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Record W7087425553 · doi:10.1108/jmtm-11-2024-0642

Driving new product development performance: the mediating role of absorptive capacity in open innovation for SMEs

2025· article· en· W7087425553 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Manufacturing Technology Management · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAbsorptive capacityDimension (graph theory)New product developmentDynamic capabilitiesOpen innovationConceptual modelIdentification (biology)Structural equation modelingSurvey data collection

Abstract

fetched live from OpenAlex

Purpose This study investigates the impact of the outside-in dimension of open innovation (OIO) on new product development (NPD) performance in technology-based small and medium-sized enterprises (SMEs), isolating a dimension often conflated with outbound and coupled strategies. Design/methodology/approach Drawing on survey data from 342 SMEs in Sweden and Slovakia, partial least squares structural equation modeling (PLS-SEM) is applied to test a conceptual framework grounded in the knowledge-based view (KBV) and the dynamic capabilities view (DCV), examining the mediating roles of potential absorptive capacity (PAC) and realized absorptive capacity (RAC) and the moderating role of trust. Findings OIO is found to significantly enhance NPD performance, both directly and indirectly, through PAC and RAC, with PAC identified as the stronger mediator. Trust strengthens the direct OIO–NPD link but does not significantly moderate the PAC–NPD or RAC–NPD relationships. This suggests that trust is more critical during the external knowledge acquisition phase than during the internal stages of knowledge transformation and application. Practical implications For managers, the study’s findings highlight the need to develop PAC and RAC as dynamic routines within the firm to help sense and transform external knowledge while developing trust-based collaborations with external partners during early innovation stages to maximize OIO benefits. Examples of such collaborations include partnering with local research institutions for early knowledge identification and deploying digital technologies to accelerate collaboration and shorten NPD cycles. Originality/value This study advances open innovation research by isolating the outside-in dimension and integrating the KBV and DCV to explain how external knowledge inflows are sensed, seized and transformed into product innovation outcomes. The study confirms the dual role of absorptive capacity as both a knowledge-based resource and a dynamic capability, positioning trust as a key relational enabler for SMEs during the knowledge acquisition phase.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.230
Teacher spread0.187 · 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