Product Price Changes Research Articles

Elasticity-integrated pricing and allocation heuristic for airline revenue management

Setting the right fares is a key lever for increasing operating profitability in the airline industry. It is crucial to design fares that are both appealing to passengers and contribute to an increase in airline revenue. Although airline revenue management techniques have evolved to capture customer-choice behavior, the pricing and allocation decisions continue to be taken independently. However, since they are linked, a single optimization model can address this shortcoming. This paper presents a joint optimization model (JOM) that considers product prices and their allocation quantities as decision variables. A sequential optimization technique that divides the model into two decision problems is adopted to cope with JOM’s complexity. The problem is divided into a master problem and a sub-problem, wherein product price changes are made in the master problem and, with these fixed prices, optimization is performed in the sub-problem. The sub-problem is solved by simplifying the non-linear JOM into a linear programming problem. The direction of product price changes in the master problem is identified using price elasticity of demand. A heuristic based on this concept is proposed and tested. The Elasticity-integrated Pricing and Allocation Heuristic (EPAH) is observed to produce a consistent increase in existing revenues.

How are climate risk shocks connected to agricultural markets?

In the climate-sensitive agricultural sector, product prices are particularly susceptible to climate risks. In this study, we constructed three novel climate risk perception indices—a climate policy uncertainty index, a climate physical risk index, and a climate concern index—using natural language processing and text mining to investigate their differential effects on bulk agricultural prices. The findings indicate that the responses of agricultural product prices to climate risk perceptions are more pronounced in the short term than in the long term. Moreover, the impacts of climate-related concerns and physical risks have stronger impacts than climate policy uncertainty. The dynamic analysis results also indicate that climate-related events have a great impact on investors and financial markets. Overall, the findings suggest that climate risk perceptions have become a significant factor in agricultural product price changes, which has important implications for policy regulators and market investors.

Price Identification And Financial Feasibility Study of Hydroponic Agriculture Iot Solution Launch Project at PT XYZ

Since 2015, the Internet of Things technology has grown significantly, reaching over 400 million users by 2022 in Indonesia. Recognizing the potential, PT XYZ, an innovative Indonesian telecommunications company, intends to launch an IoT solution for hydroponic agriculture. The launch project requires an initial investment of around Rp 500 million. Given that amount, PT XYZ aims to determine the selling price using a value-based pricing strategy and assess the project's financial feasibility and risks before proceeding. Primary and secondary data will be utilized in this research to determine the customer's willingness to pay (WTP), Capital budgeting cash flow, which includes the hypothetical price of IoT, calculating the weighted average cost of capital (WACC), free cash flow to the firm (FCFF), and terminal value. The study used various capital budgeting techniques, such as net present value (NPV), profitability index, payback period, internal rate of return (IRR), and Excel's goal seek feature, to determine the IoT solution's pricing. A risk analysis using sensitivity and Monte Carlo simulations have conducted. The research finds that the present value of benefits, or WTP, for the IoT solution, is Rp 90,708,238. Considering PT XYZ's targeted internal rate of return of 20%, the determined selling price is Rp 20,120,408, which lies within the customer's WTP, making the project feasible. Capital budgeting techniques show a payback period of 4.08 years, an NPV of Rp 3,424,935,505, and a profitability index of 8.21 over five years, indicating positive outcomes. However, the sensitivity analysis reveals that a change in product price, cost of goods sold, and salary expenses will significantly impact the NPV, resulting in a 12.69% risk, with profitability remaining high at 87.31%. In conclusion, PT XYZ's hydroponic agriculture IoT solution launch project is considered feasible, considering potential risks and mitigation strategies.

Dynamics of Price Transmission: Evidence from India’s Import Basket

This article uses granular information on trade flows between India and its trading-partners to estimate the impact of price changes on the import basket in general. We first investigate whether a change in world prices at the commodity level triggers a reorganisation of trading partners. Second, we examine the degree of transmission of world prices to Indian import prices. Lastly, we look at whether India imports less from countries that charge a higher markup on a product. Our results indicate that a change in world prices does not significantly change the set of importing countries. Using the country–product level price changes, we find a higher degree of transmission as compared to the world prices. This provides an important policy implication. In order to determine how the transmission of world prices to import prices works, we need to pay attention to the product price changes in the partner countries rather than focusing on the world prices. Lastly, we find that India imports less of a particular product on average from a country that charges a higher markup for that product relative to the average export prices charged by that country. JEL Codes: F14, F60, F02, Q27

