Investigating users’ experience on social media ads: perceptions of young users

Qudah, Dana Al; Al-Shboul, Bashar; Al-Zoubi, Ala’ M.; Al-Sayyed, Rizik; Cristea, Alexandra I.

doi:10.1016/j.heliyon.2020.e04378

Cited by 20 publications

(10 citation statements)

References 27 publications

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“…Liang et al (2012) and Tan and Chou (2007) reached the same conclusion (Lee and Kim, 2005;Moller, 2015). So as the study of Al-Shboul et al (2020).…”

Section: Discussionmentioning

confidence: 99%

Exploring the Influential Factors on Readers' Continuance Intentions of E-Book APPs: Personalization, Usefulness, Playfulness, and Satisfaction

et al. 2021

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With the rapid development of mobile devices, users can now read on the screen. Electronic reading (e-reading) has become a common reading style with the growth in online learning or electronic learning (e-learning). E-book applications (APPs) are widely developed and applied for reading on a screen. However, it is difficult for readers to change their reading habits or preference from paper-printed books to digital devices. The study of readers' continuance intention to use e-book APPs is the first step to improving e-reading. This study focuses on the influential factors on undergraduates' continuance intention of e-book APPs, which analyzed and summarized the literature related to the electronic book (e-book) applications (APPs) and undergraduates' continuous intention, combined with the characteristics of the e-book APPs, introduced relevant theories and variables, and established the factors that influence undergraduates' continuous intention of using e-book APPs. On this basis, the paper analyzed the relationship between various influencing factors and their influence on continuous intention. A model composed of five hypotheses was constructed to test the factors influencing undergraduates' continuous intention in e-book APPs. The results indicated that of all research variables, satisfaction is the most important factor that affects continuous intention; Perceived usefulness and perceived playfulness have an indirect effect on continuous intention through satisfaction; personalization has direct effects on perceived usefulness and perceived playfulness, so it also has an indirect effect on continuous intention. The findings of the study will be helpful for designers and developers of e-book APPs and provide e-book APP suggestions for readers as well.

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“…Liang et al (2012) and Tan and Chou (2007) reached the same conclusion (Lee and Kim, 2005;Moller, 2015). So as the study of Al-Shboul et al (2020).…”

Section: Discussionmentioning

confidence: 99%

Exploring the Influential Factors on Readers' Continuance Intentions of E-Book APPs: Personalization, Usefulness, Playfulness, and Satisfaction

et al. 2021

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“…The classification models depend on high-quality training data. If the data suffer from redundant and useless information, then it can lead to adverse outcomes from time to time ( Al-Qudah et al, 2020a ; Ala’M et al, 2021 ; Srinivasan et al, 2021 ; Al-Zoubi et al, 2021 ; Faris et al, 2017 ; Al Qudah et al, 2020b ). Recently, the high dimensional data increased promptly and enforced significant challenges on the existing classifier methods ( Obiedat et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

“…The filter mechanism is more about the relation or correlation between the features without considering the class label, whereas the wrapper feature selection depends entirely on the class label to select the most important features. The wrapper technique can be employed using metaheuristic algorithms, such as Genetic Algorithm (GA) ( Al-Qudah et al, 2020a ; Al-Qudah et al, 2020b ), Particle swarm optimization(PSO) ( Rostami et al, 2020 ), Multi-Verse Optimizer (MVO) ( Sadiq et al, 2019 ), Salp Swarm Algorithm (SSA) ( Ala’M et al, 2020 ), Whale Optimization Algorithm (WOA) ( Ala’M et al, 2018 ) and Competitive Swarm Optimizer (CSO) ( Ala’M et al, 2021 ). To accomplish the feature selection task, Petkovic et al, (2014) and Petkovic et al (2016) used GINI index whereas Naseer, Zhang & Zhu (2020a) used information gain.…”

Section: Methodsmentioning

confidence: 99%

Swarm intelligence-based model for improving prediction performance of low-expectation teams in educational software engineering projects

