The psychological impact of social media marketing on consumer willingness to pay for tech gadgets: A study on brand perception and decision-making.

Purpose This paper broadens the range of macroeconomic factors influencing the real estate investment trusts (REITs) index of the Euro area (EU-REIT Index). In addition to traditional determinants, we incorporate new variables, including the business cycle, bond yields, producer price index (PPI), industrial production, private sector credit, hourly earnings in manufacturing, construction volumes and residential building permits. Design/methodology/approach Using quarterly data on the EU-REIT Index from Q3 2006 to Q4 2019, the study applies the Granger causality test within a vector error correction model framework, based on the autoregressive distributed lag model, to examine both the short- and long-run relationships between the EU-REIT Index and an extended set of macroeconomic drivers. Furthermore, the robustness of the forecasting model is evaluated using root mean squared error, mean absolute error, mean absolute percentage error and Theil's U2 statistic. Findings Macroeconomic factors such as the business cycle exhibit cyclical effects, while the PPI, industrial production, private sector credit and hourly earnings in manufacturing show a negative causal impact on the REIT index. In contrast, construction volumes and residential building permits demonstrate a positive causal relationship. Overall, the inclusion of these new variables significantly enhances the forecasting accuracy of REIT models. Practical implications This study provides a more comprehensive understanding of REIT performance by expanding the set of macroeconomic factors considered in REIT dynamics, improving forecasting and investment decision-making. Originality/value The analysis validates the relevance of these newly proposed macroeconomic variables for performance assessment and forecasting in the context of REITs, offering fresh insights into their market behavior.

Toward sustainable carbon utilization: Integrated LCA-TEA assessment of carbon dioxide-derived polymers.

How has the cost-of-living crisis impacted the transition to healthy diets from sustainable food systems?

In the context of high volatility in agricultural product prices, climatic and water-related risks, seasonal cash flow gaps, and a limited collateral base, the financial sustainability of Uzbekistan’s agricultural sector becomes a key prerequisite for ensuring food security and sustainable regional growth. The purpose of this article is to develop a risk-oriented model for improving the mechanism of financial sustainability of the agricultural sector based on the integration of three interrelated instruments: crediting, insurance, and subsidization.

This study examines the determinants of coffee export performance in Tanzania using secondary annual time series data collected from NBS spanning the years 1991 to 2024. Specifically, the analysis employed an Autoregressive Distributed Lag (ARDL) model to investigate the long run effects of four key variables: real producer price, relative export price to producer price, inflation, and the exchange rate on the volume of coffee exports. Furthermore, an ARIMA (1,1,3) model was utilized to forecast export trends up to the year 2030. The results indicated the existence of a long-run cointegration relationship between coffee export volume and the selected variables. The study findings shows that, the exchange rate had a positive and statistically significant impact on coffee exports, implying that depreciation of the Tanzanian shilling enhances competitiveness in international markets. Conversely, the relative export price to producer price exhibited a negative and significant effect, suggesting weak price transmission and limited benefits to farmers from export gains. Meanwhile, real producer price and inflation showed no significant long-run effects. The error correction term was correctly signed and highly significant, confirming a strong tendency toward long-run equilibrium after short-run deviations. The study concludes that exchange rate management and improving producer price incentives are critical to enhancing coffee export performance. Structural interventions to ensure better price transmission and institutional support for smallholder farmers are also essential. These findings support Tanzania’s policy ambitions under Vision 2025, FYDP III, ASDP II, and global targets such as SDGs 2, 8, and 9

