e-commerce Models

These models and simulations have been tagged “e-commerce”.

Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
e-Commerce Revenue Estimator
Insight diagram
e-Commerce prediction rate for evaluation.

This is DRAFT and non-functional

RNTLS Insight
Insight diagram
Seller Aggregation On-Demand
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of Clone of e-Commerce Revenue Estimator
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator
Insight diagram
FEM, Assignment 1
Insight diagram
The simulation model provides a holistic insight into the e-Customers’ dynamic behavior during online shopping sessions, and combines both qualitative and quantitative aspects of the interaction between e‑Customers and a hypothetical e-Commerce website. It takes into account the existence of three classes of e-Customers: 'Spendthrifts', 'Average Spenders', and 'Tightwads', and an operational profile based on these three classes, which assumes 24% 'Tightwads', 61% 'Average Spenders', and 15% 'Spendthrifts'.
Clone of e-Commerce Revenue Estimator