Profit Space Research Articles

Optimized flow rate and efficient shaft water cooling method for EV's PMSM temperature-dependent energy system output power increase

One possible way to enhance the power density of electric vehicle (EV) powertrains is by utilizing temperature-sensitive permanent magnet synchronous motors (PMSMs) managed through liquid cooling. The management of benefits and costs from EV PMSM liquid cooling versus power are carried out for energy system output power (ESOP) increase. This study examines the effects of optimizing flow rate into housing water jackets (HWJ) and implementing compound shaft water (SWJ) cooling as management strategies using numerical multiphysics simulations and experiments. The PMSM with higher temperature at higher speed shows larger profit space brought by enhanced cooling. The optimized HWJ flow rate is a highly-efficient strategy to increase ESOP when overall pumping efficiency e1 for HWJ is less than 5 %, increasing more than 5.6 %, 2.1 % and 2.4 % ESOP at 1500, 3500, and 7000 rpm continuous working point. ESOP is insensitive to the condition of HWJ flow rate below 6 L/min or e1 over 30 %. The SWJ cooling is proved to be a low-cost and high-yield energy management strategy roughly independent of SWJ flow rate and EV's cooling system arrangement. ESOP is further increased by up to 3.9 %, 6.2 % and 4.4 % with SWJ cooling at 1500, 3500, and 7000 rpm.

Vehicle logistics intermodal route optimization based on Tabu search algorithm

With the development of logistics enterprises and the adjustment of some relevant laws and regulations, the profit space of vehicle logistics enterprises has been further compressed. To reduce vehicle logistics transportation cost and increase the profit space of vehicle logistics, the vehicle logistics multimodal transport network is constructed and the graph traversal algorithm is used to screen the feasible paths in the vehicle logistics multimodal transport network. Then, the Tabu search algorithm can optimize vehicle logistics multimodal transport route model. Results showed that Tabu search performed better than other methods in solving route optimization problems. The cost of Tabu search algorithm after convergence was 1.2 yuan/km × per set. The performance of Tabu search algorithm on NGSIM data set was better than other methods. On this data set, the area under the curve of Tabu search algorithm was much higher than that of other methods. The optimization results of Tabu search for vehicle logistics intermodal routes were effective. Among the 15 routes, only four routes were not optimized, and other routes were optimized. After optimization, the profits have increased, and the profit of Route 9 had the largest increase, which was 18%. The research successfully constructs the optimization model of vehicle logistics intermodal route, and completes the solution to increase the profit space of vehicle logistics enterprises.

Project Risk Analysis and Early Warning of Culture and Tourism Group Financial Leasing Company

Under the background of strict regulation, due to the cyclical adjustment of the financial leasing industry, some top companies have maintained a growth trend in asset size and net profit. Internal differentiation has emerged in the financial leasing industry, increasing operational pressure, and a slowing trend in asset size growth. Although the overall pressure on credit quality has eased, downward pressure on asset quality is widespread, and the recovery period for narrowing profit space is still long. With the continuous upgrading and iteration of digitization, intelligence, and specialization, Culture and Tourism Group Financial Leasing Company should strengthen its professional ethics, improve its risk analysis and prediction capabilities, design integrated business guidelines for due diligence information collection and risk analysis, rely on big data to build a leasing asset identification, evaluation, monitoring, and early warning system, and establish a comprehensive, multi angle, and lean risk analysis and early warning mechanism. Through case analysis, problems are identified in a timely manner, and continuous reflection and improvement are made. Business process diagrams are drawn according to different scenarios, crisis warning indicators are set up, and a lean risk management team is formed. Crisis warning signals are continuously tracked and released, and processes and asset quality management are continuously improved. A lean risk control system is established to reduce risk losses and create benefits for the enterprise.

