Artificial intelligence-driven digital servitization: The importance of platform characteristics and firm-level factors

IF 7.5 1区 管理学 Q1 BUSINESS
Minna Saunila, Tero Rantala, Juhani Ukko
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引用次数: 0

Abstract

This study explores the connection between artificial intelligence (AI) platform characteristics and digital servitization. The study further investigates how firm-related factors influence this connection. The AI platforms that firms utilize are industrial digital platforms that employ AI-based tools to support their operations. Digital servitization has become a common transformation in several industries collaborating with platforms and seeking ways to establish ecosystems. AI provides substantial opportunities for digital servitization to create revenue streams and improve performance by reducing costs and enhancing customer outcomes. However, the underlying characteristics of the AI platforms that support firms' digital servitization have seldom been explored among small and medium-sized enterprises (SMEs). Based on survey data collected from 179 SMEs, this study conceptualizes five characteristics as drivers of AI platform utilization and investigates their impact on digital servitization using multiple regression analyses. First, this study develops an AI platform characteristic construct. Second, the study builds a theoretical framework showing which AI platform characteristics leverage digital servitization. Ultimately, this research contributes to the understanding of the connections between AI platform characteristics and digital servitization.
人工智能驱动的数字化服务化:平台特征和企业层面因素的重要性
本研究探讨人工智能(AI)平台特征与数字化服务化之间的关系。该研究进一步探讨了企业相关因素如何影响这种联系。企业使用的人工智能平台是采用基于人工智能的工具来支持其运营的工业数字平台。数字化服务化已经成为许多行业与平台合作并寻求建立生态系统的共同转型。人工智能为数字服务化提供了大量机会,通过降低成本和提高客户成果来创造收入流和提高绩效。然而,支持企业数字化服务化的人工智能平台的潜在特征很少在中小企业中进行探索。基于179家中小企业的调查数据,本研究定义了人工智能平台利用的五个驱动因素,并使用多元回归分析调查了它们对数字化服务化的影响。首先,本研究开发了人工智能平台特征构建。其次,构建了一个理论框架,展示了哪些人工智能平台特征利用了数字服务化。最终,本研究有助于理解人工智能平台特征与数字化服务化之间的联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
17.30
自引率
20.40%
发文量
255
期刊介绍: Industrial Marketing Management delivers theoretical, empirical, and case-based research tailored to the requirements of marketing scholars and practitioners engaged in industrial and business-to-business markets. With an editorial review board comprising prominent international scholars and practitioners, the journal ensures a harmonious blend of theory and practical applications in all articles. Scholars from North America, Europe, Australia/New Zealand, Asia, and various global regions contribute the latest findings to enhance the effectiveness and efficiency of industrial markets. This holistic approach keeps readers informed with the most timely data and contemporary insights essential for informed marketing decisions and strategies in global industrial and business-to-business markets.
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