Results 111 to 120 of about 10,511 (262)
FinTech and Environmental Sustainability: Evidence From Brazil
Sustainable Development, EarlyView.ABSTRACT This study explores the dynamic interplay between economic growth and environmental sustainability from a FinTech perspective, using Brazil as a case study. While FinTech's contribution to green transformation, sustainable finance, and resource efficiency has gained increasing attention, a notable lack of empirical research remains to assess ...
Kemal Eyuboglu, Umut Uzar
wiley +1 more source
Semiparametric spatial autoregressive models with nonlinear endogeneity
Econometric ReviewsThis article constructs nonparametric two-step least squares (2SLS) and generalized method of moments (GMM) sieve estimators to estimate a functional-coefficient spatial autoregressive model with an endogenous environment variable. We derive the consistency and asymptotic normality results for our proposed sieve estimators.
openaire +1 more source
Thunderbird International Business Review, EarlyView.ABSTRACT The present study has investigated two objectives. First, it examines the unconditional impact of economic policy uncertainty (EPU) on Africa's structural transformation. Second, it explores the conditional role of human resource development in the nexus between economic policy uncertainty (EPU) and structural transformation.
Ekene ThankGod Emeka +2 more
wiley +1 more source
A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT The analysis of spatiotemporal data is essential across many fields, such as transportation, meteorology and healthcare. Data gathered in practical applications often suffer from incompleteness due to device failures and network disruptions.
Yakun Chen +7 more
wiley +1 more source
Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
wiley +1 more source
The effect of Advertising on the Profitability of Iranian Textiles
تحقیقات بازار یابی نوین, 2014 The main purpose of this paper is to examine the impact of Advertising Expenditures on the Profitability in the Iranian Textiles (textiles, garments, bags and leather) Industries. The data of the industrial workplaces with 10 employees or more activating
Ali Dehghani
doaj
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu +4 more
wiley +1 more source
Multi‐Step Ahead Short‐Term Load Forecasting Based on MCNN‐MMoL
IET Smart Energy Systems, EarlyView.This paper proposes the MCNN‐MMOL model to eliminate cumulative errors in multi‐step load forecasting. The innovation lies in the MCNN's parallel convolutional branches that achieve multi‐scale feature fusion by balancing global load trends and local sub‐load dynamics.
Suxun Zhu +7 more
wiley +1 more source
The Consequences of Soil Organic Carbon for Crop Yield, Farm Productivity and Profit
Australian Journal of Agricultural and Resource Economics, EarlyView.ABSTRACT Crop choices affect soil organic carbon (SOC) stocks, allowing farmers to manipulate the amount of carbon sequestered in the soil over time. This paper examines the private and public benefits of crop rotations that sequester additional carbon across the province of Saskatchewan, Canada using a novel field‐level dataset from the Saskatchewan ...
Devin Allen Serfas
wiley +1 more source
Explainable spatial machine learning for hedonic real estate modeling
Real Estate Economics, EarlyView.Abstract Accurately modeling rents and prices is a key challenge in real estate analysis. Traditional linear models may fail to capture complex non‐linear relationships, and spatial dependencies are often ignored in existing machine‐learning approaches.
Tim Gyger +5 more
wiley +1 more source