Price Points Research Articles

Modeling Group Exercise Members Continuation

This research presents a conceptual model that investigates group exercise program continuation, influenced by membership price, service quality, and group cohesion. A random sample of members from recreation fitness centers completed a group exercise questionnaire (three locations, n= 200). The study measured members’ perceptions of class social cohesion, group exercise service quality, price satisfaction, and continuation. Results show that Price Satisfaction, Group Exercise Service Quality (GXSQ) and Group Integration Task (GI-T) have a direct significant relationship with Intent to Repurchase. GXSQ and Price mediate the relationship of GI-T and Continuation. Price mediating the relationship of GXSQ and intent to repurchase. GI-S does not contribute to the model. The results emphasize the importance of the quality of the program (instructor and operations) and the price point when deciding to repurchase classes. The collective task and how participants perceived satisfaction are influenced by these factors, and a positive experience leads to program continuation.

Can Corporate Social Responsibility Shift Consumer Behavior? Insights from Scenario-Based Experiment in the Fast Fashion Industry

This study investigates the interplay between Corporate Social Responsibility (CSR) engagement and pricing strategies in shaping consumer purchase intentions in the fast fashion industry. Using a scenario-based experimental design with 267 participants, this research explores how different levels of CSR and two distinct price points influence purchasing behavior. Additionally, the moderating effects of individual differences, such as consumer wealth, motivations for sustainable behavior, and income, are examined. The findings indicate that higher levels of CSR engagement significantly enhance purchase intentions, particularly when combined with higher price points, perhaps due to consumer perceptions of CSR programs associated with more expensive brands as more authentic. However, price remains a critical factor for lower-income consumers, revealing an “ethical consumption gap” where affordability outweighs ethical concerns. Extrinsic motivations, such as social pressure, strongly influence wealthier consumers’ decisions, while intrinsic motivations show a more complex relationship with purchasing behavior. The findings provide practical insights for fast fashion brands, suggesting that aligning CSR with competitive pricing and authentic messaging is crucial for appealing to both price-sensitive and ethically conscious consumers.

Paradox: Revolutionizing American-Inspired Sportswear in the Chinese Market

Paradox aims to disrupt the rapidly growing Chinese sportswear market, which has reached a size of $47.8 billion, by targeting men aged 15-35 years—a demographic that consumes over 60% of the sportswear in the country. The company leverages American-inspired designs combined with affordable pricing, addressing the gap created by leading brands such as Nike, which often overprice their products, limiting access for the targeted consumers. Paradox’s competitive advantage lies in delivering quality comparable to American labels at lower price points, appealing to emerging middle-income earners eager to embrace an American athletic lifestyle.The founding team, comprised of experienced professionals from the sportswear industry, has streamlined the supply chain and manufacturing processes to maintain efficiency while employing a direct-to-consumer business model. With projected conservative sales growth of 25% per year and a solid marketing strategy focused on influencer partnerships and e-commerce, Paradox is set for significant market entry. The startup seeks $10,000 in funding to launch its first collection and expects to generate profits within the first 18 months. With its unique value proposition, strong management team, and targeted approach to an underserved market, Paradox presents itself as a lucrative investment opportunity poised to revolutionize the sportswear sector in China.

A Review of Sanitation Options and Programming in Ghana, West Africa

This review examines Ghana’s progress in sanitation. These efforts include the containment, transport, treatment, and disposal or reuse of human waste. This research specifically examined the current sanitation processes and programming efforts within Ghana, West Africa. Some reports indicate that Ghana is the second dirtiest country in Africa and the seventh dirtiest country in the world. A review of the current water, sanitation, and hygiene (WASH) options within the country indicates that significant efforts need to be undertaken. There are multiple toilet options and current practices within the country for the disposal of excrement. Unfortunately, the municipal sewer systems and wastewater treatment facilities within the country are either broken down or severely inadequate compared to their surrounding population. Current WASH programming, extension efforts, and key factors affecting the uptake of sanitation investment are reviewed. The price point where consumers would utilize sanitation products and services was analyzed, as well as the cost-to-benefit ratio of specific technologies for community members. This review demonstrated that initiatives should be undertaken to provide more sanitation professionals, renovate and expand urban municipal sewerage systems, and provide basic access to rural community areas. It was recommended that future programming, extension, and policy efforts be intentional and include relevant stakeholders and community members to provide a greater opportunity for establishing successful and substantial efforts.

