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Exploring justice perceptions in online banking recovery: gender moderation and behavioral outcomes

Research Abstract

The study addresses the recovery from service failures in online banking. It focuses on the three dimensions of perceived recovery justice – namely, distributive justice (DJ), procedural justice (PJ), and interactional justice (IJ) – and investigates their impact on post-recovery satisfaction (PRS), the moderating effect of gender, and further, the influences of PRS on customer trust (CT), affective commitment (AFFC), and customers’ behavioral intentions (CBI). The study uses partial least squares structural equation modelling to examine the data collected in Egypt from 445 respondents who experienced a service failure with online banking. The results show that the three dimensions of perceived recovery justice – DJ, PJ, IJ – exert positive influences on PRS, and gender moderates the effects of PJ and IJ on PRS: procedural justice makes women exhibit higher levels of PRS. In contrast, interactional justice makes men encounter higher levels of PRS. The results also show that PRS positively influences CBI through its direct and indirect effects (via CT and AFFC). Furthermore, PRS mediates the positive effects of DJ, PJ, and IJ on customers’ behavioral intentions. The study outcomes have significant theoretical and practical implications for online banking.

 


 

Research Authors
Attia Abdelkader Ali, Andreia Gabriela Andrei, Felipe Ruiz-Moreno, Luigi Zingone
Research Date
Research Journal
Journal of Business Economics and Management
Research Pages
164–185-164–185
Research Publisher
Emerald Publishing Limited
Research Rank
Q2
Research Vol
26
Research Website
https://doi.org/10.3846/jbem.2025.22831
Research Year
2025

The role of perceived justice and emotions in service recovery process: insights from the banking sector

Research Abstract
Purpose

This study investigates the impact of service failure severity, service recovery strategies and customers’ perceptions of recovery justice on post-recovery satisfaction, customers’ emotions and repurchase intentions in the banking sector of countries with different socio-cultural contexts.

Design/methodology/approach

The study employed a quantitative survey approach in the banking sector across Egypt and Spain. Online questionnaires were distributed to bank customers who experienced service failures within the past year. The final sample comprised 910 respondents (410 Egyptian and 500 Spanish). Data analysis was conducted with Smart PLS 4 for structural equation modeling.

Findings

Results showed that service failure severity negatively influenced recovery strategies only in Spanish banks. Service recovery strategies positively affected perceived recovery justice, which enhanced positive emotions and reduced negative ones across both countries. While perceived recovery justice and positive emotions increased post-recovery satisfaction, negative emotions decreased it. Besides, post-recovery satisfaction influenced repurchase intentions in both countries, though its mediating role between recovery justice and repurchase intentions was significant only for Spain. Educational level emerged as a significant moderator only in the Egyptian context.

Originality/value

The study developed and empirically examined a comprehensive conceptual model of the drivers and outcomes of post-recovery satisfaction in the banking sector. Providing meaningful insights into how social and cultural differences between customers in different countries can sometimes result in dramatically different behaviors following a service failure, the study highlights the need to adapt accordingly the strategies and the management processes of service recovery.

Research Authors
Attia Abdelkader Ali, Andreia Gabriela Andrei, Felipe Ruiz-Moreno, Giovanna Bagnato
Research Date
Research Journal
Business Process Management Journal
Research Publisher
Emerald Publishing Limited
Research Rank
Q1
Research Website
https://doi.org/10.1108/BPMJ-12-2024-1247
Research Year
2025

Managing generative artificial intelligence in the daily lives of people with disabilities

Research Abstract
Purpose

This research examines whether people with disabilities (PwDs) are willing to adopt generative artificial intelligence (GenAI) and identifies the factors influencing their use behavior in their daily lives.

Design/methodology/approach

The theoretical framework presented in this study integrates the unified theory of technology acceptance and use (UTAUT) and its extension, the UTAUT2, with the stimulus-organism-response (S-O-R) model. Empirical data were quantitatively analyzed using SmartPLS 4.

