درخت حوزه‌های تخصصی

The special issue aims to cover the latest research topics in designing and deploying visual information analytics and management techniques using deep learning. It is intended to serve as a platform to researchers who want to present research in deep learning. The special issue focuses explicitly on deep learning and its application in visual computing and signal processing. It emphasizes on the extent to which Deep Learning can help specialists in understanding and analyzing complex images and signals. The field of Visual Information Analytics and Management is considered in its broadest sense and covers both digital and analog aspects. This involves development of techniques for image analysis, understanding and restoration. Deep learning techniques are effective for visual analytics. Deep learning is a fast growing area and is gaining impetus for application in various fields. Therefore, in this special issue, the objective is to publish articles related to deep learning in various problems of visual information analytics and management.

The purpose of this study is to investigate the role of e-commerce marketing capabilities in enhancing Iranian carpet export capabilities via a paradigmatic model. In fact, the present study seeks to identify various factors that may influence the role of electronic marketing capabilities in promoting Iranian carpet export capacity. The identified strategies obtained from the paradigmatic model in this study are ranked in order to develop an understanding of the strength of their effects on the outcomes of e-marketing at the international level. In terms of research philosophy, the present study is based on interpretive paradigm and is considered an applied-developmental research in terms of research orientation. The data were collected using semi-structured interviews and a standardized questionnaire. The study population consisted of experts and managers of the carpet industry in Iran, who were selected using purposive sampling. Data analysis was carried out using theme analysis approach in MAXQDA software, and quantitative data were analyzed using interpretive structural modeling in Excel software. The main finding of the present study is to introduce a paradigmatic model of the role of e-commerce marketing capabilities in promoting Iranian carpet export capability. This model identifies and introduces contextual, causal, strategic, and intervening factors as well as the implications of developing e-marketing capabilities with the primary concern of promoting the country's carpet export capabilities. In addition, in the quantitative phase of the study, thirteen strategies affecting two categories of short-term and long-term outcomes were ranked based on the strength of their impact on outcomes.