E-Commerce Participation, Subjective Norms and Grassland Utilization Pressure: An Empirical Evidence of Herdsmen in Inner Mongolia, China

The general requirements of China’s rural revitalization strategy are industrial prosperity, ecological livability and rich life. However, the traditional livestock breeding model has struggled to balance the dual requirements of production development and ecological protection, and it is urgent to inject new impetus and explore new development paths. At present, e-commerce has become a bridge between pastoral areas and cities, herdsmen and consumers. E-commerce participation is not only an important starting point for herdsmen to increase the added value and profit space of livestock products, but also an effective way to change the original breeding behavior based on the premise of destroying grassland. Therefore, this paper presents an in-depth study on the issue of e-commerce enabling grassland ecological restoration, aiming to provide more scientific and effective guidance for e-commerce to be used to achieve a win–win situation in economy and ecology. Therefore, based on the data of 271 herdsmen in pastoral areas of Inner Mongolia, we used the OLS model and the two-stage least squares (2SLS) method to identify the direct impact of herdsmen’s e-commerce participation on grassland utilization pressure. The empirical results show that e-commerce participation can significantly decrease the grassland utilization pressure. The conclusion was still valid after alleviating endogeneity and conducting a robustness test. The results of a mechanism analysis suggest that the reduction effect of e-commerce participation on grassland utilization pressure is mainly due to price incentive, reputation incentive and place identity. Subjective norms can strengthen the inhibitory effect of e-commerce participation on grassland utilization pressure. Furthermore, a heterogeneity analysis demonstrates that e-commerce participation has a better, decreased impact on the grassland utilization pressure on the banners of China’s rural e-commerce demonstration county program. Under a counterfactual assumption, if herdsmen who can participate in e-commerce choose not to do this, their grassland utilization pressure will increase.

Tandem Electrocatalytic Alkyne Semihydrogenation over Bicomponent Catalysts through Hydrogen Spillover

AbstractElectrocatalytic alkyne semihydrogenation under mild conditions is a more attractive approach for alkene production than industrial routes but suffers from either low production efficiency or high energy consumption. Here, we describe a tandem catalytic concept that overcomes these challenges. Component (i), which can trap hydrogen effectively, is partnered with component (ii), which can readily release hydrogen for hydrogenation, to enable efficient generation of active hydrogen on component (i) at low overpotentials and timely (i)‐to‐(ii) hydrogen spillover and facile desorptive hydrogenation on component (ii). We examine this concept over bicomponent palladium‐copper catalysts for the production of representative 2‐methyl‐3‐butene‐2‐ol (MBE) from 2‐methyl‐3‐butyne‐2‐ol (MBY) and achieve a record high MBE production rate of 1.44 mmol h−1 cm−2 and a Faraday efficiency of ~88.8 % at a low energy consumption of 1.26 kWh kgMBE−1. With these catalysts, we further achieve 60 h continuous production of MBE with record high profit space.

Tandem Electrocatalytic Alkyne Semihydrogenation over Bicomponent Catalysts through Hydrogen Spillover.

Electrocatalytic alkyne semihydrogenation under mild conditions is a more attractive approach for alkene production than industrial routes but suffers from either low production efficiency or high energy consumption. Here, we describe a tandem catalytic concept that overcomes these challenges. Component (i), which can trap hydrogen effectively, is partnered with component (ii), which can readily release hydrogen for hydrogenation, to enable efficient generation of active hydrogen on component (i) at low overpotentials and timely (i)-to-(ii) hydrogen spillover and facile desorptive hydrogenation on component (ii). We examine this concept over bicomponent palladium-copper catalysts for the production of representative 2-methyl-3-butene-2-ol (MBE) from 2-methyl-3-butyne-2-ol (MBY) and achieve a record high MBE production rate of 1.44 mmol h-1 cm-2 and a Faraday efficiency of ~88.8 % at a low energy consumption of 1.26 kWh kgMBE -1. With these catalysts, we further achieve 60 h continuous production of MBE with record high profit space.

