Price Increases Research Articles

FT-NIR combined with machine learning was used to rapidly detect the adulteration of pericarpium citri reticulatae (chenpi) and predict the adulteration concentration

Pericarpium citri reticulatae (PCR) has been used as a food and spice for many years and is known for its rich nutritional content and unique aroma. However, price increases are often accompanied by adulteration. In this study, two kinds of adulterants (Orange peel-OP and Mandarin Rind-MR) were identified by chromaticity analysis, FT-NIR and machine learning algorithm, and the doping concentration was predicted quantitatively. The results show that colorimetric analysis cannot completely differentiate between PCR and adulterants. Using spectral preprocessing combined with machine learning algorithms, PCR and two adulterants were successfully distinguished, with classification accuracy reaching 99.30 % and 98.64 % respectively. After selecting characteristic wavelengths, the R2P of the adulterated quantitative model is greater than 0.99. Generally, this study proposes to use FT-NIR to study the adulteration of PCR for the first time, which fills the technical gap in the adulteration research of PCR, and provides an important method to solve the increasingly serious adulteration problem of PCR.

A Conceptual Framework for Optimizing Performance in Sustainable Supply Chain Management and Digital Transformation towards Industry 5.0

The economic growth of developed or emerging countries through globalization has prompted them to increase their supply chain performance. A large number of concepts, tools, and methodologies have been proposed in support of this performance improvement. They are mainly based on the use of classical optimization or enterprise modeling methods. However, environmental and social issues, not to mention digital transformation, are often ignored or not sufficiently integrated. Indeed, the world geopolitical situation, the increase in oil prices, and the commitment to protect our earth require the integration of sustainability aspects and Industry 4.0 concepts like digital twin and artificial intelligence in transforming the supply chain. This paper focuses on defining a conceptual framework to support sustainable supply chain management and digital transformation. It aims to exploit the sustainability and digital maturity of companies to transform their supply chains and enhance their performance to meet the challenges of Industry 5.0. Several practices related to sustainability, as well as two use cases on optimization and digital twin, are presented to illustrate this framework. Finally, based on the previous practices and use cases, an adapted framework for the supply chain manager to support the transition from Industry 4.0 to Industry 5.0 has been developed, as well as a performance dashboard.

Analyzing the Impact of Government Subsidies on Household Welfare during Economic Shocks: A Case Study of Iran

The study evaluates the effectiveness of Iranian government subsidies for households by comparing the welfare impact of food price shocks with the subsidy payments they receive. This helps us assess the government's efforts to reduce poverty in Iran. The household cost data in 2020 was used to calculate compensated price elasticities using the Quadratic Almost Ideal Demand System (QAIDS). Results showed negative and less than one own-price elasticities for all food items, with a sensitivity to changes in income greater than one for demand of cereals, cooking oil, and fruits. Then, compensated variations (CV) welfare index was used to evaluate the effectiveness of government support payments in reducing household vulnerability due to food price increases. The results showed that the CV fluctuates between 8.05-80.46 $ under different scenarios. In other words, consumers are in a worse situation in terms of welfare and their expenditure increases. The vulnerability index of low-income households, after applying different food price scenarios, is in the range of 1.46-14.67%, which is reduced to 1.35-14.53% by implementing the cash-targeted subsidy policy. In other words, the effectiveness of the government's subsidy policy of $19 per person could reduce the vulnerability of these households by only 0.14%.

Will future copper resources and supply be adequate to meet the net zero emission goal?

