Current Issue
Volume 1, Issue 2
The newest papers published in the Student Journal of Business and Economics. Each has its own permanent, original SJBE DOI and is freely citable, anywhere.
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This study investigates how artificial intelligence and digital transformation have shaped economic growth in Azerbaijan, drawing on time series data spanning 1996 to 2025. Using correlation analysis, Augmented Dickey-Fuller unit root testing, Granger causality testing, and ordinary least squares regression, the analysis traces the relationship between a composite Digital Economy Index and both real and non-oil GDP growth. The Digital Economy Index is constructed as a weighted composite measure incorporating five standardized indicators: internet penetration (sourced from the International Telecommunication Union), mobile subscriptions per 100 inhabitants (ITU and State Statistical Committee of Azerbaijan), ICT sector value added as a percentage of GDP (State Statistical Committee of Azerbaijan and Ibadoghlu, 2025), the United Nations E-Government Development Index (UN DESA, 2024), and the ratio of cashless payments to total transactions (Central Bank of Azerbaijan, 2024). Each component was min-max normalized to a 0–100 scale and aggregated using equal weights to ensure transparency and replicability. The results reveal a marked structural shift after 2016: while overall GDP growth slowed as oil production declined, the Digital Economy Index rose sharply and became closely linked to non-oil growth. In the post-oil period (2016–2025), this relationship is strong and statistically robust (R2 = 0.823, p < 0.001), with a one-unit rise in the index associated with a 0.208 percentage-point increase in non-oil GDP growth. These findings are interpreted alongside the objectives of the Azerbaijan Artificial Intelligence Strategy (2025–2028), and the study closes with policy recommendations aimed at translating digital gains into lasting, broad-based economic diversification beyond the hydrocarbon sector.
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25 Sep 2026
This independent research paper examines the contemporary economic and operational dynamics of the Middle Corridor (Trans-Caspian International Transport Route) connecting China and European markets via Kazakhstan, the Caspian Sea, Azerbaijan, and Georgia (Middle Corridor 2026). The central research problem addresses hidden logistical friction, demonstrating that total supply chain costs depend heavily on terminal storage and delays rather than basic transport tariffs. Utilizing empirical commercial tariff sheets from DB Cargo Eurasia GmbH (2023), this study models the exact financial impact of border idling and progressive demurrage rates at critical European cargo hubs. Furthermore, it evaluates the deployment of blockchain-backed “Smart Customs” solutions managed by the State Revenue Committee of Kazakhstan, specifically focusing on how decentralized ledger architectures secure electronic consignment notes (e-CMR) to establish multi-national data trust. The empirical findings show that automated transit workflows compress block train declaration intervals from 3 hours to just 30 minutes, yielding a distinct 83.3% time optimization (State Revenue Committee 2026). The study concludes that digital ledger trust and physical infrastructures must develop in tandem, creating a major potential for systemic cost reduction along global trade routes.
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This study examines whether uncertainty in the wording of annual reports (10-K) affects Environmental, Social, and Governance (ESG) performance for 72 US public firms. Findings show a negative relation between uncertain words and ESG performance, indicating that greater use of ambiguous words in firms' financial statements negatively affects firms' ESG scores. This finding shows that market participants may notice that firms may deploy vagueness or ambiguity to disguise their poor performance or negative impact on the environment (i.e., Greenwashing). Findings from this study could provide some insights to investors, managers, and regulators in the capital market by recommending that public firms use more transparent and clear language in their 10-K reports.
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13 Sep 2026
This paper analyses the differing labour market effects created by industrial robotics and generative Artificial Intelligence (AI) within the Australian economy. While industrial robotics and generative AI are often aggregated under the singular banner term of “automation”, treating them as a homogenous phenomenon downplays their radically divergent transmission mechanisms. By utilising a task-based framework, this paper argues that these two technologies propagate via entirely distinct tracks within the Australian economy; automation is not one overall phenomenon, but rather has a multifaceted dual-track impact, stemming from the automation of individual tasks as opposed to whole jobs. Track 1 investigates the substitution forces of robotics within sectors like mining and manufacturing. The capital intensive and highly structured nature of robotics implementation creates concentrated labour market displacement shocks that are felt within local communities. Track 2 examines the geographically diffused augmentation effects of generative AI across the services sector, specifically finance and retail. Driven by low-friction, decentralised implementation, generative AI has introduced an uneven wave of task transformation and restructuring as opposed to systemic job elimination. Via a qualitative review of domestic sectoral data, this study demonstrates that productivity gains realised at a national macro-level fail to capture the localised socioeconomic disruptions and adjustments observed at the community and firm level. By disaggregating these technological mechanisms, this paper leverages Australia’s distinct sectoral landscape to clarify the globally evolving friction between technological replacement and human reinstatement. In relation to controlling externalities, this paper uses the same disaggregation to conclude that because automation is not a singular process, labour market adaptation cannot be a singular response either.
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13 Sep 2026
Cryptocurrency is often described as a decentralized and accessible financial system, but the concentration of wealth among large holders raises questions about how decentralized cryptocurrency markets actually are. This study examines how high-net-worth individuals (HNWIs), particularly cryptocurrency “whales,” influence cryptocurrency markets and how their influence extends beyond their direct transactions. Using a literature review and secondary data analysis, this research examines ownership concentration, market spillover effects, and behavioral responses to whale activity using academic research, blockchain analytics, institutional reports, and case-based evidence. The findings show that a small number of large holders control a disproportionate share of cryptocurrency assets, allowing their transactions to affect market volatility and generate spillover effects across other assets. However, the findings also suggest that whale influence is amplified by the behavior of smaller investors. Investors may interpret whale transactions and announcements as signals of future market movements, leading them to imitate these actions and further amplify price changes. The Tesla Bitcoin case provides an example of how a major institutional announcement can influence market behavior beyond the direct financial transaction. Overall, the findings support the hypothesis that whale influence comes not only from concentrated ownership and trading power, but also from the behavioral responses of other market participants. This suggests that cryptocurrency may be decentralized technologically while remaining concentrated in terms of wealth, influence, and market power.
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10 Sep 2026
Profit-driven behavior has caused long-lasting debates. Does it serve as an impetus to unlock human potential and foster achievement, or does it treat financial gain as the sole objective, thus leading to unethical harm to society? Gaining profit is vital for enterprises to seek survival and expansion, it is undoubtedly an incentive for businesses to find ways to improve. Generating creativity, evaluating multiple alternatives, optimizing process flow, and meeting diverse customer needs, are all driven by this incentive. As a result, innovations and even revolutions occur, which raise the overall economic and technological level, enhancing human capabilities. On the other hand, the temptation for money gain compels some people to lose sight of ethical business practices. In this case, regulations are ignored, public health is put aside, and environmental sustainability is sacrificed in exchange for short-term financial rewards. However, the intention for pursuing profit is not wrong, what needs to be rectified is the path some people take to reach the goal without integrity. Cultivating ethical values and civic responsibility, selecting ethical business leaders, enforcing strong regulations, and establishing a healthy competitive environment can help shape responsible business conduct and ensure the journey of profit acquirement promotes human progress rather than causing trouble for humanity.