User Intention Research Articles

Analisis Penerimaan Aplikasi Naskah Dinas Elektronik (Nadine) Di Biro Umum Sekretariat Jenderal Kementerian Keuangan Menggunakan Technology Acceptance Model (TAM)

One of the impacts of the rapid development of information and technology (IT) in the archives sector is the presence of an electronic records management system (ERMS). Many ERMS has been developed, but not all of them have been successfully implemented. One important factor in its implementation is user acceptance. User acceptance influences user intentions when using an ERMS application. One of the ERMS is the Naskah Dinas Elektronik (Nadine) application atthe Ministry of Finance, which was implemented five years ago but has not yet been tested for user acceptance. This research was conducted to analyze the factors involved in accepting Nadine's application at the General Bureau as Centre Archives of the Ministry of Finance through the technology acceptance model (TAM). The research method used was quantitativedescriptive, with questionnaires distributed to 72 respondents using the Nadine application at the General Bureau. The data obtained was processed using a non-parametric statistical method, namelypartial least squares structural equation modelling (PLS-SEM). The research results show that system quality factors, user training factors, and facility conditions significantly influence user intentions when using the Nadine application. Perceived ease of use and perceived usefulness show a positive correlation with intention to use. Perceived usefulness has a significant direct influence on intention to use, while perceived ease of use has an indirect influence on intention to use through perceived usefulness. The implications of this research provide suggestions for policymakers to improve the quality of implementation of the Nadine application by improving system quality, providing training programs, and providing adequate facilities. This research can also be used to explore factors that influence users' intentions to accept ERMS, especially perceived usefulness and perceived ease of use.

The prospective relationship between a-priori intentions for and patterns of e-cigarette use among adults who smoke cigarettes

BackgroundElectronic (e-)cigarettes may help adult cigarette smokers achieve cigarette cessation, depending on patterns of e-cigarette use. Among cigarette smokers who do not use e-cigarettes, it is unclear if and how a-priori intentions for use are related to uptake patterns. Longitudinal studies have focused on established e-cigarette users or adolescent and young adult populations exclusively. MethodsWithin a nationwide randomized clinical trial (N = 638), adult cigarette smokers not currently using e-cigarettes were randomized (2:1) to receive (or not) one-month sampling of e-cigarettes. An exploratory factor analysis (EFA) was performed on an established 15-item measure assessing a-priori intentions for e-cigarette use to identify latent variables. Among those receiving e-cigarette products, regression models examined relationships between intentions and: 1) uptake (yes/no), 2) frequency (number of days per week), and 3) amount (puffing episodes per day) of e-cigarette use at one-month follow-up. ResultsTwo factors emerged from the EFA: 1) cigarette-related intentions (e.g., cigarette cessation, no smell) and 2) novel appeal of e-cigarettes (e.g., flavors). Three items remained and were treated as separate intentions: “feels like cigarette smoking”, “curiosity”, and “affordability“. In the final multivariable models, “feel like cigarette smoking” predicted more frequent e-cigarette use (β = 0.187, SE = 0.086, p = 0.03); however, none of the five factors/intentions were significantly associated with uptake or amount of use. ConclusionsFor adult cigarette smokers not currently using e-cigarettes, a-priori intentions for using e-cigarettes might not be predictive of if or how these products will be used in the future, suggesting that motives may not drive use behavior.

Labeling and consumer purchases

AbstractLabeling information and its presentation are intended to guide consumers at a store toward a choice of food that is healthier than they might otherwise buy. Consumer reactions to labeling are examined in this study through the Nutri‐Score (food) label, the efficacy and utility of which is still under debate. The aim is to analyze the degree of approval of Nutri‐Score through the Technology Acceptance Model, applying structural equation modeling to data gathered from a questionnaire administered to a sample of 478 Spanish consumers. All the hypotheses of the theoretical model were validated. The results of the proposed Nutri‐Score Acceptance Model affirmed that perceived usefulness is a direct predictor of consumer attitude and purchasing behavior, when consumers are evaluating the contents of the Nutri‐Score label. In turn, perceived ease of use had an indirect influence on the two previous variables. In this study, it is confirmed that Nutri‐Score is an effective system for guiding consumer purchase decisions on packaged food. The usefulness of the label generates positive attitudes toward intention of use among consumers.

