My manuscript examines how AI investment affects international firm performance through innovation, with environmental uncertainty as a boundary condition. Identify journals that are a strong fit for the topic, theory, and methodology, and compare their indexing, research scope, and key journal metrics.

Target Journals for AI Investment and International Firm Performance

Journal	Fit with the manuscript	Theoretical and methodological alignment	Indexing and supplied metric
Journal of World Business	Very strong fit for research on AI investment and international firm performance, particularly when firms, countries, or subsidiaries are compared across institutional and environmental contexts.	Strongest when the manuscript develops an international-business explanation of how AI investment produces performance advantages through innovation and when environmental uncertainty varies across markets. Quantitative panel, cross-country, multi-level, and moderated-mediation designs are suitable.	Indexed in Scopus; the supplied Scopus profile reports a CiteScore of 17.0 Scopus source profile.
International Business Review	Very strong fit if the study emphasizes internationalization, country-level uncertainty, institutional conditions, or differences between domestic and international firms.	Appropriate for contingency and mechanism-based models. The manuscript should make the international setting theoretically necessary rather than using international firms merely as the empirical sample. Survey, panel, archival, and structural-equation methods are common fits.	Indexed in Scopus; the supplied profile reports a CiteScore of 19.2 Scopus source profile.
Global Strategy Journal	Very strong fit when AI investment is framed as a strategic resource that changes firms’ innovation capabilities and international competitive positioning.	Particularly suitable for resource-based, dynamic-capabilities, organizational-learning, and nonmarket or environmental-contingency arguments. The contribution should explain how uncertainty changes the value or deployment of AI rather than treating uncertainty only as a statistical interaction.	Indexed in Scopus; the supplied profile reports a CiteScore of 15.7 Scopus source profile.
Management International Review	Strong fit for a rigorously designed international-management study with a clear mediation mechanism and cross-national or multinational-firm evidence.	A good option for moderated mediation involving innovation and environmental uncertainty, especially with panel data, multi-country samples, or comparative institutional analysis. The theoretical contribution may need to be more focused and empirically disciplined than in a strategy-oriented outlet.	Indexed in Scopus; the supplied profile reports a CiteScore of 15.0 Scopus source profile.
Research Policy	Strong but theory-demanding fit if AI investment is conceptualized as an innovation input, capability, or technological transformation mechanism.	Best when the paper makes a substantial innovation-theory contribution—for example, explaining how AI investment affects innovation productivity, recombination, knowledge development, or technological upgrading. A firm-performance outcome alone is unlikely to be sufficient; the innovation mechanism must be central and convincingly measured.	Indexed in Scopus; the supplied profile reports a CiteScore of 26.3 Scopus source profile.
Technological Forecasting and Social Change	Strong fit when the manuscript foregrounds AI adoption, technological change, digital transformation, and uncertainty surrounding emerging technologies.	Well suited to large-sample archival, survey, panel, configurational, and predictive designs. The paper should connect AI investment to innovation and performance while explaining how uncertainty affects technological value realization, rather than presenting AI simply as a new explanatory variable.	Indexed in Scopus; the supplied profile reports a CiteScore of 11.6 Scopus source profile.
Journal of International Business Policy	Conditional fit if environmental uncertainty is tied to policy, institutions, regulation, geopolitical conditions, or national differences affecting AI investment and innovation.	Appropriate when the manuscript has clear implications for international policy or institutional governance. It is less suitable if environmental uncertainty is measured only as generic market volatility without a policy or institutional dimension.	The supplied materials include the journal’s publisher page, but no corresponding CiteScore value; the metric therefore remains unverified here.
Long Range Planning	Conditional fit if the study emphasizes strategic decision-making, long-term capability development, and managerial consequences of AI investment.	Suitable for a strategic-management framing, particularly dynamic capabilities and strategic flexibility under uncertainty. The manuscript would need a more explicit strategic-choice contribution than a conventional mediation test.	The supplied materials include article-level publisher records, but no verified journal-level indexing or metric record; these should be checked before submission.

Recommendation. The best initial targets are Journal of World Business, International Business Review, and Global Strategy Journal . Choose Journal of World Business if the manuscript’s central contribution is an international-business explanation of how AI investment generates performance through innovation across markets. Choose International Business Review if the main value lies in the international setting, cross-country heterogeneity, or institutional and environmental contingencies. Choose Global Strategy Journal if the paper is primarily about AI as a strategic capability and environmental uncertainty as a condition that changes its value.

Research Policy becomes the strongest alternative when innovation—not international performance—is the principal theoretical contribution. Its identifying assumption is that the paper advances innovation theory rather than merely using innovation as a mediator. Technological Forecasting and Social Change is preferable when the manuscript’s empirical contribution concerns AI adoption and technological transformation and uses a broad quantitative or predictive methodology. Its identifying assumption is that the technology-and-uncertainty context is central to the paper’s explanation.

For the stated model, the manuscript should make the causal sequence explicit: AI investment \to innovation capability or output \to international firm performance, with environmental uncertainty moderating either the first link, the second link, or the full indirect effect. The target journal should follow that theoretical emphasis. A generic moderated-mediation model with limited international theorizing would be a weak fit for the top international-business outlets, even if the dataset contains multinational firms. Conversely, a strong international setting with a superficial treatment of innovation would weaken the case for Research Policy .

The supplied evidence verifies Scopus profiles and CiteScore values for the six journals linked to Scopus source records, but it does not verify Web of Science coverage, quartile rankings, acceptance rates, or the latest journal impact factors. Those metrics should be checked in the relevant indexing databases and the journals’ current author guidelines before submission.

2026年9月17日 07:15

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