Current Prices Research Articles

Analysis of Earnings Quality and Enterprise Valuation of Microsoft by Earnings Quality and Residual Income Model

Artificial intelligence has had a remarkable influence in recent years and has developed many revolutionary solutions in many industries. OpenAI’s ChatGPT is one of the most popular products in this trend. As the largest stockholder of OpenAI, Microsoft has committed itself to integrating artificial intelligence into its primary products, like Microsoft Office and Azure. Although Microsoft experienced a continuous slump in stock in 2022, Microsoft’s current stock price has broken through $400 per share. This paper aims to conduct a financial analysis and forecast Microsoft’s future growth to figure out Microsoft’s intrinsic value. This article uses earnings quality analysis and residual income model to evaluate Microsoft’s financial performance and conduct valuation. Microsoft’s Cash Conversion Cycle has become negative since 2021, so Microsoft can reinvest the cash it receives from sales before using it to pay suppliers. The present value of the continuing value in the Residual Income Model indicates that Microsoft is undervalued compared to the current stock price. Economic conditions and the global supply chain will also influence investors’ expectations, except for quantitative factors. Therefore, Microsoft's stock price fluctuates and does not exceed the forecasted price. This article offers some insights on Microsoft and relevant industry valuation analysis.

A Review and Economic Analysis of the Dapivirine Vaginal Ring as HIV Pre-Exposure Prophylaxis for Women, to Inform South African Public-Sector Guidelines.

South Africa has a high HIV incidence and oral pre-exposure prophylaxis (PrEP) is available as public-sector standard of care. Access to alternative prevention methods for women may further reduce HIV acquisition. South African public sector. We performed a systematic search for high-quality up-to-date guidelines recommending dapivirine rings as PrEP using the Grading of Recommendations Assessment, Development, and Evaluation -Adolopment process. We appraised the systematic review and randomized controlled trial (RCT) evidence underpinning the selected guideline's recommendations and conducted a cost-effectiveness analysis. The Grading of Recommendations Assessment, Development, and Evaluation evidence-to-decision framework guided the adaptation of source guideline recommendations, according to our local context. We identified the 2021 World Health Organization PrEP Guidelines, informed by 2 placebo-controlled RCTs, which were included in a contemporaneous systematic review. There were 23 fewer HIV acquisitions per 1000 clients with dapivirine ring vs placebo (95% confidence interval: 10 to 34), with no increase in adverse events (moderate certainty evidence). We found no RCTs comparing dapivirine to oral PrEP or among adolescent/pregnant/breastfeeding clients. Dapivirine is less cost-effective than oral PrEP at $14.59/ring, at the current price. The source guideline recommendation was adapted for the local context. Dapivirine ring seems to be less efficacious than oral PrEP, although comparative studies are lacking. Data on adolescents and pregnancy are also lacking, currently limiting the use of dapivirine as an alternative for women unable to take oral PrEP. At the current price, dapivirine is not cost-effective and unaffordable for inclusion in the South African Essential Medicines List.

Synthesis, Properties, and Techno-economic Analysis of Highly Stable Biotransformer Oil Derived from Transesterification of Palm Oil Methyl Esters and Ditrimethylolpropane.

Currently, biotransformer oil (BTO) is in high demand due to the increasing level of electrical power consumption and environmental policy. Hence, this research aimed to prepare a highly stable BTO via basic transesterification of palm oil methyl ester (POME) and ditrimethylolpropane (Di-TMP) catalyzed by sodium methoxide (NaOCH3). Under the optimal conditions (POME/Di-TMP molar ratio = 5.0/1.0, NaOCH3 loading = 8 mol % based on the Di-TMP content under 3.5 mbar, and 300 rpm at 160 °C for 2 h), the POME conversion level and POME-Di-TMPTTE selectivity reached 90.3% and 96.6%, respectively. The obtained BTO with a high POME-Di-TMPTTE portion exhibited greater oxidation stability with a higher flash point and breakdown voltage in accordance with the IEC 62770 specification. A techno-economic analysis revealed the possibility of POME-Di-TMPTTE as a commercial BTO for its competitive cost and profit based on the current commercial price of BTO.