Research on Digital Economy Driving High Quality Development of China's Manufacturing Industry

With the profound changes in the global industrial economic situation, the industrial competition pattern is further adjusted, China's original reliance on the "demographic dividend" effect of the manufacturing industry expansion path is facing the challenge of low-end locking and marginalization, the urgent need to cultivate new kinetic energy. Get rid of the inherent low-cost competition and scale expansion mode, promote the digital transformation of the manufacturing industry, are the road to high-quality development of the manufacturing industry under the new development pattern. On the one hand, the digital economy has reconstructed the layout of the manufacturing industry chain in digital space and physical space, effectively unimpeded the domestic macrocycle; on the other hand, the digital economy can promote China's manufacturing industry to the high-end of the value chain, and win a larger profit space and the right to speak for the manufacturing industry to integrate into the international cycle. Therefore, under the new development pattern of internal and external double cycle, digital economy has become the new kinetic energy for the upgrading of China's manufacturing industry. This project combs through the domestic digital economy to drive the high-quality development of the manufacturing industry related literature, summarizes the economy to drive the high-quality development of the manufacturing industry measurement method, organizes the recent years of China's manufacturing industry development related research, consolidates the research foundation and expands the research perspective, constructs the "scale - structure", We construct a four-dimensional analytical framework of "scale-structure" and "circulation-external circulation" for the high-quality development of manufacturing industry, and explore the theoretical mechanism of digitalization-driven high-quality development of manufacturing industry. Through the use of econometric modeling methods to carry out empirical analysis of the digital economy driven manufacturing high quality, according to the empirical results, more scientific formulation of the digital economy driven China's manufacturing industry upgrading countermeasures recommendations.

A practical decision-making framework for highway transportation scheme selection based on the triangular fuzzy neutrosophic information

In recent years, due to the further development of the market economy, the internal competition in the large-cargo transportation industry has become increasingly fierce, and the profit space has been greatly compressed. Therefore, large-cargo logistics enterprises are paying more and more attention to the research of highway transportation route plan. The highway transportation scheme selection is looked as the multi-attribute decision-making (MADM). In this paper, the triangular fuzzy neutrosophic numbers (TFNN) grey relational analysis (TFNN-GRA) method is established based on the classical grey relational analysis (GRA) and triangular fuzzy neutrosophic sets (TFNSs) with completely unknown weight information. In order to obtain the weight values, the information Entropy is established to obtain the weight values based on the score and accuracy functions under TFNSs. Then, combining the traditional fuzzy GRA model with TFNSs information, the TFNN-GRA method is set up and the computing steps for MADM are established. Finally, a numerical example for highway transportation scheme selection was established and some comparisons are established to study the advantages of TFNN-GRA. The main contributions of this paper are established as follows: (1) the information Entropy is established to obtain the weight values based on the score and accuracy functions under TFNSs; (2) the TFNN-GRA method is established with completely unknown weight information. (2) the TFNN-GRA method is established and the computing steps for MADM are established. (3) Finally, a numerical example for highway transportation scheme selection was established and some comparisons is employed to study advantages of TFNN-GRA method.

The Impact of Short-selling Institutions on Chinese Stock Companies and MarketFrom the Case of Luckin Coffee

As a major engine of the capital market, the stock market is favored by investors. But the huge profit space and operability are also easy to breed the soil of corruption and fraud. At present, due to the increased participation efficiency of short-selling institutions, the financial risks faced by enterprises have further increased. Through the case of Luckin coffee, we observe the stock price changes after it encountered short selling, combined with the model of the arbitrage pricing principle to find the role of short-selling institutions in the market. By disclosing corporate financial fraud, short-sellers can improve the effectiveness of market supervision to a certain extent, reduce the occurrence of stock market premiums, and bring stock prices back to their true levels. On the premise of ensuring the stability of the stock market and introducing a reasonable system, the Chinese market can also consider developing a similar mechanism to inject fresh blood into economic development.

Predicting Airbnb Listing Price with Different models

Airbnb is a platform company that provides and directs connections between hosts and guests. People who have an open room or a vacant space can become a host on Airbnb and make it available to the world community. Airbnb offers hosts an easy way to turn otherwise wasted space into profitable space. Therefore, it is particularly necessary for hosts to forecast and analyze the price of the houses they own. Machine learning is the science of developing algorithms and statistical models. The regression model is a predictive modeling technique in machine learning. This technique is often used to discover causal relationships between variables, predictive analysis, and time series models. In this project, our goal is to predict Boston Airbnb listing prices through a variety of machine-learning methods. This paper chose four regression models, which are the random forest regression model, linear regression model, K-nearest neighbor regression model, and Gradient Boosting regression model. With one of the best regression models, this paper obtained R-squared values of 0.6593 in training and 0.7198 in testing on the Boston dataset.

