Data gaps in Economics

Representative open questions

Showing 30 of 114 — one per source paper, highest-quality first.

• Artificial intelligence, capability transformation, and marine green development: empirical evidence from Coastal China (2026) · doi

  The mediation mechanisms (Marine Resource Index and Digital Governance Capacity) are tested only for coastal Chinese provinces from 2011-2023. The generalizability of these capability transformation pathways to non-coastal regions, other national contexts with different industrial structures, or different time periods remains unvalidated.

• Black and green: How electoral outcomes influence provincial circular economy performance in Italy (2026) · doi

  The paper calls for communication strategies that frame circular economy adoption as generating job creation and industrial competitiveness benefits for economic-security-focused constituencies, but lacks empirical data on how different political messaging frames (environmental protection vs. economic benefit emphasis) influence circular economy policy support across provinces with varying ideological compositions.

• What Determines the Demand for Online High-Cost Credit? Evidence from Loan Applications from Digital Credit Intermediaries (2026) · doi

  The dataset does not include welfare benefit receipt or disability status, which prior research (Rasanga et al., 2024) identifies as determinants of AFS use. Understanding how these social support and disability characteristics interact with the observed repeat application patterns in digital credit intermediaries requires additional investigation.

• Multi-asset optimal trade execution with stochastic cross-effects: An Obizhaeva–Wang-type framework (2026) · doi

  The framework incorporates stochastic cross-effects through the operator O and matrix Q, but empirical validation against real market data demonstrating the relevance of these cross-effect terms versus simpler single-asset or independent multi-asset models has not been provided. Calibration of the cross-effect parameters to actual equity, FX, or commodity market microstructure is absent.

• Ethics of AI-based supply chain optimization: a better balance between efficiency and fairness (2026) · doi

  While the paper notes that half of logistics employees will require job reskilling due to automation, it does not identify which specific supply chain roles (warehouse management, procurement, last-mile delivery) require targeted reskilling programs or benchmark the effectiveness of different reskilling approaches in supply chain contexts.

• From Hype to Hesitation: A Longitudinal Analysis of User Sentiments towards AI‑Enabled Fintech Lending Platforms (2026) · doi

  The analysis references secondary data from P2P lending platforms but does not specify whether alternative data sources (app store reviews, social media mentions, regulatory complaint databases) were integrated to triangulate user sentiment. Incorporating multi-source sentiment data would provide more comprehensive coverage of user perception heterogeneity across different platforms and user types.

• Evaluating Innovation Levels based on Standard Deviation of Parameters and MCDM Methods (2026) · doi

  The study identifies Institutions (C1) as the most critical innovation parameter with highest standard deviation (13.4972 in S3), but does not specify which institutional sub-components (governance structures, research institutions, technology policies) drive this variance or how weighting should adjust when institutional data quality differs across provinces.

• Using artificial intelligence in marketing (2026) · doi

  Organizations increasingly must hire specialized workers to correct AI-generated marketing content (graphics, texts, code), contradicting cost-reduction assumptions; studies should quantify the actual labor cost offset when including correction and quality assurance requirements for AI-assisted marketing content creation workflows.

• SSABE-TSCM: drift-aware and interpretable financial sentiment analysis for low-resource Bangla via adaptive semi-supervised and temporal contrastive modeling (2026) · doi

  Crisis-era terminology (e.g., 'digital taka' in early 2023) occurs too seldom in the training set to be learned effectively. Expanding vocabulary coverage via targeted back-translation or synthetic data generation specifically for rare Bangla financial crisis terms is required to maintain macro-F1 above 0.74 during rapidly evolving economic events.

• Mathematical Modelling of the Ukrainian IT Industry Potential Assessment in the Context of Global Challenges (2026) · doi

  The qualitative potential assessment in Table 12 is based on data from only six regions (Kyiv, Lviv, Kharkiv, Dnipro, Odesa, Zakarpattia) and a single reference year (2024); the paper does not specify the longitudinal validation needed to test whether the qualitative sociocultural model maintains predictive accuracy across temporal changes in regional IT industry development or can be extended to Ukraine's remaining regions.

• A Study on the Impact of UPI and Digital Payment system on the Spending Behaviour of college students (2026) · doi

  The research demonstrates that digital payments have transformed student spending behavior, but lacks longitudinal tracking data comparing the same cohort's spending patterns pre- and post-UPI adoption over extended periods (6+ months) to establish behavioral trajectory changes.