Findings

Effort expectancy, facilitating conditions and hedonic motivation (stimuli) positively affect perceived value (organism). Anxiety (stimulus) exerts a negative effect on perceived value. Perceived value generates a response by significantly affecting behavior intention, which drives GenAI use behavior in PwDs’ daily lives. If these stimuli are not properly managed, they lead to non-use by PwDs, resulting in avoidance behavior.

Research limitations/implications

This study enriches the technological innovation management literature by presenting a theoretical framework of the stimuli that affect GenAI use behavior by PwDs.

Practical implications

By underlining the interplay between PwDs and new technologies, this study offers practical implications and recommendations for tech and non-tech companies, policymakers and regulators to implement advanced technologies inclusively. It guides these practitioner groups to enhance user-centered innovation by adhering to the principles of inclusive technology design.

Originality/value

This study offers an inclusive analysis of GenAI use behavior by PwDs. Its originality lies in focusing on PwDs’ perceptions rather than predefined corporate-driven factors.

Research Authors
Attia Abd alkader Attia Ali
Research Date
Research Journal
Management Decision
Research Publisher
Emerald Publishing Limited
Research Rank
Q1
Research Website
https://doi.org/10.1108/MD-10-2024-2471
Research Year
2025

GenAI Use Behavior and Post-Failure Perceptions Among People With Functional Disabilities: A Multimethod Study

Research Abstract

Based on two complementary studies, this paper explores how people with functional disabilities interact with generative artificial intelligence (GenAI). Study 1 used a genetic algorithm to identify key factors influencing GenAI use behavior. These factors were then tested using Bayesian linear regression. The analysis was extended using inverse probability weighted regression adjustment (IPWRA) to study the moderating role of perceived value in the relationship between behavioral intention and use behavior. Study 2 employed a one-factor, two-level (GenAI vs. human officer) between-subjects experimental design to investigate how people with functional disabilities perceive GenAI failures compared to human errors. GenAI use behavior was found to be directly influenced by habit, promotional benefits, trust, and behavioral intention, with perceived value acting as a moderator. Exposure to GenAI failures reduced inferential trust significantly more than exposure to human errors. However, this effect was moderated by users’ attitudes and use behavior. Users with favorable attitudes and GenAI use were more resilient to generalized distrust. This paper contributes to the debate around inclusive technological innovation and behavioral research by showing that people with functional disabilities are active agents in GenAI adoption. The paper thus raises awareness of how use behavior, perceived value, and post-failure perceptions interact. Practically, it provides marketers, GenAI developers and policymakers with actionable strategies for inclusive GenAI design and failure management.

 


 

Research Authors
Attia Abd alkader Attia Ali
Research Date
Research Journal
Psychology & Marketing
Research Pages
3101-3122
Research Publisher
Psychology & Marketing
Research Rank
Q1
Research Vol
42
Research Website
https://doi.org/10.1002/mar.70028Digital Object Identifier (DOI)
Research Year
2025

Mapping Seniors’ Paths to Sustainable Tourism: An Enhanced Goal-Directed Behavior Approach

Research Abstract
This study applies an extended model of goal-directed behavior to investigate the factors influencing seniors’ engagement in sustainable tourism. Using data from 1,202 senior travelers across Western and Eastern Europe, it examines the antecedents shaping their desire and behavioral intentions toward sustainable travel. The results indicate that all variables significantly enhance seniors’ desire to engage in sustainable tourism. Certain factors, including negative anticipated emotions and perceived behavioral control, differ between Eastern and Western European senior tourists. These differences suggest that cultural and regional context influences the role of these factors in shaping sustainable travel behaviors. This research contributes to the tourism literature by providing cross-regional insights into sustainable tourism among the senior demographic, representing one of the first studies in this specific research stream. Practically, it highlights the need to adapt strategies to address regional and psychological factors to foster effective engagement in sustainable practices within this growing market segment.


 

Research Authors
Felipe Ruiz-Moreno, Carla Rodriguez-Sanchez, Giovanna Bagnato, Attia Abdelkader Ali
Research Date
Research Journal
Journal of Travel Research
Research Publisher
SAGE Publications
Research Rank
Q1
Research Website
https://doi.org/10.1177/00472875251410
Research Year
January 28, 2026

__Corporate investments in artificial intelligence and audit costs: does audit quality matter?

Research Abstract
Purpose

This study aims to investigate the influence of clients’ investments in artificial intelligence (CINV_AI) on audit costs within the Chinese context. Furthermore, this study moderates the role of audit quality on the relationship between corporate investments in AI and audit costs.

