Search

Hub-based entrepreneurial ecosystems (HEEs) have become an important venue for entrepreneurship. This study examines how ecosystem-specific resources and capabilities are orchestrated by ecosystem actors (i.e., hub firms and ecosystem entrepreneurs) to support the development of new ventures in the context of HEEs. Using an explorative single case study approach, we uncover nine distinctive resource orchestration subprocesses that are grouped into three aggregate processes that help sustain enduring entrepreneurship in the HEE context. Our findings extend and complement the literature on entrepreneurship and ecosystems by developing a new resource orchestration model and by illustrating how resource orchestration in an HEE facilitates the synergies across ecosystem ventures as well as the synergies between hub firms and ecosystem entrepreneurs in coexploring and coexploiting new opportunities. [ABSTRACT FROM AUTHOR]

Information on short-term rental platforms plays an important role in consumer purchase behavior. However, information asymmetry between host and guest has been identified as a problem in sharing economy contexts. In this paper, to fill this gap, the authors develop six hypotheses about the focal impacts of self-presentation strategy and the moderating effects of third-party certification. Based on data from Airbnb, the authors first examine how the tactics of self-presentation strategy influence consumer purchase behavior. The results show that different self-presentation tactics affect consumer purchase behavior differently. The authors also found that the third-party certification level weakens the influence of self-presentation strategy interactions on consumer purchase behavior. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate the effects of the innovativeness-related language of crowdfunding pitches on funding outcomes under different boundary conditions specified by two context-relevant signals, entrepreneurial passion and social endorsement. Design/methodology/approach: This study develops six hypotheses about the focal impacts of innovativeness-related language (i.e. incremental and radical) and the moderating effects of entrepreneurial passion and social endorsement. The hypotheses are tested with a sample of 1,057 real projects collected from a typical platform with a computer-aided content analysis method. Findings: This study finds that pitches containing more incremental innovativeness language can generate more funds and that those containing more radical innovativeness language can lead to less favorable funding outcomes. While incremental innovativeness language interacts with entrepreneurial passion language to positively affect funding outcomes, radical innovativeness language requires social endorsement to diminish its negative effect on funding outcomes. Research limitations/implications: This study demonstrates that the content of messages of entrepreneurial narratives does indeed drive funding success in the context of reward-based crowdfunding and confirms the relevance of the consumer perspective of reward-based crowdfunding by using a real dataset. Originality/value: This work joins a number of entrepreneurial narrative studies investigating the impacts of the innovativeness-related language of pitches (issue-relevant content) and their interactions with informational signals (i.e. entrepreneurial passion and social endorsement) on funding outcomes in the context of reward-based crowdfunding. [ABSTRACT FROM AUTHOR]

The sharing economy has risen rapidly in the past decade. The development of shared accommodation encourages more hotels and guesthouses to attract customers through online accommodation-sharing platforms, which has become a meaningful way to fight against the competition of the traditional hotel industry. In this condition, what the hosts are concerned about most is how to attract customers' attention through the platform display to increase reservations. Based on construal level theory, this paper explores how hosts' information displayed on online accommodation-sharing platforms determines consumers' booking behavior by influencing their psychological distance. We use machine learning methods to mine the raw data and extract the representational factors of psychological distance. Based on the data-driven behavior decision-making approach, we collected valid large-scale fine-grained secondary actual consumption data from Airbnb, the world's leading online accommodation-sharing platform, and scientifically and intelligently processed the data using machine learning methods, then tested the hypotheses using the regression analysis software STATA15. Our findings suggest that both social distance and temporal distance have a negative impact on booking behavior of guests. In detail, subject diversity, perspective taking, and facial attractiveness in the dimension of social distance positively influence guests' booking behavior; instant bookable in the temporal distance dimension positively affects booking behavior, while response time has a negative effect. This study contributes to the literature by empirically examining psychological distance in the booking behavior of guests in shared accommodation through the processing and analysis of actual consumption data. The findings have important practical implications for how shared accommodation service providers and sharing economy platform managers can operate better. [ABSTRACT FROM AUTHOR]

Social media use in government has gained a rapid growth in the last few years around the world. China has witnessed a boom in social media use in government, especially government microblogging. In this study, we employ social representation theory as the primary theoretical lens to investigate Chinese government microblogging. We hope the employment of social representation theory could help us overcome the limitation that previous studies focused on the technology and government side. Interviewing data are drawn from a number of Chinese citizens for eliciting their understandings of Chinese government microblogging, followed by structural analytical procedure on the collected data. The social representation elements are obtained and presented in a map. The findings indicate that (1) social media use in government in China is at the stage of fast growth but at low interaction level; (2) governance and social media user experiences are two new but significant concepts that might have been missed in literature; (3) government microblogging does improve citizens’ perceptions toward government; however, the final outcomes like trust and accountability cannot be achieved by relying on social media use in government alone. Theoretical contributions and practitioner implications are then discussed, followed by the limitations. Finally, we present the concluding remarks for this study. [ABSTRACT FROM AUTHOR]