To see the other types of publications on this topic, follow the link: And Industry Forecast 2023-2027.
Journal articles on the topic 'And Industry Forecast 2023-2027'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'And Industry Forecast 2023-2027.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Muftaydinov, Kiyomidin, and Ilkhomjon Yuldashevich Umarov. "MODELING AND FORECASTING ECONOMIC PROCESSES OF FOOD INDUSTRY ENTERPRISES." Annali d'Italia 61 (November 27, 2024): 31–35. https://doi.org/10.5281/zenodo.14230797.
Full textAbstract:
Today, for the effective development of the food industry in Uzbekistan, it is important to develop effective economic and managerial decisions and ensure their implementation. The article developed a model of the relationship between the cost of gross production and the depreciation of fixed assets and intangible assets. The ascending order of the case under study is shown by flattening the time series using the least squares method. The dynamics of the wage fund, depreciation of fixed assets and intangible assets in the food industry of the Republic of Uzbekistan in 2014-2023 and forecast values for 2024-2027 have been determined.
2
Sushchenko, Olena, and Oleksii Pohuda. "Analysis of the development factors of the passenger air transport market in the tourism sector." Економіка і регіон/ Economics and region, no. 1(92) (February 9, 2024): 168–73. https://doi.org/10.26906/eir.2024.1(92).3325.
Full textAbstract:
The article analyses the factors that determine the development of the passenger air transport market. It analyses the dynamics of international tourist arrivals in the regions of the world in 2019-2023 and identifies the busiest routes in the world in 2023. Also, it provides an analysis of the actual and forecast level of global traffic losses and the pace of its recovery. It was determined that according to the optimistic forecast, passenger traffic in 2027 should exceed the level of 2019 by 31%. It was also identified that the impact of global and local events has had a negative impact on both the tourism sector and the aviation industry. The surge in demand for air travel in Europe in 2023 caused flight delays by 400% during peak periods. The article examines the dynamics of the number of passengers who used the services of domestic airlines in Ukraine in 2011-2022. The paper outlines the most significant factors influencing the volume of passenger traffic, based on the actual state of the industry and current trends. It defines that the use of digital technologies will have advantages for both tourists and airlines.
3
SAVCHENKO-BELSKII, K. A., E. I. MANTAEVA, and A. A. MANTSAEVA. "ESTABLISHMENT OF A TOURIST AND RECREATIONAL CLUSTER IN THE REGION: REASONABILITY AND FORECAST." Scientific Works of the Free Economic Society of Russia 239, no. 1 (2023): 180–202. http://dx.doi.org/10.38197/2072-2060-2023-239-1-180-202.
Full textAbstract:
The article assesses the feasibility of establishing a regional economic cluster. The assessment is tested for the tourism industry. It is based on a two-level classification system of Russian regions and simulation modeling. The classification made it possible to single out typological groups of regions with different industry orientations and to identify groups of different industry development levels. Simulation modeling required studying a number of indicators of the tourism industry and identifying patterns and processes occurring in it in a formalized form. Using built models, the results of the tourism industry between 2018–2027 were predicted. Along with that, the investments were provided for the establishment and development of a tourist and recreational cluster.
4
Bylina, Svetlana Gennadievna. "FORECAST ESTIMATES OF LABOR DEMAND IN AGRICULTURE IN RUSSIA." AIC: economics, management, no. 3 (March 1, 2025): 124–34. https://doi.org/10.33305/253-124.
Full textAbstract:
The influence of the parameters of development of the Russian agricultural sector on the need for workers is studied. Using econometric models, a forecast estimate of the demand for labor in agriculture, forestry, hunting and fishing is made based on the criteria of sectoral development laid down in state program documents: the State Program for the Development of Agriculture and Regulation of Agricultural Products, Raw Materials and Food Markets (State Program), the Strategy for the Development of the Agro-Industrial and Fishing Complexes of the Russian Federation for the Period up to 2030 (Strategy) and the forecast of the Ministry of Economic Development of the Russian Federation up to 2027. The forecast for the development of agricultural sector in Russia is based on the results of the study. A decrease in the need for workers is predicted for all expected options for the sector development. At the same time, a serious shortage of personnel in agricultural production is noted, both at present and in the future, especially in accordance with the expected growth rates of investment in fixed assets. It is calculated that by 2030 the output growth rates specified in the State Program may lead to a decrease in labor demand in the industry by 161 thousand people relative to the 2023 level; the implementation of the basic version of the Strategy assumes a decrease in the number of employees by 217 thousand people compared to the 2023 data, and the target version of the Strategy - by 661 thousand people compared to the 2023. The dynamics of investments in fixed capital of the industry, laid down in the State Program, will lead to labor demand in 2030 at the 2023 level; according to the target and basic versions of the Strategy, the need for workers will be 5.9 and 19.8% higher, respectively, than in 2023. The problem of attracting qualified personnel to the industry in the medium term is expected to prevail over the problem of labor release in agricultural production. It is advisable to use the obtained estimates as basic guidelines for long-term planning of the development of the agro-industrial complex and rural areas.
5
HOSSEN, Sayed Mohibul, Mohd Tahir ISMAIL, and Mosab I. TABASH. "THE IMPACT OF SEASONALITY IN TEMPERATURE FORECAST ON TOURIST ARRIVALS IN BANGLADESH: AN EMPIRICAL EVIDENCE." GeoJournal of Tourism and Geosites 34, no. 1 (2021): 20–27. http://dx.doi.org/10.30892/gtg.34103-614.
Full textAbstract:
In the present study, we aim to investigate how seasonality influences the climate changes on the outdoor thermal comfort for traveling to visit Bangladesh. Wherein, the effect of temperature on tourist arrival is assessed using SANCOVA and SARIMA model at seven attractive sightseeing diverse places in Bangladesh. The highest temperature has appeared in Khulna and Rajshahi with 35.53 °C and 35.85 °C and the lowest temperature was appeared in Rajshahi and Rangamati with 10.40 °C and 11.72 °C, respectively. This result also revealed that the temperature for Dhaka, Chittagong, Cox’s Bazar, Khulna, and Sylhet has extreme values of decreasing, in Dhaka the temperature will be 25.140 °C on January 2023, in Chittagong 260 °C on January 2027, Cox’s Bazar 26.490 °C on January 2030, in Khulna 25.610 °C on January 2023, and in Sylhet 26.560 °C on January 2020. Our findings also indicate that the tourism industry of Bangladesh is more vulnerable to seasonal variation and this seasonality has a 74% effect on tourist’s arrival as well as a 98% effect on overall temperature in Bangladesh.
6
XU, QIAN, HUA CHENG, and YABIN YU. "Analysis and forecast of textile industry technology innovation capability in China." Industria Textila 72, no. 02 (2021): 191–97. http://dx.doi.org/10.35530/it.072.02.1759.
Full textAbstract:
The textile industry of China has been facing with fierce competition and transformational pressures. It is of great significance to study the evolution of textile industry’s technological progress and to predict the trends. The study analyses the technological innovation ability of China’s textile industry based on the data of 270,145 patent applications from 1987 to 2016. At the same time, the Logistic model is used to forecast the technology innovation capability of China’s textile industry. The study found out: the number of Chinese textile patent applications is on a upward trend; enterprises and universities are the most important patentee; the regional distribution of textile technology innovation is uneven; the number of patent applications in the southeast coastal areas is the largest; the distribution of the IPC is also uneven, D06 (fabric treatment) having the largest number of patent applications and the fastest growth rate; China’s textile industry technology innovation has entered a maturity stage in 2018, and will enter the recession stage after 2027 based on the Logistic model.
7
Gajdzik, Bożena. "Post-Pandemic Steel Production Scenarios for Poland Based on Forecasts of Annual Steel Production Volume." Management Systems in Production Engineering 31, no. 2 (2023): 172–90. http://dx.doi.org/10.2478/mspe-2023-0019.
