Shifts in consumer behavior towards organic products: Theory-driven data analytics

Abstract

Consumer behavior is key in shifts towards organic products. A diversity of factors influences consumer preferences, driving planned, impulsive, and unplanned purchasing decisions. We study choices among organic and conventional wine using an extensive survey among Australian consumers (N=1003). We integrate five behavioral theories in the survey design, and use supervised and unsupervised machine learning algorithms for analysis. We quantify a gap between intention and behavior, and emphasize the importance of cognitive factors. Findings go beyond correlation to the causation of behavior when combining predictive prowess with explanatory power. Results reveal that affective factors and normative cues may prompt unplanned and spontaneous purchasing behavior, causing consumers to act against their beliefs.

The Consumption of Organic, Traditional, and/or European Eco-Label Products: Elements of Local Production and Sustainability

“…Compared to them, 36-40% of those who had a decent living appreciated the importance of organic vegetables and fruit. Such an attitude is conditioned by the media misrepresenting organic products as overpriced [65]. Sánchez-Bravo et al reported the same results regard-ing consumers' intention to pay a higher price for eco-friendly products [66].…”

Artificial Intelligence-Based Human–Computer Interaction Technology Applied in Consumer Behavior Analysis and Experiential Education

“…The research results showed that these commercial recognition systems have different processing results when processing distorted images and some suggestions are provided for developers in response to the existing problems ( Yang et al, 2021 ). Taghikhah et al (2021) studied the influence of consumer behavior on product purchase decisions. Supervised and unsupervised machine learning algorithms were used and behavioral theory was combined to quantify the intentions and behaviors of consumers, so as to realize the combination of emotional factors and normative cues to predict the buying behavior of consumers ( Taghikhah et al, 2021 ).…”

“… Taghikhah et al (2021) studied the influence of consumer behavior on product purchase decisions. Supervised and unsupervised machine learning algorithms were used and behavioral theory was combined to quantify the intentions and behaviors of consumers, so as to realize the combination of emotional factors and normative cues to predict the buying behavior of consumers ( Taghikhah et al, 2021 ). Lixăndroiu et al (2021) studied the influence of personality characteristics and attitudes toward the Internet on traditional electronic online shopping and augmented reality E-commerce.…”

Shaping a View on the Influence of Technologies on Sustainable Tourism

“…Furthermore, based on the most recent contributions from scholars more dedicated to the benefits of technology for overall business sustainability [33,57], we can expect future advancements on demonstrating transversal organisational gains, such as cost reduction and augmented decision-making capabilities provided by big data analytics. The potential benefits arising from co-creation opportunities, AI and machine learning are suggested [60,61], which may disrupt the competitive landscape for food industry and hospitality, per example, by enabling players with proactive flexibility for more robust marketing applications and supply chain competitive advantages, because of demand forecasts driven by big data and more interactive relationships with customers.…”