We propose a framework for designing adaptive choice-based conjoint questionnaires that are robust to response error. It is developed based on a combination of experimental design and statistical learning theory principles. We implement and test a specific case of this framework using Regularization Networks. We also formalize within this framework the polyhedral methods recently proposed in marketing.
In the intervening years since publication of the chapter "Affect and Consumer Behavior" (Cohen & Areni, 1991) in the Handbook of Consumer Behavior (Kassarjian & Robertson, 1991), research in consumer behavior dealing with affect has exploded, making it one of the field's central research topics. Within psychology more generally, Schimmack and Crites (2005) located 923 references to affect between 1960 and 1980 and 4,170 between 1980 and 2000.
Two Columbia Business School students have developed an idea for a shoe accessory. They believe that this product will sell and want to set up a company. What marketing-related questions should they address in order to increase their chance of success?
Michael Dwork and his team are developing a line of environmentally-friendly disposable dinnerware. They want to use conjoint analysis to determine consumers' preferences and willingness to pay. Would you modify their questionnaire in any way?
We identify gaps and propose several directions for future research in preference measurement. We structure our argument around a framework that views preference measurement as comprising three interrelated components: (1) the problem that the study is ultimately intended to address; (2) the design of the preference measurement task and the data collection approach; (3) the specification and estimation of a preference model, and the conversion into action. Conjoint analysis is only one special case within this framework.
Whether a business is large or small, its brand is probably its most important and valuable asset. How a brand is managed has tremendous impact on an organization's ability to attract and hold customers, achieve high revenue and profits, and ensure future success. The most powerful brands are worth billions of dollars, but to build a powerful brand at any level requires time, effort, discipline, and understanding the way brands work.
Purpose — The purpose of this research is to examine how consumers form beliefs and evaluate derivatives (e.g. handheld computers) and branded derivatives (e.g. Palm handheld computers). The aim is to study how consumers combine two categories (e.g. ?handheld products? and ?computers?) to form beliefs, how the similarity between the categories influences beliefs, how the addition of a brand changes beliefs, and how the presence of brand associations impacts on evaluations.
Here's a familiar story: A new communications technology that allows one to broadcast live to millions.