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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 identify if fraud theory models suggested over the years are applicable to match-fixing and if so, whether the Krambia-Kapardis’ (2016) holistic fraud and corruption prevention model can be used to reduce significantly match-fixing in football.

An online survey was developed by the authors and was administered to football stakeholders in Cyprus, namely, players, referees, coaches and team management.

The research questions, who are the initiators of match-fixing, why is match-fixing taking place and what is the best way to prevent or reduce match-fixing, have been answered, and these findings have enabled the authors to make policy recommendations.

The survey considered match-fixing in only one sport (football) while the number of respondent categories and the 335 usable questionnaires returned did not allow advanced statistical analysis of the data obtained.

The findings point to the need both for ethics and moral values to be installed in all the stakeholders through training and continuing education. It is also suggested that teams/clubs and related associations acting as regulators ought to implement governance principles and ethical programs, including whistleblowing lines and appoint integrity officers to minimize the match-fixing phenomenon. Furthermore, society, as well as government, sport regulators and sponsors, ought to encourage and demand fair play and integrity in sport through improved measures of governance and accountability and the implementation of ethical audits and public disclosure of audited financial statements of teams. Finally, sports integrity ought to be embedded in school curriculum from a very young age.

To the best of the authors’ knowledge, this is an original contribution to knowledge that has impact on the future of sporting fairness and social legitimacy.

Various organizational landscapes have evolved to improve their business processes, increase production speed and reduce the cost of distribution and have integrated their Internet with small and medium scale enterprises (SMEs) and third-party vendors to improve business growth and increase global market share, including changing organizational requirements and business process collaborations. Benefits include a reduction in the cost of production, online services, online payments, product distribution channels and delivery in a supply chain environment. However, the integration has led to an exponential increase in cybercrimes, with adversaries using various attack methods to penetrate and exploit the organizational network. Thus, identifying the attack vectors in the event of cyberattacks is very important in mitigating cybercrimes effectively and has become inevitable. However, the invincibility nature of cybercrimes makes it challenging to detect and predict the threat probabilities and the cascading impact in an evolving organization landscape leading to malware, ransomware, data theft and denial of service attacks, among others. The paper explores the cybercrime threat landscape, considers the impact of the attacks and identifies mitigating circumstances to improve security controls in an evolving organizational landscape.

The approach follows two main cybercrime framework design principles that focus on existing attack detection phases and proposes a cybercrime mitigation framework (CCMF) that uses detect, assess, analyze, evaluate and respond phases and subphases to reduce the attack surface. The methods and implementation processes were derived by identifying an organizational goal, attack vectors, threat landscape, identification of attacks and models and validation of framework standards to improve security. The novelty contribution of this paper is threefold: first, the authors explore the existing threat landscapes, various cybercrimes, models and the methods that adversaries are deploying on organizations. Second, the authors propose a threat model required for mitigating the risk factors. Finally, the authors recommend control mechanisms in line with security standards to improve security.

The results show that cybercrimes can be mitigated using a CCMF to detect, assess, analyze, evaluate and respond to cybercrimes to improve security in an evolving organizational threat landscape.

The paper does not consider the organizational size between large organizations and SMEs. The challenges facing the evolving organizational threat landscape include vulnerabilities brought about by the integrations of various network nodes. Factor influencing these vulnerabilities includes inadequate threat intelligence gathering, a lack of third-party auditing and inadequate control mechanisms leading to various manipulations, exploitations, exfiltration and obfuscations.

Attack methods are applied to a case study for the implementation to evaluate the model based on the design principles. Inadequate cyber threat intelligence (CTI) gathering, inadequate attack modeling and security misconfigurations are some of the key factors leading to practical implications in mitigating cybercrimes.

There are no social implications; however, cybercrimes have severe consequences for organizations and third-party vendors that integrate their network systems, leading to legal and reputational damage.

