Price Points Research Articles

An econometric analysis of price elasticity and demand factors in the global honey and honey-based beverage markets

The contemporary discourse on global commodity markets presents a myriad of compelling quandaries for scholars, policy-makers, and practitioners alike. Among these markets, since 2015 the global honey and honey-based beverage sector embodies unique economic characteristics and dynamics. While the market has experienced expansive growth in a plethora of jurisdictions, Kazakhstan remains out of focus of researchers. For this reason, we decided to undertake an exhaustive econometric analysis, scrutinizing the price elasticity of demand and various demand determinants in Kazakhstan’s honey and honey-based beverage markets. Utilizing longitudinal data spanning over a decade, this investigation employs advanced econometric methodologies - including but not restricted to Ordinary Least Squares (OLS) regressions, co-integration analyses, and error-correction models - to rigorously interrogate the price elasticity of demand for honey and honey-based beverages. The research encompasses multiple control variables like GDP per capita, consumer behavior, inflation rates, and population dynamics to create a multi-faceted econometric model capable of rendering nuanced insights. It incorporates both macroeconomic and microeconomic variables to delineate the symbiotic relationship between price elasticity and demand determinants such as consumer income, advertising impact, and price points of substitute and complementary goods. The analysis showed that the honey market in Kazakhstan is fundamentally oligopolistic, and the triumvirate of top producers collectively wield a 60% market control, leaving a residual 40% for the aggregation of small and medium enterprises. However, the findings unveil a complex web of economic variables influencing the price elasticity of demand in Kazakhstan’s honey markets. Most notably, the study elucidates that the price elasticity of demand for honey and honey-based beverages is highly inelastic in the short term but transitions towards being elastic in the long run, a phenomenon predominantly influenced by changes in consumer income and preferences. A 12.3% increase in exports from 2020 to 2021 implies an increasing global demand for Kazakhstani honey, and thus should be a focus for stakeholders to leverage for market expansion. An Export-to-Production Ratio at 26% indicates that roughly one-fourth of honey produced is assigned for the international markets. The average production cost per kilogram of honey in Kazakhstan was found lower compared to the global average. Remarkably, digitization has been adopted as a salient strategy for market development. The penetration of digital platforms for honey trading increased from 2% in 2012 to 18% in 2021. The research identifies complex interplay between exogenous variables like global market trends, geopolitical factors, and cultural shifts, contributing to a comprehensive understanding of the market dynamics at play. This article makes several seminal contributions to the academic dialogue surrounding the economics of honey markets. Firstly, it adds a new geographic focus by centering on Kazakhstan, an understudied yet burgeoning market in the global honey industry. Secondly, the rigorous econometric methodology employed contributes to the methodological lexicon of commodity market analyses. Finally, the complex approach, incorporating both economic theory and real-world market trends, paves the way for future studies and aids in the formulation of policy directives aimed at stabilizing price volatility in commodity markets.

The language of wine reviews

ABSTRACT Expert wine reviewers have a niche skill set, with a particular lexicon, that facilitates their evaluation of wines. Novice consumers may find wine reviews intimidating and confusing. In this paper, we use a dataset of nearly 130,000 reviews from expert reviewers at Wine Enthusiast to explore the lexical dimension of wine reviews and determine to what extent reviewers systematically use language differently across various wine price points. Trends reveal that the information needed to make informed wine purchases are provided through the language of wine reviews. Our analysis shows that wine selection does not require a technical understanding of the wine-specific vocabulary of wine experts. We present a review of the literature on wine reviews and form four hypotheses under the theoretical framework of Kahneman’s two systems of thought—suggesting the linguistic properties of wine reviews reveal the price of wine. We examine how the lexical categories; emotional and logical linguistic content; social; and somatic experiences used in wine reviews relate to price. We then suggest the applicability of this analysis to other commodity domains in future research.