Feasibility Study of Nuclear Power Included in Carbon Trading Market: A Case Study of China's Carbon Market

As an innovative economic and clean source of energy, now nuclear power is the most worthy of large-scale development in the world. Especially in China, the development of nuclear power is not only related to China's energy security, but also of great significance to economic development and international status. Mature and stable carbon emission market is also very important for the implementation of new energy technology. Therefore whenever it comes to carbon trading, as a derivative means for countries in the world to participate in global carbon emission control, it has developed rapidly in China in recent years. Through theoretical analysis and sample data analysis, this paper studies current policies and historical sources, finds out the possible mechanism for nuclear power to enter the carbon trading market, and describes the economic benefits of the combination of nuclear power and carbon trading market. The results show that there is a correlation and causality between nuclear power and other power generation methods and carbon market, and there is a large profit space when carbon trading is included. Nuclear power has potential value for inclusion in the carbon market.

Chemical Looping Enhanced Oil Shale-to-Liquid Fuels Process: Modeling, Parameter Optimization, and Performance Analysis

The solid heat carrier moving bed with internals is an advanced oil shale retorting technology. However, the retorting gas produced by pyrolysis is generally used as fuel gas. The content of CO, H2, and CH4 in the retorting gas is high, and direct combustion leads to resource waste and environmental pollution. In addition, heteroatomic sulfur and nitrogen, as well as unsaturated hydrocarbons, reduce the quality of shale oil. To solve these problems, this paper proposed a chemical looping enhanced oil shale-to-liquid fuels (CLeSTL) process. The chemical looping hydrogen production technology is applied to convert retorting gas to hydrogen, and the hydrogen produced is used for shale oil hydrogenation to improve the oil quality. In this paper, the new process is modeled and simulated; then technoeconomic analysis is carried out. Technical analysis shows that shale oil yield is increased from 65% to 95.7% and the yield of light fraction is increased from 20% to 64%–83%. Economic analysis shows that the CLeSTL process with ligh fraction hydrogenation has the highest investment profit rate and large profit space. In addition, when the oil price is lower than 50 USD/bbl, the investment profit is 5%, which shows strong anti-risk ability.

Analysis of Coca-cola's Characteristics and Financial Indicators

Coca-Cola is by far the world's largest beverage company, with a market share of 48 percent worldwide. Coca-Cola was founded in 1886. From a drink sold only in drugstores to a famous cola in more than 200 cities, the company has made a lot of changes. Coca-Cola has become a benchmark in the global beverage industry, and some of its decisions or strategic changes may affect the global economy. Therefore, understanding the basic information and financial situation of Coca-Cola Company is a required item for many companies and individuals. Through SWOT analysis and calculation of some financial ratios (comparing Coca-Cola and Pepsi), this paper conducts a analysis and provides suggestions on the strengths, weaknesses, external opportunities, external threats and financial conditions of Coca-Cola. According to the analysis, Coca-Cola should do more research and development to make its products more novel, and it should reduce the production cost appropriately and strive for greater profit space. Secondly, Coca-Cola needs to sell a large number of inventory goods as soon as possible, replan the inventory number of products, and strengthen the operation of funds. The final recommendation is that Coca-Cola is a good company for people to invest in.

A Bi-level optimization model of integrated energy system considering wind power uncertainty

To cope with the volatility of renewable energy and improve the efficiency of energy storage investment, a bi-level (B-L) optimization model of an integrated energy system (IES) with multiple types of energy storage is established by considering the uncertainty of wind power. The upper-level optimization model considers the lowest configuration cost of energy storage as the objective function and satisfies the constraints of the energy storage configuration. The lower-level optimization model considers the lowest operation cost of the IES as the objective function and satisfies the constraints of the system operation. Second, to overcome the fluctuation problem of wind power output, a robust optimization theory is introduced to describe the uncertainty. Robust coefficients are set to reflect different risk attitudes, which improves the adaptability of the system to uncertainty. Third, the B-L optimization model is solved using the Karush–Kuhn Tucker condition. Finally, a new park is used to implement the simulation. The conclusions are as follows: (1) The economic configuration strategy and optimal operation scheme can be obtained by applying the B-L optimization model, and the upper- and lower-levels interact with each other. The optimal targets of the upper- and lower-level models are −115,848 ¥ and 57,131,102 ¥, respectively. (2) The robust optimization theory improves the ability of a system to deal with risks. Robust optimization theory improves the ability of a system to deal with risks. With an increase in the robustness coefficient, the profit space of the upper-level model increases; however, the operation cost of the lower-level model increases.

