Understanding Of Intentions Research Articles

Survey of Technology in Network Security Situation Awareness

Network security situation awareness (NSSA) is an integral part of cybersecurity defense, and it is essential for cybersecurity managers to respond to increasingly sophisticated cyber threats. Different from traditional security measures, NSSA can identify the behavior of various activities in the network and conduct intent understanding and impact assessment from a macro perspective so as to provide reasonable decision support, predicting the development trend of network security. It is a means to analyze the network security quantitatively. Although NSSA has received extensive attention and exploration, there is a lack of comprehensive reviews of the related technologies. This paper presents a state-of-the-art study on NSSA that can help bridge the current research status and future large-scale application. First, the paper provides a concise introduction to NSSA, highlighting its development process. Then, the paper focuses on the research progress of key technologies in recent years. We further discuss the classic use cases of NSSA. Finally, the survey details various challenges and potential research directions related to NSSA.

Understanding smart education continuance intention in a delayed benefit context: An integration of sensory stimuli, UTAUT, and flow theory

Smart education is a combination of AI and education, and its benefits are delayed. Existing research lacks an understanding of smart education continuance intention in the context of this delayed benefit. Thus, this study aimed to examine users' continuance intention in a delayed benefit context by integrating sensory stimulus, the extended UTAUT, and flow theory. The study focused on a mobile-based smart education (MBSE) system (Liulishuo) and collected data on 494 MBSE users. The PLS-SEM analysis suggested that the model is largely supported. Identifying MBSE's technical attributes as sensory stimuli, the extended UTAUT as primary information processing, flow as secondary information processing, and continuance intention as a decision, this study verifies the relationships between various constructs and their influence on MBSE continuance intention. The results also indicate that a user's flow state plays a crucial role in strengthening continuance intention and realizing the delayed benefits of smart education. Thus, this study provides a deeper understanding of continuous usage mechanisms as they relate to smart education.

The Factors Affecting Purchasing Behavior toward Fashion Accessories in Online Platforms: an Integrative Research Model

The purpose of this paper is to apply the multidimensional construct of two theories- the theory of consumption value and the information success model, to assess the buying behavior of fashion accessories to enhance the understanding of consumer behavior intentions and explain the formation of the intention to buy fashion accessories in online webpages. The study utilizes a deductive quantitative approach by collating the constructs from previous literature and designing a survey. The data is analyzed by employing factor and regression analysis. The results indicated that functional value, conditional value, and emotional value positively impact purchasing behavior toward fashion accessories from digital platforms.

Factors Influencing Intention to Purchase Halal Food Products Among Iranian Muslim Consumers

The growing global demand for halal food has led more countries, including non-Muslim countries to emerge and serve this potential market. Malaysia, as a Muslim country, intends to become a significant exporter of halal food and aspires to become a hub for halal food production. Demand for halal food has also continued to have an upward trend in the Malaysian market itself. Thus, the consumption behavior of Muslim consumers needs to be studied and the influencing factors on Muslim consumers’ purchase intentions should be investigated. Therefore, the purpose of this research is to conceptually discuss potential factors (attitude, subjective norm, perceived behavioral control, knowledge, acculturation, religiosity, and trust) that influence the intention to purchase halal food among Iranian consumers in Malaysia. The data will be collected through the combination of convenience and snowball sampling by distributing self-administered questionnaires and web-based surveys to 380 Iranian respondents in Peninsular Malaysia. The proposed research model is based on the Theory of Planned Behavior (TPB) study of the relationship between intention to purchase halal food factor analysis was conducted to test the validity of the research instrument. The descriptive analysis was carried out using SPSS. Structural Equation Modelling (SEM) through AMOS 23 was used to test the hypotheses of the study as well as for assessing the fitness of the conceptual model. The results of this study have significant implications for marketing managers by being able to offer better products through a deeper understanding of consumer intent to purchase and add to the body of knowledge, which benefits academia. In addition, this study is useful for relevant policymakers to modify current strategies including developing future strategies and initiatives to increase halal purchase intention by better understanding Muslim consumers’ perception of halal food products.

