Level Of Corruption Research Articles

Indirect Value of Public Infrastructure Technology

Although prior research has primarily focused on the direct value of information technology (IT) and IT adoption by individuals and firms, this study explores the indirect value of IT in the form of public infrastructure technology. By exploiting a spatial discontinuity in water monitoring stations, we discover that firms located immediately upstream of water monitoring stations exhibit significantly lower levels of corruption than firms located immediately downstream. These findings are particularly noteworthy given that water monitoring stations have the potential to generate significant indirect value as they are not explicitly designed to mitigate corruption. Further analyses reveal that public infrastructure technology alone does not hold the key to mitigating corporate corruption. Instead, it is the synergistic interplay between public infrastructure technology and organizational change that drives the outcome. These findings contribute to a deeper understanding of the broader IT value landscape, emphasizing the indirect value of technological advancements in public infrastructure that were not originally intended for such benefit. Additionally, our findings highlight the benefits of leveraging existing infrastructure technology to address emerging societal needs. This paper was accepted by D. J. Wu, information systems. Funding: J. Liu acknowledges financial support from the National Natural Science Foundation of China [Grant 72402127], Shanghai Pujiang Program [Grant 23PJC059] and the Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission [Grant 23CGA10]. S. Pei acknowledges financial support from the National Natural Science Foundation of China [Grant 72302139]. X. (M.) Zhang acknowledges financial support from the Hong Kong Research Grants Council [Grants GRF 14500521, GRF 14501320, GRF 165052947, and TRS:T31-604/18-N]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01145 .

Corruption impedes good governance in Somalia’s public sector

Purpose The purpose of this paper is to understand the level of corruption in Somalia and the causes that lead to corruption that in turn hampers good governance. Design/methodology/approach The paper relies on the data collected from Somali’s public institutions, international actors, newspaper articles and peer-reviewed literature. The degree of corruption is assessed with the Corruption Perceptions Index by Transparency International and the Control of Corruption provided by the World Bank. Findings The finding shows that the level of corruption in Somalia is high and complex because of the following reasons: weak governance and poverty, culture and tradition which include favoritism based on clan membership, lack of accountability mechanism and absence political will. Measures undertaken for anti-corruption, for instance, the establishment of the National Anti-Corruption Commission and legislation for its support face barriers and challenges that include political influence, lack of capacities among the undertaking institution and lack of participation by the public. Originality/value This research adds value to the knowledge of corruption in Somalia by identifying the concrete socio-political antecedents for corruption and the problems of fighting it. This paper further presents the following detailed strategies to address corruption: enhancing the operational and financial integrity of the Independent Anti-Corruption Commission; restructuring the civil service and merging it into a merit-based system; enhancing Public Financial Management (PFM) reforms; independence of the judiciary; and sustaining development in digital technology adoption in governance and procurement.

Suspicious activity reporting in emerging economies: the case of Iran

PurposeCountries with high levels of corruption can experience collusion between powerful elites and accountants to conceal, disguise and clean the proceeds of criminality. This study investigates the willingness of accountants to report evidence of money laundering in an emerging economy, Iran, notwithstanding potential personal and professional risks implicit in such due diligence. It evaluates the relevance of personal characteristics of accountants to the propensity to report, and the implications for policy makers in terms of audit team composition.Design/methodology/approachThe methodology is quantitative. Data was gathered by means of a suspicious activity scenario-based questionnaire administered to 1,128 of Certified Public Accountants in Iran, of which 281 responses were received. Four hypotheses were tested relating to the implications, if any, of gender, age, education and working experience for the propensity to report red flags indicative of money laundering.FindingsData revealed that accountants were generally more willing to report activity indicative of money laundering than was anticipated in an environment perceived to be characterised by professional and personal risks. Older accountants are more risk averse and more likely to report suspicious activity than younger counterparts who tend to disregard borderline indicators of money laundering. A significant red flag indicator of money laundering is a client's reluctance to provide information regarding controlling shareholders, debtors and creditors or to explain contrived and opaque corporate structures. Audit teams may be more effective when gender-balanced: female accountants tend to be more willing to report suspicious activity than male counterparts, reducing the risk of interference by powerful elites.Research limitations/implicationsThe time frame over which the research was conducted was a single year; if it had been conducted over several years it may have revealed more nuanced and evolving reporting behaviour. The study was limited to Iran: a cross-comparison with another emerging economy or economies may have revealed useful contrasts.Originality/valueThe study contributes to behavioural accounting research in emerging economies. Limited empirical data is available regarding the influence of personal characteristics of accountants on their willingness to report suspicious activity in corrupt environments where personal safety and professional security may be at risk from powerful elites. It evaluates the implications of these for suspicious activity reporting policy, and for improving the effectiveness of the scrutineering role of audit teams. An innovative questionnaire was designed which may be suitable for future comparable research in emerging economies.

