Industry Revenue Research Articles

The asymmetric impact of COVID-19: A novel approach to quantifying financial distress across industries

This paper assesses corporate financial distress in terms of liquidity and risk of insolvency due to the COVID-19 pandemic. We develop a novel multivariate approach to obtain monthly data on industry turnover, exploiting real time data to capture the atypical character of industry-specific disturbances. By combining the estimated set of industry revenue shocks with pre-pandemic financial statements, we quantify the impact of the pandemic on the risk of insolvency in the EU non-financial corporate sector. Our definition of risk of insolvency takes into account not only the equity position of firms, but also risks relating to overindebtedness. The analysis controls for firms that were financially vulnerable already before the pandemic, thus being prone to become at risk of insolvency also in absence of the COVID-19 turmoil. We find that, for the EU as a whole, 25% of firms exhausted their liquidity buffers by the end of 2021 (a practical cut-off date of the analysis, not an assumed end of the pandemic). Furthermore, 10% of firms which were viable before the pandemic, appear to have shifted into risk of insolvency as a result of the COVID-19 crisis. The magnification of financial vulnerability in the hardest-hit industries mainly occurs among firms with no legacy issues, i.e. firms with positive profitability pre-pandemic. A similar finding is reported for some of the hardest-hit countries, such as Italy and Spain. In other countries, such as Germany or Greece, the magnification of financial vulnerability mainly occurs among firms with negative profitability pre-pandemic.

Economic statistical strategies for the transportation industry based on time-varying parametric state space models

Abstract Under the new situation, the speed of economic development continues to accelerate, and under the influence of the modernization process, the transportation industry is more closely linked with the economy. To promote the sustainable development of the transportation industry, it is necessary to establish a scientific and effective economic statistics strategy to achieve steady economic growth. This paper designs a segmented time-varying parametric state space model based on the state space model to construct an economic statistical system for the transportation industry. By integrating and breaking the original design model, the structure, function, and statistical process of the system are optimized. The system is introduced into the transportation industry to analyze the application effect. According to the data, the economic revenue of the railroad transportation industry reached 464.293 billion yuan at the end of 2021, 45.48 times more than that of 10,208.81 billion yuan in 1986, and the market share increased from 23.23% in 2000 to 31.19% in 2021. The market share of waterway transportation industry, on the other hand, rose from 29.07% in 2000 to 32.87% in 2021. The share of capital investment in waterways and civil aviation continues to change in a downward trend from about 11% in the previous period. The economic statistics strategy can improve the economic efficiency of the transportation industry, so that the whole industry can gradually adapt to the current level of economic development and the needs of people’s life.

THE WORLD MARKET OF METAL CASTINGS 2019―2021: COUNTRIES, ALLOYS, TECHNOLOGIES

The analysis of the world market of metal castings in 2019–2021 is presented. Due to the fact that as of January 2022 the publication of the world statistics of the production of metal castings did not take place, an analysis of information was carried out regarding the results in the countries that are part of the global Top-10. Among them are China, India, USA, Germany, Japan, Turkey and Brazil. It is noted that in 2021 in China, 54.05 million tons of castings were produced, which is 4.0% more than in 2020. In terms of cast alloys: gray cast iron (share 41.7%), cast iron with nodular graphite (29.5%), aluminum and magnesium alloys (13.3%) and steel (12.2%). In India, the export of metal castings in terms of value for the period from 2016/2017 financial year (FY) to 2020/2021 F. increased from 2.366 to 2.865 billion USD, i.e. with a CAGR of 3.9%. In the USA for the period from 2013 to 2019 the income of the foundry industry increased from 38.7 to 44.3 billion USD, that is, with an average annual growth rate (CAGR) of 1.9%. Under the influence of the COVID-19 pandemic and the slowdown of the economy in 2020. industry revenue decreased to USD 36.7 billion (-17.1% vs. 2019). However, in 2021 the situation improved somewhat ― 43.4 billion USD (18.3% against 2020). In Germany, the production of castings from ferrous metal alloys (gray cast iron, with nodular graphite, malleable and steel) in 2021. amounted to 3.2 million tons, which is 16.4% more than in 2020. At the same time, for the period 2019-2021 production of the specified castings decreased at an average annual rate (CAGR) of -6.0%, and their export ― by -7.0%. In Japan, as a result of the changing economic situation in the world, which was formed after 2019, the production of castings during 2019-2021. is characterized by a downward trend. The production of castings from copper alloys decreased with an average annual rate (CAGR) of -5.6%, castings from aluminum alloys ― -5.1% and castings from iron alloys ― -1.5%. In Turkey in 2021 1.108 million tons of nodular cast iron castings (by 29.6% vs. 2020), 0.921 million tons of gray iron castings (by 49.1%) and 0.279 million tons of steel castings (by 45, 4%). In general, during 2019–2021 the production of castings from ferrous metal alloys in the country increased at an average annual rate (CAGR) of 9.9%. In Brazil, in 2021, foundry enterprises produced 2.5 million tons of castings, which is 21.1% higher than in 2020. At the same time, the production of castings from cast iron increased by 25.5%, from non-ferrous metal alloys ― by 7.0%, and steel ― by 3.9%. In general, during 2019–2021 the production of castings in the country increased at an average annual rate (CAGR) of 3.1%. The presented data indicate that in 2021 the global foundry industry developed in a positive trend. Estimated global production of castings from ferrous and non-ferrous metals by the end of 2021. may amount to 109.2...118.5 million tons against 105.5 million tons in 2020. However, as a result of the war between Russia and Ukraine, a number of negative factors have arisen that will cause a slowdown in foundry production in 2022–2023. The review also presents information about the world’s leading foundry companies, as well as examples of the use of 3-D printing in foundry production in the United States and Great Britain.