Environmental Value Assessment of Plastic Pollution Control: A Study Based on Evidence from a Survey in China

A scientific environmental management decision is based on the correct assessment of environmental value. Aiming to objectively and accurately assess the environmental value of plastic pollution treatment, in this paper, we design a choice experiment with four item characteristic attributes consisting of source reduction, recycling, cleanup and remediation and price. With the research data of 450 interviewed residents, a choice experiment method (CEM) and numerical simulation were used to comprehensively assess the environmental value of plastic pollution treatment in China, incorporating discount rates and future price changes of environmental products into the study. The results showed that: (1) residents’ willingness to pay per capita for source reduction, remediation and recycling was CNY 32.79, CNY 25.27 and CNY 15.78, respectively; (2) from the perspective of compensation surplus, the residents were willing to pay CNY 147.68 per capita for environmental improvement; (3) the dynamic curve of the value of plastic pollution control displayed an increasing, then gradually declining trend, and its total economic value of 100a was CNY 21,259.97 per capita; and (4) the model simulated the possible trajectory of future changes in plastic pollution control (three scenarios of constant, decreasing and increasing rates of development of plastic pollution control services) and found that addressing the plastic pollution problem early is more conducive to improving the overall welfare of society. This study can provide a basis for scientific evaluation of the benefits of plastic pollution management and allocation of pollution management resources.

Supply Chain Demand Forecasting and Price Optimisation Models with Substitution Effect

Determining the optimal price of products is essential, as it plays a critical role in improving a company’s profitability and market competitiveness. This requires the ability to calculate customers’ demand in the Fast Moving Consumer Goods (FMCG) industry as various effects exist between multiple products within a product category. The substitution effect is one of the challenging effects at retail stores, as it requires investigating an exponential number of combinations of price changes and the availability of other products. This paper suggests a systematic price decision support tool for demand prediction and price optimise in online and stationary retailers considering the substitution effect. Two procedures reflecting the product price changes and the demand correlation structure are introduced for demand prediction and price optimisation models. First, the developed demand prediction procedure is carried out considering the combination of price changes of all products reflecting the effect of substitution. Time series and different well-known machine learning approaches with hyperparameter tuning and rolling forecasting methods are utilised to select each product’s best demand forecast. Demand forecast results are used as input in the price optimisation model. Second, the developed price optimisation procedure is a constraint programming problem based on a week time frame and a product category level aggregation and is capable of maximising profit out of the many price combinations. The results using real-world transaction data with 12 products and 4 discount rates demonstrate that including some business rules as constraints in the proposed price optimisation model reduces the number of price combinations from 11,274,924 to 19,440 and execution time from 129.59 to 25.831 min. The utilisation of the presented price optimisation support tool enables the supply chain managers to identify the optimal discount rate for individual products in a timely manner, resulting in a net profit increase.

THE INFLUENCE OF PRICE AND PRODUCT VARIETY ON PURCHASING DECISIONS FOR MOUNTEA

The aim of this study was to examine how Mountea's purchase decisions were affected by product prices and product variants. Quantitative primary data were employed in the analysis in this study, and the following tests were run: validity test, reliability test, normality test, multicollinearity test, heteroscedasticity test, multiple linear regression test, T test, F test, and coefficient of determination. The study's valid data were gathered by 100 participants in the form of a Google Form, which was utilized to administer the questionnaire. Non-probability sampling using the purposive sample technique was the sampling strategy used in this investigation. SPSS version 26 was used as the testing software. The findings indicated that Mountea's purchase decisions were partially influenced by the results of the variable pricing and product variety. Purchase decisions on Mountea are influenced simultaneously by product variety and price changes.