The fact that in recent times mineral exploration has been disappointing and that transition to clean energy to achieve net zero emission by 2050 will place extraordinary pressure on copper demand, are beyond dispute. The critical question is to what extent will copper supply be capable of satisfying growing demand in a net zero future. Reality is that global copper resources have been growing significantly and steadily for decades despite increasing mine production. Besides, with dwindling exploration discoveries, this increase is primarily attributable to expansion of the resources of existing deposits through a combination of better progressive delineation and re-assessment of classification of resources in response to economic and technological changes, the so-called Australasian Joint Ore Reserves Committee (JORC) ‘modifying factors’. Analysis of MinEx Consulting's global mineral deposit database indicates that just the resources of deposits discovered since 2010 have been growing at estimated Compound Annual Growth Rates (CAGRs) in the range 7.5% to 15.5%, but greater additional tonnage is associated with deposits discovered before 2010. The result is that tens of millions of tonnes of copper are added to the inventory each year, notwithstanding increasing production and mounting Environmental, Social and Governance (ESG) pressure sterilising some deposits. In essence, copper supply shortages are unlikely to result from depletion of copper resources but rather from possible inadequacy of mining and processing capacity. Geopolitical supply risk is also low compared to some other critical metals (e.g., Co and Ni) on account of the large number and geographical dispersion of copper deposits. Increases in price due to a perception of impending scarcity will ensure that future capacity will, at a minimum, continue to grow along its historical 3% CAGR. In addition, it will create strong incentives for above-trend capacity utilisation and improvement in recycling collection and recovery. This will be followed by acceleration of expansion of capacity at many existing mines, and development of deposits at the advanced feasibility stage, releasing copper to market at lower capital cost and on shorter timeframes than exploring for and developing new mines. Estimates of possible levels of above-trend increments in capacity for the various components of the current copper endowment show that, while shortages may occur, they will not be as serious as currently generally expected. This does not mean that net zero emission may not be delayed beyond 2050, but it is more likely that it may be delayed by a range of other constrains and impediments unrelated to availability of copper, and that such delays may give copper supply breathing time.

Assessing the substitutability of mobile and fixed internet: The impact of 5G services on consumer valuation and price elasticity

In this study, we explore the dynamics of consumer choices in the Polish telecommunications market, focusing on preferences and valuations for home fixed, home mobile, and purely mobile Internet connections. Key attributes such as speed, latency, data limits, and cost are examined. Central to our research is the investigation of how the integration of 5G technology might influence demand elasticity. Using a detailed discrete choice experiment, we apply a mixed logit model with random parameters to analyze stated choice data, enabling us to unravel the complexities of demand elasticity, especially in terms of own and cross-price elasticities. This approach facilitates an assessment of the degree of substitutability between fixed and mobile Internet services.Our findings indicate a moderate substitution effect between fixed and mobile Internet services. Results from a Small but Significant and Non-transitory Increase in Price (SSNIP) test suggest that these markets should continue to be regulated separately, mirroring the distinct regulation observed in fixed and mobile telephony. Furthermore, simulations provide insights into potential future market shifts with the advent of 5G services. This paper contributes significantly to the discourse on fixed-mobile Internet substitution and offers vital insights for defining markets in antitrust discussions, competitive agreements, and potential mergers within the telecom sector.

From code to coin: Unravelling the practical business impact of algorithmic pricing

This paper examines the impact of algorithmic pricing on company value and presents the results of 31 expert interviews in various industries. The focus is on nine hypotheses, including the efficiency of automation, segmentation and value-based pricing, efficient resource allocation, perception of fairness, price transparency and uncertainty, the use of personal data and price competition. The surveys show that algorithmic pricing has considerable potential for efficiency gains through automation, particularly in terms of revenue growth. The potential for cost savings, however, varies from sector to sector. Segmentation and value-based pricing are proving to be feasible, but their implementation requires clear justification and economic rationale. Efficient resource allocation through dynamic pricing shows potential, especially in industry-specific scenarios. The perception of unfairness can have a negative impact, however, and personalised pricing risks alienating customers and reducing business value. Price transparency and uncertainty have a mixed effect, as customers often place more value on the transparency of alternative offers than on the company’s pricing process. The use of personal data poses a low risk to company value if it is transparent and mutually beneficial. The potential intensification of competition through algorithmic pricing depends on the market structure and the company’s objectives; however, algorithmic pricing can be used as an instrument to reduce price competition and increase company value. Overall, the results make it clear that the integration of algorithmic pricing strategies must be carefully and ethically designed in order to sustainably increase company value.

