Conversational agents are becoming an essential part of a growing number of personal and commercial encounters, bringing the issue of Conversational Marketing to a broader audience. A conversational agent is a developing technology that will be used in various fields throughout life, including e-commerce. The common characteristics of any conversational agent in whatever area are their capacity to engage in one-to-one personalised real-time dialogue with a human user and their availability 24 hours a day. Scale items for conversational agent phenomena have not been created scientifically or managerially in a business environment. The primary goal of this study was to develop and validate a new scale for conversational agents that could be used to quantify individual interactions in conversational marketing. As a result, the creation of a new scale for conversational agents with the objective of measuring individual customer interactions in conversational marketing was separated into two phases: Scale Development and Scale Validation. The Conversational Agent Usage Scale was developed and validated as a consequence of pilot studies. Additionally, this article discusses the practical consequences of conversational marketing, which can now be accomplished through the use of the Conversational Agent Usage Scale, which may be used by Customer Service & Support, Marketing, and Sales departments.

We conducted an experiment to explore the effect on aesthetic judgments influenced by the presence and awareness of the title of the abstract paintings produced by Artificial Intelligence. Fiftytwo participants (52 students from the Faculty of Fine Arts) were randomly signed into control and experimental groups. Participants of the control group were asked to rate five abstract paintings created by various artists, while the experimental group also rated the same paintings only differing in the names of the author that they were made by Artificial Intelligence. Consequently, in our research, we adopted Berlyne's psychobiological theory, which focuses on the role of arousal as one of the primary determinants of aesthetic preference. The results suggest that the name of AI on title can function as a novelty and surprising reference to denote performance for our visual arts perception despite the fact that it is not created by AI. However, "complexity," "interestingness," and "ambiguity" variables didn't show any statistic significant. These findings extend past research by demonstrating that title presentation affects the perception of abstract art by the participants.

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.

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