Journal articles on the topic 'Retail trade – Forecasting'
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Smagin, R. S., and T. V. Lebedeva. "ANALYSIS AND FORECASTING FINANCIAL RISKS OF RETAIL TRADING NETWORKS." Intelligence. Innovations. Investment, no. 1 (2021): 54–64. http://dx.doi.org/10.25198/2077-7175-2021-1-54.
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The relevance of the problem under study is due to the fact that, despite the many works devoted to the theoretical and applied aspects of risk research, the specifics of the formation of financial risks in the activities of retail trade networks have not been sufficiently studied. In particular, there is no methodology and practical recommendations for quantitative risk assessment using statistical methods that allow to identify trends and patterns in the dynamics of risk indicators, to consider external and internal risk factors, the results of which should be used as a basis for developing measures to reduce the risk of retail trade. networks. The aim of the work is to improve the methodology for assessing financial risks based on methods of statistical, economic and financial analysis. The article presents the results of a quantitative assessment of financial risks according to the approach developed and tested on the data of the retail trade network “Magnit”. For a quantitative assessment of the financial risks of a retail trade network, the authors proposed a system of five profitability indicators. The analysis of trends and patterns in the dynamics of profitability indicators, as well as factors influencing them, was carried out using one-dimensional and multidimensional data sets. Forecasts of profitability indicators are not contradictory and indicate the presence of a risk of losses, therefore, a detailed assessment of financial risks was carried out. It was revealed that the indicators of profitability of the retail trade network “Magnit” in the analyzed period had a statistically significant relationship with the indices of the physical volume of retail trade and consumer prices, as well as the number of economic entities in retail trade. The assessment of the financial condition of the organization by indicators of financial stability and a comprehensive assessment by the five-factor model of E. Altman are given. The scientific novelty of the work consists in improving the methodology for assessing financial risks based on statistical, economic and financial methods of analysis, as well as developing proposals for reducing financial risks for network trading organizations. The proposed methodology and research results are of interest to decision makers in network trade organizations, regulatory bodies at the regional and federal levels. Prospects for further research on the issues of assessing and predicting financial risks of retail chains consist in a more detailed study of external factors, in particular, legal restrictions, changes in the level and structure of consumer demand due to the pandemic that began in 2020.
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García, Juan R., Matías Pacce, Tomasa Rodrigo, Pep Ruiz de Aguirre, and Camilo A. Ulloa. "Measuring and forecasting retail trade in real time using card transactional data." International Journal of Forecasting 37, no. 3 (July 2021): 1235–46. http://dx.doi.org/10.1016/j.ijforecast.2021.02.005.
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Murovana, Tetiana, Tetiana Kharchenko, and Nataliia Avramenko. "FEATURES OF MARKETING RESEARCH IN RETAIL TRADE." Economic discourse, no. 4 (December 2019): 114–22. http://dx.doi.org/10.36742/2410-0919-2019-4-12.
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Introduction. The development of the global retail market is accompanied by changes in approaches to the choice of methods of marketing research tools used in retail trade. Modern marketing research methods, which include tools and mechanisms for creating, promoting, distributing and exchanging information, play an important role in the context of the economy digitalization and the entry of Ukrainian companies into new markets. In view of this, there is a need to analyze the current state and trends of the retail market in Ukraine, to investigate the main groups of methods used in conducting marketing research, as well as to distinguish some of their types that are appropriate to use in the current conditions of functioning of the retail market in Ukraine. Methods. Historical and systematic approaches have been used to study the current state and trends of retail development. The study of the dynamics of the main indicators of retail trade was conducted using statistical methods of structure analysis, index method and method of dynamics series. The forecasting of the retail turnover of enterprises was carried out using linear approximation methods, in particular, the least-squares method. Grouping methods, as well as qualitative and quantitative research methods, were used to substantiate measures to improve marketing policies, research methods and tools. Results. The current state and trends of retail market development in Ukraine were analyzed by the authors. The main groups of methods that are used in conducting marketing research were investigated, as well as their separate types, which are expedient to be used in the current conditions of functioning of the retail Market in Ukraine. The stages of conducting marketing researches in retail trade are distinguished and the basic tasks which must be solved on each of them are defined. Discussion. The implementation of the proposed measures will help to identify innovative solutions to familiarize customers with new types of products, as well as to adapt specific methods of marketing research to the current conditions of functioning of the global retail market. In addition, the implementation of the proposed measures will allow to develop measures for timely response of the manufacturing companies to the existing requests of the retail market, ensuring the financial stability and solvency of the companies involved in the field of retail trade. Prospects for further research may include in-depth analysis of prospects for the use of large-scale processing financial technologies and development of special software for the application of specific methods of marketing research (point-of-sale audit, point-of-sale price analysis, check structure, mystery shopper, trading panel, ABC-analysis, XYZ-analysis, cross-analysis, hall-tests, home-tests, etc.). Keywords: marketing research, methods of marketing research, retail, e-commerce.
