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Even though the end-user satisfaction construct has gained prominence as a surrogate measure of information systems performance assessment, it has received scant formal treatment and empirical examination in the data analytics systems field. In this respect, this study aims to examine the vital role of user satisfaction as a proxy measure of data analytics system performance in the financial engineering context.

This study empirically validated the proposed model using primary quantitative data obtained from financial managers, engineers and analysts who are working at Jordanian financial institutions. The quantitative data were tested using partial least squares-based structural equation modeling.

The quantitative data analysis results identified that technology quality, information quality, knowledge quality and decision quality are key factors that enhance user satisfaction in a data analytics environment with an explained variance of around 69%.

This empirical research has contributed to the discourse regarding the pivotal role of user satisfaction in data analytics performance in the financial engineering context of developing countries such as Jordan, which lays a firm foundation for future research.

This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.

The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.

The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.

The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.

This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.

This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.

Advances in autonomous technology have transformed customer experience. Most prior research has investigated the effect of augmented reality (AR) on purchase intention, yet few research has discussed the effect of semiautonomous AR in the context of service use. Semiautonomous AR recognizes content in the present reality, inserts and adjusts virtual content, supervises the users and enables them to feel in control of the virtual content overlaid in observed reality resulting in enriched user experience and thereby augmentation experience. This research demonstrates how perceived control of virtual content leads to higher perceived augmentation experiences among semiautonomous AR users than among non-AR users. In addition, this research examines the mediation effects of enriched user experience and perceived augmentation experience on user satisfaction and users’ willingness to continue using AR. Results also indicate that AR users perceive a higher augmentation experience than non-AR users. However, users’ willingness to continue using AR is not significantly different between AR and non-AR users.

This study derives six hypotheses and uses a preliminary study, a field study and a lab study to evaluate the hypotheses. A field study was conducted in a car dealership to test the hypotheses, and a lab experiment was conducted in a controlled setting to corroborate the results obtained in the field study and test the underlying causal effects.

Semiautonomous AR can constantly sense, plan and not necessarily always act over the virtual content to sustain the interaction with its users. Perceived control of virtual content enhances perceived augmentation experience, and its effect of perceived control of virtual content on perceived augmentation experience is higher among semiautonomous AR users than among non-AR users. Perceived control of virtual content is a key to enriched user experience, augmentation experience and thereby users’ attitude and behavior. In addition, results showed that enriched user experience mediates the effect of perceived control of virtual content on perceived augmentation. User satisfaction mediates the effect of perceived augmentation experience on users’ willingness to continue using AR. The theoretical and practical contributions are comprehensively discussed.

Some limitations of the studies are ascertained. First, a larger sample size might be required to achieve generalizability and a strong test of the applied theory. Second, new field studies can reflect customers’ real attitudes and behaviors so as to reveal realistic interactions between the device properties and the human will in solving actual problems. The user is interested in participating in the solution within the sensing-planning-acting process as depicted by this research. Third, new research to test AR’s capabilities in bounded and symbiotic conditions can illustrate the level of autonomy each type requires, providing additional insights into why supervised AR autonomy best reflects semiautonomous AR. The pioneering structural model offered in this study (perceived control of virtual content-perceived augmentation experience-users’ satisfaction-users’ willingness to continue using AR) should be tested with new samples in other industries, aside from including other variables that may enrich the model and increase its explanatory power. In addition, future research might use other AR devices such as smart glasses to explore the effects of AR on perceived control of virtual content, enriched user experience and perceived augmentation experience. Future studies can investigate the effect of auditory and visual augmentation on enriched user experience and perceived augmentation experience, and involve features of artificial intelligence (AI) to assist users in decision-making. Regarding context, this research showed that age and gender differences did not affect the results. Nonetheless, age and gender, and perhaps additional demographic characteristics, may concern future studies.

Some recommendations for technology developers are derived from this research. AR is revolutionizing service experience. As technologies are becoming autonomous, developers seek ways to design experiences to enhance consumers’ sense of control over their interaction with such systems. Companies cannot create customer experience (Becker and Jaakkola, 2020), yet they can leverage the level of autonomy in AR to sustain ongoing interaction with customers. It is vital to design an autonomous AR that focuses on users’ needs, desires and well-being (de Bellis and Johar, 2020) that drive novel experiences (Novak and Hoffman, 2019). This study recommends AR developers design autonomous features in AR that enable customers to interact with the virtual contents generated by AR and extend their own capabilities to perform a task and feel expanded. While designing a fully autonomous system may hinder users to feel in control of their choice (Schmitt, 2019), service companies can develop an AR system that sustains an interaction, involves the user in value co-creation and guides the user (Alimamy and Gnoth, 2022). AR can sustain an interaction with the users by continuously scanning the objects in the reality and providing sensory feedback such as product size recommendations (e.g. eyeglasses) that facilitate customers’ information processing (Poushneh, 2021b; Heller et al., 2019). To achieve this, developers may focus on technology qualities such as “image recognition,” a subset of AI. With image recognition, AR can effectively provide instruction as if the customer is in a real setting. The proper incorporation of image recognition in the design of AR while enabling users to interact with 3D virtual images sustains their interaction with AR and makes them feel in control of their interaction with AR. Service companies need to ensure users feel in control of their interaction and expand their capacities to engage in the service experience with AR to accomplish their desired tasks. AR’s capacities enable users to expand their abilities to fix their basic service problems without referring to or speaking to a service provider agent in a service context. Therefore, instead of taking their car back to the dealership, customers can use AR mobile applications or glasses provided by car manufacturers to learn and fix basic vehicle problems.