Dynamic input–output balance as a tool for structural policy analysis

This article extends the array of tools available for the analysis and advancement of structural policies using dynamic inter-sectoral balance, expressed in the form of a system of ordinary differential equations. This development became achievable following the publication of the authors’ methods for digitizing and calibrating such a structural model, thereby transforming it from a set of “purely theoretical constructs” into a set of computational and pragmatically valuable models. Formally, the digitization process for the model involves the introduction and computation of the eigen (intra-industry) and mutual (inter-industry) inertia matrices, the elements of which are time-dependent. These matrices substitute the conventional incremental capital intensity matrix within the model. It is worth noting that, unlike other scientific summaries, the matrix of incremental capital intensity is nowhere to be found in global statistics. No statistical institute worldwide develops or publishes it for any economy. The second factor that enhances the practical utility of the model lies in the utilization of the matrix of financial flow coefficients for its calibration. The computations conducted and presented here lead to the conclusion that the model is proficient in providing robust forecasts of gross output in current and comparable prices within the timeframe covered by Rosstat’s basic “input–output” tables. In its current format, the model holds potential as a valuable tool for scrutinizing structural changes within the domestic economy and for comparing Russia’s economic trends with those of other developed and developing nations. Digitizing it for use at the regional level would enable similar analyses on a mesolevel scale.

Macroeconomic perceptions, financial constraints, and anomalies

This paper studies the heterogeneous effects of subjective macroeconomic expectations on the cross-section of equity returns. We argue that an upward revision in expectations of macroeconomic productivity might be accompanied by an excessive increase in investment and external financing, inflated current equity prices, and thus lowered subsequent returns, particularly for financially constrained firms. Thus, following upward revisions in expectations of macroeconomic productivity, subsequent returns are relatively low for small firms, value firms, low-investment firms, risky firms, unprofitable firms, low-quality firms, and financially distressed firms—all of which are more financially constrained. In sharp contrast, following downward revisions in expectations of macroeconomic productivity, these categories of firms earn relatively high subsequent returns. We find that revisions in subjective macroeconomic expectations induce strong predictable time variation in a large set of anomalies. In particular, favorable revisions in expectations of macroeconomic productivity predict significantly stronger profitability, quality, distress, and low-risk anomalies but weaker value, investment, and size anomalies.

Negotiating pricing and payment terms for insurance covered mHealth apps: a qualitative content analysis and taxonomy development based on a German experience

BackgroundGermany was the first country worldwide to offer mobile digital health applications (mHealth apps, “DiGA”) on prescription with full cost coverage by statutory health insurances. Especially statutory health insurances criticize the current pricing and payment regulations in Germany due to “free and non-transparent” pricing in the first year and lack of cost use evidence. The study consists of two parts: The first part evaluates interests of digital health application providers and statutory health insurances in Germany to identify overlaps and divergences of interests. The second part includes the development of a comprehensive pricing and payment taxonomy for reimbursable mHealth apps in general.MethodsBoth parts of the study used the input from 16 expert interviews with representatives of digital health application providers and statutory health insurances in Germany. In part one the authors conducted a qualitative content analysis and in part two they followed the taxonomy development process according to Nickerson et al. (2013).ResultsA value based care model is expected to bring the greatest benefit for patients while statutory health insurances welcome the idea of usage based pricing. The final pricing and payment taxonomy consists of four design and negotiation steps (price finding, payment prerequisites, payment modalities, composition of negotiation board).ConclusionsAs healthcare resources are scarce and thus need to be optimally allocated, it is important to implement pricing and payment terms for reimbursable mHealth apps that result in the greatest benefit for patients. To the best of the authors’ knowledge, there has been no structured study yet that examines alternative pricing strategies for reimbursable mHealth apps.The developed pricing and payment taxonomy for reimbursable mHealth apps serves as planning and decision basis for developers, health policy makers and payers internationally.

