Industry Trade Research Articles

ECONOMIC CONDITIONS OF THE DEMAND FOR INVESTMENT AND WORKING CAPITAL LOANS FOR MICRO-ENTERPRISES – RESEARCH FOR POLAND DURING COVID-19

Aim: The study aims to find an answer to the question of whether and how the economic indicators in the industrial processing, construction, trade, and services sectors reflect changes in the market size related to investments and working capital loans for micro-enterprises. Methods: The study used data on investment and working capital loans and data on economic conditions. Monthly data for the years 2019–2021, covering the period of the COVID-19 pandemic, were used for the analyses. The estimation of dynamic models was carried out using the Generalized Method of Moments (GMM). Results: The conducted research showed that economic factors play a significant role in shaping the demand for investment and working capital loans in the micro-enterprise sector, but the impact of the economic situation was more significant in the case of investment loans than working capital loans. In periods of economic prosperity, micro-enterprises are more likely to take out investment loans than in periods of economic downturn. Micro-enterprises’ propensity to take out working capital loans is more dependent on their current situation and expectations regarding the demand for products and services. Conclusions: The research revealed differences in the characteristics of the factors significantly influencing the demand for credit, depending on the sector to which the indicator is concerned. The research shows that access to external financing is crucial for the functioning, survival, and expansion of micro, small, and medium-sized enterprises. The research fills the literature gap by showing how the economic situation in individual industries affects the credit market for the micro-enterprises sector.

Granular biopolitics: Facial recognition, pandemics and the securitization of circulation

The COVID-19 pandemic has provided opportunities for facial recognition technology and other forms of biometric monitoring to expand into new markets. One anticipated result is the wholesale reconfiguration of shared and public space enabled by the automated identification and tracking of individuals in real time. Drawing on data from several industry trade shows, this article considers the forms of ‘environmental’ governance envisioned by those developing and deploying the technology for the purposes of security, risk management, and profit. We argue that the ‘contactless culture’ that emerged during the COVID-19 pandemic anticipates the normalization of a form of mass-customized biopolitics: the ability to operate on the population and the individual simultaneously through automated forms of passive identification. This form of governance relies not just on machinic recognition, but on the real-time reconfiguration of physical space through automated access controls and the channelling of both people and information.

THE TEXTILE INDUSTRY TRADE COMPETITIVENESS OF SELECTED EUROPEAN TRANSITION COUNTRIES

The paper analyses the textile industry trade competitiveness of nine European transition economies (Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, North Macedonia, Romania, Serbia and Slovenia), in parts and in its entirety, by using the following indicators: Revealed comparative advantage (RCA), Competitiveness growth index (RCA1), Index of net business performance (RCA2), and Michaely index (MI). The analysis focuses on the period between 1995 and 2018. The results of the analysis show that the textile industry of Northern Macedonia is internationally competitive, and that most countries have revealed comparative advantages. The textile industry contributed to the surplus in trade balance in North Macedonia, Bulgaria and Romania, while North Macedonia, Romania, Bulgaria, Croatia, Bosnia and Herzegovina and Serbia achieved some level of production specialisation. It was also confirmed that these countries had statistically different levels of trade competitiveness. The top level of production finalisation accounted for the greatest average value of competitiveness indicators.

Evolution of structural properties of the global strategic emerging industries' trade network and its determinants: An TERGM analysis

This article examines the evolution of the global strategic emerging industries trade networks (GSEITNs) and employs the temporal exponential random graph model (TERGM) to investigate the principal determinants of the critical trade cooperation in the global strategic emerging industries (SEIs) from 2007 to 2020. The findings indicate that GSEITNs exhibit a sparse, hierarchical, and monopolistic structure. Despite the continual integration of emerging nations into GSEITNs, countries have grown progressively wary of the network. Moreover, the structure properties of the endogenous network proves that SEIs trade links have a substantial signaling effect. More importantly, SEIs trade is more reliant on the economic size and innovation capacity, and countries are more cautious about protecting their intellectual property, especially when trading with countries possessing similar R&D levels. Furthermore, robust bilateral political ties can augment the probability of SEIs trade between two countries, particularly in sectors such as new energy vehicles and new-generation information technology industries. In summary, this article takes into account the influence of network structure, national attributes and external networks, and provides new insights into studying trade network evolution in SEIs.