Bayesian attention‐based user behaviour modelling for click‐through rate prediction

AbstractExploiting the hierarchical dependence behind user behaviour is critical for click‐through rate (CRT) prediction in recommender systems. Existing methods apply attention mechanisms to obtain the weights of items; however, the authors argue that deterministic attention mechanisms cannot capture the hierarchical dependence between user behaviours because they treat each user behaviour as an independent individual and cannot accurately express users' flexible and changeable interests. To tackle this issue, the authors introduce the Bayesian attention to the CTR prediction model, which treats attention weights as data‐dependent local random variables and learns their distribution by approximating their posterior distribution. Specifically, the prior knowledge is constructed into the attention weight distribution, and then the posterior inference is utilised to capture the implicit and flexible user intentions. Extensive experiments on public datasets demonstrate that our algorithm outperforms state‐of‐the‐art algorithms. Empirical evidence shows that random attention weights can predict user intentions better than deterministic ones.

Fast constrained optimization for cloth simulation parameters from static drapes

AbstractWe present a cloth simulation parameter estimation method that integrates the flexibility of global optimization with the speed of neural networks. While global optimization allows for varied designs in objective functions and specifying the range of optimization variables, it requires thousands of objective function evaluations. Each evaluation, which involves a cloth simulation, is computationally demanding and impractical time‐wise. On the other hand, neural network learning methods offer quick estimation results but face challenges such as the need for data collection, re‐training when input data formats change, and difficulties in setting constraints on variable ranges. Our proposed method addresses these issues by replacing the simulation process, typically necessary for objective function evaluations in global optimization, with a neural network for inference. We demonstrate that, once an estimation model is trained, optimization for various objective functions becomes straightforward. Moreover, we illustrate that it is possible to achieve optimization results that reflect the intentions of expert users through visualization of a wide optimization space and the use of range constraints.

Investigating users' discontinuous usage intention toward social networking sites: the roles of motivation and affectivity

PurposeThis study is based on the regulatory focus theory and conservation of resources theory to examine how information confusion leads to users’ discontinuous usage intention of social networking sites (SNSs), with the mediating mechanisms of users’ motivation and affectivity.Design/methodology/approachData were obtained from 270 users in different SNSs in Vietnam. Structural equation modeling was used to analyze the sample data and test the hypotheses.FindingsResults show that information confusion has a positive influence on discontinuous usage intention, and prevention focus positively mediates this relationship. Furthermore, the negative affectivity positively mediates the link between information confusion and discontinuous usage intention and that between prevention focus and discontinuous usage intention. In addition, prevention focus and negative affectivity together play a serial mediating effect in the link between information confusion and discontinuous usage intention.Originality/valueThis study extends the regulatory focus theory and conservation of resources theory to validate a model that explains the transitional process of users’ motivation and affectivity in the link between information confusion and discontinuous usage intention of SNSs. The findings of this study provide implications for academic researchers and business managers of SNSs to understand and make better decisions to retain their users.

Consumers' intention to use online food delivery services: A meta‐analytic structural equation modeling approach

AbstractNumerous studies have investigated the variables that are associated with individuals' behavioral intention to use online food delivery (OFD) services. However, some studies have shown inconsistent findings in relationships between different variables. This study aims to examine the influential factors leading to consumers' behavioral intention to use OFD services. The meta‐analytic structural equation modeling approach was used to examine the research model, which involved reviewing and analyzing 60 studies with 61 independent samples (N = 25,390). The results revealed that convenience had a significant influence on perceived ease of use but did not directly affect perceived usefulness. Price‐saving orientation significantly influenced consumers' perceptions of ease of use and usefulness. Additionally, significant relationships were found between perceived ease of use, perceived usefulness, and perceived trust, and these factors ultimately resulted in the usage intention of OFD services. Overall, the findings theoretically contribute to the extant literature on OFD services and can help companies develop better OFD services to ensure continuous usage by consumers.

A decision model for OTT service users to adopt wireless D2D caching networks: Exploring the Korean case

As many Over-The-Top (OTT) users opt for mobile devices, mobile network traffic surges. However, current mobile communication technology faces difficulties. To provide a stable video content consumption experience to users, reliable alternatives must be found to resolve the limitation of the conventional approach. Accordingly, wireless Device-to-Device (D2D) caching networks have gained attention as a reliable alternative. Considering it can reduce network-related overheads, save related costs, and improve OTT video consumption environment, there is a high possibility that telecommunication operators want to commercialize this technology. To commercialize wireless D2D caching networks, users need to share their resources, such as personal information, smartphone storage, and battery. This study explores the decision-making process of mobile OTT users regarding D2D caching adoption on their mobile devices in Korea. An online survey of 94 respondents was conducted in South Korea. By using the analytic hierarchy process (AHP) approach, this study devised an evaluation model that includes three major factors: perceived benefits, perceived costs, and perceived situational conditions. The results reveal that risks, rather than situational factors and benefits, predominantly influence user intentions and strategies. Streaming video content via mobile data or Wi-Fi is viewed as the most feasible choice. Moreover, users show a preference for pre-downloading video content over adopting wireless D2D caching networks on their mobile devices. The findings provide a guideline for understanding the responses of mobile OTT service users and their priorities in responding to adopting wireless D2D caching networks.

