Low Price Research Articles

Environmental Discourse and Firm Value: Evidence From Conference Calls

We examine environmental discourse in conference calls and the relation between this discourse and firm value. We measure the amount of environmental discourse as the frequency count of environmentally-related topics in the transcripts of conference calls. We argue that greater environmental discourse in conference calls indicates firms’ prioritization of environmental issues. Evidence indicates that greater amounts of environmental discourse are associated with lower share price and higher cost of capital, which we interpret as reflecting the relatively higher costs of environmentally responsible operations in excess of firm-specific benefits. Additional analysis examining general environmental, social, and governance (ESG), especially social and governance, discourse shows that it is associated with lower cost of capital and higher share price, suggesting that prioritization of social and governance issues does not imply higher operational costs and indeed may signal firm-specific value creation.

Empirical Study on BYD Stock Price Prediction Based on LSTM Model

This study employs Long Short-Term Memory (LSTM) neural network models for stock price prediction. LSTM models excel in managing nonlinearities and time-series dependencies in data, thereby enhancing the accuracy of stock price forecasts, reducing investment risks, and increasing returns. Investors can reasonably use the LSTM model to predict stock prices and obtain greater returns. The research utilizes eight years of historical data from BYD, including opening prices, closing prices, highest prices, lowest prices, and trading volumes, as training data. By adjusting various hyperparameters such as epochs, learning rates, and training-test ratios, the study analyzes their impact on the predictive accuracy of the model and identifies optimal configurations through comparative experimental methods. We found that the best parameters were when epoch number was 25, training ratio was 90:10 (minimum mean square error was 0.00175572) and 4 years of training data was selected as the training set (minimum mean square error was 0.00146477).

Measurement and Validation of Market Power in China’s Log Import Trade—Empirical Analysis Based on PTM Model and AIDS Model

China is the world’s largest importer of logs, possessing the scale to exert significant influence in the international market. This paper uses a fixed-effect variable coefficient Pricing-to-Market panel model to measure China’s market power in log import trade. It also utilizes the Almost Ideal Demand System model from an elasticity perspective to explore the market behavior characteristics of various source countries in China’s log import trade, thereby validating the mechanism of market power. The results indicate that: ① China’s main trading partners can be categorized into four groups according to their market power in the log import trade. Specifically, China holds superlative market power in log imports from Indonesia, Malaysia, and Myanmar; holds strong market power in log imports from Russia, the Democratic Republic of the Congo, and Mozambique; holds weak market power in log imports from Papua New Guinea, Equatorial Guinea, France, Germany, Australia, and New Zealand; and holds no market power in Japan, Cameroon, and the United States. ② As China’s expenditure on log imports increases, there is a tendency to purchase high-quality precious wood and a greater concern for the legality of market transactions. Consequently, China is anticipated to augment its imports from source countries with no or weak market power. ③ The simple price elasticity of log imports from each source country is negative. Source countries with stronger market power tend to increase prices to achieve higher total revenue, while those with weaker market power are more inclined to lower prices to achieve the same. ④ Log products from various source countries are complementary in the Chinese market, indicating that China’s substantial demand for logs relies on the simultaneous supply from multiple countries and diverse wood types. Based on the existence or absence of market power in China’s log import trade, this paper provides targeted insights into enhancing international market power and reducing trade losses.

Relationship Between Participation of In-Hospital Cardiac Rehabilitation and Regional Characteristics in Japan - Insight From the Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination.

