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The purpose of this study is to examine the effect of micro-level place on identity theft victimization. This study uses the 2016 Identity Theft Supplement (ITS) to investigate whether aspects of an individual’s residence affect their likelihood of becoming identity theft victims.

The authors conduct logistic regressions of whether a respondent was an identity theft victim in the past year using the following variables as key predictors: number of housing units in a residence, whether the respondent operates a business out of their residence and if residence access is restricted.

The results suggest that location influences the likelihood of identity theft to a modest degree though some aspects of location (possibly those related to rewards perceptions) may be more relevant than others. Meanwhile, though location may influence initial target selection, whether someone is victimized may be more dependent on factors such as personal behavior.

To the best of the authors’ knowledge, this manuscript represents one of the first investigations into the relationship between microlevel place and the incidence of identity theft. Furthermore, it provides evidence that one does exist which bears further inquiry.

This research examines the relationship between the timeliness in announcing the discovery of a data breach and consumer trust in an e-commerce company, as well as later trust-rebuilding efforts taken by the company to compensate users impacted by the breach.

A survey experiment was used to examine the effect of both trust-reducing events (announced data breaches) and trust-enhancing events (provision of identity theft protection and credit monitoring) on consumer trust. The timeliness of the breach announcement by an e-commerce company was manipulated between two randomly assigned groups of subjects; one group viewed an announcement of the breach immediately upon its discovery, and the other viewed an announcement made two months after the breach was discovered. Consumer trust was measured before the breach, after the breach was announced, and finally, after the announcement of data protection.

The results suggest that companies that delay a data breach announcement are likely to suffer a larger drop in consumer trust than those that immediately disclose the data breach. The results also suggest that trust can be repaired by providing data protection. However, even after providing identity theft protection and credit monitoring, companies that fail to promptly disclose a breach have lower repaired trust than companies that promptly disclose.

This study contributes to the literature on e-commerce trust by examining how a company's forthrightness in reporting a data breach impacts user trust at the time of the disclosure of the data breach and after subsequent efforts to repair trust.

The purpose is to understand how farmers in rural American communities perceive crime, safety and policing.

An online survey, adapted from a version used in Victoria, Australia (Harkness, 2017), was modified and administered through social media and farming organizations throughout three US states. The survey covers topics relating to crime and victimization, feelings of safety or fear in rural areas, policing practices and trust in police in their areas and any crime prevention practices that respondents use.

With nearly 1,200 respondents and four scales investigated, results indicate that those respondents with more favorable views of law enforcement and the criminal justice system had the highest fear of crime, those who had been prior victims of crime had a higher fear of crime than those who did not, those with higher community involvement had higher fear of crime, and those from Nebraska compared to Colorado had higher fear of crime.

A better understanding of the agricultural community’s perceptions of crime, safety and policing will aid law enforcement in community policing efforts and in farm crime investigation and prevention. Limitations of the study, including the distribution method will be discussed.

Farm- and agriculture-related crimes have serious financial and emotional consequences for producers and local economies. Stereotypes about rural areas being “safe with no crime” are still prevalent. Rural American farmers’ perceptions of crime, safety and police are largely absent from the literature and are important for improving farm crime prevention.

Crime increased in Spain during the period of 2017–2019 after a decade of decline. This coincides with severe housing deprivation multiplying by three in just four years, affecting 3.4% of the population in 2020. However, no research has been found that analyzes whether this deterioration of the physical conditions of housing and its environmental elements has impacted the level of crime in Spain. This study aims to analyze how housing deprivation affects crime in the Spanish context.

For this purpose, different items that are considered by Eurostat as elements of housing deprivation are used. The difference generalized method of moments estimator is used for 16 Spanish regions that comprises the period from 2013 to 2019.

The results suggest that certain structural and environmental elements of housing are positively associated with crime: space (0.5% and 0.4%) and high housing expenditure (0.4% and 0.5%) are positively correlated with the two dependent variables; the lack of light and overcrowding stand out as they establish a positive and statistically significant association with four out of the six analyzed crime categories; the absence of lighting effect reaches up to 1.8% and 1.7% in the case of violent robberies and vehicle theft, respectively. Finally, pollution is negatively associated with robbery with violence (−1.9%), theft (−0.7%) and robbery with force (−0.5%).

To the best of the author’s knowledge, this is the first study that examines whether this deterioration of the physical conditions of housing has impacted the level of crime in Spain. It is also pioneering at the European level by using nonmonetary dimensions of inequality such as housing.

Initiator crimes, also known as near-repeat crimes, occur in places with known risk factors and vulnerabilities based on prior crime-related experiences or information. Consequently, the environment in which initiator crimes occur might be different from more general crime environments. This study aimed to analyse the differences between the environments of initiator crimes and general crimes, confirming the need for predicting initiator crimes.

We compared predictive models using data corresponding to initiator crimes and all residential burglaries without considering repetitive crime patterns as dependent variables. Using random forest and gradient boosting, representative ensemble models and predictive models were compared utilising various environmental factor data. Subsequently, we evaluated the performance of each predictive model to derive feature importance and partial dependence based on a highly predictive model.

