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The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

The purpose of this study is to investigate the adoption of cloud computing as a digital technology by small and medium enterprises (SMEs) and assess its impact on sustainability of such enterprises.

A model was developed that featured factors influencing SMEs sustainability. Primary quantitative data was gathered using a survey as an instrument. Total set of n = 387 responses were gathered using a convenience sampling method.

Findings reveal that cost reduction, ease of use, reliability and sharing and collaboration factors have significant statistical impacts on SMEs sustainability, whereas privacy and security factor has no significant statistical on SMEs sustainability.

The study poses significant implications on managers and SME development authority to create an inductive environment for technological support for SMEs’ sustainability.

The study enhances SMEs’ performance and sustainability by upgrading their existing information and communications technology as a digital infrastructure and benefiting from novel IT-based cloud revolution. Several studies have provided an understanding of the use of cloud computing services in SMEs but lack enough information about the challenges and impact on SMEs sustainability.

The assembly simulation in tolerance analysis is one of the most important steps for the tolerance design of mechanical products. However, most assembly simulation methods are based on the rigid body assumption, and those assembly simulation methods considering deformation have a poor efficiency. This paper aims to propose a novel efficient and precise tolerance analysis method based on stable contact to improve the efficiency and reliability of assembly deformation simulation.

The proposed method comprehensively considers the initial rigid assembly state, the assembly deformation and the stability examination of assembly simulation to improve the reliability of tolerance analysis results. The assembly deformation of mating surfaces was first calculated based on the boundary element method with optimal initial assembly state, then the stability of assembly simulation results was assessed by the density-based spatial clustering of applications with noise algorithm to improve the reliability of tolerance analysis. Finally, combining the small displacement torsor theory, the tolerance scheme was statistically analyzed based on sufficient samples.

A case study of a guide rail model demonstrated the efficiency and effectiveness of the proposed method.

The present study only considered the form error when generating the skin model shape, and the waviness and the roughness of the matching surface were not considered.

To the best of the authors’ knowledge, the proposed method is original in the assembly simulation considering stable contact, which can effectively ensure the reliability of the assembly simulation while taking into account the computational efficiency.

This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants.

This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants.

One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR.

The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey’s mainly). This research will aid academics in developing and understanding the determinants of SCR.

The issue of energy efficiency is becoming increasingly prevalent globally due to factors such as the expansion of the population, economic growth and excessive consumption that is not sustainable in the long run. Additionally, healthcare facilities and hospitals are facing challenges as their operational costs continue to rise. The research aim is to develop strategic frameworks for managing green hospitals, towards energy efficiency and corporate governance in hospitals and healthcare facilities.

This research employs a qualitative case study approach, with a sample of ten hospitals examined through interviews with senior management, executives and healthcare facilities managers. Relevant data was also collected from literature and analysed through critical appraisal and content analysis. The research methodology is based on the use of grounded theory research methodologies to build theories from case studies.

The research developed three integrated conceptual strategic frameworks for managing hospitals and healthcare facilities towards energy efficiency, green hospital initiatives and corporate governance. The research also outlined the concepts of green hospitals and energy efficiency management systems and best practices based on the conclusions drawn from the investigated case studies.

The study is limited to the initiatives and experiences of the healthcare facilities studied in the Middle East and North Africa (MENA) region.

The research findings, conclusions, recommendations and proposed frameworks and concepts contribute significantly to the existing body of knowledge. This research also provides recommendations for hospital managers and policymakers on how to effectively implement and manage energy efficiency initiatives in healthcare facilities.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

This study explores how strategic human resource practices enhance the competitive capability of differentiation and cost-effectiveness by leveraging knowledge resources in Indian IT/software organizations. It examines the mediating effect of knowledge management (KM) processes in the relationship between strategic HR practices, competitive differentiation and cost-effectiveness capabilities.

An online questionnaire survey collected data from 380 knowledge workers in 25 IT/software and consultancy firms. The authors checked data reliability and validity by conducting exploratory factor analysis in SPSS and confirmatory factor analysis in AMOS. The authors evaluated hypotheses using path analysis in structural equational modeling in AMOS.

Strategic HR practices significantly and positively affect KM processes and competitive capabilities-differentiation and cost-efficiency. Both strategic HR practices and KM processes have a closer association with differentiation than cost-effectiveness. Knowledge management processes significantly and positively mediate between strategic HR practices and competitive capabilities. The mediation is more substantial in predicting differentiation than cost-effectiveness.

It is a cross-sectional study with a constrained capacity to predict accurate causal inferences; The authors call for future studies with longitudinal design and objective measures. Further studies are required to explore the impact of various strategic HR configurations on KMP to understand how different routes stimulate a particular competitive strategy. This conceptual framework can be validated across different industry types and sizes.

This study provides practical insights to HR and knowledge managers regarding devising HR and KM processes to accomplish the goals of differentiation and cost-effective, competitive strategies. This study highlights that leveraging human capital for effective KM is crucial for gaining a competitive advantage.

