ABSTRACT Agricultural policy-based finance (APF) is a crucial component of China’s rural finance system. It implements national agricultural policies and channels funds to key rural areas and vulnerable sectors, which helps increase rural income. We match county branch credit data from the Agricultural Development Bank of China with county-level macroeconomic data and build a panel of about 1453 counties from 2009 to 2018. With this panel, we estimate how APF affects rural residents’ income and test whether government size moderates the effect in a nonlinear way. APF increases income by supporting agricultural product prices, moving labour into non-agricultural employment, improving agricultural productivity, and optimizing agricultural production structure. These effects are larger in counties with higher rural human capital, more advanced digital finance, and looser household registration rules. Government size helps at first. This positive moderation will gradually weaken as the size of the government continues to grow and eventually even reverse, forming an inverted U-shaped pattern. Notably, setting higher economic growth targets weakens this inverted U-shaped moderation. These findings help policymakers clarify APF support’s external validity boundary and effect mechanisms, strengthening its role in rural poverty reduction and common prosperity.

This paper investigates the degree of oil prices pass-through to import, producer, and consumer prices in Canada and the United States from 1980 to 2017 using a Structural Vector Auto-Regression (SVAR) model. The results indicate a positive long-run correlation between oil prices and aggregate price levels. The impulse response function reveals a persistent and incomplete pass-through for oil prices, i.e., 0.04 for Canada and 0.25 for the U.S. Greater pass-through exists in an economy with more oil import share. Consistent with the impulse response function, variance decomposition reveals that oil price shocks in the United States are the primary cause of the variation in import and producer prices. However, in Canada, oil price shocks explain the variation in producer and consumer prices.

Pricing is an essential element that significantly impacts the supply chain mechanisms. The primary objective of this study is to explore the transmission of producer-to-consumer prices in the Spanish fresh tomato industry. Employing the Threshold Vector Autoregressive model, and subsequently utilizing the Generalized Impulse Response Function, we investigated the nonlinear price adjustments that occur in response to positive and negative shocks affecting both tomato prices of consumers and producers. The findings show a clear pattern of distinct reactions between segments in response to shocks. Specifically, the speed and intensity of consumer price responses to producer price shocks appear to surpass those observed when producer prices respond to consumer price shocks. Furthermore, it is evident from the current research that the behavior of producers has evolved from earlier studies that utilized outdated information, suggesting a more competitive approach. The research identifies a new trend in producer behavior within the supply chain. By analyzing tomato price fluctuations, it advances current knowledge and provides essential market insights to support informed decision-making.

This paper examines how personalised pricing on digital platforms affects consumer behaviour. This article combines research related to online price discrimination and consumer decision-making with the theory of planned behaviour and attribution theory as the main analytical perspectives. It explains why consumers are more likely to have ideas such as unfair, targeted and out of control when they find different prices for the same product, which leads to privacy concerns and trust, ultimately reduces their willingness to buy, and is more likely to turn to other platforms or spread negative word of mouth. Literature and case studies show that similar goods online can have significant price differences across regions or access paths, and that many consumers have negative attitudes towards non-transparent personalised pricing. Meanwhile, personalised discounts and dynamic pricing are also likely to improve resource allocation efficiency, reduce search costs and provide more affordable options for price-sensitive consumers. Based on this 'efficiency-equity' conflict, this paper suggests that consumer acceptance depends on the legitimacy of the pricing rules, information transparency, and controllability. Therefore, the article provides actionable recommendations at four levels: market, industry, enterprise and consumer, including strengthening regulation of algorithmic pricing, improving data governance standards, internal pricing audits and ethical boundaries for enterprises, and comparison and privacy management practices for consumers. Overall, responsible and explainable personalised pricing is more likely to stimulate demand without undermining long-term trust.

Food additives are essential for food preservation and quality; however, consumers often perceive them as a potential health risk. The aim of this study was to investigate how educational background and information sources affect perceptions of food additive safety among female students, and to examine the relationship between additive use and product prices. A questionnaire survey was administered to 274 junior high school students, 145 high school students, 96 university freshmen who had not attended specialized lectures, and 137 university students who had attended such lectures. Additionally, 76 pairs of commercial food products were analyzed to compare the prices between those with and without food additives. More than 80% of the respondents expressed interest in food safety, and awareness of food additives was high across all groups, particularly for sweeteners, colorants, and preservatives. Students who had attended food safety lectures were significantly more likely to perceive additives as safe. The main sources of information differed by educational background: school education was the primary source among students who had attended lectures, the internet and social media were most common among those without specialized lectures, and parents and television were the predominant sources of information for junior high and high school students. Products without additives were, on average, 1.6 times more expensive than those with additives, and no price differences were observed across additive types. These findings suggest that specialized food safety education reduces excessive concerns about food additives, whereas "additive-free" labeling contributes to higher product prices by enhancing their perceived value.

