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Olive oil (Olea europaea L.) is widespread due to its bioactive composition, sensorial characteristics, health benefits, and protection against certain diseases. Most of papers reported so far aimed to highlight its content as well as the quality of this edible oil in many different countries. In the present work, we targeted to review the sets of factors that could influence olive oil quality (whether it is virgin olive oils, or extra-virgin olive oils produced in different areas of origin, from several genetic backgrounds, plus the olives and olive oil processing from the fruits harvesting to olive oil bottling and storage, i.e., from farmers to consumers). In addition to all the internal and external variables, the last sub-paragraph was devoted to cooking effects. Notably, olive oil quality differed depending on many factors, thus, to obtain excellent quality, producers should be alerted to the attributes of their orchards (location; latitude and altitude, pedoclimate conditions) to adapt to the appropriate growing practices, like irrigation, fertilization, and pruning. The harvest time/ripening degree, which is related to the cultivated variety and the origin areas climate, as well as the extraction methods, bottling and storage conditions (container’s type and storage time) were also considered.

A kinetic model of binary interactions is developed to describe an exchange market consisting of two groups (A and B) of manufacturing enterprises and two types of production factors (capital and labor). The relationship between production factors and output satisfies the Cobb-Douglas production function. The objective of the manufacturing enterprise is to obtain maximum profits. In the multi-agent market, manufacturing enterprises exchange surplus production factors for insufficient production factors. We assume that manufacturing enterprises in group A put all of the production factors into the market, while the manufacturing enterprises in group B have the priority of selecting a suitable percentage of production factors for exchange. A system of linear kinetic equations is developed for two groups of manufacturing enterprises to characterize the evolution of the quantity of exchanged production factors. The effect of various strategies on the price of production factors and the profit of manufacturing enterprises is explored. The findings reveal that the trading strategy of group B significantly impacts the price of production factors and effectively improves the profit under certain conditions. Furthermore, a system of Boltzmann equations for the probability distribution of production factors is presented to describe the price issues. Simulation experiments illustrate how the trading strategy and the elasticity coefficient of output influence the final price of production factors.

Data is the primary factor of production in the digital economy, playing a role in promoting the deep integration of the digital economy and the real economy and smoothing the national economic cycle. After entering the circulation system of the real economy, data is rapidly integrated into production, circulation, consumption, distribution, and other links. It optimizes resource allocation, unblocks circulation channels, promotes accurate matching of supply and demand, stimulates emerging demand, and forms a virtuous circle of digital technology application, traditional physical enterprise transformation, and technological innovation. Integrated development is an important feature of the digital economy. Data promotes the integration of factors of production, products, enterprises, industries, and markets, which fosters a circular system with deep integration of the digital economy and the real economy. To promote the deep integration of the digital economy and the real economy, the government and business entities should take measures to improve the circular efficiency of the digital economy and the real economy. These measures include attaching importance to the role of data-driven development, improving data capacity, data development, and utilization in enterprises, exploring diverse circulation models of enterprise data, and creating typical application scenarios and industrial data spaces.

With rapid economic development and the growing global demand for water resources, the relationship between water demand and economic growth has become a critical international concern. This study investigates the role of water resources in China’s economic growth by extending the Cobb–Douglas production function to include investment, labor, energy, land, and water resources. Using national and regional data from 1949 to 2023, we quantify the spatiotemporal dynamics of factor contributions across primary, secondary, and tertiary industries. Results show that investment remains the dominant growth driver, with rising contributions from energy and land, while labor is increasingly substituted. Water resources exhibit marked industrial and regional heterogeneity: since 2013, water constraints have intensified in the primary sector of the Yellow River basin and Northeast China, and in the secondary sector of the inland northwest and Yellow River provinces. Considering national food security imperatives and given the complementary nature of water–land resources and the fixed nature of land, we propose strategic water network planning based on land productivity patterns to optimize resource coordination and drive high-quality economic development.

