Identification Affecting Factors of Price Discount Threshold: Meta Synthesis

Hamidreza Biranvand, Mohsen Nazari
2020 ‫مدیریت بازرگانی  
Objective Competitiveness of business environment in the country, growth of ever-discount stores, and the prevalence of foreign brands in the form of stores and shopping centers in Tehran and other cities have caused Iranian stores and companies to widely develop their price discounts so as to increase their sales and expand their market share. In this new space, if the strategy and methods of discounting are not used effectively, that is, the percentage of discount is too high or too low, the
more » ... gh or too low, the time and repetition of the discount is high or low, and etc., Iranian stores and companies will face several risks including reduced sales, weakening of the brand's position, and so on. Hence, the present study aims to explore for the factors influencing these levels, which are referred to as the "price discount threshold" in this study. The main purpose is, then, to identify which factors affect the high and low discount threshold to use those effective strategies. This research helps stores and companies design a "discount window". Methodology This research is developmental in terms of purpose, qualitative in terms of the data analysis research and documentary in terms of data collection method. The present study is analytical-descriptive in terms of research method. This study was conducted through meta-synthesis. For this purpose, after CASP analysis, 24 studies that have directly addressed the issue of discount threshold entered the analysis phase. The selected researches were entered into Max Kioda software for codification and were using Max Kioda software. Findings In this study, 24 studies directly dealt with the discount threshold entered the analysis phase. Finally, after the integrations phase, 56 distinct codes were identified. In the next step, the codes were identified in the form of 23 concepts or themes and finally the concepts were identified in the form of 13 categories as affecting factors on the price image [...]
doi:10.22059/jibm.2019.271555.3361 doaj:a73a00f98c064c7f8b386cf2e85fac0b fatcat:567pfgletfas5mtmrh5jargjsq