The phrase "pink tax" refers to the practice of charging higher prices for products and services marketed to women than for similar products marketed to men. This phenomenon has drawn increasing attention as it reflects gender-based price differences in everyday consumption. This paper examines the impact of the pink tax on female consumers from a socioeconomic perspective. It focuses on three major industries: everyday consumer goods, beauty and personal care, and clothing. By comparing the prices of similar goods across genders and reviewing existing consumer reports and studies, the paper analyzes how the pink tax manifests across markets and influences women's consumption decisions. The analysis shows that female consumers often face higher long-term expenses, which can affect their budgeting behavior and purchasing choices. In addition, the pink tax may place a heavier burden on low-income women and reinforce existing gender inequalities. Overall, the paper argues that the pink tax is not only a market issue, but also a social concern, and greater awareness and policy attention are needed to reduce its negative effects on female consumers.

Traditional financial models often fail construction firms by ignoring industry-specific volatility. This study proposes an Explainable AI (XAI) framework to predict Return on Assets (ROA) and Debt-to-Equity (D/E) ratios using KOSPI and KOSDAQ data (2015–2024). It compares a baseline financial dataset (Dataset 1) with an industry-augmented version (Dataset 2) that incorporates the Producer Price Index (PPI) and labor wages. Using ANN, LSTM, and RF, the study found that the RF model achieved the highest predictive power (R2=0.7978). Notably, Dataset 2 improved accuracy significantly, reducing the Mean Absolute Error (MAE) for ROA by approximately 56%. SHAP analysis revealed that rising rebar and steel prices (PPI_RB) negatively impact both profitability and stability. In contrast, the concrete price index (PPI_CO) showed a positive influence, reflecting firms’ ability to manage costs or adjust prices. Crucially, material costs proved far more influential than labor costs. These findings indicate that supply-chain and raw-material-price indicators are salient predictors, suggesting that management may prioritize monitoring and mitigating supply-chain volatility, while causal validation remains beyond the scope of this study. Ultimately, by leveraging an XAI-based interpretation, this study provides a decision-making basis for formulating procurement and hedging strategies using raw material price indices, while also proposing an analytical framework that explains financial performance in the construction industry from a volatility-oriented perspective.

ABSTRACT The effectiveness of contract enforcement, an essential component of the institutional environment, may significantly impact the business choices made by an enterprise. Based on the Cobb-Douglas production function and the theory of incomplete contracts, this study optimized the Cobb-Douglas production model to analyze the influence of contract enforcement efficiency on an enterprise’s ability to set product prices, its profitability, and its ultimate competitive advantage in the market. This study empirically examined the theoretical hypotheses using a sample of A-share listed manufacturing companies from 2003 to 2021. The findings indicate that a rise in contract enforcement efficiency enhances an organization’s competitive advantage in the market. Various robustness tests validate this conclusion. The mediation mechanism analysis indicates that this influence is mainly attributed to the reduction of the enterprise’s financing costs and the results of heterogeneity test reveals that the effect of contract enforcement efficiency on competitive advantage is affected by factors such as the nature of the enterprise’s property rights, the degree of pollution of the enterprise, and the enterprise’s factor intensity. The policy significance lies in the need to attach importance to the role of contract enforcement efficiency in enhancing the competitive advantage of enterprises, as well as the coordinated development of the contract enforcement environment in different regions.

This study aims to analyze: (1) the effect of producer coffee prices, cocoa producer prices, coffee plantation area, export prices, and Indonesia’s coffee exports on Indonesian coffee production; and (2) the effect of consumer coffee prices, tea prices, granulated sugar prices, real GDP per capita, and imported coffee prices on Indonesian coffee consumption. The research model employs a multiple linear regression model using data from 2010–2023. The findings indicate that simultaneously, producer coffee prices, cocoa producer prices, coffee plantation area, export prices, and coffee exports significantly affect Indonesian coffee production. Individually, producer coffee prices and plantation area have a significant positive effect, while cocoa producer prices and export prices have a significant negative effect on coffee production. However, coffee exports have a negative but insignificant effect. Indonesian coffee production is responsive to changes in plantation area but not responsive to changes in producer coffee prices, cocoa prices, export prices, or export volume. Simultaneously, consumer coffee prices, tea prices, sugar prices, real GDP per capita, and import coffee prices significantly affect Indonesian coffee consumption. Individually, only real GDP per capita has a significant positive effect on coffee consumption. Consumer coffee prices and sugar prices have a negative but insignificant effect, while tea prices and import coffee prices have a positive but insignificant effect. Indonesian coffee consumption is responsive to changes in real GDP per capita but not responsive to price changes