This study empirically analyzes the effects of macroprudential and monetary policies on key macroeconomic variables, as well as the interactions between the two policies. To this end, a Panel Vector Autoregression model with exogenous variables (PVARX) was employed using data from OECD countries and the Eurozone-19. The PVARX model includes the macroprudential policy index, industrial production index, consumer price index, producer price index, call rate, and household credit as endogenous variables, while the U.S. federal funds rate and the New York Stock Exchange volatility index (VIX) are treated as exogenous variables. For the Eurozone-19, since a common macroprudential policy index is not available, a new aggregate index was constructed by applying GDP-weighted averages of member countries’ macroprudential policy indices. The estimation results indicate that both contractionary macroprudential and monetary policy shocks exert negative effects on major macroeconomic variables such as output and household credit. Macroprudential policy tends to tighten in response to positive shocks to output and prices. This suggests that during economic expansions, when credit growth risks intensify, regulatory tools such as the countercyclical capital buffer (CCyB) are reinforced, and when inflation rises, liquidity-absorbing measures such as the reserve requirement (RR) are strengthened. Monetary policy responds to inflationary shocks by raising policy rates, implying that it has been primarily oriented toward price stability. Moreover, interest rates rise in response to macroprudential policy shocks, indicating that monetary policy generally acts in coordination with macroprudential policy among the countries analyzed.

Many studies in the economic literature prove that real and nominal shocks affect real and nominal exchange rates in the short or long term. Therefore, it was considered worthwhile to investigate whether real and nominal shocks had affected the rise in exchange rates in Turkiye in recent years. To this end, three separate time series were created using monthly observations from 01/01/1994 (the earliest available date for the US dollar) to 01/06/2025, based on the consumer price index-based real exchange rate, the producer price index-based real exchange rate, and the nominal exchange rate. The first SVAR model included the consumer price index-based real exchange rate and the nominal exchange rate as endogenous variables, while the second SVAR model included the producer price index-based real exchange rate and the nominal exchange rate as endogenous variables. Both models were accepted after meeting the necessary assumptions and passing diagnostic tests. Based on the results of these models, it was concluded that real shocks have a permanent effect on real and nominal exchange rates in the long term, whereas nominal shocks do not significantly affect real and nominal exchange rates in the long term.

Cloudberry, Rubus chamaemorus L. (Rosaceae), is traditionally harvested as food in northern Scandinavia. It is rich in vitamins C, A and E, and antioxidants. This berry has gained much cultural, economic, nutritional, social and symbolic importance in Sweden during the past century. Cloudberries are an important part of culinary heritage. This qualitative diachronic study analyses historical data available in archives and published collections, fragmentary notes in literature and relevant modern data, using a historical ethnobiological approach. Cloudberry is the third most important wild berry species gathered for human consumption in Sweden. The berries were earlier preserved in wooden barrels during the long circumpolar winter; now they are usually frozen or made into jam and other processed products and sold throughout the country. Difficult access to growth areas, weather fluctuations, timing of harvest and lack of gatherers make harvesting challenging. Commercial harvesting has gone from being a sideline income source for the northern peasants to engaging imported seasonal workers mainly from Southeast Asia. This historical overview reveals that local berry picking is decreasing in recent decades. Fluctuations in local weather and lack of foragers influence the availability of cloudberry on the market. In 2025, there were neither enough workers nor berries, and the prices of cloudberry products have risen steeply. The cloudberry, which has enjoyed several decades of popularity both in haute cuisine and among ordinary consumers, will perhaps return to a local wild food gathered only for household needs.