Calculating carbon: The value of information in precision for blue carbon restoration projects

Coastal wetland restoration projects can receive payments for ecosystem services but often occur in regions with limited data, and additional data collection can be financially prohibitive. Value of Information analysis can quantify the difference between the expected value of an action before and after new information has been collected, aiming to understand how much data is required to make decisions that balance the costs of implementation versus the benefits of the project. The Australian carbon market provides a method that uses reintroduction of tidal flows to restore coastal wetland ecosystems for their carbon sequestration functions. The method requires a hydrological assessment of prospective sites, which is employed to estimate carbon sequestration potential. This research investigates how different amounts of data collection and different levels of complexity in the hydrological assessment influence the carbon abatement emissions estimated using the method. The results indicate that tidal restoration for blue carbon credits on grazing land may not be financially viable. We found that tidal data collected onsite were important for decision-making while complex hydrological models have low value compared to more simplistic approaches. While investing in data collection provides more value than increasing the complexity of modelling approaches, the value of information was still low. Additionally, restoration of coastal wetlands is unlikely to be financially attractive at current carbon prices, and the land would have to be unsuitable for cattle to become profitable for restoration. This work provides a framework for evaluating the financial benefit of collecting on-site data and using robust methods for estimating inundation, that can be used to guide decision-making to achieve optimal income.

An import(ant) price of Brexit uncertainty

We estimate the impact of trade policy uncertainty (TPU) on CES import price indices, focusing on the implications of Britain’s exit from the European Union (Brexit). Our analysis reveals that a higher probability of Brexit increases U.K. import price indices by raising the prices of existing products and reducing product variety from the E.U. We find evidence that the risk of higher import protection from the 2016 referendum increased current import price indices by 11 log points. This amounted to a 2 log point increase in manufactured goods prices and a 0.6 log point decrease in consumers’ real income.

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.

Stakeholder perceptions of issues and possible solutions to access to oncology medicines: a case study of multi-stakeholder engagement

Aim This case study reports on a series of multi-stakeholder dialogues on challenges to access to oncology medicines in both the public and private sectors. Methods Key stakeholders, identified from various points in the pharmaceutical supply chain, were invited to attend a series of virtual discussion sessions to address specific medicines access challenges to the provision of cancer care in South Africa. For each session, a case scenario, based on a real world situation/event was presented for discussion, and viable solutions and areas requiring further research or legislative changes were identified. Topics covered in these discussions included registration pathways and obstacles; limitations of current medicine pricing policies; alternate reimbursement models; funders’ initiatives to ensure access to oncology medicines; and essential medicine selection and procurement in the public sector. Findings The key issues raised in the discussions included: non-transparency in the approval and pricing of unregistered medicines accessed in terms of section 21 of the Medicines and Related Substances Act of 1965 (as amended); commercial decisions related to the small market for oncology medicines in South Africa; inequities between public and private sector access; alternate forms of price negotiation in the private sector; the restrictions imposed by the single exit price model; and the role of co-payments for those medicines not included as prescribed minimum benefits. Conclusions There is a clear need for a forum where all stakeholders and actors in this field can engage in discussions to find solutions to the oncology medicines access conundrum, including the development of legislative amendments.

Multiple pricing for personal assistance services

Third-party payers often reimburse health care providers based on prospectively set prices. Although a key motivation of prospective payment is to contain costs, this paper shows that this aspect crucially depends on the design of the pricing scheme due to the well-known incentives of patient selection (or “dumping”). This paper provides a general theoretical framework where heterogeneous users are served by either private for-profit or public providers, each paid an hourly compensation by a third-party payer. The private, but not the public providers may select patients. It is demonstrated that this realistic feature of the model implies that total costs depends on the number of prices. The features of the model is illustrated using the Swedish system of personal assistance services as a motivating example. Numerical results show that marginal adjustments to the current uniform pricing scheme would lead to substantial savings.

