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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 technologies (WHTs) show promise in improving the health and well-being of the aging population because they promote healthy lifestyles. They can be used to collect health information from users and encourage them to be physically active. Despite potential benefits of WHTs, recent studies have shown that older people have low continued use intention toward WHTs. Previous work on this topic is disjointed, and new theoretical viewpoints are required.

The authors propose an enablers and inhibitors perspective to model factors influencing continued use intention of WHTs among the elderly. To test the model, we collected data from Chinese elderly (N = 295) who had prior experience using WHTs.

The study results show that social value is the strongest enabler of continued WHT use, and emotional and epistemic values and device quality also increase use continuance. Inertia and technology anxiety were identified as significant inhibitors. A post hoc importance performance map analysis revealed that while emotional value is a highly significant predictor of continued WHT use, existing WHTs do not stimulate such value in our sample.

The research findings illustrate the importance of incorporating user resistance in technology acceptance studies in general and WHT usage studies in particular. This study contributes by providing an integrative model of technology continued use intention for the elderly along with practical implications for policymakers.

A limited number of prior studies have taken both enablers and inhibitors into account when explaining continued WHT use intention among the elderly. This paper fills this research gap and contributes to the WHT literature by considering both enablers and inhibitors in the same model. Moreover, this study contributes to the ongoing research on WHT, and more broadly, gerontechnology use among the elderly.

The purpose of this paper is to measure the impact of open government data (OGD) on citizen empowerment.

This study advances the body of knowledge on OGD by proposing an integrated research model based on transparency, accountability, participation and collaboration dimensions. The research model was empirically tested using 275 responses using the on-paper survey from the university students and professionals in Bangladesh. Data were analyzed using the structured equation modeling technique.

Findings revealed that transparency and participation have a positive and significant direct and indirect influence on citizen empowerment through accountability and collaboration. Overall, the four basic pillars of OGD such as transparency, participation, accountability and collaboration interrelated with each other and have the impact on citizen empowerment.

This study has proposed an instrument that sums the dimensions of open government, which avoids tautology and redundancy among OGD dimensions. More research should be done to validate the proposed model and the instruments used in this study.

For the researchers, this study provides a basis for further refinement of individual models of empowerment. For practitioners, understanding the key constructs is crucial to design, refine and implement OGD systems and applications that empower citizens, create public values and strengthen the democratic process.

This research is the first step that empirically investigates the impact of OGD on citizen empowerment which is the ultimate goals of any democratic government.

In the era of m-learning environments, multiple factors have been considered to explain adult learners' continuance usage intention, but largely without considering the role of specific configurations of variables and how they may affect learners' intention. The purpose of this study is to show how cognitive need, subjective norms, perceived usefulness, satisfaction, confirmation, attitude and perceived ease of use combine to predict learners' frequent use intentions.

It is empirically validated through configurational analysis, using fuzzy-set qualitative comparative analysis (fsQCA) on 211 adult learners with experience in using Mobile learning applications (MLA).

The findings show learners' satisfaction of MLA usage combined with the cognitive need and attitude were found to be core conditions reinforcing learners' continuance intention.

This study was conducted in the context of adult learners MLA whereby the motivations for continued usage and the nature of technological innovation could differ. In this regard, findings from this study may not be generalizable to other technological contexts.

In the planning and development of learning apps, software developers should pay attention to practical functions and extend key features that are frequently required for solving a problem using the new skill. On the marketing side, MLA companies should emphasize the full functionality of their apps to cater efficiently to the different needs and expectations of the learners.

This study contributes by extending existing knowledge on how cognitive need, satisfaction and attitude combine to increase or mitigate continuance intention to use toward the development of new configurational theories. This study fills the gap in the literature by introducing adult learners' continuance intention to use MLA and introducing through a methodological approach of fsQCA in adult learners' context.

Facial recognition payment (FRP) has been attracting attention as an alternative payment mode. This research aims to investigate the future use of FRP for both mobile payment and point of sale payment.

The body of information on this topic is promoted by proposing the valence framework, where the authors used relative advantage, initial trust, perceived playfulness and need for uniqueness as positive valence, and perceived risk, technophobia and perceived complexity as negative valence. This study also investigated the moderating effect of personal innovativeness on consumers' behavioral intention to use FRP-based payments. The authors collected data from 392 FRP users from China to test the model. The authors used structural equation modeling (SEM) to evaluate the significant determinants influencing FRP use.

The authors found that relative advantage and privacy risk are the two most influential predictors of FRP use. The findings indicate that personal innovativeness acts as a moderator between negative valence and behavioral intention. This study provides valuable policy guidelines for the mobile or point of sale (POS) payment companies for adding FRP service into their default payment method.

