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The public sector use of the internet of Things (IoT) technology is an emerging field with a potential for a variety of institutional applications in the fields of information gathering and policy implementation to establish resilience for modern society. In this context, we aim to investigate the success factors which can positively influence the continuous usage intention of IoT service with the mediation effect of perceived public value.

A conceptual model based on the strong literature and theoretical background is tailored to provide factors for IoT services success in the public sector. A quantitative survey was conducted through 381 citizens using IoT services to validate the proposed conceptual model using structural equation modeling approach in order to examine the influence of identified constructs on the continuous usage intention.

The results highlighted that the proposed model successfully accounted for about 59% perceived variance in public value creation and 63% perceived variance in citizens' continuous usage intention. IoT services success is best dignified by the perceptions of citizens who use the services, therefore, this study identifies the positive role of digital society affinity in context of social sustainability and it climaxes that the real value of IoT in public sector comes from establishment of services on top of the service delivery and that's where the public value is going to be created.

The use of IoT technology in public services will fetch much benefit to the citizens as well as to the government. The study findings are significant in identifying good practices for generating public value in digital society affinity.

The integrated conceptual model explores the driving factors of citizens' inclination towards IoT technology in a social context. Through this study, we can analyze the role of perceived public value in enhancing the citizens' engagement with IoT services. The government policymakers and ICT managers take help from this study to designing IoT public services with making the government more responsive to citizens.

This study examines the role of continuous trust (i.e., a trust that develops over time as a result of continuous usage interactions) in determining customers' intention to continue using online product recommendations (OPRs).

Based on information system (IS), continuance model, and continuous trust, we propose that continuous trust will influence customers’ intention to continue OPRs’ use directly and indirectly via their satisfaction and usefulness of the OPRs. The research model is tested using data collected via an online survey from 626 existing users of OPRs in 15 different countries.

The empirical results revealed that continuous trust is shown to be a significant predictor of customers’ intention to continue OPRs use for future purchases. Additionally, the customers’ perceived confirmation and continuous trust positively influence their perceived usefulness and satisfaction with the OPRs, which subsequently influence customers’ OPRs continuous usage intention.

The saliency of continuous trust and usefulness of OPRs present e-retailers with potential fruitful areas to shape future usage of OPRs. In addition, e-retailers must understand that improving the OPR usefulness on its own may not lead to OPRs continuous usage until OPRs trustworthiness is not continually improved. OPRs itself may be convenient and useful, but trustworthy OPRs will pay stronger dividends for customer satisfaction and OPRs’ continuous usage.

The incorporation of continuous trust into the IS continuance model offers a new theoretical lens and an alternative explanation for the OPR continuous usage intention. This study stands in contrast to the large majority of research concerning initial trust and OPRs adoption, in that it focuses on continuous trust (as opposed to initial trust) and on a customers’ OPRs continuous usage intention as opposed to the initial adoption decision.

The e-health services came up as an effective tool to mitigate effects of COVID-19 and following social distance norms. This study highlighted an issue of contentious usage intentions of e-health services among Thai older citizens. This study aims to examine the relationship of social influence (SI), information quality (IQ) and the digital literacy (DL) to contentious usage intentions.

This study follows quantitative techniques, and the sample size is 140 to analyze, that is collected from the older Thai citizens. The convenient sampling technique was used to collect the data and the items were measured by using a five-point Likert scale.

The findings of this study are having mixed results. The effect of DL and satisfaction (SAT) on continuous usage intention (CUI) is significant. The effect of IQ and SI on CUI is non-significant. The effect of IQ and SI on SAT is significant. Further, the mediating effect of SAT between IQ and CUI is non-significant. However, the mediating effect of SAT between SI and CUI is significant.

This study contributes to knowledge by empirical testing of DL and usage of the medicine. Furthermore, to the best of the authors’ knowledge, this study is one of the rare studies that incorporate technological intervention for drug usage intentions.

This study aims to examine the current state of literature on structural equation modeling (SEM) studies in “cloud computing” domain with respect to study domains of research studies, theories and frameworks they use and SEM models they design.

Systematic literature review (SLR) protocol is followed. In total, 96 cloud computing studies from 2009 to June 2018 that used SEM obtained from four databases are selected, and relevant data are extracted to answer the research questions.

A trend of increasing SEM usage over years in cloud studies is observed, where technology adoption studies are found to be more common than the use studies. Articles appear under four main domains, namely, business, personal use, education and health care. Technology acceptance model (TAM) is found to be the most commonly used theory. Adoption, intention to use and actual usage are the most common selections for dependent variables in SEM models, whereas security and privacy concerns, costs, ease of use, risks and usefulness are the most common selections for causal factors.

Previous cloud computing SLR studies did not focus on statistical analysis method used in primary studies. This review will display the current state of SEM studies in cloud domain for all future academics and practical professionals.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.

By integrating stimulus-organism-response theory and uses and gratifications theory, this study explored the salient gamification factors that satisfy the gratifications of conference attendees in the context of an event gamification mobile app and their relationships with conference engagement, continuance intention and word-of-mouth.

