درخت حوزه‌های تخصصی

A logo epitomizes a brand and depicts the picture of a product; consequently, attention, as an initial step of the AIDA model, to the logo is a good-looking index to survey the cognitive processing during consumers’ decision-making. Eye tracker extracts the visual attention data. For these reasons and appreciated from fixation duration, in the present study, the process of visual attention to the logo of a brand during decision-making was studied. To analyze the effects of the popularity of a brand on consumers’ decision-making, visual attention of 53 undergraduate students was studied. The brands were selected from two categories of beverages: soft drinks and non-alcoholic beers. Prior to the test, the participants had declared their favorite categories. The results showed that 75% of the participants selected a popular brand of their unfavorite categories. On the other hand, the difference of fixation duration between logos of popular and unknown brands did not directly relate to the choices of the participants. Therefore, these results did not correspond with the AIDA model. Additionally, cognitive processing toward the unknown brands’ logos was more than the popular brands’ logos. Moreover, the consumers who changed their decision were subjected to more cognitive processing compared to the consumers who insisted on their selection. In contrast to the AIDA model which implies that decision-making is triggered by attention, the present study indicated that decision making can also be influenced by the popularity of the brand. This can be due to optimization of the working memory usage by the brain. Finally, these results could be helpful in creating a new brand. According to the AIDA model, the more attractive logo and package of the brand, the more chance for being selected by the customers. However, our findings emphasize the importance of the popularity of the brand.

Handwriting Analysis has been used for a very long time to analyze an individual’s suitability for a job, and is in recent times, gaining popularity as a valid means of a person’s evaluation. Extensive Research has been done in the field of determining the Personality Traits of a person through handwriting. We intend to analyze an individual’s personality by breaking it down into the Big Five Personality Traits using their handwriting samples. We present a dataset that links personality traits to the handwriting features. We then propose our algorithm - consisting of one ANN based model and PersonaNet, a CNN based model. The paper evaluates our algorithm’s performance with baseline machine learning models on our dataset. Testing our novel architecture on this dataset, we compare our algorithm based on various metrics, and show that our novel algorithm performs better than the baseline Machine Learning models.

Recently, Massive Open Online Courses have become sensational in the field of distance learning. There is a plethora of advantages being listed in learning through MOOCs but this pedagogy lacks in few areas when compared with traditional classes. One of those inabilities of MOOC is its support to prepare the students for laboratory-based courses. The authors of this study chose a MOOC course that teaches Digital Photography and created an Augmented Reality (AR) experience for a module that explains the different parts of a digital camera. The 2 nd year Multimedia students of Vellore Institute of Technology have been asked to experience the MOOC video followed by the AR experience. Their feedbacks before and after the AR experience has been statistically tested and reported. The results revealed that the students feel more confident and concentrate more when the instructional video was given as an AR experience. This study suggests that AR integrated MOOC modules might help in training students better for practice-based courses.

Corona Virus (COVID-19) is a major problem among people, and it causes suffering worldwide. Yet, the traditional prediction models are not yet suitably efficient in catching the fundamental expertise as they cannot visualize the difficulty in the health's representation problem areas. This paper states prediction mechanism that uses a model of deep learning called Long Short-Term Memory (LSTM). We have carried this model out on corona virus dataset that obtained from the records of infections, deaths, and recovery cases across the world. Furthermore, producing a dataset which includes features of geographic regions (temperature and humidity) that have experienced severe virus outbreaks, risk factors, spatio-temporal analysis, and social behavior of people, a predictive model can be developed for areas where the virus is likely to spread. However, the outcomes of this study are justifiable to alert the authorities and the people to take precautions.

The Special Issue of the Journal of Information Technology Management (JITM) is publishing very selective papers on information management, technology in higher education, integrated systems, enterprise management, cultural thoughts, strategic contributions, management information systems, and cloud computing. We received numerous papers for this special issue but after an extensive peer-review process, 10 papers were finally selected for publication. The current special issue consisted of areas viz Integrated Intelligent Systems, Analytical Systems, and Enterprise Management.

This study aimed to investigate the impact of the hospital information system (HIS) on nurses' satisfaction in Iranian public hospitals and to examine the moderating effect of computer literacy. The study population consisted of nurses working in public hospitals in Iran. A sample of 385 Iranian public hospitals was surveyed and a total of 1912 questionnaires were collected over 9 months. The analytical method used to empirically test the proposed hypotheses was the SEM technique using SmartPLS3. Results showed that all four variables of nurses' attitude, system quality, information quality, and service quality had significant positive effects on nurses' satisfaction with HIS. The findings also indicated that the effects of nurses' attitude, system quality, and particularly service quality increased on nurses' satisfaction with HIS by rising computer literacy, and only the effect of (computer literacy × information quality) was not significant on satisfaction. The use of FIMIX, CTA, and permutation test analyses is the innovation of the analysis.