EXPRESS: The Multitier Discount Effect

How can firms make their quantity discounts more attractive to consumers? This research proposes that, instead of providing only a quantity discount (e.g., regular price: $6.99 each; buy two: $5.59 each), offering it along with an additional tier of discount (e.g., buy one: $6.79 each) can increase the likelihood that consumers take the quantity discount. This “multitier discount effect” occurs because the inclusion of the additional discount tier can lead consumers to perceive the quantity discount price as lower. Through a series of studies involving different consumption contexts, product categories, price points and discount levels, this research demonstrates the multitier discount effect, its mechanism and key boundary conditions. Specifically, Study 1 shows that social media ads featuring multitier (vs. control) discounts can attract higher clickthrough rates. In a preregistered incentive-compatible setup, Study 2 demonstrates the multitier discount effect and the mediating role of perceived price difference. Studies 3-5 indicate that the price level of the additional discount tier, consumers’ prior purchase frequency, and their distrust of advertised original price can each moderate the multitier discount effect. These findings add to the theoretical literature and provide actionable managerial insights.

Carbon Price Point–Interval Forecasting Based on Two-Layer Decomposition and Deep Learning Combined Model Using Weight Assignment

With the intensification of global warming, the demand for carbon emissions reduction has gradually increased in various countries. Carbon price is crucial for promoting the activation of the carbon trading market and facilitating emissions reduction. However, the current carbon price has non-linear characteristics, large fluctuations, and high complexity, making accurate predictions challenging. To effectively predict the trends and change of carbon price, this study proposed a hybrid deep learning point–interval prediction model. First, an improved variational mode decomposition–symplectic geometry mode decomposition (IVMD–SGMD) two-layer decomposition model was constructed to decompose the carbon prices into regular subsequences. Then, attention–temporal convolutional network–bidirectional gated recursive unit (Attention-TCN-BiGRU) and Encoder–Decoder long short-term memory (LSTM) combined prediction models were constructed for the prediction of subsequences. The entropy method (EM) was used to assign weights to the predictions of two models to achieve model complementarity and a linear reconstruction of the models’ results. Then the error correction was performed to obtain the final prediction results. This study conducted an experiment on carbon prices in the Guangdong and Shenzhen markets. The mean absolute error (MAE) of the two datasets were reduced by 89.69% and 87.43% lower than that for LSTM. To demonstrate the model's adaptability, prediction experiments conducted on natural gas and crude oil prices were employed, confirming its strong predictive accuracy in energy price forecasting. Based on the point prediction error, the interval prediction using the improved kernel density estimation (IKDE) provides more carbon market information for decision makers. The proposed model aids government energy policy formulation and fosters ongoing efforts to reduce carbon emissions.

Interval Forecasting of Carbon Price With a Novel Hybrid Multiscale Decomposition and Bootstrap Approach

ABSTRACTThis paper proposes a novel hybrid multiscale decomposition and bootstrap approach for carbon price interval forecasting, aiming to overcome the limitations of traditional carbon price point forecasting. The original carbon price is decomposed into simple modes using the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and various bootstrap methods are applied to perform a random sampling with a replacement on each mode, generating pseudo datasets forecasted using extreme gradient boosting (XGB). The forecasting values of all modes are then integrated into the original carbon price interval forecasting values. The empirical results, based on samples from China's Guangdong and Hubei carbon markets, provide compelling evidence of the effectiveness of our model. It achieves higher forecasting accuracy, higher interval coverage, and narrower forecasting intervals than currently popular prediction models, instilling confidence in its potential to enhance carbon price forecasting.