• Impact on Adoption of Artificial Intelligence(AI) in the Banking Industry. (2026) · doi

  The paper lists data privacy, security concerns, and regulatory limitations as major obstacles to AI adoption in banking, but lacks empirical data on how different regulatory frameworks (GDPR, banking compliance standards, data localization requirements) differentially impact AI adoption rates across banking institutions or geographies.

• DÖVLƏT BORCU, ONUN İQTİSADİ MAHİYYƏTİ VƏ NÖVLƏRİ (2026) · doi

  The article asserts that internal borrowing constrains inflationary pressure better than external borrowing due to money supply effects, but provides no quantitative analysis of the specific monetary transmission mechanisms or empirical elasticity estimates for this relationship under varying inflation regimes.

• TEXNOLOGİYALARIN İQTİSADİ VƏ SOSİAL TƏSİRLƏRİNİN GÖSTƏRİCİLƏR ƏSASINDA QİYMƏTLƏNDİRİLMƏSİ (2026) · doi

  The paper identifies that small and medium enterprises gain global market access through digital technologies but does not provide empirical data on the specific market integration patterns, competitive outcomes, or sectoral variations in SME digital adoption across different economic contexts.

• Women and medicine (2010) · doi

  The paper identifies an 'urgent need' for the Department of Health to collate 'an accurate longitudinal data set' for workforce planning but does not specify the required temporal scope, variables to be tracked, sampling methodology, or comparison populations needed to support evidence-based reconfiguration of trainee workforces in medical specialties.

• VERGİ RİSKLƏRİ VƏ VERGİLƏRİN OPTİMALLAŞDIRILMASININ MÜASİR İQTİSADİ ŞƏRAİTDƏ ROLU (2026) · doi

  The conclusion acknowledges that digitalization of tax administration and artificial intelligence systems reduce compliance errors and increase voluntary tax payments, but does not provide empirical data comparing tax compliance rates before and after digital transformation, nor specify which AI methods (machine learning algorithms, natural language processing) are most effective for tax compliance improvement.

• A Study on Integrating Production and Service Management Strategies for Achieving Competitive Advantage in Modern Organizations (2026) · doi

  The paper asserts that integrated performance management systems should focus on collective goals like customer satisfaction and efficiency, but does not provide empirical data comparing organizational outcomes between department-specific versus integrated performance appraisal criteria in production-service environments.

• An Empirical Study of Price Action, Return, Volatility and Risk in MCX vs International Exchange: A Comparative Analysis of Gold, Silver, Oil, Gas and Copper (2026) · doi

  Gold and copper are identified as stable commodities with low volatility on COMEX, while MCX commodities show slightly higher volatility; however, the paper does not control for microstructure factors (bid-ask spreads, trading volume, order flow) or exchange-specific institutional differences that might explain why MCX exhibits higher volatility than international counterparts.

• Recruiter's Perception of Artificial Intelligence Based Tools in Recruitment at Virtusa, Chennai (2026) · doi

  The study identifies faster candidate screening (39%) and better candidate quality (27%) as perceived benefits of AI-based recruitment tools but provides no objective metrics validating these claims. Comparative analysis between screening speed and quality outcomes of AI-assisted versus human-only recruitment processes requires implementation.

• How artificial intelligence improves the resilience of marine firms: insights from China’s A-share market (2026) · doi

  The heterogeneity analysis reveals divergent AI empowerment patterns between emerging and traditional marine industries (emerging: insignificant coefficient; traditional: significant positive coefficient at p=0.007), but the paper does not quantify the specific digitalization threshold at which AI marginal utility transitions from high to constrained. Research should establish the precise initial digitalization level breakpoint for emerging marine sectors (biomedicine, high-end equipment, new energy, electronics) where AI adoption ceases to enhance resilience.

• FINANCIAL LITERACY AMONG WOMEN EDUCATORS IN HIGHER EDUCATION: AN EMPIRICAL INVESTIGATION OF KNOWLEDGE, ATTITUDE, AND BEHAVIOUR (2026) · doi

  Arts stream educators show significantly higher moderate (rather than high) literacy (OR=4.838, p<0.001), indicating a need for targeted intervention, yet the paper does not characterize whether this group lacks foundational knowledge, has different risk attitudes, or exhibits behavioral barriers to financial engagement compared to Commerce educators.