This research advances the marketing literature on how users feel in control of virtual content when they interact with a semiautonomous AR that subsequently influences enriched user experience, perceived augmentation experience, attitudes and behavior.

This study aims to investigate the factors that influence the continuance intention to use personal cloud storage services among Generation Y.

A quantitative online survey was carried out to collect data from 271 respondents. Structural equation modelling with SmartPLS 4.0 software was used to run the analysis and examine the hypothesized relationships in the research model.

The study revealed that both satisfaction and habit exert a significant influence on continuance intention, whereas self-efficacy does not demonstrate a significant effect. In addition, satisfaction was found to be influenced by confirmation, perceived usefulness and perceived security. Furthermore, confirmation and cloud storage service quality were found to impact perceived usefulness, while confirmation also had an effect on perceived security. However, the hypothesized moderating role of perceived privacy risk in the relationship between perceived usefulness, perceived security and satisfaction was not supported.

This study advances the field by adapting an expanded expectation-confirmation model that delineates the nuanced impacts of habit, user satisfaction and self-efficacy on Generation Y’s continuance intention to use personal cloud storage services. It challenges the conventional wisdom regarding self-efficacy’s influence on technology adoption, offering a more intricate portrayal of its role. This research contributes a distinctive theoretical perspective, emphasizing the complex interplay of factors that inform sustained user engagement with cloud technologies.

Using surveys of Amazon and Tmall Global users, this paper aims to empirically investigate the issue of platform technological selection. We explore the impact of switching costs on users’ intentions to use an app-enabled cross-border e-commerce (CBEC) platform based on an extended technology acceptance model (TAM). The results suggest that the higher the switching cost of a platform is, the greater the users’ satisfaction and intention to use this platform. Therefore, for the platform, a moderate switching cost will be beneficial for retaining users.

Based on the TAM, this paper takes the switching costs as the starting point and focuses on exploring the relationships among switching costs, perceived usefulness, perceived ease of use, perceived reliability, satisfaction and intention to use. Online surveys of users of Amazon and Tmall Global are adopted as the main instruments of this research. We collected a total of 408 valid responses from Amazon users and 490 from Tmall Global users. For the data analysis, this study conducts frequency analysis, a test analysis of the reliability and validity of the measures, correlation analysis, and path analysis using a structural equation model.

The results show that switching costs positively affect the users’ satisfaction and intentions to use a CBEC platform through perceived usefulness, perceived ease of use and perceived reliability.

The questionnaire respondents were predominantly Chinese due to the constraints of the survey conditions. In fact, China has a high penetration rate in CBEC, and Chinese users have rich experience using the Amazon and Tmall Global platforms.

The development of CBEC has ups and downs, and users frequently switch platforms. Considering how platforms can stand out from the crowd and retain users, we believe that a moderate increase in the switching cost of the platform is helpful for companies to address these problems, and the implications of the results are particularly valid for decision-makers of CBEC platforms and companies.

Amazon and Tmall Global are the two largest CBEC platforms in the world. Using these two companies as examples for comparison can effectively identify the differences between the platforms and the conclusions are representative. We suggest that platforms can improve user satisfaction and willingness to use by establishing VIP communities, issuing coupons, providing shipping services as well as convenient after-sale complaint channels, and improving the platform’s easy-to-use interface, as ways to further enable the platform to retain more users and stand out in fierce competition.

This paper addresses an interesting and practical issue related to the effects of introducing switching costs in an extended TAM applied to CBEC platforms.

The purpose of this study is to add to the currently limited research on individual level people analytics (PA) adoption by focusing on a vital resource in the implementation of PA, namely the technology used for PA. We draw on the unified theory of acceptance and use of technology (UTAUT) to examine antecedents of the use of technology for PA.

This study uses latent profile analysis to examine how different antecedents of PA (technology) adoption jointly act among 279 users of a specific PA technology.

