درخت حوزه‌های تخصصی

In today's world, the Internet of Things (IoT), which is a fairly new technology, has become a popular topic for discussion. Meanwhile, the increasing demand for personalized healthcare with the assistance of new technologies has created new applications called e-health IoT applications; however, researchers are still attempting to find its applications, therefore they have not been able to focus on comparing these applications. We have aimed at understanding the benefits of e-health IoT applications in comparison to one another. Therefore, this study is an attempt to provide a list of e-health IoT applications for individuals and to prioritize them. The Fuzzy Analytical Hierarchy Process (FAHP) method has been used, which is a method for Multi-Criteria Decision Making (MCDM) and a useful tool for prioritizing multiple alternatives based on criteria. Eight important criteria, based on a comprehensive literature review and experts’ opinions, were determined. Then, by using the FAHP method, the weight of each criterion was calculated. As a result, seven applications identified for individuals were prioritized based on the weight of each criterion and the score of each application in each criterion. Health Effectiveness, Empowerment, Safety, Privacy, and Peace of Mind are the most important criteria in e-health IoT applications for individuals; Cost Saving, round-the-clock Access, and Time-Saving are in the next levels of importance. The results also show that Chronic disease management, Medication reminders, Health monitoring, Air quality, Fall detection, Sleep control and Fitness were respectively ranked as first, second, third, fourth, fifth, sixth and seventh among the IoT applications.

Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer’ reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This study is aimed at designing a recommender system based on the explicit and implicit preferences of the customers in order to increase prediction’s accuracy. In this study, we have combined sentiment analysis with the Collaborative Filtering (CF) based on deep learning for user groups in order to increase system accuracy. The proposed system uses Natural Language Processing (NLP) and supervised classification approach to analyze sentiments and extract implicit features. In order to design the recommender system, the Singular Value Decomposition (SVD) was used to improve scalability. The results show that our proposed method improves CF performance.

Recently, significant technological changes, greater customer demand and the rise of new business models have triggered a rapid increase in electronic service (e-service) innovations. Now, innovation in the provision of e-services has become one of the priorities of managers in order to gain a competitive advantage. However, few studies so far have explored the determinant factors needed in the organization in order to innovate and implement e-services. The purpose of this study is to provide a comprehensive framework that integrates the multiple factors of e-service innovation. Using the qualitative meta-synthesis research method and after a systematic review of the literature and examination of 61 articles, all factors needed for innovation in e-services have been identified and classified in 4 capabilities, 9 concepts, and 30 codes. The results show that e-service innovation depends on networking, informational, operational and supporting, and strategic capabilities. These capabilities create the required platform for innovation in e-services in the organization. This study contributes to current e-service researches by offering theoretical advances related to innovation in e-services. Furthermore, the capabilities, concepts, and codes identified in this study would be useful as a comprehensive conceptual framework for developers of e-service innovation to plan and evaluate their related initiatives.

The objective of the research is to clarify what Blockchain technique is and the developments of its various uses, and identify the accounting perspective of this technique and the possibility of using it in accounting work. It also aims at demonstrating how to utilize its Blockchain technique in accounting information systems, and identify the most important potential effects of the use of technique in accounting information systems. To achieve the research objectives, a descriptive approach was adopted to discuss the fundamentals of Blockchain technique and its most important accounting implications, in addition, its significance for the usefulness and reliability of the development of automated computing accounting systems. The researchers concluded that the use of Blockchain technology for accounting work requires analysis of the related impact on the development of accounting information systems in terms of their implementations and modules, with the need to fully transition in the design of accounting information systems to electronic sophisticated programs and applications developed and technologically advanced.