ARTIFICIAL INTELLIGENCE AS AN INNOVATIVE TOOL OF CORRUPTION PREVENTION IN JUDICIARY: THE ADVANTAGES

There has been made an attempt in the article to assess the possibility and expediency of application of information and communication technologies and their highest manifestation – artificial intelligence – as an anti-corruption tool in the judiciary. The essence and modern forms of the artificial intelligence phenomenon and its connection with information and communication technologies have been analyzed. There has been researched national and foreign legal regulation on the application of artificial intelligence both in the field of public administration in general and in the field of the judiciary and administration of justice in particular. The cases of the most «significant» corruption events in the judiciary have been presented and an attempt to find out the reasons of the failure of traditional tools to prevent corruption has been made. There has been called into question the ability of the state to overcome such a negative socio-power phenomenon as corruption without the implementation of radical steps which have long been overdue and became even more actualized during the armed conflict. Some positive examples of the information and communication technologies use in the judiciary have been demonstrated. Separate advantages of using artificial intelligence as a new tool for preventing corruption in the administration of justice have been briefly systematized. There has been emphasized that artificial intelligence due to its impartiality is fully capable to ensure the realization of the right to a fair trial, preserving time, financial and human resources, and reducing the level of corruption. At the same time, there has been underlined that without studying the risks and threats of using computer programs at this level of their development, relying only on them as a panacea for the destruction of corruption practices is imprudent and premature. Finally, an impulse for further research of artificial intelligence and its features as a tool of corruption prevention in the judicial system has been given.

How does auditing outgoing officials' natural resource asset management policies affect carbon emission efficiency? Evidence from a debiased machine learning model

Reducing carbon emissions to improve environmental quality has been the Chinese government's unwavering dedication in recent years. Several policies have been implemented with the objective of driving carbon reduction. The implementation of the outgoing leadership natural resources audit policy has played a pivotal role in encouraging local government officials to prioritize both economic and environmental development in their pursuit of performance metrics. However, whether the implementation of this policy contributes to an enhancement in carbon emission efficiency requires further empirical validation. This study, utilizing panel data from 282 cities across China, explores the potential impact of the audit policy (specifically referring to the outgoing leadership natural resources asset audit policy, without ambiguity) on carbon emission efficiency through the application of a debiased machine learning model. The results of the study show that the audit policy has been crucial in greatly raising the regional level of carbon emission efficiency. Furthermore, mechanistic analysis results suggest that the audit policy can enhance regional carbon emission efficiency by influencing green innovation and raising government environmental awareness and green financial levels. Based on the heterogeneity analysis, the regions east of the Hu Line, cities with low levels of corruption, less stringent economic growth objectives, and areas with high levels of public environmental concern are the areas where auditing rules have the greatest influence on carbon emission efficiency. In conclusion, based on the comprehensive results of this study, a series of policy recommendations are presented to further advance China's efforts in carbon reduction, ultimately achieving a more sustainable balance between economic and environmental development objectives.

Strengthening the fight: is the adoption of IPSAS helping Latin America tackling corruption?

