2,364 research outputs found
Big data from customers and non-customers through crowdsourcing, citizen science and crowdfunding
No full text
Purpose
The unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.
Design/methodology/approach
This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.
Findings
Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.
Originality/value
This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.
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How do banking fintech services affect SME debt?
No full textFintech technologies have become increasingly important in the banking industry, as they allow alternative effective means to interact with clients and collect hard information, i.e. codifiable data, to make better lending decisions. However, the advent of technology contrasts with the traditional bank-firm relationship based on human interactions and soft information. This study examines whether fintech favors or hampers the amount of debt finance issued by SMEs. Our findings reveal that the use of internet banking reduces SME debt, suggesting that credit decisions based on hard information reduce the likelihood of SMEs using bank debt. A key implication of our findings is that banks and entrepreneurs should reinforce their personal relationships
Visitor-sensing: Involving the crowd in cultural heritage organizations
No full textAs organizations are increasingly involving individuals across their boundaries in the generation of new knowledge, crowd involvement can also be beneficial to cultural heritage organizations. We argue that in an “Open Innovation in Science” approach, visitors can contribute to generate new scientific knowledge concerning their behavior and preferences, by which museum managers can re-design the cultural offerings of their institutions in ways that generate major economic and social impacts. Accordingly, we advance visitor-sensing as a novel framework in which museum managers leverage digital technologies to collect visitors’ ideas, preferences, and feedback in order to improve path design and the organization of artwork in exhibitions, and to shape a more satisfying museum experience for visitors. We contend that visitor-sensing has the potential to yield higher numbers of visitors, with positive impacts in terms of increased revenues and increased literacy of the general public, thus benefiting the economic and social sustainability of cultural organizations towards the achievement of the Sustainable Development Goals outlined in the Agenda 2030
Supplementary dataset Pinus Taeda [Conjunto de datos]
No full textTrial information and family numbers of the Pinus Taeda L. trial.
Diameter at breast height of the Pinus taeda L. data set will be available upon request.
Supplementary dataset Pinus Taeda for Cappa, E.P., Muñoz, F., Sanchez, L. et al. A novel individual-tree mixed model to account for competition and environmental heterogeneity: a Bayesian approach. Tree Genetics & Genomes 11, 120 (2015).Instituto de Recursos BiológicosFil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Cappa, Eduardo Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); Argentin
Collecting Money through Blockchain Technologies: First Insights on the Determinants of the Return on Initial Coin Offerings
No full textInitial Coin Offerings (ICOs), i.e. the initial offer of a crypto-token, represent an increasingly popular method to raise money. However, the determinants of ICOs ́ returns for investors are still overlooked. Following this cue, the empirical outcomes of our study based on crypto-tokens issued between 2017 and 2018 evidence the main determinants of ICOs ́ returns: first, crypto-tokens returns are positively associated to Ether’s returns; second, ICO price is negatively associated to later price increases; third, crypto-tokens returns are lower when they are offered in presale; finally, the more a crypto-token price increases between the ICO and the listing-date on the secondary-market and the more its price rises in the following month. In so doing, we contribute to a better understanding of the ICO phenomenon and highlight which aspects may benefit fund raising, which are relevant for the establishment of new startups and more broadly for the economic development of a country
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