This study identifies four user profiles, that we labeled the skeptic diplomats, the optimistic strugglers, the optimists, and the enthusiasts. These profiles relate to differences in user satisfaction and the frequency and versatility of PA technology use. This study demonstrates that performance benefits, social influence, required effort, and facilitating conditions jointly affect the use of PA technology, but that the latter two might be the most influential factors.

This study offers recommendations to practitioners and organizations on which actions by managers and the organization can be taken to support the use of PA technology.

Compared to previous research, we take a different approach by applying latent profile analysis to examine the combined effect of antecedents on user behavior and user satisfaction. In addition to a different analytical approach, we also extend existing research on individual PA adoption by focusing on actual behaviors and behavioral intention.

The purpose of this paper is to examine the mediating role of e-trust and e-satisfaction in the relationship between e-service quality and e-loyalty in the context of e-government services.

The data were collected via an online questionnaire of Jordanian citizens. The structural equation model based on partial least squares was used to test hypotheses.

The findings showed that e-service quality has a positive and significant effect on e-loyalty. E-service quality has a positive and significant effect on both e-trust and e-satisfaction. E-trust and e-satisfaction have a positive and significant effect on e-loyalty. E-trust has a positive effect on e-satisfaction. Finally, regarding the mediating effect of e-trust and e-satisfaction, e-trust and e-satisfaction partially mediate the relationship between e-service quality and e-loyalty in the context of e-government services, and hence all hypotheses were accepted.

The results of this research aid governmental policymakers in implementing information and communication technology strategies that streamline citizens’ transactions and promote their active engagement in e-government initiatives. Additionally, the government has suggested improving awareness campaigns and providing training for employees to enhance the quality of e-services provided to citizens.

Given the growing emphasis on environmental consciousness and sustainability as core principles within most companies, product-service systems are recognized as strategic approaches to achieving sustainability objectives. Consequently, understanding consumer acceptance of these systems is of paramount importance. This study seeks to explore users' perspectives on the barriers that impede the adoption of product-service systems, intending to prioritize these obstacles.

This study utilizes a social media-based approach, specifically analyzing tweets related to Zipcar, an American car rental company that exemplifies a usage-oriented product-service system. The analysis identifies the factors influencing the acceptance of this system. The study utilizes topic modeling and sentiment analysis techniques to analyze the tweets. The opportunity value of each topic is determined, aiding in the identification of topics that require improvement. Furthermore, the interrelation between topics is explored, followed by correlation analysis to assess their significance.

Eight topics strongly related to the keywords are identified. Among them, “responsiveness”, “responsibility”, and “trust” hold the highest opportunity values. The findings emphasize the importance of service providers proactively addressing the obstacles that impede consumers' willingness to adopt product-service systems. Prioritization should be given to topics with higher opportunity values.

This research uncovers the primary obstacles to adopting the product-service system by directly considering consumer opinions and providing a prioritized list of these obstacles.

For undergraduate and graduate students in universities, social media are playing an important role in their study/research because a large amount of academic information has been accumulated on social media. Indeed, social media are complementing university libraries. Given that intelligent recommender systems have been widely implemented on social media, this paper aims to examine the adoption mechanism of intelligently recommended information by university students in their study/research.

Building upon the updated information system success model and herding theory, this study developed a research model to examine the determinants of recommended information adoption in mobile applications for social media. Data were collected through an online questionnaire and analyzed with partial least squares structural equation modelling.

The results suggest that herding belief is a valid second-order construct, comprising two first-order dimensions of imitating others and discounting their own information. Information quality, system quality and service quality directly impact satisfaction with the intelligent recommender system. Furthermore, satisfaction with the intelligent recommender system and herding belief directly impact recommended information adoption by university students in their study/research.

This study draws on the updated information system success model and incorporates herding belief as an extended component to investigate recommended information adoption, providing a new lens for understanding recommended information adoption by university students in their study/research.

The synchronous interactivity in the metaverse afforded copresence, the feeling of being together with other users. Applying the flow theory, this study examines how copresence improves the subjective well-being of users through flow and escapism.

An online self-administered survey of 212 US adults who are currently using metaverse platforms is conducted. The collected data are analyzed by SPSS 27.0 for descriptive statistics and reliability analysis. AMOS 27.0 is employed for the confirmatory factor analysis. The bootstrapping analysis via the PROCESS Macro is used to analyze the mediating and moderating effects.

The results find that copresence, flow, and escapism improve the subjective well-being of metaverse users. A serial mediation analysis reveals that the influence of copresence on subjective well-being is mediated by flow and escapism. Additionally, the impact of escapism on subjective well-being is moderated by self-expansion.

The findings contribute to the metaverse literature and the industry by highlighting the role of copresence in improving user experience and subjective well-being.