Direct-to-Video (On Demand): New Industrial and Cultural Valuations of Nontheatrical Film Releases

Direct-to-Video (On Demand): New Industrial and Cultural Valuations of Nontheatrical Film Releases

Marketing Campaigns Leading to the Purchase of Accommodation Products: A Content Analysis

Social commerce revolutionized the marketing of accommodations through online campaigns, social media promotions, and development of landing pages. Marketing, at its core, induced the customers to buy the products, while the establishment of the internet shaped different marketing strategies. The aim of this study was to develop a consumer-centered analysis that focused on their initial perception on accommodation products in a marketing campaign. This exploratory study analyzed the narratives of 8 customers who availed accommodation through a marketing campaign. Content analysis revealed that the most appealing marketing characteristic for customers was the social media presence, which showed the information customers need convincing them to purchase the products. Promoting price points and location were also remarkable for customers. The customers thought that presentation-wise, location and prices enabled them to make a purchasing decision. These characteristics allowed them to compare and visualize its differences to services offered by other accommodations. Other components such as convenience, security, and cleanliness also had notable influence on customer purchase intention. The results in this study offered new opportunity to hoteliers and hospitality industry to develop a marketing set up that uses targeted promotion and quality highlighting. These results constructed new perspectives on how to approach marketing and management in a competitive scale.

Intercomparison of commercial analyzers for atmospheric ethane and methane observations

Abstract. Methane (CH4) is a strong greenhouse gas that has become the focus of climate mitigation policies in recent years. Ethane/methane ratios can be used to identify and partition the different sources of methane, especially in areas with natural gas mixed with biogenic methane emissions, such as cities. We assessed the precision, accuracy, and selectivity of three commercially available laser-based analyzers that have been marketed as measuring instantaneous dry-mole fractions of methane and ethane in ambient air. The Aerodyne SuperDUAL instrument performed the best out of the three instruments, but it is large and requires expertise to operate. The Aeris Mira Ultra LDS analyzer also performed well for the price point and small size, but it required characterization of the water vapor dependence of reported concentrations and careful set-up for use. The Picarro G2210-i precisely measured methane, but it did not detect the 10 ppbv (part-per-billion by volume) increases in ambient ethane detected by the other two instruments when sampling a plume of incompletely combusted natural gas. For long-term tower deployments or those with large mobile laboratories, the Aerodyne SuperDUAL provides the best precision for methane and ethane. The more compact Aeris MIRA can, with careful use, quantify thermogenic methane sources to sufficient precision for mobile and short-term deployments in urban or oil and gas areas. We weighed the advantages of each instrument, including size, power requirement, ease of use on mobile platforms, and expertise needed to operate the instrument. We recommend the Aerodyne SuperDUAL or the Aeris MIRA Ultra LDS depending on the situation.

The Local Food Paradox: A Second Study of Local Food Affordability in Canada

The price of food has been affected in recent months in response to events such as the war in Ukraine, energy costs, inflation, the COVID-19 pandemic, and climate change. Indeed, supply problems, as well as the repercussions of global issues, have had an impact on grocery bills. Just between September and October 2022, the price of food increased by 11.4% and 11% year-to-year. In addition, with the pandemic, buying locally has become a key factor for some in choosing which products to consume. This second edition of the report aims to answer the question Does eating local in Quebec cost more? More precisely, our objective was to identify if local products in the food sector, especially in Quebec, were competitive in their price points compared to foods coming from other regions of the world. To answer this, we used AI and machine learning to harvest data from 99 local products and 335 comparable nonlocal products, totaling 198,990 data points and 3745 prices across six data collection dates. The results showed that a total of 25 categories displayed an advantage for the local product or a neutrality, out of a total of 45 categories identified. Our results demonstrated that 55.6% of the categories that contained the local foods analyzed were price competitive with comparable products or less expensive than them.

Three years of minimum unit pricing in the Northern Territory, what does the evidence say?

Three years of minimum unit pricing in the Northern Territory, what does the evidence say?

OTP bots and crypto: A tactic to disrupt

One-time password (OTP) bots are a form of crimeware-as-a-service that is being used to bypass two-factor authentication (2FA) on victim accounts. The bots are operated through Telegram and are sold at various price points in exchange for cryptocurrency. The bot operators facilitate a false phone call to victims, impersonating their financial institution, to obtain their OTP to commit an account takeover. Account takeovers facilitated by this type of social engineering are an enormous threat to financial institutions due to the inability to identify the attack without secondary corroboration. This paper illustrates the typical workflow of an OTP bot, avenues of institutional platform investigation and detection, as well as potential mitigation options to combat OTP bot attacks.

AudioMoth adventures: How does a low-cost recording device perform in extreme environments?