• ARTIFICIAL INTELLIGENCE IN THE OPERATIONAL ACTIVITIES OF ENTERPRISES AS A FACTOR FOR INCREASING THEIR COMPETITIVENESS IN REGIONAL AND INTERNATIONAL MARKETS (2026) · doi

  The paper argues that AI reduces man-hour costs for processing large datasets and logistics costs in international enterprises, but provides no empirical measurement methodology or benchmark data comparing actual cost reduction percentages across different types of operational activities (production processes, transport chains, communication) before and after AI implementation.

• The Influence of Gen Z Characteristics and Company Strategy on Turnover Intention (2026) · doi

  The research sample size (N=24 based on df2 in F-test) is substantially underpowered for reliable regression estimation and generalization. A larger, stratified sample across multiple startup industries and geographic regions is needed to validate whether Gen Z characteristics and company strategy effects on turnover intention remain consistent across different startup sectors and organizational maturity levels.

• Organizational Justice, Cultural Intelligence and Workforce Inclusion in Digitally Transformed Multinationals: A Systematic Integrated Review of Expatriate and Hybrid Workers in Emerging Economies (2026) · doi

  Digital inclusion research has concentrated on knowledge-intensive professions with high digital literacy; systematic investigation is needed into digital inclusion outcomes specifically within manufacturing, service, and other sectors with lower baseline digital technology adoption to assess whether organizational justice and cultural intelligence mechanisms operate similarly across these industry contexts.

• WHAT ARTIFICIAL INTELLIGENCE CAN DO TO MITIGATE ASYMMETRIC INFORMATION IN ISLAMIC BANK: A CONCEPTUAL FRAMEWORK REVEALED (2026) · doi

  The paper does not specify how the proposed AI framework would integrate with existing Islamic bank credit scoring models or whether it requires retraining on historical PLS financing default data. The dataset requirements, sample sizes, and class imbalance handling for training machine learning models on asymmetric information detection remain unspecified.

• Interpreting Primary Energy Consumption in Europe and Türkiye Using Explainable Artificial Intelligence (2026) · doi

  The population variable shows a weak and scattered relationship with primary energy consumption in the explainable AI model, but the paper does not decompose this relationship by economic sectors (transportation, industry, residential) where population effects might be mediated differently through energy intensity metrics.

• Entrepreneurial Skills and Quantitative Decision - Making: The Role of Business Mathematics in Emerging Enterprises of Assam (2026) · doi

  The study identifies a noticeable gap in entrepreneurs' quantitative and analytical capabilities despite high levels of entrepreneurial skills, but does not investigate the specific business mathematics competencies (e.g., financial forecasting, statistical analysis, cost-benefit analysis) that are most deficient in emerging enterprises of Assam or which mathematical skill deficits most impair quantitative decision-making.

• TOURISM DEVELOPMENT AND SUSTAINABILITY: SOCIO-ECONOMIC AND ENVIRONMENTAL IMPACTS IN COX'S BAZAR, BANGLADESH (2026) · doi

  The research gathered perspectives primarily from local communities, government officials, and tourism stakeholders, explicitly missing other impacted groups. Future work must identify and systematically integrate viewpoints from marginalized populations, displaced residents, and informal sector workers to capture distributional equity impacts of tourism development.

• Impact of Talent Management on Emotional Intelligence in Food Industry Companies in Hodeidah Governorate (2026) · doi

  The paper recommends redesigning motivation programs to include material and moral incentives that enhance employees' professional and emotional well-being, but provides no empirical testing of what specific incentive structures, compensation models, or recognition systems would effectively bridge the non-significant gap between motivation initiatives and emotional intelligence outcomes in food industry contexts.

• Barriers to Artificial Intelligence-Driven Supply Chain Integration: An Interpretive Structural Modeling-Cross-Impact Matrix Multiplication Applied to Classification (ISM-MICMAC)-Based Analytics Modeling Approach (2026) · doi

  The study identifies a significant gap between industry requirements and skills taught in educational institutions for AI-driven supply chains, but does not specify which particular AI competencies (e.g., machine learning model development, data pipeline architecture, supply chain domain knowledge) are most misaligned or how to quantify this gap empirically across different educational systems.