Optimal pricing strategies of multinational SaaS firms under dual distribution channels

Abstract

Software as a service (SaaS) is a web-based software delivery model that is licensed on a subscription basis and is centrally managed. SaaS products have been covering every aspect of business and life. Specific examples can be services such as Apple iCloud, Dropbox, Gmail and Salesforce. In light of the recent remote working trend worldwide, SaaS nowadays becomes the most intensively competed place in a B2B sense. In rivalry for market share, SaaS giants adopt price discrimination strategies and deliver different services to every corner of the world. Nonetheless, we notice that there exist few studies regarding pricing strategies of differentiated SaaS products in B2B market. We therefore study the optimal pricing strategies of multinational firms (MNFs) under dual distribution channels. In our model, the MNF provides both standard (low-end) and customized (high-end) SaaS products across borders. The standard products are offered directly by the MNF headquarters while the customized products are offered by MNF's retailing divisions that locate in the foreign countries. When products are sold across borders, they inevitably face different value added tax rates. We incorporate the concern into our model and discuss the scenarios respectively, when MNF is selling from low tax rate region to high tax rate region and vice versa. We find out that for pricing sequence, it is optimal for the MNF to firstly price standard applications and then the retailing divisions to price customized applications as internal pricing sequence, when this MNF sells software from a region with relatively lower tax rate to regions with relatively higher tax rate. On the contrary, when this MNF sells software from a region with relatively higher tax rate to regions with relatively lower tax rate, it is optimal for the MNF to firstly price customized applications and then its retailing division to price standard applications as internal pricing sequence. These findings still hold when market size is expanded by the network effect in the long run. Another key finding is that it is never an optimal strategy for the MNF and retailing division to determine standard applications' and customized applications' prices simultaneously, regardless of the relative tax differentials. This finding is also robust under the impact of network effect.