The impact of external reference pricing on pharmaceutical costs and market dynamics

Growth in the cost of prescription drugs in the US has generated significant interest in the use of external reference pricing (ERP) to tie prices paid for drugs to those in other countries. We used data from the Pricentric ONE™ database, an international drug pricing database, to examine product launch timing, launch price, and price changes from January 2010 – October 2021 in both ERP and non-ERP settings, with a focus on 100 high-priced drugs of interest to Medicare and Medicaid. We found that ERP policies were associated with a 73% reduction in the likelihood of drug launch within 9 months of regulatory approval relative to non-ERP settings. In addition, while ERP was associated with statistically significant reductions in annual drug price changes, such policies did not impact launch price. In addition, no single ERP feature (e.g., number of countries referenced, ERP calculation) was materially associated with the outcomes of interest. We conclude that ERP policies do not appear to impact drug launch price and may delay access to new therapies, raising questions about the utility of such policies in the US and potential consequences abroad.

IMPACT OF PETROLEUM PRODUCTS PRICE CHANGES ON PRICES OF FOOD ITEMS IN THE NIGERIAN ECONOMY

There seems to be disequilibrium between food items and petroleum price changes in Nigeria. Every petroleum price change is followed by a rise in the prices of food items and increased poverty. This study therefore examines the impact of petroleum product price changes on the prices of food items in the Nigerian economy. Annual time series data from 1991 to 2021 are employed and the study adopt ARDL approach to determine the long-run and short-run relationship between the price of premium motor spirits and the price of food items in Nigeria. However, as it is reported by the unit root test there is a mixture of 1(0) and 1(1) order of cointegration. With these results, it is more suitable to apply the ARDL approach. The results show that the price of premium motor spirit has a positive and significant impact on food items during the short run but in the long run, the prices of premium motor spirits have a positive and insignificant impact on the food items in Nigeria. The results of the Toda and Yamamoto (1995) causality tests show that there is a unidirectional causality running from the price of food items to the price of premium motor spirit and from the exchange rate to the price of food items. Therefore, the government should implement policies that encourage agricultural productivity which has great potential of boosting food supply so as to reduce the price of food items across the country. This way, timely increases in petroleum prices would generate more revenue without inflationary trends in food items.

Dynamic baselines depending on REDD+ payments: A comparative analysis based on a system dynamics approach

The mechanism of reducing deforestation emissions in developing countries (REDD+) could play an increased role in climate mitigation by determining country-specific emission baselines. An impact evaluation able to assess the baselines change in response to carbon payments must be considered in order to highlight effective baselines. In this study, we proposed dynamic baselines and developed a forest-carbon-economy system-dynamic model to assess reduced deforestation emissions and payments for emission reductions. We conducted a comparative analysis from five countries, which were representatives of four forest country types. The results showed that the average dynamic baselines were lower than static baselines in Brazil, Cameroon, Guyana and Indonesia. It implied, in the context of limited climate funding, use of dynamic baselines will help REDD+ achieve more cost-efficient emissions reductions in these countries. Furthermore, the uncertainty analysis of the key parameters showed that different data sources of carbon density, carbon prices and changes in agricultural product prices affect emission reductions. Thus, when a country has high flexibility in determining data sources, it may choose profitable data under alternative data sources, which can compromise the climate effectiveness and cost efficiency of the entire REDD+ mechanism.

Futuristic projection of selected commodities in India

This study has estimated the factor demand and output supply elasticity’s for major food crops in India. The elasticity’s have provided insights on the responsiveness of output supply and factor demand to changes in product and factor prices. The estimates have been used to make supply projections of selected commodities to 2030.The study observes that Demand for rice and wheat will be met with their domestic production in the coming years, may be with a marginal Surplus/deficit under the scenarios of with or without total factor productivity growth. Total Pulses, would be short in supply of demand in the coming years.

PENGARUH KUALITAS PRODUK, HARGA DAN LOKASI TERHADAP KEPUTUSAN PEMBELIAN (STUDI KONSUMEN UMKM MIE AYAM DAN BAKSO BAROKAH INA KABUPATEN BUNGO)

This study aims to analyze the influence of product quality, price and location on purchasing decisions of the UMKM consumer study of Mie Ayam and Bakso Barokah Ina in Bungo. The research method used is quantitative, the data sources used are primary and secondary data. The population in this study were all consumers who had bought at Mie Ayam and Bakso Barokah Ina stalls in Bungo. The sample in this study as many as 96 respondents with sampling taken by using accidental sampling technique. Data collection methods used: interviews and questionnaires. The data analysis method used is multiple linear analysis and hypothesis testing using t test, F test and coefficient of determination. From the results of the t-test analysis shows that product quality, price and location partially affect purchasing decisions. The results of the F-test show that product quality, price and location simultaneously affect purchasing decisions. The results of the analysis of the coefficient of determination obtained adjusted R square (R2) of 0.670, this means that 67% of changes in purchasing decisions are caused by the changes in product quality, price and location variables. While the remaining 33% is due to changes in other variables included in the variables studied