Full textAbstract:
Abstract The paper presents the results of forecasts made for the volume of steel production in Poland based on actual data for the period from 2006 to 2021 with forecasting until 2026. The actual data used for the forecasts included annual steel production volumes in Poland (crude steel) in millions of tons. Basic adaptive methods were used to forecast the volume of steel production for the next five years. When selecting the methods, the course of the trend of the studied phenomenon was taken into account. In order to estimate the level of admissibility of the adopted forecasting methods, as well as to select the best forecasts, the errors of apparent forecasts (ex post) were calculated. Errors were calculated in the work: RMSE Root Mean Square Error being the square root of the mean square error of the ex-post forecasts yt for the period 2006-2021; ? as the mean value of the relative error of expired forecasts y*t (2006-2021) – this error informs about the part of the absolute error per unit of the real value of the variable yt. Optimization of the forecast values was based on the search for the minimum value of one of the above-mentioned errors, treated as an optimization criterion. In addition, the value of the point forecast (for 2022) obtained on the basis of the models used was compared with the steel production volume obtained for 3 quarters of 2022 in Poland with the forecast for the last quarter. Forecasting results obtained on the basis of the forecasting methods used, taking into account the permissible forecast errors, were considered as the basis for determining steel production scenarios for Poland until 2026. To determine the scenarios, forecast aggregation was used, and so the central forecasts were determined separately for decreasing trends and for increasing trends, based on the average values of the forecasts obtained for the period 2022-2026. The central forecasts were considered the baseline scenarios for steel production in Poland in 2022-2026 and the projected production volumes above the baseline forecasts with upward trends were considered an optimistic scenario, while the forecasted production volumes below the central scenario for downward trends were considered a pessimistic scenario for the Polish steel industry.
8
Duanaputri, Rohmanita, Sulistyowati Sulistyowati, and Putra Aulia Insani. "Analisis peramalan kebutuhan energi listrik sektor industri di Jawa Timur dengan metode regresi linear." JURNAL ELTEK 20, no. 2 (2022): 50. http://dx.doi.org/10.33795/eltek.v20i2.352.
Full textAbstract:
Abstrak 
 Pada kehidupan sekarang maupun akan datang, energi listrik menjadi kebutuhan pokok masyarakat. Kebutuhan energi listrik selalu mengalami peningkatan, diikuti meningkatnya pertumbuhan penduduk. Permasalahan akan muncul apabila kebutuhan energi listrik tidak diperkirakan. Maka perlu dilakukan peramalan kebutuhan energi listrik untuk memprediksikan ketersediaan energi listrik di masa mendatang. Pada penelitian ini, dilakukan peramalan kebutuhan energi listrik menggunakan metode regresi linier pada sektor industri di Jawa Timur untuk tahun 2023-2027. Berdasarkan hasil perhitungan prediksi dan MAPE (2009-2021), didapatkan metode regresi linier masih baik dan layak digunakan menurut standar MAPE. Kemudian dibandingkan hasil prediksi dan MAPE (2010-2020) antara metode regresi linear dengan metode time series pada penelitian sebelumnya, didapatkan metode time series menghasilkan prediksi dan MAPE lebih baik dibanding metode regresi linier pada pelanggan listrik, sedangkan pada daya tersambung, energi listrik terjual, dan pendapatan penjualan energi listrik didapatkan metode regresi linier menghasilkan prediksi dan MAPE lebih baik dibanding metode time series. Tetapi, penulis menghitung peramalan kebutuhan energi listrik pada sektor industri di Jawa Timur (2023-2027) hanya menggunakan metode regresi linier. Sehingga dihasilkan akan terjadi kenaikan setiap tahun dengan rata-rata untuk pelanggan listrik sebesar 5.264 pelanggan, daya tersambung sebesar 328,49 MVA, energi listrik terjual sebesar 580,64 GWh, dan pendapatan penjualan energi listrik sebesar 1.065.266,21 Juta Rupiah. Menurut hasil tersebut, maka pasokan energi listrik harus tercukupi dengan merencanakan pengembangan atau penambahan kapasitas pembangkit listrik.
 Abstract
 In present and future life, electrical energy becomes basic needs of community. Electrical energy needs always increased, followed by increased population growth. Problem will appear if electrical energy needs is not expected. Therefore, it is necessary to forecast electrical energy needs to predict the availability of electrical energy in future. In this study, calculation of forecasting electrical energy needs using linear regression methods in industrial sector in East Java for 2023-2027. Based on calculation results of prediction and MAPE (2009-2021), it is obtained linear regression method is still good and worthy of use according to MAPE standard. Then comparison results of prediction and MAPE (2010-2020) between linear regression method with time series method in previous study, it was obtained that time series method produced predictive and MAPE is better than linear regression methods on electricity customers, while in power connected, electric energy sold, and earnings of electrical energy sales obtained linear regression method produces predictive and MAPE better than time series method. However, authors calculation of electrical energy needs in industrial sector in East Java (2023-2027) only using linear regression methods. So there will be increase every year with average for electricity customers of 5,264 customers, power connected of 328.49 MVA, electric energy sold of 580.64 GWh, and earnings of electrical energy sales of 1,065,266.21 million rupiah. According to results, supply of electrical energy should be fulfilled by planning development or additional power plant capacity.
9
S. Milovanov, Svyatoslav. "Clinical Trials Trends of 2023 Year and Visionary to the Future." International Journal of Clinical Investigation and Case Reports 02, no. 01 (2023): 13–19. http://dx.doi.org/10.55828/ijcicr-21-04.
Full textAbstract:
Introduction: The importance of studying historical changes in the development of human activity is substantiated by the need to systematize such changes and the possibility of predicting them. Historical changes are extended in time and do not have clear boundaries, requiring greater involvement in their study and the prerequisites for their appearance. Clinical research is more than just the practical application of medical changes and discoveries. They make changes in medical practice but are subject to change. Changes in the clinical research industry are tendentious and develop gradually, requiring study and forecasting. According to the generally accepted temporal gradation of the forecast, there is an operational forecast of up to one month, a short-term forecast of up to one year, a medium-term forecast of up to five years, a long-term forecast of up to 20 years and a long-term forecast over long-term, and a short-term forecast is common in the clinical research industry. We analyzed publications in open sources from 1930 to 2023 by keywords in the Russian-language literature trends in the clinical trial industry and the English-language literature trends in the clinical trial industry. Discussion and Conclusion: Trends in the development of clinical trials until the end of 2023 can be divided into two groups, those related to changes in the conduct of clinical trials and changes in the products of clinical trials in nosologies. If in the first group, the trends remain similar to 2022, the ongoing digitalization of operations, the shift of centralized research towards decentralization, and the shift in protocol design towards patient-centricity, then in the second group, the number of expected drugs has decreased, and there is a shift of drugs towards biologics and gene therapy drugs.
10
KUMAR, AJAY, VINAY KUMAR, CHETNA, et al. "Forecasting cotton (Gossypium spp.) prices in major Haryana markets: A time series and ARIMA approach." Indian Journal of Agricultural Sciences 94, no. 9 (2024): 1013–18. http://dx.doi.org/10.56093/ijas.v94i9.150524.
Full textAbstract:
Economic outputs are an attractive prospect in any field and hence agriculture also relies heavily on economic stability. The costs associated with cotton farming are increasing and profitability is taking a hit in cotton cultivation. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. Present study was carried out during 2022 to 2023 in Haryana to provide some insights into the possible future prices of cotton (Gossypium spp.) with the help of data collected from AGMARKNET and various major cotton markets (Adampur, Sirsa and Fatehabad) of Haryana. The Autoregressive Integrated Moving Average (ARIMA) models have been employed in order to forecast the prices of cotton crops for the years 2022–23 to 2027–28. Through a meticulous exploration of various combinations of lagged moving average and autoregressive components, the ARIMA (1,1,1) model was selected as the most suitable for the price forecasting in these districts. The results of this analysis demonstrate that the coefficient of determination (R2) for the forecasted cotton crop prices in comparison to the real-time prices falls within acceptable ranges. This finding underscores the efficacy of the ARIMA (1,1,1) model as a reliable tool for generating short-term price estimates. This model offers valuable insights and predictive accuracy, aiding decision-makers and stakeholders in the cotton industry of Adampur, Sirsa and Fatehabad markets to make informed choices and plan effectively for the coming years. Cotton prices vary according to the season and the region, hence a valuable insight on future price assumptions will help the agriculture community.
11
Rubtsova, Natalia. "Microfinance in the Russian Federation: Changes in Industry Indicators in the Context of Global Challenges." Baikal Research Journal 15, no. 1 (2024): 13–24. http://dx.doi.org/10.17150/2411-6262.2024.15(1).13-24.
Full textAbstract:
The purpose of the study was to predict the state of microfinance organizations in the Russian Federation, verify the trends that determine their development in the context of global geopolitical challenges. The research was carried out using logical and empirical methods. The article analyzes changes in the main indicators of the functioning of microfinance organizations (MFOs) in the Russian Federation over a ten-year period (2014–2023). Based on an analysis of changes in key indicators characterizing domestic microfinance organizations (the number of microfinance organizations, the volume of microloans issued and their structure in the context of online and offline formats, the main segments of microfinance), the author comes to the conclusion that microfinance activities in the Russian Federation are highly resistant to negative impacts environmental factors. The scientific novelty of the article lies in the verification of the main trends in the development of domestic microfinance, which include tightening regulation of microfinance organizations by the Central Bank of Russia, further consolidation, industry concentration, development of non-core activities, BNPL services, dominance of online microcredit, deterioration in the quality of debt servicing, reducing the investment attractiveness of the industry. In conclusion, the author identified the forecast values of the main performance indicators of MFOs for the period 2024–2027, and possible restrictions on the future development of this.