PurposeThis paper examines the relationship between the adoption of accrual-based IPSAS and the level of perceived corruption of Latin-American countries, considering the moderating effect of the country’s institutional quality.Design/methodology/approachThe study adopted a longitudinal analysis of 19 countries, between 2010 and 2020, following a quantitative approach by using multiple linear regression with panel data.FindingsMain findings indicate that the harmonization of public sector accounting through the adoption of IPSAS generates a positive effect on the corruption level in Latin-American countries, causing a reduction in their indexes of perception of corruption. The countries’ institutional context, as hypothesized, increases such effect, making it even more significant in the cases of partial adoption.Practical implicationsTo improve accountability and decision-making in public sector entities overall, contributing to reduce corruption, IPSAS adoption requires an institutional environment favorable to take the best of their benefits.Social implicationsThe adoption of IPSAS in an environment with a high institutional quality, allows a greater effect in reducing corruption in the jurisdiction.Originality/valueThis study contributes by providing a comprehensive view of IPSAS and its impact on perceived corruption levels, expanding the existing research to Latin America, where corruption is generally high and IPSAS may contribute to reduce it. It makes an important addition by defining and considering an index of the country’s institutional quality, providing evidence that when this is high, the context enhances the work of institutions, including IPSAS, to fight corruption.

Institutional Anomie Theory and Country-Level Public Corruption

Public-sector corruption siphons trillions of dollars from the global economy and contributes to social instability. Institutional Anomie Theory, with its focus on the links between social institutions, individualistic and achievement-oriented cultural norms, and crime, offers a possible framework for understanding corruption. This possibility is contrasted with research indicating that individualistic values and free markets reduce corruption. Using twenty years of data from 83 countries, this study finds institutional imbalance toward the economy is associated with higher levels of corruption. The lowest levels of corruption are found in highly individualistic countries, though institutional imbalance had a strong positive effect on corruption in such countries. Conversely, corruption is high in collectivistic countries regardless of institutional imbalance. Findings underscore the importance of institutional and cultural configurations, and their interplay, for corruption. We discuss the implications of our study for Institutional Anomie Theory and directions for future research.

Beyond clean data: Exploring the effects of label noise on object detection performance

In recent years, the growth of large-scale datasets has significantly propelled the progress of deep learning applications. Yet, annotating these datasets remains a labor-intensive endeavor, pushing the reliance on cost-effective but less specialized data collection methods and internet data sources. This often results in noisy and inaccurate labels, compromising data quality. Traditional machine learning models assume clean data, but real-world datasets often exhibit significant label noise. This paper examines the impact of such noise on object detection performance, a pivotal aspect of computer vision. We analyze the influence of noisy labels using three renowned object detection frameworks: YOLOv5, Faster R-CNN, and the recent YOLOv8, alongside established datasets: MS COCO, VOC, and ExDARK. Additionally, experiments with the UVM dataset explore domain-specific tasks in dense object scenarios. Two new metrics — Model Health and Detection Capability — were introduced to evaluate the results. Findings indicate that models maintain over 80% of their health (a 20% decline in mAP from the baseline) with up to 40% label corruption. However, Detection Capability deteriorates more sharply under the same conditions. The research also employs the D-RISE method for model explainability, highlighting crucial image regions affecting detection outcomes. Despite the noise, critical detection areas in models remain similar to those in clean data up to the 40% corruption level, as verified by similarity metrics. This study underscores the resilience of object detection models to label noise and provides insights into maintaining performance amidst data quality challenges.

