درخت حوزه‌های تخصصی

Nowadays, the generated and shared content on tourist perceptions in social media is considered a fresh and far-reaching way to introduce the concept of the destination image. Destination decision-makers attempt to use this content to provide a deep understanding of tourism supply and demand. Marketers have to be particular about it when defining a proper destination image. In this regard, many researchers have emphasized the importance of using social media to tap into tourists’ perceptions of destination because it not only helps to deepen the administrators’ understanding of the demands of this type of tourism and to propose new approaches to determine the customers’ preferences in destination marketing but also directs new products and services to satisfy the tourists to a greater extent. Depending on the type of tourism, the contexts and criteria for this kind of virtual investigation are different. For example, in cultural destinations, tourists’ perceptions of tangible and intangible cultural heritage and services and products offered in virtual contexts are regarded as a tool to assess the tourists’ perceptions of that destination. The present study assumes that a holistic approach toward the analysis of tourist perception in the virtual sphere could be a well-qualified alternative to determine tourists’ wants in cultural destinations. Content analysis, which is a practical method in analyzing visual and textual data and  therefore is quite pertinent to the analysis of tourist perceptions, was adopted as the data analysis instrument in this study. To collect the data, two frequently-visited and widely-used websites with easy access to tourists’ comments, namely TripAdvisor and Flickr , were selected so that tourists’ experiences and perceptions could be gathered more authentically and conveniently. The findings demonstrated that the analysis of perceived authenticity of cultural destinations in Iran could provide the content required to create a destination image for purposeful marketing in Iran. Perceived Authenticity was categorized into three main themes: emotional, sensational, and rational.

The ability of now-casting and eventuality is the most crucial and vital achievement of big data analytics in the area of policy-making. To recognize the trends and to render a real image of the current condition and alarming immediate indicators, the significance and the specific positions of big data in policy-making are undeniable. Moreover, the requirement for policy-making institutions to produce a structured model based on big data analytics for now-casting and eventuality of predictive policies is growing rapidly. The literature review demonstrates that a comprehensive model to assist policy-making institutions by providing all components and indicators in now-casting of predictive policies based on big data analytics is not devised yet. The presentation of the model is the main finding of this research. This research aims to provide a comprehensive model of now-casting and eventuality of predictive policies based on big data analytics for policy-making institutions. The research findings indicate that the dimensions of the comprehensive model include: the alignment of now-casting strategies and the big data analytics’ architecture, now-casting ecosystem, now-casting data resources, now-casting analytics, now-casting model and now-casting skill. The results of using the model were analyzed and the recommendations were presented.

Brands are a symbol of product identity and even of human beings because much of a person's future success depends on his or her personal abilities and the use of available devices to build and develop a desirable image of oneself. Using personal branding can also be a tool for achieving professional success for athletes. The present study, regarding the purpose, is applied-developmental and, regarding the nature and method of data collection, is descriptive-correlational. The statistical population of this study consists of athletes in Sanandaj. From this population, using non-random sampling and based on the researcher's decision, 100 people were selected as sample members among the athletes of the city. The main tool for data collection in this study is a standard questionnaire and its validity was confirmed by professional professors in the management discipline and its total reliability was above 0.7. Regarding the type of research and variables, SPSS software and PLS software have been used to analyze statistical data and test research hypotheses. Based on the results of testing the hypotheses, all the used factors have a significant effect on professional success, among which self-modeling has the highest impact and self-promoting has the lowest impact on the professional success of athletes.