12
Zhang, Bowen. "Analysis of Bilibili's Competitive Strategy in the New Trends." BCP Business & Management 34 (December 14, 2022): 849–55. http://dx.doi.org/10.54691/bcpbm.v34i.3104.
Full textAbstract:
According to the "2022-2027 China Internet Video Industry Market Depth Research and Investment Strategy Forecast Report" published by the China Research Institute of Industry, as of the end of June 2021, the size of China's Internet users broke one billion, reaching 1.011 billion people, an increase of 0.22 billion people compared to the end of December 2020, the massive size of Internet users to promote the development of China's online video industry. The size of the short video market will increase more quickly between 2020 and 2022, with a compound annual growth rate of about 44%. The market size will grow at a slower rate during 2023-2025, but will still maintain a CAGR of 16%. China's short video market is expected to reach nearly 600 billion yuan in 2025 [1]. More than a quarter of a day is spent watching short videos on mobile devices in China. Along with visuals and audio, short video has emerged as the "third language" of the mobile Internet. Short-form video has rapidly increased in the new Internet economy. Bilibili's future development has attracted much attention. With the development of the Internet economy and the increase in significant video websites, whether Bilibili can continue its competitive advantage and successfully achieve business transformation has become controversial. This research will analyse Bilibili's business model through a SWOT analysis and make feasible suggestions for its future development.
13
Liu, Chang, Rongjie Cai, Guanliang Chen, et al. "Development Analyses and Strategies for Pet Industry and related." Mathematical Modeling and Algorithm Application 4, no. 1 (2025): 47–55. https://doi.org/10.54097/cwx12v21.
Full textAbstract:
This paper analyzes the development trends and market demands of the pet industry in China and globally, particularly focusing on pet food production and related industries from 2019 to 2023, with forecasts for 2024-2026. Through comprehensive mathematical modeling including time series analysis, regression models, and impact assessment frameworks, we address two key problems: (1) Analysis of China’s pet industry development by pet type, revealing significant growth in the cat segment (CAGR 12.15%) while the dog segment shows stability;(2) Forecast of China’s pet food production and export values, projecting continued growth with production value expected to reach 3277 billion CNY by 2026.
14
KRASNYKH, SERGEY S. "FORECAST SCENARIOS OF MINERAL PRODUCTION IN THE REGIONS OF THE URALS FEDERAL DISTRICT." Bulletin of Chelyabinsk State University 497, no. 3 (2025): 49–59. https://doi.org/10.47475/1994-2796-2025-497-3-49-59.
Full textAbstract:
In the context of sanctions restrictions, the Russian mining industry faces significant challenges related to reduced production volumes, limited access to technology and financial markets, and the need to reorient export flows. These problems are particularly relevant for key producing regions such as the Urals Federal District. The purpose of this paper is to develop forecast scenarios of mineral extraction volumes in the municipalities of the Urals Federal District until 2027, which will provide a basis for comprehensive strategies for sustainable development of the extractive industry. The study uses econometric models ARMA and ARIMA, which are applicable for time series analysis, allowing to take into account both stationary and non-stationary data. The models are developed on the basis of monthly indicators of mineral production in the regions of the Urals Federal District for the period from December 2017 to November 2024. The analysis includes the selection of model parameters, verification of their adequacy and interpretation of the results obtained. The study constructs inertial, optimistic and pessimistic scenarios of mineral extraction volumes, which can be useful for developing strategies in the current geopolitical environment.
15
Tahir, Saad, and Asher Ramish. "Xarasoft (Pvt) Ltd – vision 2027 to implement a digital supply chain for industry 4.0." Emerald Emerging Markets Case Studies 12, no. 1 (2022): 1–22. http://dx.doi.org/10.1108/eemcs-05-2021-0180.
Full textAbstract:
Learning outcomes This case study aims to be taught at an MBA level. Specifically, those students who are majoring in supply chain would benefit the most from this case study. This case study has elements of supply chain management, supply chain strategy, warehousing and logistics, and a digital supply chain for Industry 4.0. The learning outcome of this case study could be seen if the students are able to identify the challenges and opportunities of a digital supply chain for Industry 4.0 and how it could be implemented methodically. Teaching Objective 1: Students should be able to identify what challenges organizations face if they implement a digital supply chain for Industry 4.0. Teaching Objective 2: Students should be able to identify what opportunities can be tapped if Big Data Analytics are used in a supply chain teaching. Objective 3: Students should layout a methodical plan of how an analogue company can gradually achieve the objective of implementing a digital supply chain for Industry 4.0 in procurement function. Case overview/Synopsis Based in the Lahore region of Pakistan, Xarasoft is a footwear manufacturing company which has undertaken a decision to transcend to a digital supply chain for Industry 4.0 by 2027. Asif, who is the Head of the Department of Supply Chain, has to come up with a plan to present in the next meeting with the CEO. Xarasoft is a company that preferred to work in an analogue routine. The company set production targets and sold goods through marketing. With no forecast or exact demand, the company had decided to procure 140 million units of raw material and carrying a huge inventory, a percentage of which had to be thrown away as it started to degrade. While the company did have machinery on the production floor, they were operated manually and were a generation behind. Asif faced the question of what challenges he would face and exactly how would a digital supply chain for Industry 4.0 be implemented in the company. Complexity academic level Masters level supply chain courses Supplementary materials Teaching notes are available for educators only. Subject code CSS 9: Operations and Logistics.
16
Pîrvu, Daniela, Maria-Daniela Bondoc, and Luiza Mădălina Apostol. "Forecasting the Profitability of the Textile Sector in Emerging European Countries Using Artificial Neural Networks." Fibres & Textiles in Eastern Europe 32, no. 5 (2024): 39–48. http://dx.doi.org/10.2478/ftee-2024-0035.
Full textAbstract:
Abstract This study analyzes a set of key performance indicators for listed companies in the textile industry in emerging European countries: EBITDA margin, operating margin, pretax ROA, pretax ROE. Several statistical-econometric methods (dynamics analysis, structural analysis and regression) were used to provide an overview of the evolution of the public companies studied for the period 2012–2022, as well as a number of forecasts for the period 2023–2025. GMDH Shell software was used for public companies' pretax ROA forecast analysis in the textile industry in emerging European countries. The factor regression models that were constructed are valid for eight of the nine countries studied.
17
López, Gustavo Rosal. "SS62-02 REFLECTIONS ON THE USE OF EXOSKELETONS IN THE HEALTHCARE SECTOR." Occupational Medicine 74, Supplement_1 (2024): 0. http://dx.doi.org/10.1093/occmed/kqae023.0361.
Full textAbstract:
Abstract For a few years now, the concept of Human 2.O has been very present in industry. Among the lines of work of Human 2.0, perhaps the best known is that of supporting the capabilities that humans have. Thus, we can talk about increasing human cognitive capabilities (example - augmented reality) and also physical capabilities (example -exoskeletons). And this last case is the one that we are going to evaluate in this study. The exoskeleton market was valued at USD 354.22 million in 2021, and it is expected to reach USD 1620.04 million in 2027, registering a CAGR of 12.5% during the forecast period (2022-2027). The development and production of exoskeletons requires the collaboration of experts from different fields, including engineers, medical professionals and designers. It is a task undertaken by specialized companies that focus on developing advanced exoskeletons that meet the needs of users. And finally, with all this analysis we have to think about the future of exoskeletons in the healthcare sector. Are they really going to satisfy the current needs of workers in the sector? Can their costs be assumed by health organizations? What will happen to the possible rejection of their use by patients? This and other questions must be answered in a very short period of time.
18
Dany-Knedlik, Geraldine, Oliver Holtemöller, Stefan Kooths, Torsten Schmidt, and Timo Wollmershäuser. "Gemeinschaftsdiagnose Herbst 2023: Kaufkraft kehrt zurück – politische Unsicherheit hoch." Wirtschaftsdienst 103, no. 10 (2023): 680–83. http://dx.doi.org/10.2478/wd-2023-0189.