Economic Impacts of Offshore Wind Farms on Fishing Industries: Perspectives, Methods, and Knowledge Gaps

AbstractOffshore wind farms (OWFs) are rapidly developing as an alternative energy source globally and in the Greater Atlantic region of the United States. Despite the pace of development, there are still many uncertainties surrounding best practices in assessing the economic impacts of offshore wind on regional fishing industries. This work aims to provide an overview and assessment of industry perceptions, methods, results, and knowledge gaps pertaining to economic areas of concern related to interactions between OWFs and fishing industries in the region. We provide a compilation of studies focusing on industry perceptions and impacts of OWFs on the fishing industry, focusing on four key economic areas of interest: fuel expenditures; insurance costs; fishing industry revenues, income, and livelihoods; and fishing support businesses. Our findings suggest four overarching knowledge gap themes that persist across all economic areas of focus: (1) a lack of economic data or economically centered data collection efforts, (2) minimal works aiming to quantify the economic impacts of key areas of concern, (3) a lack of peer‐reviewed models and methods in quantifying economic impacts, and (4) limited syntheses containing best practices or lessons learned associated with quantifying the comprehensive economic impacts posed by OWFs on fisheries. This article aims to build awareness in areas where interdisciplinary collaboration can take place as well as serve as a foundation for informing best practice guidance as it pertains to assessing economic impacts imposed by OWFs on the fishing industry.

Statistical Analysis of Korean Welding Industry (V)

In this study, the revenue and import/export status of the domestic welding industry between 2017 and 2022 was analyzed using statistics provided by the Korea International Trade Association (KITA) and Korea Statistical Information Service (KOSTAT). The welding industry can be categorized into the welding equipment/consumables industry and welding process industry, which is part of the manufacturing process in the welding application industry. The welding process industry statistics are difficult to extract from the welding application industry statistics; therefore, they were calculated using the ratio of the welding-related expenditure to the total application industry expenditure. The welding industry's revenue, exports, and imports have recently recovered after hitting a low point during the COVID-19 pandemic. Moreover, the increase in the welding process industry imports and exports in the electronics industry offset the decrease in those of the shipbuilding and offshore industry for the specified investigation period.

Core English skills affecting Korean hoteliers’ perceived language proficiency

Fluency in English is a crucial asset in today"s highly competitive hotel industry. However, despite the significant contribution of the hotel sector to the country"s tourism industry revenue, there is a lack of knowledge regarding the usage and proficiency of English among Korean hoteliers. Therefore, the aim of this study is to thoroughly examine the usage frequency of four English skills and the perceived level of proficiency of Korean hoteliers by investigating both strong and weak skills. The study reveals that listening, speaking, reading, and writing skills are all essential in the hotel industry, but their frequency of use and proficiency level vary depending on the department, position, and hotel brand. Senior managers demonstrated the highest English proficiency, highlighting the importance of English for career development. However, this study also identifies a critical deficiency in confidence in listening skills and knowledge of grammar and sentence structure, in contrast to a high level of linguistic politeness. The respondents" ability to understand vocabulary spoken by guests and to utilize it in writing, constructing sentences, and speaking naturally were found to impact their overall perception of English proficiency. Based on the research findings, the study provides implications for English education to enhance the competitiveness of Korean hoteliers.

