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The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.

Technology advancement has changed how banks operate. Modernizing technology has, on the one hand, made it simpler for banks to do their daily business, but it has also increased cyberattacks. The purpose of the study is to to determine the factors that have the most effects on online fraud detection and to evaluate the advantages of AI and human psychology research in preventing online transaction fraud. Artificial intelligence has been used to create new techniques for both detecting and preventing cybercrimes. Fraud has also been facilitated in some organizations via employee participation.

The main objective of the research approach is to guide the researcher at every stage to realize the main objectives of the study. This quantitative study used a survey-based methodology. Because it allows for both unbiased analysis of the relationship between components and prediction, a quantitative approach was adopted. The study of the body of literature, the design of research questions and the development of instruments and procedures for data collection, analysis and modeling are all part of the research process. The study evaluated the data using Matlab and a structured model analysis method. For reliability analysis and descriptive statistics, IBM SPSS Statistics was used. Reliability and validity were assessed using the measurement model, and the postulated relationship was investigated using the structural model.

There is a risk in scaling at a fast pace, 3D secure is used payer authentication has a maximum mean of 3.830 with SD of 0.7587 and 0.7638, and (CE2).

This study focused on investigating the benefits of artificial intelligence and human personality study in online transaction fraud and to determine the factors that affect something most strongly on online fraud detection. Artificial intelligence and human personality in the Indian banking industry have been emphasized by the current research. The study revealed the benefits of artificial intelligence and human personality like awareness, subjective norms, faster and more efficient detection and cost-effectiveness significantly impact (accept) online fraud detection in the Indian banking industry. Also, security measures and better prediction do not significantly impact (reject) online fraud detection in the Indian banking industry.

The purpose of this study is to learn how the incorporation and use of leanness, agility and innovation in Indian manufacturing micro, small and medium enterprises (MSMEs) affect their bottom lines and how much these factors contribute to the MSMEs’ ability to meet their long-term sustainability goals.

The suggested model was subjected to data validation and additional empirical validation using a sample of 411 Indian manufacturing MSMEs. The analysis of construct measures is conducted through the utilization of confirmatory factor analysis, a statistical technique that is grounded in the theoretical framework of structural equation modeling (SEM). In addition, path model analysis was applied for the purpose to validate the assumptions that were included in the structural models.

Consistent with the proposed model, the findings of this study demonstrate that leanness, agility and innovation have a substantial favorable impact on the sustainability of a company’s performance. These findings may be helpful in gaining professionals, academics and policymakers to acknowledge the significance of leanness, agility and innovation in enhancing the long-term sustainability of MSMEs and enhancing the overall performance of a particular company. This research excluded the service industries-based research papers.

Many research in the field of manufacturing industries that have adopted leanness, agility, innovativeness and sustainability as individual approaches or as a collective methodology of two or more were considered in the current study. This research excluded the service industries-based research papers.

This literature review has recognized and analyzed various dimensions and roles of leanness, agility, innovativeness and sustainability that are prevalent in manufacturing industries that include the positive and negative effects on the performance of the industries. The research enlightens the path and shows future directions for research to develop efficient, effective and sustainable manufacturing industries.

By promoting the concept of focusing on the “human factor”, namely, stakeholder perspectives, the MSME sector is propagating a strategy that moves away from an excessive focus on technology and toward a more humane one. Through the application of the three key concepts of leanness, agility and innovation, this work aims to create a framework for measuring the sustainability performance of micro-, small- and medium-sized enterprises (MSMEs), with the ultimate goal of assisting the country in achieving the Sustainable Development Goals in the fields of industry, innovation and infrastructure by supporting environmentally friendly and resource-conserving businesses that give back to society and the natural environment.

The objective of this research is to assess the importance and effectiveness of integrating various approaches such as leanness, agility, innovativeness and sustainability within the framework of manufacturing micro, small, and medium enterprises (MSMEs). The authors hope that by going further into these concepts, they will be able to broaden their understanding and get a more comprehensive insight into the role that these concepts play and how they might be successfully used within this environment.

This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining strategies, this study seeks to develop a technique that could assess and predict the onset of cardiac sickness in real time. The use of a triple algorithm, combining particle swarm optimization (PSO), artificial bee colony (ABC) and support vector machine (SVM), is proposed to enhance the accuracy of predictions. The purpose is to contribute to the existing body of knowledge on cardiac disease prognosis and improve overall performance in health care.

