AI · Quantitative empirical study using descriptive and multivariate analysis of German Manufacturing Survey data.

Exploring AI adoption in manufacturing: An empirical study on effects of AI readiness

International Journal of Production Economics · 2025

Heidi Heimberger, Djerdj Horvat, Angela Jäger, Frank Schultmann

Summary

Both technological and organizational readiness are needed for AI adoption, yet a readiness-adoption gap remains; size has a U-shaped relationship with adoption and product complexity matters.

For your marketing

Possible founder application

Treat organizational change capacity and technical infrastructure as joint prerequisites; segment enterprise prospects by size and product complexity rather than assuming larger customers adopt faster.

Reported result

What the study found

Both technological and organizational readiness are needed for AI adoption, yet a readiness-adoption gap remains; size has a U-shaped relationship with adoption and product complexity matters.

Research question

What the authors investigated

How do technological and organizational AI readiness, separately and jointly, relate to AI adoption in manufacturing firms?

Design

Quantitative empirical study using descriptive and multivariate analysis of German Manufacturing Survey data.

Sample and setting

1,334 German manufacturing firms.

Scope and transfer

Limitations to keep in view

The evidence is manufacturing- and Germany-specific and observational; the abstract reports readiness/adoption associations, not randomized causal effects.

Research sources

Fetched Elsevier publisher page establishes title, authors, DOI, open-access status, 1,334-firm dataset, multivariate design, and abstract findings. Firecrawl research job 01a1436c-f86b-77df-af1c-9a2f87e3535e returned this citation and metadata.

Study strength

3.5/5 Abstract-level evidence is useful for framing questions; verify full methods before transfer.

How this was assessed

The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.

Design transparency · 2/2

Based on the reported study design in the retrieved source.

Sample and setting · 1/1

The sample context is stated; a numerical count is preserved only when reported.

Outcome clarity · 1/1

The finding is summarized from publisher or article metadata.

Access for checking · 0.5/1

Only abstract or bibliographic access was confirmed.

Double-blind? The retrieved publisher record does not establish whether participants or outcome assessors were blinded.

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