Consumer Perception of Retail Pork Bacon Attributes Using Adaptive Choice‐based Conjoint Analysis and Maximum Differential Scaling. Issue 11 (23rd October 2017)

• Record Type: Journal Article
• Authors: McLean, K. G.; Hanson, D. J.; Jervis, S. M.; Drake, M. A.
• Is Part Of: Journal of food science. Volume 82:Issue 11(2017)
• Page Start: 2659
• Page End: 2668
• Publication Date: 2017-10-23
• Subjects: bacon -- conjoint analysis -- consumer liking; Food -- Periodicals; Food -- Research -- Periodicals; Food -- Periodicals; Research -- Periodicals; Levensmiddelen; Voeding; 664
• DOI: 10.1111/1750-3841.13934
• Languages: English
• ISSNs: 0022-1147

Abstract

Abstract : Abstract: Bacon is one of the most recognizable consumer pork products and is differentiated by appearance, flavor, thickness, and several possible product claims. The objective of this study was to explore the attributes of retail bacon that influence consumers to purchase and consume bacon. An Adaptive Choice‐Based Conjoint (ACBC) survey was designed for attributes of raw American‐style bacon. An ACBC survey (N = 1410 consumers) and Kano questioning were applied to determine the key attributes that influenced consumer purchase. Attributes included package size, brand, thickness, label claims, flavor, price, and images of the bacon package displaying fat:lean ratio. Maximum Difference Scaling (MaxDiff) was used to rank appeal of 20 different bacon images with variable fat:lean ration and slice shape. The most important attribute for bacon purchase was price followed by fat:lean appearance and then flavor. Three consumer clusters were identified with distinct preferences. For 2 clusters, price was not the primary attribute. Understanding preferences of distinct consumer clusters will enable manufacturers to target consumers and make more appealing bacon. Practical Applications: Adaptive Choice‐Based Conjoint (ACBC) is a research technique that allows consumers to react to assembled products and identify product attributes that they prefer. Kano questions allow researchers to look at the individual aspects of a product and understand consumer sentiment and expectations towards those product qualities while Maximum Difference scaling allows consumers to directly rank single attributes of a product relative to one another. A combination of these 3 approaches can provide key understandings on consumer perception of retail bacon allowing companies to optimize and maximize their development and advertising resources.