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Collaboration in scientific research : factors that Influence effective collaboration during a period of transformational change

2017· article· en· W2775837068 sur OpenAlexfundaboutno aff
Barbara T. Waruszynski

Notice bibliographique

RevueVIURRSpace (Vancouver Island University) · 2017
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueInterdisciplinary Research and Collaboration
Établissements canadiensnon disponible
Organismes subventionnairesFPInnovationsGovernment of CanadaAustralian GovernmentTechnische Universiteit EindhovenYale University
Mots-clésPeriod (music)Transformational leadershipPolitical sciencePublic relations
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In an era of fiscal restraint, federal science and technology organizations are promoting more advanced whole-of-government solutions to complex problems through effective intra-organizational and inter-organizational collaboration. Although the literature reveals that there are several factors which influence the effectiveness of collaborations, there remains a major gap in determining which factors affect researchers’ attitudes and behaviours to collaborate during periods of organizational change. This ethnographic study aims to bridge this gap by: (1) identifying the factors that influence researchers’ attitudes and behaviours in scientific research collaborations; (2) establishing if these factors affect team outputs and outcomes; and (3) understanding if organizational change impacts the effectiveness of research collaborations. \n \nTheories on teamwork, collaboration, social interdependence, social systems, and organizational change are incorporated to examine effective collaboration practices in one case study. The Canadian Wood Fibre Centre (CWFC) under the Canadian Forest Service (CFS) within Natural Resources Canada (NRCan) is the case under study, and is employed to understand the effectiveness of scientific research collaborations during a period of transformational change. Twenty-six participants took part in this qualitative study, including 13 researchers and 13 managers. \n \nBased on interviews with federal researchers and managers, and industry managers, and a focus group with federal managers, the findings reveal that there are several factors that influence effective collaborations: (1) collaborative culture (e.g., shared vision, governance, and values of mutual trust and respect); (2) leadership (i.e., visionary, collective, and team leadership); (3) human and financial resources; (4) team integration and synergy (i.e., shared commitment and team cohesion); (5) shared communications (e.g., face-to-face communications); and (6) interpersonal relationships that are enabled by social interdependence. \n \nThe findings also suggest that the above factors positively influence the quality of collaborative team performance in the following ways: (1) ability for researchers to work in a collaborative culture through a shared vision, an established governance, and values; (2) visionary, collective, and team leadership styles that enable an integrated collaborative environment and goal attainment; (3) human and financial resources that support the right team composition and funding to successfully complete the projects; (4) team synergy for accomplishing goals and generating good quality outputs; (5) shared communications to foster greater information sharing and trust between researchers; and (6) social interdependence to nurture relationships over time. Team viability is dependent on how well the team performed together to achieve its project goals, and if researchers trusted each other and shared information throughout the collaboration. Individual and team satisfaction is based on participants’ overall contentment (individually and as a team) in producing scientific or client-related outputs and outcomes. \n \nThis study has also shown that organizational changes have an impact on the factors that influence effective collaboration. The findings suggest that effective collaboration is contingent on researchers’ adaptability to organizational change. Although the transformation of the forest sector generally fostered positive change, there were specific factors of organizational change that challenged the effectiveness of collaborations. These factors include: (1) the lack of integrated research programs and processes between the CWFC and its main industry partner; (2) new government administrative processes that impacted scientific productivity; and (3) the lack of face-to-face interactions due to government travel restrictions. \n \nBased on the literature review and this doctoral study, a new model on collaboration is proposed and provides a list of factors that are considered to be important in facilitating effective collaboration. Additional research is required to better unfold the interrelationships between these factors and how their interrelationships impact effective collaboration, particularly during periods of organizational change. Recommendations are put forward on how to improve collaboration in the workplace and are intended to inform departmental policies, practices, and programs on ways to enable better collaboration. Recommendations are also suggested for the conduct of future research on team science and propose ways to improve collaboration in scientific research.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,060
score de la tête « metaresearch » (Gemma)0,178
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Incitatifs · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,940
Score d'incertitude au seuil0,320

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0600,178
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,003
Études des sciences et des technologies0,0170,013
Communication savante0,0130,007
Science ouverte0,0020,014
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,067
Tête enseignante GPT0,372
Écart entre enseignants0,305 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeQualitatif
DomaineIncitatifs
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

Citations6
Publié2017
Routes d'admission2
Résumé présentoui

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