A PREDICTIVE MODEL FOR CUSTOMER PURCHASE BEHAVIOR IN E-COMMERCE CONTEXT

Predicting customer purchase behaviour is an interesting and challenging task. In e-commerce context, to tackle the challenge will confront a lot of new problems different from those in traditional business. This study investigates three factors that affect purchasing decision-making of customers in online shopping: the needs of customers, the popularity of products and the preference of the customers. Furthermore, exploiting purchase data and ratings of products in the e-commerce website, we propose methods to quantify the strength of these factors: (1) using associations between products to predict the needs of customers; (2) combining collaborative filtering and a hierarchical Bayesian discrete choice model to learn preference of customers; (3) building a support vector regression based model, called Heat model, to calculate the popularity of products; (4) developing a crowdsourcing approach based experimental platform to generate train set for learning Heat model. Combining these factors, a model, called COREL, is proposed to make purchase behaviour prediction for customers. Submitted a purchased product of a customer, the model can return top n the most possible purchased products of the customer in future. Experiments show that these factors play key roles in predictive model and COREL can greatly outperform the baseline methods

A Probabilistic Approach to Maximize Cross-Selling Revenues of Financial Products

Customer oriented approach and developing analysis for customers have become more important as the competition became a global issue, especially after technological advancements. Companies aim to sell more products to new customers and also to their current customers while keeping them in the portfolio and making sure that they are happy. Cross-selling of products and services to their customers is almost as important as gaining new customers. In this paper, a probabilistic and integrated method of cross-selling financial products is proposed. The proposed method first segments the customers based on the selected criteria and then calculates the probability of buying each product using product and customer relationship matrixes. Then, the expected yield for each group of customers and offer is calculated, and the best cross-selling strategy is determined. The proposed methodology is applied to a Turkish bank that aims to sell financial products through cross-selling. The results show that the methodology successfully determines the product order to be used in cross-selling in an effort to increase the success rate in the selling process and expected revenue

E-Fulfillment and Multi-Channel Distribution – A Review

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.Distribution;E-fulfillment;Literature Review;Online Retailing

E-Fulfillment and Multi-Channel Distribution – A Review

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering

Sistema de ventas cruzadas en Alimec

The proposed project is to achieve a cross sale products forecast, which are suggested according to sales´ tendencies presented by the company Alimec S.A. The problem presented by the company was that the new or the inexpert salesmen had difficulties increasing the list of products purchased by each store. It was decided to solve the problem by providing the salesmen with a list of suggested products which were predefined according to customer´s tendencies...El proyecto propuesto es la obtención de pronósticos de productos de venta cruzada, sugeridos de acuerdo con las tendencias de ventas que presenta la compañía Alimec S.A. El problema presentado por la empresa consistía en que los vendedores nuevos o inexpertos tenían dificultades en ampliar la lista de productos adquiridos por cada tienda. Para solucionarlo se decidió entregar a los vendedores una lista de productos sugeridos preestablecida de acuerdo a la tendencia de los clientes..

Consumer embarrassment.

Wong King Yin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2006.Includes bibliographical references (leaves 79-83).Abstracts in English and Chinese; questionnaires in Chinese.Abstract (English) --- p.2Abstract (Chinese) --- p.3Dedication --- p.4Acknowledgements --- p.5Table of Contents --- p.6Chapter Chapter 1 --- Introduction --- p.8Chapter 1.0 --- Overview --- p.8Chapter 1.1 --- Background --- p.8Chapter 1.2 --- Research Objectives --- p.11Chapter 1.3 --- Expected Contributions --- p.11Chapter 1.4 --- Organization of the Thesis --- p.12Chapter Chapter 2 --- Literature Review & Research Model --- p.14Chapter 2.0 --- Overview --- p.14Chapter 2.1 --- Literature Review on Embarrassment --- p.14Chapter 2.1.1 --- Embarrassment and Its Antecedent --- p.14Chapter 2.1.2 --- Embarrassment and Its Subsequent Behavioral Tendency --- p.24Chapter 2.2 --- Conceptual Definitions --- p.35Chapter 2.2.1 --- Consumer Embarrassment --- p.36Chapter 2.2.2 --- Cross-selling --- p.37Chapter 2.2.3 --- Helping Behavior --- p.38Chapter 2.3 --- Hypothesis --- p.40Chapter Chapter 3 --- Research Methodology --- p.44Chapter 3.0 --- Overview --- p.44Chapter 3.1 --- Research Design --- p.44Chapter 3.2 --- Pretest --- p.45Chapter 3.2.1 --- Embarrassing Product --- p.46Chapter 3.2.2 --- Scenario Development --- p.47Chapter 3.2.3 --- Questionnaire Development --- p.48Chapter 3.2.4 --- Experimental Setting --- p.51Chapter 3.3 --- Main Study --- p.52Chapter 3.3.1 --- Participants --- p.52Chapter 3.3.2 --- Materials --- p.52Chapter 3.3.3 --- Scenarios --- p.53Chapter 3.3.4 --- Manipulation Checks --- p.54Chapter 3.3.5 --- Dependent Measures --- p.56Chapter 3.3.6 --- Procedures --- p.56Chapter Chapter 4 --- Results And Discussion --- p.58Chapter 4.0 --- Overview --- p.58Chapter 4.1 --- Reliability of Scales --- p.58Chapter 4.2 --- Manipulation Checks --- p.59Chapter 4.3 --- Hypotheses Testing --- p.60Chapter 4.4 --- Discussion --- p.62Chapter Chapter 5 --- Conclusion --- p.64Chapter 5.0 --- Overview --- p.64Chapter 5.1 --- Contributions --- p.64Chapter 5.1.1 --- Theoretical Contribution --- p.64Chapter 5.1.2 --- Managerial Contribution --- p.66Chapter 5.2 --- Limitations --- p.67Chapter 5.3 --- Future Research Directions --- p.68Chapter 5.3.1 --- Embarrassing Product Typology --- p.68Chapter 5.3.2 --- Coping Strategies to Embarrassment and Fear of Embarrassment --- p.69Chapter 5.3.3 --- Coping Strategic Inclinations to Embarrassment --- p.70Chapter 5.4 --- Conclusion --- p.71Appendices --- p.73Appendix I - Booklet for Main Study --- p.73Appendix II - Booklet For Manipulation Checks --- p.76References --- p.7