Notice bibliographique
Résumé
Our understanding of “the Web” and its e-commerce (EC) potential has grown rapidly during the past decade. While ecommerce has matured and is now mainstream, there continue to be opportunities to innovate as technology improves, the public is increasingly comfortable with and dependent up the e-approach, and new or enhanced applications appear. While historical roots of the Web go back several decades, it was only in the last two that business really started to embrace the Internet, and in the last one that commercial opportunities on the Web grew rapidly. Business use has gone from simple operational efficiencies (e-mail on the Internet, replacement of private EDI networks, etc.) to effectiveness (enhanced services, virtual products, and competitive advantage). Information and information products, available in digital form, and the ability to quickly transfer these from one party to another, have led to a paradigm shift in the way organizations operate. Many BPR (business process re-engineering) projects made use of the Web to streamline business processes and reduce or eliminate delays. Web self-service has emerged as a popular approach, with benefits for both customers and providers. Even governments have embraced the Web (e-government) for information and service delivery and interaction with citizens and businesses. While the transition has followed the historical IT progression of automate, infomate, and transformate, the pace has been unprecedented. There have been successes and failures, with fortunes made and lost. After the dot-com boom/bust cycle, things settled down somewhat; yet the rapid pace of Web initiatives continues. At the forefront are innovators seeking competitive advantage. At the rear are laggards who can no longer ignore efficiencies provided by the Web and market requirements to be Web-enabled. Paralleling the improvement in IT and the Internet has been a series of economic shifts including globalization, flattening of hierarchical organizations, outsourcing and off-shoring, increasing emphasis on knowledge work (contrasted with manual labor), plus growth in the service sector and information economy. IT has both hastened these economic shifts and provided a welcome means of addressing the accompanying pressures (often through EC or other Web initiatives). To consider EC strategy and Web initiatives, one first needs to understand strategy and then extend this to the organization’s business model and tactics. A firm’s general business strategy includes, but is not limited to, its IT strategy (Figure 1). Similarly, EC strategy is a subset of IT strategy. Strategy should drive actions (tactics), through an appropriate business model. When strategy (business, IT, and EC) and tactics are closely aligned, and tactics are successfully executed, desirable results are obtained. Sometimes this normative view becomes reversed or otherwise changed. In the extreme, Web initiatives become the sole major focus (as was the case in the early days of the dot-com boom). However, without alignment between such tactics and the firm’s strategy and business model, such an approach is either doomed to eventual failure or substantial modification. In addition to commercial use of the Web, there are many non-commercial uses and non-commercial users (governments, educational institutions, medical organizations, etc.). The term e-business is often used to include both commercial and non-commercial activity on the Internet. In this article, the focus is on commercial activities (B2B and B2C). While e-government includes use of EC, governments are often driven by goals and responsibilities other than profit generation or cost reduction.
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; 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 ».