Methodology for appraisal of dynamic e-commerce business models

Abstract

E-commerce is transforming the way products, services and information are bought, sold and exchanged. Companies are discovering that a well-planned and executed e-commerce presence is crucial to overall business success. Statistics show that e-commerce is growing very rapidly. According to Goldman Sachs Investment Research [May 2000], the expected worldwide gross value of commerce transactions being done online is to grow to 7.6 trillion by 2005 from 225 billion in 1999. One of the most significant determinants of online business performance is the business model. The business model spells out how a company makes money by specifying where it is positioned in the value chain. Given the central role the business models play in a firm's performance, it is important to be able to understand how one business model compares with another. When making choices about the components and linkages of a business model, a firm needs to be able to determine which business model alternatives are best. A good analysis of competitors also ought to include a comparison of business models. This thesis aims at developing a methodology to compare the e-commerce business models with respect to pre -defined parameters, which signify the robustness of any e-commerce business model. After a detailed literature review of the broad business model categories (B2B, B2C, C2B and C2C) and current e-commerce business models, generic models were selected and a taxonomy for the models was developed. Parameters for appraisal of the business models were identified. Each attribute for all the business models was assigned a numerical score (based on sub-attributes and qualitative factors) on a bipolar scale and normalized weights were assigned for each attribute. Different Multiple Attribute Decision Making (MADM) techniques were applied to the decision matrix to rank the business models, and the results of the techniques were then compared. Sensitivity analysis was performed to evaluate the effect of changes in input variables on the ranking of business models. Programs in C language were developed for carrying out both MADM and Sensitivity Analysis simulations. Results show that the Auction model is the strongest business model while Advertising model is the weakest.