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The purpose of this paper is to estimate the implications of illicit market use for the value of Bitcoin in an event studies framework.

This study uses a data set of 58 state-level marijuana decriminalisation and legalisation bills and referenda in the USA in 2010–2022.

Decriminalisation is associated with a strong and consistent positive Bitcoin price response around the event, recreational legalisation induces a more ambiguous reaction and medical legalisation is found to have a negative albeit small impact on Bitcoin value. This suggests decriminalisation enhances shadow economy use value of Bitcoin, whereas recreational and medical legalisation are not consistently reducing illicit drug cryptomarket activity. The effects are robust to various estimation windows, in subsamples, and also when outliers, heavy tails, conditional heteroskedasticity and state size are accounted for.

New to the literature, the choice of US marijuana bills, specifically as sample events, is based on both theoretical and empirical grounds.

“Web3” is a practice in participatory digital infrastructures through the ability to read, write, and control own digital assets. Web3 is hailed as the alternative to the failings of big tech, offering a participatory mode of digital organization and shared ownership of digital infrastructure through algorithmic governance. This paper offers an introductory playbook to researchers entering the field of Web3 by providing an analytical lens to approach the emergent field of Web3 as “infrastructuring.” It argues that Web3 can be understood as a collective, community exploration of “how to infrastructure.” Drawing on qualitative examples derived from digital ethnographic methods, the study reveals that play, politics, and prefiguration are fundamental qualities underpinning Web3’s vision of offering an “exit” from established institutional infrastructures. Therefore, a primary challenge Web3 faces in its governance experiments centers around the question of how to effectively build and manage infrastructure.

The objective of this paper is to explore the development of the Blackmail-as-a-Service business model within the Digital Thrift Shop. This service model involves the sale of doxing files to customers, as well as the removal of the content from the shop and its dissemination to victims or individuals closely connected to them.

To access the Digital Thrift shop, this study relies on the Tor browser and a darknet indexing site. The authors then use an application to collect and store the web pages as PDFs. Finally, content analysis is performed on these PDFs to understand the Blackmail-as-a-Service business model developed by the Digital Thrift.

The doxing data available on the Digital Thrift is primarily targeted toward women. Digital Thrift has also established a way to value the purchase, sale and the removal of blackmail data. The presence of Blackmail-as-a-Service on darknet sites poses unique challenges for criminal justice agencies in terms of jurisdiction, due to the lack of harmonized laws and the obstacles involved in taking down content from darknet sites. Finally, the use of a service model for blackmail allows criminals without technical skills to engage in cyber-victimization using blackmail.

Research into Blackmail-as-a-Service from boutique providers has not been conducted. To the best of the authors’ knowledge, this is one of the first study seeking to understand the Blackmail-as-a-Service business model on the darknet when used to target adults. This study presents evidence of a lack of connection between the buyers of the compromising material and the potential victim, challenging preconceived notions about image-based sexual abuse and its connection to individuals involved in interpersonal relationships.

Exhibiting an unprecedented rate of advancement, technology’s progression over the past two decades has regrettably led to a disturbing increase in the distribution of child sexual abuse materials (CSAM) online. Compounded by the emergence of an underground cryptocurrency market, which serves as a primary distribution channel for these materials, the investigation and sanctioning of CSAM present a complex and unique set of challenges. The purpose of this study is to accurately diagnose the CSAM sentencing landscape and build a more comprehensive, evidence-based legal framework in penology.

The study collected and analyzed case details regarding CSAM sanctions in a database sourced from the US Department of Justice for 2020. Various factors were analyzed such as the victim’s age, offender typology and previous conviction, accompanied by an analysis of how these factors affect the sentence length.

The study found that the hierarchical agency-level interactions give insight into resource allocation prioritization, as well as confirming a close relationship between prior conviction history and sentence length, with the victim’s age inversely related to sentence length. Leveraging data-driven insights, the study paves the way for more targeted and effective sanctions, ultimately contributing to the broader goal of safeguarding children from online sexual exploitation.

The paper provides a critical analysis of the complex landscape surrounding CSAM distribution and judicial sentencing. By examining case details and leveraging data-driven insights, it offers valuable contributions to understanding the interplay between various factors such as victim age, offender typology and prior convictions on sentencing outcomes. This comprehensive approach not only sheds light on the dynamics of CSAM sanctions but also lays the groundwork for evidence-based legal frameworks in penology. Its originality lies in its nuanced examination of hierarchical agency interactions and its potential to inform more targeted interventions for safeguarding children from online exploitation.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

Drawing from the Moral Disengagement theory and the Social Exchange Theory, the present study posits to examine the influence of personality, that is Machiavellianism on organizational deviance in the service industry. Furthermore, the role of moral disengagement as a mediator accentuating the organizational deviance of service employees was examined. Also, the role of Servant Leadership as a moderator on the mediated relationship between Machiavellianism and Organizational Deviance via Moral Disengagement is investigated.

The data was collected from 269 employees working in hotels in northern India using the snowball technique. SPSS 22 and AMOS 22 were the statistical tools utilized to test the hypothesized relationships.

Machiavellianism was positively related to Organizational Deviance. Findings support the fact that Moral disengagement is a mediator in the relationship between Machiavellianism and Organizational Deviance. Service Leadership moderated the mediated relationship between Machiavellianism and Organizational deviance via Moral disengagement such that the relationship was found to be weaker when Service Leadership was high.

