Niigata Institute of Technology Repository
Not a member yet
5446 research outputs found
Sort by
The Role of Technology in the Impact of Non-Renewable Energy Consumption on Ecological Resilience: Application of Threshold Structural Vector Autoregression (TSVAR) Model
No full textNew technologies play an increasingly vital role in managing energy resources and enhancing environmental sustainability. Given the significant challenges posed by the use of non-renewable energy sources, it is essential to examine how technology can mitigate their consumption and promote ecological resilience. This study investigates the asymmetric effects of non-renewable energy consumption on ecological resilience through technological influence in Iran over the period 1990–2022, using the Threshold Structural Vector Autoregression (TSVAR) model. The results reveal a threshold of 0.171% for the growth rate of non-renewable energy consumption, beyond which the impact on ecological resilience differs substantially. The study finds that the ecological response varies depending on whether energy consumption is above or below this threshold. These findings underscore the importance of integrating advanced technologies and digital solutions into the energy sector. Policy implications include prioritizing technological innovation and smart energy systems to improve efficiency, reduce reliance on fossil fuels, and ultimately strengthen ecological resilience across multiple dimensions
Mining Exploration Business Strategy around Logging Roads
No full textA mining exploration company, Kermode Resources Ltd, provides an example of surface sampling results from the logging road, and this article describes methods for data visualization of exploration results. The paper uses a bottom-cut as an example of a descriptive statistical method to determine whether the best results cluster in one particular spatial area, using public results from Kermode. The paper introduces a toy model of the area around these sampling results and uses it to discuss potential acid rock drainage. Further, the paper describes a possible synergy between the mining exploration and forestry: when a logging road uses sulphide-rich rocks, it creates a potential pain point for the forestry industry because of increased pollution from heavy metals; however, these same sulphide-rich outcrops are a potential pleasure point for a mining exploration company seeking to find a minerals deposit
Detecting Stablecoin Failure with Simple Thresholds and Panel Binary Models: The Pivotal Role of Lagged Market Capitalization and Volatility
No full textIn this study, we extend research on stablecoin credit risk by introducing a novel rule-of-thumb approach to determine whether a stablecoin is ``dead" or ``alive" based on a simple price threshold. Using a comprehensive dataset of 98 stablecoins, we classify a coin as failed if its price falls below a predefined threshold (e.g., \$0.80), validated through sensitivity analysis against established benchmarks such as CoinMarketCap delistings and \cite{feder2018rise} methodology. We employ a wide range of panel binary models to forecast stablecoins' probabilities of default (PDs), incorporating stablecoin-specific regressors. Our findings indicate that panel Cauchit models with fixed effects outperform other models across different definitions of stablecoin failure, while lagged average monthly market capitalization and lagged stablecoin volatility emerge as the most significant predictors—outweighing macroeconomic and policy-related variables. Random forest models complement our analysis, confirming the robustness of these key drivers. This approach not only enhances the predictive accuracy of stablecoin PDs but also provides a practical, interpretable framework for regulators and investors to assess stablecoin stability based on credit risk dynamics
Fertility responses to tropical cyclones: Causal evidence and mechanisms
No full textIn light of growing concerns over escalating natural disaster risks and persistently low fertility rates, this paper quantifies the causal impacts of tropical cyclones and identifies the pathways through which they influence childbearing decisions among Australians of reproductive age. Using an individual fixed effects model and exogenous variation in cyclone exposure, we find a robust and substantial decline in fertility, occurring only after the most severe category 5 cyclones, with the effect weakening as distance from the cyclone’s eye increases. We find no evidence of delayed cyclone effects, indicating that the fertility loss attributable to these most severe cyclones is permanent. Our findings are robust to extensive validity checks, including a falsification test and various randomization tests. The fertility decline is most pronounced among younger adults, individuals with lower educational attainment, those childless at baseline, and those lacking prior private health or residential insurance. While physical health, financial constraints, and migration appear unlikely to drive the effect, the evidence points to reduced family formation, increased marital breakdown, child mortality, cyclone-induced home damage, elevated psychological stress, and heightened risk perceptions as plausible mechanisms
Artificial Intelligence and Economic Growth: Opportunities, Challenges, and Future Directions
No full textArtificial Intelligence (AI) has become one of the most influential drivers of economic transformation in the 21st century. By boosting productivity, optimizing business processes, supporting innovation, and enabling the emergence of new industries, AI contributes significantly to long-term economic growth. However, this technological shift also brings risks such as labor market disruption, inequality, skill mismatches, and regulatory gaps. This article examines the relationship between AI adoption and economic growth, highlighting the mechanisms through which AI stimulates economic performance, the structural challenges it generates, and strategies needed to ensure inclusive and sustainable growth. The paper draws on recent literature, economic reports, and empirical studies to offer a comprehensive perspective on the future of AI-driven economic expansion.
