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1

E-Commerce Customers’ Preference Implicit Identification

100%

Zdziebko T.

Folia Oeconomica Stetinensia

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2012

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vol. 11

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issue 1

33-46

EN

Knowledge of users’ preferences are of high value for every e-commerce website. It can be used to improve customers’ loyalty by presenting personalized products’ recommendations. A user’s interest in a particular product can be estimated by observing his or her behaviors. Implicit methods are less accurate than the explicit ones, but implicit observation is done without interruption of having to give ratings for viewed items. This article presents results of e-commerce customers’ preference identification study. During the study the author’s extension for FireFox browser was used to collect participants’ behavior and preference data. Based on them over thirty implicit indicators were calculated. As a final result the decision tree model for prediction of e-customer products preference was build.

2

E-commerce – trends and development opportunities

86%

Radziszewska A.

Zeszyty Naukowe UPH seria Administracja i Zarządzanie

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2016

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vol. 36

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issue 109

73-85

PL

The paper describes the tools of marketing communication with e-customers and trendsconcerning e-commerce. Special attention has been paid to personalization and recommender systems.The paper treats the characteristics of consumer behaviours on the business-to-customermarket and the main barriers in customer relationship management. In this context the relationshipwith e-customers and the tools of marketing communication in electronic customer relationship havebeen described. The rapid growth of e-commerce has created product overload where customers onthe Web are no longer able to effectively choose the products they are exposed to. There is a lot ofimperfect information and a large supply available for consumers, and so it is extremely difficult toidentify their own needs and preferences and ways for satisfying them. Recommendations are a typeof communication and an especially important issue in e-marketing. It is easy to find many websiteswhere a customer needs advice before taking the decision to purchase a product. Therefore, recommendationsare a powerful tool to assist customers in these decisions. The paper refers to the challengesresulting from the growing importance of network and virtual communities, where the consumeris perceived as a value co-creator.

3

Products and services recommendation systems in e-commerce. Recommendation methods, algorithms, and measures of their effectiveness

72%

Lasek M., Kosieradzki D.

Informatyka Ekonomiczna

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2014

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issue 1(31)

304-317

EN

The article concerns products and services recommendation systems in ecommerce which have become increasingly important for both consumers and retailers. The methods used for the recommendation of products and services, as well as the algorithms used to implement them, are presented in the article. Particular attention was paid to the problems of testing the suitability of algorithms, along with the effectiveness measures of the applications of the methods and algorithms.

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1 Folia Oeconomica Stetinensia

1 Informatyka Ekonomiczna

1 Zeszyty Naukowe UPH seria Administracja i Zarządzanie

1 Kosieradzki D.

1 Lasek M.

1 Radziszewska A.

1 Zdziebko T.

1 2016

1 2014

1 2012

E-Commerce Customers’ Preference Implicit Identification

E-commerce – trends and development opportunities

Products and services recommendation systems in e-commerce. Recommendation methods, algorithms, and measures of their effectiveness