When it was originally released in 2018, the AudioMoth acoustic recording device delivered an attractive new platform for passive acoustic monitoring. With a price point under 100 US dollars, a size smaller than a deck of cards, and open-source software, the AudioMoth is an exciting option for getting started with bioacoustics monitoring. However, these same features often invite skepticism from those who have never used it. How good is the recording quality from its tiny MEMS microphone? How does it hold up to extreme outdoor conditions? The addition in 2022 of the HydroMoth for underwater recording, only invited more questions about its ability to perform in extreme environments underwater. This presentation will offer personal reports of the author's own experiences using the AudioMoth and HydroMoth. It will also include original field recordings captured in extreme environments like strong winds, heavy rains, and salt water lagoons. Special attention will be given to the two hurricanes that hit Florida in 2022, which were both captured by the author during a HydroMoth deployment. The audience will leave with a better idea of what to expect from the AudioMoth platform should they consider using it for their own projects.

Points of Interest and Housing Prices

ABSTRACT Points of Interest (POI) are an inherent element of the urban landscape, and their number and density reflect, among other things, the degree of urbanization and the city’s spatial structure. The very presence of POI in the closest vicinity of a residential property may indirectly or directly affect housing value. This paper aims to demonstrate the usefulness of POI density information of different categories in assessing the quality of a property’s immediate surroundings. While the mere presence of POIs in the nearest neighborhood may affect real estate prices, the influence of specific categories may not necessarily be positive. Therefore, the study attempted to classify POIs and determine their importance in the price formation process using spatial regression models. The results indicate that a high density of POIs in the immediate area is a stimulant for housing prices. The detailed analysis indicated that only some POI categories might be related to transaction prices, while in certain situations, some POI categories may negatively impact prices.

Jeans and their Fashionable Meanings: Revisiting Beverly Gordon's Cultural Conceptual Framework

Jeans and their Fashionable Meanings: Revisiting Beverly Gordon's Cultural Conceptual Framework

Consumer willingness to pay for farmed seaweed with education on ecosystem services

Kelp aquaculture in the US is expected to grow significantly in the coming years. While the market potential is substantial, increasing demand is widely seen as a key step towards realizing this potential. Recent work on restorative aquaculture practices has led to increased study and valuation of ecosystem services of kelp aquaculture. This study demonstrates the efficacy of education on ecosystem services of kelp aquaculture as marketing material for kelp end products. Through an online willingness to pay survey, this study found a significant increase in consumer willingness to pay for end products after a brief education on ecosystem services. Price point of the product, income, gender, knowledge of ecosystem services, and frequency of kelp product consumption were found to be significant predictors of the magnitude of change in consumer willingness to pay. Of the four major categories of ecosystem services, supporting services were reported to be most important to consumers. These findings can guide private and public organizations in marketing efforts to drive consumer behavior and to actualize the large potential of kelp aquaculture in the USA.

Pricing time-to-event contingent cash flows: A discrete-time survival analysis approach

Prudent management of insurance investment portfolios requires competent asset pricing of fixed-income assets with time-to-event contingent cash flows, such as consumer asset-backed securities (ABS). Current market pricing techniques for these assets either rely on a non-random time-to-event model or may not utilize detailed asset-level data that is now available with most public transactions. We first establish a framework capable of yielding estimates of the time-to-event random variable from securitization data, which is discrete and often subject to left-truncation and right-censoring. We then show that the vector of discrete-time hazard rate estimators is asymptotically multivariate normal with independent components, which has not yet been done in the statistical literature in the case of both left-truncation and right-censoring. The time-to-event distribution estimates are then fed into our cash flow model, which is capable of calculating a formulaic price of a pool of time-to-event contingent cash flows vis-á-vis calculating an expected present value with respect to the estimated time-to-event distribution. In an application to a subset of 29,845 36-month leases from the Mercedes-Benz Auto Lease Trust 2017-A (MBALT 2017-A) bond, our pricing model yields estimates closer to the actual realized future cash flows than the non-random time-to-event model, especially as the fitting window increases. Finally, in certain settings, the asymptotic properties of the hazard rate estimators allow investors to assess the potential uncertainty of the price point estimates, which we illustrate for a subset of 493 24-month leases from MBALT 2017-A.

