Flipping the odds of AI-driven open innovation: The effectiveness of partner trustworthiness in counteracting interorganizational knowledge hiding

Jose Arias-Pérez, Thanh Huynh

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This paper aims to analyze the negative effect of knowledge hiding on the relationship between artificial intelligence (AI) capability and open innovation (inbound and outbound) when partner trustworthiness (benevolence, integrity, and ability) is high. Structural equations were used to test this three-way interaction with survey data from a sample of 229 firms, mainly from highly digitalized sectors. The findings indicate that interorganizational knowledge hiding affects only the relationship between AI capability and outbound open
innovation and that partner ability is the only factor that will counteract this negative effect. Therefore, co-exploitation of AI-based solutions with external allies is the sole scenario to encourage knowledge hiding by increasing employees' perceptions of the likelihood of AI negatively impacting their personal interests at work. Moreover, when trustworthiness is at the forefront of the intraorganizational discussion, the findings downplay the significance of
benevolence and integrity as traits that significantly reduce knowledge hiding. In contrast, at the interorganizational level, knowledge hiding is lessened only when employees perceive that co-exploitation with external partners represents an opportunity to learn and capture crucial AI knowledge.
Original languageEnglish
Pages (from-to)30-40
Number of pages11
JournalIndustrial Marketing Management
Volume111
Early online date28 Mar 2023
DOIs
Publication statusPublished - May 2023

Funder

This work was supported by Universidad de Antioquia under project number 2022-47671

Keywords

  • Partner trustworthiness
  • Partner ability
  • Knowledge hiding
  • Artificial intelligence capability
  • Open innovation
  • Digital transformation

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