Measuring the performance of SMEs during the pandemic situation using system dynamic

PurposeThis study aims to create a system dynamics simulation model to forecast the performance of small and medium-sized enterprises (SMEs) if some decision-making is executed to reduce the negative of the coronavirus disease 2019 (COVID-19) pandemic. In particular, this study will focus on SMEs that belong to the furniture industry because the furniture industry is one of the leading industries in Indonesia.Design/methodology/approachThe study develops a system dynamics-based model by using three subsystems, i.e. the “production subsystem,” “demand and revenue subsystem” and “raw material (or wood supply) subsystem.”FindingsThe best scenario is the third scenario which increases the capacity to the normal situation and government subsidy during and after the pandemic. This scenario gives the best performance for industry revenue and gross domestic product (GDP). However, for the government, the most significant expenditure occurs in the third scenario. This seems a trade-off for the government whether to save the wooden-based furniture industry by encouraging the industry to continue operating during the pandemic accompanied by high subsidies or limiting the activities of the wooden-based furniture industry to prevent the spread of COVID-19 by providing low subsidies.Research limitations/implicationsFirst, this study does not try to combine the system dynamics (SD) methodology with the other method or use a multi-methodology since SD has several limitations and the other method may have several advantages compared to SD. Second, the models used in this study do not consider the decline in forest area and quality. Third, the demand for wooden-based furniture is obtained from historical data on domestic and foreign sales and fourth, the model does not include the government budget as a constraint to make any subsidy to help the SMEs.Practical implicationsThis study provides essential insights into implementing the policies in the world pandemic situation when SMEs face lockdown policy.Social implicationsThe study revealed that relevant policy scenarios could be built after simulating and analyzing each scenario's effect on SMEs' performance during the pandemic.Originality/valueThis study will enrich the previous study on the impact of the pandemic on SMEs and the dynamic system modeling on SMEs. The previous study discussed the pandemic's impact on SME performance and the impact's analysis in isolation from the dynamic nature of SME owners' decisions or government policy. In this study, the impact generated from the pandemic situation could be different depending on the decision and policies taken by managers from SMEs and the government.

Modelling the Gross Domestic Product and the Per Capita Income of Türkiye using Autoregressive Deep Learning Networks

The gross domestic product and the per capita income are leading indicators regarding the income and the wealth of nations. The gross domestic product and the per capita income can be modelled dependent on various econometric data such as the export revenue, tourism revenue, trade deficit and the industrial revenue. In this work, an alternative and novel method is presented for the modelling of the gross domestic product and the per capita income. In this study, the gross domestic product and the per capita income are modelled autoregressively employing deep learning networks namely autoregressive deep learning networks. The input data of the developed deep learning networks are taken as the past values of the modelled variable making the deep learning networks effectively autoregressive models. As application examples of the autoregressive deep learning models, the gross domestic product and the per capita income data of Türkiye for the period of 1960-2021 are separately modelled. The autoregressive deep learning networks are developed in Python programming language. The coefficient of determination (R2), mean absolute error (MAE), mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the developed models are also computed. The plots of the results of the developed autoregressive deep learning models and the performance metrics of the models show that the developed autoregressive deep learning models can be utilized to accurately model the gross domestic product and the per capita income.

Kontribusi Penelitian Universitas terhadap Pendapatan Industri: Bukti Empiris dari Top University di Indonesia

Competition does not only occur in the business world, but universities also must compete against competition from both domestic and foreign universities. One important indicator for university ranking is industry revenue which reflects commercial value and strengthens university-industry collaboration. The purpose of this study is to obtain empirical evidence regarding the effect of teaching, research, and citations on industrial income. This study uses a multiple linear regression approach, using data from The Times Higher Education World University Ranking from 2019-2023 to get a sample of universities in Indonesia which are included in it. The results showed that teaching had no significant effect on industrial income, research had a significant positive effect on industrial income, and citations had a significant negative effect on industrial income.

Electrodialysis Deacidification of Acid Hydrolysate in Hemicellulose Saccharification Process: Membrane Fouling Identification and Mechanisms

