Purpose Restaurant entrepreneurs are increasingly leveraging crowdfunding as an alternative financing mechanism. In the context of restaurant crowdfunding, studies have identified factors related to campaign communication that affect crowdfunding success from the entrepreneurs’ perspective. Integrating a funder perspective, this study aims to investigate the role of the consumption value offered by rewards and builds a value-based understanding of restaurant crowdfunding. Design/methodology/approach This study uses a sample of 3,134 restaurant campaigns launched on the Kickstarter crowdfunding platform, and texts of 34,128 rewards were analyzed using a Python program. A hierarchical linear regression approach with a generalized logistic regression model was adopted to test hypothesized relationships. Findings Drawing upon consumption value theory (CVT), this study finds that in restaurant crowdfunding, utilitarian value holds a strong inverted-U relationship and participatory value holds a strong linear relationship with crowdfunding success. However, socioemotional value does not have a significant effect on outcomes. This study also finds evidence for positive effects of greater variety, higher number of rewards and lower average pledge level on restaurant crowdfunding success. Practical implications This study extends the literature on restaurant crowdfunding by integrating insights on the effects of value offered through rewards. Primarily, this study finds evidence for distinct effects of consumption values for restaurant crowdfunding audience. Practically, this study holds implications for reward menu design and value offering design for restaurant entrepreneurs seeking crowdfunding. Originality/value Restaurant crowdfunding has been studied to a limited extent, with extant literature focusing on characteristics of campaign descriptions. The role of rewards is uncovered using CVT and thus a value-based understanding of restaurant crowdfunding is presented.

Fine-grained financial sentiment analysis on news headlines is a challenging task requiring human-annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple entities are present in a news headline. In an effort to further research in this area, we make publicly available SEntFiN 1.0, a humanannotated dataset of 10,753 news headlines with entity-sentiment annotations, of which 2,847 headlines contain multiple entities, often with conflicting sentiments. We augment our dataset with a database of over 1,000 financial entities and their various representations in news media amounting to over 5,000 phrases. We propose a framework that enables the extraction of entity-relevant sentiments using a feature-based approach rather than an expression-based approach. For sentiment extraction, we utilize 12 different learning schemes utilizing lexicon-based and pretrained sentence representations and five classification approaches. Our experiments indicate that lexicon-based N-gram ensembles are above par with pretrained word embedding schemes such as GloVe. Overall, RoBERTa and finBERT (domain-specific BERT) achieve the highest average accuracy of 94.29% and F1-score of 93.27%. Further, using over 210,000 entity-sentiment predictions, we validate the economic effect of sentiments on aggregate market movements over a long duration.

As the world moves toward the "New Normal" with borderless innovation and remote work, Multinational Enterprises (MNEs) are increasingly involved in tapping talent that is external to organizational boundaries. This study distills learnings from the use of globally distributed external talent that has been facilitated by innovation intermediaries, a development that holds significant managerial implications for the post-COVID industrial era. Moving beyond the conventional and recognized need for global talent management practices, we provide a perspective on talent management outside organizational boundaries, a topic that that has received limited attention so far. Through the lenses of open innovation and talent management, we define a typology of innovation problems on the basis of latent talent needs. We take a step further, and for each problem type, we identify the competencies that are relevant, the reward mechanisms of the intermediaries, and the extent of collaboration required with internal talent. This typology provides a basis for researchers in the talent management community to study talent acquisition and management strategies of MNEs across various contexts and various innovation needs.

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