The Impact of Digital Transformation on the Anti-Corruption and Cyber-Fraud System

The article deals with the assessment of the digital transformation impact on the anti-corruption and anti-cyber fraud system. The article explores the interconnection between three key indices: the Corruption Perceptions Index (CPI), the National Cybersecurity Index (NCSI), and the Information and Communication Technology (ICT) Development Index in 138 countries as of 2023. In the first stage, a preliminary analysis of the indices was conducted, which showed significant variation between countries. The average CPI value was 47.5, indicating an average level of corruption globally, but some countries have very low and very high scores. Similarly, the NCSI and ICT indices also vary, indicating uneven development of cybersecurity and information and communication technologies. Correlation analysis revealed a medium to strong positive correlation between the indices. The strongest correlation (0.61) was observed between CPI and ICT, confirming that developing digital technologies can help reduce corruption. A significant correlation was also found between NCSI and ICT (0.61), which emphasizes the importance of information technology development for improving cybersecurity. The clustering method allowed us to divide countries into three groups: countries with low scores on all three indices, countries with moderate scores, and leading countries with high levels of transparency, cybersecurity, and digital development. The study confirmed the importance of investing in digital infrastructure to increase transparency and security and pointed to the need for reforms in countries that score low on all indices.

Risks of “Social Legitimacy” of Corruption under Sanctions: Assessment of the Sentiments of the Regional Business Community

Introduction. In the context of a large-scale sanctions regime, the intensification of anti-corruption work requires special attention among a number of adjustment measures related to structural changes in the economy and changes in supply logistics. Sanctions become a trigger for the emergence of new corrupt practices. The purpose of this article: using sociological analysis methods, to identify the “social legitimacy” (admissibility, acceptability) of corrupt behavior in the business community as a risk factor for the growth of corruption in unfavorable conditions of sanctions pressure. Materials and Methods. The article is based on the results of a sociological study conducted by the authors using a questionnaire survey to assess the level of business corruption in 2021 pre-sanction and in 2022‒2023 sanction years for the Russian economy among the business community of the Sverdlovsk region (n = 500 annually). In order to compare regional trends with all-Russian ones, the results of sociological studies were used: “Business Barometer of Corruption in Russia” and “Consequences of the introduction of sanctions for Russian business.” Results. Risks to the social legitimacy of corruption under sanctions have been identified: against the general background of a negative assessment of corruption by the business community, there has been an increase in the number of supporters of the position that corruption can help solve pressing business problems, as well as those who are neutral towards corrupt business practices; an increase in the desire of the business community to justify the use of corrupt behavior patterns with the usual “that’s the way it is in Russia” has been revealed. Another risk is the dissonance between values and behavior: “In general, corruption is bad, but in a crisis situation, in my daily practice, I can, even must, use corrupt schemes”. Discussion and Conclusion. The life position of the business community, in which corruption is accepted as an inevitable norm of social interaction, turns out to be a barrier to anti-corruption work. The need to intensify sociological research to study the culture of everyday life in the Russian business community has been recorded. The results obtained can be used by government agencies, the chamber of commerce and industry; the union of small and medium-sized businesses, representatives of the business community to intensify anti-corruption work.

Participatory Democracy in Southern Africa: Explaining Botswana’s Exceptionalism

Botswana has had fair and stable elections since its independence in 1966. It has a relatively high standard of living, a relatively well-functioning welfare state, and relatively low levels of government corruption. Voter participation is among the highest in the world, topping 80 percent in the past elections. Access to education and healthcare is free to all citizens. How can we best explain Botswana’s exceptionalism in the political, economic, and social realms, and what policy lessons does the case of Botswana contain? This article shows that it is Botswana’s millennial tradition of direct village democracy, kgotla, that best explains its exceptional performance. I visited Botswana in May of 2023 to evaluate the importance of participatory democracy in Botswana and assess its explanatory power. When comparing local participation to other, potentially relevant causal factors, I find that local political participation provides the most robust explanation for good governance in Botswana. In Botswana, citizens are able to hold their elected officials accountable, learn how politics works by acquiring the necessary technical knowledge (techne) through participating in regular, monthly public assemblies, and, as a result, make better-informed political decisions.