Acid saccharification of hemicelluloses offers promising pathways to sustainably diversify the revenue of the lignocellulose biorefinery industry. Electrodialysis to separate inorganic acids from acid hydrolysate in the hemicellulose saccharification process could realize the recovery of sulfuric acid, and significantly reduced the chemical consumption than the traditional ion exchange resins method. In this work, the deacidification of corncob acid hydrolysate was conducted by a homemade electrodialysis apparatus. The results showed that: (1) more than 99% of acid can be removed through the electrodialysis process; (2) A non-negligible membrane fouling occurred during the electrodialysis process, which aggravated with the repeated batch running The final global system resistance rose from 15.8 Ω (1st batch) to 43.9 Ω (10th batch), and the treatment ending time was delayed from 120 min (1st batch) to 162 min (10th batch); (4) About 90% of protein, 70% of ferulate acid, and 80% of p-coumarate acid precipitated from the corncob acid hydrolysate during the electrodialysis process. The zeta potential of corncob acid hydrolysate changed from a positive value to a negative value, and an isoelectric point around pH 2.3 was reached. HSQC, FTTR, and GPC, along with SEM and EDS analysis, revealed that the fouling layers mostly consisted of hydrolysates of protein and lignin. The result of HSQC indicated that the membrane foulant may exist in the form of lignin-carbohydrate complexes, as the lignin component of the membrane foulant is in the form of p-coumarate and ferulate. From the result of FTIR, a strong chemical bonding, such as a covalent linkage, existed between the lignin and protein in the membrane foulant. Throughout the electrodialysis process, the increased pH decreased the stability of colloidal particles, including lignin and proteins. Destabilized colloidal particles started to self-aggregate and form deposits on the anion exchange membrane's surface. Over time, these deposits covered the entire membrane surface and the spaces between the membranes. Eventually, they attached to the surface of the cation exchange membrane. In the end, a suggestion to control and minimize membrane fouling in this process was discussed: lower pH as a process endpoint and a post-treatment method.

Modelling the Tourism Revenue of Türkiye Using Deep Learning Networks

The gross domestic product of countries plays a key role in the development and wealth of nations. There are several components of the gross domestic product, such as industrial revenue, revenue from services, and tourism revenue. Türkiye is located in Anatolia, which is very rich from a historical viewpoint. Therefore, Türkiye attracts tourists from all over the world, making its tourism revenue an important contributor to its gross domestic product. This study aimed to model the tourism revenue of Türkiye using machine learning methods. In this study, the tourism revenue of Türkiye, dependent on the number of tourists, oil prices, and the exchange rate, are modelled for the period of 2008-2022. The data of these variables were taken from official sources, and then the causality analyses were carried out. As the next step, the tourism revenue is modelled as a function of the number of tourists, oil prices, and the exchange rate. A deep learning network is developed using the Python programming language for modelling the tourism revenue. The developed deep learning network is then trained using a portion of the data. The performance of the developed deep learning network is then evaluated using the performance metrics such as the coefficient of determination, mean absolute error, root means square error, and the mean absolute percentage error. These metrics show that the developed deep learning network successfully models the tourism revenue dependent on the number of tourists, oil prices, and the exchange rate.

Administration of Petroleum Industry Revenue Governance under the Nigerian Petroleum Industry Act 2021: An Overview

Administration of Petroleum Industry Revenue Governance under the Nigerian Petroleum Industry Act 2021: An Overview

Single-Step Non-Chromatographic Purification of Recombinant Mammalian Proteins Using a Split Intein ELP Tag System.

Glycoprotein therapeutics are currently used by large patient populations and generate significant revenue for the biopharmaceutical industry. These therapeutic proteins are currently purified at industrial scale using individualized processes involving multiple chromatographic steps. In the absence of a viable affinity platform method, the required chromatographic steps are difficult to develop and inevitably lead to significant yield losses. Further, during preclinical development, there is a need for reliable platform technologies capable of performing high-throughput screening for biologic candidates. Although affinity tags can provide a solution to some of these challenges, they require specific affinity resins, and the tag itself can interfere with the target protein characteristics. Fusion protein systems consisting of elastin-like polypeptide (ELP) and self-cleaving split inteins such as Npu DnaE can serve as potential non-chromatographic platform technologies for the single-step purification of tagless glycoproteins expressed in mammalian cells. In this chapter, we demonstrate the use of this technology to obtain highly purified anti-ErbB2 ML39 single-chain variable fragment (scFv) expressed from Expi293F suspension cells.

Analysis and Countermeasure Research on the Development Status of Guangdong Culture Tourism Industry

In the era of low carbon economy, culture tourism industry has gradually become the “green sunrise industry” that major countries in the world give priority development to. Guangdong has always invariably place a high premium on the development of culture tourism industry. However, the outbreak of the COVID-19 has greatly impacted the previously prosperous cultural tourism industry, which directly led to a sharp decline in the revenue of cultural tourism industry. Now, China’s management of COVID-19 has been downgraded to the less strict Category B from the current top-level Category A, meaning the culture tourism industry will usher in new development opportunities. Herein, we analyze and study the policy orientation, key projects, regional cooperation, intelligent construction and other aspects of Guangdong’s cultural tourism industry, put forward targeted countermeasures and suggestions on the development status and existing problems of Guangdong’s culture tourism industry by comparing the development modes of culture tourism industry in other cities.