Optimal ordering and transportation scheme of raw materials in production enterprises based on objective programming model

In order to better realize the development of construction production enterprises and create greater profit space for them, based on the relevant data of raw material suppliers and forwarders of a production enterprise within five years, this paper first uses ARIMA algorithm to solve the enterprise's ordering scheme, and then uses 0-1 integer programming to find the constraints between suppliers and forwarders, Finally, LINGO software is used to build the target programming model to solve the 24-week transfer scheme.

Merchandising for Sustainable Fashion: A Systematic Literature Review

With the emergence of environmental pollution and the excessive waste of resources, the traditional development of the pure pursuit of economic growth has encountered challenges. More and more people are advocating for the concept of sustainable development, which makes sustainable merchandising an urgent necessity. Clothing brands should adhere to the brand sustainability concept and sustainable management in the merchandising process, which can truly improve the competitiveness of the brand. For this reason, a series of studies on sustainable merchandising strategies has been conducted by apparel companies and academia. The existing reviews on sustainability aspects focus on material, recycling, and life-cycle aspects. However, less attention has been paid to the sustainable merchandising aspects of apparel. Therefore, this paper presents a systematic literature review of this topic. We summarize the relevant research on sustainable merchandising from a merchandising perspective and systematically review the relevant theories and cases of sustainable merchandising for the relatively blank field of sustainable brand merchandising for apparel. We have achieved the purpose of integrating the analysis of factors influencing sustainable merchandising, and merchandising strategies. Additionally, on this basis, we discuss how brands can combine social responsibility with merchandising to develop and enjoy the profit space brought by merchandising while assuming and promoting their own brand responsibility. This literature review is based on journal articles, book chapters, and conference papers from the Web of Science (WOS) database and Google Scholar. Through an in-depth analysis of the existing literature, this paper provides an overview of the research topic, the sustainable merchandising of apparel, from a merchandising perspective and discusses the shortcomings of existing merchandising strategies. The findings reveal that there are drawbacks to the current apparel merchandising strategies such as low feasibility, ignoring the driving power of the market, weak consumer awareness, consumer culture, and lack of government intervention and support. This has resulted in the slow development of clothing brands in the sustainable merchandising market. The results of this study provide direction for the development of future sustainable merchandising strategies. It guides policymakers and practitioners to develop relevant strategies for sustainable merchandising in order to provide better market space for sustainable merchandising of apparel.

Role of the National Office of Buddhism (NOB) in Managing the Abandoned Monasteries of Chiang Mai