Self-aligned multi-layer X-ray absorption grating using large-area fabrication methods for X-ray phase-contrast imaging

X-ray phase-contrast (XPCi) imaging methods are an emerging medical imaging approach that provide significantly better soft tissue contrast and could function as a viable extension to conventional X-ray, CT, and even some MRI. Absorption gratings play a central role in grating-based XPCi systems, especially because they enable the acquisition of three images in a single exposure: transmission, refraction, and dark-field. An impediment to commercial development and adoption of XPCi imaging systems is the lack of large area, high aspect ratio absorption gratings. Grating technology development, primarily due to technological limitations, has lagged system development and today prevents the scaling up of XPCi system into a footprint and price point acceptable to the medical market. In this work, we report on a self-aligned multi-layer grating fabrication process that can enable large-area X-ray absorption gratings with micron-scale feature sizes. We leverage large-area fabrication techniques commonly employed by the thin-film transistor (TFT) display industry. Conventional ITO-on-glass substrates are used with a patterned film of Cr/Au/Cr that serves as a self-aligned lithography mask for backside exposure. Commonly available SU-8 photoresist is patterned using the backside exposure mask followed by an electroplating step to fill the gaps in the SU-8 with X-ray attenuating material. Consequently, the electroplated patterned material acts as a self-aligned photomask for subsequent SU-8 layer patterning and so forth. The repeatability of the reported process makes it suitable for achieving higher aspect ratio structures and is advantageous over previously reported X-ray LIGA approaches. A prototype three-layer grating, with a thickness of around 40,upmu text{m}, having a visibility of 0.28 at 60,text{kV}_p with a 70,text{mm}times 70,text{mm} active area was fabricated on a 4-inch glass substrate and demonstrated by modifying a commercially available 3D propagation-based XPCi Microscope. The scalable and cost-effective approach to build larger area X-ray gratings reported in this work can help expedite the commercial development and adoption of previously reported Talbot-Lau, speckle-tracking, as well as coded-aperture XPCi systems for large-area clinical and industrial applications.

Characterization of Growth Performance, Pork Quality, and Body Composition in Mangalica Pigs.

European heritage breeds, such as the Blonde (B), Red (R), and Swallow-bellied (SB) Mangalica pig, display an extreme propensity to fatten and are reputed to produce superior quality pork. This suggests that Mangalica pork should command a higher price, and the Mangalica is a candidate breed to target niche markets within the United States. Our objectives were to test this hypothesis by (1) directly comparing growth performance and carcass merit of purebred Yorkshire (Y), B, R, and SB Mangalica pigs to identify the best breed for adoption, and (2) comparing indices of pork quality in purebred R, Y, and crossbred (R × Y) pigs to determine if crossbreeding represented a viable alternative to the adoption of purebred Mangalica. Daily feed intake, average daily gain (ADG), and feed efficiency were highest in Y and lowest in SB pigs with B and R ranked intermediately (p < 0.001). Backfat thickness was greatest in B and lowest in Y with R and SB ranked intermediately (p < 0.001). Marbling score was greatest in R pigs and lowest in Y pigs with B and SB ranked intermediately (p < 0.01). In contrast, loin eye area (LEA) was greatest in Y pigs compared to B, R, and SB (p < 0.001). Indices of meat quality were then compared in R, R × Y, and Y pigs. Backfat thickness and marbling scores were greater in R than R × Y and Y pigs (p < 0.001) while LEA was greater in Y than R × Y and R pigs (p < 0.001). Loin and ham ultimate pH, color, and firmness scores were significantly greater in R than R × Y or Y pigs (p < 0.05). Meanwhile, cook loss was significantly less in R than Y pigs (p < 0.007) while Warner-Bratzler Shear Force (WBS) was not different in chops between groups (p < 0.11). These data indicate that though Mangalica exhibit poorer growth performance, Mangalica pork exhibits superior pork quality attributes, suggesting that higher price points for Mangalica pork in niche markets are justified.