ABSTRACT In contrast to other countries, China's agricultural production faces the challenges of aging and feminization, which have a tremendous impact on food security. The purpose of this research was to reveal the correlations between aging and feminization and agricultural production factor input and its heterogeneity. This was evaluated using the ordinary least squares (OLS) model. The research found that the aging of farming did not correlate with the input of land factor and employment input. However, the feminization of farming significantly correlated with the input of land factor and employment input. In particular, an increase in the feminization of farming by one standard deviation reduced the land factor input by 18.9% and employment input by 31.3%. Second, agricultural aging and feminization had a positive and significant effect on agricultural machinery input but a negative and significant effect on material input. The instrumental variable method test results were consistent with those of the main regression. Third, heterogeneity analysis showed that the correlations between aging and feminization and the input of land, employment, agricultural machinery, and materials were significantly different with different educational levels of house heads and the proportion of agricultural income. Therefore, this study provides a reference for adjusting the rural labor structure and accumulating advanced rural production factors.

Introduction: China’s public welfare forest compensation policy is a pivotal environmental governance tool, promoting ecological conservation and advancing the practice of Payments for Environmental Services (PES). While prior studies have primarily focused on short-term ecological or income outcomes, there remains a lack of research on the policy’s long-term influence on rural households’ production factor allocation and livelihood strategies across forestry, agriculture, and non-agricultural sectors.Methods: This study employs panel data from 12,810 farming households in 18 counties across 9 provinces, spanning the years 2003 and 2007–2019. A differences-in-differences (DID) model is applied to evaluate the impact of the compensation policy on rural production behaviors, including inputs in forestry, planting, animal husbandry, and labor allocation.Results: The analysis reveals that the policy significantly reduces input use in forestry, especially among more actively participating households. It moderately increases non-agricultural labor supply—mainly through labor out-migration—but shows no significant impact on planting or animal husbandry. Although the policy supports under-forest economic activities, it fails to fully compensate for declines in inputs to bamboo, economic, and timber forests. Policy effects vary significantly across different household types, shaped by resource endowments and regional economic contexts.Discussion: These findings provide robust, long-term empirical evidence on the production-side effects of ecological compensation. The study highlights the importance of designing more nuanced PES policies that account for household heterogeneity and regional disparities, aiming for greater equity and effectiveness in implementation.

Access to complementary resources through strategic equity alliance networks is an important activity for both smaller and larger firms. In the literature, there is an intensive debate on the impact of alliance resources for smaller firms. We submit that the effect of alliance resources on the smaller firm financial performance depends on the attributes of these resources. Specifically, we argue that the attributes of partner organizational capital are negatively related and the attributes of partner production factor resources are positively related to the smaller firm financial performance. We test our theoretical framework by applying a longitudinal analysis to a dataset of 1730 firm-year observations of strategic equity alliances in the software industry in 25 countries over an 11-year period. We find support for our hypotheses, highlighting the critical importance of resource attributes for smaller firms in strategic equity alliance networks.

Technological innovation has become an essential element to increase companies’ productivity. Moreover, this impact of technological innovations on productivity differs from one economy to another. This research work aimed to detect the impact of technological innovations on Moroccan technical progress measured by the global productivity of production factors. To achieve this goal, this study used a vector error correction model (VECM) to estimate the function of the aggregate productivity of the short-term and long-term factors of production. The results of the estimates made on-time data covering the period 1998 to 2018 and showed that the global productivity of production factors is explained by the development of human capital and the realisation of foreign direct investments. The adoption of technological innovations and the importation of information and communication technologies have a predominantly low impact on this productivity.

The coronavirus triggered a record fall of GDP in Croatia, 8.1% in 2020, one of the largest declines in the EU. The large macroeconomic shock stemming from the pandemic has affected both supply and demand. On the one hand, government measures have imposed unprecedented supply-side restrictions. On the other hand, growing uncertainty affected domestic and foreign demand. Croatia was particularly affected by a plunge in international tourism demand. Such a major macroeconomic shock poses a challenge for estimating potential GDP, which is difficult to estimate even in stable economic conditions. When estimating potential GDP in the context of the corona crisis, the main issue is the breakdown of the shock into a permanent and a temporary part (supply and demand shock). In this paper, we try to give the most logical breakdown of Croatian data and describe possible methodological approaches to the estimation of potential GDP during the pandemic.

We establish that cryptocurrency returns are driven and can be predicted by factors that are specific to cryptocurrency markets. Cryptocurrency returns are exposed to cryptocurrency network factors but not cryptocurrency production factors. We construct the network factors to capture the user adoption of cryptocurrencies and the production factors to proxy for the costs of cryptocurrency production. Moreover, there is a strong time-series momentum effect, and proxies for investor attention strongly forecast future cryptocurrency returns.