Full textAbstract:
Abstract According to the Joint Economic Forecast, Germany’s gross domestic product will decline by 0.6% in 2023. This is a strong downward revision of 0.9 percentage points from the forecast made in spring 2023. The most important reason for this revision is that industry and private consumption are recovering more slowly than has been expected in spring. Germany has been in a downturn for more than a year. The sharp rise in energy prices in 2022 put an abrupt end to the recovery from the pandemic. However, wage increases have meanwhile followed the price hike, energy prices have fallen, and exporters have partially passed on their higher costs, so that purchasing power is returning. Therefore, the downturn is expected to subside by the end of the year.
19
Widjanarko, Bambang, Awan Panjinata, Agus Sukoco, and Joko Suyono. "Analyzing the Financial Performance of PT. Steel Pipe Industry of Indonesia Tbk." International Journal of Industrial Engineering, Technology & Operations Management 1, no. 2 (2023): 86–92. http://dx.doi.org/10.62157/ijietom.v1i2.32.
Full textAbstract:
The financial report is a vital tool for acquiring insights into a company's financial position and business performance. Through financial statement analysis, crucial indicators pertaining to the company's financial health are unveiled, rendering it a valuable resource for guiding financial decision-making processes and offering a comprehensive portrayal of the company's performance. This study evaluates the financial performance of PT Steel Pipe Industry of Indonesia Tbk. and forecasts the company's sales turnover over the next five years. This research adopts a quantitative descriptive approach, utilizing secondary data spanning from 2018 to 2022 from the PT Steel Pipe Industry of Indonesia Tbk. The data analysis process encompasses several stages, including (i) Ratio Analysis of Financial Reports from 2018 to 2022, (ii) Compilation of sales data, (iii) Projections of sales figures using the least squares method, and (iv) Forecasting profits for the period from 2023 to 2027. The findings of this study indicate that the PT Steel Pipe Industry of Indonesia Tbk. is facing challenges in its financial performance, as the ratio values consistently fall below industry-standard financial metrics. However, the company has demonstrated resilience in maintaining its profitability levels, evidenced by a 6% increase in profit percentage in 2021 compared to 2020. This can be attributed to the company's consistent profit generation efforts, resulting in year-on-year profit growth.
20
Alfyorov, S. Yu. "ANALYSIS OF THE GLOBAL COAL MARKET IN 1992–2023. FORECAST UP TO 2035." Geoeconomics of Energetics, no. 1 (April 8, 2025): 75–90. https://doi.org/10.48137/26870703_2025_29_1_75.
Full textAbstract:
The article presents a comprehensive analysis of coal consumption and production volumes from 1992 to 2023, with a detailed examination of the dynamics across countries and regions. The author identifies key players in the global coal market as well as the main trends in their development. Special attention is given to analyzing the factors driving transformations in the coal industry, including economic, ideological, geopolitical, and sanitary-epidemiological. The methodological basis of the study includes statistical analysis of coal production and consumption data by country, comparative analysis to assess the development dynamics of different countries and regions, factor analysis to determine the root causes of changes in the global coal market, and content analysis of official reports, statements, doctrinal documents, and other sources reflecting the state and prospects of the coal industry. Based on the obtained data and considering current trends in global economic development, the energy sector, and geopolitical processes, the article provides a forecast for the global coal market until 2035. The authors reason that during this period it is expected to form a stable trend to reduce the volume of coal production and consumption on a global scale. Special attention is paid to the forecast of the Russian coal market development. The presented findings and projections may be useful for researchers, analysts, policymakers, and the business community engaged in issues of energy security, the coal industry, and global economic development.
21
CHERNIAVSKYI, Ivan. "FORECASTING THE EXPORT POTENTIAL OF UKRAINIAN GRAIN INDUSTRY ENTERPRISES, TAKING INTO ACCOUNT THE LEVEL OF DEVELOPMENT OF DOMESTIC SELECTION." Ukrainian Journal of Applied Economics 4, no. 4 (2019): 199–208. http://dx.doi.org/10.36887/2415-8453-2019-4-23.
Full textAbstract:
The scientific article is devoted to the problem of forecasting the grain production volume and enterprise export potential of the Ukrainian grain industry (taking into account the development level of domestic breeding) for the medium term under 3 alternative scenarios. Grain sowing area was forecasted by 2023 using an adaptive forecasting model. The results of the conducted research show that by 2023 the area of corn sowing will increase to 4922 thousand hectares. The corn yield forecast for 2023 has been developed, which shows that the yield level will increase substantially. So, if in 2017 the yield of this crop was 61 hwt / ha, then on average in 2023 it will be 76.6 hwt / ha. It is established that yield is one of the main factors for increasing the volume of grain production. The forecast suggests that on average, corn grain exports from Ukraine tend to grow in the future, namely that it will grow by 11.8 % in 2023 compared to the 2018/2019 marketing year and amount to 30835 thousand tons. Under the optimistic scenario, corn production in the year 2023 will be 42536 thousand tons, which is 54.4 % more than in the 2018/2019 marketing year. The results of the study show that in the future (by 2023), the volumes of maize seeds use will increase – on average they will increase by 8 %, and by the optimistic forecast – by 25 % compared to the 2018/2019 marketing year and will amount to 585 thousand tons. The analysis shows that in 2019 there was a rapid development of both world and Ukrainian breeding. Thus, analyzing the varieties of the main grain crops, it should be noted that in the analyzed period the number of registered varieties suitable for distribution in Ukraine increased by 11.7 times, including the domestic ones – 10.5 times. Accordingly, maize grew 21.8 times and 14.4 times, respectively. It is worth noting a fairly high proportion of domestic wheat varieties, whose share is 72 %. What cannot be said for other crops, in particular, the share of domestic varieties is only 47 %. In the medium to long term, Ukraine can increase its seed exports by a dozen times. Opportunities for capacity-building of seed plants are steadily increasing every year. Large seed companies, such as “Pioneer”, “Monsanto”, “Syngenta”, “Moisadur”, “Euralis Semens” and domestic “Mais”, “Eridon”, “Selena”, “Eurostandard”, have potential to attract foreign investments to bring Ukraine to the forefront in sales of cereal seeds (wheat, barley, oats, rye and corn) and oilseeds (sunflower, soybean, mustard and rapeseed). Key words: cereals, corn, corn seeds, forecasting, adaptive forecasting models, export potential, acreage, yield.
22
Liu, Yibing. "Financial Analysis and Strategic Forecast of Toyota." Advances in Economics, Management and Political Sciences 43, no. 1 (2023): 218–24. http://dx.doi.org/10.54254/2754-1169/43/20232167.
Full textAbstract:
One of the main forces boosting the nations economic expansion is the automobile industry. It has developed a respectable market share in the worlds four-wheeler businesses, which are essential to certain economic sectors. The one-year study period was the fiscal year of 2023, and the key information was gathered from the annual reports of the corporations-Toyota and its competitors. The paper analysis the Toyota Motor Corporation in four parts. Collected the evidence from the annual report, industry report and so in, the paper analysis the automobile corporation deeply. Firstly, the Introduction wraps up the companys history, development, business overview, and strategy. In accounting analysis, this paper analyzes some critical parts. I choose three critical items from the income statement and balance sheet to discuss the accounting records, Intangible incurred by R&D expenses, Vehicles and equipment on operating leases, and Revenue recognition. In the third part, this paper analyzes Toyota from four perspectives, liquidity, solvency, efficiency, and profitability with three ratios respectively. It argues for the current and future business, which gives the investor a deep understanding of Toyota and the automobile industry.
23
Wu, Xiaoran. "A Financial Valuation and Strategic Forecast on Nike, Inc." Highlights in Business, Economics and Management 34 (June 10, 2024): 58–63. http://dx.doi.org/10.54097/3sg56a84.
Full textAbstract:
The objective of this article is to evaluate Nike Inc.'s overall performance in the past three years and make predictions about its future prospects. Initially, this paper will analyze the three most significant accounting policies outlined in Nike's annual report for 2023. This analysis will assist us in determining the company's effectiveness in managing its assets, utilizing them, generating profits, and identifying long-term development trends. Furthermore, this paper will conduct a comparative assessment of various financial ratios with competitors within the Nike industry to gauge the company's performance in the previous year. This evaluation will provide valuable insights into Nike's financial position, operational achievements, and market standing. Finally, based on the comprehensive evaluation of Nike's overall performance in 2023, it will offer forecasts regarding its market value and future performance over the next two years. As a globally renowned sports goods brand known for its remarkable success thus far, Nike has strategically implemented a product portfolio strategy that has propelled it forward in terms of market advancements. The conclusion drawn from this article aims to enhance other sports goods brands' understanding of effective marketing strategies employed by Nike while fostering growth across the entire industry.
24
Barač Miftarević, Sandra. "Medical Tourism in Croatia." Journal of applied health sciences 8, no. 1 (2022): 121–31. http://dx.doi.org/10.24141/1/8/1/11.
