Information Form and Level-of-Analysis as Moderators of the Influence of Information Diagnosticity on Consumer Choice Confidence and Purchase Readiness
Notice bibliographique
Résumé
INTRODUCTIONProduct information plays a central role in readying consumers to act on purchase opportunities. Consumers rely on product information to understand choice alternatives (Akdeniz, Calantone, & Voorhees, 2013) and arrive at a confident choice decision (Mehta, Xinlei, & Narasimhan, 2008). Choice confidence, or the extent to which a consumer understands his/her preference and believes the preference to be correct (Heitmann, Lehmann, & Herrmann, 2007), serves as a gateway to many consumer reactions. These include purchase intention (Laroche, Kim, & Zhou, 1996) and purchase action (Greenleaf & Lehmann, 1995). Because choice confidence plays an important role in determining consumer response to purchase opportunities, it is important to develop deeper understanding of the drivers of this psychological state as well as its influence on purchase readiness.Information that is more diagnostic (i.e., useful in a choice decision; Lynch Jr, Marmorstein, and Weigold (1988)) facilitates a choice decision and strengthens choice confidence (Yoon & Simonson, 2008). Prior research has shown that this relationship is altered by factors that change the way that consumers perceive, or engage in, the choice task. Some of these factors include personality traits (Andrews, 2013), and goals (Tsai & McGill, 2011) or characteristics (Andrews, 2016) of the choice task. To this growing body of literature, the present research adds a novel investigation of the moderating potential of two information characteristics that are commonly varied in consumer marketspaces, information form and level-of-analysis (LOA). Information form is conceived in the present research as product information that is represented verbally, i.e., via words such as completely, or numerically, i.e., via a number that represents a unit of measurement such as 100%. In practice, product information is also presented at different levels-of-analysis (LOA). Levelof-analysis (LOA) refers to the way that information is arranged, grouped, or organized. For example, information may be presented at the component (micro focus) or system (macro focus) level (Ostroff & Harrison, 1999; Singer, 1961). The present research examines differences in the influence of product information that is presented at an attribute (i.e., component) or a summary (i.e., system) level of analysis.Marketing managers must determine whether to present product information in verbal form or an equivalent numeric form. Additionally, managers must decide whether to present attribute-level details about the product or to summarize the information for the consumer. Such decisions are, in no way, trivial. Differences in the way in which product information is presented have been shown to alter consumer response (Lutz, McKenzie, & Belch, 1983; MacKenzie & Lutz, 1989). Thus, it is important to understand the consequences to choice confidence of differences in information form and level-of-analysis (LOA).Verbal vs. numeric information differ in terms of the specificity and the meaning that is conveyed (O. Huber, 1980; Viswanathan, 1994; Viswanathan & Childers, 1996). Each form of information exerts unique influences on the way that consumers process information (Childers & Viswanathan, 2000; Jiang & Punj, 2010). Differences in the way product information is processed are anticipated to produce corresponding differences in the influence of information diagnosticity on choice confidence.Presenting information at a summary- vs. an attribute-level can also produce differences in consumer information processing (Viswanathan & Hastak, 2002). Therefore, level-of-analysis holds the potential to moderate the information diagnosticity effect. An examination of consumer marketspaces reveals that marketing organizations regularly employ different combinations of information form and level-of-analysis (LOA). For example, GoodGuide.com provides attribute-level ratings in numeric form for more than 250,000 products. …
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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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 ».