The ‘Biophilic Organization’: An Integrative Metaphor for Corporate Sustainability

This paper proposes a new organizational metaphor, the ‘Biophilic Organization’, which aims to counter the bio-cultural disconnection of many organizations despite their espoused commitment to sustainability. This conceptual research draws on multiple disciplines such as evolutionary psychology and architecture to not only develop a diverse bio-cultural connection but to show how this connection tackles sustainability, in a holistic and systemic sense. Moreover, the paper takes an integrative view of sustainability, which effectively means that it embraces the different emergent tensions. Three specific tensions are explored: efficiency versus resilience, organizational versus personal agendas and isomorphism versus institutional change. In order to illustrate how the Biophilic Organization could potentially provide a synthesis strategy for such tensions, healthcare examples are drawn from the emerging fields of Biophilic Design in Singapore and Generative Design in the U.S.A. Finally, an example is provided which highlights how a Taoist cultural context has impacted on a business leader in China, to illustrative the significance of a transcendent belief system to such a bio-cultural narrative

Facial communicative signals: valence recognition in task-oriented human-robot interaction

From the issue entitled "Measuring Human-Robots Interactions" This paper investigates facial communicative signals (head gestures, eye gaze, and facial expressions) as nonverbal feedback in human-robot interaction. Motivated by a discussion of the literature, we suggest scenario-specific investigations due to the complex nature of these signals and present an object-teaching scenario where subjects teach the names of objects to a robot, which in turn shall term these objects correctly afterwards. The robot’s verbal answers are to elicit facial communicative signals of its interaction partners. We investigated the human ability to recognize this spontaneous facial feedback and also the performance of two automatic recognition approaches. The first one is a static approach yielding baseline results, whereas the second considers the temporal dynamics and achieved classification rate