Model Pembiayaan Agribisnis Berbasis UMKM di Kabupaten Sinjai (Studi Kasus: KUB Anggrek Desa Aska)

Financing in agribusiness, especially in businesses related to making MSME-based banana frond handicrafts, is needed in managing their business. The choice of the right financing model will depend on the needs and conditions of MSMEs. This study aims to analyze and describe the financing model at the Anggrek KUB of Aska Village, South Sinjai District, Sinjai Regency. The sampling method used is purposive sampling method. The results showed that Anggrek KUB of Aska Village currently only uses a financing model from personal capital, the P3AP2KB Office of Sinjai Regency, the UMKM Cooperative and Manpower Office of Sinjai Regency, and the Industry Trade and Energy Mineral Resources Office of Sinjai Regency. Alternative models for financing the Aska Village Orchid KUB include crowdfunding, venture capital, Microfinance Institutions (MFIs), and grants and aid programs.

Financial Distress During the COVID-19 Pandemic: Altman and Springate Model Prediction

Background: The retail trade industry has experienced a sharp decline in economic growth during the COVID-19 pandemic. Regulation of social distancing, restrictions on retail shop operating hours, and disruption of online shopping behavior contribute to worsen the financial performance of retail trade companies. </p> <p> Purpose: The purpose of this research is to analyze the prediction of financial distress of retail trade companies. This research chose to use the Altman and Springate Model since both of them are the most accurate and conservative models to predict. </p> <p> Research Methodology: The financial distress analysis technique used is Altman and Springate Model. The calculation of the Altman and Springate Score is based on an equation formula for data in the period before and during the COVID-19 pandemic. The Altman’s Score are grouped in the Safe Zone, Grey Area, and Financial Distress; while the Springate’s Score are grouped in the Safe Zone and Financial Distress categories. </p> <p> Findings: Altman Model Analysis stated that most of the companies experienced a decreased scores, the company’s financial performance during COVID-19 pandemic was predicted financial distress and belong to the Grey Zone category than before COVID-19 pandemic. Springate Model Analysis states that all companies have decreased scores, and the company’s financial performance during COVID-19 pandemic is predicted financial distress than before COVID-19 pandemic. Springate Model revealed a more conservative indicator, but both models stated there were still exist several companies in the Safe Zone category to continue their business. </p> <p> Research limitations: The limitations of this study are only using Altman and Springate Model. The object of this research is the retail trade industry only, then future research may be able to expand the analyzed industry in the new normal conditions. </p> <p> Originality/value: The originality of this research is focused on the retail trade companies as the most affected industry by COVID-19 pandemic. In addition, this research analyzes financial distress based on Altman Z-Score and Springate Model as the most powerful model to predict.

‘Normalizing Informality’ in Local–Transnational Spaces: Contraband, Conflict and Street Trade in Eastern Ethiopia

Informality arguably remains the main source of employment and income for most participants in the cities of the Global South. It is rampant in cities along national borders and transport routes. This paper discusses the ‘normality of informality’, exploring the nexus between contraband, conflict and informal cross-border trade in a local–transnational space, drawing from Dire Dawa in eastern Ethiopia. Data were collected through key informants and in-depth interviews in 2015/2016 and 2019. This study also benefitted from secondary sources. Since its establishment in 1902, the city has become a major hub of commerce, industry, transportation, and cross-border trade. Combining the literature on the informal economy and cross-border trade and drawing on evidence from eastern Ethiopia, this study explores how trade is deeply embedded in local–transnational interactions through partnerships between state and non-state actors. This study argues that informal cross-border trade is a societal mode of provisioning with extensive livelihood opportunities that survive even through periods of conflict and repression. Thus, reducing the vulnerability of participants in informal cross-border trade could be a more effective policy target than eradicating them.