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KOÇ, Feden, Ahmet Çağdaş SEÇKİN, and Osman BAYRİ. "MAKİNE ÖĞRENMESİ İLE ULUSLARARASI MUHASEBEDE ERTELENMİŞ VERGİLERİN TAHMİNLEMESİ." Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 9, no. 2 (July 29, 2022): 1303–26. http://dx.doi.org/10.30798/makuiibf.1034685.
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The aim of this study is to estimate the possible deferred tax values and the TAS-TFRS profit/loss of 31 companies in three different sectors- the wholesale trade, retail trade and hospitality industry- whose shares are traded on Borsa Istanbul (BIST). This estimation is based on the companies' deferred tax values for the years 2015-2019 as well as twelve main economic parameters. Within the context of the study, the deferred tax output parameters, which companies will present in their annual financial reports in 2020, have been estimated using the following methods: the DTA value using the random forest method with an accuracy rate of 0,823, the net DTA value using the artificial neural networks method with an accuracy rate of 0,790, the DTL value using the random forest method with an accuracy rate of 0,823 and the net DTL value using the random forest method with an accuracy rate of 0,887. In addition, it has been discovered that the TAS-TFRS profit/loss, which is one of the output parameters, can be estimated using the random forest method with an accuracy rate of 0,629.
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Prabantarikso, R. Mahelan, Zaenal Abidin, Edian Fahmy, Mayda Tyastika, and Amabel Nabila. "Determinant of net interest income of commercial banks in Indonesia." Accounting 8, no. 3 (2022): 259–68. http://dx.doi.org/10.5267/j.ac.2022.1.002.
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This study aims to identify the factors that contribute to the formation of Net interest income (NII) for commercial banks in Indonesia in the short and long-term using the Vector Error Correction Model (VECM). The results showed that in the short term all variables in each period tend to adjust to achieve long-term balance. In the short term, the variables that affect NII are credit and NPL of large and retail trade, construction credit, transportation credit and NPL warehousing and communication, as well as lending rate facility. While in the variable length figures that affect NII are credit variables and NPL large and retail trade, Credit and NPL Transportation, warehousing and communication, other credit and Third-Party Funds (Deposit) collected. The analysis of Impulse Response Function can be proven that NII most quickly achieves stability when dealing with the shocks of large trade and retail NPL. Meanwhile, in the Forecasting Variance Decomposition analysis, it can be concluded that the variable that gives the greatest contribution to NII is the amount of construction credit.
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Lola, I. S., and A. B. Manukov. "Potential of Using the Results of Market Observations in Forecasting Employment in Small Businesses in Russia." Voprosy statistiki 28, no. 2 (May 3, 2021): 42–53. http://dx.doi.org/10.34023/2313-6383-2021-28-2-42-53.
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The article presents results of analysis of the predictive potential of short-term forecast estimates of employment level in the small business segment by four sectors of the Russian economy: manufacturing, construction, wholesale and retail trade.From the authors’ point of view, one of the promising sources of data for such estimates can be found in market observations of entrepreneurial activity, which now are a common source of economic information in national as well as international practice. These surveys play an important role in measuring the dynamics of employment in countries and industries, being a supplementary statistical tool.The objective of the work was to prove the existence of a stable statistically significant relationship between the predicted estimates of employment based on business (market) surveys and the dynamics of the corresponding statistical macro-aggregates in various sectors, and applicability of predictive models of employment change based on results of business (market) surveys.The novelty of the presented results (authors’ contribution) resides in the fact that for the first time, using an expanded sample (over 14 thousand respondents), were studied the possibilities of predicting labour market indicators in small businesses based on leading data from business surveys, examining separately retail trade, wholesale trade, construction, and manufacturing. According to the results obtained based on the Granger causality and pseudo-out-of-sample analysis, in all the industries under consideration, entrepreneurial assessments and expectations are effective predictive indicators for forecasting employment dynamics in the short term (two to four months) and identifying turning points in employment growth in the small business segment. The most sensitive predictive estimates were found in the retail and wholesale sectors, with the best results obtained for wholesale trade. For this reason, the authors recommend using the employment expectations indicator primarily in these sectors to monitor the level of employment and unemployment.