The influence of various regional backgrounds on participation in cardiac rehabilitation (CR) remains underexplored. We investigated the regional characteristics that potentially promote CR participation. This was a nationwide cross-sectional cohort study using the Japanese Registry of All Cardiac and Vascular Diseases and the Diagnosis Procedure Combination. This study included a cohort of 2.7 million inpatients hospitalized between April 2012 and March 2021. The CR participation rate for each hospital was calculated as the percentage of eligible patients who underwent CR during their admission. Among all hospitals, those that do not perform CR were defined as No-CR hospitals. The remaining hospitals were categorized into High- and Low-CR hospitals based on the median level of the CR participation rate (41.5%). High-CR hospitals had significantly smaller medical service areas (P<0.0001), a higher number of physicians per population (P<0.0001), higher air temperature (P=0.02), and fewer primary industry workers (P=0.005) than the other 2 groups. Logistic regression analyses revealed that a lower consumer price index was a significant regional factor that characterized High-CR hospitals, and a lower population aged ≥65 years was a factor approaching significance that characterized the region where High-CR hospitals are located. High-CR hospitals were found in regions with a lower consumer price index and a trend towards a lower population aged ≥65 years.

Pricing Strategies for O2O Catering Merchants Considering Reference Price Effects and Unconditional Coupons

Coupon marketing is an important promotion model for the O2O catering supply chain. As a well-known catering O2O platform in China, Meituan provides its members with the opportunity to buy unconditional coupons at low prices, and it is very popular with consumers. It is worth studying how catering merchants develop pricing and promotion strategies considering consumers’ reference price effects in two scenarios: participating and not participating in coupon stacking (S-PICS/S-NPICS). In order to explore the pricing mechanism of meals, two models using Stackelberg games are established considering some exogenous variables, such as commission rate, reference price, and sensitivity of consumers to coupon prices. The results show that (1) the reference price has a great influence on the maximum profits of catering merchants, varying in different scenarios; (2) in S-NPICS, the merchants’ maximum profit increases with an increase in the reference price, while, in S-PICS, an increase in the reference price leads to a decrease in merchants’ maximum profit; (3) the profit of merchants in S-PICS is higher than that in S-NPICS, indicating that merchants can benefit from coupon stacking; (4) when the commission rate of the coupons increases, the merchants in both S-PICS and S-NPICS should raise their online meal prices to obtain higher profits. This study provides a balanced reference for pricing strategies and coupon promotion strategies in different scenarios through the use of deduction and simulation methods, which is conducive to the sustainable development of the O2O catering supply chain. As consumers enjoy using these coupons, including unconditional ones, it is suggested that merchants and Meituan should focus on coupon promotion and develop better dining pricing strategies.

Patient out-of-pocket expenditure in primary care comparing high income, middle income and low-income countries

Background: Out-of-pocket health expenditures (OOPHE) in primary care can pose a significant financial burden on individuals and households, particularly in low- and middle-income countries. Understanding the factors influencing OOPHE is crucial for developing effective policies to improve healthcare access and affordability. Objective: This systematic review aimed to identify and analyze the factors influencing OOPHE in primary care settings across high-, middle-, and low-income countries. Methods: A comprehensive search of electronic databases was conducted to identify relevant studies. Included studies were assessed for quality and data were extracted to identify key factors influencing OOPHE. Results: Demographic characteristics, socioeconomic factors, healthcare utilization, system factors, and cultural factors were all found to influence OOPHE. Lower income levels, limited insurance coverage, frequent healthcare utilization, and higher disease severity were consistently associated with higher OOP costs. Conclusion: The findings highlight the significant burden of OOP expenditures on individuals and households. Policymakers should prioritize strategies to expand health insurance coverage, improve access to primary care services, negotiate lower prices for healthcare goods, and address underlying socioeconomic factors. Further research is needed to explore the impact of specific interventions and the role of cultural factors in shaping OOP expenditures.

Early prediction of fabric quality using machine learning to reduce rework in manufacturing processes

The increasing competition and rapid technological advancements in today's business world have raised customer expectations. People now expect quick delivery, low prices, and high-quality products. As a result, companies must adapt to this competitive environment to survive. Rework, which is a significant cost in production, increases expenses, reduces production efficiency, and can lead to customer attrition. Research shows various efforts across different sectors to reduce rework, although there is still a gap in the textile sector's fabric dyeing units. Common problems in these units include non-retentive colors, customer dissatisfaction with shades, and repeated dyeing due to environmental factors or dye vat issues. This study uses logistic regression and artificial neural networks models from machine learning to predict which fabrics will need rework, using data from a textile company in Bursa. The analysis indicates that artificial neural networks models perform better.

