Smuggling harms the economy and development of a country. Various statistical methods can be used to determine the geographical distribution of smuggling within a country. In this regard, clustering techniques (both classical and spatial analysis) have been used to present an overview of...

We examine the factors behind Afghanistan's persistent underdevelopment. Drawing on various theories of development traps operating at the demographic, economic and institutional levels, we seek to assess whether and to what extent their functioning affects Afghanistan's development. To capture...

We study how spillovers from water pollution cleanup in the Ganges affect social welfare in an aggregate economy consisting of Kanpur and Varanasi, two cities through which this river flows. We view pollution cleanup in both cities as a local public good and point out that, if Kanpur cleans up...

Deceptive communication, as involved in impersonation fraud and other forms of economic crime, can inflict loss, making it important to be able to distinguish these from trustworthy ones. This article pursues the hypothesis that repeated exposure or experience can cause learning and hence better...

We investigate if directors of Australian companies can generate abnormal returns on their reported trades, if these abnormal returns are significant enough to be mimicked by outsiders, and if insider trades have an effect on returns of other investors. We find that insiders take advantage of...

In this study, we propose a mathematical model of a 4D clustered traveling salesman problem (CTSP) to address the cost-effective security and risk-related difficulties associated with the TSP. We used a multiparent-based memetic genetic algorithm to optimize paths between all clusters and...

This study was conducted by examining the interrelationships between Corruption, Human Resources, and Unemployment in Indonesia. We use data sourced from the World Bank and Transparency International with the period used from 1996 to 2021. This study aims to examine the relationship that exists...

Sentiment analysis is crucial in understanding and analyzing public opinions, feedback, and social media data. In this study, we propose a modified Bayesian Boosting algorithm with weight-guided optimal feature selection for sentiment analysis. The goal is to improve the accuracy and efficiency...