BackgroundMany factors including the impact of colonization and subsequent intergenerational trauma contribute to health inequalities for Aboriginal and Torres Strait Islander people, respectfully referred to as Indigenous Australians. The unacceptable health gap is higher for the Indigenous Australians living in very remote communities. Food insecurity—a lack of regular access to safe, nutritious, and affordable food—is influenced by both housing and retail environments. Ensuring that houses have functional and adequately maintained kitchens and access to affordable, healthy food are significant policy challenges for Australian governments; yet, little is known about these environmental health drivers in very remote areas.ObjectiveThis study aims to benchmark environmental health food security risk factors impacting 19 very remote Indigenous communities in Western Australia. Specific objectives include using digital apps (1) to assess the appropriateness and suitability of kitchens in houses (internal environment), (2) to assess the affordability of food and sanitary goods (external environment) compared with the nearest town and capital city, and (3) to identify residents’ perceptions of appropriate kitchens.MethodsThe mixed methods eHealth study includes 3 approaches. The internal environment is assessed via an in-house audit of facilities used to prepare, store, and cook food to maintain Healthy Living Principle 4 using a customized digital app and a 5-minute face-to-face yarn with tenants (n=130). This provides lived experience perspectives to inform housing and store pricing policy recommendations. The external environment assesses retail practices and food item (n=97) and sanitation product (n=28) prices in remote community stores, extending Healthy Diets ASAP (Australian Standardized Affordability and Price) to compare the mean price per product, the whole diet, and sanitation goods with the nearest town and capital city. Descriptive statistics and frequencies will be reported for the audits, and thematic analysis of the interviews will be undertaken.ResultsTenant interviews and data collection for the in-house and retail audits across the 19 communities will be undertaken by mid-2026, and the analysis will be completed by the end of 2026. Findings will be collated and triangulated to provide benchmark data for environmental health determinants of food security in very remote Western Australian communities. Preliminary findings will be shared with each community to support their advocacy, policy, and practices for timely maintenance of homes, suitable kitchen design, and store retail practices.ConclusionsThis is the first study in Australia to explore the environmental health drivers of food insecurity in very remote Indigenous communities using digital technology from the perspectives of the tenant, in-house facilities, and in-store retail practices. The food security environmental health benchmarking will provide evidence for advocacy to promote culturally appropriate and practical solutions to improve living conditions and health of families in these areas.International Registered Report Identifier (IRRID)PRR1-10.2196/71697

Leveraging web-scraped data to examine alcohol pricing: an Australian feasibility study with retail data.

Climate change critically affects food production, availability, and stability, particularly in regions that rely on subsistence agriculture. This study examines the relationship between climate variables and food security indicators in Burundi from 1990 to 2022 using a co-integration model within an Error Correction Model framework. Results reveal that precipitation positively influences food production annually but negatively in the long run. Food consumption, producer prices, and rural populations also exhibited long-run negative effects. The findings highlight the adverse impact of climate change on agricultural yields, emphasizing the need for strategies to enhance productivity, resilience, and sustainability among smallholder farmers.

Prices of aquaculture and capture fisheries products in India: the highs and the lows

The electric power industry is a critically important component of the industrial economy, and its stable development and sustainable operation ensures the energy security of the country. The regional aspect of the electric power industry is characterized by close interaction with the end user, where the development of additional mechanisms for participants in interaction is a prerequisite for maintaining the operability of the energy supply system. The issue of implementing a new regulatory agreement instrument for the Astrakhan Region's electric grid complex, designed to eliminate the lack of funds and underfunding of the grid organization, is being considered. To date, the state has not formed an effective management structure and an established procedure for the application of such a tool as a regulatory agreement, the experience of applying such agreements in the Astrakhan region can serve as a basis for the introduction of similar tools in other subjects. The analysis of the main characteristics of the Astrakhan Region's electric power cluster has been carried out, as a result of which the territorial grid organization branch of ROSSETI Yug PJSC – Astrakhanenergo has been identified as the most preferable for applying the mechanism for concluding regulatory agreements. The classification of methods of state regulation of prices (tariffs) for products and services in the electric power industry is characterized. The current problems of activity in the conditions of a critical shortage of funds, including those caused by problems of tariff regulation, are described. Based on the data analysis, it is concluded that it is impossible to reduce the amount of justified debt recognized by the regulatory authority to the network organization through tariff solutions. In the context of the relevant issues, the mechanism of the regulatory agreement is considered as a specialized instrument of personal regulation, used exclusively to overcome the most serious problems and implement large-scale infrastructure projects. The algorithm for developing a draft regulatory agreement for the network organization of ROSSETI Yug PJSC is substantiated.