Design/methodology/approach

To test the hypotheses, this study uses an ordinary least squares regression using a final sample of 26,654 firm-year observations spanning the period 2016–2023. To mitigate potential endogeneity concerns, the researchers adopted the instrumental variable technique, specifically the two-stage least squares method.

Findings

This study reveals that corporate investments in AI has a statistically significant positive effect on audit costs, suggesting that clients with high investments in AI-increasing operational complexity and risk, increasing audit effort, improving audit efficiency and ultimately incurring higher audit costs. Furthermore, the results indicate that audit quality positively and significantly reinforces the link between corporate investments in AI and audit costs. Finally, the robustness tests support the main findings and confirm their validity.

Practical implications

This paper provides valuable insights for corporate managers, investors and auditors. For managers and investors, it emphasizes that AI implementation constitutes a substantial investment, encompassing considerable direct expenditures on assets and technology, as well as indirect costs such as increasing audit costs. For auditors, it emphasizes that these AI investments necessitate more audit effort and team members with specific IT expertise.

Originality/value

The results provide new evidence contributing to the recent inconclusive literature that investigates the impact of client IT capabilities (AI) on audit costs. To the best of the authors’ knowledge, this is the first study to investigate the moderating role of audit quality in the relationship between corporate AI investment and audit costs.

Research Authors
Mohsen Anwar Abdelghaffar Saleh; Shadi Emad Areef Alhaleh; Abdelkarim Mahmoud Mohamed; Sameh Abdelsalam Mustafa
Research Date
Research Department
Research Journal
Journal of Financial Reporting and Accounting
Research Pages
PP.1-21
Research Publisher
© Emerald Publishing Limited
Research Vol
Vol. ahead-of-print No. ahead-of-print.
Research Website
https://doi.org/10.1108/JFRA-06-2025-0446
Research Year
2026

Key audit matters and audit fees: Do two-tier board characteristics matter?

Research Abstract
Purpose

This study investigates the relationship between key audit matters (KAMs) and audit fees in the Chinese context. Furthermore, this study moderates the characteristics of the dual-board system (board of directors (BOD) and supervisory board (SB)) on the association between KAMs and audit fees.

Design/methodology/approach

The ordinary least squares (OLS), fixed effects (FE), and random effects (RE) were applied using a final sample of 17,286 firm-year observations from 2017 to 2022 to test the hypotheses. We relied on the instrumental variable using the two-stage least square (IV-2SLS) method and generalized method of moments (GMM) to address the endogeneity issue.

Findings

Our results show a positive and significant relationship between KAMs and audit fees. These findings indicate that audit fees are related to compliance with the requirements of China Standards on Auditing (CSA) No.1504 KAMs. Furthermore, our results indicate that factors such as board size, the level of board independence, and the size of the SB positively and significantly reinforce the association between KAMs and audit fees. However, the outcomes depict that SB independence has a significant and negative effect on the association between KAMs and audit fees. In contrast, the findings reveal that chief executive officer (CEO) duality does not have a statistically meaningful impact on the relationship between KAMs and audit fees. Finally, the robustness tests support the main findings and confirm their validity.

Research limitations/implications

Our paper focuses solely on the total number of KAM topics, while future studies could investigate how specific types of KAM disclosures, such as those related to revenue recognition, accounts receivable, and goodwill impairment, which are the most frequently reported KAMs, influence audit pricing in the Chinese context.

Practical implications

This study has theoretical and practical importance for regulators, auditors, practitioners, shareholders, and academics. For example, it can help regulators gain a clearer understanding of the impacts of the new Chinese auditing standard (CSA No. 1504) on audit fees.

Social implications

This study offers significant social implications by emphasizing the role of audit transparency and unique governance structures in protecting stakeholder interests, improving public trust in audit reports, and supporting economic development.

