Information Form and Level-of-Analysis as Moderators of the Influence of Information Diagnosticity on Consumer Choice Confidence and Purchase Readiness
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".