This research uses a knowledge-mining strategy to enhance the detection and quantification of cardiac issues. Decision trees are used to form predictions of cardiovascular disorders, and these predictions are evaluated using training data and test results. The study has also introduced a novel triple algorithm that combines three different combination processes: PSO, ABC and SVM to process and merge the data. A neural network is then used to classify the data based on these three approaches. Real data on various aspects of cardiac disease are incorporated into the simulation.

The results of this study suggest that the proposed triple algorithm, using the combination of PSO, ABC and SVM, significantly improves the accuracy of predictions for cardiac disease. By processing and merging data using the triple algorithm, the neural network was able to effectively classify the data. The incorporation of real data on various aspects of cardiac disease in the simulation further enhanced the findings. This research contributes to the existing knowledge on cardiac disease prognosis and highlights the potential of leveraging past data for strategic forecasting in the health-care sector.

The originality of this research lies in the development of the triple algorithm, which combines multiple data mining strategies to improve prognosis accuracy for cardiac diseases. This approach differs from existing methods by using a combination of PSO, ABC, SVM, information gain, genetic algorithms and bacterial foraging optimization with the Gray Wolf Optimizer. The proposed technique offers a novel and valuable contribution to the field, enhancing the competitive position and overall performance of businesses in the health-care sector.

This study aims to conceive and develop a pricing model for the Ijara contingent convertible contract (ICCC, hereafter), considering the possibility that the lessee may default. The ICCC model grants the lessor the option of converting the unpaid amount into equity or recovering the leased equipment and selling it at market price in case of financial distress.

The ICCC is consistent with the profit-sharing approach and the new risk management techniques, which are compatible with Islamic philosophy. Relying on real options theory and the contingent claim approach, a closed-form solution of the firm’s assets is developed in a dynamic environment, where the rate of return is generated by a Cox-Ingersoll-Ross stochastic process.

Examining the numerical analysis reveals the impact of the firm value, the conversion or sell decision and the conversion ratio and volatility on the ICCC value. The value of the ICCC can increase substantially as the value of the firm approaches the conversion threshold. The conversion ratio as well as the asset market price play equally an important role in the decision to convert or sell.

This paper develops a pricing model for a contingent Ijara contract, which incorporates a conversion option to mitigate the lessee’s credit risk during periods of economic instability. The ICCC is a cooperative strategy that would be advantageous to all parties, including the lessor and lessee. In the event of a conversion, businesses may be able to continue operating thanks to this financial innovation, and the lessor may profit from the company’s recovery by freeing up more resources for the use of more profitable ventures.

This study aims to explore the strategies for implementing research data management (RDM) services in Tanzania’s higher education institutions (HEIs).

The study drew upon the technology, organization, people and environment (TOPE) framework. Using a qualitative case study approach, data was collected through semistructured interviews with librarians, lecturers, information and communication technologies (ICT) and research and innovation staff. Data was thematically analyzed.

Numerous participants recognized the importance of RDM services, such as creating data management plans, enhancing the retrieval and reuse of research data and offering support for data curation and preservation. The study also identified organizational support, including developing policies and guidelines, providing financial assistance and ensuring data security. Furthermore, the study highlighted the importance of ICT infrastructure, including servers, software and hardware. A lack of ICT infrastructure and limited skills and knowledge among those responsible for implementing RDM services were among the challenges identified.

This study used the TOPE framework, along with relevant literature, to guide the formulation of research objectives and questions. While the TOPE framework offers a comprehensive view through its four dimensions, there is a need to integrate additional models, such as data curation, to achieve a more holistic understanding.

This study provides valuable insights into strategies for implementing RDM services in HEIs. It highlights the importance of professional development for stakeholders, enabling them to develop and enforce effective strategies supporting a data-driven research agenda.

This study contributes original insights by outlining the necessary strategies for HEIs to consider when implementing RDM services. The study adds value to understanding effective RDM implementation requirements in an academic setting by identifying various strategies for developing RDM activities.