Originality/value

Our empirical findings provide novel evidence that contributes to the recent inconclusive literature on the impact of KAMs on audit fees. To the authors’ knowledge, this study provides the first empirical evidence in China that explores the moderating role of the dual-board system characteristics on the relationship between KAMs and audit fees.

Research Authors
Mohsen Anwar Abdelghaffar Saleh; Dejun Wu; Sameh Abdelsalam Mustafa; Abdelkarim Mahmoud Mohamed; Naila Amara
Research Date
Research Department
Research Journal
Journal of Applied Accounting Research
Research Pages
PP.1-21
Research Publisher
© Emerald Publishing Limited
Research Website
https://doi.org/10.1108/JAAR-08-2024-0297
Research Year
2026

Corporate investments in artificial intelligence and audit costs: does audit quality matter?

Research Abstract


 

Purpose

This study aims to investigate the influence of clients’ investments in artificial intelligence (CINV_AI) on audit costs within the Chinese context. Furthermore, this study moderates the role of audit quality on the relationship between corporate investments in AI and audit costs.

Design/methodology/approach

To test the hypotheses, this study uses an ordinary least squares regression using a final sample of 26,654 firm-year observations spanning the period 2016–2023. To mitigate potential endogeneity concerns, the researchers adopted the instrumental variable technique, specifically the two-stage least squares method.

Findings
This study reveals that corporate investments in AI has a statistically significant positive effect on audit costs, suggesting that clients with high investments in AI-increasing operational complexity and risk, increasing audit effort, improving audit efficiency and ultimately incurring higher audit costs. Furthermore, the results indicate that audit quality positively and significantly reinforces the link between corporate investments in AI and audit costs. Finally, the robustness tests support the main findings and confirm their validity.
Practical implications

This paper provides valuable insights for corporate managers, investors and auditors. For managers and investors, it emphasizes that AI implementation constitutes a substantial investment, encompassing considerable direct expenditures on assets and technology, as well as indirect costs such as increasing audit costs. For auditors, it emphasizes that these AI investments necessitate more audit effort and team members with specific IT expertise.

Originality/value

The results provide new evidence contributing to the recent inconclusive literature that investigates the impact of client IT capabilities (AI) on audit costs. To the best of the authors’ knowledge, this is the first study to investigate the moderating role of audit quality in the relationship between corporate AI investment and audit costs.

Research Authors
Mohsen Anwar Abdelghaffar SalehCorresponding Author; Shadi Emad Areef Alhaleh; Abdelkarim Mahmoud Mohamed; Sameh Abdelsalam Mustafa
Research Date
Research Journal
Journal of Financial Reporting and Accounting

Enhancing Insurance Fraud Detection Accuracy with Integrated Machine Learning and Statistical Methods

Research Abstract

The insurance industry plays a critical role in managing risks and providing financial security globally. However, the industry faces challenges, particularly with the increasing complexity of fraudulent activities. To address these challenges, this work seeks to construct suitable decision models by integrating methods such as feature discretization, feature selection, data resampling, and binary classification in order to create a prediction system for identifying insurance fraud. The research investigates various scenarios, including different combinations of classifiers, feature selection methods, feature discretization techniques, and data resampling strategies, and the performance of the predictive system is evaluated using established metrics. The experimental results revealed that integrating multiple methodologies during data preprocessing significantly enhances the performance of classification models. The model that utilizes the KBD + RFE + Over + RF scenario achieves the highest AUC and F1-score, indicating exceptional performance in detecting insurance fraud. Our research demonstrates that the proposed models’ ability to predict insurance fraud has been significantly enhanced by utilizing resampling methods and highlights the importance of these techniques in improving the efficiency of the utilized integrated artificial intelligence techniques. In addition, the article concludes that the insurance industry can greatly benefit from modern predictive methods to make sound decisions.

Research Authors
Ahmed Abdelreheem Ahmed Mohamed Khalil
Research Date
Research File
Research Journal
Computational Economics Journal
Research Publisher
Springer
Research Rank
1
Research Website
https://link.springer.com/article/10.1007/s10614-025-11074-0
Research Year
2025
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