Impact of Second-hand Trading Platform Benefits on Trust, Attitude, and Usage intention - A Focus on Fashion Product Transactions -

Impact of Second-hand Trading Platform Benefits on Trust, Attitude, and Usage intention - A Focus on Fashion Product Transactions -

What factors determine the intention to use and recommend public autonomous shuttles in a real-life setting?

PurposeUser acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.Design/methodology/approachGrounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).FindingsThe study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.Practical implicationsThis study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.Originality/valueWhile extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

Analysis of Using Behavior on the GoHalalGo Application: UTAUT Model Approach

The main objective of this research is to examine how performance expectations, social influences, effort expectations, and facilitating conditions impact user behavior on the GoHalalGo halal travel application in Indonesia. The research used a quantitative survey method, sampling was carried out randomly on 253 GoHalalGo users. This research uses Partial Least Squares (PLS) analysis to test the hypothesis. Findings from the SmartPLS analysis show that performance expectations, social influence and effort expectations are highly influential factors on behavioral intention. Facilitating condition has no significant effect on behavioral intention, however facilitating condition has a significant effect on using behavior. Furthermore, these factors have a significant influence on user intentions in using the GoHalalGo application

The Effect of SNS Beauty Information Quality on Satisfaction and Behavioral Intention

The purpose of this study is to provide basic data to understand SNS satisfaction and behavioral intentions by applying SNS beauty information quality and to seek SNS marketing strategies that can attract consumer satisfaction based on this. For the empirical survey according to the purpose of this study, a survey was conducted on adults using SNS, and the final 273 copies were used as the final analysis data. The collected data were analyzed through SPSS 22.0, and the collected data were subjected to frequency analysis, factor analysis, reliability analysis, and multiple regression analysis. As a result of the study, it was found that SNS beauty information quality affects satisfaction and behavioral intention, and specifically, information provision, usefulness, reliability, and up-to-date should be noted, and consumers are expected to have a positive effect when trendy and reliable information is useful to consumers. These findings are expected to help attract efficient customers to revitalize the beauty industry by providing important information to understand the behavior of recent SNS consumers, and in subsequent studies, various factors of SNS beauty information quality that affect the satisfaction and behavioral intentions of diversified SNS users are expected to be conducted.

A Study on the Impact of the Characteristics of the Digital Subscription Economy on Customer Experience Value, Satisfaction, and Continuous Usage Intention

A Study on the Impact of the Characteristics of the Digital Subscription Economy on Customer Experience Value, Satisfaction, and Continuous Usage Intention

Applying the Value-Based Acceptance Model (VAM) to the Effects of Perceived Benefits and Sacrifices of Airline Technology-Based Self-Service (TBSS) on Perceived Value and Continued Usage Intention

Applying the Value-Based Acceptance Model (VAM) to the Effects of Perceived Benefits and Sacrifices of Airline Technology-Based Self-Service (TBSS) on Perceived Value and Continued Usage Intention

Understanding Drivers of Food Delivery Mobile App Adoption: An Empirical Study of Usage Intentions Among Paxel Platform Consumers in Indonesia

Understanding Drivers of Food Delivery Mobile App Adoption: An Empirical Study of Usage Intentions Among Paxel Platform Consumers in Indonesia

Creating Search Engine Using Machine Learning Methods

Abstract: The vast and ever-expanding amount of information available in the WWW has led to the widespread usage of search engines for data retrieval. It can be challenging to locate information that is actually relevant and helpful, even while ordinary search engines offer users an intuitive interface for entering queries and retrieving web page links as results. To rectify that problem, which paper presents a novel search engine that work ML techniques. The target is to come up users with most relevant web sites when they query the engine. The suggested search engine improves the relevancy and accuracy of search results by utilizing machine learning algorithms. This system seeks to grasp user intent, adjust to individual preferences, and deliver contextually relevant information by going beyond the bounds of traditional search engines. By using machine learning models, the search engine may learn dynamically and enhance the standard of its results over time by continuously refining its understanding. More sophisticated and adaptable search engines are being developed as an outcome of these combination of state-of-the-art machine learning libraries, tools for processing natural language, and effective indexing systems. The target of the research is too advance information retrieval systems by providing a more advanced and user-focused method of tackling the difficulties presented by the WWW's immense scope

AI Based Multilingual College Enquiry Voice Bot Using Python

Abstract: This paper addresses the growing need for seamless cross-language communication in our global society. Leveraging AI, it offers a versatile conversational agent capable of understanding and responding to inquiries in multiple languages. Through speech recognition and advanced NLP, the system interprets user intent and retrieves relevant information from a college database. Integrated language translation services enable communication in various languages namely-Kannada, English, Tamil and Telugu enhancing accessibility. Responses are dynamically translated into the user's preferred language using text-to-speech conversion. This project demonstrates AI's potential in bridging linguistic barriers and improving access to educational resources. Future enhancements could include personalized responses and expanded language support in five South Indian languages, further enriching the user experience and solidifying the bot's role as a valuable educational tool.

