In the era of rapid technological innovation and high social and economic uncertainty, government and companies are required to make decisions more quickly than ever. Although various large big-data such as transaction logs and location information, various studies showed that they are not useful for managerial or policy decision making as it is, because the big-data suffer from various biases such as selection bias. This team will develop new data-fusion techniques for various types of datasets including governmental survey data, big-data and macro-level information, to improve accuracy of public statistical information, or to aid investment/managerial decision making. We also investigate new data acquisition methods in business and economic fields which utilize statistical machine learning methods.
Development of new data acquisition methods in business and economic fields
Inference with anonymization of big-data in business and economics fields