کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
552634 1451087 2014 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Finite mixture partial least squares for segmentation and behavioral characterization of auction bidders
ترجمه فارسی عنوان
کمترین مربعات تقسیم جزئی برای تقسیمبندی و ویژگیهای رفتاری داوطلبان حراج
کلمات کلیدی
تقسیم بندی و پروفایل کمترین مربعات تقسیم جزئی، داده کاوی، تجارت الکترونیکی، رفتارهای حراج آنلاین
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
چکیده انگلیسی


• We demonstrate how to segment, without a priori knowledge, online bidders using real time data.
• Our model can capture and evaluate bidder behavior and personality.
• FIMIX-PLS is capable of profiling and segmenting the bidders based on their individual characteristics.
• Analysis confirms FIMIX-PLS' ability of segmenting bidders into statistically identifiable homogeneous groups.

The purpose of this study is to demonstrate how to empirically segment, without a priori knowledge, online auction bidders using experimental data and finite mixture models. The proposed method utilizes a finite mixture partial least squares (FIMIX-PLS) approach to examine bidder behaviors and personality characteristics, evaluate bidder differences, and then segment the bidders. The empirical experiment is conducted for two different auction mechanisms — English and Vickrey. Results from both auction mechanisms indicate that FIMIX-PLS is capable of profiling and segmenting the bidders based on their individual characteristics. The post hoc analysis confirms the segmentation scheme and the capability of FIMIX-PLS in segmenting bidders into statistically identifiable homogeneous groups without a priori information of group characteristics. Such advantage is practical for online businesses dealing with increasing amount of data about their customers on a real time basis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 57, January 2014, Pages 200–211
نویسندگان
, , , ,