Presenting the perceived fairness model of dynamic pricing (meta synthesis approach)

Objective: lack of perceived fairness of the price, various destructive consequences such as lack of trust in the seller and existing prices, decrease in demand, decrease in customer satisfaction, negative advertising by customers towards the company, loss of customer loyalty to the company or brand, complaints against the company , leads to reluctance to buy again. Considering all the mentioned destructive consequences, it is necessary and necessary to design a perceived fairness model of dynamic pricing. The perceived unfairness of dynamic pricing has destructive consequences for the company, and the existence of an applicable model in this area can reduce these consequences. Therefore, the aim of the current research is to present the perceived fairness model of dynamic pricing with a meta-composite approach.

Methodology: The research is descriptive in terms of practical purpose, in terms of data collection and in terms of qualitative approach. The method of this research is qualitative. Meta-synthesis includes steps: search, evaluation, composition, expression and partial interpretation of both quantitative and qualitative research groups. Transcombination can be done with different methods, in this study, the 7-step model of Sandelowski and Barso was used. The data collection tool is past documents, which generally included 32 articles. The method of data analysis is content analysis.

Findings: The findings of the research show that the drivers affecting the perceived fairness of dynamic pricing in three categories: customer-related factors (demographic characteristics, price knowledge, price expectation, consumption and behavioral experience, familiarity with dynamic pricing), company-related factors ( pricing transparency, communication with customers, trust) and market-related factors (price position, price dispersion). Drivers are the set of factors that affect the perceived fairness of dynamic pricing. The drivers include various factors. Perceived fairness of dynamic pricing includes two dimensions: emotional fairness and cognitive fairness. Customers who expect low prices will be suspicious and unfair about price increases. The actions of the companies to create awareness among the customers regarding the reasons for the price increase, the time of the price change, similar actions in the past periods, have a significant impact on the customers' correct understanding of the price change and will not cause them to feel unfair. Perceived fairness consequences of dynamic pricing are categorized into two categories: positive consequences (customer satisfaction, customer loyalty, repurchase intention) and negative consequences (negative feelings, negative behaviors, and negative advertising by customers).

Conclusion: Any price difference should have a logical reason and should be used as a segmentation tool. Although any pricing policy affects the purchase intention of consumers, the adopted policies should not harm the perceived fairness of the customer. The set of drivers identified on the perceived fairness of dynamic pricing in deciding to price the same goods in different conditions is a basis for pricing officials in companies.