CDO Positions: A Study on the Impact of Chief Data Officers on Organizational Performance
Notice bibliographique
Résumé
Purpose – The purpose of this paper is to employ a strategic change view, with the appointing of a CDO, to develop theoretical links and empirically examine the association between the CDO’s presence and organizational performance utilizing accounting measures. \n \nDesign/methodology/approach – Adopted for this study is the “matched sample comparison group” methodology, also known as the matched pair analysis, to empirically test the hypotheses, compare the performance of the treatment sample group with CDOs and the control sample group without CDOs, and assess the relationship between CDO presence and firm performance. The financial data for treatment firms with CDOs and control firms without CDOs was collected from the Compustat database. The Wilcoxon signed-rank test and regression analysis were used to analyze the performances for the treatment and control sample groups. \n \nFindings – Overall, the results indicate that firms that have lower performance will be more likely to appoint a CDO and still maintain a competitive cost structure relative to firms without CDOs. Even though the cost ratios of firms with CDOs were not lower after the appointment of the CDO than before the appointment, CDOs promptly improve their profitability relative to peers who do not have CDOs, without significantly increasing cost. Finally, prior year financial performance has very great impact on current year financial performance. \n \nPractical implications – With limited statistical confidence, due to a small sample and short period of performance measurements to analyze, as the CDO position is a quite new to Canada, the conclusion can still be made that: CDOs are hired when performance is low and excel at solutions, which they seem to bring swiftly, by improving revenues and profitability without significantly increasing costs. This research further addresses both the academic and business communities emphasizing that, in this moment in big data history, the position of the CDO is not to be ignored or disregarded, as this role may prove to appreciably advance and elevate corporate Canada. \n \nOriginality/value – The study explores the relationship between the CDO’s presence and firm performance. It is the first attempt to explore the CDO’s impact on the profit and cost performances from a purely Canadian perspective, evaluating only firms listed on the Toronto Stock Exchange – TSX. Prior studies have been from a global standpoint and heavily focused on the United States of America.
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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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,002 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».