Can a robot lie? Young children's understanding of intentionality beneath false statements

AbstractIncluding robots in children's lives calls for reflection on the psychological and moral aspects of such relationships, especially with respect to children's ability to differentiate intentional from unintentional false statements, that is, lies from mistakes. This ability calls for an understanding of an interlocutor's intentions. This study examined the ability of 5‐6‐year‐olds to recognize, and morally evaluate, lies and mistakes produced by a human as compared to a NAO robot, and to attribute relevant emotions to the deceived party. Irrespective of the agent, children had more difficulty in understanding mistakes than lies. In addition, they were disinclined to attribute a lie to the robot. Children's age and their understanding of intentionality were the strongest predictors of their performance on the lie‐mistake task. Children's Theory of Mind, but not their executive function skills, also correlated with their performance. Our findings suggest that, regardless of age, a robot is perceived as an intentional agent. Robot behaviour was more acceptable for children because his actions could be attributed to someone who programmed it to act in a specific way.Highlights The ability to recognize an intention to lie or not in different agents represents a significant developmental step. Children saw a human/robot making intentionally or unintentionally false statements, and understanding the mistake was more difficult than the lie. Robots may be associated with the human concept by younger children with important implications for use of cHRI in education.

Rodičovské plány a cesty k rodičovství gayů a leseb

Through a qualitative analysis of interviews with 52 men and women with non-heterosexual identities, the article deepens the understanding of parental intentions and the formation of pathways to gay and lesbian parenting in the Czech Republic. The article explains the reduced parental intentions and postponement of gay and lesbian parenting in the contexts of heteronormative, biologizing and gendered discourses of parenthood and the lack of legislative recognition of homoparental families in Czechia. The analysis also sheds light on the various choices of gay and lesbian pathways to parenthood in conditions that severely limit their parenting options.

Broad-Deep Network-Based Fuzzy Emotional Inference Model with Personal Information for Intention Understanding

A broad-deep fusion network-based fuzzy emotional inference model with personal information (BDFEI) is proposed for emotional intention understanding in human-robot interaction. It aims to understand students’ intentions in the university teaching scene. Specifically, feature extraction is carried out by convolution and maximum pooling, and then the ridge regression algorithm is used for emotional behavior recognition, which reduce the influence of the complex structure and slow network updates in deep learning. Multivariate analysis of variance is used to select the key personal information affecting the intention and obtain the coefficient of influence degree. Finally, fuzzy inference is used to understand the intention. According to the recognition results, the accuracy on FABO database of our proposal is 1.89%, 12.21% and 0.78% higher than those of the Residual Network combined with geodesic flow kernel (ResNet-101+GFK), a fuzzy deep neural network with sparse autoencoder (FDNNSA), and an affect recognition on a video-skeleton of bimodal information with a hierarchical classification fusion strategy (HCFS), respectively, indicating that our proposal can effectively capture the emotional intention of students in the teaching scene.

Insect production as a novel alternative to livestock farming: Exploring interest and willingness to adopt among German farmers

Given the challenges confronting food and feed production and the need for more sustainable agri-food systems, insect production is gaining attention as an economically feasible and environmentally beneficial alternative to livestock farming. Surprisingly, despite some examination of consumer perceptions and acceptance, little attention is given to the farmers who would be tasked with making successful use of this sustainability-oriented innovation. This research makes three contributions to understanding farmer adoption of insect production, by (1) reflecting on farmer interest and willingness to adopt in a developed-country context; (2) employing a unique sample of 517 German farmers; (3) and utilizing a novel PLS-SEM model based on the Edinburgh Study of Decision-making on Farms. The latter is specifically relevant for assessing the importance of (and interrelationships between) farmer-specific (e.g., personality) and farm-related determinants, which is the first time this has been done for this topic. Our findings determine that the willingness of livestock farmers to adopt insect production is determined by a combination of personal, psychological, and farm structural variables. In particular, personality traits of openness and extraversion and the reliance on off-farm work are established as key drivers for willingness to adopt, whereas neuroticism, age, and the efficient use of available resources were main obstacles. Our study thus provides key insights for farmers, insect-related companies, and regulators to gain a better understanding of farmer intentions and the potential conditions under which the shift from livestock farming to insect cultivation might be supported.

