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This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

This study aims to determine the prevalence of selected health behaviors (smoking, diet, exercise and early cancer detection) and outcomes (obesity, cardiovascular fitness, type II diabetes mellitus and cancer) among Arab immigrants living in Colorado and evaluate the relationships between acculturation and health behaviors from a socio-ecological perspective.

This paper is a cross-sectional survey of 100 adult Arab immigrants living in Colorado.

The study showed that Arab immigrants in Colorado engage in healthy behaviors such as eating a healthy diet rich in fruits and vegetables (34 per cent), exercising (44 per cent) and seeking early cancer screening (35 per cent among women and 42 per cent among men). In comparison to the general population in Colorado, the study results showed that Arab immigrants were more likely to engage in moderate or vigorous exercise (p < 0.001, OR = 1.84) and consume the recommended daily amounts of fruits and vegetables (p = 0.05, OR = 1.56). The study revealed that culture plays an important role in shaping and affecting Arab immigrant health behaviors. Those who were more acculturated were more likely to be physically active and eat healthy.

The prevalence of overweight in the current sample was similar to the rate of overweight in other studies of Arab immigrants. This study’s findings about overweight signal a need for culturally sensitive health promotion interventions for Arab immigrants. The study limitations included the use of self-reported measures in the survey, the use of cross-sectional design and the use of a probability sample.

Understanding culturally relevant predictors of certain health behaviors, such as exercise and diet, can help health providers design health promotion interventions that focus on the individual and the environment to meet the health needs of Arab immigrants.

This paper aims to investigate the effect of paternalistic leadership (benevolent, moral and authoritarian) on knowledge sharing of nurses through the mediation of organizational commitment (affective, continuance and normative). Further, the study examines the moderating role of Islamic work ethics on the association between organizational commitment and knowledge sharing.

In this quantitative study, data was collected from 312 nurses working in the health-care sector of Pakistan through “Google Forms” in two waves. Moreover, structural equation modeling was used to test the proposed hypotheses.

The study noted affective and normative commitment as mediators between the associations of benevolent, moral and authoritarian leadership with knowledge sharing, whereas continuance commitment was not found as an explaining variable. In addition, Islamic work ethics was found to strengthen the association of affective and normative commitment with knowledge sharing. However, Islamic work ethics was found to weaken the association between continuance commitment and knowledge sharing.

This study offers practical insights for health-care executives to act as fatherly figures to enhance the knowledge sharing of their nurses. The study recommends that managers in the health-care system build such an environment that helps nurses follow Islamic work ethics. It may enhance their level of organizational commitment and encourage them to engage in knowledge sharing behaviors to have a successful work environment.

To the best of the authors’ knowledge, this research is the first to extend the literature on paternalistic leadership. More specifically, this study investigated how various dimensions of paternalistic leadership (benevolent, moral and authoritarian) effects three-dimensional commitment (affective, continuance and normative) to enhance knowledge sharing behavior among nurses.

Following the unceasing pressure on companies to adopt sustainable business practices to mitigate climate effect, this study aims to examine corporate governance (CG) attributes and role of activist investors in influencing extensive sustainability practice for firms in the developed and emerging climes.

Using a panel ordered probit regression analysis for 368 companies over 2016 to 2019, the study examined CG attributes that drive extensive corporate sustainability practice. The study addressed endogeneity bias using STATA Extended panel ordered probit regression model with endogenous covariates.

The result showed CG attributes is critical for firms, and activist investors play a critical role in driving extensive sustainability practice. Findings further reveal the extent of adoption is relatively low in the emerging climes but showed sign of improvement over the years examined.

The study focused mainly on larger firms operating in different sectors globally. Hence, findings cannot be generalized for small sized entities.

The study provides an insightful explanation regarding the extensive sustainability practices and the vital role assumed by activist investors.

The increasing number of companies responding to Carbon Disclosure Project and consequent improvement in scores indicates a corporate commitment to ensuring a sustainable future.

This research offers significant insights to the extent discussion on attributes of CG critical for sustainability practice. The findings ascertain useful tools to aid the continued adoption of sound sustainability practices around the globe.

The purpose of this study is to understand the public value of the government of Kuwait using blockchain technology to develop the capabilities of smart cities.

Research was conducted in Kuwait, where the increased use of blockchain technology has been evidenced in both the private and public sectors. A total of seven IT managers were interviewed to gauge their responses to blockchain and its use in Kuwait ministries.

