Price Scenarios Research Articles

Determination of the economically justifiable price of cenobamate in the treatment of focal-onset seizures in adult patients with drug-resistant epilepsy in Spain

Objective To determine the economically justifiable price (EJP) of cenobamate to become a cost-effective alternative compared with third-generation anti-seizure medications in the treatment of focal-onset seizures (FOS) in adult patients with drug-resistant epilepsy (DRE) in Spain. Methods Cost-effectiveness analysis comparing cenobamate with brivaracetam, perampanel, eslicarbazepine acetate and lacosamide. Markov model simulation of treatment pathway over a 60-year time horizon. Determination of effectiveness and quality-adjusted life-years (QALYs) of each health status, and disutilities associated with treatment-related adverse events. Acquisition costs and use of medical resources were obtained from published literature and expert opinion. Base-case of cenobamate’s EJP calculated applying a willingness-to-pay (WTP) threshold of €21,000/QALY. Analyses performed at different thresholds, including dominant price scenario. Results robustness were assessed through sensitivity analyses. Results Base-case shows that cenobamate’s daily EJP of €7.30 is cost-effective for a threshold of €21,000/QALY. At a daily price of €5.45, cenobamate becomes dominant over all treatment alternatives producing cost-savings for the national health system (NHS). Sensitivity analyses supported the robustness of base-case findings. Conclusions Treatment with cenobamate produces incremental clinical benefit over third generation ASMs and at the base-case EJP could represent a cost-effective option for the adjunctive treatment of FOS in adult patients with DRE in Spain.

Out-of-pocket costs for oral anticancer drugs.

14 Background: Oral anticancer drug annual out-of-pocket costs (OOPCs) for Medicare beneficiaries are frequently > $10,000. Many of these medications are available as multiple formulations (e.g., tablet/capsule) and multiple strengths (e.g., 25mg/50mg). Oral medications are typically priced per unit (pill), allowing for more cost-effective prescribing when patients use fewer pills to obtain a recommended dose. It is unclear whether cancer drugs follow this traditional paradigm. We sought to assess the relationship between drug formulation features and OOPCs. Methods: We included 20 oral anticancer drugs with the highest spending in Medicare Part D in 2020. For each drug, we identified formulations, strengths, and schedules using NCCN guidelines and UptoDate. For each product, we calculated a lowest expected annual drug OOPC for all relevant strengths/schedules using the 2022 Part D Plan Finder. For example, the drug osimertinib is available in 40 and 80 mg tablets, with total daily doses of 80 and 160mg, reflecting 4 pricing scenarios. We assessed costs for 1 year of monthly fills. We compared cost ratios across formulations for each drug. Results: Of the 20 drugs, 17 (85%) were available as brand-name only; 3 (15%) were also available as generic. Fifteen (75%) were available as a single formulation only (e.g., tablet only); 5 (25%) were available as multiple formulations (e.g., tablet and capsule). Eighteen (90%) were available in multiple strengths. Median annual drug OOPCs was $12,979. For brand vs generic comparisons (n = 4, keeping other variables constant, 1 drug could have > 1 comparison due to different strengths), brand coverage for imatinib and 250 mg abiraterone tablets was limited, leading to high cost ratios (brand/generic > 50). For 2 other comparisons, the brand was less costly (abiraterone 500 mg tablets, ratio 0.85) and more costly (everolimus 10 mg tablets, ratio 1.18) for 1 each. For tablet vs capsules/others (n = 4), tablets were cheaper for 2 (ratio, 0.63- 0.96), a little more costly for 1 (ratio 1.04), and a lot more costly for 1 (ratio 2.13, ibrutinib 140 mg). For comparisons across strengths of the same formulation to achieve the same total dose (n = 14), using lower strength/higher fill quantity was more costly for 10 drugs (median ratio 1.79), the same for 1, and less costly for 3 (ratios 0.35- 0.89). Conclusions: Even when considering the least costly Part D plan, 2022 oral anticancer drug OOPCs remain high. Counter to expectations, in some cases generics were more costly than brands, and more pills at a lower dose were less costly than fewer pills. There was no consistent pattern. Oncologists and pharmacists cannot be expected to know the unpredictable OOPC ramifications of biologically equivalent prescription decisions. As cancer primarily affects older adults, often living on fixed incomes, policy-level change to lower OOPCs are necessary to avoid financial ruin and enhance access for Medicare beneficiaries.