Due to its emphasis on interpersonal interaction and intangible services, the hotel industry differs from other sectors of the economy. Employees contact directly with clients and are responsible for meeting their demands. As a result of these frequent interactions, controlling employee deviation is essential in the services industry. The study holds significant and notable implications from the organizational or managerial perspective.

The present study distinctively contributes by bringing the effect of personality on deviant behaviors in the hotel industry which is unmapped, besides examining the role of moral disengagement as the mediator and servant leadership as a moderator mitigating organizational deviance and morally disengaged workforce.

This study aims to explore the impact of cryptocurrency on intelligence activities by law enforcement agencies, focusing on the changing landscape due to its exploitation by terrorist organizations. Investigating the dual nature of cryptocurrency as a global payment system and a potential threat to national security, the purpose is to understand how law enforcement adapts its strategies in response to this evolving challenge.

The research uses a comprehensive approach by analyzing the integration of research and collection stages within the intelligence circle, particularly emphasizing blockchain analysis. By examining the actions of law enforcement authorities in the case study of Hamas’ crypto fundraising campaign, the study highlights how open-source information, accessible through blockchain, allows for strategic collaboration between law enforcement authorities and specialist companies in the field of intelligence analysis. This methodology enables law enforcement to enhance their intelligence gathering capabilities to trace illicit activity by terrorist organizations, leading to a successful seizure of crypto funds.

The findings reveal a symbiotic relationship between terrorist organizations and the crypto space, with the latter becoming an attractive means for financing activities. Law enforcement, in response, has evolved its intelligence practices, combining collection and research to trace and crack down on illicit crypto transactions.

The study sheds light on the dynamic challenges faced by law enforcement in maintaining an effective intelligence response to the ever-evolving methods used by terrorist organizations in using cryptocurrencies.

This study aims to improve the mechanical properties of an object produced by fused deposition modelling with high-grade polymer.

The study uses an ensembled surrogate-assisted evolutionary algorithm (SAEA) to optimize the process parameters for example, layer height, print speed, print direction and nozzle temperature for enhancing the mechanical properties of temperature-sensitive high-grade polymer poly-ether-ether-ketone (PEEK) in fused deposition modelling (FDM) 3D printing while considering print time as one of the important parameter. These models are integrated with an evolutionary algorithm to efficiently explore parameter space. The optimized parameters from the SAEA approach are compared with those obtained using the Gray Relational Analysis (GRA) Taguchi method serving as a benchmark. Later, the study also highlights the significant role of print direction in optimizing the mechanical properties of FDM 3D printed PEEK.

With the use of ensemble learning-based SAEA, one can successfully maximize the ultimate stress and percentage elongation with minimum print time. SAEA-based solution has 28.86% higher ultimate stress, 66.95% lower percentage of elongation and 7.14% lower print time in comparison to the benchmark result (GRA Taguchi method). Also, the results from the experimental investigation indicate that the print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3D printed high-grade thermoplastic PEEK polymer.

This study is valid for the parameter ranges, which are defined to conduct the experimentation.

This study has been conducted on the basis of taking only a few important process parameters as per the literatures and available scope of the study; however, there are many other parameters, e.g. wall thickness, road width, print orientation, fill pattern, roller speed, retraction, etc. which can be included to make a more comprehensive investigation and accuracy of the results for practical implementation.

This study deploys a novel meta-model-based optimization approach for enhancing the mechanical properties of high-grade thermoplastic polymers, which is rarely available in the published literature in the research domain.

This paper aims to explore the potential role of digitalization in reshaping Botswana's assets and liabilities declaration system. Digitalization presents opportunities to not only improve efficiencies in how services are delivered and citizens are engaged but also to integrate innovative ways to combat wicked problems such as illicit enrichment and conflicts of interest in the public service.

This qualitative paper adopts an exploratory research design to investigate how digital technologies can be used to enhance anti-corruption reforms in a developing country context. Primary data, focusing on the shortcomings and successes of Botswana’s asset declaration system, were collected from interviews with key policy actors in Botswana’s anti-corruption landscape, whereas secondary data were drawn from documents such as official reports, news and social media reports and available literature on the topics of digitalization and anti-corruption reforms. A comparative case study approach is used, highlighting successes and challenges in the use of electronic disclosure systems in Georgia, Ukraine and South Africa.

The analysis provides insights into the potential benefits and challenges associated with the integration of digital technologies in the asset and liability declaration process. The integration of digital technologies in the anti-corruption efforts of Georgia, Ukraine and South Africa has contributed to the development of robust electronic declaration systems. However, political resistance, costs, technical capacity and verification processes are identified as some of the core challenges confronting agencies tasked with implementing asset declaration systems.

The political and socio-economic contexts in the country case studies presented are distinct, as are the challenges posed by corruption. Although Botswana can gain insights from the implementation experiences of Georgia, Ukraine and South Africa, policymakers and implementers need to take into account these subtleties and their potential influence on the success or failure of a similar system. The research has implications for policy and practice by proposing an alternative approach to the implementation of Botswana’s asset declaration system. This will be of interest to policymakers, anti-corruption activists and scholars.

To the best of the authors’ knowledge, prior research has not studied the relationship between digitalization and anti-corruption reforms in Botswana. This paper contributes to the dearth of knowledge regarding the role of digitalization as a driver of anti-corruption reforms. The paper informs policy decisions related to the implementation of digital transformation initiatives in line with Botswana’s anti-corruption and digital transformation agendas.