Data gaps in Economics

Representative open questions

Showing 30 of 112 — 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 analysis identifies infrastructural deficits and administrative fragmentation as structural barriers to circular economy adoption in marginalised Italian territories, but lacks empirical quantification of how specific infrastructure types (waste management systems, recycling facilities, logistics networks) correlate with provincial circularity index scores at different scales of territorial marginalisation.

• Improving social inclusion of female migrants: a randomised controlled intervention in Spain (2026) · doi

  Several social resources indicators—trust in social workers, autonomy in managing the IMV (Minimum Vital Income), and autonomy in accessing social resources—were measured only at endline with no baseline data collected. This prevents causal attribution of changes in these dimensions of social inclusion to the intervention and limits understanding of pre-existing differences between treatment and control groups.

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

  The dataset does not contain loan application outcomes, preventing determination of whether applicants engaging in repeat applications for consumption smoothing will actually engage in repeat borrowing for consumption smoothing purposes. This creates an important endogeneity concern that cannot be resolved with the current lead generator data structure.

• 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

  The model confuses positive articles for neutral or negative when macroeconomic worries (e.g., inflation) overshadow small gains. Incorporating external macro-economic indicators (inflation rate, subsidy flags, taka devaluation metrics) as explicit features into SSABE-TSCM is needed to refine temporal context and reduce this confusion pattern in low-resource Bangla financial sentiment analysis.

• 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 paper acknowledges security concerns persist regarding UPI and digital payment systems among students, but provides no comparative analysis of security perception vs. actual breach incidents or specific vulnerability categories that students perceive as most problematic.

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

  The study reports that 60% of respondents believe AI can replace human involvement in banking services, but does not investigate which specific banking operations (loan approvals, customer service, risk assessment, compliance) exhibit different human-replacement feasibility rates or identify operational contexts where AI-human collaboration outperforms full automation.

• 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.

• 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

  The study covers only 2015-2024 commodity price data; extending the analysis to include pre-2015 periods and post-2024 data would determine whether the observed cointegration relationships between MCX and international exchanges (COMEX, NYMEX) remain stable across different market regimes, particularly during extreme events like the 2008 financial crisis or the 2020 pandemic.

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

  The paper reports that 30% of respondents identify lack of integration with existing systems as a primary challenge to AI tool adoption, but does not investigate which specific ATS (applicant tracking system) platforms create integration barriers or what technical compatibility standards should be prioritized. Empirical testing of AI tool integration with multiple ATS architectures is needed.

• 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

  The study is geographically limited to West Bengal, India, a single state region. The conclusion explicitly calls for 'longitudinal and multi-state studies' but does not specify which states, institutional types, or regional economic conditions should be compared to test whether the identified predictors (income, professional experience, teaching stream) replicate across India's diverse higher education landscape.

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

  The case study presents only Kyivstar (a single telecommunications enterprise) with a digital transformation index of 0.82, but does not provide comparative data across multiple enterprises in regional and international markets to validate whether the proposed AI competitiveness framework generalizes across different industries, company sizes, or market contexts.

• 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.