The role of speculation on housing price disparities

This paper explores the impact of speculation on disparities in home purchase prices within neighborhoods. Using administrative data on residential real estate transactions in Singapore's private housing market, our analysis reveals that housing unit prices increase over time within a neighborhood in the presence of speculators. However, this pattern remains stable after the implementation of macroprudential policies aimed at deterring speculation. Our mechanism analysis indicates that while speculative sales contribute to the increase in the price of neighboring units over time, speculative purchases have negligible effects. These findings underscore the potential of macroprudential policies in mitigating speculation and promoting housing affordability.

How competition play a role in dental pricing? A study on French medico-administrative and tax reports dataset

ObjectivesFrench dentists charge additional fees for dental prostheses. This paper aims to provide new information on the determinants of dental price setting and inform public decision-making in the context of the widespread rejection of prosthetic dental care for financial reasons. We focus on the competitive mechanism in the dental prosthetics market and measure the impact of the density of professionals and competitors' prices on the fees charged by dentists. MethodsWe use data merging from an administrative health insurance database and information from tax declarations of French dentists. We test the effect of competitor prices and competition on individual price-setting using instrumental variables. The database obtained included 29,220 dentists. ResultsPractitioners’ prices grow with competitors’ prices (+1€ in competitor prices entails an increase of + 0.37€ in the practitioner's price). Women set lower prices, and having a young child in the household predicts an increase in price of 6.8€ (p-value=0.014). Rural areas present lower fees than urban areas (+11.4€ (p value=0.000)). ConclusionProsthetic prices are strategic complements that are compatible with the application of monopolistic competition in the dental care market. We encourage the regulator to develop competitive mechanisms, for example, through a public offer at moderate prices.

The effect of hydropower bidding strategy on the iberian day-ahead electricity market

In 2021, the Iberian Electricity Market, which includes Portugal and Spain, experienced a significant increase in electricity prices. On average, prices tripled compared to pre-pandemic levels in 2019, despite stable demand. This trend, though less pronounced in other European markets, has raised concerns about the efficiency and competitiveness of wholesale electricity markets. This study investigates the bidding behavior of non-pumped hydropower plants in the Iberian market, employing a merit order model based on real data from 2019 to 2021. The analysis reveals a clear mismatch between hydropower bid prices and actual production costs. Although this practice is legal, it conflicts with the European Union's goal of promoting fair competition within the internal electricity market.Our findings suggest that aligning hydropower bid prices with 2019 levels could have reduced annual market costs by approximately 2324 million euros under a moderate scenario. This indicates substantial potential for cost savings and improved integration of hydropower. However, this strategy also benefits companies that own these hydropower plants, as they often possess large portfolios and can capitalize on increased market prices through other plants, particularly renewable energy units, which offer electricity at very low prices and have a high likelihood of being dispatched.Furthermore, the study highlights regulatory gaps allowing hydropower plants to price low-cost energy similarly to thermal plants, raising consumer costs and distorting market dynamics. These findings emphasize the need for stronger regulatory oversight and reforms to prevent excessive price inflation by hydropower, which plays a critical role in renewable energy integration and grid stability. Policymakers must ensure fair pricing while compensating hydropower plants for their flexibility and essential contributions to the energy system.