Taiwan Passengers’ Willingness to Pay for Air Sleeper Seats

To provide passengers with a better flight experience and make their journey more comfortable, airlines are diversifying their services to attract more customers. One of these services includes the development of a sleeper seat. A sleeper seat, also known as family couch in Taiwan, mainly provides a row of 3–4 economy class seats that allow passengers to lie down. Although Taiwan’s China Airlines originally offered this service, it stopped due to poor sales; however, other international airlines continue to implement similar services. Regarding previous research exploring air service issues, almost no research has focused on sleeper seats. Accordingly, this article focuses on exploring Taiwanese passengers’ willingness to pay (WTP) for the sleeper seat service and the influencing factors. The contingent valuation method (CVM) was used to construct the price scenario of passengers’ WTP. To avoid estimation bias and thus provide more reliable results, the spike model was used to estimate passengers’ WTP for the sleeper seat service and the influencing factors. According to the results, when considering multiple variables, people were willing to increase the price paid to use parent-child cabins by NTD 11,194, which was about 75% of the original price but lower than the preferential price offered by the airlines, indicating a gap between the amount people were willing to pay and the airlines’ pricing. In addition, if passengers were traveling with children or if the passengers had higher flight frequencies and personal incomes, they were willing to purchase the sleeper seat service. However, people who had not experienced the sleeper seat service were unwilling to purchase it. This paper is practical to reflect current aviation industry marketing, and the research results contribute to the existing literature and provide a reference for Taiwan’s civil aviation industry when relaunching the sleeper seat service in the future.

Economic evaluation of production capacity for natural gas hydrate industrial exploitation in the South China Sea

Natural gas hydrate (NGH) is a worldwide strategic and prospecting commercial resource in the 21st century. The industrialization of NGH has great strategic significance for the achievement of peak carbon dioxide emissions and carbon neutrality. Prior to its industrialization, an economic evaluation of production capacity for each well per day should be conducted to determine whether it is profitable at different given gas prices. In this study, a new hybrid method based on the discounted cash flow (DCF) method and the energy return on investment (EROI) method is used to estimate the economic production rate of NGH exploitation at four different gas price scenarios. The results show that the lowest production rate to make NGH exploitation economic ranges from 1.96 to 29.60 × 104 m3/d/well. With the change in the number of wells, gas–water ratio, gas price, decreasing rate in production cost, and sensitivity analysis are carried out. It shows that all these key factors have a significantly negative effect on the economic production rate initially, and then the sensitivity to the economic production rate will become lower and lower with the rising value of each key factor.

A Review of Logistics Pricing Research Based on Game Theory

As the scope and complexity of logistics outsourcing services expand, logistics activity has become a separate market service. It has become a critical issue to determine how to appropriately price logistics services. In this study, we systematically review the scientific literature on the pricing of logistics services based on content analysis and bibliometric methods, focusing on the application of game theory. We compare and analyze the literature in terms of three dimensions: logistics scenarios, game models, and influencing factors. This study identifies the main players and key research scenarios of logistics pricing, analyzes6aa the most appropriate and commonly used game models, and clarifies the main influencing factors of logistics pricing. Finally, we suggest future research directions to fill gaps in existing knowledge. This study conducts a systematic review of the current state of empirical research in the field of logistics pricing, which aids in the development of new models. The results of this study help to advance logistics services from a pricing standpoint, thereby increasing the economic and environmental sustainability of logistics activities.

Stormwater Utility Fee Estimation Method for Individual Land Use Areas

In South Korea, a reasonable rate system that can be domestically applied to calculate sewage and stormwater separately from the domestic sewage fee system is needed. This study proposed a phased pricing scenario to separate sewage and stormwater in Bupyeong-gu, Incheon, and the rate changes were compared based on a simulated calculation of the stormwater utility fee. In this investigation, stormwater runoff cases from other countries and the current domestic system were analyzed. A stormwater utility fee introduction scenario was presented that considers the impervious surface area. Water and sewage usage statistics and hydrant spatial data were collected from the Incheon Metropolitan City Waterworks Authority, and the total amount of water and sewage fees from the land use area were calculated. The stormwater utility fee was calculated, and the rates of each step were compared. The total sewage fee of Bupyeong-gu during 2014 was KRW 21,685,446,578, and the phased stormwater utility fee was calculated, assuming that 40% represents the stormwater cost. The sewage fee for the residential area in phase 3 decreased by 0.77% compared to phase 1. For the commercial areas, the sewage fee decreased by 36.87%. Because the impervious surface ratio was high, the overall area contributing to the impervious surface area was small. In the industrial area, the sewage fee increased by 8.35%. In the green area, the sewage fee increased by 37.46%. The sewage fee for the apartment complexes decreased by 10.6%. Finally, the possibility of estimating the actual stormwater utility fee was confirmed.

