Notice bibliographique
Résumé
<p>The purpose of this research is to refine the notion of Supply Chain Orientation (SCO) as originally posited by Mentzer et al. (2001) and Min and Mentzer (2004). Supply chain orientation is defined to be “the extent to which there is a predisposition among chain members toward viewing the supply chain as an integrated entity and on satisfying chain needs in an integrated way” (Hult et al., 2008, p. 527). This orientation (management philosophy), when implemented, manifests as Supply Chain Management (SCM) within and across organizations.</p> \n \n<p>The process of ‘refining’ supply chain orientation involved three stages: determining additional SCO factors / indicators beyond those already in existence, refining the total set of factors / indicators through factor analysis techniques, and associating the SCO concept to other SCM-related concepts. Determining additional SCO factors and the vetting of the existing SCO model was done through a qualitative method (structured interviews with industry experts). Analysis of the interview data resulted into two new SCO factors—SCM Capability and Measurement Propensity—being identified. The high accuracy / low generalizability nature of the interview process required an industrywide survey in order to gather su cient quantitative data for a meaningful analysis. The new SCO factors were developed into survey questionnaire measurement items.</p> \n \n<p>An invitation to participate in a web-based, quantitative survey was e-mailed to executive at roughly a third of the manufacturing companies in Canada. The results of that data gathering exercise were analyzed in a multi-stage process. First, after removing ‘motherhood statements’ from the indicator set, an exploratory factor analysis (EFA) was conducted to determine the underlying structure of SCO. Three factors—Benevolence (Trust), Internal SCM Focus, and Partner Reliability—emerged through this process. This “refined” SCO construct was then subject to a rigourous confirmatory factor analysis (CFA) process. </p> \n \n<p>The CFA process found the SCO factors to be reliable. A dependent variable, Supply Chain Operational Performance (SCOP) was found to be positively influenced by changes in SCO. SCO was found to be a unique strategic orientation through the literature review process and validated as its own construct through a discriminant validity process. SCO was determined to be a second-order reflective latent variable, and top management support was found to be an antecedent to SCO.</p> \n \n<p>Of interest to SCM practitioners and academics, SCO was found to be statistically invariable between respondents who were or were not members of a SCM industry association. As well, SCO did not vary outside statistical bounds across the supply chain from ultimate supplier (Earth) to ultimate customer. However, SCO was found to be stronger in companies that employed an “e cient” supply chain strategy (using the taxonomy of Lee (2002)) versus other generic strategies (like “agile” supply chain strategy).</p> \n \n<p>The contributions of this research to academics include a parsimonious definition of SCO which meets the criteria of Wacker (1998), an operationalization of the Lee (2002) model, and additional evidence of the power of Parallel Analysis (PA) of Thompson (2004) in determining factors in an EFA. Supply chain orientation is an important theoretical ‘building block’ from which SCM theory can be built and through the refinement process, SCO was tied into the dynamic capabilities area of the larger resource-based view (RBV) theoretical framework.</p> \n \n<p>Supply chain orientation was found to positively influence SCOP. The Council of Supply Chain Management Professionals reported that business logistics (SCM) costs in the United States alone in 2009 were 1.3 trillion dollars. Hence, improving upon the understanding of the mechanisms of supply chain management and its components can have substantial economic consequences.</p>
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».