Keywords: Artificial Intelligence, Economic Growth, Productivity, Innovation, Labor Market, Digital Transformation
A Novel Hybrid Lexicon and Economic Optimized kNN Framework for Sentiment Analysis in Tourism Platforms
No full textSentiment analysis in tourism platforms plays a vital role in understanding customer feedback, enhancing service quality, and supporting strategic economic decision-making across tourism markets. Challenges such as imbalanced sentiment classes, domain-specific language, and noisy data reduce the economic efficiency and analytical value of conventional approaches. This paper introduces a novel hybrid framework that combines lexicon-based sentiment and emotion analysis with an economically optimized weighted kNearest Neighbors (kNN) classifier. The framework incorporates advanced data augmentation techniques and comprehensive feature engineering, including n-gram TF-IDF extraction and metric learning—to improve minority sentiment class recognition and increase the economic robustness of predictive analytics. A modified co-optimization layer jointly tunes augmentation
parameters, feature extraction methods, and classifier hyperparameters to maximize minority-class F1-scores while minimizing computational and economic costs. Experimental evaluations on real-world tourism review datasets demonstrate significant improvements in classification performance compared
to baseline models such as SVM, Random Forest, and CNN, highlighting the framework’s economic value in large-scale tourism data processing. Additionally, a real-time business intelligence dashboard is developed for economic monitoring and dynamic visualization of sentiment trends and minorityclass heatmaps, enabling tourism stakeholders to make informed economic
and managerial decisions and strategically respond to customer sentiments. The findings confirm a predominance of positive sentiments across tourism services while identifying economically critical areas requiring improvement. Future work will explore multilingual sentiment analysis and aspect-based models to enhance granularity, scalability, and economic impact. This research contributes an effective, interpretable, and economically oriented solution for advanced sentiment analysis in tourism platforms
Economic Resilience and Vulnerability: Concepts and Indices
No full textThis paper examines the concepts and indices of economic resilience and vulnerability. The central notion in clarifying both resilience and vulnerability is that of an adverse shock. If a shock does not alter the growth path of an economy or cause a recession, the economy is considered “resilient.” Resilience refers to an economy’s ability to return to its pre-shock growth trajectory. A resilient economy, after experiencing a shock, resumes its long-term growth path. Endogenous growth can strengthen economic resilience, and resilient economies tend to experience sustainable growth. Macroeconomic stability and effective institutions are two principal indicators of economic resilience. Resilience stems largely from economic policymaking, while vulnerability is related to the inherent structural characteristics of an economy that expose it to adverse shocks. Export concentration, dependence on strategic imports and external financing, as well as geographical vulnerability, constitute the main indicators of economic vulnerability. The greater the capacity to respond to shocks, the lower the vulnerability. The paper explores the indices of economic resilience, including Briguglio, Centennial group and Oxford FM Global. In vulnerability indices, the paper discusses the Briguglio vulnerability index, Guillamount and OECD indices
Review of Understanding Technology in the Context of National Development: Critical Reflections (2025)
No full textUnderstanding Technology in the Context of National Development: Critical Reflections by Tiwari, Kostenko, and Yekhanurov (2025) has quickly gained academic and pedagogical significance. The work offers a comprehensive examination of how digital transformation and technological innovation intersect with national development strategies, governance models, and economic growth. It situates technology as both a driver of progress and a subject of critical reflection within development economics and ICT4D (Information and Communication Technologies for Development). Drawing on key policy frameworks including OECD’s digital transformation guidelines, United Nations (UN) development agendas, and the Network Readiness Index the authors analyze themes such as technological advancements, human capital, governance, and innovation ecosystems. The review finds that the book makes a valuable contribution to debates on digital transformation and development by identifying thematic pillars, capturing stakeholder insights, elaborating on twin foundations of tech enabled growth, and proposing concrete solutions to governance and inclusion challenges. This is shown by its adoption as post graduate course material for Industrial & Organizational programs at University Malaysia Sabah (UMS), Malaysia and Esa Unggul University, Indonesia, where the author is associated with and currently using the book for post graduate studies courses listed in the curriculum. The curricular integration underscores the book’s broader pedagogical relevance in Southeast Asia. In doing so, it bridges theoretical discourse with practical policy considerations, providing scholars, policymakers, and practitioners a timely resource aligned with global development frameworks
Cryptocurrency Technology and The International Monetary System
No full textThroughout the millennial history of money, various payment instruments have been developed: some designed to facilitate economic transactions and others to preserve accumulated wealth, adapting in each historical period to the conditions and capabilities of the society of their time. In this context, the maturity achieved by the cryptocurrency industry over the last five years, especially in areas such as
blockchain, oracle networks, self-custody, multi-chain environments, and decentralized applications —DApps—combined with today's colossal data processing capacity, opens up the possibility of applying these 21st-century
technologies to the construction of a new international monetary system. This article explains how to use these telematic tools to achieve this, as well as their implications in the financial and economic arena, including enhanced financial stability and the recognition of the Fundamental Right of People to Safeguard the Wealth
When Ranks Fail: New Evidence on Intergenerational Educational Mobility
No full textMany recent studies on intergenerational educational mobility adopted the rank-rank model popularized by the work of Chetty et al. (2014, QJE) on income mobility, under the assumption that the approach remains valid for discrete variables. However, conversion of discrete data such as years of schooling into percentile ranks fails to make the empirical rank distribution uniform, unlike continuous variables such as income. Thus, the estimates of relative educational mobility from rank-rank regressions are not margin-free, and capture a fundamentally different concept of mobility compared to the rank-rank slope in income mobility analysis. Taking advantage of recent advances on discrete copulas, we introduce a margin-free measure of relative educational mobility, Yule’s coefficient, which is the analogue of the rank-rank slope in income mobility. Yule’s coefficient was proposed by Geenens (2020) as a summary measure of the margin-free dependence structure between two discrete variables such as children’s and parents’ schooling. The margin-free dependence structure is estimated by an iterative matrix re-scaling procedure applied to the joint probability mass function of the bivariate discrete distribution. We report estimates of Yule’s coefficient for 6 countries: the USA, Bangladesh, India, Indonesia, Chile, and Mexico. The evidence suggests that, in many cases, the rank-rank slope estimates for schooling overestimate the margin-free relative educational mobility (positional mobility). For example, the estimates for the USA (PSID data) are: rank-rank slope=0.441 and Yule’s coefficient=0.534. The extent of overestimation in the national estimates varies considerably across countries: 3.09%−48.31%. The cross-country rankings and evolution of educational mobility across cohorts are substantially different when we use the margin-free Yule’s coefficient instead of the rank-based measures