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LABURTSEVA, Olena, and Halyna ALDANKOVA. "MARKETING COMMUNICATION SYSTEM OF RETAIL ENTERPRISES." Economy of Ukraine 2018, no. 9 (October 5, 2018): 139–52. http://dx.doi.org/10.15407/economyukr.2018.09.139.
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The actual problem of marketing communications management of Ukrainian retailers from the point of view of the system approach is considered. It is shown that the specificity of these marketing communications is determined both by the goals they are aimed at, and by means of communication. The objectives of marketing communications are: formation of the brand image of retailer, attracting consumers to visit places of sale, incentive to make a purchase, promotion of consumer satisfaction and ensuring the consumer loyalty. The main types of marketing communications are advertising, sales promotion, public relations, direct marketing, integrated marketing communications at places of sale and personal sales. Within each type, subspecies of traditional and electronic communications are singled out. A systemic approach to managing marketing communications in the modern conditions should be based on the principles of purposefulness, customer focus, specificity, integration, interactivity, individualization, optimality and social ethics. At the same time, the success of communications is determined primarily by the extent to which they are convenient and useful to consumers. To implement these principles, it is proposed to implement in the process of managing the marketing communications system of retail enterprises such specific functions as marketing researches of consumer attitudes towards communications, adjustment of communications based on research results and forecasting the communicative effects. Approbation of the proposed methodological approach is made using data of enterprises of retail trade networks, which carry out sales of household electrical goods, information and communication equipment. It has been established that trade networks are now more intensively using less important for consumers types of communications, and vice versa. Changing the structure of the marketing communications system taking into account the benefits of consumers will improve the indicators of the communicative effects of marketing communications; this will enhance the competitiveness and economic efficiency of retail businesses in Ukraine.
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Kopchykova, Inna. "FEATURES OF THE DEFINITION «OPERATIONAL ACTIVITY OF TRADE NETWORKS»." Scientific Bulletin of Mukachevo State University. Series “Economics” 1(13) (2020): 92–96. http://dx.doi.org/10.31339/2313-8114-2020-1(13)-92-96.
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From the formation of effective strategic goals and improvement of operational activities depends on the optimization of production methods, planning the development of new products, changing the cost of production, planning and forecasting sales. The introduction of new areas of operational activity is an effective strategic development. The relevance of the research topic is due to the development of modern formats of trade and the need to implement new solutions for operational management, in terms of improving the effectiveness and quality of basic management functions – planning, organization, management and control. The retail industry is in a constant process of transformation. Economists cannot say how much the new formats will be in demand. Determining the mechanism of functioning of trade networks in Ukraine has not yet been the subject of extensive research, which has a negative impact on the practice of their operation. The article raises the relevance of the concept of operational activity of retail chains as an economic category. The essence of retail operations is considered. The purpose of the article is to study the concept and clarify the economic category «operational activities of the trade network». The main task is to study the nature and components of retail operations, as well as to develop ways to optimize operational management, the main of which are well-developed logistics schemes, electronic sales channels, organization of food halls and food courts, digitalization and personalization, construction of omnichannel communication networks and the consumer, the use of big data to improve customer service. Based on the use of general economic research methods, the approaches of scientists to the interpretation of the concept of "operational activity" are analyzed and systematized. The scientific novelty of the study is to clarify the essence and highlight the most important characteristics of the operational activities of retail in Ukraine. The practical significance lies in the substantiation of the main components of the operational activity of the trade network. Based on the study, it is determined that operating activities in the process of financial and economic activities occupy a basic place, as they are the basis for stimulating the development of entrepreneurial activity. Keywords: means of operational activity, objects of operational activity, operational activity, components of operational activity, trade network.
