Option framing and Markov chain: A descriptive approach in a state-space modeling of customer behavior

Abstract

In the field of marketing, option framing is a product or service configuration where the consumers customize the package they wish to procure either by adding options to a base model, an initial configuration with a minimum number of essential features, or by subtracting options from a fully-loaded model, a product or service configuration with both essential and all of the optional features. Additive framing is selecting features to augment the base model, while subtractive framing is deselecting features from the fully-loaded model. A focal issue for companies that could possibly offer such products or services with option framing is finding out which process, additive or subtractive framing, is bound to give a final configuration with more features. The scenarios of option framing can be described by a finite Markov chain process. The Markov chain attempts to capture the decision process of the two types of framing through the estimated probabilities of movement from one phase to the other. In each of the decision phases, the key measure is the number of features in the configuration and the transition probabilities. The option framing is used on an actual study, where the empirical results verify the theories favoring subtractive framing, such as differential loss aversion and anchoring-adjustment theories. Separate Markov chains are evaluated for additive and subtractive framing, with the final configurations of the product or service package, along with the corresponding number of options, as main results.