Digital sport entrepreneurial ecosystems

Abstract

The entrepreneurial ecosystems literature has increasingly explored network relationships between different stakeholders, as well as the role of context. This article addresses the challenge of including a sport context in the entrepreneurial ecosystem literature thereby contributing to the sport entrepreneurship literature by bringing insights from entrepreneurship ecosystem research. In‐depth interviews of football stakeholders in the sport entrepreneurship ecosystem are conducted in terms of understanding the emergence of digital sport start‐ups. The issues raised help explore the changing nature of digital entrepreneurial ecosystems to take into account new sport technological advances. Mixed embeddedness theory is used as the conceptual foundation to understand sport digital entrepreneurial ecosystems. Key management practices are identified in terms of sport start‐ups participating in entrepreneurial ecosystems. The article concludes by making suggestions for future research.

Lifestyle Entrepreneurship: Literature Review and Future Research Agenda

“…ALE activities, such as fitness/ sport or recreational activities, allow individuals to earn a living while participating in their favourite activity (Hoyte, 2019; Jones et al, 2017). For instance, investigating digital sport entrepreneurs, Ratten and Thompson (2020, p. 568) report that such entrepreneurs ‘are often motivated by passion and lifestyle reasons more so than other types of entrepreneurs’. Ikonen (2017) finds that passion for dogs was the main factor behind dog‐related rural hospitality businesses.…”

Sensitizing Netizen’s behavior through influencer intervention enabled by crowdsourcing – a case of reddit

“…Sentiment analysis on a textual dataset can be conducted through two approachesthe lexicon-based approach and the machine learning approach (Kharde and Sonawane 2016;Piryani, Madhavi, and Singh 2017;Taboada et al 2011). A lexicon-based approach relies on a pre-classified list of words or lexicons where the semantic orientation of each word is predefined and categorised to be a positive, negative, or neutral sentiment and also into eight emotionsanger, anticipation, disgust, fear, joy, sadness, surprise, and trust.…”

Netizens' behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach

“…In contrast, the use of social media analytics to catch consumer emotions can yield a more specific outcome due to the normal dedication to pastime and appetite for self-disclosure (Yadav et al, 2021a, b and c). Although research has been carried out on prominent social media sites, such as Facebook (Arora et al, 2019;Kulkarni et al, 2020) and Twitter (Abu-Salih et al, 2018;Ratten and Thompson, 2020), relatively only a few studies have been carried out on a website, such as Reddit, in the sports domain (Peterson, 2019;Xue et al, 2019). A blockchainbased esports framework Also, to the best of our knowledge, no research has been undertaken concerning customers' attitudes towards the platform that brings together esports and its associated entities in a decentralized, peer-to-peer environment.…”

“…, 2020) and Twitter (Abu-Salih et al. , 2018; Ratten and Thompson, 2020), relatively only a few studies have been carried out on a website, such as Reddit, in the sports domain (Peterson, 2019; Xue et al. , 2019).…”