Full textAbstract:
Recently, medical tourism became one of the rapidly growing industries globally with 25% growth yearly with the value of over 200 billion euros. North America, Asia and Europe hold the most significant share of this value. According to The Medical Tourism Market – Global Industry Analysis Report, the forecast by 2027 will be a value of 272.70 billion US dollars. Croatia has strong potential for developing the medical tourism industry as an integral and essential part of the whole tourism industry in Croatia. But, lack of political will and public sector efforts decrease these opportunities. Fundamental healthcare reform is needed and improves outdated infrastructure with low service quality, including accommodation and accompanying catering and recreational facilities. Health care tourism is not competitive in this exceptionally demanding market. Singapore, India and Turkey can be excellent examples of doing thing rights, showing the path to success to the Croatian medical tourism industry. Where is Croatia right now, and what can be done to move forward is a big question. Several authors offer possible solutions that can lead to achieving objectives and goals stated in the National Strategy for Development of Healthcare and Action Plan until 2028. The future development of the medical tourism industry is an exciting area both in applicative and scientific fields, which can encourage further scientific efforts to explore more deeply the subject.
25
Xu, Mingyu, Xin Lai, Yuying Zhang, et al. "An Integrated Hog Supply Forecasting Framework Incorporating the Time-Lagged Piglet Feature: Sustainable Insights from the Hog Industry in China." Sustainability 16, no. 19 (2024): 8398. http://dx.doi.org/10.3390/su16198398.
Full textAbstract:
The sustainable development of the hog industry has significant implications for agricultural development, farmers’ income, and the daily lives of residents. Precise hog supply forecasts are essential for both government to ensure food security and industry stakeholders to make informed decisions. This study proposes an integrated framework for hog supply forecast. Granger causality analysis is utilized to simultaneously investigate the causal relationships among piglet, breeding sow, and hog supply, as well as to ascertain the uncertain time lags associated with these variables, facilitating the extraction of valuable time lag features. The Seasonal and Trend decomposition using Loess (STL) is leveraged to decompose hog supply into three components, and Autoregressive Integrated Moving Average (ARIMA) and Xtreme Gradient Boosting (XGBoost) are utilized to forecast the trends, i.e., seasonality and residuals, respectively. Extensive experiments are conducted using monthly data from all the large-scale pig farms in Chongqing, China, covering the period from July 2019 to November 2023. The results demonstrate that the proposed model outperforms the other five baseline models with more than 90% reduction in Mean Squared Logarithm (MSL) loss. The inclusion of the piglet feature can enhance the accuracy of hog supply forecasts by 42.1% MSL loss reduction. Additionally, the findings reveal statistical time lag periods of 4–6 months for piglet and 11–13 months for breeding sow, with significance levels of 99%. Finally, policy recommendations are proposed to promote the sustainability of the pig industry, thereby driving the sustainable development of both upstream and downstream sectors of the swine industry and ensuring food security.
26
YUMASHEVA, E. I. "Market of Finishing and Thermal Insulation Materials in 2023." Stroitel'nye Materialy 819, no. 11 (2023): 75–79. http://dx.doi.org/10.31659/0585-430x-2023-819-11-75-79.
Full textAbstract:
The 15th annual conference of the Construction Information company took place in St. Petersburg on October 12–13, 2023. More than 120 representatives from 72 organizations from three countries took part in its work – commercial directors, heads of marketing departments, dealer centers, supply and sales specialists. Traditionally, the conference examines the results of the work of the Russian construction complex as a whole over the past year, as well as a number of sub-sectors of the building materials industry. The main results of the work of the industry of dry building mixtures, gypsum finishing materials, mineral and polymer-based thermal insulation materials, facade systems, paint and varnish materials, voiced in the reports of conference participants, are presented. The forecast for the development of these sub-sectors for the short term is also shown.
27
Kuznetsov, V. V., O. A. Kholodov, and T. I. Sharovatova. "Forecast parameters of the crop industry development in the Rostov region." Vektor nauki Tol'yattinskogo gosudarstvennogo universiteta. Seriya Ekonomika i upravlenie, no. 4 (2023): 5–17. http://dx.doi.org/10.18323/2221-5689-2023-4-5-17.
Full textAbstract:
The paper describes the forecast parameters of the sustainable development of the crop industry in the Rostov region, which determine the key trends of the agricultural sector of the region. The data of the Ministry of Agriculture and Food of the Rostov region, research papers and scientific publications on this problem were used as the analytical base for conducting the research. The research involved the analysis of the current state of the crop production industry in the Rostov region and an assessment of its resource potential. Studies have shown that the effective use of the existing resource potential of the industry in the region in conditions of its significant dependence on the imported seed material and technologies makes it possible to ensure sustainable qualitative dynamics of its development. The paper argues that the use of a scientifically based agricultural system makes allows stimulating positive dynamics of economic growth without additional financial investments. This scientifically based approach is the basis for the development of the forecast parameters for the crop production industry development. The process of forecasting based on trend modeling of crop yields and rationalization of the cropping plan, methods of chain substitutions, and expert assessments resulted in three forecast scenarios for the development of the industry: the first (target), the second (inertial) and the third (mixed). The implementation of the first (target) option involves an increase in the yield of cultivated crops, taking into account the use of high-quality seed material and optimal weather conditions, as well as the transition to a scientifically based structure of cropping pattern. The inertial option is based on the rationalization of the agricultural land structure while maintaining the current yield. The mixed variant is characterized by an increase in yield with a constant structure of the area of sowing. The most preferred and promising option for the crop production industry in the Rostov region is the implementation of the target option. Ignoring the science-based approach in the long term prevents from full unlocking the regional potential of the industry.
28
Kasatkina, Ekaterina, Daiana Vavilova, and Rinat Faizullin. "Development of econometric models to forecast indicators of the livestock industry." E3S Web of Conferences 548 (2024): 03002. http://dx.doi.org/10.1051/e3sconf/202454803002.
Full textAbstract:
The article discusses the importance of animal husbandry in ensuring food security and maintaining a high quality of life. In the current study, statistical monthly data on animal husbandry in the Udmurt Republic from 2018 to 2023 is analyzed to create models for forecasting key indicators: the average daily milk yield, the number of cows, and the total volume of milk production. The model of the average daily milk yield takes into account seasonal fluctuations, temperature, and time trends, with an average relative error of just 1.55%. The autoregressive model for predicting the number of cattle with a lag of 12 months has shown high accuracy with an average relative approximation error of 0.19%. The econometric model of total milk production takes into account the average daily milk yield and other factors, demonstrating high accuracy in its forecasts. These results are important to support decision-making on the development of animal husbandry and the agricultural sector in general.
29
Loseva, A. V., and G. I. Gadzhimirzoev. "Dynamics and prospects of development of China’s fishing industry and its role in the global economy." Trudy VNIRO 194 (January 22, 2024): 218–27. http://dx.doi.org/10.36038/2307-3497-2023-194-218-227.
Full textAbstract:
Objective: to reflect the retrospective, current and prospective state of the fishing industry in China, to assess the existing trends and highlight their key factors.Method: general scientific methods of analysis and synthesis, as well as methods of statistical processing, analysis and visualization of data were used.Novelty: the main factors and conditions that ensure the progressive growth of the fishing industry in China are identified; a forecast model for the growth of fish production is constructed.Results: The key indicators of China’s fishing industry in retrospect and the current state are analyzed; a quantitative characteristic of China’s position in the global fishing industry and trade in fish products is given; a quarterly forecast of the output of the country’s fishing industry is constructed based on modeling of dynamics series with seasonal components. The key guidelines of the Chinese government regarding the development of the industry, implemented within the framework of five-year planning, aimed at reducing the burden on the environment, restructuring the industry towards increasing the scale of aquaculture, qualitative improvement of the industry on the basis of innovative technological potential and scientific developments, are disclosed.Conclusions are drawn about the multiplicative effect of modern transformations in the fishing industry of China, significant both for the national and for the global economy as a whole.
30
Thomakos, Dimitrios D., Marilou Ioakimidis, and Konstantinos Eleftheriou. "Forecasting Tourism Demand for Medical Services." Journal of Developing Areas 57, no. 3 (2023): 315–20. http://dx.doi.org/10.1353/jda.2023.a907749.
