under different operational model
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Abstract: We model pricing strategy under platform competition with different Utility’s operational models. The analysis indicates the optimal pricing strategies of the two platforms, as well as the change trends of price, and suggests four bargaining strategies based on the customer perceived value of the Utility platforms.
Key words: Pricing game, Operational model, Utility platform
In the process of development of Utility platform, the growing of retail Utility always keeps the high speed on increases and the pricing model is a key question to research. Some research have already explored the pricing games of retailers and e-retailers but we notice that the price competition among Utility platforms get more intense, and the influence of operational models to the Utility platforms is become more and more obvious. In this paper, the operational models are divided into two types: the first type is that the platform set the price by and bargain with supplier and the second type is that the Utility provides a platform for supplier and consumers and the price of product is decided by supplier. For the same product which sells on two Utility platforms, the pricing model is not only related to the customer perceived value, but also influenced by the operational model. The platform of the first type should consider the wholesaling price, the competition with the second type platform and the bargaining game with the product supplier when they set the retailing price.
In this paper, we consider three keys of the pricing model: the operational model, the competition of the two platforms and the customer perceived value.
Here, we consider two types of operational models which are adopted by Utility retailer platforms with one product manufacturer. The two types of Utility retailer platform are denoted by m and r
Platform m : the Utility provides a platform for supplier and consumers. Because that this kind of Utility platform does not participate in the selling activities of online sellers and each online seller have a fairly weak voice in bargaining power, so the price of product is decided by supplier;
Platform r : the platform sells product through its own channel. Relying on powerful scale advantage, this kind of Utility platforms purchase product from supplier set the price and bargains with supplier.
Supplier s : supplier s provides products to platform r and the online sellers of platform m . The difference is for the sellers of platform m , supplier s set the price of the product based on wholesaling and retailing, but for platform r , the price of the same product is set by the platform, based on the sales volume and wholesale price.
We can see that, the competition of Utility platform m and r actually translates to a competition between platform r and supplier s . In order to maximizing the profit, supplier s has to consider not only the retailing price but also the wholesaling price. The wholesaling pricing cannot be too low or else the selling of platform r will encroach on the market share of platform m ; in the meantime, it cannot be too high, otherwise the whole sales volume of the market will decrease. But for platform r , they want to use their strong bargaining power to negotiate with supplier s for a lower wholesaling price. In this way, supplier s and Utility platform r constitute a multi-stage game relationship which decides the online price of the two Utility platforms together. In this paper, we emphatically analyze the first two stages:
StageⅠ: Utility platform r purchases product from supplier s ; supplier s provides product to platform r and set the wholesaling price; then, platform r set price for itself and supplier s set retailing price for the online sellers of platform m . StageⅡ: based on the sales volume of stage 1, platform r bargain with supplier s ; supplier s set a new wholesaling price; then, platform r and supplier s reset the retailing price respectively. Using the customer utility theory, we build the demand function of each platform. We choose parameter v , which is distributed in the [0, 1] interval, to denote the value of customers buying product and αi (i = 1, 2) , which is also distributed in the [0, 1] interval, denote the preference of the Utility platform m and r ,(i.e. customer perceived value). So, the utility of each Utility platform can be measured by U i = αi v − pi , (i = m, r) , with pi denoting the retailing price of platform m and r
In the meantime, we assume that the search cost of the two Utility platforms is 0. This assumption is realistic because that the two platforms are selling products online, the customers do not need to spend a lot to search the information of the product. In the rest part of this paper, we use Bertrand game model to analyze the equilibrium in the two stages of this game.
In this section, we analyze the equilibrium of stageⅠin this game. The same product is sold on these two Utility platforms, and we assume the product is sufficient and purchased from supplier at the price of the current stage whenever necessary, so based on customer utility theory, we get: These are the demand functions of platform m and r . For Utility platform m , the price of product is set by supplier s , so, the payoff, which should be maximized, consists of two parts: wholesaling to platform r and retailing to customers through platform m . But for platform r , the whole payoff derived from its online selling. Plugging these functions into payoff function, we get:
Among these functions, pt denote the wholesaling price for platform r , which is set by supplier s . For convenience, in our paper, we assume the cost of production is a fixable constant C . In order to obtain maximal payoff, the price response function of platform m and r is then derived as:
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