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.

This article deals with developing a model of digital marketing with a focus on customer experience and with the aim of optimizing the customer management process, increasing the quality and length of the customer journey (increasing loyalty), and improving the consequences of the marketing process in companies, and seeks to answer this question. What is the digital marketing model with the customer experience management approach and what components does it include? The research method is mixed (qualitative-quantitative) and since a model for this issue is not available in past research, the first part of the research explores model extraction through qualitative methods (here, foundation data analysis) and to determine Relationships within the model quantitatively explain the model using quantitative methods (here structural equations). The method of collecting information in the qualitative part, in addition to conducting library studies, in the form of in-depth interviews with experts in the fields of information technology, marketing, and commerce, information technology policy, and actually business managers and stores that provide services and products through channels and digital tools in this section, the statistical sample limit was carried out by the snowball method (saturation to the end of the problem) and the quantitative part of the research and explanation of the model was through data collection with questionnaire tools and closed interviews from the customers of several digital businesses, which was done with the method 385 people were randomly selected and available using Cochran's formula. In the end, the main conditions, background conditions, intervening conditions, phenomena, strategies, and consequences affecting the digital marketing model with the customer experience management approach were extracted and the relationships between them were determined.