Does Home Sharing Impact Crime Rate? A Tale of Two Cities

The rise of home sharing has disrupted traditional industries and has a number of unforeseen societal impacts. These changes sparked policy debates on how to keep home sharing platforms’ rapid growth in a sustainable manner. This paper empirically investigates whether and how home sharing impacts the crime rate in the community. Using two policy changes in New York City and San Francisco to mimic an experimental design, and using a difference in difference model, we found a positive association between commercial home sharing and the increase of the crime rate. Leveraging instrumental variables estimation method, we further found that there is no significant relationship between non-commercial (authentic) home sharing and violent criminal activity. This paper provides empirical evidence to support policy change. It also contributes to the understanding of the sharing economy business model and its societal impacts. Further robustness checks will be implemented to validate the findings of this research

Does regulation help? The impact of California‘s AB5 on Gig Workers

There is a widespread debate over how gig workers should be classified. The passage of California Assembly Bill 5 (AB5) - a landmark legislation that aims to correct the misclassification of gig workers, has significant implications for workers, platforms, regulators, and the economy. In this research, leveraging the passage of AB5 as a shock for a natural experiment, we empirically investigate the impact of AB5 on gig workers in California to provide insights. With the data collected from a leading online labor market that connects clients and gig workers, we applied a Difference in Difference approach, and we found that the monthly earnings of gig workers in California, compared to those in other states, have a significantly higher increase after AB5 was signed into law. This effect stems from both increased daily earnings and increased working days. We discuss the implications for policymakers and platforms

The interaction of dark traits with the perceptions of apprehension

This paper integrates dark personality traits with the economics of crime and rational choice theories to identify the role that the Dark Triad and thrill-seeking have on the perceptions of being caught engaging in violating privacy laws. Psychopathy and thrill-seeking had a moderate negative effect on the perceptions of the probability of being apprehended for distributing illegally obtained healthcare information. The implication is that individuals scoring high on the psychopathy and thrill-seeking scales will need less money or monetary incentives to violate HIPAA laws. We also found additional support that white hat hackers score high on the Machiavellian, psychopathy and thrill-seeking scales. We also validated a previous finding that a white hat hacker might drift towards grey hat and black hat hacking

Psychological Profiling of Hacking Potential

This paper investigates the psychological traits of individuals’ attraction to engaging in hacking behaviors (both ethical and illegal/unethical) upon entering the workforce. We examine the role of the Dark Triad, Opposition to Authority and Thrill-Seeking traits as regards the propensity of an individual to be interested in White Hat, Black Hat, and Grey Hat hacking. A new set of scales were developed to assist in the delineation of the three hat categories. We also developed a scale to measure each subject’s perception of the probability of being apprehended for violating privacy laws. Engaging in criminal activity involves a choice where there are consequences and opportunities, and individuals perceive them differently, but they can be deterred if there is a likelihood of punishment, and the punishment is severe. The results suggest that individuals that are White Hat, Grey Hat and Black Hat hackers score high on the Machiavellian and Psychopathy scales. We also found evidence that Grey Hatters oppose authority, Black Hatters score high on the thrill-seeking dimension and White Hatters, the good guys, tend to be Narcissists. Thrill-seeking was moderately important for White Hat hacking and Black hat hacking. Opposition to Authority was important for Grey Hat hacking. Narcissism was not statistically significant in any of the models. The probability of being apprehended had a negative effect on Grey Hat and Black Hat hacking. Several suggestions will be made on what organizations can do to address insider threats

Nomogram for Predicting Bone Development State of Female Children and Adolescents–A Fast Screening Approach Based on Pubes Stages for Growth and Development

Objective: To develop a nomogram for predicting bone development state (BDS) of female children and adolescents in a large scale.Methods: Four hundred forty-seven female students were designated as the training cohort to develop the predictive model, whereas 196 female students were used as the validation cohort to verify the established model. Bone age, height, body mass, body fat percentage, and secondary sexual characteristics were recorded, and BDS was determined with the chronological age and bone age. Multivariate logistic regression was conducted to determine the factors, and nomogram was developed and validated with the training and validation cohorts, respectively.Results: One hundred forty-seven female students were identified as BDS abnormal in the training cohort (32.9%), and 104 were determined in the validation cohort (53.1%). Age, height, weight, and pubes stage were selected for the predictive model. A nomogram was developed and showed a good estimation, with a C-index of 0.78 and a good calibration in the training cohort. Application of the nomogram to the validation cohort showed a similar C-index of 0.75 and a good calibration.Conclusion: A nomogram for predicting bone development was developed, which can provide a relatively good estimation of BDS for female children and adolescents in Chinese metropolis