The paper’s originality considers mitigating cybercrimes in an evolving organization landscape that requires strategic, tactical and operational management imperative using the proposed framework phases, including detect, assess, analyze, evaluate and respond phases and subphases to reduce the attack surface, which is currently inadequate.

The research aim of this article is to generate novel insights into how public sector organizations (PSOs) strategically communicate with the public about critical issues on social media. To this end, the study explores the public's experiences of the Swedish Police's sense of safety communication on Instagram in the third largest city in Sweden, where the lack of a sense of public safety is a main societal challenge.

The research was designed as a case study employing photo-elicitation interviews as a method to collect the empirical material. A phenomenography approach was used to analyze public experiences of the Swedish Police's Instagram communication in Malmö, Sweden.

Findings show that the police's strategic communication of safety on Instagram is experienced along the dimensions of a sense of protection, a sense of proximity and a sense of ambiguity. Taken together, these dimensions broaden and develop the knowledge of what communicating a sense of safety in the public sphere entails.

This study adds to previous research on strategic communication in public sector organizations by demonstrating what strategic communication accomplishes at the receiving end outside of the organization.

The purpose of this paper is to give an account for preparative collaboration between the police and municipal eldercare in Sweden concerning missing persons with dementia.

Design/methodology/approach used was a qualitative case study design, consisting of one focus group with representatives for the participating organisations, followed by directed content analysis.

The findings showed a lack of current collaboration and reluctance to new collaborative initiatives. However, when focussing on preparative collaboration of coordinated responses to missing incidents, possibilities for improvement could be identified. The improvements concerned updated personnel response checklists, along with suggestions for an elaborate life story document in eldercare, with police access. Finally, better coordination of the return of the found person and a follow up were proposed.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal collaboration is more suitable. The amount of data in this study is a research limitation which calls for further research.

It is suggested that collaboration must be given different meanings and use different approaches adapted to the different phases in a rescue operation. In the preparation and the response phase, the focus should be on coordination of the resources available. In the pre-planning and prevention phases, as well as in evaluation and learning, horizontal co-operation is more suitable.

The originality/value of this paper can be found in the novelty of missing person research in Sweden, and in practical suggestions for preparative collaboration concerning persons with dementia who go missing. Finally, it can be found in the suggested need for a more dynamic and process-sensitive view of collaboration in SAR or rescue operations.

The emergence of machine learning has opened a new way for researchers. It allows them to supplement the traditional manual methods for conducting a literature review and turning it into smart literature. This study aims to present a framework for incorporating machine learning into financial statement fraud (FSF) literature analysis. This framework facilitates the analysis of a large amount of literature to show the trend of the field and identify the most productive authors, journals and potential areas for future research.

In this study, a framework was introduced that merges bibliometric analysis techniques such as word frequency, co-word analysis and coauthorship analysis with the Latent Dirichlet Allocation topic modeling approach. This framework was used to uncover subtopics from 20 years of financial fraud research articles. Furthermore, the hierarchical clustering method was used on selected subtopics to demonstrate the primary contexts in the literature on FSF.

This study has contributed to the literature in two ways. First, this study has determined the top journals, articles, countries and keywords based on various bibliometric metrics. Second, using topic modeling and then hierarchy clustering, this study demonstrates the four primary contexts in FSF detection.

In this study, the authors tried to comprehensively view the studies related to financial fraud conducted over two decades. However, this research has limitations that can be an opportunity for future researchers. The first limitation is due to language bias. This study has focused on English language articles, so it is suggested that other researchers consider other languages as well. The second limitation is caused by citation bias. In this study, the authors tried to show the top articles based on the citation criteria. However, judging based on citation alone can be misleading. Therefore, this study suggests that the researchers consider other measures to check the citation quality and assess the studies’ precision by applying meta-analysis.

Despite the popularity of bibliometric analysis and topic modeling, there have been limited efforts to use machine learning for literature review. This novel approach of using hierarchical clustering on topic modeling results enable us to uncover four primary contexts. Furthermore, this method allowed us to show the keywords of each context and highlight significant articles within each context.