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The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery

32
Citations
January 1, 2025
Published Date

Research Abstract & Technology Focus

AbstractThis research analyses managers’ perceptions of the multiple types of artificial intelligence (AI) required at each stage of the business‐to‐business (B2B) service recovery journey for successful human–AI collaboration in this context. Study 1 is an exploratory study that identifies managers’ perceptions of the main stages of a B2B service recovery journey based on human–AI collaboration and the corresponding roles of the human–AI collaboration at each stage. Study 2 provides an empirical examination of the proposed theoretical framework to identify the specific types of intelligence required by AI to enhance performance in each stage of B2B service recovery, based on managers’ perceptions. Our findings show that the prediction stage benefits from collaborations involving processing‐speed and visual‐spatial AI. The detection stage requires logic‐mathematical, social and processing‐speed AI. The recovery stage requires logic‐mathematical, social, verbal‐linguistic and processing‐speed AI. The post‐recovery stage calls for logic‐mathematical, social, verbal‐linguistic and processing‐speed AI.
human machine collaboration managers perceptions leveraging
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Frequently Asked Questions (FAQ)

Curated market intelligence mapped to this research.

What is the core focus of the research titled 'The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery'?

This literature focuses on: AbstractThis research analyses managers’ perceptions of the multiple types of artificial intelligence (AI) required at each stage of the business‐to‐business (B2B) service recovery journey for successful human–AI collaboration in this context. Stu...

Are there open-source GitHub repositories related to The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery?

Yes, open-source projects like slowmist/openclaw-security-practice-guide (This guide is designed for OpenClaw itself (Agent-facing), not as a traditional human-only hardening checklist.) are actively building upon these concepts.

Which startups are commercializing the technology behind The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery?

Products like Superset are bringing this to market. Their focus is: Run an army of Claude Code, Codex, etc. on your machine.

What other academic literature is closely related to 'The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery'?

Yes, highly correlated activity was mapped. An entry titled 'AI–Human Hybrids for Marketing Research: Leveraging Large Language Models (LLMs) as Collaborators' discusses this: The authors’ central premise is that a human–LLM (large language model) hybrid approach leads to efficiency and effectiveness gains in the marketin...

Are there commercial applications of 'The Rise of Human–Machine Collaboration: Managers’ Perceptions of Leveraging Artificial Intelligence for Enhanced B2B Service Recovery' in market news publications?

Yes, highly correlated activity was mapped. An entry titled 'The Oz Paradigm: Why AI Still Needs a Human Behind the Curtain' discusses this: AI agents can scale marketing execution, but they cannot replace human judgment. Discover why B2B marketers must guide, verify, and strategically d...

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