A feasibility study on predicting cow calving time over 40 h in advance using heart rate and financial technical indicators

In dairy farming, the uncertainty of cow calving date often imposes waiting costs for days on farmers. Improving the accuracy of calving date prediction would mitigate these costs, specifically before a few days of the event. We monitored and analyzed the heart rate patterns of eight pregnant cows in the days leading up to calving using a dedicated monitoring device. We decomposed the heart rate data into three distinct components: trend, daily cycle, and the remainder, and discovered that the heart rate trend exhibited a sharp decline more than 40 h before the calving event via the trend turning point. To detect the turning point, we applied common financial technical indicators traditionally used to identify turning points of asset prices in trading markets for the extracted heart rate trend. This study remains a feasibility study because of the limited observations, but it indicates that these indicators can effectively capture the trend’s turning point in real time, offering a promising approach for enhanced calving prediction. In addition to discussing the practical implications for cow management, we also contemplate the broader utility of these technical indicators in the context of various dynamic scientific data analyses.

DIBS*: Crafting a Treasured Niche

In January 2022, Siddharth Pande, the founder and owner of DIBS*, a new creative branding studio providing design solutions based in Delhi, was trying to identify an appropriate strategic position for his business in an overcrowded market. Digital spaces have turned business outcomes significantly, especially after the outbreak of the COVID-19 pandemic and the resultant mobility restrictions. Digital agencies experienced plenty of new opportunities as all traditional and new-age businesses were competing to improve their online presence and humanize their brands to connect with their customers. This also gave birth to a plethora of digital brand consulting agencies which offered differentiated services at varying price points. In the design industry that relied on a star system where agencies struggled to make any headway, how could DIBS* craft a treasured niche?

Cation Engineering Perovskite Cathodes for Fast and Stable Anion Redox Chemistry in Zinc‐Iodine Batteries

AbstractZinc‐halogen batteries are promising for sustainable energy storage, offering high redox capacities at economical price points. However, they are hindered by issues such as the irreversibility caused by the dissolution of intermediates and the sluggish charge transfer, which limit their widespread adoption. Addressing these issues, bismuth‐iodide perovskite cathodes are employed as a halogen element enriched model system. These perovskite cathodes demonstrate considerable anion redox capacities. In a combined simulation and experimental study, it is uncovered that the (BAD)BiI4 (BAD+ denotes benzamidinium) cathode, greatly improves interactions with iodine species and boosts charge transfer capability compared to its (BA)BiI4 (BA+ denotes benzylaminium) counterpart. These enhancements can be attributed to the synergistic effects arising from stronger Bi−I···I halogen bonds and C═N─H···I hydrogen bonds. The (BAD)BiI4 cathode attains a reversible I−/I0 redox chemistry with 92% capacity retention after 30 000 cycles at a current density of 10 A g−1I, outperforming previously reported anion redox batteries. Additionally, the defect‐tolerant property and the I−/I0/I+ conversion of the (BAD)BiI4 are elucidated. The I5− forms a notably stronger bond with (BAD)BiI4 in comparison to I3−, which effectively mitigates polyiodide shuttling. These advantageous characteristics highlight the promise and adaptability of the developed perovskite cathodes for high‐performance anion redox chemistry.

Cost-Effectiveness of Zanubrutinib Versus Bendamustine and Rituximab in Patients With Untreated Chronic Lymphocytic Leukemia

Zanubrutinib, a potent and specific irreversible Bruton's tyrosine kinase inhibitor, has proven to be effective in untreated chronic lymphocytic leukemia (CLL), whether used alone or in combination with other therapies. Here, we compared the cost-effectiveness of zanubrutinib with bendamustine-rituximab (R-bendamustine) to determine its effectiveness as the first-line treatment for Chinese patients with untreated CLL. The evaluation utilized a partitioned survival model, constructed using TreeAge Pro 2011 software, incorporating data from SEQUOIA trial (NCT03336333). Transition probabilities were estimated from the reported survival probabilities in trials using parametric survival modeling. In this analysis, the quality-adjusted life years (QALYs), incremental cost-effectiveness ratio, and lifetime cost were calculated from the Chinese health care system perspective. Sensitivity analyses, including 1-way analysis and probabilistic sensitivity analysis, were carried out to explore the uncertainty of the modeling results. Additionally, several scenario analyses, including different zanubrutinib price calculation and 20-year time horizon, were evaluated. The findings revealed that zanubrutinib had an incremental cost-effectiveness ratio of $58,258.18 per additional QALYs gained compared with bendamustine-rituximab, with zanubrutinib being cost-effective only if its price was reduced by more than 30%. Research indicated that zanubrutinib achieved at least a 3.70% probability of cost-effectiveness at the threshold of $38,223.34/QALY. One-way sensitivity analysis revealed that the results were sensitive to the utility of progressed disease. The study highlighted the importance of considering the cost-effectiveness of zanubrutinib at its current price point for patients with untreated CLL in China, emphasizing the need for further assessment and potential pricing adjustments to enhance its economic viability in clinical practice.