For Money, and for Fun: Exploring the Effects of Gamification and Financial Incentives on Motivating Online Review Generation

Online reviews can serve as an important strategy to counter and mitigate the negative effects of information asymmetry which can lead to selecting a sub-optimal product or the wrong product. Prior research has demonstrated that financial incentives can motivate online review generation. However, the literature has largely ignored the growing use of gamification to encourage online review generation. In this paper, we propose using a combination of gamification and financial incentives to stimulate online reviews. We employed a randomized experiment to compare the effectiveness of gamification and financial strategies to improve the quantity, the quality, and the valence of online reviews. We found that combining gamification and financial incentives leads to the largest volume of reviews. But the relationship between gamification/financial incentives and the quality of the online reviews was not statistically significant. The results also suggested that the underreporting issue, where potential reviewers do not review because of time constraints and the effort required, can be mitigated by providing gamification and financial incentives. This study has important theoretical and managerial implications

Suppressing Epidemic Spreading via Contact Blocking in Temporal Networks

In this paper, we aim to effectively suppress the spread of epidemic/information via blocking/removing a given fraction of the contacts in a temporal (time evolving) human contact network. We consider the SI (Susceptible- Infected) spreading process, on a temporal contact network to illustrate our methodology: an infected node infects a susceptible node with a probability β when a contact happens between the two nodes. We address the question: which contacts should be blocked in order to minimize the average prevalence over time. We firstly propose systematically a set of link properties (centrality metrics) based on the aggregated network of a temporal network, that captures the number of contacts between each node pair. Furthermore, we define the probability that a contact c(i, j, t) is removed as a function of the centrality of the corresponding link l(i, j) in the aggregated network as well as the time t of the contact. Each of the centrality metrics proposed can be thus regarded as a contact removal strategy. Empirical results on six temporal contact networks show that the epidemic can be better suppressed if contacts between node pairs that have fewer contacts are more likely to be removed and if contacts happened earlier are likely removed. A strategy tends to perform better when the average number contacts removed per node pair has a lower variance. Strategies that lead to a lower largest eigenvalue of the aggregated network after contact removal do not mitigate the spreading better. This contradicts the finding in static networks, that a network with a small largest eigenvalue tends to be robust against epidemic spreading, illustrating the complexity introduced by the underlying temporal networks.Accepted author manuscriptMultimedia Computin

Examining the Impact of Yelp\u27s Elite Squad on Users\u27 Following Contribution

As one of the leading online review platforms, Yelp leverages a gamification design, Yelp Elite Squad (YES), to engage Yelp users. To become a YES member, users need to demonstrate a high level of community involvement, and therefore, they should significantly contribute to the Yelp community in the pre-YES period. To date, however, it is not clear how YES members behave after they receive this status. In this paper, we leverage a large volume of Yelp data to examine this question empirically. Using a dynamic panel analysis, we find that a YES member will produce more content in the subsequent period. We further find that if a user receives the YES status for two consecutive years, the most current YES status has a positive effect on users\u27 future contributions, but this effect is not as strong as the effect of a first-time status recipient. This research contributes to the online user engagement and gamification literature. We also offer practical implications for online community design

Does Online Social Support Work in Stigmatized Chronic Diseases? A Study of the Impacts of Different Facets of Informational and Emotional Support on Self-Care Behavior in an HIV Online Forum

We build an online social support model of self-care behavior for patients of stigmatized chronic diseases. We conceptualize three dimensions of informational support namely objective information, experiential information, and crowd consensus, and hypothesize their positive effect on self-care behavior. We conceptualize three dimensions of emotional support namely emotional tone, self-disclosure, and community involvement, and hypothesize their positive effect on self-care behavior. We also hypothesize how these dimensions interact with each other in promoting self-care behavior. Using data from 31,132 threads from an online health community for HIV patients, we test our hypotheses using Tobit regression. We find statistically significant support for our hypotheses, except for the interaction of experiential and objective information on self-care. Contrary to our hypotheses, we find that self-disclosure is negatively associated with self-care behavior. Our findings have important implications for management of stigmatized chronic diseases