Presentation on theme: "Copy Alert: A Method and Metric to Detect Visual Copycat Brands Talk Invitation Department of Information Management The authors propose a method and metric."— Presentation transcript:
Copy Alert: A Method and Metric to Detect Visual Copycat Brands Talk Invitation Department of Information Management The authors propose a method and metric to quantify consumer confusion between leading brands and copycat brands due to the visual similarity of their packaging designs. The method has three components. First, image-processing techniques establish the objective similarity of the packages of leading and copycat brands based on their colors and textures. Second, a perceptual decision task (triangle test) assesses the accuracy and speed with which consumers can identify differences between brands from rapidly (300 msec.) flashed images of their packages. Third, a competing accumulator model describes the buildup of evidence on each of the alternative brands during consumers' perceptual decisions, and predicts the accuracy and response time of brand identification. Jointly, this establishes the impact that the visual features of copycat packaging has on consumer confusion. The method is applied in a test of experimentally-designed and market copycats in fifteen product categories. A three-tiered metric (Copy- Alert, Copy-Warning, Copy-Safe) establishes to what extent copycat brands imitate the package designs of target brands, and which visual features are responsible for this. Michel Wedel PepsiCo Chair in Consumer Science, University of Maryland, USA Friday, March 7 th, 9: :30am E.Sun Hall, Building I, College of Management
Jie Zhang The Harvey Sanders Fellow of Retail Management, University of Maryland, USA Usage Experience with Decision Aids and Evolution of Online Purchase Behavior Friday, March 7 th, 11: :00pm E.Sun Hall, Building I, College of Management Talk Invitation Department of Information Management This study investigates how usage experience with various decision aids available in an online store contributes to purchase behavior evolution in a new Internet shopping environment. In the context of online grocery stores, we categorize four types of decision aids: those for 1) nutritional needs, 2) brand preference, 3) economic needs, and 4) personalized shopping lists, and construct a Non- homogeneous Hidden Markov Model of store visit incidence and shopping trip spending. The same model is also applied to study purchase incidence and quantity decisions in eight product categories. We find that consumers evolve through distinct states of purchase behaviors and exhibit stronger tendency to use habitual decision heuristics over time. While their average levels of price and promotion sensitivities increase first and then decrease, individual consumers show divergent patterns. Moreover, consumers’ usage experience with decision aids contributes to their behavior evolution, and the effects differ by the specific decision aids and behavioral state. In general, the impact of usage experience with decision aids on purchase behavior evolution appears to be stronger for higher-purchase-frequency and non- food categories. We demonstrate that targeted promotion activities based on our models can improve store-level and category-specific sales for an online retailer.