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Enregistrement W4306759283 · doi:10.1093/acrefore/9780190224851.013.253

A Practice-Based View of Innovation Adoption

2022· reference-entry· en· W4306759283 sur OpenAlexaff
Rangapriya Kannan, Paola Perez-Aleman

Notice bibliographique

RevueOxford Research Encyclopedia of Business and Management · 2022
Typereference-entry
Langueen
DomaineBusiness, Management and Accounting
ThématiqueInnovative Approaches in Technology and Social Development
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésKnowledge managementBusinessContext (archaeology)Organizational learningAdaptation (eye)Process (computing)Resource (disambiguation)Organizational culturePublic relationsComputer sciencePolitical sciencePsychology

Résumé

récupéré en direct d'OpenAlex

Abstract Innovation adoption is challenging at both intra-organizational and interorganizational levels. Several decades of innovation adoption research have identified various barriers at both levels. Intra-organizational barriers are often related to the characteristics of the innovation, adopters, managers, environment, and ecosystem but can also include an incompatibility with an organization’s strategy, structural impediments, organizational resource constraints, a lack of fit of the innovation with an organizational culture and climate, decision making challenges, a lack of integration with an organization’s knowledge management, human resource management practices, dynamic capabilities, and active innovation resistance from customers. Interorganizational barriers include uncertainty with learning and implementation, the distributed nature of the innovation process, differences in production systems, disparities in regulatory systems, variation within local contexts, and the nature of embedded knowledge adopted in diverse organizational contexts. One of the key missing aspects in understanding innovation adoption is how extant practices within an organizational or interorganizational context enhance or hinder innovation adoption. Although the practices of innovation adoption emerge and evolve dynamically, existing research does not highlight fine-grained practices that lead to its success or failure. A practice lens focuses on people’s recurrent actions and helps to understand social life as an ongoing production that results from these actions. The durability of practices results from the reciprocal interactions between agents and structures that are embedded within daily routines. A practice lens allows us to study practices from three different perspectives. The first perspective, empirically explores how people act in organizational contexts. The second, a theoretical focus investigates the structure of organizational life. This perspective also delves into the relations between the actions that people take over time and in varying contexts. Finally, the third perspective which is a philosophical one focuses on how practices reproduce organizational reality. By focusing on the unfolding of constellations of everyday activities in relation to other practices within and across time and space, a practice lens hones in on everyday actions. Everyday actions are consequential in producing the structural contours of social life. A practice lens emphasizes what people do repeatedly and how those repetitive actions impact the social world. A practice theory lens also challenges the assumption that things are separable and independent. Instead, it focuses on relationality of mutual constitution to understand how one aspect of the issue creates another aspect. Relationality of mutual constitution is the notion that things such as identities, ideas, institutions, power, and material goods take on meaning only when they are enacted through practices instead of these being innate features of these things Focusing on duality forces us to address the assumptions that underlie the separation. A practice perspective on innovation adoption highlights the concepts of duality, dynamics, reciprocal interactions, relationality, and distributed agency to inform both the theory and practice of innovation adoption. Understanding these concepts enables a practice lens for successful adoption of innovations that impact organizational and societal outcomes, such as economic development, productivity enhancement, entrepreneurship, sustainability, equity, health, and other economic, social, and environmental changes.

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)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,947
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0030,007
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
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 Opus0,063
Tête enseignante GPT0,318
Écart entre enseignants0,255 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

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

En bref

Citations3
Publié2022
Routes d'admission1
Résumé présentoui

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