Full textAbstract:
ABSTRACT: Medical tourism is considered nowadays as a multi-billion industry which can promote a country's economic growth. Therefore, forecasting the scheduled tourism demand for medical services is of great importance for policy makers. Doing so, however, is not an easy task due to the following reasons: Data on medical tourism are (i) not easily accessible; (ii) not typically distinguished from tourists' non-scheduled (unintentional) use of a country's medical services; and (iii) usually not publicly available for long time periods. In this paper, we present a novel way to forecast tourism demand (intentional and unintentional) foro medical services —a rough but informative proxy of medical tourism— using limited data. To perform the analysis, we use data on the percentage of hospital discharges of non-residents for 17 European countries over the period 2008-2019 retrieved from Eurostat. Our methodological approach is based on a forecasting technique recently developed by Kyriazi, Thomakos and Guerard ; the adaptive learning forecasting. According to this method, MSE (Mean Squared Error)-performance enhancements can be achieved using any forecast as input —as long as that input is not a 'perfect' forecast— by learning from past forecast errors. Within this context, even the most basic forecast, the no-change or naïve forecast, can be used as input to the adaptive learning procedure. Kyriazi, Thomakos and Guerard approach is very well suited to our research question because (i) the no-change forecast is a natural candidate in a short time series where models cannot be estimated with sufficient accuracy, (ii) the no-change forecast is obviously far from being the 'perfect' forecast, and (iii) the adaptive learning process can be initialized by the no-change forecast and then learn by its own past forecast errors. Our results show that adaptive learning forecasting leads to performance enhancements that range from the 5% to more than 20% relative to the no-change benchmark. This finding indicates the efficiency of the adaptive learning method in forecasting medical tourism demand; an important subcategory of tourism demand for which data are not easily accessible and freely available historical data are existing for short time periods.
31
Ladan, Musa Sanni, Yohanna Tella, and Oluwagbenga Falola. "Time Series Analysis on Monthly Production of Crude Oil in Nigeria." Journal of Science Research and Reviews 1, no. 2 (2025): 1–13. https://doi.org/10.70882/josrar.2024.v1i2.8.
Full textAbstract:
This study delves into a comprehensive time series analysis of the monthly production of crude oil, in Nigeria, a critical component of the country’s economy and a significant player in the global oil market. Understanding patterns, trends, and dynamics of crude oil production is essential for policymakers, industry stakeholders, and researchers to make informed decisions and forecasts. The research utilizes monthly secondary data on crude oil production in Nigeria, collected from the Nigeria National Petroleum Cooperation (NNPC) annual statistical bulletin 2010 and 2023 respectively, to explore various aspects of the time series, including seasonality, trends, and potential forecasting models. Minitab 17.0 was applied to run the data, advanced time series model, ARIMA (Auto-regressive Integrated Moving Average) was employed using the Box-Jenkins approach for crude oil production in Nigeria from January 1999 to June 2023 to forecast future production levels based on the historical data patterns. ARIMA (2,1,1) model was the best model fitted to the crude oil production data. The pattern showed that the model fitted for this study is adequate since the P-value can be seen from table 2 is greater than 0.05. The result indicates that the forecasted values of crude oil production fluctuate steadily.
32
Zasuhina, Ol'ga, Anna Terekhova, Grigory Shitenkov, Leonid Golovatiukov, Nikolay Malinin, and Alexandra Khukhryanskaya. "FORECAST, DEVELOPMENT AND PROSPECTS FOR DIGITALIZATION IN THE ELECTRIC POWER INDUSTRY." Bulletin of the Angarsk State Technical University 1, no. 17 (2023): 22–27. http://dx.doi.org/10.36629/2686-777x-2023-1-17-22-27.
Full textAbstract:
Solutions, trends and opportunities for digitalization in the energy industry, and information se-curity issues are considered. An analysis of new national standards in the information sphere is provided
33
Şeker, Ferhat. "Combining the power of artificial intelligence and mathematical modelling: A hybrid technique for enhanced forecast of tourism receipts." European Journal of Tourism Research 36 (November 1, 2023): 3614. http://dx.doi.org/10.54055/ejtr.v36i.3246.
Full textAbstract:
Despite being one of the most visited countries in the world, Türkiye's share of tourism revenue does not rank among the top ten. Therefore, it would be worth researching tourist expenditures and analysing this data could provide valuable insights. This research develops a novel approach to estimating and modelling tourism receipts by analysing expenditure types. Artificial intelligence-based methods, such as machine learning, have been increasingly used in the tourism literature to improve various aspects of the industry. However, little research has been conducted using a hybrid method to model and estimate tourist expenditure. This paper is the first to combine conventional mathematical analysis, specifically first-order two-variable polynomial equations, with artificial intelligence-based machine learning algorithms in a tourism setting. The research results indicate that expenditure types such as accommodation and food & beverage significantly impact Türkiye's tourism revenue and Türkiye's total tourism revenue will not exceed 45 billion dollars by 2027. This study provides a valuable and practical contribution to improving the accuracy and efficiency of methods for managing tourism economics, particularly in European countries where the economy heavily relies on income generated by tourism. Additionally, it fills a gap in studies focused on tourists' expenditure types by combining artificial intelligence and traditional analysis, making it a unique piece of research.
34
Palka, Dorota, Peter Blistan, and Henryk Badura. "Forecast of the Maximum Methane Concentration in the Longwall Outlet and in the Ventilation Roadway. Case Study." Management Systems in Production Engineering 31, no. 4 (2023): 398–403. http://dx.doi.org/10.2478/mspe-2023-0044.
Full textAbstract:
Abstract The mining process of the coal seam wall is accompanied by the release of methane into the mine atmosphere. This process is highly variable and depends on the methane content in the seam and the methane saturation of the rocks surrounding the seam. This is the specificity of the Polish hard coal mining industry. In the article, prognostic formulas for the maximum methane concentration at the outlet of the longwall ventilation gallery were developed. In the presented article, these formulas were used to predict methane concentration at the longwall outlet and in the ventilation gallery at a distance of up to 10 m in front of the longwall. In order to assess the accuracy of the forecasts, their results were compared with the forecast at the exit of the ventilation roadway. The obtained results are so accurate that it is worth repeating this type of check also using measurements in other longwalls. It will allow to reduce the risk of methane explosion during operation.
35
Xiao, Qiang, and Hongshuang Wang. "Prediction of WEEE Recycling in China Based on an Improved Grey Prediction Model." Sustainability 14, no. 11 (2022): 6789. http://dx.doi.org/10.3390/su14116789.
Full textAbstract:
Accurate waste electrical and electronic equipment (WEEE) recycling forecast is an essential reference for optimizing e-waste industry layout and division of labor policies, conducive to better guiding enterprises’ recycling activities and improving the efficiency of WEEE recycling in China. The nonlinear grey Bernoulli model (NGBM (1,1)) was constructed by analyzing the recycling data characteristics of WEEE from 2012 to 2020, and a particle swarm optimization (PSO) algorithm was introduced to solve the model parameters and optimize the background value coefficients. The prediction results were compared with other grey prediction models to verify the effectiveness of the improved NGBM (1,1) model for WEEE recycling prediction in China and the applicability of the PSO algorithm for improving the prediction accuracy of each grey model. Statistical data were used to forecast the WEEE recycling volume in China from 2021 to 2023, and the results show that the value of WEEE recycling will continue to grow at 9%. The value of recycling will reach 16 billion yuan by 2023, while the value of WEEE recycling will see a slight decline. Based on the calculation results, the WEEE recycling industry development trend is predicted to guide the promotion of the WEEE industry recycling program and the national circular economy program.
36
YASHALOVA, Natal'ya N., and Denis M. TAVRIKOV. "Hardware industry of the Russian Federation: History of formation, current situation and forecast of development." Economic Analysis: Theory and Practice 23, no. 11 (2024): 2086–99. https://doi.org/10.24891/ea.23.11.2086.
Full textAbstract:
Subject. The article discusses the economics of the hardware industry of the Russian Federation. Objectives. The study aims at the forecast assessment of production volumes of hardware products in Russia, based on the analysis of strategic planning documents for the development of the main related sectors of the economy, using steel and wire products in their operations (construction, transport, energy, industry, agriculture). Methods. The study draws on research methods, like monographic, statistical and economic, systems analysis, and forecasting. Results. We considered the main aspects of the hardware industry development in the era of the USSR and at the present time. Currently, the production of hardware has decreased fourfold, as compared to the Soviet period. The findings are important for planning the strategic development of the hardware industry and devising the industry support measures. Conclusions. According to the forecast analysis of the steel and wire production in the Russian Federation for 2030–2035 that rests on planned indicators of the branches of the national economy being the main consumers of hardware, the hardware industry should increase production volumes by 32% by 2030–2035 relative to 2023.
37
Zhou, Zhenghan. "A Review of the Global Economic Shock in 2022 and a Prediction of the Global Economic Development in 2023." Advances in Economics, Management and Political Sciences 21, no. 1 (2023): 142–52. http://dx.doi.org/10.54254/2754-1169/21/20230246.
