人工智能能力和绿色创新对可持续绩效的影响:大数据和知识管理的调节作用

IF 12.9 1区 管理学 Q1 BUSINESS
Hussam Al Halbusi , Khalid Ibrahim Al-Sulaiti , Ali Abdallah Alalwan , Adil S. Al-Busaidi
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引用次数: 0

摘要

本研究探讨了工业对环境的影响,重点是导致生态系统退化的资源消耗增加和废物产生。它提倡将可持续实践和循环经济(CE)作为减轻这些影响的战略。因此,本研究探讨了人工智能(AI)能力如何直接影响绿色创新及其对可持续绩效和循环经济的后续影响。此外,研究还引入了人工智能能力与绿色创新关系中的两个关键调节因素--大数据分析和知识管理系统。我们利用卡塔尔各行业的多部门人口数据验证了该模型,并采用结构方程建模(SEM)和人工神经网络(ANN)作为分析方法。结果表明,人工智能能力对绿色创新产生了重大影响,这些创新与可持续绩效和消费总值密切相关。值得注意的是,与大数据分析和知识管理系统的互动增强了人工智能能力的积极影响。因此,本研究强调了人工智能对绿色创新、塑造可持续绩效和首席执行官的显著影响。将大数据分析和知识管理系统确定为重要的调节因素增加了研究的复杂性。研究结果指导各行业在实际应用中整合人工智能、大数据分析和知识管理系统,强调以整体方法促进各行业的环境责任实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI capability and green innovation impact on sustainable performance: Moderating role of big data and knowledge management
This study addresses the environmental impact of industries by focusing on increased resource consumption and waste generation that lead to ecosystem degradation. It advocates sustainable practices and a circular economy (CE) as strategies to mitigate these effects. Thus, the study examines how Artificial Intelligence (AI) capabilities directly affect green innovations and their subsequent influence on sustainable performance and CE. In addition, it introduces two key moderating factors—big data analytics and knowledge management systems—in the relationship between AI capabilities and green innovation. We validate the model using multi-sectoral population data from various Qatari industries and employ structural equation modeling (SEM) and artificial neural networks (ANN) as analytical approaches. The results indicate the significant impact of AI capability on green innovation, with these innovations critically linked to sustainable performance and CE. Remarkably, interactions with big data analytics and knowledge management systems enhance the positive impact of AI capabilities. Hence, this study emphasizes AI's noteworthy implications for green innovation, shaping sustainable performance, and CE. Identifying big data analytics and knowledge management systems as vital moderators adds complexity. The findings guide industries to integrate AI, big data analytics, and knowledge management systems for practical applications, stressing a holistic approach to promoting environmentally responsible practices across sectors.
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来源期刊
CiteScore
21.30
自引率
10.80%
发文量
813
期刊介绍: Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.
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