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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 paper is to assess the information quality of e-government websites by university-education citizens of Bangladesh. It also investigated citizens' demographic and Internet related variables associated with perceived information quality ratings and the validity of the underlying factor structure of information quality dimensions.

An online survey was conducted to assess information quality of e-government websites among a sample of university-educated citizens in Bangladesh. Descriptive statistics were obtained to examine respondents' ratings on information quality of these websites on a five-point Likert scale. A multiple linear regression model was applied to determine the effect of demographic and Internet use variables associated with information quality ratings on e-government websites. Finally, a confirmatory factor analysis (CFA) was performed to determine the underlying factor structure of information quality dimensions.

The findings revealed that the ratings on most information quality items were close to 4.00 on a five-point scale, indicating a generally high information quality of Bangladesh e-government websites. Out of 20 information quality dimensions, value-added and authority were the two top-rated information quality dimensions while security, completeness, reliability, advertisement, relevance and ease of use were the least rated dimensions. The results of multiple regression suggested that gender, age and the device used for accessing the Internet were significantly associated with information quality of e-government websites. The CFA results indicated that information quality dimensions corroborate the factor structure of information quality dimensions used in earlier studies, although the model fit statistics were not fully validated.

The focus of this study was confined to university-educated citizens in Bangladesh. Therefore, the results of this study may not be generalized to other demographic groups in Bangladesh or elsewhere.

This paper can provide guidelines for developing high-quality, informative and citizen-centric e-government websites and suggest ways on how these websites can be evaluated for information quality.

This study is the first to examine the information quality of e-government websites from the citizens' perspective in Bangladesh. The findings of this paper can assist responsible government agencies in making the websites more informative and useful for a diverse group of users.

This study aims to provide an in-depth understanding of investors’ cognition and decision-making process with regard to internet financial products. The objective is to effectively guide users’ rational investments.

First, based on grounded theory, this study develops a tool for measuring users’ perceived value (PV) of internet financial products via in-depth interviews. Then, after comprehensively considering users’ environmental, individual and psychological characteristics, this study proposes a theoretical model of internet financial product investment decisions based on the PV of users. Finally, an empirical study is conducted on 693 valid sample data from e-commerce and online banking financial platforms.

The empirical results suggest that network externalities influence users’ financial behavior by herding (HE) (imitating others and discounting their own information) and PV. PV and HE are key factors in users’ investment decisions with regard to internet financial products. Moreover, users’ self-efficacy (SE) and platform type play moderate roles in the influence mechanism.

The research conclusions provide valuable references for designing financial products and establishing regulatory rules, which will help the internet financial industry to grow soundly and innovatively.

This study uncovers the mediating effect of HE and PV between network externalities and users’ investment intentions in the context of internet financial products. In addition, the moderating effect of users’ SE and platform types is revealed.

Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

The internet has evolved into an indispensable platform for seeking health information, particularly among transgender individuals. With an abundance of online resources available, extensive research into the credibility and reliability of this information is essential, as concerns about the quality of online resources persist. Transgender individuals are drawn to online health information due to the anonymity it offers, providing them with a sense of freedom from social isolation and the discomfort of experimenting with their transgender identity. However, it is crucial to assess the accuracy and reliability of the transgender health information available on the internet. This article aims to evaluate the quality of online transgender health resources by utilizing ten credibility indicators, along with six indicators to assess the veracity of the content.

A total of 179 online resources were meticulously reviewed after excluding any unnecessary and irrelevant ones, to ensure a comprehensive assessment.

The findings suggest that among the chosen resources, none of them meet all the criteria for maintaining high standards of accuracy and reliability in health information. In other words, none of these sources completely adhere to the established measures for ensuring that the information they provide is trustworthy and of high quality in the context of health.

The study provides valuable insights into the online realm of transgender health information, revealing both the strengths and weaknesses of the existing resources. By pinpointing areas that need enhancement and showcasing commendable practices, this research strives to promote a more knowledgeable and supportive online environment for individuals in search of transgender health information.

In this context, the aim of the present research is to examine what factors determine that consumers restrain from shopping used products through the Internet. So, this research aims to analyze what makes consumers prevent from shopping second-hand products online.

For this purpose, the authors propose and empirically test a conceptual model of the barriers towards online second-hand shopping behavior. Drawing on a sample of 405 consumers data were analyzed through structural equation modeling (SEM).

The findings reveal that contamination effects and the lack of trust towards the online store, followed by the low perceived product reliability and the poor product perceived quality prevent consumers from shopping used products online. Conversely, consumer embarrassment for shopping second-hand products and the purchase uncertainty do not influence consumers' second-hand shopping behavior.

This study contributes to the marketing literature on second-hand shopping, being an attempt to explore the factors that prevent consumers from purchasing used products through the Internet.

Quality of life is dependent on a healthy lifestyle and the self-care behavior of individuals. The study's purpose is to find out the determinants of individuals' self-care behavior. As such, self-care behavior is influenced by several factors that include individual knowledge, available information sources and their use, information-seeking related skills and cognitive state.

A quantitative research design followed using a questionnaire-based survey method. A total of 384 responses from the Pakistani public were collected using the convenience sampling technique. Structural equation modeling (SEM) was performed for examining the possible link between the variables.

Health literacy, Internet and social media use, and health information-seeking behavior had a direct/indirect positive impact on self-care behavior, but health anxiety had a negative impact. Health literacy and health information-seeking behavior positively mediated the relationship among Internet and social media use health anxiety and self-care.

Improving health literacy appears to be key to supporting better self-care, but it is an exploratory study, more research is required to confirm these findings. Policymakers, health professionals and information professionals should work together to improve health literacy and support informed self-care among the population.

Thus far, no previous study has examined the collective role of social media exposure, health anxiety, health literacy and health information-seeking behavior as predictors of self-care behavior. Although self-care behavior among the general population might be different compared to chronic patients, only few studies have examined the former as a unit of analysis.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

User behavior in online information evaluation is the result of a multitude of factors related to social, cultural, personal and psychological issues. The present study aimed to examine the effects of three important psychological variables including personality, self-efficacy and attitude on online information evaluation.

Four validated measures were administrated in person and online among 355 postgraduate students at Shahed University, Tehran, Iran. For testing the possible relationships among the variables, the reliability, normality and Pearson correlation tests were performed by using SPSS 24.0. Moreover, to test the ten hypotheses of the research, the structural equation modeling was considered using AMOS 26.0.

The findings confirmed the first five research hypotheses indicating the direct positive relationships among the four variables except for the impact of self-efficacy on attitude. The mediated effects of the variables were not supported except for the mediating role of attitude in the impact of personality on online evaluation behavior. The variable personality was found to be fundamental among the tested paths because it influenced the information evaluation behavior, both directly and indirectly.

The study showed the impacts of the three variables, which demonstrates that online information evaluation is greatly affected by psychological factors.