The questionnaire was developed in Qualtrics and administered on a gamification application called Goosechase during an annual hospitality conference. The proposed hypotheses were tested using the partial least square-structural equation modeling (PLS-SEM).

The gratifications of social presence, education and entertainment through a gamification mobile app influences attendees’ engagement during the conference while achievement gratification does not. Positive effects of conference engagement on their continuous intention and WOM have been also validated.

By adopting a unique integrated approach that utilizes UGT and S-O-R framework, while considering conference engagement as work-related engagement, this study offers a fresh perspective on gamification apps and discusses its theoretical and practical implications in depth.

A lack of reliable and effective communication tools poses major barriers impeding the performance of construction projects consisting of diverse participants. Although some construction project teams (CPTs) begin to apply social media (SM) as an available approach for project management the entire mechanism of SM adoption in this specific context remains understudied. Therefore, this study aims to adopt a CPT's lens to investigate the critical antecedents and associated effects underlying SM adoption in the construction industry.

Based on the technology–organization–environment (TOE) theory, a conceptual model was proposed and tested by empirical data collected from 159 CPTs in China. Structural equation modeling technique was employed for data analysis.

The results demonstrate that all the five extracted TOE-based antecedents including two technological factors (i.e. compatibility and expected cost), one organizational factor (i.e. top management support) and two environmental factors (i.e. project partner collaboration and project fit) are crucial to the adoption of SM in CPTs. Besides, SM acceptance is found to mediate the relationships between organizational and environmental factors and SM use. Moreover, SM use significantly predicts the communication effectiveness of CPTs.

A questionnaire study based on cross-sectional data from China may only unveil the logic of SM adoption in the context of Chinese construction industry within a shorter time interval. It is recommended that future research could develop longitudinal studies among various construction practitioners in different countries to further specify and generalize the current findings.

This paper provides a comprehensive understanding of SM adoption in the construction industry by exploring the preadoption antecedents and postadoption effects from the perspective of project teams. The empirical findings advance the current web-based project management literature and afford new insights for construction practitioners into better managing SM application to reap its full capabilities in projects.

The present study aims to probe into the determinants of mobile wallet adoption by millennials with the assistance of extended technology acceptance model.

The data was collected from the students studying professional courses in leading private universities in the north region of India. Keeping in view of the objective and hypotheses, the Partial Least Square Structural Equation Modeling (PLS -SEM) technique was used to test the proposed model.

The tested model brings into notice the imperative observation, which clearly outlines that there are all significant relationships, which can be observed herein. To explicitly state: perceived ease of use (PEOU) has a significant positive relationship with the perceived usefulness followed by PEOU also shares a significant positive relationship with the behavioral intention, and lastly trust as a variable under study establishes a significant positive relationship with actual use (AU).

Implications for the banking industry are to ensure the safety and privacy (financial information) confidential.

The present study contributes to the literature of mobile wallet in the developing nations.

The purpose of this paper is to investigate the online learning experience (LE) of massive open online courses (MOOCs) among the students in India using the lens of community of inquiry (CoI) model and two additional contextual factors.

The study conducted a survey using a structured questionnaire among the undergraduate and postgraduate students to examine the LE of MOOCs using the CoI framework and contextual variables – technical barrier (TB) and hedonic motivation (HD). The primary data were analyzed with the partial least squares structural equation modeling technique.

The results show that teaching presence (TP) influences cognitive presence (CP) and social presence (SP). SP influences CP. It is also found that TP, SP and CP influence the LE of MOOCs. It is found that TB negatively influences LE but is not significant and HD significantly influences LE positively for MOOCs.

This study has a few limitations as it is a cross-sectional study in India, which surveyed undergraduate and postgraduate MOOCs learners, and caution needs to be taken while generalizing the outcomes. Further studies can be conducted across other countries considering demographic factors like age, gender, income groups, education and profession.

This research highlights the antecedents influencing the LE of MOOC learners using the CoI framework which will help the MOOC designers and marketers to apprehend the factors influencing LE. The results of this research will help them formulate suitable strategies in the design and delivery of MOOCs to improve the LE of learners.

This unique research investigates and empirically validates the CoI framework to understand LE of MOOC learners in India. This research extends the CoI framework by adding contextual factors – TB and HD in the context of a developing country.

Drawing on dual process theory as the overarching framework, this study investigates how different types of incidental vocabulary learning yield different performance, repetition, and continuance intention outcomes and uncovers the underlying mechanism.

We identify four popular types of incidental learning: traditional, a murder mystery game, noneducational live streaming, and VTuber. We propose that the underlying mechanism is the mediating role of perceived novelty as heuristic processing, and effort and performance expectancy as systematic processing. We conduct a between-subject experiment with four groups for the four types of incidental learning. From a total of 220 subjects, 55 valid responses were collected from each group. Analysis of variance and a partial least squares structural equation model are employed to examine the differences and mechanism.

The results show that noneducational live streaming performs significantly best for all three outcomes. The mechanism test demonstrates that perceived novelty and performance expectancy play significantly positive mediating roles, whereas effort expectancy has a null mediating effect.

The research provides both theoretical and practical implications.