By analysing environmental factors affecting overall residential burglary and initiator crimes, we observed notable differences in high-importance variables. Further analysis of the partial dependence of total residential burglary and initiator crimes based on these variables revealed distinct impacts on each crime. Moreover, initiator crimes took place in environments consistent with well-known theories in the field of environmental criminology.

Our findings indicate the possibility that results that do not appear through the existing theft crime prediction method will be identified in the initiator crime prediction model. Emphasising the importance of investigating the environments in which initiator crimes occur, this study underscores the potential of artificial intelligence (AI)-based approaches in creating a safe urban environment. By effectively preventing potential crimes, AI-driven prediction of initiator crimes can significantly contribute to enhancing urban safety.

Given its growing economic potential and social impact, this study aims to understand the motivations and concerns regarding metaverse usage. It identifies user needs and risks around the metaverse grounded on uses and gratifications theory and perceived risk theory.

The authors analyzed user reviews and rating data from Roblox, a representative modern metaverse platform. They applied BERTopic modeling to extract topics from reviews, identifying key motivations and risk aspects related to metaverse usage. They further constructed an explanatory model to assess how those affect user satisfaction and changes in these effects over time.

This study discovered that gratifications like entertainment, escapism, social interaction and avatar-based self-expression significantly influence user satisfaction in the metaverse. It also highlighted that users find satisfaction in self-expression and self-actualization through creating virtual spaces, items and video content. However, factors such as identity theft, fraud and child safety were identified as potential detriments to satisfaction. These influences fluctuated over time, indicating the dynamic nature of user needs and risk perceptions.

The novelty of this study lies in its dual application of the uses and gratifications theory and perceived risk theory to the metaverse. It provides a novel perspective on user motivations and concerns, shedding light on the distinct elements driving user satisfaction within the metaverse. This study unravels the metaverse’s unique capacity to assimilate features from established digital media while offering a distinctive user-generated experience. This research offers valuable insights for academics and practitioners in digital media and marketing.

This research pioneers the application of both uses and gratifications and perceived risk theories to understand factors influencing metaverse satisfaction. By establishing a comprehensive framework, it explores the metaverse’s unique value as a user-content creation platform, while encompassing existing digital platform characteristics. This study enriches the academic literature on the metaverse and offers invaluable insights for both metaverse platforms and brand marketers.

The purpose of the study is to identify cybersecurity threats that hinder the adoption of digital banking and provide sustainable strategies to combat cybersecurity risks in the banking industry.

Systematic literature review guidelines were used to conduct a quantitative synthesis of empirical evidence regarding the impact of cybersecurity threats and risks on the adoption of digital banking.

A total of 84 studies were initially examined, and after applying the selection and eligibility criteria for this systematic review, 58 studies were included. These selected articles consistently identified identity theft, malware attacks, phishing and vishing as significant cybersecurity threats that hinder the adoption of digital banking.

With the country’s banking sector being new in this area, this study contributes to the scant literature on cyber security, which is mostly in need due to the myriad breaches that the industry has already suffered thus far.

This study builds on the extant research of the authors on illegal rural enterprise (IRE). However, instead of taking a single or micro case approach within specific sections of the farming and food industries we examine the concept holistically from a macro case perspective. Many IRE crimes simply could not be committed without insider knowledge and complicity, making it essential to appreciate this when researching or investigating such crimes.

Using data from published studies, we introduce the theoretical concept of “Shadow infrastructure” to analyse and explain the prevalence and endurance of such criminal enterprises. Using a multiple case approach, we examine data across the cases to provide an analysis of several industry wide crimes—the illicit halal meat trade; the theft of sheep; the theft of tractors and plant; and the supply of illicit veterinary medicines.

We examine IRE crimes across various sectors to identify commonalities in practice and in relation to business models drawing from a multidisciplinary literature spanning business and criminology. Such enterprises can be are inter-linked. We also provide suggestions on investigating such structures.

We identify academic and practical implications in relation to the investigation of IRE crime and from an academic perspective in relation to researching the phenomenon.

This study combines data from numerous individual studies from a macro perspective to provide practical solutions to a multifaceted problem.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

Although (tele)work is increasingly being adopted and employees’ behavior is recognized to be key for organizational outcomes (e.g. performance), the current literature on counterproductive work behaviors (CWB) in telework settings is fragmented, and a valid measurement instrument is lacking. This study aims to address this gap and starts by presenting a review of the current literature on counterproductive work behavior in flexible work arrangements (i.e. telework). Based on this study, eight categories of work behavior that appear to be frequent under telework settings were identified.

Next, four studies aimed at developing and validating a measurement instrument that captures employee counterproductive work behavior when teleworking: the counterproductive [tele]work behavior scale (CTwBS).

In Study 1, the CTwBS was created, and in Study 2, its factorial validity was examined (N = 350). In Study 3, using a sample of teleworkers (N = 289), the convergent and discriminant validity of the CTwBS was tested using self-ratings of (positive and negative) affect, attitudes toward telework and frequency of CWB in general. In Study 4, a daily-diary study across five workdays (N = 232 × 5 = 1,160) examined the criterion validity of the CTwBS.

The results indicated that the CTwBS is a valid and reliable instrument for capturing employee counterproductive work behavior in telework settings. Theoretical and practical implications are discussed.

To the best of the authors’ knowledge, CTwBS is the first measure aimed at assessing counterproductive work behavior in telework settings.