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The purpose of the study is to investigate micro determinants for dynamic wine pricing in Argentina. We test whether attributes and time affect the price rate of change. The rate of change is selected given the inflationary context of the country. The analysis provides valuable information for wine marketing decisions.

The modeling approach relies on panel data analysis for exploiting the data cross-section and time dimension. The contribution explores a massive price dataset at a weekly frequency. The dependent variable is the weekly price variation rate for product/wine and covariates are attributes, time and nominal variables. Given that endogeneity issues arose, the estimations rely on a two-stage least squares and instrumental variables with cluster-robust errors.

Estimations show that attributes, time and cost variables are statistically significant, with clear seasonal patterns and quality segmentation affecting pricing: wines made out of specific grapes such as Chenin, Merlot and Seedling or composing a broad category such as red wine, exhibit price undershooting (price rate of change below average). On the other hand, wines out of grapes such as Bonarda, Margaux, Mistela, Moscatel, Oporto, Tannat and Sauvignon Blanc show price overshooting (rate of change above average). In summary, wine made from determined grapes and specific wineries show divergent pricing.

Covariates such as alcohol content, label descriptor information, winery history, substitute competition and vintage, among others, have not been considered given that the research analyzes more than 750 wine products. Another limitation is that the work does not explore many time-series covariates, such as promotions and idiosyncratic shocks.

The contribution presents new information on wine pricing patterns affected by weeks, months and years, including the effect of the prolonged 2020 Argentine lockdown. It also analyzes estimations on pricing at the level of grape/blend and wineries previously unknown in this market. The information can influence inventory decisions on the side of the sellers and purchase decisions on the side of consumers.

The analysis includes fine but also low-cost wines that form part of the diet of low-income families in the country. The work detects a divergent pattern in pricing divided by the quality/price of the wine. It also presents information on price timing that may help consumers in the best moment to buy.

The contribution analyzes unprecedented information on weekly wine prices and presents evidence of pricing tactics from a point-of-sale perspective: It identifies different adjustment speeds related to product features and time effects.

This paper aims to find the best tools to influence the improvement of sustainability in food supply chains (FSCs) by conducting a systematic review of articles. The reader will learn how the different industry 4.0 tools (I4.0T) benefit the FSC and the limitations of each tool.

A review of 436 articles published during the period 2019 to 2022 referenced in the Scopus and Web of Science databases was performed. The review was limited to articles published in English and directly related to Industry 4.0, circular economy and sustainability in the food supply chain.

The results show different contributions of I4.0, with some being more influential than others in improving sustainability in FSCs; for example, Internet of Things and Blockchain have been shown to contribute more toward transparency, traceability, process optimization and waste reduction.

The paper's contribution consisted of ranking according to their importance and the I4.0T that affect sustainability in FSCs by classifying the aspects of each tool and the sustainability factors through a categorization by the Analysis Hierarchy Process.