Al‐Ahmad

Al-Zoubi

Kabir

et al. 2022

PeerJ Computer Science

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Software engineering is one of the most significant areas, which extensively used in educational and industrial fields. Software engineering education plays an essential role in keeping students up to date with software technologies, products, and processes that are commonly applied in the software industry. The software development project is one of the most important parts of the software engineering course, because it covers the practical side of the course. This type of project helps strengthening students’ skills to collaborate in a team spirit to work on software projects. Software project involves the composition of software product and process parts. Software product part represents software deliverables at each phase of Software Development Life Cycle (SDLC) while software process part captures team activities and behaviors during SDLC. The low-expectation teams face challenges during different stages of software project. Consequently, predicting performance of such teams is one of the most important tasks for learning process in software engineering education. The early prediction of performance for low-expectation teams would help instructors to address difficulties and challenges related to such teams at earliest possible phases of software project to avoid project failure. Several studies attempted to early predict the performance for low-expectation teams at different phases of SDLC. This study introduces swarm intelligence -based model which essentially aims to improve the prediction performance for low-expectation teams at earliest possible phases of SDLC by implementing Particle Swarm Optimization-K Nearest Neighbours (PSO-KNN), and it attempts to reduce the number of selected software product and process features to reach higher accuracy with identifying less than 40 relevant features. Experiments were conducted on the Software Engineering Team Assessment and Prediction (SETAP) project dataset. The proposed model was compared with the related studies and the state-of-the-art Machine Learning (ML) classifiers: Sequential Minimal Optimization (SMO), Simple Linear Regression (SLR), Naïve Bayes (NB), Multilayer Perceptron (MLP), standard KNN, and J48. The proposed model provides superior results compared to the traditional ML classifiers and state-of-the-art studies in the investigated phases of software product and process development.

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“…An advertisement has a significant impact on consumer buying behavior through various media such as newspapers, magazines, outdoor ads, blogs, and websites [21]. Social media users find social media ads useful and personalized, and that the perceived usefulness and personalization significantly affect the usage of host architecture, which significantly affects users' experience [22]. However, it does not rule out advertisements through digital media, considering that digital media can easily reach more consumers.…”

Section: Subsection Mean 277 68%mentioning

confidence: 99%

Improving Pigmented Rice Farmers' Marketing Activity for Sustainable Agroindustry: Consumers' Voice to be Considered

2021

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The demand for pigmented rice is highly increasing due to the consumer changing on a healthy lifestyle. The price of pigmented rice is higher than white rice, so it may be an opportunity to improve farmers' welfare. However, as producers, the farmers said they understand the consumer's needs and wants. They lack access to consumers' information. This article attempted to reveal the consumers' perspective of pigmented rice in Indonesia through their preferences and perceived quality. Those are variables indicating consumer voices. Two hundred sixty-one respondents are joining the survey from some big cities in Indonesia. The survey was exploring consumer voices about pigmented rice. The result shows that 83% of consumers said that pigmented rice is a superior product with a high price and high value. But the quality remains inconsistent, difficult to serve and combine with other dishes. The most attractive social media for them is Instagram Feeds. They often see the advertisement on social media and have more likely attracted by a campaign that been share on social media. Those help producers to market the rice better and broader, improving sustainable agroindustry on pigmented rice.

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Investigating users’ experience on social media ads: perceptions of young users

Cited by 20 publications

References 27 publications

Exploring the Influential Factors on Readers' Continuance Intentions of E-Book APPs: Personalization, Usefulness, Playfulness, and Satisfaction

Exploring the Influential Factors on Readers' Continuance Intentions of E-Book APPs: Personalization, Usefulness, Playfulness, and Satisfaction

Swarm intelligence-based model for improving prediction performance of low-expectation teams in educational software engineering projects

Improving Pigmented Rice Farmers' Marketing Activity for Sustainable Agroindustry: Consumers' Voice to be Considered

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