We assessed alcohol product availability, sales, and prices among privatized off-premises alcohol sales in 42 US states and quantified sales among lower-priced products. We used NielsenIQ weekly retail scanner data from 28 license states (where alcohol sales are privatized) and 14 control states (where alcohol sales are partially privatized and partially government controlled, e.g., for distilled spirits)-collectively representing privatized off-premises alcohol sales in 42 US states from November 11, 2018-November 4, 2023. We descriptively analyzed the latest year (November 2022-November 2023) of alcohol product availability (number of unique products), standard drink price, and standard drink sales, and compared it to estimates in the earliest year (November 2018-November 2019). We quantified the sales market share of products priced at or below $0.50, $0.75, and $1.00 per standard drink. Overall, product availability increased from 2018-2019 to 2022-2023 among all alcohol types, ranging from +7.4% (beer) to +67.0% (ready-to-drink beverages [RTDs]), while sales decreased for beer (-8.0%) and wine (-10.7%) and increased for spirits (+7.4% [license states only]) and RTDs (+68.6%). The average standard drink price paid remained <$2.00 through 2023. During 2022-2023, in license states, 57.4% of sales were ≤$1.00 per standard drink; across all states, 23.3% of beer sales (13.0% of beer products), 28.7% of wine sales (7.4% of wine products), and 18.4% of RTDs sales (24.0% of RTDs products) were ≤$1.00 per standard drink. Among 42 US states, a substantial portion of alcohol sales were among lower priced products.

BACKGROUND: Providing the least costly, safe, and highly effective pharmacotherapy to patients with rheumatoid arthritis remains an urgent issue. AIM: This work aimed to develop approaches for optimizing drug provision for patients with rheumatoid arthritis (using the city of Almaty as an example). METHODS: This work used the information resources of the Ministry of Health of the Republic of Kazakhstan; reports from the Almaty City Rheumatology Center, the State Register of Medicinal Products of the Republic of Kazakhstan, the Clinical Protocol for the Diagnosis and Treatment of Rheumatoid Arthritis No. 12 dated September 29, 2016; wholesale prices for medicinal products, antineoplastic agents, and immunomodulators (anatomical therapeutic chemical groups L01, L04) provided by the City Rheumatology Center; and statistical indicators accumulated based on data from the World Health Organization and the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. RESULTS: The highest disease prevalence (60%) was observed among working-age patients aged 35–55 years, whereas only 0.36% of the medicinal products used belonged to biologic agents. The cost ranking (ascending order) of adverse drug reaction therapy was as follows: adalimumab, etanercept, rituximab, tocilizumab, golimumab, and infliximab. With regard to additional cost expenditures, the leading agents (based on the lowest cost of the treatment course) were golimumab, rituximab, and infliximab. The lowest total treatment cost across all treatment stages (in ascending order) was identified for etanercept, adalimumab, and infliximab. CONCLUSION: Strengthening physician-led patient education regarding treatment strategies is necessary to improve adherence among patients with rheumatoid arthritis. To expand therapy options, the inclusion of etanercept in the guaranteed free medical care list must be considered. To reduce expenditures for medicinal provision, producing biologic agents in the Republic of Kazakhstan is required.

The aim of this study was to assess the efficiency of agricultural farms in Poland, taking into account their type of farming. The analysis covered commercial farms participating in the Polish FADN system. The research period encompassed the years 2019-2023. To achieve the research objective, indicator, comparative, and descriptive analysis methods were applied. The study focused on economic efficiency, understood as the ratio of achieved outputs to inputs incurred. Selected indicators of productivity, profitability, and return on investment were used to measure the economic efficiency of the examined farms. The analysis showed that during the study period, both the level of farm resources in Poland and the efficiency of agricultural activity underwent certain changes. In 2019-2022, an upward trend in farm efficiency was observed; however, in 2023, the situation deteriorated significantly, as evidenced by a marked decline in productivity, profitability, and return on investment. The decrease in efficiency in the last analyzed year resulted from a reduction in production volume and a sharp drop in farm income, caused, among other factors, by high production costs, low agricultural product prices, unfavorable weather conditions, and the adverse impact of the war in Ukraine on the Polish grain and fertilizer markets. The analysis of farm efficiency by production type revealed differences in efficiency depending on the production orientation. It was found that farms specializing in granivorous animals generally demonstrated the highest efficiency in the use of land, labor, and capital resources, while farms specializing in grazing animals exhibited the lowest efficiency.

