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Enregistrement W1499773649

Towards Understanding the Formation and Impact of E-service Failures

2008· article· en· W1499773649 sur OpenAlexaff
Chee‐Wee Tan, Izak Benbasat, Ronald T. Cenfetelli

Notice bibliographique

RevueJournal of the Association for Information Systems · 2008
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueTechnology Adoption and User Behaviour
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésService (business)Transactional leadershipTypologyConsumption (sociology)MarketingComputer scienceProcess (computing)Consumer behaviourProduct (mathematics)PerceptionPerspective (graphical)E-commerceBusinessPsychologyWorld Wide WebSocial psychologySociologyArtificial intelligence
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

E-service failure has been the bane of e-commerce by compelling consumers to abandon transactions entirely or to switch to brick-and-mortar establishments. Yet, despite the downsides of e-service failures, there has not been a study to-date that systematically investigates how perceptions of failure arise within online transactional environments and their impacts on consumer behavior. Departing from the multi-attribute utility approach prevalent in conventional consumer research, this study advances a typology of e-service failure from a goal-directed perspective. Assimilating Lee and Ariely’s (2006) shopping goal theory with Van Osselaer et al.’s (2005) classification of consumer goals, it is the contention of this study that when transacting online, consumers are not only motivated to (1) purchase a product suited to their extrinsic requirements (i.e., consumption goals) and personal preferences (i.e., criterion goals) while enjoying the transactional experience (i.e., process goals), but they are also seeking ways to (2) translate what are often elusive intentions into tangible objectives (goal activation) and achieve those objectives in the most efficacious manner (i.e., goal implementation). Consequently, e-service failures can be delineated according to the type of consumer goal (i.e., consumption, criterion or process) they target and the transactional stage (i.e., activation or implementation) at which they occur. A research model of e-service failure is then constructed and testable hypotheses are derived.\nTo empirically validate the model, a 3x3 experimental design is proposed and elaborated. The experiment employs a 3 (Type of Failure: Activation Success + Implementation Failure; Activation Failure + Implementation Failure or Activation Failure + Implementation Success) x 3 (Type of Goal: Consumption; Criterion; or Process) between-subjects factorial design will be conducted. A totally separate control group without any form of e-service deficiency (Activation Success + Implementation Success) across the three goal categories will also be incorporated into the experimental design to contrast differences in consumers’ perceptions, attitudes and behaviors arising from the distinction between the presence and absence of implementation failures given the successful activation of consumer goals. It is anticipated that the empirical findings from our experiment will serve to inform academics and practitioners on: (1) how consumer perceptions of different types of e-service failure manifest on e-commerce websites, and; (2) their impact on transactional attitudes and intentions.\nConceptually, our proposed experimental study is designed to not only verify the veracity of our research model, but to also challenge the premise underlying past research into consumer behavior. Theories like the EDT have contended that expectations constructed from previous transactional experiences form the baseline from which consumers assess future transactions. Yet, if we were to establish goal activation as a prerequisite for perceptions of implementation failure to arise, it will imply that while prior transactional experiences might be pertinent in affecting consumer behavior, goals—which are activated through immediate interactions with the e-commerce website—may be a more salient influence. Additionally, the experiment represents an opportunity to validate our typology of e-service failures by demonstrating how they might occur in reality and explaining why each e-service failure type might be more or less effective in affecting online consumer behavior. Pragmatically, empirical findings can offer cautionary advice to practitioners to be vigilant in web interface design so as to avoid activating unwanted goals, especially when the website is ill-equipped to fulfill them. Further, the typology of e-service failures can provide guidelines for practitioners to establish benchmarks for designing error-free e-commerce websites. Finally, this study acts as a pre-requisite to uncovering corresponding e-service recovery mechanisms that can be offered on e-commerce websites to alleviate consumers’ disappointment and feelings of dissatisfaction in the event of e-service failures.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,025
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,025
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0050,004
Études des sciences et des technologies0,0020,008
Communication savante0,0080,021
Science ouverte0,0020,008
Intégrité de la recherche0,0040,005
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,136
Tête enseignante GPT0,362
Écart entre enseignants0,226 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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
Publié2008
Routes d'admission1
Résumé présentoui

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