创新管理中的人工智能(AI)生成工具:关于创新管理者使用 ChatGPT 的研究

IF 4.1 3区 管理学 Q2 BUSINESS
Antonio Cimino, Alberto Michele Felicetti, Vincenzo Corvello, Valentina Ndou, Francesco Longo
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引用次数: 0

摘要

目的 利用人工智能加强创新管理专业人员的创造力和解决问题的能力,对于改善组织决策具有巨大的潜力。然而,有关创新管理者使用人工智能技术的研究还很缺乏。本研究采用挪用理论来探讨敏捷领导力(AL)、创新导向(IO)和个人创造力(IC)等特定因素如何影响创新经理对 ChatGPT(CGA)等生成性人工智能工具的使用。采用结构方程模型对数据进行了两步分析。首先,对测量模型进行评估,以确保构造的可靠性。研究结果研究结果表明,IO 和 IC 与 CGA 之间存在正相关关系,这表明那些具有强烈创新导向和较高个人创造力的创新经理更有可能采用 ChatGPT 并将其个性化。原创性/价值我们的研究结果对于寻求在创新管理中最大限度地发挥生成式人工智能潜力的组织具有重要意义。了解推动采用和定制生成式人工智能工具的因素,可以为更好地融入创新流程的战略提供信息,从而提高创新成果和改进决策流程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generative artificial intelligence (AI) tools in innovation management: a study on the appropriation of ChatGPT by innovation managers

Purpose

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

Design/methodology/approach

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

Findings

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Originality/value

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.

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来源期刊
CiteScore
8.20
自引率
8.70%
发文量
126
期刊介绍: ■In-depth studies of major issues ■Operations management ■Financial management ■Motivation ■Entrepreneurship ■Problem solving and proactivity ■Serious management argument ■Strategy and policy issues ■Tactics for turning around company crises Management Decision, considered by many to be the best publication in its field, consistently offers thoughtful and provocative insights into current management practice. As such, its high calibre contributions from leading management philosophers and practitioners make it an invaluable resource in the aggressive and demanding trading climate of the Twenty-First Century.
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