Potensi dan Peluang Akomodasi Alternatif Glamour Camping (Glamping) di Kawasan Destinasi Pariwisata Sembalun Kabupaten Lombok Timur

The aim of the research carried out was to determine the potential and opportunities for the availability of alternative Glamping accommodation in the Sembalun tourism destination area, East Lombok district, as well as to determine the calculation of Location Quotient (LQ), Specialization Index, Shift Share and Net Shift (PB) in analyzing the potential and opportunities for provision. alternative accommodation. The research methodology used in this research is a type of descriptive quantitative research based on the calculation of the Specialization Index, Location Quotient (LQ), and Shift Share. With a rational-comprehensive approach. Types and sources of data in this research, primary and secondary data, with data collection techniques in literature and direct observation or observations. The results of this research show that the specialization index calculation for 17 (seventeen) sectors based on current prices obtained values ​​of 0.31; 0.30 and 0.26. Meanwhile, based on constant prices, the IS value obtained for 3 (three) years was 0 .62; 0.54; 0.46, the value of the specialization index is close to one. For the combined calculation of LQ and Net Shift, it is known that the accommodation, food and drink provision sector have a value of LQ > 1, and PB > 1, which means that the agricultural sector in a broad sense is based on current and constant prices. for 3 years has a stable LQ value which means the potential and opportunities to build and develop accommodation in tourism destinations, are still quite large.

The high price of equity in pulse oximetry: A cost evaluation and need for interim solutions.

Disparities in pulse oximetry accuracy, disproportionately affecting patients of color, have been associated with serious clinical outcomes. Although many have called for pulse oximetry hardware replacement, the cost associated with this replacement is not known. The objective of this study was to estimate the cost of replacing all current pulse oximetry hardware throughout a hospital system via a single-center survey in 2023 at an academic medical center (Duke University) with three hospitals. The main outcome was the cost of total hardware replacement as identified by current day prices for hardware. New and used prices for 3,542/4,136 (85.6%) across three hospitals for pulse oximetry devices were found. The average cost to replace current pulse oximetry hardware is $6,834.61 per bed. Replacement and integration costs are estimated at $14.2-17.4 million for the entire medical system. Extrapolating these costs to 5,564 hospitals in the United States results in an estimated cost of $8.72 billion. "Simply replacing" current pulse oximetry hardware to address disparities may not be simple, cheap, or timely. Solutions for addressing pulse oximetry accuracy disparities leveraging current technology may be necessary, and might also be better. Trial Registration: Pro00113724, exempt.

Seeking sustainable efficient global agricultural production with nexus approach

This study aims to estimate the shadow prices of water and carbon dioxide (CO2) in global agriculture under three scenarios: pursuing economic efficiency, sustainable development goals (SDGs), and environmental protection. It assesses the social cost of environmental impacts compared to actual prices. This study also evaluates substitutability among water, labor, and capital in the three scenarios for developing relevant agricultural policies depending on distinct agricultural conditions. Social costs tend to be underestimated because they are not directly observed. Our society has faced an overproduction of agriculture in terms of CO2 emissions and the exploitation of water. This study employs a method of a directional technology distance function for global agricultural production based on Food and Agriculture Organization data on agricultural inputs and outputs. The following three critical findings were obtained: First, the average shadow price of water under the economic scenario was close to the current actual water prices, and water prices would increase if agricultural production accomplished the three SDGs (Goal 2, 6, and 13). Second, labor is substituted for water under the environmental scenario because water prices increase rapidly. In contrast, water is complementary to labor under the SDGs scenario, implying that labor becomes more important for increasing food production. Third, the current CO2 prices are lower than those in the economic scenario. These values are significantly lower than those under the SDGs and environmental scenarios. Based on these results, we conclude that agricultural products are often undervalued because the appropriate value of water is overlooked in real markets. The contribution to reducing CO2 in agriculture is insufficient, owing to current low carbon taxes.

