Designing a Profit-Maximizing Product Line for Heterogeneous Market

Abstract

Designing product line is important marketing decision that affects the firm's overall performances and profitability. This is particularly important due to the fact that the contemporary markets are characterized by sophisticated and diverse preferences of consumers as well as strong competition. Therefore, to meet market demand, firms prefer to offer a product line instead of a single product. In order to decide both on the number and position of products in its product line, the company should understand the way in which consumers value and choose products. For that purpose, a multi-attribute research technique known as conjoint analysis can be used. At the same time, the company should take into account product and pricing strategy of competitors and the possible competitors' reactions on its own strategy. For modelling market competition, the concept of the Nash equilibrium appears as an appropriate tool. This paper proposes a model for designing a competitive profit-maximizing product line for a heterogeneous market. Preferences were modelled by a model of partial utilities associated with the corresponding attribute levels, while the logit model is used to transform respondents' preferences into a potential market share. The problem of optimizing the product line was formulated as a nonlinear binary programming model. Proposed model was tested on the previously published conjoint data set, thus confirming its efficiency and applicability.

Avoiding the Privacy Paradox Using Preference-Based Segmentation: A Conjoint Analysis Approach

“…Some of them calculate only aggregated results, consider intentions and not current behavior, and do not consider heterogeneity in preferences but rather socio-demographic data. Having in mind that deciding to provide personal information online is a complex psychological process [8], conjoint analysis appeared to be an adequate method that attempts to experimentally uncover the hidden rules that individuals use to make trade-offs [33][34][35][36]. Moreover, the authors in [22] suggest that studies analyzing the trade-offs in privacy behavior should employ at least one:…”

“…Conjoint analysis (CA) is a stated preference method that aims to experimentally uncover the hidden rules that individuals use to make trade-offs between products or services. Although it originated in mathematical psychology and was first used in marketing to determine consumer preferences, CA has found wide application to understand individual preferences in numerous areas and in different contexts [33][34][35][36].…”