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Todorov, Lyubomir. "COVID-19 and domestic trade in Bulgaria." Problems and Perspectives in Management 20, no. 4 (October 26, 2022): 111–26. http://dx.doi.org/10.21511/ppm.20(4).2022.09.
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Domestic trade is an essential contributor to economic growth and an indicator of the people’s welfare. It is vulnerable to the COVID-19 crisis due to the pandemic itself and the government’s measures against it. An accurate estimation of the pandemic influence on domestic trade is needed for effective economic intervention in support of the economic recovery and improvement of the well-being of the population. The aim of this paper is to estimate the magnitude and timing of the COVID-19 impact on domestic trade in Bulgaria. The data used in the study covered the period 2000–2020 with monthly data for the indicator “Turnover for wholesale and retail trade and repair of motor vehicles and motorcycles in Bulgaria.” This paper employed unit root tests, autocorrelation function analysis, building, estimating, forecasting ARIMA and ARCH models, and intervention analysis. The results revealed that Bulgarian domestic trade followed the difference-stationary process as unit root tests failed to reject the random walk hypothesis. The COVID-19 impact on domestic trade proved to be long-lasting and has permanently decreased its level since March 2020. The timing of the impact coincided with the government’s measures against the pandemic. The drop in the volume of domestic trade was substantial and estimated at 19.3%. Following the nature of domestic trade, determined and decisive intervention is necessary if the Bulgarian government seeks to expand domestic demand and successfully procure economic recovery.
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Hirche, Martin, Juliane Haensch, and Larry Lockshin. "Comparing the day temperature and holiday effects on retail sales of alcoholic beverages – a time-series analysis." International Journal of Wine Business Research 33, no. 3 (January 18, 2021): 432–55. http://dx.doi.org/10.1108/ijwbr-07-2020-0035.
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Purpose Little research on the influence of external factors, such as weather and holiday periods, on retail sales on alcoholic beverages is available. This study aims to investigate how weekly retail sales of different alcoholic beverages vary in association with daily maximum temperatures and annual federal holidays across selected US counties in the years 2013 to 2015. The research provides information, which can contribute to better sales forecasts. Design/methodology/approach Secondary data of weekly retail sales (volume) of alcoholic beverages from 37,346 stores in 651 counties in the USA are analysed. The data cover on average 21% of all existing US counties and 12% of the total US off-trade retail sales of alcoholic beverages in the period studied (Euromonitor, 2017). Additional data of federal holidays and meteorological data are collated for each county in the sample. Seasonal autoregressive integrated moving average models with exogenous regressors (SARIMAX) are applied to develop forecasting models and to investigate possible relationships and effects. Findings The results indicate that off-trade retail sales of beer, liquor, red and white wine are temperature sensitive throughout the year, while contrary to expectations rosé, sparkling and other wines are not. Sales sensitivities to temperature also differ by geography. In the warmest regions, liquor and white wine sales do not respond to temperature changes, as opposed to the coolest regions, where they are responsive. Public holidays, particularly Easter, Thanksgiving, Christmas and New Year holidays, represent a constant influencing factor on short-term sales increases for all investigated alcoholic beverage categories. Originality/value This is the first large-scale study of weather and holiday-related sales variations over time, across geographies and different alcoholic beverage categories. Seasonal and non-seasonal short-term sales variations are important for retailers and manufacturers alike. Accounting for expected changes in demand accommodates efficiencies along the supply chain and has implications for retail management, as well as adjusting marketing efforts in competing categories.
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Blokhin, A. A., and R. V. Gridin. "Russian retail trade: institutional differences of trading companies as a factor of industry dynamics." Russian Economic Journal, no. 2 (May 2020): 40–57. http://dx.doi.org/10.33983/0130-9757-2020-2-40-57.
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The article establishes: a) the fact of significant institutional differences between groups of companies in the Russian retail trade; b) the trend of increasing these differences in recent years. Criteria for structuring a sample of large companies in the form of a number of clusters that differ in their institutional strength and compete with each other are identified and tested. Among the criteria — presence in ratings, market coverage, participation in business associations, size and complexity of companies, etc. The mechanism of dominance of market leaders over other companies is revealed on the basis of the concept of institutional rent received by a group of leading companies from the income of «lagging» companies; the conditions for the transition of companies from one group to another are revealed. Based on the analysis of information about retail chains included in the selected clusters, estimates of their integrated financial and economic indicators are given; the comparative dynamics of the latter is revealed. The hypothesis about the significance of institutional differences in clusters for the dynamics of the industry as a whole and individual groups of companies is confirmed. The article substantiates proposals for forecasting such institutional transformations of markets, scenarios of which take into account the existing market hierarchies of dominant and other companies. Recommendations are put forward to improve state regulation of industry development, taking into account the existing market architecture.