The increasingly dire state of the environment worldwide has made sustainable consumption a major focus, placing green marketing in the forefront as an important corporate strategy. Similarly, the role that religiosity, especially in Muslim consumer settings, plays concerning purchase intention has gained considerable attention. This systematic literature review aggregates findings from 50 recent scholarly articles that examine interlinkages between green marketing strategies, religious values, and consumers' decision-making processes. The review revealed that although green marketing significantly leads to consumer behavioral change, perceived authenticity, transparency, and reduction of green washing often act as moderators that impede or enhance its performance. Besides, religiosity was proven to be one of the strong predictors of green purchase intention, and studies have emphasized its role in setting ethical consumption patterns among Muslim consumers. The review summarized that the Theory of Planned Behavior was the most used theoretical framework, and there is an increasing trend in bibliometric and systematic review approaches. The main challenges for green marketing strategies include consumer skepticism and high prices of green products, while digital transformation and social media were identified as key enablers for future green marketing strategies. The study offers an integrated framework for this multidisciplinary area and suggests some actionable insights for academia and practitioners.

Rubber prices experience significant and prolonged fluctuations, which impact farmer incomes and management decisions. Understanding historical patterns and price predictions is considered crucial for production planning, marketing, and farmer protection policies. This study aims to identify the characteristics of rubber price time series in Lahat Regency and develop a reliable forecasting model to support short- to medium-term decision-making. This study uses secondary data on monthly average producer prices for the period January 2019–December 2023. The analysis includes the Augmented Dickey–Fuller stationarity test to determine the need for transformation, differencing, and/or logarithmic transformation when necessary, identification of autocorrelation patterns using ACF/PACF, model estimation on the processed data, and evaluation of residual diagnostics (Ljung–Box, normality test) and forecasting accuracy metrics (RMSE, MAE, MAPE, Theil). The level data shows non-stationarity and becomes stationary after the first differencing; The model on log-transformed data had significant parameters and higher explanatory power than the model on de-differenced data, with RMSE and MAPE values ​​within a reasonable range. Forecast confidence intervals widened at longer time horizons, indicating increased projection uncertainty. Conclusion: Validated forecasts can inform farmers and policymakers to manage price risk and design market interventions.

In In today’s fast-paced e-commerce landscape, pricing strategies play a pivotal role in driving customer acquisition, maximizing revenue, and adapting to volatile market conditions. This paper introduces an AI-powered dynamic pricing framework that combines supervised machine learning with real-time market intelligence to recommend optimal product prices. The system integrates Random Forest and Artificial Neural Network (ANN) classifiers to predict consumer purchase behavior, achieving an average accuracy of 94.6% and an F1-score of 0.92. While Random Forest delivered a precision of 93.1%, ANN exhibited superior recall, underscoring their complementary classification capabilities. For precise price estimation, a multivariate linear regression model was implemented, attaining a high coefficient of determination (R² = 0.917) and a low Mean Absolute Error (MAE) of 2.87. The framework maintains prediction latency under 300 ms, ensuring suitability for real-time applications. Market data ingestion from platforms such as BigBasket was automated using Python-based web scraping, while an intuitive Gradio-powered GUI enables seamless user interaction. Designed to be scalable and modular, the system adapts effectively to evolving market dynamics and product-specific attributes. This research demonstrates how the synergy of machine learning, real-time analytics, and automation can drive intelligent pricing strategies that enhance competitiveness, customer targeting, and operational efficiency in modern e-commerce ecosystems.