A combined model based on decomposition and reorganization, weight optimization algorithms for carbon price point and interval prediction

With the increasing environmental and climate problems caused by global warming, more and more countries are paying attention to reducing carbon emissions. Accurately predicting carbon prices can help create a stable carbon market and mitigate global warming. Therefore, a combined model which has four modules is proposed, they are the decomposition of carbon price series, reorganization of subsequences, point forecasting, and interval forecasting. For data preprocessing of decomposition, it can reduce the non-linearity of sequences. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) decomposes the original series into multiple Intrinsic Mode Functions (IMFs). Reorganization uses SampEn (SE) and T-test to reorganize the decomposed sequence into three new sequences according to actual meanings. For point prediction, the combined prediction model uses Particle Swarm Optimization (PSO) to obtain the optimal weights of Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU), which can integrate their strengths to improve prediction accuracy. Interval prediction is based on fitting the optimal distribution function by Maximum Likelihood Estimate (MLE). Different significance intervals can be obtained from the point prediction results and the distribution function. Empirical and comparative experiments show this combined model has excellent point and interval predictions. Besides, the significance and stability are demonstrated. Finally, some valuable references are provided for policymakers.

Pet Owners' Preferences for Quality of Life Improvements and Costs Related to Innovative Therapies in Feline Pain Associated with Osteoarthritis-A Quantitative Survey.

This research aimed to explore UK cat owners' preferences for treatments for feline osteoarthritis (OA) by exploring preferences around quality of life (QoL) improvements, safety considerations, and costs associated with hypothetical innovative pain therapies. Aspects identified in an existing conceptual framework were extracted for inclusion in exploratory interviews with cat owners (n = 3) to identify key domains that contribute to the QoL of cats. QoL descriptions for cats with OA and hypothetical product attributes were developed and validated through interviews with veterinarians (n = 3). An online survey was subsequently shared with 255 pet owners in the UK. Pet owners were presented with QoL descriptions and hypothetical product attributes to gather their preferences for QoL improvements and their willingness to pay (WTP) for (unbranded) pain therapies at various price points. Pet owners were motivated to improve their cats' QoL, which translated into WTP for therapies; specifically, pet owners valued QoL improvements in mobility, pain expression, and well-being. When presented with a product profile of the hypothetical novel monoclonal antibody (mAb) and cost, 50% of cat owners were willing to pay more for a mAb that is expected to have improved efficacy and safety when compared to a hypothetical standard of care (SoC). Significantly more pet owners preferred the mAb than the SoC when price was not presented (p < 0.01), with product efficacy and safety driving pet owners' decision-making. The majority of pet owners did not agree that taking their cats to the veterinarian once a month for their treatment would be burdensome. Cat owners in the UK are motivated to improve their cats' QoL, which translates into WTP for the efficacious treatment of pain associated with osteoarthritis. Veterinarians should offer cat owners the pain treatment they feel is best suited for improving the cat's QoL and to ensure subsequent owner-pet bond is preserved.

Price benchmarks of drugs selected for Medicare price negotiation and their therapeutic alternatives.