Industrial and textile waste trade: Multilayer network and environmental policy effects

Waste management is an international enterprise, and it is important to understand global flows of recyclable materials. The Pollution Haven Hypothesis (PHH) suggests that waste moves from high income nations with stringent environmental policy to low income nations with less environmentally stringent policy, by exploiting low labor and regulatory costs. This paper assesses the PHH thesis for slag/dross and textiles (SDT) wastes in PHH through novel integration of the multilayer network and gravity models. The multilayer network model generates network effect that quantifies interlayer connections of multiple waste trade networks. Instead of North-South movement of waste, North-North, South-South, and even South-North are shown. Results from the gravity model indicate that stringent waste management policies reduce both waste exports and imports. PHH is not found for slags/dross where high income countries are importing the waste, contradicting PHH. On the other hand, PHH is more evident between highly connected hubs and havens in SDT waste trade networks.

Blockchain-cloud privacy-enhanced distributed industrial data trading based on verifiable credentials

Industrial data trading can considerably enhance the economic and social value of abundant data resources. However, traditional data trading models are plagued by critical flaws in fairness, security, privacy and regulation. To tackle the above issues, we first proposed a distributed industrial data trading architecture based on blockchain and cloud for multiple data owners. Subsequently, we realized implemented distributed identity management by the distributed verifiable credentials scheme that possesses the desirable properties, i.e., selective disclosure, multi-show unlinkability, threshold traceability, and public verifiability. Finally, we presented a fair trading mechanism without trusted third parties based on smart contracts, and we employed blockchain and multi-signature to ensure data integrity during data storage and trading. The security and performance analysis shows that our proposal is feasible for sensitive data trading for multiple data owners and provides a useful exploration for future industrial data trading and management.

The close connection between liquidity and profitability: analysis of the retail market

Purpose- Analyzing profitability and liquidity indicators are essential for healthy financial management. Liquidity refers to the extent to which a company can convert its assets into cash quickly and without significant loss of value while profitability refers to the extent to which a company generates profits and returns investments for its owners. An important dimension in the relationship between liquidity and profitability is time. A company may be liquid and profitable at one point in time, but this may not hold true over time. In addition to these things, the Romanian retail industry is an industry that contributes massively to the achievement of the GDP and is also an important employer, offering employment opportunities to a significant part of the population. The purpose of this study is to determine the relationship between liquidity indicators and the profitability of retail companies. Methodology- STATA software was used to model the data and estimate the results, using multiple linear regressions. Findings- The analysis reveals that shows that liquidity rates have a low impact on the profitability of Romanian companies in the retail trade industry. Conclusion- Based upon the analysis, it may be concluded that managers must establish more favorable policies regarding the credit granted by suppliers, which can lead to a decrease in the cash conversion cycle and implicitly to an increase in the profitability of retail companies. At the same time, the simple conclusion is to pay more attention to the company's liquidity, observing the direct relationships between liquidity rates and profitability in the sense of increasing the last one. Keywords: business economics, financial management, liquidity, market, profitability, retail JEL Codes: L21, L81, M21

