Pricing strategy for the service supply chain of S&T innovation platforms: Platform “burning money” or piggybacking alliance?
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    Abstract:

    In the era of innovation-driven development, it is of great significance to the S&T innovation platform and social economy to provide supporting services for resource sharing for innovation and to realize the effective use of scientific and technological innovation resources through the platform supply chain, thereby revitalizing social resources. The level of supporting services provided by science and technology resource providers on the S&T innovation platform not only affects their innovation output, but also affects the number of users who join the platform. Considering the actual situation of China’s science and technology innovation, this paper examines the preference of scientific research for the quality of the supporting services provided by resource providers on the platform. Game theory is applied to studying the pricing decisions of the S&T innovation platform. Two strategies, platform subsidies and piggybacking alliances, are extensively examinedbased on ordinary pricing strategies. Based on the realistic situation of the supply and demand characteristics of users on both sides of the platform, the profit maximization strategies of different types of S&T innovation platforms are revealed. The research has found that under the three strategies, the platform pays commission to resource providers within a certain range of unit operating costs. The commission increases with the increase of user quality preference coefficient, and the optimal subsidy amount and drainage quantity also increase. Comparing the three strategies, the service fee of the platform is the lowest under SS and the highest under AS, both of which can bring higher returns to the platform under certain conditions. Different types of S&T innovation platforms should choose different pricing strategies to maximize platform profits when the proportion of high-quality resource providers in the market is different. In addition, after considering the characteristics of innovation risk, a higher quality preference coefficient is required to achieve a substantial increase in the profits of the S&T innovation platform.

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  • Online: October 16,2024
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