The Centers for Medicare and Medicaid Services (CMS) are currently negotiating prices with pharmaceutical manufacturers for the first 10 Part D drugs selected for Medicare drug price negotiation. Non-publicly available data, including the net prices of selected drugs and their therapeutic alternatives, will play a central role in the determination of the maximum fair prices (MFPs). To estimate price benchmarks involved in the derivation of the starting point of the CMS initial price offer for the 10 drugs selected for Medicare price negotiation. For the 10 drugs selected for negotiation, we reported (1) the list price, (2) the net price after manufacturer discounts, (3) the maximum negotiated price based on the minimum statutory discount, and (4) the ceiling of the MFP, estimated as the lowest of the latter 2. We also estimated net prices for therapeutic alternatives to the selected drugs. Net prices were estimated using peer-reviewed methodology that isolates commercial discounts negotiated between payers and manufacturers from mandatory discounts under government programs. All price benchmarks were estimated at the product level, for 30-day equivalent dosing, using 2021 data. 6 products (apixaban, rivaroxaban, empagliflozin, sacubitril/valsartan, etanercept, and insulin aspart) had therapeutic alternatives with lower net prices, which will be integrated with clinical benefit data in the derivation of initial price offers. The other 4 products (ustekinumab, ibrutinib, sitagliptin, and dapagliflozin) had therapeutic alternatives with higher net prices than the drugs selected for negotiation. For ibrutinib and ustekinumab, prices based on the minimum discounts were considerably lower than the estimated net prices and will likely set the starting point of the initial price offer. For dapagliflozin and sitagliptin, the starting point of the initial price offer will likely resemble their existing net prices. Our analyses identify different negotiation scenarios for the first 10 drugs selected for Medicare price negotiation, based on key elements involved in the derivation of the initial price offer. Our analyses can help improve transparency in the negotiation process, because the CMS is not required to reveal the information used in the derivation of price offers.

Introduction and Validation of Low-Cost Ocular Biometry in Healthy and Cataractous Eyes Using a Thermally Tunable Swept-Source Laser

To introduce and validate a novel substantially lower-priced and rapid swept-source investigational optical biometer in healthy and cataractous eyes, using a thermally tuned laser diode used extensively in cell phones and data communication as an alternative swept source. Prospective accuracy, validity, and reliability analysis. A total of 60 eyes of 59 subjects (29 eyes of 29 healthy subjects and 31 eyes of 30 cataract patients) were enrolled in a prospective comparative study at the Vienna General Hospital between August 2021 and April 2023. Averaged intraocular distances were acquired in 2.5 seconds from datasets consisting of 5000 consecutive A-scans at a single position by a low-cost swept-source optical biometry (SSOB) system. Instrument repeatability was assessed via standard deviations (SDs) and coefficients of variation (CoVs) of parameters such as axial length (AL), anterior chamber depth (ACD), lens thickness (LT), and central corneal thickness (CCT). Healthy subjects and cataract patients were subsequently measured on the same day with the SSOB and a referential partial coherence interferometry (PCI) biometer (IOLMaster 500) to establish AL inter-device correlation (r) for instrument calibration. AL and ACD as shared parameters between both biometers were evaluated for their limits of agreements (LoA) using Bland-Altman analysis. Repeated measurements of AL, ACD, LT, and CCT revealed SDs of 18 µm, 12 µm, 12 µm, and 10 µm, respectively. All parameters except for CCT had a COV <1%. Except for 1 eye with white cataract, 59 eyes of 59 study participants with various degrees and types of cataract could be measured with both devices. The AL inter-device correlation was excellent (r > 0.99). The 95% LoAs between both biometers were -0.14 to 0.13 mm for AL and -0.28 to 0.25 mm for ACD. Optical biometry using a thermally tunable VCSEL swept-source light source has the potential to provide clinically relevant biometric parameters at an unprecedented 100-fold lower price point than currently used state-of-the-art optical biometers, paving the way for compact devices in remote care settings.