Design and analysis of negative CO2 emission methanol synthesis process incorporating green hydrogen and blue hydrogen

Methanol (MeOH) production by integration of green and blue hydrogen is evaluated herein. From 2018 to 2023, methanol demand increased by 3.6 % due to its use in various chemical industries as an eco-friendly fuel and as a method of transporting hydrogen and capturing renewable CO2. Moreover, due to the continual decrease in the cost of renewable energy, research into the use of green hydrogen from electrolysis is being conducted. Most of this research has focused on producing methanol from the green hydrogen obtained from proton-exchange membrane (PEM) electrolysis along with CO2 emissions from power plants. The present study examines processes based on oxyfuel combustion with oxygen obtained from either the PEM or an air separation unit (ASU) to produce methanol. By using oxyfuel combustion, the carbon capture process (which accounts for 30–50 % of the blue hydrogen cost) and pure (>98.75 %) 7.45 tCO2/tH2 can be obtained by separating H2O from the flue gas. By using the PEM, green hydrogen can capture 0.35 tCO2/tMeOH of external CO2. Furthermore, a carbon techno-economic analysis (CTEA) and a sensitivity analysis are conducted to evaluate the sustainability and feasibility of the proposed processes. As a result, the levelized cost of methanol (LCOM) is $373.91/tMeOH for the Blue process and $428.78/tMeOH for the Blue + Green process, each of which is below the current market price of $500/tMeOH. If the PEM price continues to decrease, and the carbon credit increases by €300/tCO2, after 2030, the Blue + Green process will become more lucrative than the Blue-only process. Thus, by considering the continuous decrease in renewable energy prices, the production of methanol via a hybrid Blue + Green process is suitable for a sustainable future.

A cost-minimization analysis of anti-VEGFs for the treatment of neovascular age-related macular degeneration in the Netherlands.

Age-related macular degeneration (AMD) is the main cause of severe vision loss globally. Neovascular AMD (nAMD) is an advanced stage of AMD treated with anti-vascular endothelial growth factors (anti-VEGFs). Although anti-VEGF treatment is effective, the frequent intravitreal injections place a burden on patients, (in)formal caregivers, and clinics. This study assesses the health-economic impact of anti-VEGF agents with lower injection frequency that have the potential to reduce treatment burden and compares it to the standard of care. We developed a cost-minimization model to evaluate the direct medical costs associated with first-line unilateral anti-VEGF treatment across a 3-year time horizon in the Netherlands. The analysis compared aflibercept 8mg, aflibercept 2mg, bevacizumab, faricimab, and ranibizumab. Our model adopted a treat-and-extend (T&E) regimen for aflibercept 2mg, bevacizumab, and ranibizumab. For aflibercept 8mg, a flexible regimen that was extendable up to 24weeks was applied, while faricimab followed a flexible regimen that was extendable up to 16weeks. Additionally, since list prices may vary from net prices, we calculated the break-even price for each anti-VEGF in comparison to bevacizumab, which is the recommended first-line treatment due to its low medication price. Based on list prices, aflibercept 8mg led to the lowest treatment costs (€16,251 per patient over a 3-year time horizon), closely followed by bevacizumab (€17,616 per patient over a 3-year time horizon). Ranibizumab led to the highest per-patient costs (€31,746 over a 3-year time horizon). For bevacizumab, most costs were attributable to administration, while for the other anti-VEGFs, most were attributable to medication. Aflibercept 8mg is cost-saving compared to bevacizumab at their medication prices at the time of writing. Aflibercept 2mg, faricimab, and ranibizumab should be priced below €488, €591, and €75, respectively. To be cost-equal to bevacizumab with current list prices, anti-VEGFs should be administered with a maximum of 12.7 to 13.8 injections over a 3-year time horizon. According to the injection frequency observed in clinical trials, aflibercept 8mg would be the anti-VEGF that generates the lowest per-patient healthcare costs for the treatment of nAMD in the Netherlands after a treatment period of three years. Our study indicates that anti-VEGF drugs with a lower injection frequency might provide a cost-saving solution to the increasing burden of anti-VEGF treatment on the healthcare system.