Personalized Recommender System for Children's Book Recommendation with A Realtime Interactive Robot

In this paper, we study the personalized book recommender system in a child–robot interactive environment. Firstly, we propose a novel text search algorithm using an inverse filtering mechanism that improves the efficiency. Secondly, we propose a user interest prediction method based on the Bayesian network and a novel feedback mechanism. According to children’s fuzzy language input, the proposed method gives the predicted interests. Thirdly, the domain-specific synonym association is proposed based on word vectorization, in order to improve the understanding of user intention. Experimental results show that the proposed recommender system has an improved performance, and it can operate on embedded consumer devices with limited computational resources.

A Study on the Mechanism of College Students’ Entrepreneurial Exit: Regulating Effect of Entrepreneurial Self efficacy and Entrepreneurial Ability

Based on the theory of planned behavior and entrepreneurial failure, this paper conducts a questionnaire survey of college students’ entrepreneurs through stratified sampling method to study the influencing factors of Entrepreneurial exit intention behavior, and establishes a structural equation model to more intuitively analyze the path relationship between Entrepreneurial self-efficacy and Entrepreneurial exit intention, with a view to promoting a correct understanding of Entrepreneurial exit intention and providing systematic and personalized training for entrepreneurs, Only by building a scientific and reasonable Entrepreneurial exit intention mechanism and path can entrepreneurs and potential entrepreneurs face entrepreneurial challenges directly and truly promote the sustainable development of innovation and entrepreneurship practice in the whole society.

Mpox knowledge, vaccination and intention to reduce sexual risk practices among men who have sex with men and transgender people in response to the 2022 mpox outbreak: a cross-sectional study in Victoria, Australia.

The first mpox case was reported in May 2022 in Australia. Most cases have been diagnosed in men who have sex with men (MSM). This study aimed to examine community understanding of mpox, attitudes towards vaccination, and potential changes in sexual practices surrounding the mpox outbreak among MSM and transgender people in Victoria, Australia. Participants were recruited from sexual health clinics and communities in Victoria, Australia, in August-October 2022. Participants were asked about their understanding and knowledge of mpox, vaccination uptake and intentions to change sexual practices. Univariable and multivariable logistic regression was performed to examine the factors associated with mpox vaccine uptake. Most participants (97.8%, 525/537) had heard about mpox and 10.5% (55/525) knew someone who had had mpox. Of the 12 mpox knowledge questions, the median score of correct answers was 10 (IQR=8-11) out of a maximum of 12. More than a third (36.6%, 191/522) had been vaccinated against mpox. MSM who had a good knowledge of mpox had the highest odds of receiving mpox vaccine compared with those who had poor knowledge (aOR=4.05; 95% CI: 1.54-10.61). To prevent mpox, half reported they would reduce having sex with casual partners, stop having chemsex (used drugs for the purpose of sex), stop attending sex-on-premises-venues, and stop having group sex. A quarter reported they would increase condom use for anal sex. One-third of high-risk participants and a substantial proportion of participants intended to reduce or stop certain practices, which may explain the large reduction in mpox cases.

EFL Students’ Use of E-Books for E-Learning: Applying Technology Acceptance Model (TAM)

This paper examines trends of using e-books as a learning tool among EFL students of Al-Balqa Applied University (BAU) by applying the Technology Acceptance Model (TAM) and the number of English language courses as an external independent variable. Data is collected by administering a questionnaire to 283 respondents from Humanities and Social Sciences Faculties along with Medical, Engineering, and Science Faculties. Data is analyzed using SPSS and AMOS statistical analysis software. The analysis reveals that perceived ease of use (PEOU) positively affects perceived usefulness (PU) and attitudes towards using e-books, PU has a significant effect on attitudes and intentions to use e-books, and the attitudes have significant intentions to use e-books. On the other hand, attitudes and intentions are not significantly related to the regular use of e-books in comparison to students with limited use of e-books. Finally, the students who studied or are studying three or more English courses have positive attitudes and higher intentions towards using e-books if compared to those who studied less than three. This study is important to get a better understanding of e-book reading intentions among university students. It is believed to be the first study of undergraduates’ intention on using e-book during/after the pandemic in Jordan using TAM.