This study aims to propose a moderated mediation model to investigate the moderating effects of environmental, social and governance (ESG) performance on the relationship between inefficient investment and firm performance and the mediating effect of firms that participate in institutional research on the relationship between investment efficiency and performance. This study also analyses the heterogeneity of the corporate nature, intensity of industrial research and development (R&D), industrial competition and regional marketization.

This study uses a panel data fixed-effects model to conduct a regression analysis of 1,918 Chinese listed firms from 2016 to 2020. A Fisher’s permutation test is used to examine the differences between state-owned and nonstate-owned firms.

Inefficient investment negatively impacts corporate performance and higher ESG performance exacerbates this effect by attracting more institutional research which reveals more problems. State-owned enterprises perform significantly better than nonstate-owned enterprises in terms of ESG transformation. Industrial R&D intensity, competition and regional marketization also mitigate the negative effects of inefficient investment on corporate performance.

This study suggests that companies should consider inefficient investments that arise from agency issues in corporate ESG transformation. In addition, state-owned enterprises in ESG transformation should take the lead to achieve sustainable development more efficiently. China should balance regional marketization, encourage enterprises to increase R&D intensity, reduce industry concentration, encourage healthy competition and prevent market monopolies.

This study combines the agency and stakeholder theories to reveal how inefficient investments that arise from agency issues inhibit value creation in ESG initiatives.

The objective of this review is to provide a comprehensive analysis of risk management practices in the healthcare sector, with a particular focus on identifying challenges and strategies in Moroccan hospitals.

A literature search was carried out on several academic search engines using search terms reflecting the relationship between risk management and public hospitals in Morocco.

The Moroccan public hospital is confronted with several disjunctions, which can be sources of multiple risks. This influences the quality of care provided to patients and can sometimes threaten their vital prognosis. The risk management process can help health professionals, researchers and risk managers to be agile and identify and anticipate risks in order to avoid serious accidents that can affect the whole organization, especially after the pandemic lived experiences (COVID-19).

Protecting human life in an environment where risks are omnipresent is a dilemma that every hospital organization must confront. So, risk management in the hospital is not a simple process, given the interaction of several components and the sensitivity of the field. Risk management in this establishment must be rigorous because every error can cost human life. In this sense, the analysis of risk management processes in Moroccan hospitals, based on what really exists, enables the identification of shortcomings in order to master the risk management system and thus protect goods and services as well as human life, which is the ultimate goal of the hospital organization’s existence.

Despite the rapid growth of corporate social responsibility (CSR) in emerging markets, there remains a need in the current literature for deeper insights into the factors influencing CSR practices in these contexts. This study aims to address this research gap and enhance the discourse on CSR in emerging markets by exploring the reciprocal relationship between business and government and its potential role in driving firms’ CSR efforts in these burgeoning economies.

The study is grounded in the theory of reciprocity and integrates insights from existing literature to posit that, within a reciprocal relationship, firms respond positively to government regulatory support by actively participating in CSR initiatives. To test this hypothesis, data from prominent sources, including the CSRHub database, the World Bank’s Ease of Doing Business, and the International Country Risk Guide, are gathered, yielding a sample of nearly 1,500 firms operating in diverse emerging markets. A series of empirical tests are then conducted to validate the existence of the reciprocal relationship and its influence on firms’ CSR efforts.

The findings reveal strong evidence of a reciprocal relationship between business and government in emerging markets. When the government provides favorable regulatory support, firms tend to reciprocate by shouldering greater responsibility in promoting societal well-being, specifically through active participation in CSR initiatives directed toward the well-being of the community in which they operate. These findings are robust across various estimation methods.

The study advances the understanding of CSR in emerging markets and provides valuable insights into the role of reciprocity in promoting CSR in real-world settings. This offers promising avenues for future theoretical and empirical research in the field of CSR.

Policymakers are urged to recognize the significance of business-government relations in fostering CSR. Developing a supportive regulatory environment can motivate firms to invest in CSR, benefiting both businesses and the communities they serve. For businesses, aligning CSR initiatives with community needs can foster a mutually beneficial relationship with the government, leading to greater social benefits and competitive advantages.

To the best of the authors’ knowledge, this study pioneers the application of the reciprocity theory to explain the interplay between business and government in shaping firms’ CSR endeavors in emerging markets.

This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.