Exploring the psychology of price barriers in Baltic stock markets

PurposeThe purpose of this study is to investigate the presence of psychological barriers both in the main stock market indices of the Baltic states and the most actively traded individual stocks. A psychological barrier refers to a specific price point, often at round numbers (i.e. powers of 10), that investors believe is challenging to breach, influencing their behavior and trading decisions.Design/methodology/approachWe conduct uniformity tests and barrier tests, such as barrier proximity tests and barrier hump tests, to evaluate the presence of psychological barriers. Additionally, we explore variations in means and variances near these potential barriers using regression and GARCH analysis.FindingsThe findings reveal that psychological barriers do exist in the Baltic stock markets, particularly within market indices. The Estonian market index stands out with the most pronounced indications of psychological barriers. Individual stocks also display significant changes in means and variances related to potential barriers, albeit with less uniformity.Practical implicationsCollectively, our findings challenge the traditional assumption of random returns within the Baltic stock markets. For practitioners, the finding that psychological barriers exist opens up opportunities for investment strategies that can capitalize on them.Originality/valueThis study is the first to comprehensively investigate psychological barriers in the Baltic stock markets. Our results provide a valuable contribution to understanding the impact of that phenomenon on pricing dynamics, which is particularly pertinent in less-researched frontier markets like the Baltic states.

A hybrid model for point and interval forecasting of agricultural price based on the decomposition-ensemble and KDE

A hybrid model for point and interval forecasting of agricultural price based on the decomposition-ensemble and KDE

Tensions undermining equitable school funding: insights from Australia

ABSTRACT School funding policy in Australia not only promotes educational equity in some ways but also creates substantial between-school resource inequalities due to its embrace of market ideologies. School funding policies are designed to promote school choice and competition, based on the assumption that they are both a right and an effective lever for improving educational outcomes. School funding is used to create an educational marketplace with varying ‘price points’, leading to the acceptance of a two-tiered system of basic provision via the public sector and enhanced provision for those willing to pay via the private sector. Political commitment to making school funding more equitable has been largely absent. Marketisation is the mechanism by which schooling maintains its capacity to reproduce social inequality without evoking class-based discourse or anxiety.

Study of Factors involved in smartphone brand preferences in Delhi NCR

Smartphone usage is rapidly increasing in today's society due to their diverse functionalities, effectively serving as portable substitutes for laptops, while also offering calling capabilities. We conducted a study to explore consumer preferences regarding smartphones in the Delhi NCR regions.This study delves into the factors driving smartphone brand preferences among young consumers in Delhi and the National Capital Region (NCR). Through this study we investigated user familiarity with smartphones, brand preferences, and the key factors influencing purchasing decisions. Additionally, we delved into consumer preferences regarding smartphone specifications such as design, multimedia features, operating platform, and price points. This research, encompassing 26 including both students and working individuals, employs various statistical tests like correlation and cross-tabulation. The findings from this study are expected to provide valuable guidance for smartphone companies in developing marketing strategies tailored to meet consumer preferences. Keywords: stress, students, stress management.

Robotic platforms in gynaecological surgery: past, present, and future.

More than two decades ago, the advent of robotic laparoscopic surgery marked a significant milestone, featuring the introduction of the AESOP robotic endoscope control system and the ZEUS robotic surgery system. The latter, equipped with distinct arms for the laparoscope and surgical instruments, was designed to accommodate remote connections, enabling the practice of remote telesurgery as early as 2001. Subsequent technological progress has given rise to a range of options in today's market, encompassing multi-port and single-port systems, both rigid and flexible, across various price points, with further growth anticipated. This article serves as an indispensable guide for gynaecological surgeons with an interest in embracing robotic surgery. Drawing insights from the experience of the Strasbourg training centre for minimally invasive surgery (IRCAD), this article offers a comprehensive overview of existing robotic platforms in the market, as well as those in development. Robotic surgical systems not only streamline established operative methods but also broaden the scope of procedures, including intra- and transluminal surgeries. As integral components of the digital surgery ecosystem, these robotic systems actively contribute to the increasing integration and adoption of advanced technologies, such as artificial intelligence-based data analysis and support systems. Robotic surgery is increasingly being adopted in clinical practice. With the growing number of systems available on the marketplace, the primary challenge lies in identifying the optimal platform for each specific procedure and patient. The seamless integration of robotic systems with artificial intelligence, image-guided surgery, and telesurgery presents undeniable advantages, enhancing the precision and effectiveness of surgical interventions. This article provides a guide to the robotic platforms available on the market and those in development for gynaecologists interested in robotic surgery.