Internet of Things Platform Service Supply Innovation: Exploring the Impact of Overconfidence

Xiufeng Li and Zefang Li

Papers from arXiv.org

Abstract: This paper explores the impact of manufacturers' overconfidence on their collaborative innovation with platforms in the Internet of Things (IoT) environment by constructing a game model. It is found that in both usage-based and revenue-sharing contracts, manufacturers' and platforms' innovation inputs, profit levels, and pricing strategies are significantly affected by the proportion of non-privacy-sensitive customers, and grow in tandem with the rise of this proportion. In usage-based contracts, moderate overconfidence incentivizes manufacturers to increase hardware innovation investment and improve overall supply chain revenues, but may cause platforms to reduce software innovation; under revenue-sharing contracts, overconfidence positively incentivizes hardware innovation and pricing more strongly, while platform software innovation varies nonlinearly depending on the share ratio. Comparing the differences in manufacturers' decisions with and without overconfidence suggests that moderate overconfidence can lead to supply chain Pareto improvements under a given contract. This paper provides new perspectives for understanding the complex interactions between manufacturers and platforms in IoT supply chains, as well as theoretical support and practical guidance for actual business decisions.

Date: 2025-11
New Economics Papers: this item is included in nep-pay
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2511.01332 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2511.01332

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().