Xiaolan Fu

Pervez N. Ghauri

Juha Väätänen

This volume reports the results of the large international 'MNEmerge' research project, financed by the European Commission, and provides an understanding of the impact of multinational enterprises on United Nations Millennium Development Goals and successive Sustainable Development Goals in developing countries.

Multinational Enterprises and Sustainable Development

Andreas K. Engel

Jianwei Zhang

Stefan Wermter

Changshui Zhang

Fuchun Sun

Brigitte Röder

Gui Xue

The purpose of this Research Topic is to reflect and discuss links between neuroscience, psychology, computer science and robotics with regards to the topic of cross-modal learning which has, in recent years, emerged as a new area of interdisciplinary research. The term cross-modal learning refers to the synergistic synthesis of information from multiple sensory modalities such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Cross-modal learning is a crucial component of adaptive behavior in a continuously changing world, and examples are ubiquitous, such as: learning to grasp and manipulate objects; learning to walk; learning to read and write; learning to understand language and its referents; etc. In all these examples, visual, auditory, somatosensory or other modalities have to be integrated, and learning must be cross-modal. In fact, the broad range of acquired human skills are cross-modal, and many of the most advanced human capabilities, such as those involved in social cognition, require learning from the richest combinations of cross-modal information. In contrast, even the very best systems in Artificial Intelligence (AI) and robotics have taken only tiny steps in this direction. Building a system that composes a global perspective from multiple distinct sources, types of data, and sensory modalities is a grand challenge of AI, yet it is specific enough that it can be studied quite rigorously and in such detail that the prospect for deep insights into these mechanisms is quite plausible in the near term. Cross-modal learning is a broad, interdisciplinary topic that has not yet coalesced into a single, unified field. Instead, there are many separate fields, each tackling the concerns of cross-modal learning from its own perspective, with currently little overlap. We anticipate an accelerating trend towards integration of these areas and we intend to contribute to that integration. By focusing on cross-modal learning, the proposed Research Topic can bring together recent progress in artificial intelligence, robotics, psychology and neuroscience.

Cross-Modal Learning: Adaptivity, Prediction and Interaction

Liming Chen

Ke Zhao

Tong Chen

Hongying Meng

Moi Hoon Yap

Jiajin Yuan

Adrian Keith Davison

Facial Expression Recognition and Computing: An Interdisciplinary Perspective

A rigorous examination of the motivations, sources, obstacles to and consequences of China's drive to become a leading innovative nation.

China's Path to Innovation

Investigating the nature, drivers and sources of innovation in Africa, this book examines the channels for effective diffusion of innovation in and to Africa under institutional, resource and affordability constraints. Fu draws on almost a decade of research on innovation in Africa to explore these issues and unpack the process, combining a rigorous statistical analysis of a purposely designed multi-wave, multi-country survey with in-depth studies of representative cases. Building on this research, Fu argues that African firms are innovative but unsupported. Those 'under-the-radar' innovations that widely exist in Africa as a result of the constraints are not sufficient to enable Africa to leapfrog the innovation gap in the era of the fourth Industrial Revolution. This is the first comprehensive analysis of the creation and diffusion of innovation in low income countries. It also provides the first survey-based analysis of innovation in the informal economy.

The Nature and Sources of Innovation in Africa

Innovation under the Radar

The first systematic and comprehensive analysis of innovation in Africa based on mixed methods and dedicated firm-level, multi-country, multi-year survey data. For researchers, graduate students and policy makers in the fields of innovation studies, African business, international business, and development studies.

Xiaolan Fu

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