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Open government data (OGD) is a comparatively new field in e-government and the factors influencing its continuance use by citizens have not been extensively explored. A better understanding of these factors can help the government to articulate strategies and policies that can advance the acceptance and use of OGD technologies. Thus, this paper aims to empirically determine the predictors influencing the continuance usage intention of OGD technologies.

Following an empirical investigation among 370 respondents in Bangladesh, a developing country, the paper applied path analysis using the structural equation modeling approach. The unified theory of acceptance and use of the technology model is integrated with the information system continuance model to investigate the continuance usage intention of OGD technologies.

The outcomes of this study reveal that performance expectancy, effort expectancy, social influence and facilitating conditions (FC) directly affect users’ satisfaction (SAT). In addition, SAT and FC were found statistically significant toward continuance usage intention of OGD technologies.

The findings of this study suggest policymaker and OGD providers to formulate or modify their strategies to retain the existing OGD users and stimulate persistence usage.

Facilitating long-term use by citizens would increase their engagement and they might derive value from the OGD platforms. Concurrently, the government’s objective of ensuring increased future use of OGD technologies would be better realized.

The novelty of this study lies in the fact that it addresses a previously overlooked area of open data research, namely, the acceptance and use of open data technologies and ways to stimulate it. This study has contributed to the existing but limited literature on continuance usage intention of OGD technologies in the context of a developing country.

Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

This study aims to underline the possible influence of the moderator, information systems (IS) infusion, on Open Government Data (OGD) adoption and usage.

Using the partial least squares-structural equation modeling methodological approach, the adapted unified theory of acceptance and use of technology (UTAUT) model has been used for understanding the role of the moderating variable, namely, IS infusion.

Findings show that the moderating impact of IS infusion is positively significant with respect to the performance expectancy–behavioral intention relationship thereby bolstering the impact on users’ perception of OGD vis-à-vis work/academics performance and negatively significant for social influence–behavioral intention, information quality–behavioral intention, thereby clinching the fact that with the increased engagement and involvement of OGD in the everyday life of the user, the role of significant others and information quality gets least significant.

Extant OGD-focused research has underscored the impact of different variables as far as OGD adoption and usage is concerned; the present study seeks to add on to the extant literature by understanding the implications of IS infusion on the adapted UTAUT model constructs and behavioral intention relationships.

Malnutrition is one of the serious public health problems especially for children and pregnant women in developing countries such as Bangladesh. This study aims to identify the risk factors associated with child nutrition for both male and female children in Bangladesh.

This study was conducted among 23,099 mothers or caretakers of children under five years of age from a nationally representative survey named Bangladesh Multiple Indicator Cluster Survey, 2019. This study used chi-square test statistic for bivariate analysis and multinomial logistic regression was used to evaluate the adjusted effects of those covariates on child nutritional status.

The prevalence of severely malnourished, nourishment was higher for males than females (5.3% vs 5.1%, 77.4% vs 76.8%) while moderately malnourished were higher for females (18.1% vs 17.4%). The findings from the multinomial model insinuated that the mother’s education level, wealth index, region, early child development, mother’s functional difficulties, child disability, reading children's books and diarrhea had a highly significant effect on moderate and severe malnutrition for male children. For the female children model, factors such as mother’s education level, wealth index, fever, child disability, rural, diarrhea, early child development and reading less than three books were significant for moderate and severe malnutrition.

There is a solution to any kind of problem and malnutrition is not an exceptional health problem. So, to overcome this problem, policymakers should take effective measures to improve maternal education level, wealth status, child health.

Open government data (OGD) are considered as a technology capable of promoting transparency openness, and accountability, which in turn has a positive impact on innovation activities and creates responsive government, collaboration, cooperation, co-creation and participation. The purpose of this paper is to explore the adoption of OGD and open data portals among students, in an attempt to discover how governments can improve their actions in this respect.

This study develops a behavioural intention-based analysis using constructs from the Unified Theory of Acceptance and Use of Technology, which is supplemented with additional constructs that meet the purpose of the study. In total, ten constructs divided into 33 items constituted the input for our study. Input data for the developed model have been collected through a structured questionnaire distributed between bachelor's and master's level students in three countries – the Czech Republic, India and Latvia. A structural equation modelling technique was used to analyse the relationships between variables of the model and test the nine hypothesis defined.

Six constructs have been identified to facilitate significant relationships with behavioural intention. The analysis of the results of the three countries allows us to draw more objective conclusions in respect to the aim of the study and to reveal country-specific aspects that need to be addressed in the future.

This study adds to the existing literature few theoretical and practical aspects. It highlights the role of open data portals as a central point of OGD infrastructures. It enables governments to understand the relationships among the related constructs, improving their actions and modifying their data infrastructures accordingly.

The purpose of this study is to investigate the factors, which drive teenagers’ behavioural intention to adopt wearable technologies and their behavioural intention to recommend others.

This study proposes a new adoption model combining two different models including the extended unified theory of acceptance and use of technology and the theory of planned behaviour, which provided relevant contributions for understanding the adoption of wearable technologies. A structural equation modelling approach using analysis of a moment structures 23 software was used to analyse the data collected from 318 respondents.

