WAR: What Else Is It Good For? A Comparison of Maximum Difference Scaling, Adaptive Choice-based Conjoint, Constant Sum Scaling and Wallet Allocation Rule Utilities

Abstract

Purpose – This research compares the results of Maximum Difference Scaling (MaxDiff), Adaptive Choice-Based Conjoint (ACBC), and constant sum scaling with the results of a Wallet Allocation Rule (WAR) approach for identifying the features of smartphones deemed most valuable by consumers. Design/methodology/approach – The authors examine the responses of 554 recent purchasers and 598 intended purchasers of smartphones about the features of smartphones that they have considered/will consider in their purchase decisions and the relative value they assign to each feature. MaxDiff, ACBC, constant sum scaling and WAR are used for quantifying the importance of these features and correlation analysis is used to compare the results of the four methods. Findings – The authors find that constant sum scaling and WAR provide nearly identical results at both the aggregate and individual levels, while MaxDiff and ACBC produce similar results to WAR at the aggregate level only. Originality/value – This research validates the feasibility of a simple method for estimating the utility of product features by demonstrating the similarity of results to more established and/or complex methods. The availability of a simpler method creates value by allowing more firms to engage in this kind of co-creative research while reducing costs for customers to participate.