International journal of economic perspectives

The effect of labor absorption, government expenditure, and life expectancy on poverty with economic growth as a mediation variable in Aceh Province

2026-03-24T01:54:11+00:00

This study aims to analyze the influence of labor absorption, government expenditure, and life expectancy on poverty with economic growth as a mediating variable in Aceh Province. Panel data regression method is used. The findings in model I show that labor absorption has no effect on poverty, while government expenditure has a positive effect on poverty and life expectancy has a negative effect on poverty. Model II shows that labor absorption has a negative effect on economic growth, and government expenditure has a positive effect on economic growth while life expectancy has a positive effect on economic growth. Model III explains that economic growth has a negative effect on poverty. Model IV results in labor absorption and government expenditure have no effect on poverty, while life expectancy has a negative effect on poverty and economic growth has a positive effect on poverty. The results of the mediation effect explain that economic growth mediation has no effect on labor absorption on poverty, and government expenditure on poverty through economic growth as a mediator has a negative result, and life expectancy on poverty through economic growth as a mediator has a negative effect. Through the results of this study, it is hoped that the Aceh Government in providing poverty alleviation policies needs to be directed at synergy between increasing economic growth and improving socio-economic indicators in order to achieve community welfare.

Does Islamic Finance fulfill the objectives of Maqasid Al-Shari’ah?

2026-04-01T07:01:05+00:00

This study examines whether Islamic finance is fulfilling the objectives of Maqasid al-Shari’ah. It adopts qualitative analysis, where an in-depth interview session with 7 experts in the industry is undertaken. The findings are classified into 3 themes; 1) Information on the Islamic banking-growth nexus, 2) Information on the Islamic capital market-growth nexus, and 3) Information on the Takaful-growth nexus. The first theme shows that although Islamic Banking (IB) sector is gradually moving towards equity financing, it is still highly-dependent on debt-financing. The second theme shows that Islamic Capital Market (ICM) is significantly contributing to the ESG via the implementation of SRI Sukuk, Bond Grant Scheme, ESG Financing/Sukuk, and value-based judgement projects. The final theme shows that Takaful industry has contributed its own humble quota to economic growth by creating jobs to the society and adding values to both participants and businesses. The work gives some insights into the field of Islamic finance in the light of Maqasid al-Shari’ah from the perspective of a developing country, which is Malaysia.

Data-driven recruitment and HR analytics: A Review of strategic applications in talent acquisition

2026-02-10T08:16:43+00:00

This study presents a systematic review of data-driven recruitment (DDR) literature published between 2015 and 2025. Based on 26 peer-reviewed studies, the review uses the PRISMA framework to analyze methodological patterns, thematic trends, and theoretical contributions. The results show a shift from early efficiency-focused research to more recent concerns about algorithmic fairness, diversity, and governance. By situating DDR within the Resource-Based View, Human Capital Theory, organizational justice perspectives, and socio-technical systems theory, the review highlights how recruitment analytics influence both organizational performance and ethical considerations. Key research gaps include the limited number of studies in emerging economies, methodological diversity, and inadequate accountability mechanisms. The paper provides theoretical, managerial, and policy implications, proposing a more integrated framework for balancing efficiency with fairness in recruitment analytics and advancing the HRM literature.

THE IMPACT OF ARTIFICIAL INTELLIGENCE AND MACHINE ALGORITHMS ON COMPETITION LAW FRAMEWORK IN INDIA

2026-01-28T07:39:47+00:00

The rapid integration of Artificial Intelligence (AI) and machine learning algorithms into digital markets has significantly transformed business practices and competitive dynamics across jurisdictions, including India. While algorithm-driven technologies have enhanced efficiency, transparency, and consumer choice, they have simultaneously introduced complex challenges for competition law enforcement. This paper critically examines the impact of artificial intelligence and machine learning algorithms on the Indian competition law framework, with a particular focus on algorithmic price-fixing, data-driven collusion, discriminatory pricing, and personalised advertising. It explores how self-learning algorithms can facilitate tacit coordination among firms without explicit human intervention, thereby undermining traditional notions of agreement, intent, and liability under the Competition Act, 2002. The study highlights the growing difficulty faced by competition authorities in detecting and regulating anti-competitive conduct in digital markets where pricing and strategic decisions are increasingly automated. Through doctrinal and analytical research, the paper evaluates whether the existing legal provisions—especially those relating to anti-competitive agreements—are sufficiently equipped to address AI-driven collusion and market distortions. It argues that while AI and algorithms offer undeniable economic benefits, their unchecked deployment poses serious risks to market fairness and consumer welfare. The paper concludes by emphasising the need for a nuanced and adaptive competition law framework in India, capable of balancing innovation with effective regulation, and calls for regulatory clarity to address emerging challenges posed by intelligent, autonomous systems.