MétaCan
Menu
Back to cohort
Record W2956910742 · doi:10.1108/jbim-11-2018-0330

Environmental turmoil and firms’ core structure dynamism: the moderating role of strategic alliances

2019· article· en· W2956910742 on OpenAlexaff
Rui Xue, Gongming Qian, Zhengming Qian, Lee Li

Bibliographic record

VenueJournal of Business and Industrial Marketing · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsYork University
Fundersnot available
KeywordsDynamismBusinessCore competencyMarketingIndustrial organizationStrategic allianceAllianceOutsourcingStrategic management

Abstract

fetched live from OpenAlex

Purpose Much of the extant evidence in the marketing literature posits that firms use strategic alliances to share resources, costs and risks as paths to performance improvements. Drawing from the organizational ecology theory, this study aims to propose a different rationale, namely, that strategic alliances protect a firm’s core structure – its stated goals, authority structure, core technologies and marketing strategies – by mitigating the need for hazardous changes in hostile environments. Design/methodology/approach This study collected quantitative data using market survey and analyzed the data with the regression method. Findings Using Chinese firms in three technology industries as the research setting, this research finds a positive and significant relationship between environmental hostility and core structure dynamism. Although strategic alliances themselves have no direct bearing on core structure dynamism, they are found to moderate this relationship negatively, that is, strategic alliances attenuate the relationship between environmental hostility and structural changes. Research limitations/implications This paper argues that strategic alliances have significant moderating effects on firm performance, that is, firms use strategic alliances to outsource competence to partners and, thus, avoid internal turmoil. However, the moderating effect alone cannot explain the complexity of strategic alliances. There could exist other effects that remain unknown. In addition, individual-level factors could have significant impacts on strategic alliance management. Future studies should look into these issues to advance the authors’ knowledge on strategic alliances. Practical implications The findings of this study show that managers should outsource competence to partners when they experience turmoil in markets. Adapting to market turmoil internally could lead to market failure. Originality/value This study provides a new rationale for strategic alliances, that is, firms use strategic alliances to reduce market uncertainty. This rationale has not been reported in the existing literature.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.207
Teacher spread0.178 · 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 teacher head, 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

Citations19
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Business and Industrial MarketingSame topicInnovation and Knowledge ManagementFrench-language works237,207