Consumer perception and willingness to pay for precision viticulture wines: An experimental auction approach

• Limited consumer awareness of Precision Viticulture (PV) as a major innovation. • Approximately 87 % of consumers willing to exchange conventional wine for PV wine. • Average willingness to pay (WTP) for the PV attribute is €2.41. The wine industry increasingly embraces technological innovations to enhance sustainability and production efficiency. Among these, precision viticulture (PV) has emerged as a promising approach, integrating advanced monitoring and data analysis to optimize vineyard management. As consumers place growing importance on environmental responsibility, understanding their perception and willingness to pay (WTP) for PV wines is essential for wine producers aiming to align their practices with evolving market trends. This study empirically investigates consumer acceptance and WTP for wines produced using PV technology. An incentivized experimental auction, leveraging the Becker-DeGroot-Marschak (BDM) mechanism with an endow-upgrade design, was employed to collect data from 160 participants between July 2023 and January 2024. Findings indicate a high willingness to exchange, with approximately 87% of respondents accepting a PV-produced white wine (Falanghina) over its conventional counterpart. For those who accepted, the average WTP for the PV attribute was €2.41. To explore the influencing factors, a logistic regression model assessed the decision to accept the PV wine, while an Ordinary Least Squares (OLS) regression identified the determinants of the stated WTP for the PV attribute. Logistic regression analysis revealed that gender and education significantly influenced the likelihood of accepting PV wines. Conversely, OLS analysis indicated that household size negatively affected WTP, whereas individuals with higher health consciousness were more inclined to pay a premium for PV wines. These results suggest that while consumers acknowledge PV’s efficiency and sustainability benefits, their WTP is also shaped by socio-demographic factors and personal health attitudes. Therefore, effective communication strategies highlighting the specific benefits of PV are crucial for enhancing consumer acceptance and WTP. This study contributes to the literature by providing novel empirical insights into how consumers perceive and value the complex intersection of tradition and innovation within the contemporary wine industry.

Authors

Institutions

Publication Details

Journal
Sustainable Futures
Published
2026-02-14
DOI
https://doi.org/10.1016/j.sftr.2026.101744
Primary Topic
Wine Industry and Tourism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Consumer perception and willingness to pay for precision viticulture wines: An experimental auction approach

Giuseppe Marotta, Anna Uliano, Concetta Nazzaro, Marcello Stanco
Sustainable Futures
Wine Industry and Tourism
article

Consumer perception and willingness to pay for precision viticulture wines: An experimental auction approach

Giuseppe Marotta, Anna Uliano, Concetta Nazzaro, Marcello Stanco
article en

Abstract

• Limited consumer awareness of Precision Viticulture (PV) as a major innovation. • Approximately 87 % of consumers willing to exchange conventional wine for PV wine. • Average willingness to pay (WTP) for the PV attribute is €2.41. The wine industry increasingly embraces technological innovations to enhance sustainability and production efficiency. Among these, precision viticulture (PV) has emerged as a promising approach, integrating advanced monitoring and data analysis to optimize vineyard management. As consumers place growing importance on environmental responsibility, understanding their perception and willingness to pay (WTP) for PV wines is essential for wine producers aiming to align their practices with evolving market trends. This study empirically investigates consumer acceptance and WTP for wines produced using PV technology. An incentivized experimental auction, leveraging the Becker-DeGroot-Marschak (BDM) mechanism with an endow-upgrade design, was employed to collect data from 160 participants between July 2023 and January 2024. Findings indicate a high willingness to exchange, with approximately 87% of respondents accepting a PV-produced white wine (Falanghina) over its conventional counterpart. For those who accepted, the average WTP for the PV attribute was €2.41. To explore the influencing factors, a logistic regression model assessed the decision to accept the PV wine, while an Ordinary Least Squares (OLS) regression identified the determinants of the stated WTP for the PV attribute. Logistic regression analysis revealed that gender and education significantly influenced the likelihood of accepting PV wines. Conversely, OLS analysis indicated that household size negatively affected WTP, whereas individuals with higher health consciousness were more inclined to pay a premium for PV wines. These results suggest that while consumers acknowledge PV’s efficiency and sustainability benefits, their WTP is also shaped by socio-demographic factors and personal health attitudes. Therefore, effective communication strategies highlighting the specific benefits of PV are crucial for enhancing consumer acceptance and WTP. This study contributes to the literature by providing novel empirical insights into how consumers perceive and value the complex intersection of tradition and innovation within the contemporary wine industry.

Sustainable FuturesVol. 11
University of Sannio (IT)
Openalex Percentile: Top 57%
Wine Industry and Tourism
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.