Economic Value of Food Commodities and Labor Shift due to Rice Field Conversion in Batu City, Indonesia

Increasing tourist activities in Batu City makes agricultural land conversion unavoidable. This research aims to determining the lost economic value of food commodities due to converted agricultural land area and labor shift. The conversion area of agricultural land in all areas can be identified through Landsat image 8 ETM+ in 2017 and 2021. An overlay analysis using ArcGIS 10.2 software with 7 variables was then utilized to determine land capability and land suitability. Then, it was combined with the survey results of 334 land price points to determine the distribution of agricultural land prices in Batu City by using Kriging interpolation analysis. The results of the research show that the agricultural land area has decreased in the past 4 years by 169.96 Ha, with a lost economic value of approximately 5 billion Indonesian rupiah. The agricultural land price in Batu City is divided into 4 classifications. The results indicate that the agricultural land price is high, so it accelerates the agricultural land conversion. Therefore, the government should pay close attention to land conversion.

Could Collected Chemical Parameters Be Utilized to Build Soft Sensors Capable of Predicting the Provenance, Vintages, and Price Points of New Zealand Pinot Noir Wines Simultaneously?

Soft sensors work as predictive frameworks encapsulating a set of easy-to-collect input data and a machine learning method (ML) to predict highly related variables that are difficult to measure. The machine learning method could provide a prediction of complex unknown relations between the input data and desired output parameters. Recently, soft sensors have been applicable in predicting the prices and vintages of New Zealand Pinot noir wines based on chemical parameters. However, the previous sample size did not adequately represent the diversity of provenances, vintages, and price points across commercially available New Zealand Pinot noir wines. Consequently, a representative sample of 39 commercially available New Zealand Pinot noir wines from diverse provenances, vintages, and price points were selected. Literature has shown that wine phenolic compounds strongly correlated with wine provenances, vintages and price points, which could be used as input data for developing soft sensors. Due to the significance of these phenolic compounds, chemical parameters, including phenolic compounds and pH, were collected using UV-Vis visible spectrophotometry and a pH meter. The soft sensor utilising Naive Bayes (belongs to ML) was designed to predict Pinot noir wines' provenances (regions of origin) based on six chemical parameters with the prediction accuracy of over 75%. Soft sensors based on decision trees (within ML) could predict Pinot noir wines' vintages and price points with prediction accuracies of over 75% based on six chemical parameters. These predictions were based on the same collected six chemical parameters as aforementioned.

Design Elements That Increase the Willingness to Pay for Denim Fabric Products

This study analyzed what design elements are attractive to consumers of denim fabric products. A questionnaire survey was used to investigate the brands and design elements that consumers prefer. Subsequently, the degree to which participating consumers liked the five design elements (traditional, transformative, pattern, multi-material, and decorative designs), fast fashion brands, and luxury brands were used as explanatory variables to determine the consumers’ willingness to pay. A multiple regression analysis was performed on these variables. The results indicated that consumers who preferred traditional and transformative designs showed a positive effect on their willingness to pay for denim fabric products. Therefore, these elements could be attractive design elements that may command a high price point in new product planning proposals. Moreover, depending on the type of brand preferred by consumers, the impact of design elements on their purchase intention of denim fabric products has different consequences. This study analyzes the design elements preferred by consumers and contributes to the creation of design proposals by designers and apparel firms.

Are Market Prices for Patent Licenses Observable?

Despite the pervasiveness of patent licensing in many industries, there is a dearth of publicly available information on licensing transactions. Notably, information on price—i.e., the royalty agreed upon by licensor and licensee—is purposefully kept secret. We assess to what extent “market prices” on patent licenses are observable by assembling all publicly available information on royalty amounts associated with the licensing of 4G and 5G standard essential patents (SEPs). Our data come from a range of sources including court verdicts and litigation settlements, arbitration awards, public announcements, and published licensing agreements. We show that even for a highly visible technology such as mobile broadband, the available price points are few and far between. Moreover, any comparison of the available data points, let alone their aggregation, is extremely challenging due to largely unobservable heterogeneity in the terms and scope of the underlying licensing agreements. Our results point to a lack of transparency in the market for patent licensing that might adversely affect market participants and competition more broadly.

An efficient novel approach to E-commerce retail price optimization through machine learning

Businesses can use price optimization to discover the most profitable price point by using customer and market data to drive their decisions. The optimal price points will result in the company making the most money possible, but they may also be created to help the company expand into untapped markets or increase its market share, for example Businesses can use machine learning to price products and services to maximise sales or profitability by using data instead of educated guess-work. When utilised for price optimization, ML-based algorithms can be used to forecast demand for a particular product as well as the ideal price and how buyers will respond to specific pricing. Pricing decisions can be made more accurately using machine learning, which will boost a company's revenue.