A percentage-off discount versus free surcharge: The impact of promotion type on hotel consumers’ responses

Despite surcharges' recent popularity in the tourism and hospitality industry, academics and practitioners have yet to fully explore relevant promotional strategies. To better understand the implications of promotion types, this research considered how a “free resort fee” promotion differed from the more common percentage-off discount in influencing hotel consumers' responses depending on the pricing scenario (i.e., a high vs. low resort fee). Two experiments revealed that consumers' perceived attractiveness of the promotions did not differ; however, a percentage-off discount generally led to stronger booking intentions than a free resort fee. Comparatively, when the resort fee was high, the promotion exempting resort fees resulted in greater attractiveness and booking intention than a percentage-off discount. Experiments also revealed the mechanism underlying consumers’ affective reactions. This research contributes to the pricing literature and provides hospitality managers and marketers insight into ways to encourage positive consumer responses based on promotion types and situational factors.

Transition towards university campus carbon neutrality by connecting to city district heating network

The campus of Tallinn University of Technology consists of 26 buildings with a total annual heat demand of approximately 20 GWh. A local natural gas-fired boiler provides annually approximately 13 GWh of heating to 12 buildings in the campus and 14 buildings are connected to district heating system. This paper analyses the possibilities of replacing the natural gas boiler with district heating. Two systems were modelled using EnergyPRO software and compared to the reference system of the local boiler and heating network: connection to an existing high-temperature district heating network and a low-temperature energy cascade. All the three systems were modelled with two different energy price scenarios. The results were analysed from the perspective of the university campus and the entire city’s system. The low-temperature energy cascade connection to the city’s network will reduce carbon dioxide emissions by 955 tonnes CO2. The conventional high-temperature connection would reduce the emission by 765 tons CO2. District heating connection will also lead to primary energy savings supporting the university’s efforts towards achieving its sustainable development goals. The low-temperature energy cascade utilising the return water of the city’s district heating network reduces the heat losses and increases the efficiency of heat and electricity production when compared to the systems with separate campus heating or the conventional high-temperature district heating.

Reference price effect of partially similar online products in the consideration stage

Reference price is an important basis for online retailers to formulate pricing strategies. Existing studies on the reference price effect primarily use completely similar products for price comparison analysis, while using partially similar products is difficult to study the reference price effect due to weak comparability. Therefore, based on spatial econometrics and text mining, this study designs a research framework to analyze the reference price effect of partially similar online products. We explore three reference price scenarios for partially similar online products in the consideration stage of online shopping, namely: the reference price effects of retail price and unit size price, and the influence of brand on the reference price effect. This study extends the research on the reference price effect under these three scenarios from completely similar online products to partially similar online products, which provides novel insights into the reference price effect of partially similar online products.

Evaluation of Multiple Forest Service Based on the Integration of Stand Structural Attributes in Mixed Oak Forests

In order to understand forest services at stand level through the integration of structural attributes, forest structures in three main stand types were analyzed based on various structural attributes relating to the services of habitat conservation, timber production and soil water conservation in Loess Plateau, China. Forty sample plots with similar site and environment conditions were established in three types of oak stands. Twenty-two indexes such as stand density, mean DBH, mean height, etc., were selected to analyze the relationship between structural attributes and forest service. With a core set of structural attributes selected by principal component analysis, the link between the service and structural attributes and the compatibility between each service was analyzed using correlation analysis. The results show that the oak–broadleaf mixed forest has the highest structural complexity index (SCI), indicating the best habitat conservation among others, while the oak–pine mixed forest and pure oak forest have the highest timber value in different scenarios of timber price, indicating the largest potential for timber production. Little differences were found between stand types regarding the indicators for soil water conservation. The structural attributes that had a positive correlation with habitat conservation (e.g., number of shrub species, species richness of canopy layer, the proportion of broadleaves and snag density) were identified to be negative for timber production; while the attributes that had a positive correlation with timber production (e.g., stand density and proportion of pine and oaks) were found to be negative for habitat conservation. The results of the trade-off analysis showed that timber production tends to be conflicting with the other two non-timber forest services. In order to enhance the provisioning of multiple services, it was suggested to implement the interventions that could balance these services, such as structural retention and single-tree selective logging. This study could contribute to the theoretical base for the decision making in the multi-purpose sustainable management of oak forests in China.

Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector

China is pursuing aggressive action to reduce greenhouse gas emissions from its coal-dominated electric power system. Two key strategies are power market reform and carbon pricing. This paper investigates the combined effects of these two strategies in reducing CO2 emissions from power system operations. We develop an economic dispatch model to simulate hourly power supply system operation in China Southern Power Grid in 2018 under fifteen carbon pricing scenarios; these reflect a wide range of policy ambition, from today's carbon prices to much higher ones that aim to instigate aggressive emission mitigation. Our results show that moderate carbon pricing alone is insufficient to effectively reduce CO2 emissions without concurrent power market reform. With power market reform and as carbon prices increase, large coal units supplemented by energy storage witness higher use rates as they supplant smaller coal-fired generators, until a carbon price of 300 RMB/TCO2 phases out coal use in favor of natural gas. Only at carbon prices higher than 300 RMB/TCO2 do emissions begin to decrease appreciably. Geographic disparities emerge among the five provinces that comprise the Southern Power Grid, with Guangdong witnessing the most CO2 emission reduction at high carbon prices, while emission reductions in other provinces are negligible. Carbon pricing also dramatically increases total power system costs, even at low carbon prices. Our results show the necessity of introducing power market reform and carbon pricing policies concurrently if the goal is to reduce CO2 emissions, with the ultimate goal being a carbon price significantly greater than 300 RMB/TCO2. Because both options will be necessary, our research maps a path to deep emission reductions in China Southern Power Grid for investors, analysts, and policy makers as discussions regarding both reforms accelerate.

Impacts of Harvesting Age and Pricing Schemes on Economic Sustainability of Cassava Farmers in Thailand under Market Uncertainty

This paper involves an analysis to determine appropriate cassava harvest practices and choose a pricing scheme between farmers and factories, cassava yards, and collectors in Thailand. Harvest practices represent all activities from land preparation to harvest. A key decision that governs the amount of resources required during cassava life cycle is the cassava’s harvesting age. The harvesting age can be from eight to 18 months in two patterns: fixed age, e.g., harvest every 12 months, and variable age, e.g., harvest at an age between 10 and 14 months. After harvesting, there are two common pricing schemes to consider, which are weight-based and starch-content-based. Factors that affect the two decisions made by Thai farmers at a given time are the market price, which highly varies within a season and between seasons, and yields in terms of weight and starch content, both of which change with cassava’s age and/or harvest month. Economic sustainability measure for Thai farmers is the average monthly profit that the farmers gain over cassava harvest cycle under uncertain market price. To handle uncertainties, a simulation model is constructed to imitate cassava planting activities from cultivation to harvest. The purpose is to evaluate various harvesting ages and two pricing schemes under uncertain cassava market prices. Market prices in 15 seasons (2006–2021) are grouped using the k-mean clustering into four price scenarios. As cassava grows in the simulation, the required resources are consumed until the decisions on harvesting time and pricing scheme are made with estimated selling probability under different price scenarios and uncertainty in cassava yield. Through simulation, harvesting age and pricing scheme that are most profitable and robust-to-system-variation are determined. Finally, a guideline for Thai farmers to choose a pricing scheme is developed based on the sensitivity analysis of the simulation model.

How do college students perceive future shared mobility with autonomous Vehicles? A survey of the University of Alabama students