Investor Reaction To The Implementation Of Sustainability Reporting

The purpose of the disclosure of Sustainability Reporting is to solve social and environmental issues and may have an impact on achieving sustainable development in the face of social responsibility issues. In addition, Sustainability Reporting Disclosures can be used to achieve company goals. This study aims to analyze the implementation of Sustainability Reporting and whether it affects investor reactions in considering investment decisions. Sustainability Reporting disclosure in this study was tested as an independent variable with control variables EPS, PBV, and Dividends. An increase or decrease in stock prices indicates that investors react to the information disclosed, in this study, stock prices were tested as the dependent variable. The total research sample is 30 companies listed on the Indonesia Stock Exchange, with the category of companies getting an assessment rating from the National Center for Sustainability Reporting (NCSR). The results of hypothesis testing show that Sustainability Reporting disclosures have a significant effect on stock prices, so it can be concluded that Sustainability Reporting disclosures can provide a reaction to investor decisions. Control variables EPS, PBV, and Dividend Policy significantly affect stock prices.

Hierarchical Analysis of Foodstuffs and Housing in the Formation of the Final CPI After the Covid Pandemic -19 Early 2019-2021 in Ternate City

The review of the study on Edibles and Ownership of very expensive housing will be felt with the continuous high increase in general prices which results in the price of goods that are increasingly scarce in the market, these expensive all the imbalance of demand and supply does not become constant. The economy is currently spinning during the covid-19 pandemic, Social Limitations are the main cause while on the other hand, health is very important when hit by the covid-19 attack. All economic and health joints become sook (stagnant) in the sense that everyone needs rest. However, everyone also needs food, so everyone needs a job to earn income which leads to social welfare, food and board. The city of Ternate is Ternate is currently facing the challenges of high food staple prices and a strong demand for housing, which have made market conditions increasingly unstable. This situation necessitates balanced, measurable policies from all stakeholders in both the short and medium term to stabilize staple food prices. The city also grapples with complex issues such as high transportation costs and long distribution lines, all of which demand effective solutions to control prices and ensure market stability.

The Development of Industrial Agglomeration in Industrial Designation Areas and its Impact on Land Use Change (Case Study: Pringsurat Subdistrict and Kranggan Subdistrict, Temanggung Regency)

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Industrial agglomeration refers to the clustering of industries in a specific region, where they are in close proximity and have interconnections. This phenomenon not only stimulates the growth of industrial activities, but also influences the development of other economic sectors. As industrialization expands, it gradually extends into rural areas that usually have abundant undeveloped land primarily used for agriculture. Consequently, this trend prompts a transition from agricultural to industrial land use. Pringsurat subdistrict and Kranggan subdistrict are located in Temanggung Regency, Central Java Province. Both of these subdistricts are designated as Industrial Designation Areas (KPI) according to the Temanggung Regency Spatial Plan 2011-2031. The plan has implications for the rapid development of large and medium industries. The purpose of this study is to examine the growth of industrial agglomeration in Pringsurat subdistrict and Kranggan subdistrict and their impact on agricultural land conversion. This research was conducted from 2023 to 2024 and utilizing data from 2021 and 2022. The approach of this research is descriptive quantitative and utilizes spatial analysis with Geographic Information Systems (GIS) and descriptive analysis techniques. Based on the results of the analysis, there is an agglomeration of large and medium industries in Pringsurat subdistrict and Kranggan subdistrict. The growth of agglomeration encourages the establishment of new industries and industry linkages. Furthermore, agglomeration growth has led to changes in land use, an increase in the variety of land uses, and an increase in land prices. Results of the analysis also show that there are regulatory changes in the development of industrial agglomeration that will affect to local government decision in the future. </span></p></div></div></div>

Field evaluation and characterization of a novel biostimulant for broccoli (Brassica oleracea var. italica) cultivation under drought and salt stress which increases antioxidant, glucosinolate and phytohormone content

