Anne-Laure Mention

Abstract
Scholars and practitioners continue to recognize the crucial role of entrepreneurial ecosystems (EEs) in creating a conducive environment for productive entrepreneurship. Although EEs are fundamentally interaction systems of hierarchically independent yet mutually dependent actors, few studies have investigated how interactions among ecosystem actors drive the entrepreneurial process. Seeking to address this gap, this paper explores how ecosystem actor interactions influence new ventures in the financial technology (fintech) EE of Singapore. Guided by an EE framework and the use of an exploratory-abductive approach, empirical data from semi-structured interviews is collected and analyzed. The findings reveal four categories representing both the relational perspective, which features interaction and intermediation dynamics, and the cultural perspective, which encompasses ecosystem development and regulatory dynamics. These categories help explain how and why opportunity identification and resource exploitation are accelerated or inhibited for entrepreneurs in fintech EEs. The present study provides valuable contributions to scholars and practitioners interested in EEs and contributes to the academic understanding of the emerging fintech phenomenon.

Abstract
This study tackles the initiation of industry convergence to develop a patent-level framework aiming to anticipate convergence. Despite the vast amount of studies in the convergence literature, much remains to be understood about the dynamics of convergence, from the outset at the technology level to further development at the industry level. The evaluation of technical domain combinations facilitates the identification of industry convergence at early stages. This study analyzes patent data to measure the continuity in the combination of technical knowledge domains, which drives convergence. We also identified the patent indicators which promote the formation of the influential combinations that drive industry convergence. The present findings revealed that only a few unprecedented combinations in technical domains developed in future technologies, which implies the significance of distinguishing the combinations that may be expanding rapidly in subsequent years. The results also reported that the influential combinations need to be identifiable for future inventors, useful and practical for future technologies, and compatible with a variety of technical domains. This research provides insights for studies in innovation and technology management as well as implications for inventors, managers, and policymakers toward technology road-mapping.

Abstract
Research on incubation models indicates that incubators and accelerators are crucial catalysts for the development of start-ups. To facilitate start-ups in financial markets, several regulatory authorities have adopted a new incubation model called a ?regulatory sandbox?. Regulatory sandboxes enable eligible applicants to test their technology-enabled financial solutions for a certain period of time (subject to conditions the regulator imposes). As such, these instruments allow innovation while preventing severe instability in financial markets caused by systemic risk. Despite their importance, management research has devoted little attention to studying how sandboxes operate as a new incubation model. In our abductive study, we adopt the activity system framework and a qualitative analysis approach to investigate the activities of five leading sandboxes and compare them with the activities of other incubation models. The data analysis yielded an activity model with three design elements (achieving membership, participating and detaching) and one design theme (improving connectedness). Thus, sandboxes are characterized by providing regulatory guidance and facilitating access to testing across international jurisdictions, distinguishing them from both generic and specialized incubation models. Our primary contribution to the incubation literature is extending the knowledge of a unique incubation model through a set of theoretical propositions.

Abstract
What causes ineffective external idea evaluation in open innovation (OI) still remains an unsolved puzzle, with most such studies focused on creative idea generation or using samples of untrained evaluators. To help better understand the microfoundations of OI, this article examines the effects of mood on external idea evaluation using a practitioner sample. Drawing on "mood-as-an-input" theory, in two behavioral experiments using music induction, cognitive tasks, and idea framing, we test how one's mood affects the innovativeness rating of an externally developed idea, and examine whether this effect is stable within a mood state regardless of the level of creativity (high and low) of an idea. We found that people in happy and sad mood conditions differ in their evaluation of the same external idea, which is explained by differences in assessment of creativity of an idea and not the perceived certainty of its success. Moreover, a given mood state does not affect how ideas low in creativity are rated in their innovativeness, compared to ideas high in creativity. This article by investigating effects of mood within an OI process augments individual level OI literature, while informing the ways external idea evaluation can be managed toward enhancing OI potential.

Abstract
In this chapter, the authors examine whether an individual’s wellbeing is enhanced by the level of innovation in the country in which they live. The study is based on quantitative analysis of cross-country data from the World Values Survey. The authors use the Global Innovation Index (GII) and the number of recorded patents as proxies for country-level innovation and find that innovation is positively associated with subjective wellbeing.