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Convergent Innovation in Food through Big Data and Artificial Intelligence for Societal-Scale Inclusive Growth

机译:通过大数据和人工智能实现社会规模包容性增长的融合食品创新

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Inclusive innovation has not yet reached societal scale due to a well-entrenched divide between wealth creation and social equity. Taking food as the initial test bed, we have proposed the convergent innovation model to address such challenges still facing 21st century society by bridging sectors and disciplines around an integrated goal on both sides of the social-economic divide for innovations that target wealth creation with an upfront consideration of its externalities. The convergent innovation model is empowered by two key enablers that integrate an advanced digital infrastructure with leading scientific knowledge on the drivers of human behaviour in varying contexts. This article discusses the structure, methods, and development of an artificial intelligence platform to support convergent innovation. Insights are gathered on consumer sentiment and behavioural drivers through the analysis of user-generated content on social media platforms. Empirical results show that user discussions related to marketing, consequences, and occasions are positive. Further regression modelling finds that economic consequences are a strong predictor of consumer global sentiment, but are also sensitive to both the actual price and economic awareness. This finding has important implications for inclusive growth and further emphasizes the need for affordable and accessible foods, as well as for consumer education. Challenges and opportunities inspired by the research results are discussed to inform the design, marketing, and delivery of convergent innovation products and services, while also contributing to dimensions of inclusion and economic performance for equitable health and wealth.
机译:由于财富创造和社会公平之间的根深蒂固的鸿沟,包容性创新尚未达到社会规模。我们以食品作为最初的试验床,提出了融合创新模型,通过围绕社会经济鸿沟两侧的综合目标衔接部门和学科,针对以财富创造为目标的创新,以解决21世纪社会仍然面临的挑战。预先考虑其外部性。融合创新模型由两个关键推动力推动,这些推动力将先进的数字基础架构与有关在不同情况下人类行为驱动因素的领先科学知识相结合。本文讨论了支持融合创新的人工智能平台的结构,方法和开发。通过分析社交媒体平台上用户生成的内容,可以收集有关消费者情绪和行为驱动因素的见解。实证结果表明,与营销,后果和场合有关的用户讨论是积极的。进一步的回归模型发现,经济后果是消费者全球情绪的有力预测指标,但对实际价格和经济意识也很敏感。这一发现对包容性增长具有重要意义,并进一步强调了对可负担得起的食品以及消费者教育的需求。讨论了研究结果所带来的挑战和机遇,以为融合创新产品和服务的设计,营销和交付提供信息,同时也有助于实现包容性和实现公平健康和财富的经济绩效。

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