Sorry Not Sorry: Presentational strategies and the electoral punishment of corruption

A growing literature has explored various factors that hamper the electoral punishment of corruption. Most studies have focused on how voters react to a corruption allegation, but this focus leaves out an important, common aspect of corruption allegations that voters also encounter: politicians' blame avoidance strategies. This study examines how politicians' presentational strategies in response to corruption allegations affect voter sanctioning. Employing an online survey experiment on a sample of 3531 U.S. citizens, we find that politicians' action-oriented strategies, such as denying allegations, acknowledging a problem but denying responsibility, or acknowledging a problem and taking responsibility, are more effective than passive non-response. These three active strategies do not differ in their effectiveness. This result is robust to heterogenous levels of state-level corruption, partisan bias, and political knowledge. Our findings suggest that politicians’ presentational strategies may undermine political accountability for corruption, although they do not fully counteract the effect of corruption on voting intentions.

Does governmental corruption aid or hamper early moral development? Insights from the Dominican Republic and United States contexts.

We tested whether children growing up in the Dominican Republic (D.R.), a context with relatively high governmental corruption levels, would support versus distance themselves from widespread unethical practices like bribery. In Experiment 1 (moral judgments; n = 106), D.R. elementary schoolers and adults evaluated judges who accepted gifts from contestants before or after selecting contest winners and predicted whether bribe-taking judges would be secretive. Like adults, older-but not younger-D.R. elementary schoolers differentially condemned judges who accepted gifts before versus after picking contest winners. Unlike adults, children often predicted that judges would disclose receiving gifts. In Experiment 2 (moral behaviors; n = 44), D.R. elementary schoolers could secretly accept or reject a bribe in exchange for 1st place while judging a drawing contest. All but two children rejected the bribe. Together, these findings stand in contrast with U.S. bribery-related developmental trends (Reyes-Jaquez & Koenig, 2021, 2022) and support this contention: When growing up in a more morally heterogeneous context like the D.R., children eventually assume a critical and differentiated stance toward-and will resist or subvert-some of their culture's unethical practices. Greater exposure to a wide range of unethical transactions might hinder aspects of bribery-related moral development early on, depending on how these aspects are measured (moral judgment vs. behavior). Nevertheless, over time, such exposure may strengthen children's capacity to resist unethical cultural practices, indicated by children's overwhelming rejection of bribes. We discuss the importance of including diverse response modalities (verbal, behavioral) when measuring psychological constructs in non-Western societies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring the time variability of the solar wind using LOFAR pulsar data

High-precision pulsar timing is highly dependent on the precise and accurate modelling of any effects that can potentially impact the data. In particular, effects that contain stochastic elements contribute to some level of corruption and complexity in the analysis of pulsar-timing data. It has been shown that commonly used solar wind models do not accurately account for variability in the amplitude of the solar wind on both short and long timescales. In this study, we test and validate a new, cutting-edge solar wind modelling method included in the enterprise software suite (widely used for pulsar noise analysis) through extended simulations. We use it to investigate temporal variability in LOFAR data. Our model testing scheme in itself provides an invaluable asset for pulsar timing array (PTA) experiments. Since, improperly accounting for the solar wind signature in pulsar data can induce false-positive signals, it is of fundamental importance to include in any such investigations. We employed a Bayesian approach utilising a continuously varying Gaussian process to model the solar wind. It uses a spherical approximation that modulates the electron density. This method, which we refer to as a solar wind Gaussian process (SWGP), has been integrated into existing noise analysis software, specifically enterprise . Our Validation of this model was performed through simulations. We then conduct noise analysis on eight pulsars from the LOFAR dataset, with most pulsars having a time span of $ 11$ years encompassing one full solar activity cycle. Furthermore, we derived the electron densities from the dispersion measure values obtained by the SWGP model. Our analysis reveals a strong correlation between the electron density at 1 AU and the ecliptic latitude (ELAT) of the pulsar. Pulsars with $|ELAT|< 3^ circ $ exhibit significantly higher average electron densities. Furthermore, we observed distinct temporal patterns in the electron densities in different pulsars. In particular, pulsars within $|ELAT|< 3^ circ $ exhibit similar temporal variations, while the electron densities of those outside this range correlate with the solar activity cycle. Notably, some pulsars exhibit sensitivity to the solar wind up to $45^ circ $ away from the Sun in LOFAR data. The continuous variability in electron density offered in this model represents a substantial improvement over previous models, that assume a single value for piece-wise bins of time. This advancement holds promise for solar wind modelling in future International Pulsar Timing Array (IPTA) data combinations.