Price changes of dairy products in the European Union

This article presents changes in the prices of milk and other dairy products in the European Union (EU). First, the descriptive statistics of the prices of milk and dairy products are presented, and then correlation and regression analyses were conducted to measure the relationships between the prices. We used the augmented Dickey-Fuller (ADF) test and generalised autoregressive conditional heteroscedasticity (GARCH) model to measure the stationarity and changes in dairy product prices in the EU. At the EU level, we checked the changes in prices of butter, skim milk powder, whole milk powder, Cheddar, Edam, Gouda, Emmental and whey powder. Our analysis confirmed that the butter, skim milk powder, whole milk powder, Cheddar, Edam and Gouda processes depend on previous values. The biggest price changes were observed in whey powder (34.12%), butter (24.46%) and skim milk powder (21.78%).

The impacts of COVID-19 on GDP, food prices, and food security

COVID-19 has led to a wealth of research examining possible impacts; however, potential impacts to food security have received much less attention. We use a computable general equilibrium model to simulate the potential impacts of COVID-19 using observed changes from 2020 (September) in unemployment, trade, oil prices, and production to inform our model. Estimated GDP and food price changes are then used as inputs into the International Food Security Assessment (IFSA) model which estimates changes in food consumption, and food gaps in developing countries. Results indicate that the COVID-19 lockdowns lead to a decrease in global GDP of 7.2 per cent, and a decrease in grain prices of 9 per cent. These changes lead to an increase in the number of food-insecure people in 2020 of 211 million (a 27.8 per cent increase). We also perform a sensitivity analysis, providing a lower and upper bound of potential impacts from COVID-19.

Impact of Carbon Tax Increase on Product Prices in Japan

The introduction or strengthening of a carbon tax is being considered in many countries as an economic policy instrument to reduce greenhouse gas (GHG) emissions. However, there is no study analyzing the impact of a carbon tax increase in a uniform method for various products, reflecting the energy taxes and exemptions. Therefore, this study analyzes the price changes of products associated with the introduction of a stronger carbon tax, using Japan as an example. A process-based life cycle assessment database was used to enable a detailed product-level analysis. Five scenarios with different taxation amounts and methods were analyzed. The results show that price changes vary greatly by industry sector and product, even within the same industry sector. For example, seasonal vegetables and recycled plastics are less affected by carbon tax increases. Imported products, such as primary aluminum, are not affected by the Japanese carbon tax change, indicating a risk of carbon leakage. If GHGs other than CO2 are also taxed, the price of CH4 and N2O emitting products, such as rice and beef, would rise significantly. The method presented in this paper enables companies to assume price changes in procured products due to carbon taxes and policymakers to analyze the impact of such taxes on products.

Reducing the Decarbonisation Cost Burden for EU Energy-Intensive Industries

Carbon leakage features prominently in the climate policy debate in economies implementing climate policies, especially in the EU. The imposition of carbon pricing impacts negatively the competitiveness of energy-intensive industries, inducing their relocation to countries with weaker environmental regulation. Unilateral climate policy may complement domestic emissions pricing with border carbon adjustment to reduce leakage and protect the competitiveness of domestic manufacturing. Here, we use an enhanced version of GEM-E3-FIT model to assess the macro-economic impacts when the EU unilaterally implements the EU Green Deal goals, leading to a leakage of 25% over 2020–2050. The size and composition, in terms of GHG and energy intensities, of the countries undertaking emission reductions matter for carbon leakage, which is significantly reduced when China joins the mitigation effort, as a result of its large market size and the high carbon intensity of its production. Chemicals and metals face the stronger risks for relocation to non-abating countries. The Border Carbon Adjustment can largely reduce leakage and the negative activity impacts on energy-intensive and trade-exposed industries of regulating countries, by shifting the emission reduction to non-abating countries through implicit changes in product prices.