Nano-organic polymers with rich redox sites as anode materials for dual-ion batteries

Organic electrode materials (OEMs) are considered one of the potential electroactive materials used in rechargeable batteries due to their high availability, low price, and sustainability. Nevertheless, the high solubility of their organic small molecules and their low electrical conductivity limit their practical applications. In this study, porous nanorods organic conjugated polymer were successfully prepared by a solvothermal method using 1,4,5,8-naphthalenetetracarboxylic anhydride and azodicarbonamide as precursors for dual-ion battery anodes. The successful synthesis of polymer extends the π-conjugated structure, effectively reducing its solubility in organic electrolytes. Moreover, the azo group (NN) in the polymer was easily conjugated with the adjacent aromatic ring, increasing the utilization of the active site, thereby improving the conductivity of the material so that the polymer has a high discharge capacity (90.5 mAh g−1 at 2 C, up to 96 % capacity retention). Even with a high rate of 10 C, the polymer still exhibits excellent electrochemical performance (50.0 mAh g−1 at 270 cycles). Moreover, reaction kinetics tests show that the electrode material was based on a pseudocapacitive storage mechanism influenced by diffusion and double-layer control. Therefore, the design strategy of such a material paves the way for the application of dual-ion batteries.

Capturing the Benefits of Autonomous Vehicles in Ride Hailing: The Role of Market Configuration

We develop an economic model of autonomous vehicle (AV) ride-hailing markets, in which uncertain aggregate demand is served with a combination of a fixed fleet of AVs and a flexible pool of human drivers (HVs). Dispatch efficiencies increase with scale because of density effects. We analyze market outcomes in this setting under four market configurations, defined by two dispatch platform structures (common platform versus independent platforms) and two levels of supply competition (monopoly AV versus competitive AV). A key result of our analysis is that the lower cost of AVs does not necessarily translate into lower prices; the price impact of AVs is ambiguous and depends critically on both the dispatch platform structure and the level of AV supply competition. In the extreme case, we show that if AVs and HVs operate on independent dispatch platforms, there is a monopoly AV supplier, and labor supply elasticity is sufficiently high, then prices are even higher than in a pure-HV market. Indeed, to guarantee consistently lower prices (relative to a pure HV market) in all scenarios and under all supply and density elasticities, a common dispatch platform between AVs and HVs is required. Furthermore, competitive AVs lead to lower prices than monopoly AVs in every such scenario. Our results illustrate the critical role that market configuration plays in realizing potential welfare gains from AVs. This paper was accepted by Omar Besbes, revenue management and market analytics. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2020.03112 .

Development and evolution of mathematical and econometric models for the analysis of macroeconomic processes (including historical perspective) and their forecasting

Practical usefulness of factor-vector autoregression has been considered, which makes it possible to study macroeconomic processes impact on the monetary policy state, to conduct full-scale monitoring and to identify economic growth impact on monetary policy. Publications devoted to the issues of unstable economic development and mathematical models describing the process of economic dynamics under conditions of high inflation and unstable development have been analyzed. The basic scenario in economy has been given. Monetary policy impact on macroeconomic variables using vector autoregressive (VAR) models has been studied. The FAVAR model with international reserves as the monetary policy variable and MIACR where the responses of one-year government bond rate and consumer index were positive have been estimated as the main instruments. The impulse responses shown indicate that the Russian authorities had a lack of monetary policy independence due to the country’s high dependence on the oil and natural gas sectors, which does not reveal evidence of monetary policy impact on lower consumer prices.