The objectives of the research are to study roles of the National Office of Buddhism (NOB) with respect to managing the abandoned monasteries of Chiang Mai, and specifically, 1) to identify unsustainable conditions that face abandoned monasteries, 2) to clarify unsustainable ways of thinking about abandoned monasteries , 3) to seek a rental management policy for abandoned monasteries , and 4) to seek management solutions for particular abandoned monasteries . Research problems are raised in relation to the lack of sacred fulfillment within the dead monument approach. Passive management in rental deeds without upgrading quality of life and community member interactions with the monuments indirectly lead to inappropriate conditions of some abandoned monasteries. I suggest that abandoned monasteries be thought of in terms of ‘religious heritages’ rather than ‘historic sites’ to provide multifaceted solutions to the management issues. There are 948 abandoned monasteries in Chiang Mai, only 8 of them are located in the city walled area. The abandoned monasteries within the old Chiang Mai city walled area, Chiang Mai Province, Thailand were physically examined. In addition to the site surveys of the abandoned monasteries, 33 in-depth interviews were conducted, with 12 interviews focusing on what I term the “official approach” (i.e. with government agencies and key higher education representatives) and 21 interviews focusing on what I term the “local approach” (i.e. with religious leaders and local community members). Secondary data analysis included a review of both Thai and English documents to identify the latest key thinking on management practices for abandoned monasteries. Literature sources analysis and case study analysis are also provided for 8 of the abandoned monasteries in the study area. Finally, 4 management keys (zoning management, public participation, sustaining of the sacred place condition, and local community ownership) were developed based on identified gaps in the NOB approach to managing abandoned monasteries. It can be concluded that the NOB approach to abandoned monastery deed management should consider 1) revising the ‘dead monument’ concept for hibernated sacred places that leads to unsustainable conditions, 2) the dilemma of the ‘sacred space’ that transitions to the ‘profitable space’ and represents unsustainable ways of thinking, 3) passive action of rental management is an outdated policy, and 4) results of the 4 management keys are supplemental solutions for the particular policy making and promoting sustainability of abandoned monasteries.

Research on optimization of construction project cost control in construction enterprises

As a pillar industry of the national economy, the construction industry plays an important role in promoting economic growth, social stability and improvement of quality of life of people. Influenced by the deepening reform of the market economy system and the normal prevention and control of the COVID-19 epidemic, the construction market has increasingly high requirements and the market competition is becoming increasingly fierce. The major enterprises compete with each other to obtain the project at a low price, which seriously disturbs the market order and further compresses the market profit space. In the limited market share, in order to improve their competitiveness, cost control has become the focus of construction enterprises. This paper analyzes the current situation of cost control of construction projects in construction enterprises, finds out the existing problems and puts forward countermeasures and suggestions in order to realize the dynamic cost control of the whole process of construction projects.

Analysing the Cost-Effectiveness of Charging Stations for Electric Vehicles in the U.K.’s Rural Areas

While U.K. authorities have attempted to tailor measures to boost sales of electric vehicles (EVs) and support citizens through different schemes, the size and geographic coverage of the existing charging network are insufficient, which undermines electromobility promotion. There are 15,853 public charging points installed in the U.K. as of 3 August 2021, and the demands for public EV charging are rising. For rural areas, there is little support from local authorities or private companies. To identify how a charging station can be installed and work, this study researches existing charging stations nationwide. Generally, most Public Charging Stations (PCS) in rural areas have unsatisfactory cost-effectiveness due to their long payback period. This paper presents how many rural PCS are able to afford the cost in the first eight years. Based on the ever-increasing demands of the market, EV producers are switching their business strategies. Meanwhile, the rural areas may become urban with the same definition. When it comes to the analysis of cost-effectiveness, it is possible for the PCS to bring more elements into the calculation. For Capital Expenditure (CAPEX) and Operation Expenditure (OPEX), the unnecessary cost leaves more profit space, like the possibility of unplanned maintenance costs.

Profitability of container shipping via the Arctic Northeast Passage: A simulation and regression analysis

The progressive retreat of Arctic sea ice in recent years has offered unprecedented opportunities for commercial shipping via Arctic shipping routes. However, actual annual transits via the Arctic Northeast Passage (NEP) are rare which signals that shipping companies are reluctant to use the NEP from a cost-benefit perspective. This paper analyzes the profitability of container shipping via the NEP. Based on observational data the distribution of profit for a single-voyage along the NEP for different ice class ships (Arc4 and Arc7) in different shipping modes (direct mode and transshipment mode) is generated via Monte Carlo simulations. The simulated data are then used in a seemingly unrelated regression analysis and in cross-equation testing to investigate the relative impact of various revenue and cost factors on the profit of container shipping via the NEP for the different shipping modes and ice ship classes. The study finds that the impacts of the various cost factors considered in the analysis indeed differ greatly across different shipping modes and different ice classes of container ships. The direct mode has a greater profit space than the transshipment mode and the Arc4 class ship has higher profitability than the Arc7 class ship under reasonable assumptions. Moreover, when the container freight rate of the NEP increases by 60% on basis of that of the traditional routes, shipping via the NEP will be profitable.