AIMC Topic: Consumer Behavior

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Decompartmentalisation as a simple color manipulation of plant-based marbling meat alternatives.

Biomaterials Sep 3, 2021
Recent efforts for cell-based meat cuts focus on engineering edible scaffolds, with visual cues which are key to enhancing consumer acceptance, receiving less attention Here, we employed artificial intelligence (AI)-based screening of potential plant...
Artificial Intelligence Animals Swine Humans Meat Consumer Behavior Tissue Engineering Chickens Color Cattle
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Gaze and Event Tracking for Evaluation of Recommendation-Driven Purchase.

Sensors (Basel, Switzerland) Feb 16, 2021
Recommendation systems play an important role in e-commerce turnover by presenting personalized recommendations. Due to the vast amount of marketing content online, users are less susceptible to these suggestions. In addition to the accuracy of a rec...
Neural Networks, Computer Software Reproducibility of Results Machine Learning Consumer Behavior
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Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Previous research has studied medical professionals' perception of artificial intelligence (AI). However, there has been a limited understanding of how healthcare consumers perceive and use AI-powered technologies such as mobile health apps. We colle...
Sleep Consumer Behavior Motivation Exercise User-Computer Interface Health Promotion Telemedicine Mobile Applications Mental Health Feedback Communication Humans Artificial Intelligence
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Insights into mobile health application market via a content analysis of marketplace data with machine learning.

PloS one Jan 6, 2021
BACKGROUND: Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come.
Machine Learning Feedback Mobile Applications Marketing Consumer Behavior Knowledge Social Networking Privacy Telemedicine
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SE-stacking: Improving user purchase behavior prediction by information fusion and ensemble learning.

PloS one Nov 25, 2020
Online shopping behavior has the characteristics of rich granularity dimension and data sparsity and presents a challenging task in e-commerce. Previous studies on user behavior prediction did not seriously discuss feature selection and ensemble desi...
Biobehavioral Sciences Machine Learning Consumer Behavior Humans
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State-Transition Modeling of Human-Robot Interaction for Easy Crowdsourced Robot Control.

Sensors (Basel, Switzerland) Nov 15, 2020
Robotic salespeople are often ignored by people due to their weak social presence, and thus have difficulty facilitating sales autonomously. However, for robots that are remotely controlled by humans, there is a need for experienced and trained opera...
Humans User-Computer Interface Robotics Commerce Crowdsourcing Consumer Behavior
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Robots at work: People prefer-and forgive-service robots with perceived feelings.

The Journal of applied psychology Oct 8, 2020
Organizations are increasingly relying on service robots to improve efficiency, but these robots often make mistakes, which can aggravate customers and negatively affect organizations. How can organizations mitigate the frontline impact of these robo...
Robotics Consumer Behavior Humans Emotions
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Using Behavioral Analytics to Predict Customer Invoice Payment.

Big data Jan 23, 2020
Experiences from various industries show that companies may have problems collecting customer invoice payments. Studies report that almost half of the small- and medium-sized enterprise and business-to-business invoices in the United States and Unite...
Biobehavioral Sciences Reimbursement Mechanisms Accounts Payable and Receivable Machine Learning Models, Statistical Consumer Behavior Humans
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An Interactive Model of Target and Context for Aspect-Level Sentiment Classification.

Computational intelligence and neuroscience Dec 19, 2019
Aspect-level sentiment classification aims to identify the sentiment polarity of a review expressed toward a target. In recent years, neural network-based methods have achieved success in aspect-level sentiment classification, and these methods fall ...
Humans Neural Networks, Computer Psycholinguistics Restaurants Emotions Semantics Data Mining Consumer Behavior Machine Learning Computers
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Aroma perceptual interactions of benzaldehyde, furfural, and vanillin and their effects on the descriptor intensities of Huangjiu.

Food research international (Ottawa, Ont.) Nov 21, 2019
Aldehydes are important in the aroma of Huangjiu and contribute the almond and sweet aromas to Huangjiu. The perceptual interactions of 3 important aldehyde compounds were investigated using S-curves. Three volatiles, benzaldehyde, furfural, and vani...
Benzaldehydes Humans Male Furaldehyde Female Food Analysis Smell Wine Taste Gas Chromatography-Mass Spectrometry Young Adult Consumer Behavior Odorants Adult Volatile Organic Compounds
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