E-Finance Lab Team

Internet distribution channels may be either advantageous or detrimental for a company. Therefore, this study analyzes their performance, antecedents, and effect on company performance. Using survey data from multichannel retailers and structural equation model methodology, the authors show that Internet channel performance contributes to both financial and strategic company performance, with a greater effect on the latter. Similar and uncoordinated channels hinder Internet channel performance, but experience with direct channels and channel power are not required to pursue an Internet channel successfully. Customer migration and managerial commitment to the Internet channel have strong positive influences on financial performance. Overall, the results encourage the adoption and development of Internet channels.

In recent years nonlinear pricing has attracted a lot of attention from academics and practitioners due to increased possibilities of its application in the growing area of service industries. In case of wireless communication, internet access or TV pay-channels providers usually offer a set of optional tariffs that consists of a usage-independent fixed fee and a marginal price. Analysis of nonlinear pricing is, however, very complex and poses many difficulties because of the interdependency between the consumption level and marginal price. Willingness-to-pay functions account for this interdependency and can be used to predict consumer behavior, analyze the effect of price changes on the market as well as to design of the optimal nonlinear pricing scheme. So far, several studies made proposals on how to use survey data to estimate willingness-to-pay functions (Iyengar et al. 2006, Wolk and Skiera 2006). While those studies laid down the foundations for using survey data to estimate willingness-to-pay functions, they suffer from a limited comparison of data gathering and estimation procedures. In this study we review, enhance and compare various methods that use survey data for the estimation of willingness-to-pay functions. First, we focus on the data gathering procedure (i.e., ranking-based conjoint, choice-based conjoint, and contingent valuation) while in the second step we analyze various estimation procedures (i.e., one-step versus two-step procedures). In an empirical study we measure the perceived task difficulty, the time required for accomplishing the task, face, internal and predictive validity. Based on the results we provide recommendations concerning the most reliable and valid procedure for using survey data to estimate willingness-to-pay functions.