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Improving a startup’s ability to obtain funding is critical to the survival of the organization. Although existing studies have observed various biases in investment decisions, few have studied the neural mechanisms behind such behavioral observations. We propose to apply cutting-edge neuroscientific techniques to uncover the neural processes engaged during pitches by entrepreneurs to investors and to use this new knowledge to identify strategy artifacts promoting pitch success. We hypothesize that pitches are dynamically shaped by covert cognitive, emotional, and social processes, which are in turn influenced by tactical approach (story-telling vs dry facts), physical context (online vs in-person), and demographics (gender, ethnicity). The role of inter-brain synchrony (i.e., correlation of cortical activity between brains) – within the startup team or between the entrepreneurs and investors – in pitch outcomes remains unknown. By uncovering the covert processes that mediate pitch outcomes, we provide an evidence-based, scientific approach to improving pitch success.

This chapter focuses on the micro-contexts of cross-innovation between digital audiovisual media and the health care sector by examining two cases, both start-ups working on virtual reality-assisted rehabilitation solutions. Through a discussion of the two cases, this chapter aims to elucidate the broader dynamics of digital health care as experienced by innovators seeking to contribute to it. It addresses the challenges faced by innovators, including the lengthy and costly nature of medical licensing, the inflexibility and fragmentation of pertinent regulations, and health care institutions’ and insurers’ resistance to change. It also highlights the importance of networking and the emergence of digital health care as a distinct and increasingly visible epistemic community, while touching upon the tensions between the public and the private sectors as a target market for innovators.

Chapter 4 presents the research into the attributes of a stimulus, which the brain uses to construct a perception of the external stimulus. The processes used in all five senses are examined and compiled into a collective model of the processes the perceptual system uses to discriminate and understand an external stimulus. While there are many commonalities across the senses, the structure of the discipline (energy) each system processes yields unique insights into the processes of the total system.

This chapter presents a novel human arm gesture tracking and recognition technique based on fuzzy logic and nonlinear Kalman filtering with applications in crane guidance. A Kinect visual sensor and a Myo armband sensor are jointly utilised to perform data fusion to provide more accurate and reliable information on Euler angles, angular velocity, linear acceleration and electromyography data in real time. Dynamic equations for arm gesture movement are formulated with Newton–Euler equations based on Denavit–Hartenberg parameters. Nonlinear Kalman filtering techniques, including the extended Kalman filter and the unscented Kalman filter, are applied in order to perform reliable sensor fusion, and their tracking accuracies are compared. A Sugeno-type fuzzy inference system is proposed for arm gesture recognition. Hardware experiments have shown the efficacy of the proposed method for crane guidance applications.

This chapter uses the expertise literature (e.g., Ericsson et al., 2018; Ericsson & Pool, 2016) to explore ways that entrepreneurship education might be enhanced through the deliberate practice of specific entrepreneurial behaviors and cognitive skills. What is appealing about the use of expertise methods and theory is the application of very rigorous standards for improving behavioral and cognitive skills that are correlated to better outcomes. The authors suggest that an expertise approach challenges entrepreneurship educators to identify what aspects of the entrepreneurial process might be “deliberately practiced” and to consider modifying aspects of training entrepreneurs to better develop their entrepreneurial capabilities.

This chapter develops Lefebvre’s concept of rhythmanalysis to investigate the ways super-diversity comes to life in the everyday city through the intersection of the spatial and temporal. The chapter explores the multicultural intimacies of streets in a London neighbourhood through a close ethnographic focus on rhythms and atmospheres using slow-motion video. The research contributes to an emerging field of visual ethnographic scholarship by presenting slow-motion video as a method to explore the ‘presence’ (Lefebvre, 2004) of super-diversity and conviviality on the street.

I argue that in slowing down the encounters of the street, slow-motion video shows the often overlooked sensible and affective elements of super-diverse urban space, the mundane interactions between bodies, materials and technologies that create a form of ‘convivial affect’. I argue that these everyday encounters are shaped by a situated politics of difference and yet are also mediated by wider rhythms and atmospheres, contributing to a sense of ‘social time’. I draw attention to both the human and non-human elements of the streets. These material and technological elements can uncover the wider discourses and circulatory regimes of atmospheres in urban super-diverse neighbourhoods, focussing on their relation to broader flows of capital, forms of postcolonial culture and translocality.

This research has implications for how we understand super-diversity and its manifestations in urban space. It encourages policymakers and academics to recognise the affective human and non-human encounters that are a crucial aspect of conviviality, the everyday ways we live together with difference.