An Anchoring and Adjustment Model of Purchase Quantity Decisions

1998 ◽  
Vol 35 (1) ◽  
pp. 71-81 ◽  
Author(s):  
Brian Wansink ◽  
Robert J. Kent ◽  
Stephen J. Hoch
Keyword(s):  
Field Experiments ◽  
Brand Choice ◽  
Anchoring And Adjustment ◽  
Adjustment Model ◽  
Final Study ◽  
Purchase Incidence ◽  
Point Of Purchase ◽  
Multiple Unit ◽  
Suggestive Selling ◽  
Purchase Quantity

How do consumers decide how many units to buy? Whereas prior research on individual consumers’ purchases has focused primarily on purchase incidence and brand choice, the authors focus on the psychological process behind the purchase quantity decision. The authors propose that a simple anchoring and adjustment model describes how consumers make purchase quantity decisions and suggests how point-of-purchase promotions can increase sales. Two field experiments and two lab studies show that anchor-based promotions—presented as multiple-unit prices, purchase quantity limits, and suggestive selling—can increase purchase quantities. The final study shows that consumers who retrieve internal anchors can counter these anchor-based promotions effectively. Firms might receive net benefits from anchor-based promotions depending on whether increases in unit sales reflect increased category consumption, brand switching, variety switching, store switching, or stockpiling.

An Anchoring and Adjustment Model of Purchase Quantity Decisions

1998 ◽  
Vol 35 (1) ◽  
pp. 71 ◽  
Author(s):  
Brian Wansink ◽  
Robert J. Kent ◽  
Stephen J. Hoch
Keyword(s):  
Anchoring And Adjustment ◽  
Adjustment Model ◽  
Purchase Quantity

Determining Segmentation in Sales Response across Consumer Purchase Behaviors

1998 ◽  
Vol 35 (2) ◽  
pp. 189-197 ◽  
Author(s):  
Randolph E. Bucklin ◽  
Sunil Gupta ◽  
S. Siddarth
Keyword(s):  
Brand Choice ◽  
Two Dimensions ◽  
Joint Estimation ◽  
Purchase Behavior ◽  
Purchase Incidence ◽  
Scanner Panel Data ◽  
Sales Response ◽  
Purchase Behaviors ◽  
Purchase Quantity ◽  
Scanner Panel

The authors develop a joint estimation approach to segment households on the basis of their response to price and promotion in brand choice, purchase incidence, and purchase quantity decisions. The authors model brand choice (what to buy) by multinomial logit, incidence (whether to buy) by nested logit, and quantity (how much to buy) by poisson regression. Response segments are determined probabilistically using a latent mixture model. The approach simultaneously calibrates sales response on two dimensions: across segments and the three purchase behaviors. The procedure permits market-level sales elasticities to be decomposed by segment and purchase behavior (i.e., choice, incidence, and quantity). The authors apply the approach to scanner panel data for the yogurt category and find substantial differences across segments in the relative impact of the choice, incidence, and quantity decisions on overall sales response to price.

A Process Management Strategy for Re-Design: An Anchoring Adjustment Approach

1998 ◽  
Author(s):  
Lisa A. Dixon ◽  
Jonathan S. Colton
Keyword(s):  
Design Process ◽  
Management Strategy ◽  
Process Management ◽  
General Pattern ◽  
Evaluation Metrics ◽  
Anchoring And Adjustment ◽  
Adjustment Model ◽  
Design Activities ◽  
Design Process Model ◽  
Process Strategy

Abstract Preceding research on the re-design process focused on the development and verification of an Anchoring and Adjustment design process model. Compared to the existing, predominantly top-down, models, this new model was tailored specifically to describe designers’ approaches to re-design tasks. Building upon that work, this paper presents an evaluation of a re-design process strategy that is based on the key elements identified in the Anchoring and Adjustment model (a general pattern for re-design activities and two evaluation metrics). The overall goal was to formulate an efficient and effective process management strategy unique to re-design activities. Data were collected from three industry re-design projects for the evaluation. First, an analysis of the data confirmed that the pattern of design activities and evaluation metrics used by the company’s designers could be mapped onto those that comprise the Anchoring and Adjustment model. Second, the analysis of the data suggested that with additional formalization — based on an anchoring and adjustment approach — the company’s current process management technique could provide more accurate feedback to the designers for the more efficient and effective management of their re-design processes. One of the industry case studies is detailed to illustrate the research results and conclusions.