Shari-ah convergence and stock portfolio returns: a field study

Purpose- The aim of this study is to develop a Shari-ah compliance index that measures the degree of convergence to Islamic rules and to examine the relationship between the developed Shari-ah compliance index and the performance of stock portfolios consisted of the shares of the companies in the dataset. Methodology- Shari-ah compliance criteria was determined after an analysis of the existing literature and the practices of multinational financial institutions. In current practices, Shari-ah compliance is assessed in two stages; in the first stage, companies operating in industries that do not comply with Islamic rules are identified, and in the second stage, Shari-ah compliance is determined with the calculation of certain ratios. In this study, in line with current practices, companies engaged in entertainment, media (except newspapers), conventional finance, gambling, hotel-restaurant-bar management, pork products, cigarettes, weapons and defence, gold and silver trading industries were marked as non-compliant. For the second stage of Shari-ah compliance assessment, there are significant differences in the ratios applied by financial institutions; in the context of this study two ratios measuring indebtedness level (total liabilities/total assets and interest-bearing liabilities/total assets), one ratio measuring liquidity level (the ratio of the sum of cash and financial investments to total assets). and two ratios measuring income compliance level (the ratio of the sum of interest-earning cash and financial investments to total assets and the ratio of financial income to total income) were employed. The variable weights were assessed with IDOCRIW multi-criteria decision-making technique. The dataset consisted of stock exchange listed 1,235 manufacturing, service and technology industry companies located in 10 different Islamic countries (Bahrain, Bangladesh, Jordan, Kuwait, Malaysia, Oman, Pakistan, Qatar, Turkiye, and the United Arab Emirates) that have adopted the international financial reporting standards. The Sharia-ah compliance ratios were calculated for five years between 2017 and 2021 by using financial statement data and food notes obtained from stock exchanges and/or company websites. Findings- To construct stock portfolios, companies were divided into nine groups according to their degree of compliance for each year for which the Shari-ah compliance index is calculated. The first group included companies with a compliance degree between 90% and 100%, and the last group included companies with a compliance degree between 0% and 50%. 10-year adjusted monthly stock returns of all companies for the 2013-2022 period were obtained from the investing.com website. For each of the five years and for all nine groups, stock portfolio weights were calculated with minimum variance technique developed by Markowitz by using the past five years adjusted stock returns; yearly portfolio returns were computed by applying the calculated stock weights. When five-year portfolio returns are analyzed, the portfolio composed of 0-50% Shari-ah compliant stocks is third in return ranking. Among the remaining eight portfolios four portfolios composed of stocks with Shari-ah compliance degree above 75% take the first four rankings. The return difference is statistically significant at 5% confidence level. Conclusion- Although the threshold values applied for Shari-ah compliance varies among institutions, the generally accepted level is 70%. The findings of the study show that in Islamic geography, portfolios consisting of stocks of companies that keep the indebtedness, liquidity and non-compliant income levels below the threshold accepted by Sharia rules have higher performance than others. A possible explanation of the findings is the demand of Islam conscious investors. Keywords: Sharia-ah convergence, multi-criteria decision-making techniques, minimum variance technique, indebtedness, liquidity JEL Codes: G31, G32, G12

Siquian City’s Exporting of Goods: Competitiveness and Survival Analysis Amidst Challenges

In 2020, in the face of the sudden impact of the new coronavirus pneumonia epidemic, Suqian's economy has withstood the test of the epidemic, showing a good situation of "rapid stabilization and gradual recovery", and the "13th Five-Year Plan" has come to a successful end. In the year of 2020, when the Sino-US trade war has not ended and the new coronavirus epidemic is raging, Suqian's foreign trade can achieve such good results, which is worthy of affirmation. However, while affirming that Suqian can still achieve such excellent results in the export of goods in such a severe situation at home and abroad, we should also see that there are still many shortcomings in the development of Suqian's foreign trade. Based on this, this paper firstly analyzes the current situation of Suqian's goods export from four aspects, such as the scale of goods export, export goods, export trade mode and the export situation of goods in each sector. Secondly, the paper analyzes the existing problems of Suqian's export of goods. The main problems are: the gap between Suqian and southern Jiangsu, the unbalanced development of various sectors, the unreasonable structure of export of goods, etc. Thirdly, from the internal and external environment, this paper analyzes the reasons for these problems in Suqian's goods export. The internal reasons include: inter-regional industrial transfer, insufficient level of industrial development, and insufficient location advantage; The external reasons are as follows: the impact of the COVID-19 epidemic, Sino-US trade friction, sluggish international market demand, the impact of international industrial transfer and trade barriers have weakened the competitiveness of Suqian's export goods; Finally, from the two levels of government and enterprises to improve the problems of Suqian goods export countermeasures and conclusions.