Relationship between Prices and Quality of Essential Medicines from Different Manufacturers Collected in Cameroon, the Democratic Republic of the Congo, and Nigeria.

Achieving universal access to affordable medicines and at the same time ensuring the quality of medicines presents a challenge, especially in low- and middle-income countries. Here, the relationship between medicine prices and medicine quality was investigated in three African countries. From different types of health facilities and medicine vendors, 711 samples of 18 different essential medicines were purchased and analyzed for quality (assay and dissolution) according to the United States Pharmacopeia. Without exception, all originator brand medicines and all SRA generics (generic medicines manufactured in countries with stringent regulatory authorities [SRAs]) complied with pharmacopeial specifications. In contrast, 21.1% of the non-SRA generics (manufactured in countries without SRAs) were substandard. The median prices of originator brands and SRA generics were three times and two times higher than those of non-SRA generics, respectively. Within the non-SRA generics, no positive correlation was observed between medicine quality and medicine price. Medicines manufactured in India, China, or African countries showed similar quality and similar prices. Only a single WHO-prequalified medicine sample was found among the 711 samples. Non-SRA generic medicines produced by manufacturers for which WHO had published Public Inspection Reports showed a significantly lower rate of substandard medicines (7.3%) and, at the same time, significantly lower prices (by 33%) than other non-SRA generics. Falsified medicines (total 2.0%) were found among all categories of medicines and had prices similar to those of non-SRA generics. Our findings indicate that adequate quality assurance does not necessarily imply an increase in medicine prices.

Recent Advances and Prospects of Nucleic Acid Therapeutics for Anti-Cancer Therapy

Nucleic acid therapeutics are promising alternatives to conventional anti-cancer therapy, such as chemotherapy and radiation therapy. While conventional therapies have limitations, such as high side effects, low specificity, and drug resistance, nucleic acid therapeutics work at the gene level to eliminate the cause of the disease. Nucleic acid therapeutics treat diseases in various forms and using different mechanisms, including plasmid DNA (pDNA), small interfering RNA (siRNA), anti-microRNA (anti-miR), microRNA mimics (miRNA mimic), messenger RNA (mRNA), aptamer, catalytic nucleic acid (CNA), and CRISPR cas9 guide RNA (gRNA). In addition, nucleic acids have many advantages as nanomaterials, such as high biocompatibility, design flexibility, low immunogenicity, small size, relatively low price, and easy functionalization. Nucleic acid therapeutics can have a high therapeutic effect by being used in combination with various nucleic acid nanostructures, inorganic nanoparticles, lipid nanoparticles (LNPs), etc. to overcome low physiological stability and cell internalization efficiency. The field of nucleic acid therapeutics has advanced remarkably in recent decades, and as more and more nucleic acid therapeutics have been approved, they have already demonstrated their potential to treat diseases, including cancer. This review paper introduces the current status and recent advances in nucleic acid therapy for anti-cancer treatment and discusses the tasks and prospects ahead.

A multi-stage machine learning approach for stock price prediction: Engineered and derivative indices

In this paper, a machine learning approach is proposed to predict the next day's stock prices. The methodology involves comprehensive data collection and feature generation, followed by predictions utilizing Multi-Layer Perceptron (MLP) networks. We selected 5,283 records of daily historical data, including open prices, close prices, highest prices, lowest prices, and trading volumes from four well-known stocks in the FTSE 100 index. A novel set of engineered and derivative indices is extracted from the original time series to enhance prediction accuracy. Two Multi-Layer Perceptron (MLP) are proposed to predict the next day's stock prices using the engineered discrete and continuous indices. The case study uses the daily historical time series of stock prices between January 1, 2000, and December 31, 2020. The proposed machine learning approach presents suitable applicability and accuracy, respectively.