Full textAbstract:
In 2022, affected by global macroeconomic fluctuations, the economies of some countries around the world have experienced obvious fluctuations, thereby promoting inflation in various countries and limiting the rapid development of some industries around the world. This paper reviews the global economic shock in 2022 and analyzes the impact of China's economy on global economic development from the perspective of the new energy sector. As an important part of new energy, the photovoltaic industry can be analyzed to obtain a development forecast of the global economy in 2023. By analyzing the development of the photovoltaic industry, it is concluded that China's economy and the global economy will show a recovery trend in 2023.
38
Lukomets, Artem. "TOOLS FOR IMPROVING RESOURCES IN PLANT PRODUCTION." Vestnik of Kazan State Agrarian University 18, no. 3 (2023): 180–85. http://dx.doi.org/10.12737/2073-0462-2023-180-185.
Full textAbstract:
Targeted and regulated management of crop production development and its resource support on the basis of the organizational and economic mechanism contributes to the achievement of goals with optimal resource consumption. As the methodological base of the study, general scientific methods, works of domestic and foreign scientists on crop production and products of its processing were used. The article considers tools for improving resource support as elements of the organizational and economic mechanism for the development of the industry. Tools for improving the resource support of crop production are an integral part of the organizational and economic mechanism and should be aimed at creating conditions for the reproduction process in the industry and import substitution of certain types of resources. The proposed tools are organized by groups corresponding to subsystems of the crop industry: technological, economic, social, environmental, organizational. The developed forecast for the development of the crop industry and the proposed measures of the organizational and economic mechanism were assessed by calculating structural shifts. Structural shifts make it possible to estimate the efficiency of shifts in the actual and predicted structure. The calculation of the shift efficiency indicates that the structure of commodity production in the forecast year within the forecast confidence interval will not change significantly, which indicates that the structure of crop production is balanced. The projected growth of crop production within the confidence interval will affect the growth of the industry's profitability by only 0.99% to 57.15%. Profitability growth is projected due to an increase in the share of oilseeds and a reduction in the share of other crop products in the structure of marketable products.
39
Zhou, Kai, Zihao Li, and Zhaofeng Liu. "Trajectory Of Development in China's New Energy Vehicle Industry Through Data Analysis and Expectation." Highlights in Science, Engineering and Technology 96 (May 5, 2024): 132–38. http://dx.doi.org/10.54097/06ad5c42.
Full textAbstract:
Amidst a global shift towards sustainable transportation, this study conducts an in-depth analysis of data about China's new energy vehicle (NEV) sector from 2013 to 2022. This research primarily evaluates the standards and key factors influencing the NEV industry's evolution. Spearman correlation and decision tree models indicate that the average price of new energy vehicles and the government subsidies for them have the most significant impact on the development of the new energy industry in China. Expanding on these insights, a robust LASSO linear regression model was developed to further explore these dynamics. Additionally, an ARIMA time series model was employed, leveraging historical data to forecast the factors likely to influence the NEV industry in the coming decade. Integrating these forecasts into the initial evaluation model, the study anticipates a positive growth trajectory for China's NEV development, especially between 2023 and 2025. This research not only sheds light on the current state of the NEV industry in China but also provides valuable predictions for its future direction, contributing to the broader understanding of sustainable vehicle evolution in the global context.
40
Byastinova, L. M. "The use of Multifactor Regression Models in Forecasting in the Agricultural Sector of Yakutia." Vestnik of North-Eastern Federal University Series "Economics Sociology Culturology, no. 4 (December 20, 2023): 102–10. http://dx.doi.org/10.25587/2587-8778-2023-4-102-110.
Full textAbstract:
Under the constantly changing economic conditions of management, ensuring food security in the country, as well as in the regions becomes especially relevant. Agriculture is the only industry that is able to bring countries into a state of complete self-sufficiency, which is clearly indicated in the Doctrine of Food Security of Russia. With this in mind, the intensification of agricultural sectors, through the introduction of new technologies and improving the quality of land use is a particularly topical challenge. In this regard, the state faces the issues of the development of the industry and scientific forecast of its main indicators, taking into account the existing factors and conditions. This article provides a detailed methodology for developing a forecast for the agricultural sector using multivariate regression models. The main factors influencing the indicators of agriculture are considered, the main ones are highlighted and a multifactorial regression model is developed to forecast the indicator of gross agricultural output for the next five years. Recommendations are given for improving the application of this method in relation to the region under consideration.
41
Khrulkov, D. V. "Using the Indicator ‘Economiic Level of Technology’ in Managing Industrial and Technological Systems in Consumer Goods Industry." Vestnik of the Plekhanov Russian University of Economics 20, no. 2 (2023): 202–11. http://dx.doi.org/10.21686/2413-2829-2023-2-202-211.
Full textAbstract:
The article studies issues of assessing efficiency of production and technological systems (enterprises) in consumer goods industry. Sanction restrictions built new challenges for customer goods industry but at the same time opened new opportunities. The drawback of the current approaches to managing enterprises of customer goods industry is the absence of dynamic appraisal of the technological process quality, which can cause a delayed response to crisis phenomena. To provide efficient management it is proposed to use the indicator ‘economic level of technology’ (ELT) that implies complex assessment of quality and efficiency of the production and technological system. Advantages of this indicator include possibility to forecast the development of production on the basis of due regard to laws of technological process development. With the help of calculations illustrated by two enterprises of microlevel, i.e. the transnational company Nike and the Russian company Dochki Synochki, as well as the US macroeconomic system it was proved that this indicator of efficiency can forecast arising of crucial trends in operational work of the enterprise and economy in general. Taking into account problems facing enterprises of customer goods industry ELT indicator could be used to raise effectiveness of managerial decision-making on the enterprise level and industry and state level in view of target support of development.
42
Sonea, Cosmin, Dana Tapaloaga, Raluca Aniela Irimia Gheorghe, Maria Rodica Gurau, and Paul-Rodian Tapaloaga. "Milk Production Forecast Analysis in Romania - A Problem to Possible Solutions Approach." Annals of "Valahia" University of Târgovişte. Agriculture 15, no. 1 (2023): 9–12. http://dx.doi.org/10.2478/agr-2023-0003.
Full textAbstract:
Abstract Romania is a country located in southeastern Europe, known for its rich history, culture, and agriculture. One of the most important agricultural sectors in this country is milk production. In recent years, the milk production industry has faced numerous of challenges. In this direction, the aim of our paper was to use the exponential smoothing method of forecasting in order to analyse the milk production future trends, based on empirical data provided by FAOSTAT, and to provide some insights regarding possible solutions. According to our observations, in the following period (2023-2033) the milk production tends to slowly decline, situation that impose some measures. In conclusion, regarding the forecasted situation, Romania can avoid the milk production decline and improve the current situation by adopting and implementing some preventive measures.
43
Chen, Yuanyuan, Mohammad Affendy Arip, and Nor Afiza Abu Bakar. "Cold Chain Logistics Demand Forecasting for Fresh Agricultural Foods in Fujian Province, China." International Journal of Religion 5, no. 5 (2024): 78–84. http://dx.doi.org/10.61707/e1m9vh53.
Full textAbstract:
China's current cold chain infrastructure for fresh agricultural products faces numerous challenges, particularly within the context of Fujian Province. The cold chain logistics sector in the region is characterized by limited development and requires immediate improvements in its foundational supporting infrastructure. The establishment of a comprehensive cold chain logistics system tailored for fresh agricultural goods remains incomplete, resulting in inefficiencies within the supply network. An in-depth examination of the necessity for refrigerated transportation networks for fresh agricultural products through scientific inquiry reveals the potential for strategic investments in the industry. To address this gap, a study employing the GM (1,1) model is conducted to forecast the future demand for cold chain logistics in fresh agricultural items specifically within Fujian Province, China, over the next five years. The findings of the study indicate that by 2027, the demand for cold chain logistics services for fresh produce in Fujian Province is projected to reach 4765.6 million tons. These insights furnish valuable information for optimizing investment planning in cold chain logistics infrastructure and formulating pertinent legislative measures to stimulate industry growth. In summary, the integration of these findings into the context of Fujian Province underscores the significance of enhancing cold chain logistics capabilities to address existing challenges and capitalize on future opportunities within the region's fresh agricultural sector.
44
Młody, Michał, Milena Ratajczak-Mrozek, and Maja Sajdak. "Industry 4.0 technologies and managers’ decision-making across value chain. Evidence from the manufacturing industry." Engineering Management in Production and Services 15, no. 3 (2023): 69–83. http://dx.doi.org/10.2478/emj-2023-0021.