Class grievances before and after the Arab uprisings

To date, analysis of the role of entrepreneurs in the Arab uprisings has been limited. We use micro-level World Bank survey data collected from Arab entrepreneurs in the manufacturing and service sectors across a range of countries to highlight entrepreneur grievances as one proxy for the role that class might have played in the Arab uprisings. We find evidence that dissatisfaction with levels of corruption was particularly high among entrepreneurs in Egypt, Syria and Yemen on the eve of the Arab uprisings, but we also find that Arab entrepreneurs throughout the region share concerns when it comes to macroeconomic and political stability, infrastructural shortcomings and worker training, all of which are key to successful development. More recent data indicate that entrepreneurs in a number of countries (some of which had regime changes, while others did not) remain concerned about the same factors. Although they varied according to size and country, entrepreneur concerns at times went against pre-conceptions concerning Arab capitalist classes and were at odds with the recommendations of international financial institutions.

Measuring corruption: whose perceptions should we rely on? Evidence from Iceland"

The extent of corruption in Iceland is highly contested. International corruption measures indicate a relatively small amount of corruption while domestic public opinion suggest a serious corruption problem. Thus, uncertainty prevails about the actual extent of corruption and whose perceptions to rely on. This problem is relevant for corruption research in general. Perceptions are increasingly used as proxies for the actual levels of corruption in comparative research. But we still do not know enough about the accuracy of these proxies or the criteria they must meet in order to give dependable results. In fact, radical differences exist concerning evaluations of perceptions between those who believe in unbiased learning and those believing perceptual bias to be widespread. The purpose of this article is, therefore, to attempt to gauge which factors may influence how perceptions of corruption are shaped and why differences in corruption perceptions between different groups may be so pronounced. We present findings from original survey data from three parallel surveys – among the "public", experts, and "municipal practitioners" – conducted in Iceland in 2014. Expectations based on the perceptual bias approach are tested, indicating that perceptions may be affected by (1) information factors, (2) direct experience of corruption and (3) emotive factors. The validity of perception measures should be considered with this in mind. Domestic experts are likely to be well informed and avoid perceptual bias to a greater extent than other groups. Our examination of the Icelandic case suggests that the Corruption Perception Index (CPI) tends to underestimate corruption problems in "mature welfare states", such as Iceland, whilst the general public tends to overestimate it.

Corruption’s Crossroads: Exploring Firm Performance and Auditors’ Role in Emerging Markets

This study examines the relationship between country-level corruption (proxied by the Corruption Perception Index, CPI) and firm performance (measured by Return on Assets, ROA) across 18,286 firms in the East Asia, South Asia, and Southeast Asia regions. Additionally, the moderating effects of audit quality (proxied by auditors’ reputation) on the relationship are examined. The findings of the study indicate a positive association between corruption and ROA in high-income nations, thus providing evidence in favor of the “greasing the wheel” theory. On the other hand, a negative association is documented in the upper middle- and low-income nations, which is consistent with the “sanding the wheel” notion. Notably, audit quality has a positive moderating influence on the relationship between corruption and ROA, especially in nations with low corruption levels, reaffirming the pivotal role of reputable auditors in enhancing firm performance within these economic contexts. The results of this study have important ramifications for forming policy suggestions and enhancing governance. The findings highlight the opportunity to improve governance practices and regulations to reduce corruption and increase transparency. Policymakers can develop ways to strengthen institutional frameworks by recognizing the complex link between corruption, corporate profitability, and the function of respected auditors.