This article evaluates the relationship between energy intensity (EI), investment in fixed capital (INVEST), employment (EMP), producer price index (PPI), and real output in Azerbaijan’s manufacturing industry over the period 2007–2024 within the ARDL-ECM framework. Since the ADF tests indicate that the variables have mixed orders of integration, I(0) and I(1), the Bounds test is applied to check for the presence of a long-run relationship, which is confirmed. In the ECM model, the negative and statistically significant error-correction coefficient shows that deviations from equilibrium are corrected rapidly. The results reveal that an increase in EI leads to a decline in real output, while efficiency improvements reduce EI and raise production volume. Growth in EMP positively affects output. INVEST in the manufacturing sector exerts a negative short-run effect due to “installation delays,” but a positive effect with a one-year lag. PPI shocks, especially with lags, have a negative impact. Inference is conducted using HAC/Newey-West robust standard errors. The LM, BPG, RESET, Jarque-Bera, and CUSUM/CUSUMSQ diagnostics confirm that the model’s functional form and stability are satisfactory.

This study evaluated the economic returns from livestock and poultry production in Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, focusing on buffalo, goat, sheep, and poultry enterprises. A comprehensive cost-return analysis revealed that buffalo milk production was more profitable in Andhra Pradesh than in Telangana due to higher yields and better prices. Goat rearing in Tamil Nadu generated greater returns than in Karnataka, mainly because of lower feed costs. Sheep farming in Karnataka recorded significantly higher profitability, supported by 35-40 per cent higher kid prices. Poultry farming showed consistent economic resilience across all states. Economic factors were most influential in Andhra Pradesh, Tamil Nadu, and Telangana, while animal health and management were critical in Karnataka. Major constraints included high disease incidence and inadequate product prices.

Advancements in concentrating solar power (CSP) plants are essential for the wider adoption of these technologies. Increasing the operating temperature of the plants is one of the most promising ways to achieve further cost reductions and performance improvements. In this context, progress in supporting components—such as molten salt tanks—is critical to enable these advancements. This study compares a novel molten salt tank based on a refractory concrete formulation with a conventional design made from 347H stainless steel over the period 2015–2025. The prices of refractory concrete and stainless steel were analyzed across the decade to estimate the costs of the corresponding TES tanks in 2015 and 2025. The results showed that, while the concrete-based tank was more expensive than the conventional tank in 2015, the situation reversed by 2025, with the conventional stainless steel solution becoming 11% more expensive than the refractory concrete alternative. Additionally, an analysis of the producer price indexes for both materials highlighted that concrete exhibited a more stable price trend compared to stainless steel, which was subject to greater intra- and inter-year fluctuations. Finally, a brief examination of the 347H stainless steel production chain identified key causes of price volatility, such as the high geographic concentration of its main raw material extraction sites worldwide.

Purpose This study aims to thoroughly examine consumer awareness of halal products by investigating the reservation price for halal products through a laboratory experiment in Indonesia. Design/methodology/approach The authors adopt the multiple price list method to elicit the reservation price and explore individual valuation to halal products using an incentivised economic experiment. The authors model the individual choice and estimate behavioural preferences (risk and ambiguity aversion), as well as estimating the determinants of the individual reservation price. Findings The participants exhibit a certain behavioural pattern in which non-halal products are valued higher than those of halal products based on price ratio (subjective valuation against product price). The additional benefits of the halal products do not appear to be perceived in a linear comparison with non-halal products. Research limitations/implications This study focuses on the demand side, using university members as participants under a within-design experiment, which may limit the scope of investigation. Future research could extend the analysis to the supply side to help understand the impact of halal certification through a randomised control trial design. Practical implications This raises an important issue of consumer trust in halal products, especially within Indonesian culture, where “being halal” should be officially recognised by the authorities. The government needs to understand its market to enhance the halal market. Originality/value This study investigates consumer’s reservation prices for halal products (both certified and self-claimed) compared to non-halal products using a laboratory economic experiment. The authors complement the existing literature – mostly focused on the supply side through survey methods – by examining the demand side of the halal industry.

