درخت حوزه‌های تخصصی

Today, different customer’s willingness to pay alongside the maturity of data analytics has made it possible to offer segmented prices and gain maximum consumer surplus. Price segmentation is defined as a strategy in which prices are free to adjust based on the "fences" of time of purchase, place of purchase, customer characteristics, product characteristics, etc. Since strategic pricing policies are not practically possible for every single customer, each of them falls into one section. Price segmentation is based on key concepts such as "willingness to pay" and "consumer surplus". However, it also causes "price unfairness perception". Since such feeling is triggered when people compare their deal to another’s, approaches to "make difference in transactions" would be helpful. This study aims to investigate the perceived fairness in three price segmentation methods. The present research is practical in terms of purpose and is descriptive survey research in terms of research method. The statistical population of the research is 384 customers of Tehran's online stores. Data collection was done by questionnaire and data analysis by one-way analysis of variance and least significant difference method using SPSS software. Cronbach's alpha was used to assess the validity of the questionnaires. Findings indicate that the method based on "customer characteristics", has the least level of perceived fairness.  The "product bundle" method has increased perceived fairness, but not much, and price segmentation based on "product features" results in the highest perceived fairness.

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.