S P Jain School of Global Management

The rapid emergence of financial technology (FinTech) has reshaped global banking. Its implications for credit risk in China’s fast-evolving market, however, remain important and underexplored. This study empirically investigates the relationship between FinTech adoption and bank credit risk using a panel dataset of 42 A-share listed banks in China over the period 2013 to 2022. A novel FinTech index is constructed through text mining of annual reports to capture bank-specific adoption levels. Employing ordinary least squares (OLS), system generalized method of moments (GMM), and robustness checks with alternative variables, the study finds consistent evidence that higher levels of FinTech adoption are significantly associated with lower non-performing loan (NPL) ratios, indicating improved credit risk profiles. Importantly, the analysis reveals that financial regulation plays a moderating role, with stricter regulatory environments diminishing the credit risk-reducing effect of FinTech. Furthermore, heterogeneity analysis suggests that the impact of FinTech on credit risk differs across bank types, with statistically weaker but economically meaningful variation. Among them, urban commercial banks experience a significant reduction in credit risk due to the adoption of FinTech. In contrast, joint-stock commercial banks show a significant increase in credit risk following FinTech adoption. For state-owned commercial banks and rural commercial banks, the effects are negative but statistically insignificant. The findings contribute to the evolving literature on FinTech, financial intermediation, and risk management, offering practical implications for bank managers and policymakers alike.

This study presents an ensemble decision-making approach to evaluate Blockchain and Internet of Things (BCT-IoT) integrations for enhancing supply chain (SCs) performance. While existing evaluations focus on individual functional aspects, they often overlook interdependencies and fail to provide reliable ranking and grading under uncertainty. To overcome these limitations, a novel multidimensional Ensemble Generalized Three-Way-Decision (EG3WD) approach is developed. The first dimension represents the bi-level hierarchical Half-Quadratic Programming (HQP) structure, while the second dimension involves the weighting process. Weights are determined using a reformulated Fuzzy-Weighted-Zero-Inconsistency-Based-Interrelationship-Process (FWZICbIP) technique within a Mixed-Normal-Hesitant-Fuzzy-Sets (MNHFS) environment referred to as FWZICbIP-MNHFS and are integrated with an HQP-flat based ensemble technique. This approach enables robust ranking and grading of BCT-IoT alternatives within SCs performance evaluations. Key contributions include: (1) integrating expert evaluations across the supply chain, blockchain, and IoT domains; (2) enhancing expert and criterion weighting under uncertainty; (3) introducing a dynamic fuzzy-opinion matrix to link BCT-IoT alternatives with functional aspects using a utility-based dynamic localization technique; and (4) applying a probabilistic multidimensional EG3WD approach with adaptive Bayesian thresholds for robust triadic classification. The approach was applied to 40 BCT-IoT alternatives. Results show that alternative A11 achieved the highest probability (0.9728) and was consistently classified as Positive, while A31 had the lowest (0.0460), falling in the NEG region. Compared to existing approaches, multidimensional EG3WD demonstrated superior performance in managing uncertainty, consistency, and decision reliability.

Featuring real-world examples and ethical guidance, the authors demystify prompt engineering, showing you how to craft effective prompts, streamline research, generate teaching materials, and foster creativity in both classroom and scholarly settings. With a focus on responsible management and quality education, chapters not only equip you with future-proof skills but also address the ethical considerations of AI in education. Discover how to boost productivity, maintain academic integrity, and stay ahead in a rapidly evolving digital landscape.

The research aims to identify and understand the patterns associated with product seasonality in the United Arab Emirates, based on products associated with different cultures and traditions. In addition, the research aims to identify UAE-based consumers’ attitudes and behaviors toward the seasonality of the products. The study also aims to offer recommendations for strategizing marketing and communication campaigns of seasonal products in the UAE. A systematic review of the available literature sources has been performed to identify factors that influence the seasonality of the products. Further, the findings of the systematic review have been contextualized within the specific context of Middle Eastern cultural influences on marketing of seasonal products. Following this, the surveys with participants from the United Arab Emirates (N = 300) have been deployed to understand consumer behavior and motivation related to highly seasonal products, such as Vimto and Pumpkin Spice Latte. The findings indicate that numerous factors influence the seasonality of product campaigns in the United Arab Emirates. The factors can be grouped into two clusters: objective (e.g., weather conditions, climate) and subjective (e.g., religion, beliefs). Due to the influence of these factors, some products show high seasonality even though marketing and communication efforts are made throughout the entire year. Moreover, consumer attitudes show potential to expand the purchasing range for the products by alignment and introduction of different product modifications. According to the available body of literature, this is the first research that analyzes the seasonality of the products in the United Arab Emirates in a dual context—combining both systematic review and quantitative research. Also, the research offers suggestions and guidelines for marketing and communication practitioners on how to set up campaigns to increase the purchasing periods of the products in the UAE market.