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Enregistrement W2781445152 · doi:10.4018/978-1-60566-026-4.ch576

Supporting E-Commerce Strategy through Web Initiatives

2009· book-chapter· en· W2781445152 sur OpenAlexaff
Ron Craig

Notice bibliographique

RevueIGI Global eBooks · 2009
Typebook-chapter
Langueen
DomaineBusiness, Management and Accounting
ThématiqueInformation Technology Governance and Strategy
Établissements canadiensWilfrid Laurier University
Organismes subventionnairesnon disponible
Mots-clésPaceThe InternetBusinessBoomWorld Wide WebWeb engineeringWeb developmentEngineeringComputer scienceWeb intelligence

Résumé

récupéré en direct d'OpenAlex

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 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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,887
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,002

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,266
Écart entre enseignants0,243 · 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'étudeThéorique ou conceptuel
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

Citations0
Publié2009
Routes d'admission1
Résumé présentoui

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