FRP is a relatively new technology that has not received much research attention in information system (IS) literature. Most studies on payment investigated enablers, and less effort has been given to study both enablers and inhibitors together. Furthermore, the authors employed SEM-based analysis to identify the most important factors influencing consumers' future use decisions.

The purpose of this paper is to identify the key facilitators and inhibitors of fitness wearable technology (FWT) adoption and the intention to recommend this technology.

An innovative and integrated research model was developed by combining constructs from two well-established theoretical models, the extended unified theory of acceptance and use of technology (UTAUT2) and diffusion of innovation (DOI). The proposed research model was empirically validated using data collected from 392 respondents in China. The data was analyzed using the partial least squares method, a statistical analysis technique based on structural equation modeling.

The results indicate that performance expectancy, effort expectancy, social influence, habit, compatibility and innovativeness have significant direct and indirect effects on FWT adoption and the intention to recommend it. The significance of people’s intention to recommend FWT to others in social networking sites (e.g. Facebook, Weibo, and WeChat) is also confirmed.

The findings may facilitate the design and implementation of FWT products, applications and functionalities that can achieve high consumer acceptance and positive recommendations in social networks.

This study is among the first to investigate FWT adoption from behavioral, social and environmental perspectives. It also highlights the importance of social marketing campaigns and suggests directions of future wearable technology adoption research.

Food waste in the hospitality sector has emerged as a global concern. Various technology-driven online food services such as the food delivery apps (FDA) contribute to hospitality food waste. FDA users might behave irresponsibly by ordering more foods than required which may lead to food waste generation. To date, limited studies have been attempted to understand how consumers’ over-ordering behavior through FDA result in hospitality food waste.

The authors used partial least squares structural equation modeling (PLS-SEM) to analyze survey data from 248 FDA users.

The results indicated that perceived convenience and trust positively influence consumers' attitude toward FDA, which in turn promotes over-ordering behavior. Interestingly, the anticipated positive relationship between price advantage and attitude toward FDA was not supported by the data. Furthermore, the authors confirmed that over-ordering behavior contributes to food waste, an outcome that has crucial implications for both the hospitality sector and sustainability efforts.

The current study employs the stimulus-organism-behavior-consequence (SOBC) theory to investigate the catalysts and consequences of over-ordering behavior via FDA. This study thus highlights the importance of the SOBC model in understanding consumer behavior.

As businesses keep investing substantial resources in developing business analytics (BA) capabilities, it is unclear how the performance improvement transpires as BA affects performance in many different ways. This paper aims to analyze how BA capabilities affect firms’ agility through resources like information quality and innovative capacity considering industry dynamism and the resulting impact on firm performance.

This paper tested the research hypothesis using primary data collected from 192 companies operating in Bangladesh. The data were analyzed using partial least squares-based structural equation modeling.

The results indicate that BA capabilities improve business resources like information quality and innovative capacity, which, in turn, significantly impact a firm’s agility. This paper also found out that industry dynamism moderates the firms’ agility and, ultimately, firms’ performance.

The contribution of this work provides insight regarding the role of business analytics capabilities in increasing organizational agility and performance under the moderating effects of industry dynamism.

The present research is to the best of the authors’ knowledge among the first studies considering a firm’s agility to explore the impact of BA on a firm’s performance in a dynamic environment. While previous researchers discussed resources like information quality and innovative capability, current research theoretically argues that these items are a leveraging point in a BA context to increase firm agility.

The pressure to survive in a highly competitive market by using artificial intelligence (AI) has further demonstrated the need for automation in business operations during a crisis, such as COVID-19. Prior research finds managers' mixed perceptions about the use of technology in business, which underscores the need to better understand their perceptions of adopting AI for automation in business operations during COVID-19. Based on social exchange theory, the authors investigated managers' perceptions of using AI in business for effective operations during the COVID-19 pandemic.

This study collected data through a survey conducted in China (N = 429) and ran structural equation modeling to examine the proposed research model and structural relationships using Smart PLS software.

The results show that using AI in supply chain management, inventory management, business models, and budgeting are positively associated with managers' satisfaction. Further, the relationship between managers' satisfaction and effective business operations was found to be positively significant. In addition, the findings suggest that top management support and the working environment have moderating effects on the relationship between managers' satisfaction and effective business operations.

The results of this study can guide firms to adopt an AI usage policy and execution strategy, according to managers' perceptions and psychological responses to AI.

The study can be used to manage the behavior of managers within organizations. This will ultimately improve society's perception of the employment of AI in business operations.

The study's outcomes provide valuable insights into business management and information systems with AI application as a business response to any crisis in the future.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Automation of business operations can help companies overcome significant challenges like those presented by the Covid-19 global pandemic. Using artificial intelligence (AI) leads to valuable improvements to speed and efficiency in many key functions. Favorable outcomes are likelier when managers are positive towards technology and this can be helped through such as provision of top leadership support and a favorable workplace environment.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.