Brand Choice, Purchase Incidence, and Segmentation: An Integrated Modeling Approach

1992 ◽  
Vol 29 (2) ◽  
pp. 201-215 ◽  
Author(s):  
Randolph E. Bucklin ◽  
Sunil Gupta
Keyword(s):  
Market Segmentation ◽  
Laundry Detergent ◽  
Brand Choice ◽  
Purchase Behavior ◽  
Brand Preference ◽  
Purchase Incidence ◽  
Scanner Panel Data ◽  
Liquid Laundry Detergent ◽  
Marketing Variables ◽  
Scanner Panel

The authors develop an approach to market segmentation based on consumer response to marketing variables in both brand choice and category purchase incidence. The approach reveals segmentation as well as the nature of choice and incidence response for each segment. Brand choice and purchase incidence decisions are modeled at the segment level with the disaggregate multinomial logit and nested logit models; segment sizes are estimated simultaneously with the choice and incidence probabilities. Households are assigned to segments by using their posterior probabilities of segment membership based on their purchase histories. The procedure thereby permits an analysis of the demographic, purchase behavior, and brand preference characteristics of each response segment. The authors illustrate their approach with scanner panel data on the liquid laundry detergent category and find segmentation in price and promotion sensitivity for both brand choice and category purchase incidence. The results suggest that many households that switch brands on the basis of price and promotion do not also accelerate their category purchases and that households that accelerate purchases do not necessarily switch brands.

Analyzing purchase incidence and brand choice by hazard models

OR Spectrum ◽  
1998 ◽  
Vol 20 (1) ◽  
pp. 55-63
Author(s):  
Harald Hruschka ◽  
Helmut Stoiber ◽  
Alfred Hamerle
Keyword(s):  
Brand Choice ◽  
Hazard Models ◽  
Purchase Incidence

A Model of Brand Choice and Purchase Quantity Price Sensitivities

1988 ◽  
Vol 7 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Lakshman Krishnamurthi ◽  
S. P. Raj
Keyword(s):  
Brand Choice ◽  
Purchase Quantity

Predicting what? The strengths and limitations of a test of persuasive advertising principles

2016 ◽  
Vol 50 (1/2) ◽  
pp. 312-316 ◽  
Author(s):  
Malcolm J. Wright
Keyword(s):  
Memory Retrieval ◽  
Brand Choice ◽  
Major Advance ◽  
Contextual Cues ◽  
Content Type ◽  
Persuasive Advertising ◽  
Point Of Purchase ◽  
Consumer Memory ◽  
Random Fluctuations ◽  
With Memory

Purpose – The purpose of this paper is to discuss Armstrong et al.’s (2016) finding that ads that more closely follow evidence-based persuasion principles also achieve higher day-after-recall. Design/methodology/approach – The author evaluates the importance of Armstrong et al.’s result and considers the criticisms that their work only examines some aspects of persuasion and that their dependent variable is known to have a low correlation with sales. Findings – Armstrong et al.’s result provides a major advance in the knowledge of persuasive advertising. While they do not examine all aspects of persuasion, the scope of their tests is still very extensive. Day-after-recall is also arguably a better measure of advertising effectiveness than sales impact, due to the difficulty of identifying small sales changes among the random fluctuations that constantly occur in most markets and given the known processes by which consumer memory operates. Originality/value – By synthesising prior work on advertising and consumer memory, the author provides a simple model of how advertising interacts with memory. This model explains why ad recall ought to be poorly correlated with sales, and highlights the need for Armstrong et al.’s result to be followed by further research into how contextual cues at the point of purchase affect memory retrieval and brand choice.

Analyzing purchase incidence and brand choice by hazard models

OR Spectrum ◽  
1998 ◽  
Vol 20 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Harald Hruschka ◽  
Helmut Stoiber ◽  
Alfred Hamerle
Keyword(s):  
Brand Choice ◽  
Hazard Models ◽  
Purchase Incidence
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