While last decade has witnessed a rapid growth of digital economy, there is limited understanding in literature on whether the conventional wisdom on pricing strategy still holds for information goods. On one hand, in...While last decade has witnessed a rapid growth of digital economy, there is limited understanding in literature on whether the conventional wisdom on pricing strategy still holds for information goods. On one hand, information goods, similar to durable goods, are subject to value depreciation; on the other, they differ from traditional goods in negligible marginal cost and the sensitivity to social influences. This paper develops a two-period, game-theoretic model to investigate optimal pricing strategy of information goods. On one dimension, two different depreciation mechanisms （self- and time-depreciation） are considered; on the other, two prevalent pricing schemes （perpetual licensing and subscription-fee models） are studied. We obtain closed-form solutions in all scenarios. Our findings suggest that vendors of time-depreciation information goods should adopt subscription-fee model to attract early adopters and exploit social influences, while the vendors of self-depreciation information goods should strategically balance between depreciation and social influences. Interestingly, as social influences become strong enough, the difference between pricing schemes diminishes and the tradeoff between candidate strategies vanishes. We also extend the model to static pricing in which the vendor commits to future price. We discover that the superiority of subscription-fee model might be overturned under static pricing. Our results above also imply that building consumer feedback and interaction systems could be helpful for minimizing the potential loss of a suboptimal pricing scheme.展开更多
In the age of artificial intelligence,firms'internal data are increasingly valuable when merged with each other for inter-firm analysis and predictions.However,the inter-firm data transactions represent a novel ch...In the age of artificial intelligence,firms'internal data are increasingly valuable when merged with each other for inter-firm analysis and predictions.However,the inter-firm data transactions represent a novel challenge on pricing due to the complex nature of data,such as quality information asymmetry,lack of pricing standards,and the negligible marginal cost.This paper conducts a case study at Shanghai Data Exchange to explore the factors that can facilitate the data transactions between buyers and providers.We use interview transcripts from 18 participating firms to construct our three theoretical dimensions:increasing the perceived value,mitigating the cost,and improving the market design.We then browse through 18 factors to assess their value for further improvements.The managerial implications are also discussed.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.71271001,70901046,and 71302002
文摘While last decade has witnessed a rapid growth of digital economy, there is limited understanding in literature on whether the conventional wisdom on pricing strategy still holds for information goods. On one hand, information goods, similar to durable goods, are subject to value depreciation; on the other, they differ from traditional goods in negligible marginal cost and the sensitivity to social influences. This paper develops a two-period, game-theoretic model to investigate optimal pricing strategy of information goods. On one dimension, two different depreciation mechanisms （self- and time-depreciation） are considered; on the other, two prevalent pricing schemes （perpetual licensing and subscription-fee models） are studied. We obtain closed-form solutions in all scenarios. Our findings suggest that vendors of time-depreciation information goods should adopt subscription-fee model to attract early adopters and exploit social influences, while the vendors of self-depreciation information goods should strategically balance between depreciation and social influences. Interestingly, as social influences become strong enough, the difference between pricing schemes diminishes and the tradeoff between candidate strategies vanishes. We also extend the model to static pricing in which the vendor commits to future price. We discover that the superiority of subscription-fee model might be overturned under static pricing. Our results above also imply that building consumer feedback and interaction systems could be helpful for minimizing the potential loss of a suboptimal pricing scheme.
基金the National Natural Science Foundation of China(NSFC)under Grants 71672042,71822201,91746302。
文摘In the age of artificial intelligence,firms'internal data are increasingly valuable when merged with each other for inter-firm analysis and predictions.However,the inter-firm data transactions represent a novel challenge on pricing due to the complex nature of data,such as quality information asymmetry,lack of pricing standards,and the negligible marginal cost.This paper conducts a case study at Shanghai Data Exchange to explore the factors that can facilitate the data transactions between buyers and providers.We use interview transcripts from 18 participating firms to construct our three theoretical dimensions:increasing the perceived value,mitigating the cost,and improving the market design.We then browse through 18 factors to assess their value for further improvements.The managerial implications are also discussed.