OLED Smartphone 2.0 and AIO OPD Sensing: The Future of Smartphone OLED and Security

AbstractFull‐screen fingerprint sensing will be an industry revenue upside and good for consumers.

An analysis of the determinants of China’s domestic catering industry revenue—Based on the data of 31 provinces in China from 2006 to 2020

An analysis of the determinants of China’s domestic catering industry revenue—Based on the data of 31 provinces in China from 2006 to 2020

The origin of LYONs: A case study in financial innovation

The origin of LYONs: A case study in financial innovation

Cross-Sectoral Transfer of Budgetary Subsidies Through Differential Railway Tariffs

The paper exposes and analyses a serious flaw in Russia’s current rail freight tariffs. Subsidized sectors of the Russian economy are overcharged while a range of other sectors are undercharged. This transfers budgetary subsidies from one sector to another in a way that is opaque to regulators. The article details how this transit subsidy is part of conveyer belt that runs from the national budget to refining, rail transport and ultimately to coal mining. Analysis shows that the transit subsidies from differential railway tariffs are quite large (from 2019 to 2021 coal industry revenues were augmented by an annual average of RUB 270 billion through this technique). The article also demonstrates that subsidizing coal production through differential railway tariffs cannot be justified by rational economic considerations, as it only prolongs the life of many hopelessly unprofitable enterprises and thus hinders sustainable economic development in coal-mining regions. The paper studies the feasibility of eliminating this kind of subsidy by making tariffs for oil and coal transportation converge. If those subsidies had been eliminated in 2023, the author concludes that it would have been relatively painless for the industry and could potentially bring about a RUB 245 billion reduction in annual state budget subsidies by 2050. The funds saved could be redirected to economic diversification and social development in the regions where the coal industry is concentrated.

In Case You Haven't Heard…

Now that marijuana is legalized in so many places, guess what's cropping up in those same places? Illegal marijuana shops — in other words, shops that sell what they say is marijuana, but don't have a license, don't pay fees to the state, don't guarantee the safety of their product, and have now aroused the ire of citizens. For example, in Buffalo, New York, local lawmakers just passed a resolution to write rules and regulations for marijuana stores. The state legalized recreational use of the drug, but that leaves cities to work out details. Buffalo legislators have asked the New York Office of Cannabis Management — a state agency paid for by taxpayers — to step in and take action against unregulated stores. The lawmakers in Buffalo — as in many jurisdictions — who look at marijuana stores as a source of revenue, tourism, and part of a hospitality industry, are not opposed to legal marijuana. They just want any store that opens before it has a license to be banned. Meanwhile, how does one know if what they are buying is safe and legal? Questions to answer next year. Maybe.

A homomorphic approach for security and privacy preservation of Smart Airports

The concept of Smart Airport is emerging in the Aviation sector because of the industry 4.0 revolution. To provide the best facility to the air travelers, most of the airports have enhanced their infrastructure using smart automation and Cloud Services (CS), etc. which play a significant role in increasing the revenue of the aviation industry. As the use of digital technology at airports is increasing, they are becoming progressively vulnerable to cyber-attacks and data breaches. The data collected by the airports is stored in specialized cloud databases, which ensures the availability of the data at any time. However, cloud servers have been compromised several times which leads to a lack of trust by the consumers. To meet the privacy and security objectives of the data collected at the airports and stored in the cloud, this research proposes a Searchable Encryption (SE) scheme based on Partial Homomorphic Encryption (PHE). The proposed scheme allows users to search on the encrypted data stored in the cloud hence enhancing the usability of the encrypted data. In this paper, a Single Keyword Searchable Encryption (SKSE) scheme is presented which is implemented using Paillier Cryptosystem. The proposed scheme comprises of two variants (a) Secure SKSE (b) Efficient SKSE. The Secure SKSE scheme exploits the probabilistic properties of the Paillier cryptosystem, whereas, the Efficient SKSE scheme is lightweight as it is based on the deterministic properties of the Paillier cryptosystem. Both variants of SKSE scheme are deployed on a public cloud platform “Contabo” and tested on the real-world aviation data to assess the performance of both approaches. The security and performance analysis illustrates that the proposed Secure SKSE maintains a high-security level by providing probabilistic encryption and trapdoors. On the other hand, the Efficient SKSE is 84 times faster in terms of performance.