Exploring the Potential for Renewable Energy Consumption in Reducing Environmental Degradation in Somalia

Somalia has a relatively small amount of forested land, covering only about 10.5% of the nation’s total land area. The reason for this is that much of the country’s tropical forests, which were originally located along the Shabelle and Jubba rivers reclaimed agricultural land. This study examines the relationship between environmental degradation and various variables, including renewable energy consumption, GDP, FDI inflow, and population. The study employed ARDL model to analyze the econometric relationship between various latent variables. This study found that that in Somalia, renewable energy consumption, GDP and FDI have both short-term and long-term negative and statistically significant effects on environmental degradation. However, FDI exhibits a positive and significant relationship with environmental degradation in both the short and long run. The findings of the study suggest that there is a positive correlation between renewable energy consumption and economic growth, and a negative correlation between renewable energy consumption and environmental degradation. The study also suggests that FDI may play a role in promoting renewable energy consumption and economic growth. The limitation of this study is that the study does not control for all of the potential factors that could influence the relationship between the variables. For example, the study does not control for the level of corruption in Somalia, which could potentially affect both economic growth and environmental degradation. Future research should address the limitations of this study by controlling for all of the potential factors that could influence the relationship between the variables.

Tax Compliance among Managers: Evidence from Randomized Audits1

Abstract Earlier studies of individuals’ law-abiding behavior find significant effects of home country corruption level on compliance. In our study of manager’s tax compliance, we use data from random audits and find associations between tax compliance and the use of an external accountant, age, manager’s place of origin and employees’ conflict exposure, but no effect from a manager’s own conflict exposure, nor Corruption Perception Index scores. The use of an external accountant seems to commit managers to comply with reporting requirements. Our findings suggest that factors such as managers’ age and company characteristics are important in understanding manager compliance. To study whether other mechanisms not previously tested may provide explanatory power, we specify two machinelearning models, which confirm our findings, but also suggest other associations. Nontechnical summary Our study examines tax compliance among managers using data from random audits. We found associations between tax compliance and the use of an external accountant, age, manager’s place of origin and employees’ conflict exposure. However, the manager’s own conflict exposure and corruption levels in their home country did not affect compliance. External accountants seem to encourage managers to comply with tax rules. Machine-learning models confirmed these findings and suggested other relevant factors.

Organized Crime, Poverty, and Drug Trafficking in Nigeria: A Sociological Perspective

The main thrust of this study is to investigate organized crime, poverty, and drug trafficking in Nigeria: A sociological perspective. The study avers that organized crime, poverty and drug trafficking has been identified over the years as not only a threat to national security in Nigeria, but also a serious social problem befalling contemporary society and globally threaten peace and unity. Regrettably, Nigeria was initially tagged as a drug-transit nation, gradually; that conception has changed in recent times, because of frantic and dogged effort by government at all levels to fight drug related activities to a standstill. The study argued that regardless of the counter efforts by NDLEA and other government agencies, sizeable amounts of drugs gain passage through the extensive seaports, airports and land borders in Nigeria on a daily basis. The objective of the study is to investigate the effects of rising organized crime, poverty, and drug trafficking on national security in Nigeria with focus on social problems and increasing damage of our national image globally. However, the study relied heavily on relevant theoretical and empirical literature from internet search engines, such as Google, journals, and text books, etc. The study adopted a quantitative research method. Functionalism Theory were explained and adopted as theoretical framework. The study reveals that the preponderance increases of organized crime, poverty, and drug trafficking in Nigeria is a veritable strong weapon for terrorism financing, social problems, corruption inducement, political instability and neglect to economic development. This has affected Nigeria international image and the negative effects are highly felt in the rising level of insecurity and drug related crimes in the country. Consequently, data for the study were generated using the secondary sources interpretative documents related to the organized crime, poverty, and drug trafficking in Nigeria. The study also identified a high level of institutional cum political corruption, poverty (unemployment) as among major contributing factors to the rising trends of organized crime, drug trafficking in Nigeria. Based on the discussion the study recommended among others: Urgent steps should be taken to increase capacity building and strengthening of Nigerian security agencies as well as good governance.