The impact of aggregate demand shocks on Germany’s trade balance and industry

ABSTRACT We examine the impact of aggregate demand shocks on Germany’s trade balance and industry after the adoption of the Euro. Using a Structural Vector Autoregression we find that Germany’s trade balance and industry are highly responsive to aggregate demand shocks. As Germany’s income increases, this leads to an increase in imports and a gradual reduction in its trade balance. However, Germany’s export capacity stabilizes its trade balance. This is over a period of rapid globalization, technological progress confronting all economies, several global trade disruptions and with disturbances to crucial energy requirements for Germany’s industry and export sector.

Industry momentum and trading volume: evidence from China

PurposeAs the world's largest emerging market, the evidence of momentum effect in China is also mixed. Meanwhile, prior studies mainly examined individual stock momentum in China, with little concern for industry momentum and its relationship with trading volume. The motivation of this study is to investigate industry momentum in China and examine whether trading volume can enhance its profitability.Design/methodology/approachFirstly, the authors test the existence of industry momentum in China; secondly, the authors test the correlation between trading volume and momentum returns using the double ranking method; finally, the authors test whether trading volume enhances the momentum returns using Fama–French five-factor model.FindingsThe authors find that there is a significant industry momentum effect in China, and the momentum returns jointly come from winner and loser portfolios. The intervals between the formation and holding periods have an impact on the performance of momentum portfolios. In terms of trading volume, the authors find that high-volume industries have industry momentum effects while low-volume industries do not. The industry momentum strategies achieve higher excess returns in high-volume industries.Practical implicationsPrior literature found higher momentum returns in low-volume stocks in China, but the research in this study suggests that implementing an industry momentum strategy in low-volume industries will miss out on higher returns or even bring losses, and instead the investors should invest in high-volume industries to get the best performance.Originality/valueThis study extends existing research by focusing on industry momentum and its relationship with trading volume in the Chinese stock market and finds an interesting relationship between industry momentum returns and trading volume, which is different from related studies.

Implementation of Commercial Business License Policy in Downstream Oil and Gas Business Activities in Bitung City

The purpose of this research is to describe, analyze and describe how the management of the Non-Subsidized Solar Industrial Fuel trading business permit in Bitung City. What are the factors that hinder the processing of Non-Subsidized Fuel Trading Business License for Industrial Solar in Bitung City The research method uses a qualitative approach. Data collection techniques using interviews, documentation studies and observation. The results showed that the commercial business license policy for downstream oil and gas business activities in Bitung City has not been implemented properly because there are business actors who do not take care of the Commercial Business License even though they have been trading in Bitung City and its surroundings. There are obstacles in managing the Commercial Business License in Bitung City, namely the submission of files and management must be done directly to the Ministry of Energy and Mineral Resources because there is no representative authority in Bitung City.

Book Reviews

Alex Tsiukes reviews O’Brien, David J. (2021) Defining Public Goods: An Institutional Approach to Community-Building and Negotiating Inter-Community Conflict. Anqi Chen reviews Kresl, Peter K. (2021) The City and Quality of Life. Xingcan Cao reviews Isard, Walter. (2021) Location and Space-economy; a General Theory Relating to Industrial Location, Market Areas, Land Use, Trade, and Urban Structure.

Forecasting carbon price using signal processing technology and extreme gradient boosting optimized by the whale optimization algorithm

AbstractPredicting carbon prices is crucial for the growth of China's carbon trading industry. This paper proposes a residual correction model that considers multiple influencing factors. First, the best historical data and main external factors input by the model are determined by using the partial autocorrelation function and Spearman correlation analysis, and the carbon price forecasting index system is constructed. Second, the whale optimization algorithm (WOA) is utilized to determine the optimal parameters of the extreme gradient boosting (XGBoost), and the WOA‐XGBoost model is built to perform preliminary carbon price forecasts and obtain the residual series. Finally, the carbon price residual series undergoes decomposition into multiple components utilizing the complete ensemble empirical mode decomposition for subsequent forecasting and the aggregation of outcomes. Experiments are conducted to predict two carbon trading markets in Hubei and Guangzhou, and a feature importance analysis is performed. The results indicate that the proposed hybrid model consistently outperforms the comparative models in terms of prediction accuracy. Furthermore, it is revealed that historical carbon prices and European Union carbon prices are the key factors influencing the prediction of carbon market prices.