Inventory pledge financing decisions based on a permissioned blockchain by controlling fraudulent risk

Inventory pledge financing (IPF) is a crucial financing way for small and medium-sized enterprise (SMEs). But banks are reluctant to finance SMEs due to fraudulent risk in practice. This paper discusses the application of blockchain in IPF, particularly its impact on mitigating fraud risks. Utilizing game theory models, we illustrate how the finance and operation decisions of participants, along with supply chain efficiency, are influenced by the introduction of blockchain. Meanwhile, equilibrium outcomes are analysed and numerical study is given. Our analysis reveals that under certain conditions, blockchain integration can lead to reduced loan interest rates, lower wholesale prices, increased order quantities by buyers, and enhanced supply chain efficiency. Lastly, we develop a protocol to demonstrate the transfer of digital warehouse receipt on a permissioned blockchain to avoid fraudulent risk. This study provides a theoretical foundation, and a guidance for decisions-making in blockchain-enabled IPF schme.

Has competition law enforcement been effective in South Africa?

ABSTRACT The South African Competition Act was crafted on the basis that it could be used to address distortions and inequalities in the market through enforcing competition. A question which has arisen is whether competition enforcement has been effective given that many economic sectors are still largely dominated by monopolies, duopolies or oligopolies. In this study, I assess whether competition enforcement has reduced inequality in South Africa by studying the link between market power and inequality, following a competition intervention in selected product markets. Using the nonlinear autoregressive distributed lag model, I assess whether competition enforcement in the market for bread, maize meal, and sunflower oil, has been effective in increasing consumer welfare, by lowering income inequality through lower prices. The findings of this study suggest that firms in these markets abuse their market power even post-intervention, such that they can raise prices and reduce consumer welfare, increasing inequality indirectly.

News Selection and Household Inflation Expectations

We examine the impact of systematic media reporting on household inflation expectations, focusing on how selective news coverage influences household responses to inflation news. In a model where monitoring all economic developments is costly, households will account for news selection when forming inflation expectations. The model implies an asymmetry: news about high inflation influences inflation expectations more than news about low inflation. Using micro panel data, we find support for this hypothesis. Exposure to news about higher prices increases household inflation expectations by approximately 0.4 percentage point, whereas exposure to news about lower prices has no discernible effect.

The Efficacy, Safety, and Persistence of Therapy after Non-Medical Switching from an Originator Adalimumab in Inflammatory Bowel Disease: Real-Life Experience from Two Tertiary Centres.

During the last two decades, an increased number of molecules with multiple mechanisms of action have been approved for the treatment of inflammatory bowel disease (IBD), with a substantial increase in the costs related to therapy, which has become a concern for payers, regulators, and healthcare professionals. Biosimilars are biologic medical products that are highly structurally similar to their reference products; have no clinically meaningful differences in terms of immunogenicity, safety, or effectiveness; and are available at a lower price. Materials and Methods: This was an observational prospective study conducted in two IBD centres in Bucharest and included 53 patients, 27 male (M) and 26 female (F), diagnosed with IBD according to standard clinical, endoscopic, radiological, and histological criteria, who were non-medically switched at the indication of the National Insurance House to a biosimilar of Adalimumab. Aims: The aim was to determine the rates of clinical remission, adverse effects, and treatment persistence at one year. Results: No significant differences were found in terms of the faecal calprotectin (FC) and C-reactive protein (CRP) levels 6 and 12 months after changing from the originator biologic treatment to a biosimilar. Only one patient required a change in their biological treatment following the clinical and biological loss of response. The main adverse effect reported by the patients was pain at the injection site. Of the 53 patients, only 2 reported pain at the injection site, and 1 patient reported experiencing abdominal pain and rectal bleeding immediately after the switch, but no recurrence was observed clinically or endoscopically. Conclusions: This observational study is the first to be carried out in Romania that shows that, after a non-medical switch, biosimilars of Adalimumab are as efficient and safe as the originator Adalimumab in the clinical treatment of patients with IBD.