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Tudor, Cristiana. "Integrated Framework to Assess the Extent of the Pandemic Impact on the Size and Structure of the E-Commerce Retail Sales Sector and Forecast Retail Trade E-Commerce." Electronics 11, no. 19 (October 5, 2022): 3194. http://dx.doi.org/10.3390/electronics11193194.
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With customers’ increasing reliance on e-commerce and multimedia content after the outbreak of COVID-19, it has become crucial for companies to digitize their business methods and models. Consequently, COVID-19 has highlighted the prominence of e-commerce and new business models while disrupting conventional business activities. Hence, assessing and forecasting e-commerce growth is currently paramount for e-market planners, market players, and policymakers alike. This study sources data for the global e-commerce market leader, the US, and proposes an integrated framework that encompasses automated algorithms able to estimate six statistical and machine-learning univariate methods in order to accomplish two main tasks: (i) to produce accurate forecasts for e-commerce retail sales (e-sale) and the share of e-commerce in total retail sales (e-share); and (ii) to assess in quantitative terms the pandemic impact on the size and structure of the e-commerce retail sales sector. The results confirm that COVID-19 has significantly impacted the trend and structure of the US retail sales sector, producing cumulative excess (or abnormal) retail e-sales of $227.820 billion and a cumulative additional e-share of 10.61 percent. Additionally, estimations indicate a continuation of the increasing trend, with point estimates of $378.691 billion for US e-commerce retail sales that are projected to account for 16.72 percent of total US retail sales by the end of 2025. Nonetheless, the current findings also document that the growth of e-commerce is not a consequence of the COVID-19 crisis, but that the pandemic has accelerated the evolution of the e-commerce sector by at least five years. Overall, the study concludes that the shift towards e-commerce is permanent and, thus, governments (especially in developing countries) should prioritize policies aimed at harnessing e-commerce for sustainable development. Furthermore, in light of the research findings, digital transformation should constitute a top management priority for retail businesses.
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Melnyk, Iryna, Yuriy Turyanskyy, Ihor Mishchuk, Nataliіa Mitsenko, and Roksolana Godunko. "Modeling the possibilities of economic adaptation of trade enterprises and hospitality industry in the context of epidemiological zoning." Problems and Perspectives in Management 18, no. 4 (December 2, 2020): 191–202. http://dx.doi.org/10.21511/ppm.18(4).2020.17.
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The article identifies the negative impact of the coronavirus crisis on the expected efficiency of retail, hotel, restaurant and tourism businesses. The aim of the paper is to develop a methodological algorithm for short-term forecasting of opportunities to restore the effective activity of enterprises under quarantine restrictions.Seasonal component adjustments were performed in the Demetra+ software. Modeling the recovery of effective activity included an assessment of the influence of macroparameters on the dynamics of an enterprise’s sales volumes under pre-quarantine conditions, defining the size of economic losses, determining coefficients of macroindicators’ dynamic influence under conditions of differentiation of quarantine restrictions, constructing a matrix of multiple regression equations, which clearly demonstrates the forecast prospects for restoring the effective activity of enterprises, depending on the quarantine zoning. A situational model of the possible scenario dynamics of enterprises’ trade turnover was built taking into account the quarantine zoning and the logical transformational algorithms of influence on variable system parameters caused by it. The thermometer principle was used as a fuzzy logic tool to consider the specifics of the dynamics of various linguistic variables and bring the forecast model as close as possible to the epidemiological zoning logic. Approbation of the methodology revealed a clear correlation between the severity of quarantine restrictions and the expected growth of enterprise activity amounts. In a more advanced form, the method should be used for short-term macroeconomic forecasting when determining quarantine restrictions and epidemiological zoning.
