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This study aims to empirically evaluate the effectiveness of government auditing of local authorities’ compliance with the procurement rules.

A diff-in-diff approach is used where the measure of compliance is (changes in) the incidence of private litigation under the Public Procurement Act, in audited vs non-audited municipalities. Further, semi-structured interviews were conducted with chief procurement officials.

No statistically significant effect is found. While strong effects of audits can be ruled out, the statistical results and the interviews do not, however, contradict a modest but long-lasting effect.

Few studies have addressed the effect of public procurement auditing on compliance. This study develops an empirical framework and presents empirical results.

This paper aims to examine the regional dynamics that further consolidated Israel’s national security in the Middle East in the aftermath of the Arab Spring, reflecting upon the nuclear challenge between Iran and Israel and Iran's expanding activities in the region.

To prove the central argument, the study uses a conceptual framework that centers on deterrence as the main approach used by states to consolidate their influence in the Middle East region.

Iran's nuclear progress and influence in the region has strengthened Israel’s security and fostered an unprecedented open rapprochement led by USA efforts with the Gulf regimes.

The paper draws particular attention to the Iran–Israel nuclear competency, and the Israeli preferred policy options regarding Iranian activities in the region amid turbulent Middle East. In addition, the paper offers insight to the regional dynamics that further consolidated Israel’s national security in the region while maintaining a status of Arab vulnerability and backwardness.

This paper attempts to develop a simple, static model of tax administration that is capable of explaining the widespread collusive petty tax administration corruption observed in developing countries.

This paper utilizes a positivist research framework and adopts a theoretical method of analysis, although secondary data will also be mentioned to support theoretical arguments whenever it is appropriate to do so.

A high rate of collusive tax corruption is inevitable in developing countries.

The model is static and needs to be extended into a dynamic model.

Traditional enforcement tools such as higher audits or a higher penalty regime against tax evasion do not work. Tax simplification can lessen the incidence of tax corruption.

Fighting tax corruption requires significant changes in the attitudes of taxpayers and tax auditors.

This paper combines the literature on Kantian economics and tax compliance in an innovative fashion.

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.

Prolonged exposure to daily stressors can have long-term detrimental implications for overall mental health. For asylum seekers in European Union transit or destination countries, navigating life in reception centres can represent a significant burden. The purpose of this study was to explore post-migration stressors during residency in reception centres, and to formulate recommendations for adequate service provision in Belgium.

Research was conducted in two reception centres in Belgium. A total of 41 in-depth interviews were carried out with asylum seeker residents (n = 29) and staff (n = 12). Purposive recruitment was used for asylum seekers (for variation in length of centre residency and family status) and staff (variation in job profiles). Interviews were conducted in English, French or with a translator in Arabic or Dari. Interviews were audio-recorded, transcribed verbatim and manually coded using thematic analysis.

Asylum seekers face significant constraints with regard to their living conditions, including total absence of privacy, overcrowding and unhygienic conditions. These act as continuous and prolonged exposure to daily stressors. Several barriers to accessing activities or integration opportunities prevent meaningful occupation, contribute towards eroded autonomy and isolation of asylum seeker residents. Inadequate capacity and resources for the provision of psychosocial support in reception centres leads to a sense of abandonment and worthlessness.

Analysis indicates that structural and practical challenges to adequately support asylum seekers are rooted in policy failures necessary for appropriate resourcing and prioritization of preventative measures. Such deliberate decisions contribute towards state deterrence strategies, eroding both individual well-being and manufacturing a crisis in the systems of support for asylum seekers.

The purpose of this study is to evaluate the current state of forensic accounting education in the Kingdom of Saudi Arabia (KSA), as well as to identify the desired aims and skills required to practice forensic accounting as a profession. It also seeks to understand the education and skills provided by KSA forensic accounting education programs, the job skills required by professional accountants and the skills required by professional accountants' employers.

The study is exploratory in nature. A convenience base sampling approach was used to select the academicians and practitioners working in KSA. Participants were requested to fill out an electronic questionnaire and rank each statement on a 5-point Likert score. The responses were converted and analyzed using the T-test, to evaluate the inter- and intra-group trends in the data.

The study included 58 responses from practitioners and 30 from academicians. Both groups mentioned that the classroom and the Internet were their primary source of forensic accounting information, especially in professional accounting qualifications. According to the participants, most of the institutions in KSA do not offer forensic accounting courses. Nonetheless, forensic accounting is critical for strengthening the credibility of financial reporting in courtrooms. The study finds subtle inter-group differences regarding the development of an ideal curriculum for forensic accounting, which translates to a bigger difference in curriculum development and practice skills. Both groups were optimistic about the future path of forensic accounting in KSA.

The study reports critical differences between the status of forensic accounting education and the skills required to practice forensic accountancy in KSA.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

This study aims to analyze the socio-ecological policy trade-off caused by technological innovations in the post-COVID-19 era. The study outcomes are utilized to design a comprehensive policy framework for attaining sustainable development goals (SDGs).

Study is done for 100 countries over 1991–2019. Second-generation estimation method is used. Innovation is measured by total factor productivity, environmental quality is measured by carbon dioxide (CO₂) emissions and social dimension is captured by unemployment.

Innovation–CO₂ emissions association is found to be inverted U-shaped and innovation–unemployment association is found to be U-shaped.

The study outcomes show the conflicting impact of technological innovation leading to policy trade-off. This dual impact of innovation is considered during policy recommendation.

The policy framework recommended in the study shows a way to address the objectives of SDG 8, 9 and 13 during post-COVID-19 period.

Policy recommendations in the study show a way to internalize the negative social externality exerted by innovation.

This study contributes to the literature by considering the policy trade-off caused by innovation and recommending an SDG-oriented policy framework for the post-COVID-19 era.

The purpose of this paper is to conduct a systematic review of the factors that shape tax morale. A large range of random explanatory variables identified in the literature as determinants of tax morale are synthesised and structured by drawing inspiration from the institutional theory.

To do this, a systematic search has been conducted using a library catalogue which provides access to more than 400 databases.

The finding is that the institutional theory provides a suitable theoretical basis to explore tax morale. Indeed, all the factors until now identified as determinants of tax morale (except the control variables/socio-demographic characteristics) can be categorised either as belonging to formal institutions or to informal institutions. The most salient factor is trust, with both vertical and horizontal trust positively related to tax morale.

The outcome is a call for a more nuanced understanding of not only the effect of formal and informal institutions on tax morale but also how formal and informal institutions interact and alter each other and, consequently, affect tax morale.

The paper seeks to encourage governments to start recognising that as low tax morale arises when a gap exists between formal and informal institutions, they need to design policy measures aimed to reduce this gap, rather than persisting with deterrence measures.

This is the first systematic review of the factors that influence tax morale using an institutionalist lens.