Anthropogenic global warming is affecting crop yield and thus compromising food security. Drought and salinization of the irrigation water or soil are increasingly frequent in most arable land, specifically in arid and semiarid areas such as the Mediterranean basin. Many crops have been displaced or their yield has plummeted in recent years, causing food shortages and price increases. In a context of global population growth and reduction in the availability of natural resources used in agriculture, finding novel tools that help farmers to maintain yield in an increasingly arid and saline scenario is of pivotal importance. This is particularly important in organic agriculture, where the number of available tools is very limited. Biostimulants are substances or microorganisms of natural origin whose function is to stimulate plant processes related to nutrient absorption, nutrient use efficiency, tolerance to abiotic stress or the quality of the agricultural products obtained. In the present work, we have evaluated, in field, the agronomic effectiveness of a novel biostimulant formulation in a cruciferous crop of great interest in the Mediterranean basin (broccoli) under control conditions, water and salt stress. Our research has shown that our product had a positive effect on broccoli production and in delaying flowering time. We have also found that the application of our biostimulant increased enzymatic and non-enzymatic antioxidant defense under drought conditions. Similarly, when exposed to salinity, the biostimulant increased the concentration of different phytohormones and glucosinolates. Taken together, our biostimulant increases the tolerance of broccoli to salt stress and water limitation by increasing the antioxidant response, the level of glucosinolates and eliciting the hormonal response.

Central bank information effects in Japan: the role of uncertainty channel

AbstractThis study identifies central bank information shocks and pure monetary policy shocks for Japan by combining high-frequency identification with sign restrictions. The empirical findings provide robust evidence of the central bank information effect in Japan. Specifically, the central bank’s optimistic outlook, conveyed through contractionary monetary actions, reduces economic uncertainty and leads to increases in stock prices and output. Additionally, changes in uncertainty play a significant role in the transmission of the central bank’s information effect. The overall impact of monetary policy and information shocks, as identified through our method, is found to be larger than that identified using conventional techniques such as Cholesky decomposition.

Quantifying seasonal market trends for tomato, pumpkin and cabbage in Guwahati (Assam, India)

The objective of the present study was to examine the seasonal and trend patterns in wholesale prices of tomato, pumpkin and cabbage over different seasons in Guwahati city, Assam. From time series and box plots, the study found that pumpkin prices are higher in November rather than lower prices during April or June. We find that cabbage is priced lowest from January to May and induces peaks in prices, rising the most in October. During January-April, tomato prices fall and reach a low point in April. From May onwards, the prices increase and peak in November. We performed the Mann-Kendal trend test, which showed no significant trend in the prices of all three perishable crops. It was proven that it is weakly loading and uniform across all years. Seasonal indices show a rise in the prices of pumpkins from May to October, cabbage from April to October and tomatoes from April to October reflecting their shorter shelf life and seasonal nature of these crops.

Uncertainty about what is in the price

A critical question facing speculators contemplating to trade on private information is whether their signal has already been priced in by the market. In our model, speculators assess the novelty of their information based on recent price movements, and market makers are aware that speculators might be trading on stale news. An asymmetric response to past price movements ensues: after price increases, buy volume – because it may result from stale news trading – has a lower price impact than sell volume (and vice versa after price decreases). Consequently, return skewness is negatively related to lagged returns. We find strong support for these and other predictions using a comprehensive sample of US stocks.

Impact of climate change on agriculture in Australia: an interactive fixed effects model approach

ABSTRACT Developing policies and programmes aimed at mitigating the impacts of climate change on crop yield requires methods that correctly quantify the dependence of crop yield on weather. This article utilizes recent advances in econometric methodology and proposes an interactive fixed effects model for modelling crop yield. An attractive feature of the proposed model is that it allows for the varying degrees to which different farmers adapt to global events, such as, an increase in the global fertilizer price and an introduction of a new technology. Thus, the proposed method is an improvement over the standard method based on the fixed effects model, which is widely used in the literature for modelling crop yield. We apply the proposed approach to model wheat yields across 24 statistical areas that cover the wheat belt of the state of Victoria, Australia. Our forecasts point to a potential 14% loss in yields in the state of Victoria and a 27% loss in North-West Victoria, under the Hotter & Drier climate scenario, which the IPCC predicts to be more likely for Victoria in the medium term. Should this eventuate, it would have significant negative impacts on the wheat industry, food security and the economy.

