Ephemeral social media platforms, which displays rich media, primarily images and videos, are only available only for a short period of time. It has recently attracted researchers ' attention to better understand how ephemeral social media platforms impact users of social media. We design quantitative survey study that sampling data collected over two weeks (N= 149) to understand engagement differences (consuming, participating, producing) between Millennials and Non-millennials (the Silent Generation, the Baby Boomers, Generation X), on one of the leading ephemeral mobile platforms-on Instagram "Stories". Our data demonstrated that Millennials show statistically significant differences by engaging Instagram "Stories" than Non-millennials. However, results unexpectedly demonstrate that non-millennial (age 40 and more in 2020) users show the same engagement level in "watching" and "reading" ephemeral content as Millennial users.

This research paper provides a comprehensive exploration of the role of Artificial Intelligence (AI) in value creation within the e-commerce sector, focusing on how task and information complexity affect AI deployment. It first outlines the historical development of value theory and value creation, highlighting the shift from traditional modes to modern interactive and co-creation models. Following this, the paper delves into AI’s potential in various e-commerce dimensions including personalization, product recommendation, supply chain efficiency, and more. The centrepiece of the study is a detailed matrix classifying AI into Automated Intelligence, Assisted Intelligence, and Augmented Intelligence, based on the complexity of tasks they execute and the information they analyse. This research study engaged a panel of fifteen industry and academic experts to critically examine and assign complexity scores to various Artificial Intelligence applications within the e-commerce and similar sectors. The experts evaluated task and information complexity, thereby enabling a classification of the applications into a comprehensible matrix. This classification not only provides a guide for AI system design and evaluation but also enhances understanding of their functional dynamics. The paper contributes theoretically by advancing our understanding of AI as a value creator in e-commerce and practically by offering a roadmap for businesses to adopt and leverage AI technologies. As AI continues to revolutionize the e-commerce sector, the findings of this study provide invaluable insights for businesses seeking to gain a competitive advantage in the digital marketplace.