Abstract
Big data knowledge, such as customer demands and consumer preferences, is among the crucial external knowledge that firms need for new product development in the big data environment. Prior research has focused on the profit of big data knowledge providers rather than the profit and pricing schemes of knowledge recipients. This research addresses this theoretical gap and uses theoretical and numerical analysis to compare the profitability of two pricing schemes commonly used by knowledge recipients: subscription pricing and pay-per-use pricing. We find that: (1) the subscription price of big data knowledge has no effect on the optimal time of knowledge transaction in the same pricing scheme, but the usage ratio of the big data knowledge affects the optimal time of knowledge transaction, and the smaller the usage ratio of big data knowledge the earlier the big data knowledge transaction conducts; (2) big data knowledge with a higher update rate can bring greater profits to the firm both in subscription pricing scheme and pay-per-use pricing scheme; (3) a knowledge recipient will choose the knowledge that can bring a higher market share growth rate regardless of what price scheme it adopts, and firms can choose more efficient knowledge in the pay-per-use pricing scheme by adjusting the usage ratio of knowledge usage according to their economic conditions. The model and findings in this paper can help knowledge recipient firms select optimal pricing method and enhance future new product development performance.
Highlights
The rapid development of information technology, Internet of Things, social networking, and cloud computing has ushered in a new era of big data
To facilitate more effective knowledge transactions from the perspective of firms as knowledge recipients, this present research developed a model that compares two pricing schemes commonly used by knowledge transactions recipients: subscription pricing and pay-per-use pricing
The experimental result shows that the subscription price of the big data knowledge has no effect on the optimal time of knowledge transaction in the same pricing scheme, but the usage ratio of big data knowledge affects the optimal time of knowledge transaction
Summary
The rapid development of information technology, Internet of Things, social networking, and cloud computing has ushered in a new era of big data Against this unprecedentedly available data as a backdrop, the knowledge extracted from big data can help firms guide decision-making, cut costs and increase sales [1,2]. The most popular pricing schemes for big data knowledge transactions are subscription pricing and pay-per-use pricing [11] These pricing methods mainly focus on firms’ profitability from a big data knowledge provider’s standpoint rather than from that of a knowledge recipient. Prior research has not examined the pricing schemes in big data knowledge transactions from the perspective of firms as knowledge recipients—a theoretical gap addressed by the present research and with practical implications for their knowledge transaction and new product development.
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