The Innovativeness of Foreign Firms in China

This paper studies the relationship between foreign ownership and innovations of high novelty in context of advanced developing countries. We develop hypotheses about a direct relationship in terms of two dimensions, propensity and intensity of innovations of high novelty, and a contingency hypothesis about the moderating impact of R&D internationalisation on the relationship with propensity. The analysis is based on innovation survey data on manufacturing firms from Jiangsu province of China. Hypotheses are tested using non-parametric methods. We find that foreign firms do not have a higher propensity of innovations of high novelty, not even when they engage in formal R&D. However, the evidence suggests that foreign firms have a higher intensity of innovations of high novelty than domestic firms.multinational enterprises, foreign firms, innovation, manufacturing, China

ALIP: Adaptive Language-Image Pre-training with Synthetic Caption

Contrastive Language-Image Pre-training (CLIP) has significantly boosted the performance of various vision-language tasks by scaling up the dataset with image-text pairs collected from the web. However, the presence of intrinsic noise and unmatched image-text pairs in web data can potentially affect the performance of representation learning. To address this issue, we first utilize the OFA model to generate synthetic captions that focus on the image content. The generated captions contain complementary information that is beneficial for pre-training. Then, we propose an Adaptive Language-Image Pre-training (ALIP), a bi-path model that integrates supervision from both raw text and synthetic caption. As the core components of ALIP, the Language Consistency Gate (LCG) and Description Consistency Gate (DCG) dynamically adjust the weights of samples and image-text/caption pairs during the training process. Meanwhile, the adaptive contrastive loss can effectively reduce the impact of noise data and enhances the efficiency of pre-training data. We validate ALIP with experiments on different scales of models and pre-training datasets. Experiments results show that ALIP achieves state-of-the-art performance on multiple downstream tasks including zero-shot image-text retrieval and linear probe. To facilitate future research, the code and pre-trained models are released at https://github.com/deepglint/ALIP.Comment: 15pages, 10figures, ICCV202

Foreign ownership and novelty of product innovations in China

Presented at the GLOBELICS 6th International Conference 2008 22-24 September, Mexico City, Mexico.This paper examines a relationship between foreign ownership and innovation novelty in the context of host advanced developing economies. The analysis is focused on two dimensions of product innovation novelty, the novelty of introduced innovations and the economic benefits from introduced novelty. We find that foreign affiliates do not have higher odds than domestic firms to introduce product innovations of higher novelty. Indeed, the findings indicate that the higher odds of foreign firms of introducing innovations of higher novelty are moderated by exploitation of ownership advantages and by a host market orientation. However, we find that foreign affiliates have higher odds to capture higher economic benefits from product innovations of higher novelty than domestic firms. Hence, although foreign affiliates are not higher up on an innovation novelty ladder than domestic firms, they replenish their product and innovation portfolio with innovations of higher novelty at a faster rate than domestic firms