INVESTIGATING THE CUSTOMER BUYING BEHAVIOR OF FABRIC PRODUCTS IN INDIA

Purpose: The purpose of this study is to understand the variables affecting the consumers while purchasing the products and to identify whether the purchase of the products creates or disappointment leading to affinity towards handloom products. Design/Research Methodology/approach: Data were collected from 251 handloom product customers in Bhopal through a questionnaire and collected data is analysed with the help of Percentage analysis and Factor analysis. Findings: The attitude of the consumers towards handloom products was highly influenced by the attributes of convenience, attraction, expectation and awareness. Research Implications: The consumers prefer handloom products for their regular use and were of the opinion that their reaction will differ towards price changes of handloom products and hence, the sellers can consider these as the important elements while fixing of the prices of the handloom products. Scope for future work / Research limitations: This study mainly focused to identify the factors influencing the attitude of the consumers towards purchase of handloom products and also study about the consumer attitude depending on the demographic factors of the handloom product. The consumers attitude may also be assessed by including some more attitudinal factors. Further this contribution surveyed 251 respondents from a particular city; hence the result may or may not be applicable to the other cities or states in India. Originality/value: The analysis based on secondary data has found that there are various studies on factors affecting consumer attitude but this paper has taken demographic factors affecting consumers purchasing attitude towards handloom products. Key Words: Demographic factors, factor analysis, customer delight Paper type: Research paper

What women want? How contextual product displays influence women’s online shopping behavior

A lack of touch and feel options inhibits online purchases; to enhance online product presentations, this study suggests a potential influence of rich contextual product displays, relative to plain white backgrounds. The results of five studies reveal that the product usage context influences purchase intentions among female customers. Women and men differ in their decision-making processes and evaluate different attributes and benefits prior to purchase. Displaying a product in a rich contextual setting appears to enhance women’s perceptions of emotional value, which heightens their purchase intentions. This article also explicates the additive effect of including contextual elements and confirms the robustness of these effects across product categories and price changes. These findings suggest various notable implications for academics and practitioners.

Antifungal Lotion as Value-Added Product for Harvested BSFL Processing: Simple Process Design and Economic Evaluation

Advancing the value of products derived from insect biomass is a potential way to increase the demand of processing insect as renewable and sustainable resources. Among several species of insect, black soldier fly larvae (Hermetia illucens) is promising biomass source because of its favorable characteristics such as easy cultivation, fast-growing, and worldwide distribution. One problem that could limit the development of insect-based bioproduct is the low market price and displeasing uses for edible food. To overcome this problem, value-added product development is necessary to carried out. Thus, establish an antifungal lotion using extracted materials from BSFL biomass was discussed in this report followed by the economic evaluation and sensitivity analysis. The result reveal that equipment availability in market and raw material readiness espouse the production expediency. From the economic aspect, the direct fixed capital cost (DFC) for a plant of this capacity is around US$3.6 million, or approximately 6 times the total equipment cost. Thus, the net profitability will remain stable even the market price of BSFL might fluctuate in the range of 20%. In contrary, the change in main product price was impactful to the rate of return (ROI), internal rate of return (IRR) and, payback time (PBT) value. The overall result suggests that this project is worthy to being built.

Impact of Loss and Gain Forecasting on the Behavior of Pricing Decision-making

Recent forecasting research has shown a paradigm shift from algorithm aversion to appreciation. Despite growing trust in technological decision support, business decisions are often made based on gut feeling and intuition, ignoring part or all of the available data and information. Creating effective decision support solutions necessitates the understanding of the impact of emerging artificial intelligence and machine learning technologies on business decision-making processes. This study examines whether forecasting information delivery at a time when a business decision is made influences or changes the decision maker’s mind, thereby leading to a different decision. The study employs a 2 × 2 between-subject experimental setting where forecasted results (gain/loss) and automated advice (risk/certainty) were crossed-examined. A sample of 137 participants was asked to make four different product price change decisions assisted by automated decision aid. The experiment involved two independent samples, one taken from Amazon Mechanical Turk workers and the other from the members of LinkedIn managerial groups. Results show that decision-makers are more likely to rely on automated recommendation and change their initial decision when forecasted decision outcomes lead to gain, whereas they would discount algorithmic aid if a loss is forecasted. This research adds to the extant literature in the field of human-technology interactions and contributes to the descriptive and prescriptive decision theories by illustrating that gain forecasting has a higher impact on the algorithm appreciation than loss forecasting.