University students are young, open to new technologies, and their perceptions of the Shared Autonomous Vehicles (SAVs) may indicate their travel behaviors in the future. College towns in small urban or suburban areas offer researchers a unique environment to understand the travel behaviors of future commuters, and test emerging mobility services, such as SAVs. The study performs a survey with the aim of understanding university student perception regarding SAVs. The survey was conducted among the University of Alabama students in Tuscaloosa. The key survey questions include their knowledge and attitudes about AV and shared mobility. The results showed 97% of respondents are aware of AVs, but only 41% know specific automation technologies. As for shared mobility services, 98% of respondents are familiar with Uber and Lyft services. The survey also asked survey participants to indicate their Willingness-To-Pay (WTP) for hypothetical SAV services in three price scenarios. The prices were assumed as relative to the cost of using ride-hailing services with human drivers such as Uber and Lyft. Random parameter ordered logit models were developed to uncover the correlates of the WTP for SAV services. The models identified significant relationships between the WTP and various factors related to respondents’ socio-demographics, awareness of AV companies, and experiences with human-driver ride-hailing services. The awareness of AV companies and ride-hailing services is positively related to the WTP for SAV services. Students who know more AV companies appear to have a greater WTP, and students who are heavy users of Uber or Lyft services are also likely to SAV users in the future. Significant variations were also found in model estimates, indicating that some relationships could vary significantly across observations due to the unobserved heterogeneity. The findings offer insights to decision-makers and investors trying to estimate the market potential of emerging mobility services with AVs.

Field validation of a farmer supplied data approach to close soybean yield gaps in the US North Central region

CONTEXTProducer-reported data can be used to identify suites of management practices that lead to higher yield and profit. However, a rigorous field validation of the approach in relation to its potential impact on farmer yield and profit is lacking. OBJECTIVEThis study aimed to validate a producer-data approach on its capability to guide on-farm evaluation of management practices with greatest potential for increasing producer yield and profit. We show proof of concept using soybean in the North Central US region as a case study. METHODSWe used a combination of regression tree analysis and a spatial framework to determine practices with highest influence on yield for specific climate domains across the region. These practices were used as a basis for designing an ‘improved’ management package for each domain. The impact associated with adoption of the ‘improved’ management package on producer yield, seed constituents, and profit was evaluated against a ‘reference’ treatment that follows farmer management via replicated on-farm trials across 100 sites over two crop seasons. RESULTS AND CONCLUSIONSAverage yield was 278 kg ha−1 higher in the improved versus reference management, equivalent to a closure of the current exploitable yield gap by 40%. In turn, adoption of the improved management led to an average increase of $76 ha−1 in net profit. Sensitivity analysis showed that adoption of the improved management packages should increase farmer profit across a wide range of grain price scenarios, with very small downside risk. Seed protein concentration was negatively associated with the positive yield advantage of the improved management, whereas seed oil concentration tended to increase. SIGNIFICANCEAnalysis of producer data can accelerate discovery, evaluation, and adoption of suites of management practices that consistently lead to higher farmer yield and profit, which, in turn, would help speed up current rates of yield gain.

Crop Sequencing to Improve Productivity and Profitability in Irrigated Double Cropping Using Agricultural System Simulation Modelling

Land and water are two major inputs for crop production. Simulation modelling was used to determine crop sequences that maximise farm return. Crop yield was determined for different irrigation scheduling scenarios based on the fraction of available soil water (FASW). Farm returns ($ ML−1 and $ ha−1) were evaluated for seven crop sequences. Three irrigation water price scenarios (dry, median, wet) were considered. The yield of summer crops increased with irrigation. For winter crops, despite increase in irrigation, the yield would not increase. The optimum irrigation (ML ha−1) was: soybean 8.2, maize 10.4, wheat 2.5, barley 3.1, fababean 2.5, and canola 2.7. The water productivity curve of summer crops has a parabolic shape, increasing with FASW, reaching a maximum value at FASW 0.4–0.6, and then decreasing. The water productivity of winter crops decreases as FASW increases following a power function. Gross margins are positive when water is cheap ($60 ML−1) and when water has a median price ($124 ML−1). When water is expensive ($440 ML−1), positive gross margin would be obtained only for the continuous wheat scenario. Deficit irrigation of summer crops leads to significant yield loss. Supplemental irrigation of winter crops results in the highest gross margin per unit of water.

