracy obtained is 80%, and the character recognition accuracy is 97.1%. Meanwhile, for the model obtained from preprocessing data, the highest number plate recognition accuracy obtained was 88%, and the character recognition accuracy was 98.2%.

Firms today use information about customers to improve service and design personalized offerings. To do this successfully, however, firms must collect consumer information. This study enhances awareness about a central paradox for firms investing in personalization; namely, that consumers who value information transparency are also less likely to participate in personalization. We examine the relationship between information technology features, specifically information transparency features, and consumer willingness to share information for online personalization. Based on a survey of over 400 online consumers, we examine the question of whether customer perceived information transparency is associated with consumer willingness to be profiled online. Our results indicate that customers who desire greater information transparency are less willing to be profiled. This result poses a dilemma for firms, as the consumers that value information transparency features most are also the consumers who are less willing to be profiled online. In order to manage this dilemma, we suggest that firms adopt a strategy of providing features that address the needs of consumers who are more willing to partake in personalization, therefore accepting that the privacy sensitive minority of consumers are unwilling to participate in personalization, despite additional privacy features.

Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.

[Display omitted] •A model of privacy while shopping for embarrassing products is proposed.•Perceptions of being watched lead a shopper to feel less in control of his/her privacy.•Control of privacy leads to temporary and permanent abandonment and less purchase intentions.•A shopping basket can lessen the negative effects of a visual privacy invasion. This research fills a gap in the retailing literature regarding the impact of shoppers’ perceptions of being watched while shopping for embarrassing products. Four studies consistently show that an employee watching a shopper can cause the shopper to either permanently or temporarily leave the shopping area as purchase intentions decrease. Reactance theory explains this relationship, which is mediated by consumers’ feelings of control over their own privacy. Essentially, when shoppers believe an employee is watching them, they feel less in control of their privacy, resulting in negative consequences for the retailer. This relationship is especially important for products that consumers may already feel some level of embarrassment over purchasing in the first place. The results have important theoretical implications for reactance theory by demonstrating that a consumer can regain control even when the original threat to behavior still exists. Additionally, increasing options that allow a consumer to regain control will reduce the overall reactance to the threat to privacy and will improve retailer outcomes. Practitioner recommendations present several techniques that allow the consumer to regain privacy control in spite of the sometimes necessary practice of watching in-store consumers.

Advances in information technology and e-commerce enable firms to make personalized offers to individual consumers based on information about the consumers. However, the collection and use of private information have caused serious concerns about privacy invasion by consumers, creating a personalization—privacy tradeoff. The key approach to address privacy concerns is via the protection of privacy through the implementation of fair information practices, a set of standards governing the collection and use of personal information. In this paper, we take a game-theoretic approach to explore the motivation of firms for privacy protection and its impact on competition and social welfare in the context of product and price personalization. We find that privacy protection can work as a competition-mitigating mechanism by generating asymmetry in the consumer segments to which firms offer personalization, enhancing the profit extraction abilities of the firms. In equilibrium, both symmetric and asymmetric choices of privacy protection by the firms can result, depending on the size of the personalization scope and the investment cost of protection. Further, as consumers become more concerned about their privacy, it is more likely that all firms adopt privacy protection. In the perspective of welfare, we show that autonomous choices of privacy protection by personalizing firms can improve social welfare at the expense of consumer welfare. We further find that regulation enforcing the implementation of fair information practices can be efficient from the social welfare perspective mainly by limiting the incentives of the firms to exploit the competition-mitigation effect.

In this paper we integrate insights from diverse islands of research on electronic privacy to offer a holistic view of privacy engineering and a systematic structure for the discipline's topics. First we discuss privacy requirements grounded in both historic and contemporary perspectives on privacy. We use a three-layer model of user privacy concerns to relate them to system operations (data transfer, storage and processing) and examine their effects on user behavior. In the second part of the paper we develop guidelines for building privacy-friendly systems. We distinguish two approaches: \"privacy-by-policy\" and \"privacy-by-architecture.\" The privacy-by-policy approach focuses on the implementation of the notice and choice principles of fair information practices (FIPs), while the privacy-by-architecture approach minimizes the collection of identifiable personal data and emphasizes anonymization and client-side data storage and processing. We discuss both approaches with a view to their technical overlaps and boundaries as well as to economic feasibility. The paper aims to introduce engineers and computer scientists to the privacy research domain and provide concrete guidance on how to design privacy-friendly systems.