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Enregistrement W4415210040 · doi:10.1177/23294884251377038

Communication of Mission, Vision, and Goals: The Key to Successful Change Management in Changing Times

2025· article· en· W4415210040 sur OpenAlexaffabout
Eli Sopow, Maria Yuri Sushkova

Notice bibliographique

RevueInternational Journal of Business Communication · 2025
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueOrganizational Strategy and Culture
Établissements canadiensUniversity Canada West
Organismes subventionnairesnon disponible
Mots-clésVariance (accounting)Government (linguistics)Explanatory powerService (business)Change management (ITSM)Common-method varianceKey (lock)Regression analysisSurvey data collection

Résumé

récupéré en direct d'OpenAlex

The purpose of this study is to present new empirical evidence that communication of an organization’s mission, vision, and goals (MVG) is the strongest single predictor of successful change management during current environments of uncertainty. This study provides evidence from the 2022 to 2023 Canadian national Public Service Employees Survey (PSES) that successful communication of an organization’s mission, vision, and goals is the strongest statistically validated explanatory power of successful change among many commonly recommended change management actions with a direct benefit to addressing psychological safety and readiness for change. This paper applies a quantitative approach and analysis to selected scaled-answer data derived from the overall 2022 to 2023 Public Service Employee Survey of Canada (PSES, N = 189,584 employees within 90 federal government departments and agencies spread across Canada). The Statistical Product and Service Solutions (SPSS) software is used in applying linear regression analysis including confirmation of linearity, independence of errors, tests for collinearity, homoscedasticity, normality of residuals, correlations, and application of control variables. The research model explains that 87.1% of the variance in change management effectiveness is attributed to four factors. The most significant factor is effective communication of mission, vision, and goals ( r = .887, β = .507, p < .001, 53.43% unique contribution); followed by support for high service levels ( r = .834, β = .298, p < .008, 18.50% contribution); work contributes to goals ( r = . 466, β = .254, p < .007, 13.52% unique contribution), and having clear objectives ( r = .785, β = .182, p < .025, 6.86% unique contribution). The evidence also shows that while the strongest ratings of successful change are aligned with the above ratings of communicating a department’s mission, vision, and goals the reverse is true: Departments with below-average ratings for change management also show below-average ratings for communicating its mission, vision, values. The ability of organizations to adapt is critical in a time of rapid external and internal environmental change. This is especially true in national government departments where changing environments can impact such major factors as technology, healthcare, public safety, socio-economic conditions, the natural environment, and international relations. There is robust literature on many recommended processes and competencies linked to change management. However, this research presents new evidence from an analysis of a national government employee survey that the strongest predictive factor on well managed change is the effective communication of a workplace mission, vision, and goals. Inherent within this factor’s benefit is its impact on reducing the constituent parts of fear of change, namely a sense of powerlessness and the unknown. This paper’s findings present many direct social implications. For a start, the Canadian federal government directly touches the daily lives of over 40 million people be it through the provision of health care, employment, economic and immigration policies, public safety, international affairs, taxation, or pension programs. Federal governments are empowered and expected by society to offer safety, security, socio-economic advantages, trusted performance, fairness, and accountability. Similarly, private corporations and organizations are influenced by evolving regulatory and administrative frameworks, including Diversity, Equity, and Inclusion (DEI), Environmental, Social, and Governance (ESG) considerations as well as Corporate Social Responsibility (CSR) pressures. These demands, driven by employees, shareholders, society, and governments, emphasize the growing interconnection of organizational accountability and societal expectations. This paper proves new statistically grounded evidence that for organizational change to succeed, employees must first understand why and how an organization’s mission, vision, and goals play a critical role in change and specifically how the change will improve existing services, how work directly contributes to the goals, and is training commensurate with new needs. A failure to successfully achieve these results shows a concomitant lessening of change management success and may be an explanatory factor in high rates of change management failure as well as the presence of fear of change.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,785
Score d'incertitude au seuil0,284

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,277
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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