Risk Modelling Approaches for Student-like Models with Fractal Activity Time

The paper focuses on value at risk (V@R) measuring for Student-like models of markets with fractal activity time (FAT). The fractal activity time models were introduced by Heyde to try to encompass the empirically found characteristics of real data and elaborated on for Variance Gamma, normal inverse Gaussian and skewed Student distributions. But problem of evaluating an value at risk for this model was not researched. It is worth to mention that if we use normal or symmetric Student`s models than V@R can be computed using standard statistical packages. For calculating V@R for Student-like models we need Monte Carlo method and the iterative scheme for simulating N scenarios of stock prices. We model stock prices as a diffusion processes with the fractal activity time and for modeling increments of fractal activity time we use another diffusion process, which has a given marginal inverse gamma distribution.
 The aim of the paper is to perform and compare V@R Monte Carlo approach and Markowitz approach for Student-like models in terms of portfolio risk. For this purpose we propose procedure of calculating V@R for two types of investor portfolios. The first one is uniform portfolio, where d assets are equally distributed. The second is optimal Markowitz portfolio, for which variance of return is the smallest out of all other portfolios with the same mean return.
 The programmed model which was built using R-statistics can be used as to the simulations for any asset and for construct optimal portfolios for any given amount of assets and then can be used for understanding how this optimal portfolio behaves compared to other portfolios for Student-like models of markets with fractal activity time.
 Also we present numerical results for evaluating V@R for both types of investor portfolio. We show that optimal Markovitz portfolio demonstrates in the most of cases the smallest possible Value at Risk comparing with other portfolios. Thus, for making investor decisions under uncertainty we recommend to apply portfolio optimization and value at risk approach jointly.

Deep reinforcement learning-based operation of fast charging stations coupled with energy storage system

Fast charging stations (FCSs) can reduce the charging time of electric vehicles (EVs) and thus can help in the widespread adoption of EVs. However, FCSs may result in the power system overload. Therefore, the deployment of the battery energy storage system (BESS) in FCSs is considered as a potential solution to avoid system overload. However, the optimal operation of FCSs equipped with BESS is challenging due to the involvement of several uncertainties, such as EV arrival/departure times and electricity prices. Therefore, in this study, a deep reinforcement learning-based method is proposed to operate FCSs with BESS under these uncertainties. The state-of-the-art soft actor-critic method (SAC) is adopted and the model is trained with one-year data to cover seasonality and different types of days (working days and holidays). The performance of SAC is compared with two other deep reinforcement learning methods, i.e., deep deterministic policy gradient and twin delayed deep deterministic policy gradient. A comprehensive reward function is devised to train the model offline, which can then be used for the real-time operation of FCS with BESS under different uncertainties. The trained model has successfully reduced the peak load of the FCS during both weekdays and holidays by optimizing the operation of the BESS. In addition, the robustness of the proposed model against different EV arrival scenarios and extreme market price scenarios is also evaluated. Simulation results have shown that the proposed model can reduce the peak load of the FCS under diverse conditions in the desired fashion.

Thailand’s mid-century greenhouse gas emission pathways to achieve the 2 degrees Celsius target

BackgroundThe Paris Agreement aims at minimizing threats of climate change by keeping global temperature rise well below 2 degrees Celsius above the pre-industrial level and to pursue efforts to limit the rise to 1.5 degrees Celsius. The Representative Concentration Pathways (RCPs) are developed to investigate GHG emission pathways. RCP2.6 focuses on limiting the global temperature rise to less than 2 degrees Celsius. This paper assesses the impacts of carbon price and CCS on energy and GHG emissions in Thailand. The no carbon price (T0) and the carbon price pathways are compared. In addition, the net-zero emissions and year are discussed.ResultsThe decarbonized energy system with low-carbon power generation and increased electricity usage in the final energy consumption is the main pillar of GHG mitigation. Imposing carbon prices; increasing solar, wind, and biomass electricity generation; energy efficiency improvements in power generation; and energy savings in the industry and the building sectors, will be the key options for clean power generation in the carbon prices (CT) scenarios. Renewable electricity, coal and natural gas, coupled with CCS and bio-energy with CCS (BECCS) will be utilized significantly to curb GHG emissions. The increase of renewable energy and the electrification of end-use plays a key role in reducing GHG emissions. Fuel switching from diesel to biodiesel, energy efficiency improvement and electric pick-ups and trucks will help reducing GHG emissions in the transport sector.ConclusionsThere are three major policy implications to meet Thailand’s 2 degrees Celsius target. First, carbon prices will be the mechanism to accelerate the transformation in the energy sector. Wind and solar electricity will be key pillars of clean electricity in 2050. Policy-makers should update the renewable electricity plans to meet Thailand’s 2 degrees Celsius target in 2050. Second, coal- and gas-fired plants, and BECCS will become important options in reducing CO2 emissions. The policy-makers should investigate the application of CCS in the power sector and the storage location. Third, a major transformation in the transport sector is critically needed. Liquid biofuel and electrification in pick-ups, sedans, and trucks will help reduce GHG emissions.

