Search results

A growing body of literature focuses on crime hotspots; however, less is known about the spatial distribution of crime at mass transit systems, and even less is known about trajectory patterns of hotspots in non-English-speaking countries.

The spatiotemporal behaviour of 1,494 crimes reported to the Hong Kong’s Railway Police District across a two-year period was examined in this study. Crime harm weights were then applied to offences to estimate the distribution of crime severity across the transit system. Descriptive statistics are used to understand the temporal and spatial trends, and k-means longitudinal clustering are used to examine the developmental trajectories of crime in train stations over time.

Analyses suggest that 15.2% and 8.8% of stations accounted for 50% of all counted crime and crime harm scores, respectively, indicating the predictability of crime and harm to occur at certain stations but not others. Offending persists consistently, with low, moderate and high counts and harm stations remaining the same over time.

These findings suggest that more localised crime control initiatives are required to target crime effectively.

This is one of the only studies focusing on hotspots and harmspots in the mass transit system.

High divorce rates have coincided with higher rates of remarriage. Although remarriages are more susceptible to dissolution than first-order marriages, less research has focused on factors that promote vulnerabilities among remarried couples. In the current study, the authors focused on whether predictors of divorce differ by the number of times someone has been married. The authors examined some of the most common reasons for divorce, as identified by parents who completed a state-mandated divorce education course (n = 8,364), while also controlling for participant sociodemographic characteristics. Participants going through their first divorce were more likely to identify growing apart and infidelity as reasons for seeking a divorce. Conversely, those going through a subsequent divorce were more likely to list problems with alcohol/drug abuse, childrearing differences, emotional/psychological/verbal mistreatment, money problems, physical violence, and arguing. Multivariate analyses indicated that sociodemographic factors were stronger predictors of divorce number than commonly listed reasons for divorce for both male and female participants. Implications for remarital and stepfamily stability and directions for future research are discussed.

Most studies explore the success of mergers and acquisitions through ex ante analyses based on the compatibility of resources and capabilities between the acquirer and target. As more than half of them fail, there seems to be room for enhancing our understanding of when and how acquisitions can actually improve firms' competitiveness. Diverging from these conventional approaches, the authors posit that attention should be at the strategic level. The purpose of this paper, therefore, is to explore the existence of compatibility between acquirers’ and targets’ competitive strategies and its effect on post-acquisition business performance.

Through the Thomson Reuters Eikon financial and acquisition databases, the authors built a unique data panel of 174 acquirer–target matched acquisitions in the manufacturing sector from 24 different countries between 2000 and 2020. The authors used a two-step System-GMM approach to address the hypotheses proposed in this paper. This methodology allowed to isolate and easily compare the differential effects of each possible combination of strategic similarity and dissimilarity between the target and acquiring company on the latter’s post-acquisition strategies.

The need to unravel the motives behind successful acquisitions has gained enormous interest in recent years among academics and managers to improve – or maintain – firm competitiveness. Through a panel data of 174 acquisitions among manufacturing firms (2000–2020), this study shows that differentiated firms improve their business performance by acquiring firms with similar strategies; nevertheless, their performance worsens if the acquired firm follows a cost-leadership strategy. Concerning acquirers with a cost-leadership strategy, the lack of clear behavioral patterns suggests that the lower knowledge absorption capacity associated with these firms might be a decisive factor in being able to assimilate and efficiently exploit the acquired firm's knowledge.

Overall, this approach offers a new and valuable perspective for practitioners because it improves understanding of the possible causes of merger failure and opens new attentions to consider in maximizing success and long-term competitiveness. The results of this study bring, thus, an unexpected result to this research: the importance of the acquirer’s strategy beyond the similarity or dissimilarity of the strategies of the acquirer and the acquired company.

While prior research has established that traumatic brain injury (TBI) is a risk factor for violent offending, there is little understanding of mechanisms that may underpin this relationship. This is problematic, as a better understanding of these mechanisms could facilitate more effective targeting of treatment. This study aims to address these gaps in the extant literature by examining TBI as a predictor of violent offending and test for mediation effects through cognitive constructs of dual systems imbalance and hostility among a sample of justice-involved youth (JIY).

The Pathways to Desistance data were analyzed. The first three waves of this data set comprising the responses of 1,354 JIY were analyzed. Generalized structural equation modeling was used to test for direct and indirect effects of interest. A bootstrap resampling process was used to compute unbiased standard errors for determining the statistical significance of mediation effects.

Lifetime experience of TBI was associated with increased violent offending frequency at follow-up. Hostility significantly mediated this relationship, but dual systems imbalance did not. This indicated that programming focused on reducing hostility among JIY who have experienced TBI could aid in reducing violent recidivism rates.

To the best of the author’s knowledge, this study was the first to identify significant mediation of the relationship between TBI and violent offending through hostility.

A considerable amount of police evaluation research focuses on innovative approaches to reduce crime at places. This is hardly coincidental; policing and place-based scholars have found crime is highly concentrated, and when police focus on these places, they can prevent and reduce crime. The regularity of such findings led Weisburd (2015) to assert the existence of a “law of crime concentration.” Given that bold assertion, the authors test whether the law of crime concentration is generalizable to one of the most common public safety concerns that police handle—traffic crashes.

To determine whether the law of crime concentration applies to traffic crashes, the authors examined crash locations and times in all counties in Utah across four years. Following and expanding on Weisburd's methods, the authors calculate the bandwidth of concentration for these crashes and analyze various types by severity and possible explanations for variations in crash concentrations across the state.

