In Vivino Veritas: An Investigation on Consumers’ Quality Perception and Wine Choice Determinants

Posted: 2 Jun 2022

See all articles by Enrico Mazzoli

Enrico Mazzoli

Università degli studi della Tuscia - Department of Economics, Engineering, Society and Business, University of Tuscia, Via del Paradiso 47, 01100 Viterbo, Italy

Luigi Palumbo

University of Tuscia; Bank of Italy - Economic Outlook and Monetary Policy Directorate

Date Written: May 19, 2022

Abstract

To wine amateurs, the choice of which wine to buy can be a daunting and stressful experience, especially when that is prompted by a last-minute invitation to a dinner party. In everyone’s mind, the ideal result would be to select a wine that pairs well with the food to be served, that all attendees appreciate and something we bought without spending a fortune. A less ideal outcome would be to discover that the party host is a wine guru, that s/he realised how little you have spent on the purchase, and that all attendees experience how bad your Albariño pairs with gigot d’agneau fumé. Luckily, these days, much of the drama above can be averted with technology supporting undecided (and unaware) wine consumers.

Vivino is one of the most known smartphone apps fit for that purpose. It provides customers and community members with information and consumer feedback on practically any wine on the market. Users can photo-scan a wine and quickly learn wine characteristics, origin, average price, grape varietals and how much peers have liked it—thus reducing information asymmetry.

Information asymmetry has been long debated in economics since the early contribution of Akerlof (1970) on adverse selection. Asymmetry of information happens when traders do not have access to the same complete and homogeneous information in a transaction. We often find the concept in market transactions and first time buying of experience goods. Like most other agri-food products, wines are experience goods, meaning consumers can only learn their quality, intrinsic property, and flavour after purchasing and tasting them. Therefore, consumers buying such goods for the first time face an information asymmetry as opposed to producers, who instead followed each step of the production process (Castriota et al., 2013). To reduce such asymmetry, consumers adopt a variety of coping strategies, including, among others, collection of information before the purchase through word-of-mouth (peers’ judgements), consultation of experts’ guides, and use of apps like Vivino. This shows that buyers gather several cues before making their final decision.

Several studies have tried to identify those factors behind consumers’ choices and untangle the effect each cue plays on the decision to buy (Hall & Lockshin, 2000; Kim et al., 2013; Reinstein & Snyder, 2005; Robertson et al., 2018). The perceived quality of a product is one of those — together with price, expert reviews and peers’ evaluations. In their research, Horowitz and Lockshin (2002) investigated the indicators of wine quality from the consumers’ point of view and concluded that a reasonable amount of the variance in wine evaluations can be explained by extrinsic factors - those that can be known to the consumer before buying the bottle of wine (e.g. price). Nevertheless, the discussion on perceived wine quality cannot be based only on extrinsic variables like price. Other intrinsic (i.e. grapes, acidity, colour, taste) and institutional variables (origin, reputation of winery, denomination, certification) do influence customers’ valuations. Wine products may see variables such as price and quality be connected by a two-way correlation, where quality levels determine prices or where prices influence quality perception (ibid.).

In this paper, we investigate consumers' cues contributing to wine quality perception. We develop a regression model to predict wine ratings based on intrinsic and extrinsic variables. The dataset comprises 16,000 observations and 136 variables. We set out a series of regressions where the dependent variable – the average quality rating of wines – is regressed on several independent explanatory variables. Our contribution to the literature is that we use quality rating as the dependent variable instead of the more often used price. We do so to identify those cues that correlate most strongly with the definition of quality – as perceived by customers.

Our analysis found that the perception of wine quality – measured through users’ ratings– appears to be strongly correlated to wine prices. In other words, a more costly wine, ceteris paribus, tends to be rated more favourably by consumers. We also tried to identify how other extrinsic and intrinsic wine variables affect quality perception on Vivino. We found that popularity – measured by the number of wine reviews received by a single wine - is positively correlated to wine quality reviews. A more popular wine tends to be graded higher on the five-star marking system of Vivino. At the same time, we analysed the effect that places of origin and wine designations (i.e. protected designation of origin and protected geographical designation) have on quality scores. We found out that wine origin may influence the final score but its effect differs widely depending on the wine region.

Keywords: information asymmetry, quality, wine selection, digital application

JEL Classification: D12, L15, L66, L86

Suggested Citation

Mazzoli, Enrico and Palumbo, Luigi, In Vivino Veritas: An Investigation on Consumers’ Quality Perception and Wine Choice Determinants (May 19, 2022). Available at SSRN: https://ssrn.com/abstract=4114012

Enrico Mazzoli (Contact Author)

Università degli studi della Tuscia - Department of Economics, Engineering, Society and Business, University of Tuscia, Via del Paradiso 47, 01100 Viterbo, Italy ( email )

Rettorato, Via S.M.in Gradi n.4
Viterbo, 01100
Italy

Luigi Palumbo

University of Tuscia ( email )

Rettorato, Via S.M.in Gradi n.4
Viterbo, 01100
Italy

Bank of Italy - Economic Outlook and Monetary Policy Directorate ( email )

Via Nazionale 91
Rome, 00184
Italy

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
360
PlumX Metrics