Modeling and forecasting United States oil production along with the social cost of carbon: conventional and unconventional oil

PurposeThe USA is one of the largest oil producers in the world. For this purpose, the authors model and predict the US conventional and unconventional oil production during the period 2000–2030.Design/methodology/approachIn this research, the system dynamics (SD) model has been used. In this model, economic, technical, geopolitical, learning-by-doing and environmental (social costs of carbon) issues are considered.FindingsThe results of the simulation, after successfully passing the validation test, show that the US unconventional oil production rate under the optimistic scenario (high oil prices) in 2030 is about 12.62 million barrels/day (mb/day), under the medium oil price scenario is about 11.4 mb/day and under the pessimistic scenario (low oil price) is about 10.18 mb/day. The results of US conventional oil production forecasting under these three scenarios (high, medium and low oil prices) show oil production of 4.62, 4.26 and 3.91 mb/day, respectively.Originality/valueThe contribution of this study is important in several respects: First, by modeling SD that technical, economic, proven reserves and technology factors are considered, this paper models US conventional and unconventional oil production separately. In this modeling, nonlinear relationships and feedback loops are presented to better understand the relationships between variables. Second, given the importance of environmental issues, the modeling of social costs of CO2 emissions per barrel of oil is also presented and considered as a part of oil production costs. Third, conventional and unconventional US oil production by 2030 is forecast separately, the results of this study could help policymakers to develop unconventional oil and plan for energy self-sufficiency.

Diversified crop rotations increase the yield and economic efficiency of grain production systems

Crop rotations with high plant diversity and biomass input have been recognized worldwide as a crucial practice for increasing the sustainability of grain production systems, particularly in regions under no-tillage (NT) management. Nonetheless, low-diversity grain production systems based on double cropping (two crops in the same agricultural year) repeated over time, including soybean followed by maize (known in Brazil as “second crop maize”) or wheat, remain prevalent in Brazil. The continuous use of these systems can impair soil yield capacity, farmers’ profits, and environmental sustainability. Therefore, this study aimed to verify the grain yield and profitability of different production systems with different levels of plant diversity. This study was based on results obtained during the 2009–2017 cropping seasons through a long-term field trial conducted under NT since 1985 in southern Brazil. The trial covered two 4-year agricultural cycles with two crops per year, resulting in eight crops per cycle and 16 crops over the entire period. The experiment followed a randomized complete block design, with five treatments and four replicates. The treatments involved three diversified crop rotations, comprising different cover crops and two double-crop systems (wheat-soybean and maize-soybean). For a given agricultural year, wheat and cover crops (white oats, black oats, and forage radish) were grown from May to September, and the second crop maize was grown from March to August. Soybean and first crop maize were grown during the summer from October to February. The grain yield, gross revenue, production cost, and cumulative profit were analyzed for each production system. Gross revenue and profit were primarily estimated based on the actual annual average commodity prices received by farmers, and two additional price scenarios (pessimistic and optimistic) were proposed considering the average prices from 2010 to 2017. Regardless of the cropping season, first crop maize and wheat grain yields were higher in diversified crop rotations. The production system only affected the second crop maize yield in 2010/2011, with a higher value obtained in a diversified crop rotation system. The soybean yield in diversified crop rotations was higher than that in double-crop systems. Considering each cash crop separately, soybean produced the highest average profit (US$ 472.50 ha−1), followed by the first crop maize (US$ 245.31 ha−1) and wheat (US$ 77.71 ha−1), whereas the second crop maize led to economic losses (−US$ 121.73 ha−1). All diversified crop rotations produced a higher 8-year cumulative profit and gross margin than the maize–soybean in double-crop system. The relative economic performance of production systems remained unchanged under alternative price scenarios (pessimistic and optimistic) compared with that under the observed (actual) price scenario. However, the cumulative profit of maize and soybean in double-crop system was the most negatively impacted in the pessimistic scenario (−45.9%), indicating greater economic risk. Overall, lack of direct revenues from cover crops were compensated by increased grain yield in the spring-summer season and profitability of diversified crop rotation systems. Therefore, diversified crop rotation systems are economically competitive with double crop systems, rendering them feasible management options for conserving natural resources and increasing crop resilience to adverse climatic conditions.