Analisa Faktor Pengaruh Purchase Intention Melalui Engagement Sebagai Mediasi dan Brand Equity Sebagai Moderasi Pada Pengguna Media Sosial

This study aims to investigate the factors that influence the purchase intention of social media users. The research examines the impact of social presence, psychological distance, trust, engagement, social media marketing, electronic word of mouth (EWOM), and brand equity on purchase intention. Engagement is identified as a mediator, and brand equity as a moderator in the relationship. Data was collected from 290 reSPondents through the distribution of questionnaires and analyzed using the SmartPLS 3.0 program. The results of the data analysis indicate a positive correlation between trust, engagement, EWOM, and brand equity with purchase intention. However, there is no significant effect of social presence, psychological distance, and social media marketing. Additionally, the results showed no mediating effect of engagement, and the moderating impact of brand equity was less than 5%.

Navigating Trust in Mobile Payments: Using Necessary Condition Analysis to Identify Must-Have Factors for User Acceptance

Drawing upon the mobile technology acceptance model (MTAM), this study addresses this conspicuous gap by identifying the necessary conditions for fostering trust and usage intention of mobile payment (m-payment) gateways. Data collected from 218 users of mobile-payment from Malaysia were analyzed using partial least squares structural equation modeling (PLS-SEM) to identify the should-have factors for perceived trust and intention to use mobile payment gateways. In addition, necessary condition analyses (NCA) are utilized to identify the must-have factors for perceived trust and intention to use mobile payment gateways. Results revealed that other factors of mobile usefulness, perceived security, and user mobility explained perceived trust except for mobile ease of use. In turn, mobile usefulness, user mobility, perceived security, mobile ease of use, and perceived trust established a positive relationship with intention to use. The NCA complemented these results showing that mobile usefulness, mobile ease of use, and user mobility qualified as necessary and sufficient conditions for perceived trust with medium-sized effect and mobile usefulness is qualified as a medium-sized necessary and sufficient condition for intention to use. This is the first few article that extends earlier literature by offering arguments on the different aspects of MTAM. By using NCA, we provide theoretical and methodological evidences, we identify which are the essential ones that enhances trust and usage.

Analyzing consumer perceptions and adoption intentions of central bank digital currency: a case of the digital rupee

PurposeThis paper aims to comprehensively analyze the factors influencing the adoption intentions of the digital rupee, a digital currency, among users in India.Design/methodology/approachDrawing upon the Technology Acceptance Model (TAM), the study examines the relationships between cognitive beliefs (perceived usefulness, perceived ease of use, perceived trust, perceived self-efficacy, perceived cost and awareness), affective belief (attitude) and adoption intention of the digital rupee. The study uses a structured questionnaire to collect primary data from 1,707 respondents, which are then analyzed using structural equation modeling.FindingsThe results indicate that perceived usefulness and perceived ease of use significantly impact users' attitudes toward the digital rupee, as well as their adoption intentions. The findings further reveal that perceived trust, perceived self-efficacy, and awareness positively influence attitude and adoption intention. On the other hand, perceived cost exhibits a negative effect on attitude and adoption intention. These results provide empirical evidence on the factors that shape users' attitudes and intentions toward adopting the digital rupee.Research limitations/implicationsThe research methodology used in this study ensures rigorous data collection and analysis. The structured questionnaire enabled the collection of detailed information from a large sample of respondents, allowing for robust statistical analysis. The utilization of structural equation modeling facilitated the examination of complex relationships among variables, enhancing the reliability and validity of the findings.Practical implicationsThe study's findings offer practical guidance for policymakers, financial institutions and researchers in shaping digital currency regulatory frameworks, tailored financial services and further exploration of adoption dynamics.Social implicationsThe research has social implications by potentially influencing the way individuals and communities in India engage with digital currencies, impacting financial inclusion and digital economic participation.Originality/valueThis research contributes to the understanding of the adoption of digital currencies in India and provides valuable insights for policymakers, financial institutions and researchers in the field of digital finance and technology adoption.