The Effect of Electronic Word of Mouth on Brand Image and Purchase Intention of Youth Customers in Kathmandu Valley

This study examines the effect of electronic word of mouth on brand image and purchase intention of youth customers in Kathmandu Valley. Brand purchase of customer is the dependable variable. The independent variables are brand image, price, information usefulness, source credibility and purchase intention. The primary source of data is used to assess the opinions of the respondents regarding the electronic word of mouth on brand image and purchase intention of youth customers in Kathmandu Valley. The study is based on primary data of 135 respondents. To achieve the purpose of the study, structured questionnaire is prepared. The correlation coefficients and regression models are estimated to test the significance and importance of different factors influencing brand image and purchase intention of youth customers during in Kathmandu Valley. The study showed that brand image and information usefulness have positive impact on brand purchase of customer. It indicates that increase in brand image and information usefulness leads to increase in brand purchase of customer. Likewise, source credibility has a positive impact on brand purchase of customer. It indicates that increase in source credibility leads to increase in brand purchase of customer. Similarly, purchase intention has a positive impact on brand purchase of customer. It means that increase in purchase intention leads to increase in brand purchase of customer. Moreover, price has a negative impact on brand purchase of customer. It indicates that increase in price leads to decrease in brand purchase of customer.

The Consumer Preference and Buying Pattern of Medicines through E-Pharmacy During COVID-19 in Kathmandu Valley

This study examines the consumer preference and buying pattern of medicines through e- pharmacy during COVID-19 in Kathmandu valley. Consumer buying behaviour is selected as the dependent variable. Similarly, patient safety, price, consumer loyalty, consumer satisfaction and purchase intention are selected as the independent variables. This study is based on primary data with 145 observations. The correlation coefficients and regression models are estimated to test the significance and importance of different factors influencing e- pharmacy during COVID-19 in Kathmandu valley. The study showed that patient safety has a positive impact on consumer buying behaviour. It means that increase in patient safety leads to increase in consumer buying behaviour. Similarly, consumer loyalty has a positive impact on consumer buying behaviour. It indicates that increase in consumer loyalty leads to increase in consumer buying behaviour. Moreover, consumer satisfaction has a positive impact on consumer buying behaviour. It means that increase in consumer satisfaction leads to increase in consumer buying behaviour. Likewise, price has a positive impact on consumer buying behaviour. It shows that increase in price leads to increase in consumer buying behaviour. Similarly, price has positive impact on consumer buying behaviour. It shows that higher the price, higher would be the consumer buying behaviour. Further, purchase intention has a positive impact on consumer buying behaviour. It shows that higher the purchase intention, higher would be the consumer buying behaviour.

Does urbanization drive up housing prices? Novel evidence from remote sensing and dynamic panel quantile regression

Purpose This study aims to quantify the influence of urbanization on housing prices at the district-based level, while also investigating the heterogeneous impacts across different quantiles of housing prices. Design/methodology/approach The study uses remote-sensed spectral images from the Landsat 7 ETM+ satellite to measure urbanization, replacing prior reliance solely on urban population metrics. Subsequently, the two-step system generalized method of moments is used to evaluate how urbanization influences district-based housing prices through three spectrometries: Urban Index (UI), Normalized Difference Built-up Index (NDBI) and Built-Up Index (BUI). Finally, this study examines the heterogeneous impacts across various housing price quantiles through Dynamic Panel Quantile Regression with non-additive fixed effects under Markov Chain Monte Carlo simulation. Findings The study demonstrates that urbanization leads to an increase in regional housing prices. However, these impact magnitudes vary across housing price quantiles. Specifically, the impact exhibits an inverse V-shaped curve, with urbanization exerting a more pronounced influence on the 60th percentile of housing prices, while its effect on the 10th and 90th percentiles is comparatively weaker. Originality/value This study uses a novel method of remote sensing to measure urbanization and investigates its effects on housing prices. Furthermore, it provides an empirical application of non-additive fixed effect quantile regression for analyzing heterogeneity.