Findings of this study reveals that performance expectancy (β = 0.28; t = 2.049), facilitating conditions (β = 0.28; t = 1.989), social influence (β = 0.23; t = 3.150) and attitude (β = 0.18; t = 3.246) have a statistically significant impact on behavioural intention. Additionally, behavioural intention (β = 0.15; t = 2.543) and attitude (β = 0.15; t = 3.261) have a statistically significant impact on intention to recommend others. However, effort expectancy, price value, hedonic motivation and habit did not have a significant influence on behavioural intention.

In this study, the understanding of the determinants contributing to teenagers’ behavioural intention to use wearable technologies and driving their intention to recommend others to adopt these devices will provide insights to practitioners and decision makers to customize the features of wearable devices to promote sustainable use of these technologies.

This study is among the first to investigate wearable technologies from behavioural perspectives especially on teenagers in Bangladesh. Hence, the findings of this study will help to comprehensively explain teenagers’ behavioural intention to adopt wearable technologies and their intention to recommend others.

The purpose of this study was to investigate the factors that would influence the intention to use social banking during the coronavirus disease 2019 (COVID-19) pandemic. This study integrated two theories, namely the integrated technology acceptance model (TAM), which focused on the acceptance of technology by consumers, and electronic word of mouth (eWOM), which focused on consumer behavior. This study also applied the significant variables in the context of Thailand, which were trust and perceived risk.

A quantitative research method was applied by collecting data from 411 consumers during the COVID-19 pandemic in Thailand. A combined multi-analytic approach of a structural equation model (SEM)-neural network was used to analyze the data. In the first step, the SEM was used to determine the important factors that affected the adoption of social banking. In the second step, a neural network model was used to prioritize the important factors to confirm the results of the SEM method in step 1.

The empirical results of the data analysis using the SEM method showed that the perceived ease of use, perceived usefulness and trust were the most significant determinants of adopting social banking. This was consistent with the neural network method of the important factors.

The results of this research could initiate issues that should be developed for the continued use of online banking among consumers in the context of developing countries, such as Thailand.

This research model provided guidelines for the effective development of mobile banking applications for use on mobile devices. The results of this research made strong theoretical contributions to the existing literature on online banking and offered procedures and information to the relevant sectors.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-10-2022-0709

The purpose of the study is to understand the moderating impact of perceived technological innovativeness (PTI) in terms of gender differences as far as adoption and usage of Open Government Data (OGD) is concerned.

Partial least squares-structural equation modelling (PLS-SEM) methodological approach is used wherein the adapted unified theory of acceptance and use of technology (UTAUT) model is being used for estimating the research model.

PTI has been attested to have moderating impact on the UTAUT-BI relationships in select cases (SI, SQ, IQ, TR-BI). Furthermore, gender differences were observed as far as far as the PTI's moderating role on UTAUT-BI relationships were concerned.

While there has been ample impetus upon the OGD adoption and usage propensities underscoring the role of different variables, the present study's contribution lies in terms of understanding the moderating role of PTI as far as individual-centric analysis is concerned.

With the continuous development of the global COVID-19 epidemic, mobile learning has become one of the most significant learning approaches. The mobile learning resource is the basis of mobile learning; it may directly affect the effectiveness of mobile learning. However, the current learning resources cannot meet users' needs. This study aims to analyze the influencing factors of accepting open data as learning resources among users.

Based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), this study proposed a comprehensive theoretical research model. Data were obtained from 398 postgraduates from several universities in central China. Confirmatory factor analysis was used to determine the reliability and validity of the measurement model. Data has been analyzed using SPSS and AMOS software.

The results suggested that perceived usefulness, performance expectancy, social influence and facilitating conditions have a positive influence on accepting open data as learning resources. Perceived ease of use was not found significant. Moreover, it was further shown in the study that behavioural intention significantly influenced the acceptance of open data as learning resources.

There is a lack of research on open data as learning resources in developing countries, especially in China. This study addresses the gap and helps us understand the acceptance of open data as learning resources in higher education. This study also pays attention to postgraduates' choice of learning resources, which has been little noticed before. Additionally, this study offers opportunities for further studies on the continuous usage of open data in higher education.

The purpose of this paper is to develop a prototype of Online Food Delivery Application that addresses the actual needs of the user and to study the factors affecting the acceptance of Food Friend Application (FFA).

This is an applied research study using design thinking to study the real needs of consumers when ordering food online during the COVID-19 outbreak. The real needs of customers were used to create FFA. Then, the key predictors of FFA adoption were studied by integrating psychological variables, including Alertness to distinction, Openness to novelty, Orientation in the present; and Technological variables Design, Information Quality and Mobility, with comprehensive data analysis. Initially, Structural Equation Modeling was used to study the statistical relationships toward FFA acceptance, while a neural network model was used to validate the first step analysis.

Analysis results from both methods confirmed that Alertness to distinction, Orientation in the present, Mobility and Openness to novelty affected FFA at statistically significant levels. Surprisingly, technological variables in terms of Design and Information Quality had no statistical relationship toward FFA.

In addition to dealing with digital disrupts, the current business world also needs to deal with the pandemic and the rapidly changing consumer behavior. COVID-19 is a clear catalyst for digital business trends, for example, food delivery that has to deal with dramatic changes in consumer behavior. The strong methodological results of this research are greatly beneficial to academics, food online delivery service providers, application developers and government agencies.