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

In today's competitive digital landscape, social media marketing has become a powerful mechanism for shaping consumer perceptions and influencing purchase behavior. However, limited research has examined how social media marketing activities (SMMAs) drive consumers' willingness to pay premium prices for technology products, particularly in emerging markets. Grounded in the Stimulus-Organism-Response (S-O-R) framework, this study aims to clarify how five SMMA dimensions, including informativeness, interactivity, personalization, electronic word-of-mouth (eWOM), and trendiness, affect brand awareness, brand image, and brand trust, which subsequently shape consumer attitudes and willingness to pay premium prices for tech gadgets. A quantitative research design was adopted, and data were collected from 371 Vietnamese consumers through an online survey. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study tested the hypothesized relationships among SMMAs, brand-related outcomes, and consumer responses. The findings reveal that informativeness, personalization, and eWOM significantly enhance brand awareness, image, and trust, while interactivity positively influences awareness but has no significant impact on image or trust. Moreover, brand image and brand trust emerge as critical determinants of consumers' willingness to pay premium prices. The results advance theoretical understanding by refining the S-O-R framework and extending personalization theory, highlighting the contextual roles of interactivity and trendiness in shaping brand-related outcomes. Practically, the study provides valuable insights for digital marketers in the tech gadget industry, emphasizing the need for transparent information, personalized marketing, and the amplification of positive eWOM to strengthen brand trust and increase consumers' willingness to pay premium prices.

Captive finance subsidiaries create a channel for trade policy to affect consumer credit. Examining the impact of the Trump administration’s metal tariffs on captive automobile lenders, we find that consumers received higher interest rates from captive lenders after the tariffs relative to unaffected noncaptive lenders. Further, we document a disparate impact on low-income borrowers and in areas with less lending competition. Our results suggest that tariffs may impact not only the price of goods but also the financing terms of purchases. Thus, focusing solely on directly affected product prices may underestimate tariff pass-through significantly. (JEL F13, F14, G21, L22, L61, L62)

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

Abstract The Brazil nut ( Bertholletia excelsa H.B.K.) is one of the most valuable non-timber forest products in the Amazon, yet its production chain remains underexplored in terms of structure, efficiency, and territorial dynamics. This study aims to analyze the spatial distribution, productive performance, and socioeconomic drivers of the Brazil nut value chain in the state of Amazonas, Brazil, identifying critical bottlenecks and opportunities for sustainable development. To this end, official data from 2010 to 2023 were used to perform descriptive spatial analysis and log–log econometric modeling. Results show a high concentration of production in the microregions of Purus, Rio Negro/Solimões, and Jutaí/Solimões/Juruá, where traditional extractivism, community governance, and fluvial accessibility favor regular output. In contrast, regions such as Alto Rio Negro and Baixo Amazonas face infrastructural limitations and low organizational capacity. The econometric model indicates that a 10% increase in the number of extractivists raises total production by 15.62%, and a 10% increase in yield results in a 10.06% increase, highlighting the labor-dependence of the chain. Furthermore, average producer price positively affects output, while higher per capita income correlates negatively, suggesting that extractivism tends to be abandoned as other income sources emerge. These findings reveal a structurally vulnerable chain that lacks technological intensification and value aggregation. Public policies focused on infrastructure, cooperativism, technological inclusion, and socio-biodiversity valorization are essential to enhance the competitiveness and resilience of the Brazil nut sector in the Amazon.

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.

In recent years, the demand for clean agricultural products in Vietnam has increased, reflecting consumers’ growing awareness of health, quality of life, and environmental protection. However, the current consumption level remains modest and not commensurate with the market potential. This study aims to analyze factors influencing online purchase intention and consumers’ willingness to pay premium prices for clean agricultural products. The research data were collected from a direct survey of 246 households in Vinh Long province. The research hypotheses were developed based on the Theory of Planned Behavior (TPB) and tested using a Binary Logit Model. The results indicate that household characteristics, consumer attitudes, perceived security in online payments, and perceived convenience significantly affect both online purchase intention and willingness to pay premium prices. These findings enrich the theoretical understanding of consumer behavior in agricultural e-commerce and provide practical implications for policymakers and marketers to promote the consumption of clean agricultural products through online shopping channels in Vietnam.