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Record W3110314978 · doi:10.5267/j.msl.2020.11.021

Do stakeholders matter? Stakeholders as moderators in the relationship between formal strategic plan-ning and organizational performance

2020· article· en· W3110314978 on OpenAlexvenueno aff
Naseem Mohammad Twaissi, Jehad Aldehayyat

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsModerationStrategic planningBusinessStakeholderStructural equation modelingOrganizational performanceKnowledge managementTest (biology)Sample (material)Empirical researchProcess managementMarketingPsychologyManagementComputer scienceEconomicsSocial psychology

Abstract

fetched live from OpenAlex

In this globalized world, every company is struggling to sustain and improve its performance. This study investigated the role of formal strategic planning on organizational performance. Moreover, this relation is explored further with the moderation of stakeholders’ involvement. The empirical data were collected from 220 chief executives or general managers of manufacturing companies using a questionnaire survey. AMOS software was used to analyze the collected data. Structural equation modeling (SEM) was conducted to test the hypothesis, and moderation was investigated using a slop test. The results of the study revealed that formal strategic planning could enhance the performance of the organization. Furthermore, the results highlighted that stakeholder's involvement could strengthen the relationship between formal strategic planning and organizational performance. Previous studies have highlighted the importance of overall strategic management in enhancing an organization's performance. The research also revealed that performance was affected mainly by formal strategic planning and stakeholder involvement. The study used manufacturing companies in Jordan. Moreover, the data was collected from 220 respondents. Therefore, future studies should be conducted from any other country's perspective and use a larger sample size. This study has used moderation of stakeholder's involvement to get more specific results. Future studies should use organizational culture as a moderating variable.

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 score0.038
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.003
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 head0.132
GPT teacher head0.246
Teacher spread0.115 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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