Blockchain technology offers many benefits for the development of smart cities in Kuwait. This is a statement that received almost mutual agreement amongst all the IT managers interviewed. However, as regards wider acceptance, the majority mentioned that a framework is necessary to better articulate the public value of using blockchain in smart cities in Kuwait.

This paper develops research hypotheses and a framework for articulating the public value of blockchain technology for smart cities in Kuwait.

South Asia is one of the fastest-growing regions in the world. With its fast economic development, the energy requirement for the region has rapidly grown. As the region relies mainly on nonrenewable energy sources and is suffering from issues like pollution, the high cost of energy imports, depleting foreign reserves, etc. it is searching for those factors that can help enhance the renewable energy generation for the region. Thus, taking these issues into consideration, this paper aims to investigate the impact of macroeconomic factors that can contribute to the enhancement of renewable energy output in South Asia.

An autoregressive distributed lag methodology has been applied to examine the long-term effects of remittance inflows, literacy rate, energy imports, government expenditures and urban population growth on the renewable energy output of South Asia by using time series data from 1990 to 2021.

The findings indicated that remittance inflows have a negative and insignificant long-term effect on renewable electricity output. While it was discovered that energy imports, government spending and urban population growth have negative but significant effects on renewable electricity output, literacy rates have positive and significant effects.

Considering the importance of renewable energy, this is one of the few studies that has included critical macroeconomic variables that can affect renewable energy output for the region. The findings contribute to the body of knowledge that a high literacy level is crucial for promoting renewable energy output, while governments and policymakers should prioritize reducing energy imports and ensuring that government expenditures on renewable energy output are properly used. SAARC, the governing body of the region, also benefits from this study while devising the renewable energy output policies for the region.

This paper aims to propose that the socio-technical perspective is under-represented when appraising the adoption potential of renewable energy technologies (RETs) in late-industrialising countries and that this results in under-adoption. It also aims to identify a methodological approach that allows the socio-technical perspective to be integrated into management decision-making, alongside the more typical economic appraisal methodology.

A case study and novel mixed-methodology approach is used, which applies the diffusion of innovations framework, innovation system (IS) framework and system dynamics modelling (SDM) alongside traditional economic modelling and appraisal techniques. This approach is used to assess the adoption potential of solar photovoltaic (PV) and diesel water pumping systems in the wildlife conservation sector and surrounding rural communities in Kenya. The case study approach tests the merits of the mixed-methodology approach.

The life-cycle costs of solar PV water pumping systems are lower in nearly all financing and utilisation scenarios; offer additional social, technical and environmental benefits; and the conditions exist for greater adoption. The use of an integrated diffusion of innovations and IS framework generates significant qualitative data that can support management decision-making. The use of SDM techniques aid conceptualisation of the community economic, water and institutional systems into which water pumps may be diffused and provide a starting point for formal SDM simulation. The results suggest that these techniques capture the socio-technical perspective well and, when used alongside traditional project appraisal approaches, produce more complete information with which to support management decision-making.

This mixed-methodology approach could be used by practitioners to increase the diffusion and adoption of RETs in more complex contexts in late-industrialising countries. The emergent theory built through the case-study approach should be tested further to assess the merits of applying these techniques to support RET management decision-making in other contexts and more broadly.

The purpose of this study is to explore the impact of remote auditing on audit quality in non-Big 4 firms in Jordan. It also examines the role of auditors’ capabilities in this relationship, emphasizing their importance in implementing this technology effectively.

The perspectives of non-Big 4 audit firms regarding the influence of remote auditing on audit quality were gathered through the administration of a comprehensive questionnaire.

This study demonstrates that remote auditing can enhance audit quality in non-Big 4 firms. The strength of this effect is bolstered by the auditor’s technical knowledge, communication skills and professional skepticism.

Remote auditing is a promising alternative to traditional methods for non-Big 4 firms, with significant implications. Effective remote audits require technical knowledge, communication skills and professional skepticism. To succeed, firms must invest in training programs that equip auditors with the necessary remote auditing techniques.

This groundbreaking study investigates the effects of remote auditing on audit quality in Jordanian non-Big 4 firms and examines the influence of auditors’ capabilities. Results show that auditors’ capabilities enhance the positive impact of remote auditing on audit quality.