Factors influencing adoption of cloud computing services in HEIs: a UTAUT approach based on students' perception

The use of cloud computing services in higher education institutions (HEIs) is gaining momentum. From a stakeholder analysis perspective, this study aims to advance the understanding of students' intentions to adopt cloud technologies. By extending the unified theory of acceptance and use of technology (UTAUT) framework, we have tried to investigate the interplay and influence of students' cognitive factors in explaining their perception towards cloud adoption. The data sample consisted of 190 undergraduate students from Indian educational institutes. The findings revealed that social influence, performance expectancy and facilitating conditions are positively related to the attitude towards cloud adoption. Moreover, the positive effect of facilitating conditions on students' attitude is mediated by perceived trust. It was also found that performance expectancy of cloud-enabled learning mediates the effects of social influence on students' attitude towards the latest technology. The present study has profound implications on HEI's change management plans and can design ways for the seamless integration of learning functions using cloud technologies.

Нотный текст как «тайна за семью печатями», или Странности в композиции и нарративе как «особое приглашение»

The author addresses the issue of the multi-layered nature of a musical work, which can exist in three forms — mental (conceptualized), visual (encoded in musical notation), and auditory (audible) text. A deep understanding of the author's intention is facilitated by the analyst's attention to various details, which can be noticed due to professional experience and the position of a "distinguished interlocutor" engaging in a dialogue with the composer.

Cross-Modality Pyramid Alignment for Visual Intention Understanding.

Visual intention understanding is the task of exploring the potential and underlying meaning expressed in images. Simply modeling the objects or backgrounds within the image content leads to unavoidable comprehension bias. To alleviate this problem, this paper proposes a Cross-modality Pyramid Alignment with Dynamic optimization (CPAD) to enhance the global understanding of visual intention with hierarchical modeling. The core idea is to exploit the hierarchical relationship between visual content and textual intention labels. For visual hierarchy, we formulate the visual intention understanding task as a hierarchical classification problem, capturing multiple granular features in different layers, which corresponds to hierarchical intention labels. For textual hierarchy, we directly extract the semantic representation from intention labels at different levels, which supplements the visual content modeling without extra manual annotations. Moreover, to further narrow the domain gap between different modalities, a cross-modality pyramid alignment module is designed to dynamically optimize the performance of visual intention understanding in a joint learning manner. Comprehensive experiments intuitively demonstrate the superiority of our proposed method, outperforming existing visual intention understanding methods.

Socrates: Data Story Generation via Adaptive Machine-Guided Elicitation of User Feedback.

Visual data stories can effectively convey insights from data, yet their creation often necessitates intricate data exploration, insight discovery, narrative organization, and customization to meet the communication objectives of the storyteller. Existing automated data storytelling techniques, however, tend to overlook the importance of user customization during the data story authoring process, limiting the system's ability to create tailored narratives that reflect the user's intentions. We present a novel data story generation workflow that leverages adaptive machine-guided elicitation of user feedback to customize the story. Our approach employs an adaptive plug-in module for existing story generation systems, which incorporates user feedback through interactive questioning based on the conversation history and dataset. This adaptability refines the system's understanding of the user's intentions, ensuring the final narrative aligns with their goals. We demonstrate the feasibility of our approach through the implementation of an interactive prototype: Socrates. Through a quantitative user study with 18 participants that compares our method to a state-of-the-art data story generation algorithm, we show that Socrates produces more relevant stories with a larger overlap of insights compared to human-generated stories. We also demonstrate the usability of Socrates via interviews with three data analysts and highlight areas of future work.

Analysis of entrepreneurial implementation intention on vocational education student at Universitas Padjadjaran: An Empirical Analysis

Entrepreneurship is an innovative and creative process that can add value to products, create job opportunities, raise productivity, revitalize, and diversify markets, improve social welfare, and, more broadly, develop the economy. Entrepreneurship education encourages the founding of new businesses by students and alums and equips them with critical decision-making skills that enhance the success of graduates in the job market. That is why we seek to develop better entrepreneurs. Part of that is raising their intentions to start a business; another is making their intentions more realistic. To do both requires a deeper, richer understanding, and analysis of an entrepreneurial implementation intention in vocational education students is essential. In this study, researchers want to know what variables affect Entrepreneurial Implementation Intention in vocational education students at Universitas Padjadjaran. The results of this study found that Entrepreneurial Knowledge affects the main determinant of this research to encourage the increase of Entrepreneurial Implementation Intention.