A small proportion of street segments and intersections experience a disproportionately high number of crashes, and the degree of concentration of crashes may be even higher than that of crime. Further, there are variations in the levels of crash concentration across counties and in the severity of injuries resulting from the crashes.

Place-based criminologists and policing scholars have not often explored traffic crashes in their analyses. Yet, traffic problems take up a significant amount of law enforcement time and resources and are often priorities for most law enforcement agencies. Given what the authors know from traffic, policing and crime and place research, targeted approaches at micro traffic crash hot spots can be beneficial for public safety prevention.

This study is the first to explore the application of Weisburd's Law of Crime Concentration to traffic crashes. Given that police spend a significant amount of time and resources on traffic-related problems in their jurisdiction, finding more effective, evidence-based approaches to address this public safety concern should be a high priority for police and researchers alike.

The purpose of this paper is to review the utilization of game theory in the entrepreneurship literature. Game theory can potentially be employed to assess strategies incentivizing productive entrepreneurial activities and subsequent economic development. Therefore, the author reviews entrepreneurship articles and explores the application of game-theoretic models and concepts in the literature.

First, the author provides an overview of the entrepreneurship ecosystem concept, highlighting key challenges in its study. The author also briefly highlights successful applications of game theory in the innovation literature. Second, the author systematically reviews and synthesizes entrepreneurship research employing game-theoretic models and concepts. The author's objective is to provide a state-of-the-art overview of the use of game theory in entrepreneurship.

Broadly, the author categorizes entrepreneurship-game theory articles into three groups based on their scope and purpose: entrepreneurial policy applications, inter-firm applications and entrepreneurship theory applications. Entrepreneurial policy applications include entrepreneurs and the government or policy as the main players in a game. Inter-firm applications encompass games between entrepreneurs and other private entities. Entrepreneurship theory applications include articles that utilize game theory to advance the author's understanding of entrepreneurial behavior and/or mechanisms in the market.

To the best of the author's knowledge, no previous paper has reviewed the use of game-theoretic approaches and models in entrepreneurship literature. This study addresses this research gap.

Building on the arguments of expectancy theory and social exchange theory, the present study provides insights into the process by which pay-for-performance (PFP) impacts employee job performance.

Based on a sample size of 226 employees working in a technology company in India, the study examines the relationships between PFP, procedural justice, organizational citizenship behavior (OCB) and employee job performance. Data on perceptions of PFP and procedural justice were collected from the employees, data on OCB were collected from the supervisors and the data on employee job performance were collected from organizational appraisal records.

The study found support for the positive relationship between PFP and job performance and for the sequential mediation of the relationship between PFP and job performance via procedural justice and OCB. Further, procedural justice was found to mediate the relationship between PFP and OCB.

The study was cross-sectional, so inferences about causality are limited.

The study tests the relationship between PFP and employee job performance in the Indian work context. The study shows that the existence of PFP is positively related to procedural justice which, in turn, is positively related to OCB. The study found support for the sequential mediation of PFP-job performance relationship via procedural justice and OCB.

The study provides an insight into the underlying process through which PFP is related to employee job performance. To the best of our knowledge, such a study is the first of its kind undertaken in an organizational context.

During the Covid-19 outbreak, universities around the globe were closed or went online due to lockdowns implemented to curb the pandemic's spread. This study aims to examine the changes in Malaysian academics' job and life satisfaction during a testing four-month period, from the beginning of the first Covid-19 lockdown until two months after it ended. It also assesses the impact of affective states and age group on these two constructs.

In this longitudinal study, the authors collected data from 220 academics in Malaysia at three time points in 2020, namely the beginning of the lockdown (April), the end of the lockdown (June) and two months after the lockdown (August). The authors applied multivariate latent growth curve (LGC) modeling to study changes in job satisfaction and life satisfaction. In addition, we added age group, as a time-invariant covariate, as well as positive and negative affect, as two time-varying covariates, to our LGC model. The authors estimated the LGC model using the EQS 6.4 statistical package.

The results show that both job and life satisfaction were stable over time, although their means were below the average. Positive affect was a significant predictor of both types of satisfaction, and age group was a significant predictor of job satisfaction.

The main implication the authors draw from this study is connected to job and life satisfaction's mean values being below average. In line with the affective events theory (AET), the authors recommend paying particular attention to work environment features, such as providing sufficient infrastructure for employees working from home and keeping social relations intact. Especially young academics should receive sufficient support.

The study is one of a limited number that examined longitudinal effects during the Covid-19 pandemic in the domains of human resource management and organizational behavior. Hence, this study expands our knowledge of employees' affect and attitudes during an unprecedented global health crisis, particularly in the under-researched area of the Malaysian higher education sector.

Vehicle companion is one of the most common companion patterns in daily life, which has great value to accident investigation, group tracking, carpooling recommendation and road planning. Due to the complexity and large scale of vehicle sensor streaming data, existing work were difficult to ensure the efficiency and effectiveness of real-time vehicle companion discovery (VCD). This paper aims to provide a high-quality and low-cost method to discover vehicle companions in real time.

This paper provides a real-time VCD method based on pro-active data service collaboration. This study makes use of dynamic service collaboration to selectively process data produced by relative sensors, and relax the temporal and spatial constraints of vehicle companion pattern for discovering more potential companion vehicles.

Experiments based on real and simulated data show that the method can discover 67% more companion vehicles, with 62% less response time comparing with centralized method.

To reduce the amount of processing streaming data, this study provides a Service Collaboration-based Vehicle Companion Discovery method based on proactive data service model. And this study provides a new definition of vehicle companion through relaxing the temporal and spatial constraints for discover companion vehicles as many as possible.