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Frugal Innovation: Context, Theory, and Practice  

Lukas Neumann and Oliver Gassmann

Frugal innovation as a concept was initially sparked by a groundbreaking article published in The Economist in 2010. In it, the conception and application of a handheld electrocardiogram (ECG), the Mac 400, specifically designed to serve the rural population in India, was introduced. Every aspect of this product and its ecosystem was designed to serve the customer at less than 25% of the original cost. Since this publication, a lively discussion around this concept has developed in academia as well as in the industry. As a term, “frugal innovation” refers to solutions (products or services), methods, or designs that focus on serving new customers in resource-constrained contexts at the bottom of the pyramid (BoP) and/or emerging and developing markets. This understanding has broadened somewhat as such innovations gain increasing attention and relevance throughout all customer segments across the globe. What remains consistent is that frugal innovation is based on a new type of value architecture that is specifically developed to serve customers’ needs in the respective context by utilizing as few resources as possible. This approach leads to many cases where frugal innovations are novel and disruptive to their market environment. Research shows that for firms, especially traditional “Western” ones, these innovations require significant changes in firms’ activities along the entire value chain.

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Innovation in Artificial Intelligence: Illustrations in Academia, Apparel, and the Arts  

Andreas Kaplan

Artificial intelligence (AI), commonly defined as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation,” can be classified into analytical, human-inspired, and humanized AI depending upon its application of cognitive, emotional, and social intelligence. AI’s foundations took place in the 1950s. A sequence of vicissitudes of funding, interest in, and support for AI followed subsequently. In 2015 AlphaGo, Google’s AI-driven system, won against the human grandmaster in the highly complex board game Go. This is considered one of the most significant milestones in the development of AI and marks the starting of a new period, enabling several AI innovations in a variety of sectors and industries. Higher education, the fashion industry, and the arts serve as illustrations of areas wherein ample innovation based on AI occurs. Using these domains, various angles of innovation in AI can be presented and decrypted. AI innovation in higher education, for example, indicates that at some point, AI-powered robots might take over the role of human teachers. For the moment, however, AI in academia is solely used to support human beings, not to replace them. The apparel industry, specifically fast fashion—one of the planet’s biggest polluters—shows how innovation in AI can help the sector move toward sustainability and eco-responsibility through, among other ways, improved forecasting, increased customer satisfaction, and more efficient supply chain management. An analysis of AI-driven novelty in the arts, notably in museums, shows that developing highly innovative, AI-based solutions might be a necessity for the survival of a strongly declining cultural sector. These examples all show the role AI already plays in these sectors and its likely importance in their respective futures. While AI applications imply many improvements for academia, the apparel industry, and the arts, it should come as no surprise that it also has several drawbacks. Enforcing laws and regulations concerning AI is critical in order to avoid its adverse effects. Ethics and the ethical behavior of managers and leaders in various sectors and industries is likewise crucial. Education will play an additional significant role in helping AI positively influence economies and societies worldwide. Finally, international entente (i.e., the cooperation of the world’s biggest economies and nations) must take place to ensure AI’s benefit to humanity and civilization. Therefore, these challenges and areas (i.e., enforcement, ethics, education, and entente) can be summarized as the four summons of AI.