The Convergence of Ikigai and Design Thinking: Crafting a Purposeful Framework

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Victor Christianto
Florentin Smarandache

Abstract

In an era where innovation is not just about solving problems but also about enhancing human experiences and fostering personal fulfillment, the convergence of Ikigai principles with Design Thinking methodology offers a promising avenue for holistic problem-solving and innovation. This paper explores the intersection of Ikigai—a Japanese concept representing one's reason for being—and Design Thinking—a human-centered approach to innovation. We propose a conceptual framework, termed Ikigai-Driven Design (IDD), which integrates the principles of Ikigai with the stages of Design Thinking. IDD comprises five main stages: Empathize, Define, Ideate, Prototype, and Test, each combining elements of Ikigai and Design Thinking to foster purposeful innovation. The Empathize stage emphasizes understanding what users love and what the world needs, drawing insights from human-centered research methods. In the Define stage, practitioners frame problems through the lens of Ikigai, aligning identified needs with their own passions and strengths. The Ideate stage encourages divergent thinking, leveraging practitioners' Ikigai to generate creative solutions. Prototypes created in the Prototype stage embody practitioners' purpose and values, tested and refined based on user feedback in the Test stage. By integrating Ikigai principles with Design Thinking methodology, IDD offers a structured yet flexible approach to innovation that resonates deeply with users and contributes to practitioners' sense of fulfillment and meaning.

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How to Cite
Christianto, V. and Smarandache, F. (2024) “The Convergence of Ikigai and Design Thinking: Crafting a Purposeful Framework”, Sustainable Machine Intelligence Journal, 7, pp. (1):1–8. doi:10.61356/SMIJ.2024.77101.
Section
Original Article

How to Cite

Christianto, V. and Smarandache, F. (2024) “The Convergence of Ikigai and Design Thinking: Crafting a Purposeful Framework”, Sustainable Machine Intelligence Journal, 7, pp. (1):1–8. doi:10.61356/SMIJ.2024.77101.