ANALYSIS OF THE ECONOMIC PERFORMANCE OF PROJECT ADVANCED OIL RECOVERY WITH CO2 INJECTION (EOR/CCUS-CO2) THROUGH FINANCIAL INDICATORS: BRAZILIAN OVERVIEW

Enhanced Oil Recovery (EOR) is a method associated with Carbon Capture, Utilization, and Storage (CCUS) that consists of injecting CO2 into mature oil fields to store CO2 and enhance production. CO2-EOR projects are costly, requiring technical and economic evaluations to determine their viability. This research analyzes various economic parameters in CO2-EOR projects to develop a comprehensive model for assessing their economic viability in Brazil. The model was tested on projects developed by Silva et al. (2010) and included six scenarios of CO2-EOR in mature reservoirs. The results demonstrate the impact on well completion costs. The scenario with the highest oil production had one additional completion and, for this reason, did not show the best Net Present Value (NPV) result. This work also conducts a sensitivity analysis of parameters and reviews their impacts on NPV. Results indicate a significant impact of barrel price and minimum attractiveness rate on the NPV, while finding that the taxation of excess CO2 was not very significant. Low barrel prices (&lt;$9) proved to be unfeasible with negative NPVs.

Molten salt approach of zeolitic imidazole framework derived strontium doped porous carbon based bifunctional electrocatalysts for direct methanol fuel cell

Direct Methanol Fuel Cells (DMFCs) have sparked widespread interest and offer a viable approach for generating power. It has a number of commercial advantages, including low price, compact construction, and a quick refilling process that directly convert the chemical energy of methanol into electrical energy through an electrochemical reaction. However, direct methanol fuel cells (DMFCs) frequently rely on platinum catalysts, which are expensive and limited in scalability. Platinum catalysts can be poisoned by carbon monoxide (CO) thus preventing their widespread commercialization. Due to these drawbacks, there is growing interest in developing catalysts based on non-noble metals to improve DMFC technology's deployment. Herein, we report a facile synthesis method using a molten salt approach, which involves the solvent-free mixing of strontium nitrate tetrahydrate with ZIF-67, followed by direct pyrolysis in an Ar/H2 atmosphere at 800 °C. For methanol oxidation the strontium oxide loaded catalytic materials i.e., CoxOy SrO/C (1:1) exhibited a peak current density of 161 mA/cm2 and stability of 71 % over 28800s and for ORR it exhibit current density of −5.86 mA/cm2 and half wave potential of 0.87 V. The facile MOF synthesis strategy, enhanced by molten salt processing, shows great potential for creating non-noble catalytic materials for high-performance fuel cells.

Retailer-Manufacturer Partnerships in E-Commerce: Dual Product Strategy and Market Share Dynamics

A new practice among online retail platforms, e.g., Amazon and Wayfair, is to offer their own private label product and a substitutable exclusive manufacturer product. We employ a game theoretic approach to examine conditions under which a retailer and a manufacturer find it optimal to enter into such a partnership. Our analysis reveals that a retailer finds it profitable to partner with a manufacturer with one of two profiles. The first is a manufacturer with low unit production and holding costs and large capacity, and the retailer gives the manufacturer most of the market share. In this case, the retailer uses a low private product price and marketing effort to pressure the manufacturer to set a low exclusive product price, which increases the manufacturer's revenue and the retailer's fees. The second is a manufacturer with a large consumer base, high unit production and holding costs, and small capacity. For this profile, the retailer takes most of the market share by offering a low private product price, and the manufacturer is unable to counteract the retailer's low private product price and marketing effort. The partnership results in a lower price when the marketing effort is costly and the retailer relies on private product price, intensifying price competition. Under some conditions, the retailer's profit may decrease in his share of the manufacturer's revenue. Also, the retailer may increase the marketing effort and decrease the private product price, not to take market share, but to pressure the manufacturer to decrease price.