A Proposed Model of Perceived Support and Entrepreneurial Intentions with Theory of Planned Behavior as Mediator; Case of Omani Youth

Entrepreneurship intentions among youngsters is a topic of interest in research due to its relevance in understanding the entrepreneurship phenomenon. The current study extends the understanding of entrepreneurship intention by combining the two models namely the Theory of Planned Behavior and the Perceived Support Model. The study is based on a proposed model utilizing the Theory of Planned Behavior components as a mediator between the relationship of the perceived support model and entrepreneurship intention among Omani youngsters. Data collection is based on a cross-sectional survey-based method (n=662) and the analysis is based on AMOS software and consists of two stages. The first stage included testing the reliability and the validity by performing the Confirmatory Factor Analysis and the mediation analysis is performed in the second stage. The results indicate that between the relationship of the perceived support model and the entrepreneurship intention, attitude significantly mediates perceived educational support (β=-.014, P<.05); and perceived structural support (β=.021, P<.05). The relationship of perceived structural support influencing entrepreneurship and mediated by perceived structural support is also significant (β=.019, P<.05). Similarly, perceived behavioral control significantly mediate between perceived structural support (β=.028, P<.05) and entrepreneurship intention. Whereas, the other proposed relationships turned out to be insignificant. Thus, overall, we found partial support for the mediation model. The study recommends that for entrepreneurship intention to be promoted among youngsters, there should be a greater focus on perceived educational support and perceived structural support.

MILLENNIAL WILLINGNESS TO WEAR A FACE MASK (WTW) AFTER THE COVID-19 VACCINATION

The COVID-19 pandemic has had a profound effect on communities worldwide, with governments imposing restrictions on movement, global vaccination, quarantine, social distance measures, stay-at-home policies, and other preventative measures such as mandatory use of face masks. Despite widespread agreement that symptomatic individuals and those working in healthcare settings should continue to use the face mask following COVID-19 vaccination, discrepancies were observed in the public and societies raising awareness among Malaysian millennials. Global efforts to develop a vaccine have been accelerated to alleviate the growing burden of COVID-19. Thus, vaccination significantly decreased adverse outcomes such as non-ICU hospitalisation, as well as ICU hospitalisation and death, in several countries. Similarly, during the COVID-19 pandemic, the use of face masks by the Malaysian population, particularly the millennial generation, became widespread. However, few studies have been conducted on the millennials' willingness to continue using face masks following their COVID-19 vaccination programme in Malaysia. The purpose of this study is to gain insight into the factors that influence millennials' willingness to wear face masks following their COVID-19 vaccination programme in Malaysia. The application of the Theory of Planned Behaviour (TPB) as the guiding principle relationship enables an understanding of the millennials' continued intention to use a face mask following the COVID-19 vaccination. The hypotheses were tested using a partial Least Squares-Structural Equation Modeling (PLS-SEM) approach. The study's significance is that it advances the theoretical methodology and has practical implications for the public, scholars and practitioners, marketers, healthcare, and government in terms of prioritising willingness to continue using face masks following COVID-19 vaccination among Malaysian millennials.

Examining purchase intention for luxury fashion: integrating theory of reasoned action, with affect-behavior-cognition (ABC) model, identity and social identity theories

PurposeThis study aims to study the attitude toward purchasing luxury fashion of young consumers based on an extended model that integrates the constructs of the theory of reasoned action (TRA), identity theory, social identity theory, affect–behavior–cognition (ABC) model of attitude and brand attractiveness.Design/methodology/approachA purposive sampling approach was used to collect data from 237 young luxury fashion consumers in Hong Kong. Results were analyzed using partial least square.FindingsThe findings revealed that self-identity predicts affect-based attitudes (i.e. passive engagement and active engagement), and social identity predicts cognition-based attitude (i.e. attitude toward celebrity endorsement). Moreover, both affect- and cognition-based attitudes were found to be antecedents that enhanced brand attractiveness, which in turn positively affected purchase intention.Research limitations/implicationsThis study collected data from Generation Z. Although this generation is the world’s most influential consumer group and is highly engaged in social media, the findings may not be representative of the entire population in Hong Kong. Therefore, the findings should be used cautiously in the whole luxury fashion industry.Originality/valueThis study extends the understanding of luxury fashion purchase intention from TRA to the connection among identity, social identity theories and ABC model of attitude and brand attractiveness. The findings of this study also contribute to practical insights on developing suitable marketing strategies for the Asian luxury fashion market.