Study to determine medical imaging devices costs of maintenance and repair: case of a university hospital in turkey

Abstract Objectives: Unperformed maintenance and repairs cause medical devices to become idle or unusable before their useful life. In this study, it was aimed to determine a standard for maintenance and spare parts expenditures of medical imaging devices. Methods: In the study conducted on nearly 30 medical imaging devices of a university hospital, firstly, the economic life of the devices was determined depending on the intensity of use. It was determined that the expenditures changed in the first five years, the second five years and after the economic life. Expenditures were categorized according to the period and technological level. Results: According to the results obtained, the annual expenditure of medium technology devices varies between 2% and 7% of the current price. For high-tech devices, expenditures vary between 4% and 13%. In the study, the required expenditure rates for the devices according to the technology level were also predicted. Conclusions: It has been determined that the maintenance and repair practices of imaging devices in health institutions in Turkey are inadequate. Managers should closely monitor the inventory of medical imaging devices for effective use, quality service delivery and employee health.

Carbon market design and market sentiment

Concerns about systematic price distortions in the EU Emission Trading System (ETS) have risen in recent years. This paper shows how carbon-market design affects the impact of market sentiment, i.e. systematic deviations of price expectations from fundamentals by at least some market participants, on equilibrium prices. The Market Stability Reserve (MSR) of the EU ETS that adjusts supply based on past allowance banking undermines self-stabilization of the carbon market by discouraging rational intertemporal arbitrage. The MSR increases vulnerability of the EU ETS to market sentiments. Initially, the allowance price responds more to distorted expectations while the MSR (partially) prevents the distortion to spread across periods. Making the MSR more responsive to banking decisions increases the likelihood that distorted expectations turn out to be correct ex post. In contrast, a mechanism that adjust the cap based on the current allowance price does not face a trade off between stabilizing prices in the present and the future.

NGHIÊN CỨU THIẾT KẾ, CHẾ TẠO THIẾT BỊ THEO DÕI TRUYỀN DỊCH TĨNH MẠCH ỨNG DỤNG CÔNG NGHỆ MẠNG KẾT NỐI VẠN VẬT

This paper focuses on the research and development of a medical device designed to monitor and supervise intravenous infusion for patients by leveraging Internet of Things (IoT) technologies. The proposed device is expected to have the following fundamental functionalities: setting the volume of the solution to be infused; setting the drip rate in drops per minute; calculating and displaying the remaining volume of the solution; calculating and displaying the remaining infusion time; and Alerting doctors and patients at different time intervals. The advantages of the designed product include low system design cost based on the current price of components; simple and comprehensible programming language with high scalability; experimental results indicating stable and accurate system operation with low power consumption; and ease of operation, use, maintenance, and servicing. Furthermore, the research results have practical applicability in hospitals or medical facilities and can be used as a practice model for Biomedical Engineering students at educational institutions, where there is a significant lack of practical training products in this field. Keywords: Intravenous infusion; medical devices; monitoring; control; Internet of Things.

Economic validation and comparison of microbial tryptophan, erythritol and collagen production in an integrated sugarcane biorefinery

Low sugar prices present a significant challenge to the global sugarcane industry, prompting the exploration of diversification strategies for expanding product portfolios. Techno-economic analyses and environmental sustainability assessments were carried out to evaluate the microbial production of tryptophan, erythritol, and collagen from A-molasses in a biorefinery annexed to an existing sugarcane mill. Tryptophan production exhibited the highest profitability, with a minimum selling price (MSP) at 59.7 % of its current market price, although the achievable production volumes of tryptophan from one sugar mill would oversupply the global market. Due to the larger market size of for collagen the achievable production capacity in the collagen scenario would avoid market saturation, reducing the risk of oversupply and rendering it more economically viable. In contrast, erythritol production was marginally not profitable, with an MSP exceeding the current market price by 1 %, primarily attributed to high operational costs. All scenarios demonstrated relatively low greenhouse gas (GHG) emissions (ranging from 9.1 to 16.5 kg CO2eq/kg product), with tryptophan production emerging as the most environmentally favourable option due to minimal chemical and freshwater usage. When compared with literature-reported data on ethanol and short-chain fructooligosaccharides (scFOS), only collagen and ethanol production were deemed viable, based on their favourable profitability and contribution to the market.