The paper adds to the strategic HR and KM literature by exploring the mediating role of KM processes in enabling strategic HR processes to enhance differentiation and cost-effective, competitive strategies. It provides original empirical evidence from knowledge-intensive IT/software consultancies, particularly in India's emerging economy. It indicates the current state of HR practices adopted for optimum utilization of knowledge resources and the importance of differentiation strategy for Indian knowledge-intensive IT/software firms.

Due to the limitation of experimental conditions and budget, fatigue data of mechanical components are often scarce in practical engineering, which leads to low reliability of fatigue data and reduces the accuracy of fatigue life prediction. Therefore, this study aims to expand the available fatigue data and verify its reliability, enabling the achievement of life prediction analysis at different stress levels.

First, the principle of fatigue life probability percentiles consistency and the perturbation optimization technique is used to realize the equivalent conversion of small samples fatigue life test data at different stress levels. Meanwhile, checking failure model by fitting the goodness of fit test and proposing a Monte Carlo method based on the data distribution characteristics and a numerical simulation strategy of directional sampling is used to extend equivalent data. Furthermore, the relationship between effective stress and characteristic life is analyzed using a combination of the Weibull distribution and the Stromeyer equation. An iterative sequence is established to obtain predicted life.

The TC4–DT titanium alloy is selected to assess the accuracy and reliability of the proposed method and the results show that predicted life obtained with the proposed method is within the double dispersion band, indicating high accuracy.

The purpose of this study is to provide a reference for the expansion of small sample fatigue test data, verification of data reliability and prediction of fatigue life data. In addition, the proposed method provides a theoretical basis for engineering applications.

The current study aims to examine the influence of smart mobile banking services (SMBS) on senior clients’ intention to use banking applications through the moderating role of digital accounting. For that sake, features of SMBS were adopted and included (convenience, security, trust and ease of use).

Quantitative approach was used through adopting a questionnaire as a tool of study. The questionnaire was built by researcher through the aid of previous studies; the questionnaire was distributed on a convenient sample of senior bank clients who were above 60 years old as according to UNCEF. After application process, researcher retrieved (306) properly filled questionnaires and SPSS was used to screen and analyze gathered primary data. It is worth mentioning that Cronbach’s alpha scored higher than 0.70 which guaranteed the reliability and consistency of study tool.

Results of the study indicated that SMBS influence senior clients’ intention to use these applications and this influence is moderated by ramifications of digital accounting. It appeared that features of SMBS were mainly ease of use and trust, which can effect on how senior clients are convinced to use SMBS. Digital accounting appeared in the sense of guaranteeing a high level of stability and accountability to use SMBS through security, easy access, continuous update and valid presentation of application contents. Results of hypothesis testing accepted the main hypothesis which argued that there was a statistically significant influence of SMBS on senior clients’ intention to use, with a value of (R² = 0.73, p = 0.5). Based on such results, the study recommended that bank managers should focus on providing reliability and privacy by introducing digital accounting practices in a deeper way to ensure efficiency, reliability and compatibility in the banking services provided.

Limitations of current study were presented through the application on senior clients who were above 60 years old according to UNICEF. As for the practical implications of study revealed that understanding the factors that influence senior clients’ intention to use SMBS can help banks develop strategies to improve their experience with the banking service. For example, if digital accounting is found to be a significant moderating factor, banks can invest in digital accounting solutions to provide a more user-friendly interface for senior clients. As for theoretical implications, the study can extend the technology acceptance model by examining the moderating role of digital accounting in the relationship between SMBS and senior clients’ intention to use. This can contribute to a better understanding of the factors that influence technology adoption among senior clients.

The originality of current study is that it focuses on the use of SMBS, which is a relatively new technology that has gained significant popularity in recent years due to its convenience and accessibility. Also, the study examines senior clients, who are an important demographic for the banking industry, as they represent a large portion of the population that is more likely to face challenges in adopting new technologies.

The purpose of this paper is to evaluate the reliability and signature reliability of solar panel k-out-of-n-multiplex system with the help of universal generating function.

Energy scarcity and global warming issues have become important concerns for humanity in recent decades. To solve these problems, various nations work for renewable energy sources (RESs), including sun, breeze, geothermal, wave, radioactive and biofuels. Solar energy is absorbed by solar panels, referred to as photovoltaic panels, which then transform it into electricity that can be used to power buildings or residences. Remote places can be supplied with electricity using these panels. Solar energy is often generated using a solar panel that is connected to an inverter for power supply. As a result, a converter reliability evaluation is frequently required. This paper presents a study on the reliability analysis of k-out-of-n systems with heterogeneous components. In this research, the universal generating function methodology is used to identify the reliability function and signature reliability of the solar array components. This method is commonly used to assess the tail signature and Barlow-Proschan index with independent and identically distributed components.

The Barlow-Proschan index, tail signature, signature, expected lifetime, expected cost and minimal signature of independent identically distributed are all computed.

This is the first study of solar panel k-out-of-n-multiplex systems to examine the signature reliability with the help of universal generating function techniques with various measures.