Exploring AI-enabled digital service platform adoption in industrial business-to-business firms through a mixed-method approach

IF 7.3 1区管理学 Q1 BUSINESS

Industrial Marketing Management Pub Date : 2026-05-01 Epub Date: 2026-05-23 DOI:10.1016/j.indmarman.2026.04.003

Ruchi Mishra , Rajesh Kr Singh

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引用次数: 0

Abstract

Despite the increasing applications of artificial intelligence (AI)-enabled digital service platforms in business-to-business (B2B) industrial marketing, studies in this domain remain limited, especially in the context of AI-enabled platforms in industrial settings and emerging economies, such as India. To address this gap, the present study employs an exploratory sequential mixed-methods design. In the first phase, exploratory focus group interviews were conducted with industry practitioners to identify context-specific factors influencing the adoption of AI-enabled digital service platforms. Thereafter, using the insights from this phase, a conceptual model was developed that extends the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) by incorporating perceived service quality and transformational leadership. In the second phase, the proposed framework was empirically analysed using survey data from 300 industrial B2B firms through covariance-based structural equation modelling.

The findings reveal that perceived ease of use, perceived usefulness, and perceived service quality significantly influence user attitudes, while perceived service quality, subjective norms, and attitude shape the behavioural intention to adopt AI-enabled digital service platforms. The study also suggests a mediated relationship between transformational leadership and attitude, facilitated by the perceived ease of use and usefulness. Furthermore, the research highlights the mediating role of attitude in the relationship between perceived service quality and the intention to use these platforms. The study contributes by extending TAM and TPB through the integration of transformational leadership and service quality, and by contextualising AI-enabled platform adoption within an emerging market B2B industrial setting and provides actionable guidance for practitioners and decision-makers.

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通过混合方法探索工业企业对企业采用人工智能支持的数字服务平台

尽管支持人工智能（AI）的数字服务平台在企业对企业（B2B）工业营销中的应用越来越多，但这一领域的研究仍然有限，特别是在工业环境和新兴经济体（如印度）中支持人工智能的平台的背景下。为了解决这一差距，本研究采用探索性顺序混合方法设计。在第一阶段，对行业从业者进行了探索性焦点小组访谈，以确定影响采用人工智能数字服务平台的特定环境因素。此后，利用这一阶段的见解，开发了一个概念模型，通过将感知服务质量和变革型领导结合起来，扩展了技术接受模型（TAM）和计划行为理论（TPB）。在第二阶段，通过基于协方差的结构方程模型，对300家工业B2B企业的调查数据进行了实证分析。研究结果显示，感知易用性、感知有用性和感知服务质量显著影响用户态度，而感知服务质量、主观规范和态度塑造了采用人工智能数字服务平台的行为意愿。研究还表明，变革型领导与态度之间存在中介关系，在感知易用性和有用性的促进下。此外，研究还强调了态度在感知服务质量与使用平台意愿之间的中介作用。该研究通过整合变革型领导力和服务质量来扩展TAM和TPB，并通过在新兴市场B2B行业环境中采用人工智能支持的平台，为从业者和决策者提供可操作的指导。

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

Industrial Marketing Management Multiple-

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.