Search results
1 – 2 of 2Gunjan Malhotra and Mahesh Ramalingam
This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence…
Abstract
Purpose
This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.
Design/methodology/approach
The study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.
Findings
The results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.
Originality/value
The study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.
Details
Keywords
Alberto Cavazza, Francesca Dal Mas, Maura Campra and Valerio Brescia
This study aims to investigate the use of Artificial Intelligence (AI) applied to vertical farms to evaluate whether disrupting technology supports sustainability and increases…
Abstract
Purpose
This study aims to investigate the use of Artificial Intelligence (AI) applied to vertical farms to evaluate whether disrupting technology supports sustainability and increases strategic business model choices in the agricultural sector. The study responds through empirical analysis to the gap on the subject of AI-driven business models present in the growing sector literature.
Design/methodology/approach
The paper analyzes the case of “ZERO”, a company linked to the strategy innovation ecosystem of the Ca’ Foscari University of Venice, Italy. The empirical data were collected through a semi-structured questionnaire, interviews and the analysis of public news on the business model available in the analyzed case study. The research is empirical and uses exploratory, descriptive analysis to interpret the findings. The article focuses on the evaluation of AI impact on the agricultural sector and its potential to create new business models.
Findings
The study identified how AI can support the decision-making process leading to an increase in productivity, efficiency, product quality and cost reduction. AI helps increase these parameters through a continuous learning process and local production, and the possible decrease in prices directed toward the goal of zero km food with fresh products. AI is a winning technology to support the key elements of the vertical farm business model. However, it must be coupled with other devices, such as robots, sensors and drones, to collect enough data to enable continuous learning and improvement.
Research limitations/implications
The research supports new research trends in AI applied to agriculture. The major implication is the construction of ecosystems between farms, technology providers, policymakers, universities, research centers and local consumer communities.
Practical implications
The ZERO case study underlines the potential of AI as a destructive technology that, especially in vertical farms, eliminates external conditions by increasing productivity, reducing costs and responding to production needs with adequate consumption of raw materials, boosting both environmental and social sustainability.
Originality/value
The study is original, as the current literature presents few empirical case studies on AI-supporting business models in agriculture. The study also favors valuable strategic implications for the policies to be adopted in favor of new business models in agriculture.
Details