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Record W4287958210 · doi:10.1108/cr-03-2022-0037

OFDI activity and urban-regional development cycles: a co-evolutionary perspective

2022· article· en· W4287958210 on OpenAlexafffund
Harald Bathelt, Maximilian Buchholz, John Cantwell

Bibliographic record

VenueCompetitiveness Review An International Business Journal incorporating Journal of Global Competitiveness · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIncentiveForeign direct investmentConceptualizationEconomicsOriginalityValue (mathematics)Perspective (graphical)Virtuous circle and vicious circleEconomic geographyEconomic systemDevelopment economicsMarket economyMacroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Purpose While conventional views of foreign investment activity primarily relate to efficiency-seeking investments, the authors argue that most other outward foreign direct investments (OFDIs) likely have positive effects on income development in the home region. Data on the US urban system not only illustrates this but also shows that this impact is not equal in all city-regions. The purpose of this paper is to develop an explanation as to why high- and low-income cities are associated with self-reinforcing cycles of OFDI activity that have different home-region impacts. Design/methodology/approach Conventional views assume that inward foreign direct investments (IFDIs) have a positive impact on target regions, while OFDIs are often treated as the flip side of this story, being seen as having negative effects by shifting jobs and income abroad. This paper counters this logic by developing a conceptual argument that systematically distinguishes different types of OFDIs and relates them to economic development effects in the home (investing) region. Findings Using a co-evolutionary conceptualization, this paper suggests that many high-income cities are characterized by a virtuous cycle of development where high, successful OFDI activity generates both positive income effects as well as incentives to engage in further OFDIs in the future, thus leading to additional income increases. In contrast, it is suggested that low-income cities are characterized by what we refer to as vicious cycles of development with low OFDI activity, few development impulses and a lack of incentives and capabilities for future investments. Originality/value This paper develops a counter-perspective to conventional views of OFDI activity, arguing that these investments have a positive impact on regional income levels. The authors develop a spatially sensitive explanation which acknowledges that OFDIs do not trigger a linear process but are associated with diverging inter-urban development paths and may contribute to higher levels of intra-urban inequality. From these findings, the authors derive conclusions for future research and public policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.289
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2022
Admission routes2
Has abstractyes

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