Environmental pollution has emerged as a major concern in the 21st century following the introduction of sustainable development (SD) by the year 2030, whereby one of the predominant goals is related to the manufacturing industry. In Malaysia, the automotive industry is acknowledged as the backbone driving for economic growth and recognised as a source of environmental deterioration. Therefore, eco-innovation is, thus, introduced as one of the efforts for minimised environmental effects, reduced social impact and firm value sustenance. In particular, eco-product innovation is one of the renowned environmental innovation dimensions and displays high adoption and diffusion rates in developed countries due to green awareness and government financial assistance. However, developing countries such as Malaysia show relatively low adoption of such practices amongst companies, whereby most of the efforts are driven by the governments, supplier and customer demands. Therefore, this paper aims to delineate the factors of voluntary initiatives undertaken by the Malaysian automotive and auto parts industry towards eco-product innovation.

The research drew from the micro-level perspective, thus using dynamic capabilities (DC) constructs and environmental management system (EMS) strategy variables. The constructs included technology collaboration, green human resources and eco-culture, while the variables denoted formal EMS and top management support. Survey data were obtained from 242 entities within the Malaysian automotive and auto parts industry, which were subjected to analysis via confirmatory factor analysis and structural equation modelling.

The findings revealed the moderating role played by eco-product innovation for the association linking EMS strategy and sustainability development, while no moderator effects were observed between DC and sustainability development. Thus, future research can be performed in the meso and macro-level areas by using qualitative research across different sectors.

This paper explicates novel literature content, particularly for the field of eco-product innovation; it positions an empirical analysis from the micro-level perspective regarding the antecedence of DC and environmental strategy towards eco-product innovation and SD, mainly in the automotive industry.

The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with multiple gateways. It entails IoMT devices and wearables connecting to exchange sensitive data with a sensor node which performs the aggeration process and then communicates the data using a Fog server. If the aggregator sensor loses the connection from the Fog server, it will be unable to submit data directly to the Fog server. The node transmits encrypted information with a neighboring sensor and sends it to the Fog server integrated with federated learning, which encrypts data to the existing data. The fog server performs the operations on the measured data, and the values are stored in the local storage area and later it is updated to the cloud server.

SHDCT uses an Internet-of-things (IoT)-based monitoring network, making it possible for smart devices to connect and interact with each other. The main purpose of the monitoring network has been in the collection of biological data and additional information from mobile devices to the patients. The monitoring network is composed of three different types of smart devices that is at the heart of the IoT.

It has been addressed in this work how to design an architecture for safe data aggregation in heterogeneous IoT-federated learning-enabled wireless sensor networks (WSNs), which makes use of basic encoding and data aggregation methods to achieve this. The authors suggest that the small gateway node (SGN) captures all of the sensed data from the SD and uses a simple, lightweight encoding scheme and cryptographic techniques to convey the data to the gateway node (GWN). The GWN gets all of the medical data from SGN and ensures that the data is accurate and up to date. If the data obtained is trustworthy, then the medical data should be aggregated and sent to the Fog server for further processing. The Java programming language simulates and analyzes the proposed SHDCT model for deployment and message initiation. When comparing the SHDCT scheme to the SPPDA and electrohydrodynamic atomisation (EHDA) schemes, the results show that the SHDCT method performs significantly better. When compared with the SPPDA and EHDA schemes, the suggested SHDCT plan necessitates a lower communication cost. In comparison to EHDA and SPPDA, SHDCT achieves 4.72% and 13.59% less, respectively. When compared to other transmission techniques, SHDCT has a higher transmission ratio. When compared with EHDA and SPPDA, SHDCT achieves 8.47% and 24.41% higher transmission ratios, respectively. When compared with other ways it uses less electricity. When compared with EHDA and SPPDA, SHDCT achieves 5.85% and 18.86% greater residual energy, respectively.

In the health care sector, a series of interconnected medical devices collect data using IoT networks in the health care domain. Preventive, predictive, personalized and participatory care is becoming increasingly popular in the health care sector. Safe data collection and transfer to a centralized server is a challenging scenario. This study presents a mechanism for SHDCT. The mechanism consists of Smart healthcare IoT devices working on federated learning that link up with one another to exchange health data. Health data is sensitive and needs to be exchanged securely and efficiently. In the mechanism, the sensing devices send data to a SGN. This SGN uses a lightweight encoding scheme and performs cryptography techniques to communicate the data with the GWN. The GWN gets all the health data from the SGN and makes it possible to confirm that the data is validated. If the received data is reliable, then aggregate the medical data and transmit it to the Fog server for further process. The performance parameters are compared with the other systems in terms of communication costs, transmission ratio and energy use.