Нейромережеві прогностичні технології класифікації криз та оцінки банкрутства суб’єктів торговельної галузі

The ongoing war in Ukraine has led to a significant increase in the number of business bankruptcies. Timely assessment of bankruptcy risk is critical for making effective management decisions. The aim of the study is to develop an adaptive model for assessing the propensity of an enterprise to bankruptcy based on fuzzy neural networks, taking into account the specifics of the Ukrainian market in wartime. To achieve the aim, several stages were carried out: formation of a sample of enterprises in the trade industry; determination of crisis classes using cluster analysis; building a fuzzy neural network using the Fuzzy Logic Toolbox package in MATLAB; training the network on historical data and testing on new data. At the first stage, a sample of enterprises is formed, with the help of which the model will be trained. At the second stage, classes of crisis (threat of bankruptcy) are formed. At the third stage, with the help of the apparatus of fuzzy neural networks, a membership function with a certain set of parameters is formed. With the help of this function, it is possible to attribute this or that enterprise with a certain degree of belonging to one of the classes of crisis formed at the previous stage. The fourth stage is to check the adequacy of the obtained model and the possibility of its practical use. At the fifth stage, the practical implementation of the model is carried out: with the help of the membership function, the propensity of the researched enterprise to bankruptcy is determined, that is, to what extent the studied enterprise belongs to one or another class of crisis. As a result of the application of the proposed algorithm, a fuzzy neural network was built, which used the financial indicators of Ukrainian enterprises. To train the model, a dataset was used that included 12 enterprises in the trade industry. The developed model allows to classify enterprises by the level of financial sustainability with high accuracy. Fuzzy neural networks have been shown to be an effective tool for predicting bankruptcy under uncertainty. The use of fuzzy neural networks made it possible to take into account uncertainty and adapt to changes in the external environment. The obtained results indicate the perspective of using fuzzy neural networks to assess the financial sustainability of enterprises. The developed model can be used as a tool for early detection of signs of crisis and making timely managerial decisions.

The Impact of International Trade Development on China’s Free Trade and the Value of the Agricultural Industry Chain

Abstract The development of international trade is both a challenge and an opportunity for China’s free trade and agricultural industry chain. Linear regression modeling is employed in this paper to examine how international trade development affects the value of China’s free trade and agricultural industry chain. The variables in the linear regression model are set, and the correlation coefficient is calculated to obtain the correlation coefficient between them. This basis is used to test the regression coefficients for significance and multicollinearity using the least squares method. The data show that the difference between the minimum value and the mean value of the free trade economy index is significant, about 0.3-0.6, while the difference between the maximum value and the mean value is slight, about 0.1-0.4, which indicates that the free trade economy of the provinces with poor free trade economy in China is much lower than the average free trade economy level in China. The degree of international trade development shows the most apparent upward fluctuation from the five quantile regressions of 0.2, 0.4, 0.6, 0.8, and 1.0, gradually increasing from a regression coefficient of 0.2428 to 1.149, which suggests that the international trade development has a significant positive effect on the change of the positional situation of the value chain of the agricultural industry. This study not only enriches the connotation of the theory of free trade and the agricultural industry chain in China but also provides reference and information for enhancing the resilience and sustainability of the development of the agricultural industry.

СОВРЕМЕННЫЕ ТЕНДЕНЦИИ И ПЕРСПЕКТИВЫ РАЗВИТИЯ РЫНКА ИНТЕРНЕТ-ТОРГОВЛИ

The article examines the issues that determine the trends and prospects for the development of online commerce in Russia, analyzes the dynamics and structure of this market segment. The study of the assortment and regional structure of online sales allows us to identify the peculiarities of market development and determine the main prospects. The impact of online commerce on the trading industry as a whole is being studied. The trends and features of the activities of marketplaces are considered.