The demand for organic food products in China is growing in response to both increased spending power and food safety concerns. However, identifying likely buyers of organic products proves challenging due to their re...
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ISBN:
(纸本)9781890843298
The demand for organic food products in China is growing in response to both increased spending power and food safety concerns. However, identifying likely buyers of organic products proves challenging due to their relatively small fraction in the overall population. Our study explores applications of machine learning algorithms for effective management of organic food marketing campaigns in China. Based on the data we collected through an online choice-experiment type questionnaire of Chinese consumers, a purchase likelihood estimation framework has been developed that utilizes customer profile traits such as age group, family status, education level, and geographic location. In addition, we apply clustering techniques to perform data-driven organic market segmentation and identify consumer profiles ready to pay more for high quality, certified organic products. The resulting market segments are compared to various types of organic consumers discussed in the literature. Our algorithms provide a useful framework for online retailers who are seeking lean strategies of market entry in China with their health food brands.
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first ...
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ISBN:
(纸本)9781479958771
Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users.
Quote data are a vital part of information almost every trading algorithm relies on. While increasing effort is put into making trading algorithms better, the quote data as foundation of the algorithms is often assert...
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ISBN:
(纸本)9781479923809
Quote data are a vital part of information almost every trading algorithm relies on. While increasing effort is put into making trading algorithms better, the quote data as foundation of the algorithms is often asserted to be perfect. In reality, much work is needed to acquire good quote data. This paper shows methods of collecting and storing quote data and how to measure and improve its quality and completeness. Applying these methods leads to greatly improved results and higher speed of algorithms which rely on this quote data.
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