AI Inter-organizational research

As artificial intelligence (AI) increasingly mediates inter-organizational decision-making, concerns arise about how algorithmic opacity reshapes trust, information sharing, and cooperation between firms. This study investigates the relational consequences of AI-supported negotiation, focusing on explainability as a sociotechnical governance mechanism. Using a dyadic negotiation experiment involving 76 professional dyads across three global software providers, we compare human-only negotiation with opaque (black-box) AI and explainable AI (XAI) decision-support systems. Results show that black-box AI significantly reduces partner-directed trust, voluntary information sharing, and subjective satisfaction, despite improving negotiation efficiency. In contrast, explainable AI restores—and in some cases enhances—relational outcomes, yielding higher trust, earlier cooperative gestures, and greater willingness to disclose strategic information. Moderated mediation analyses reveal that explainability mitigates the negative indirect effect of AI on satisfaction through trust. These findings demonstrate that explainability is not merely a technical usability feature but a relational requirement that shapes how organizations interpret intentions and evaluate fairness in AI-mediated collaboration. By articulating explainability as a relational governance mechanism, this study advances theory on AI-enabled cooperation and offers practical guidance for the responsible design of negotiation and procurement systems in digitally mediated inter-organizational environments随着人工智能（AI）愈发广泛地介入组织间决策，算法不透明性如何重塑企业间的信任、信息共享与合作模式，这一问题引发了诸多担忧。本研究围绕AI辅助谈判的关系性后果展开探究，将可解释性视作一种社会技术治理机制作为核心分析视角。本研究依托一项双边谈判实验展开：实验招募了来自三家全球软件供应商的76组专业搭档，对比了纯人工谈判、不透明（黑箱）AI决策支持系统与可解释AI（XAI）决策支持系统三种情境下的谈判结果。实验结果表明，尽管黑箱AI能够提升谈判效率，却会显著降低针对合作方的信任度、自愿信息共享意愿与主观满意度。与之形成鲜明对比的是，可解释AI不仅能够修复（甚至在部分场景下优化）关系性结果，具体表现为更高的信任水平、更早出现的合作姿态，以及更强的战略信息披露意愿。有调节的中介分析结果显示，可解释性能够通过信任这一路径，削弱AI对满意度产生的负向间接影响。上述研究结果表明，可解释性并非仅仅是一项技术可用性功能，而是一项关系性要求——它能够塑造组织在AI介导的协作中解读合作意图与评估公平性的方式。本研究将可解释性明确为一种关系性治理机制，既推动了AI赋能型合作领域的理论发展，也为数字化介导的组织间环境下的谈判与采购系统的负责任设计提供了实践指引。