Full textAbstract:
Abstract The paper aims to identify how Industry 4.0 technologies affect the quality and speed of the managers’ decision-making process across the different stages of the value chain, based on the example of the manufacturing sector. The paper adopts qualitative research, based on nine in-depth interviews with key informants, to capture senior executives’ experiences with implementing Industry 4.0 technologies in their organisations. The research is focused on three manufacturing industries: the automotive, food and furniture industries. The research shows that depending on the stage of the value chain, different Industry 4.0 technologies are more suitable for the support of managers’ decisions. Various Industry 4.0 technologies support decision-making at different stages of the manufacturing value chain. In the Design stage, 3D printing and scanning technologies play a crucial role. In the case of Inbound Logistics, robotisation, automation, Big Data analysis, and Business Intelligence are most useful. During the Manufacturing stage, robotisation, automation, 3D printing, scanning, Business Intelligence, cloud computing, and machine-to-machine (M2M) integration enable quick decision-making and speed up production. Sensors and the Internet of Things (IoT) optimise distribution in the Outbound Logistics stage. And finally, Business Intelligence supports decisions within the Sales and Marketing stage. It is also the most versatile technology among all particular stages. The paper provides empirical evidence on the Industry 4.0 technology support in decision-making at different stages of the manufacturing value chain, which leads to more effective value chain management, ensuring faster and more accurate decisions at each value-chain stage. When using properly selected Industry 4.0 technologies, managers can optimise their production processes, reduce costs, avoid errors and improve customer satisfaction. Simultaneously, Industry 4.0 technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks. This knowledge allows organisations to make better decisions and take proactive actions to prevent problems.
45
Satryo Muhammad Alfaizin, Putri Savitri, Dita Agustin, and Yandafiq Muntafa. "Analisis Prediksi Penjualan Menggunakan Metode Fuzzy Mamdani dan POM-QM : Studi Kasus pada CV Mamifood Sukses Abadi." Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika 3, no. 1 (2024): 48–59. https://doi.org/10.61132/jupiter.v3i1.655.
Full textAbstract:
In the increasingly competitive Industry 4.0 era, companies need to forecast product demand to meet consumer needs and improve operational efficiency. CV Mamifood Sukses Abadi, an MSME that produces milk and cheese-based foods, has faced sales fluctuations in the last two years, thus requiring accurate forecasting to plan production strategies and resource management. This research aims to forecast demand using the Fuzzy Mamdani method and the POM-QM application. Fuzzy Mamdani was chosen for its ability to handle decision-making with multiple criteria and balanced weights, while POM-QM was used to validate predictions through quantitative methods. Product sales data for the years 2022 and 2023 were analyzed to produce accurate forecasts. The methods used include Moving Average for forecasting and evaluation of the results using MAPE. The analysis results show that the Moving Average method with N = 2 produces a MAD value of 402.523 and a MAPE of 22.155%, while the results of Fuzzy Mamdani show that product demand in the next period tends to decrease. This research is expected to provide insight for CV Mamifood Sukses Abadi in planning a more efficient production strategy.
46
Oba, K. M. "A Predictive Model for POP Cement Prices in the Nigerian Construction Industry." Journal of Engineering Research and Reports 25, no. 12 (2023): 14–23. http://dx.doi.org/10.9734/jerr/2023/v25i121037.
Full textAbstract:
This study was aimed at formulating a model to predict the price of Plaster of Paris (POP) cement using a multiple linear regression modelling technique. The prices of POP cement were predicted between the fiscal years 2024 and 2030, given the prices between the fiscal years 2017 and 2023. Secondary data were obtained for the Interest Rates, Inflation Rates, Naira exchange rates against the US Dollar, Population growth rates, and Gross Domestic Product (GDP) growth rates between 2017 and 2023. Primary data were obtained to investigate the prices at which POP was sold between the fiscal years 2017 and 2023. Exponential trends forecasting was used to forecast the above decision variables or factors affecting the price of POP cement between 2024 and 2030. A multiple linear regression model was derived for the prediction of the POP cement prices between the said years. The model was found fit, adequate, and of a high predictive attribute with an R2 value of 0.99. This study will help in the proactive planning of effective cost management for building construction projects in which POP cement was used. It will reduce problems and challenges of cost overrun on construction projects in the Nigerian construction industry.
47
Gu, Weifan, Baohua Guo, Zhezhe Zhang, and He Lu. "Civil Aviation Passenger Traffic Forecasting: Application and Comparative Study of the Seasonal Autoregressive Integrated Moving Average Model and Backpropagation Neural Network." Sustainability 16, no. 10 (2024): 4110. http://dx.doi.org/10.3390/su16104110.
Full textAbstract:
With the rapid development of China’s aviation industry, the accurate prediction of civil aviation passenger volume is crucial to the sustainable development of the industry. However, the current prediction of civil aviation passenger traffic has not yet reached the ideal accuracy, so it is particularly important to improve the accuracy of prediction. This paper explores and compares the effectiveness of the backpropagation (BP) neural network model and the SARIMA model in predicting civil aviation passenger traffic. Firstly, this study utilizes data from 2006 to 2019, applies these two models separately to forecast civil aviation passenger traffic in 2019, and combines the two models to forecast the same period. Through comparing the mean relative error (MRE), mean square error (MSE), and root mean square error (RMSE), the prediction accuracies of the two single models and the combined model are evaluated, and the best prediction method is determined. Subsequently, using the data from 2006 to 2019, the optimal method is applied to forecast the civil aviation passenger traffic from 2020 to 2023. Finally, this paper compares the epidemic’s impact on civil aviation passenger traffic with the actual data. This paper improves the prediction accuracy of civil aviation passenger volume, and the research results have practical significance for understanding and evaluating the impact of the epidemic on the aviation industry.
48
Wang, Shiyuan. "Analysis and Prediction of Online Beer Sales Based on SARIMA Model." BCP Business & Management 36 (January 13, 2023): 359–66. http://dx.doi.org/10.54691/bcpbm.v36i.3454.
Full textAbstract:
With the boom of e-commerce in China, online shopping has become the mainstream way of shopping in Chinese. To explore the impact of online shopping on beer sales, this paper uses a time series SARIMA model to analyze online beer sales data from January 2020 to September 2022 obtained from Internet platforms and predicts online beer sales from October 2022 to September 2023. This paper first introduces the current research on beer sales in China, and then briefly analyzes the current situation of the beer industry. Thirdly, based on the real data of beer online sales on the Internet platform, SARIMA model is used to forecast the sales volume of next year. The result shows that beer online sales are expected to show an upward trend, with the industry being the most competitive in June 2023, and a small sales peak both in November 2022 and January 2023 due to the e-commerce carnival. Therefore, beer online sales are significantly affected by seasonality and platform promotions.
49
Walicka, Monika. "Mapping Strategies of Net Working Capital in the Energy Sector in Poland – Transformation Perspective." Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu 68, no. 2 (2024): 51–61. http://dx.doi.org/10.15611/pn.2024.2.05.
Full textAbstract:
The aim of the article is to identify net working capital management strategies used in the energy sector. The analysis covered all companies listed on the Warsaw Stock Exchange under the WIG-Energy industry index. The study was conducted on the basis of financial reports for 2022-2023, with data from the latest reported quarters, i.e. Q1 and Q2 of year 2023, used in strategy mapping. The ratio analysis method was used with reference to industry indicators, and the dynamics of changes in the examined indicators was taken into account. The research results indicate that currently energy entities mainly use agressive strategies (64%). The sector's net working capital forecast indicates that the strong growth trend that has been seen since 2020 will gradually begin to slow down from 2023. As a result of using the indicator mapping technique, significant concentration of indictors can be noted in the sector, with only two entities differing from the rest of the sector in this regard.
50
ZHILINA, Ekaterina V., Anzhelika A. NIKITINA, Elena A. KHUNAFINA, and Ilyuza M. KHANOVA. "Regional specific features of the consumer sector of the economy." Regional Economics: Theory and Practice 19, no. 8 (2021): 1406–19. http://dx.doi.org/10.24891/re.19.8.1406.
Full textAbstract:
Subject. This article discusses the development of meat food market in Russia. Objectives. The article aims to define trends in the development of the meat industry, forecast the meat food consumption in Russia, and analyze the effect of various factors on the meat food consumption level. Methods. For the study, we used a statistical analysis. Results. The article presents the forecast of meat food consumption until 2023 and describes the dependence of meat consumption on a number of factors. Conclusions. Changes in consumer behavior patterns are affecting the meat food market. The direct relationship between the real incomes of the population and the level of consumption has a significant impact on the demand for meat products.