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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.

This paper was aimed at investigating the impact of knowledge management (KM) procedures on enriching human resources in Water and Waste Water Company in East Azerbaijan, Iran.

The samples used in this study included the employees of Water and Waste Water Company in Tabriz, East Azerbaijan, Iran. A questionnaire was used for collecting data from the employees of the abovementioned company. Its reliability and validity were first examined and checked. Then, Smart partial least squares 2.0 was used for analyzing the structural model.

The results acknowledged the validity of the introduced model for enriching human resources. The findings indicated that five variables, namely, kind of knowledge, top managers, information technology, culture and organization of knowledge, have significant impact on enriching human resources.

It is undoubtable that research studies might have specific limitations which should be pointed out and addressed in future studies. The followings are the major limitations of the study: because the present study was carried out in Water and Wastewater Company in Tabriz, East Azerbaijan, hence, generalizing the findings of this study to other professional contexts and organizations should be made with caution. In fact, the present study need to be replicated in other context to find whether the same or different results are obtained. In other words, different cultural, contextual and professional conditions might result differently from the ones reported here. Inasmuch as the present study was a cross-sectional study and the data were collected via questionnaire, a longitudinal study with a longer observation and investigation might shed more light on the efficacy of KMS in organizations. The present study focused on a specific dependent variable (human resource empowerment) which was explained by different dimensions of an independent variable, i.e. KM. However, the impact and efficacy of KMS can be investigated on other organizational variables and parameters. In this study, due to certain logistic and real-life limitations such as the limited time of the staff members of the target organization, we had to use only one data-collection instrument. Nevertheless, future studies can use data triangulation so as to better capture professional contexts of the study. Furthermore, another limitation of the study is related to the individual variables of the employees which remained untouched. That is, whether employees’ personal, emotional and cognitive variables can modify the impact of KM on human resource empowerment was not investigated in the present study.

Organizational managers are recommended to provide the background for employees to share their experiences. Organizations should invest on designing and developing patterns and strategic perspectives in human resource empowerment as a key factor toward becoming knowledge-based organizations.

This paper is one of the few applied studies which acknowledged the relationship between knowledge management initiatives and empowering human resources. It addresses the gap between knowledge management and human resource empowerment.

This paper aims to present an evolutionary algorithm (EA) to accelerate the convergence for the radiative transfer equation (RTE) numerical solution using high-order and high-resolution schemes by the relaxation coefficients optimization.

The objective function minimizes the residual value difference between iterations in each control volume until its difference is lower than the convergence criterion. The EA approach is evaluated in two configurations, a two-dimensional cavity with scattering media and absorbing media.

Experimental results show the capacity to obtain the numerical solution for both cases on all interpolation schemes tested by the EA approach. The EA approach reduces CPU time for the RTE numerical solution using SUPERBEE, SWEBY and MUSCL schemes until 97% and 135% in scattering and absorbing media cases, respectively. The relaxation coefficients optimized every two numerical solution iterations achieve a significant reduction of the CPU time compared to the deferred correction procedure with fixed relaxation coefficients.

The proposed EA approach for the RTE numerical solution effectively reduces the CPU time compared to the DC procedure with fixed relaxation coefficients.

The purpose of this paper is to present the formulation of the first exhaustive price index for Argentinian (and other Latin American countries) visual artists using 5,069 works sold in auctions by 71 Argentinian artists during the years 1980-2014.

The authors estimated a regression of hedonic prices using the ordinary least squares method. When the regression was run and the results were analysed, the authors then estimated the annual price index of Argentinian artists’ work to then compare them with different financial and economic variables.

The average annual nominal arithmetic rate of return in dollars for Argentinian art during this period was 6.81 per cent, with a 29.11 per cent standard deviation. Argentinian art shows a low correlation with Argentinian and US companies’ shares and a slightly negative correlation with US bonds. This is the reason for artworks to be included in investors’ portfolios despite the relatively high volatility.

Valuating works of art in Argentina can be explained by a series of their attributes. The benefits of art as an investment should be contrasted with factors including illiquidity and high transaction costs that are inherent when investing in works of art.

Argentinian artists’ works have higher prices when, ceteris paribus, they are dated; they are auctioned in either Christie’s, Sotheby’s, Galería Arroyo, Roldan & Cia, Meeting Art, or Naon & Cia; they are oil or acrylic paintings; they are larger in size – although the price increase is decreasing when the size of the painting increases; and when the artist dies before their work is auctioned.

This work presents the first rigorous price index of Argentinian artists’ works. Additionally, and as far as the authors have been able to observe, the time-period in this article is the longest that has been used in studies on art as an investment in emerging markets.

Este trabajo presenta la elaboración del primer índice exhaustivo de precios de artistas plásticos de Argentina (y de cualquier otro país de Latino América) a partir de 5.069 ventas de obras de 71 artistas argentinos realizadas en subastas durante el período 1980-2014.

Se estimó una regresión de precios hedónica por el Método de Mínimos Cuadrados Ordinarios. Una vez corrida la regresión y analizados sus resultados, se procedió a estimar el índice anual de precios de obras de artistas argentinos, para posteriormente relacionarlos con diversas variables financieras y económicas.

El rendimiento promedio aritmético nominal anual en dólares del arte argentino durante ese período fue de 6,81% con una desviación estándar de 29,11%. El arte argentino exhibe una baja correlación con las acciones de empresas argentinas y de EEUU y ligeramente negativa con bonos de EEUU, lo cual le confiere atributos para ser incluido en las carteras de los inversionistas, a pesar de la elevada volatilidad.

Se consigue que la valoración de arte en Argentina puede ser explicada por una serie de atributos de las obras de arte. Los beneficios del arte como inversión deben ser evaluados con la iliquidez y los elevados costos de transacción, entre otros costos, inherentes a la inversión en obras de arte.

Las obras de artistas argentinos tienen precios más altos cuando, ceteris paribus: están fechadas, se subastan en Christie's, en Sotheby's o en Galería Arroyo, son ejecutadas en óleo o en acrílico, tienen un mayor área, aunque el aumento de precio es decreciente al aumentar el área, y cuando el artista ya había fallecido al momento de celebrase la subasta.

Este trabajo propone el primer índice riguroso de precios de obras de artistas de Argentina. Además, y hasta donde hemos podido comprobar, el período utilizado en este trabajo es el más largo que se haya empleado en estudios del arte como inversión en mercados emergentes.