A review of policy levers to reduce meat production and consumption

C Bryant, A Couture, E Ross, A Clark, T Chapman - Appetite, 2024 - Elsevier
It is increasingly apparent that we require a substantial reduction in animal production and
consumption for the sake of the environment and public health. In this paper, we conducted …

Machine learning and marketing: A systematic literature review

V Duarte, S Zuniga-Jara, S Contreras - IEEE Access, 2022 - ieeexplore.ieee.org
Even though machine learning (ML) applications are not novel, they have gained popularity
partly due to the advance in computing processing. This study explores the adoption of ML …

The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation

J Hartmann, J Schwenzow, M Witte - arxiv preprint arxiv:2301.01768, 2023 - arxiv.org
Conversational artificial intelligence (AI) disrupts how humans interact with technology.
Recently, OpenAI introduced ChatGPT, a state-of-the-art dialogue model that can converse …

Machine learning and AI in marketing–Connecting computing power to human insights

L Ma, B Sun - International Journal of Research in Marketing, 2020 - Elsevier
Artificial intelligence (AI) agents driven by machine learning algorithms are rapidly
transforming the business world, generating heightened interest from researchers. In this …

Sentiment analysis in the age of generative AI

JO Krugmann, J Hartmann - Customer Needs and Solutions, 2024 - Springer
In the rapidly advancing age of Generative AI, Large Language Models (LLMs) such as
ChatGPT stand at the forefront of disrupting marketing practice and research. This paper …

Uniting the tribes: Using text for marketing insight

J Berger, A Humphreys, S Ludwig… - Journal of …, 2020 - journals.sagepub.com
Words are part of almost every marketplace interaction. Online reviews, customer service
calls, press releases, marketing communications, and other interactions create a wealth of …

[HTML][HTML] Algorithmic bias in machine learning-based marketing models

S Akter, YK Dwivedi, S Sajib, K Biswas… - Journal of Business …, 2022 - Elsevier
This article introduces algorithmic bias in machine learning (ML) based marketing models.
Although the dramatic growth of algorithmic decision making continues to gain momentum in …

How sensory language shapes influencer's impact

GL Cascio Rizzo, J Berger, M De Angelis… - Journal of Consumer …, 2023 - academic.oup.com
Influencer marketing has become big business. But while influencers have the potential to
spread marketing messages and drive purchase, some posts get lots of engagement and …

[HTML][HTML] Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges

YR Shrestha, V Krishna, G von Krogh - Journal of Business Research, 2021 - Elsevier
The current expansion of theory and research on artificial intelligence in management and
organization studies has revitalized the theory and research on decision-making in …

[HTML][HTML] More than a feeling: Accuracy and application of sentiment analysis

J Hartmann, M Heitmann, C Siebert… - International Journal of …, 2023 - Elsevier
Sentiment is fundamental to human communication. Countless marketing applications mine
opinions from social media communication, news articles, customer feedback, or corporate …