تصمیم گیری های بهینه بر روی گزینه خرید گروهی با قیمت خرده فروشی نوشته شده و تقاضای ناهمگن
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|40448||2015||11 صفحه PDF||سفارش دهید||12578 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Electronic Commerce Research and Applications, Volume 14, Issue 1, January–February 2015, Pages 23–33
Group buying is now a popular business mechanism whereby customers are encouraged to bargain together. Today’s group buying usually adopts a fixed group price rather than using a dynamic pricing mechanism and many retailers sell products using both a group buying and a posted price. Therefore, there are usually different shopping channels as the market can be divided into two segments, a group buying segment and an individual segment, according to consumers’ preference. However, sometimes the group buying option can decrease total revenue by influencing the individual market segment. Consequently, the seller has to decide: (1) whether to offer a group buying option and (2) if offering such an option, which combination is the best? In this paper, we classify customers into collectivist customers and individualistic customers depending on their different valuations of the time and energy spent in group buying communication and study the optimal pricing strategy according to actual market information. Although collectivist customers prefer to participate in group buying, our results show that this is true only in certain conditions in an individualistic dominant market where the potential demand of the individualistic customers is greater than that of the collectivist customers or the price coefficient of the individualistic customers is less than that of the collectivist customers. In these circumstances, the seller should provide a posted retail price together with a group buying option which can assist in customer discrimination, but in other conditions, the seller should only provide a posted retail price. Additionally, we have extended the two customer classifications to multiple classifications in this paper.