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Podskrebko, O. S., N. O. Ivanchenko, and V. V. Tkachenko. "Modeling of the System of Evaluation of Retail Enterprises on the Basis of KPI and Process Approach." Business Inform 4, no. 519 (2021): 66–72. http://dx.doi.org/10.32983/2222-4459-2021-4-66-72.
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The article proposes a model for evaluating the activities of retail enterprise, which is based on five stages and allows determining ways to increase the efficiency of functioning, which will improve the adaptive properties of the economic object. The analysis of types of KPI is carried out, process and functional approaches are identified as the main ones for the direct development of key performance indicators, as well as the characteristics of the evaluation of effective marketing at enterprises, including those that function in the sphere of retail trade, are determined. The authors considered how modeling and forecasting of key financial indicators of an enterprise contribute to the creation of strategies for its development. The article notes that for the initial evaluation of a retail enterprise focused on long-term success, it is mandatory to conduct an audit aimed at assessing the efficiency of the economic object and defining how quickly the enterprise adapts to dynamic environmental conditions. The carried out analysis allowed to identify the key factors that contribute to an improvement of the enterprise’s operation. Also, on the example of the Isikawa diagram, the ratio of KPI, strategies and understanding of business processes was considered in order to set, control and analyze the achievement of goals.
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Lemonjava, Givi. "TIME SERIES MODELS FOR FORECASTING EXCHANGE RATES." Globalization and Business 4, no. 8 (December 27, 2019): 149–60. http://dx.doi.org/10.35945/gb.2019.08.020.
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This paper investigates the behavior of daily exchange rate of the Georgian Currency LARI (GEL) exchange rate against the USDand EUR. To forecast exchange rates there are numerous models, which tend from very simple to very complicated models for analysis of GEL/USD and GEL/EUR time series variable. The objective of this paper is to com- pare the performance of individual time series models for predictingexchange rates. We will investigate the application of following time series analysis models: moving average, ex- ponential smoothing, double exponential smoothing adjust- ed for trend, time-series decomposition models, and ARIMA class models. The forecasting ability of these models is subsequently assessed using the symmetric loss functions which are the Mean Absolute Percentage Error (MAPE), the Mean Absolute deviation (MAD), and the Mean Squared error /deviation (MSE/MSD). In some cases, predicting the direction of exchange rate change may be valuable and profitable. Hence, it is reasonable to look at the frequency of the correctpredicted direction of change by used models, for short - FCPCD. An exchange rate represents the price of one currency in terms of another. It reflects the ratio at which one currency can be exchanged with another currency. Exchange rates forecasting is a very important and challenging subject of finance market, to determine optimal government policies as well as to make business decisions. This is important for all that firms which having their business spread over different countries or for that which raise funds in different currency. Business people mainly use exchange rates forecasting results in following types of decisions like choice currency for invoicing, pricing transactions, borrowing and landing currency choice, and management of open currency positions. The forex market is made up of banks, commercial companies, central banks, investment management firms, hedge funds, and retail forex brokers and investors. Forecasting the short- run fluctuations and direction of change of the currency ex- change rates is important for all these participates. The main goal of this study is to forecast of future ex- change rate trends by using currency rates time-series, rep- resenting past trends, patterns and waves. The monetary policy of the National Bank of Georgia since 2009 have been followed the inflation targeting regime, where exchange rate regime is floating - change of exchange rate is free. The offi- cial exchange rate of the Georgian GEL against the USD is cal- culated each business day. The official exchange rate of GEL against USD is calculated as the average weighted exchange rate of the registered spot trades on the interbank market functioning within the Bloomberg trade platform. Then, the official exchange rate of GEL against other foreign currencies is determined according to the rate on international markets on the basis of cross-currency exchange rates.
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Puzanova, E. V. "Forecast of Epizootic situation for main helminthoses of Farm livestock in the Russian Federation for 2020." Russian Journal of Parasitology 14, no. 2 (June 22, 2020): 53–61. http://dx.doi.org/10.31016/1998-8435-2020-14-2-53-61.
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The purpose of the research is forecasting an epizootic situation for the main helminthoses of farm livestock in the Russian Federation for 2020.According to the WAHID of the International Office of Epizootics (Office International des Epizooties – QIE), the following zoonotic helminthoses were recorded in the Russian Federation in 2019: 489 people were infected with echinococcosis (causative agents were Echinococcus granulosus and E. multilocularis), among them 4 people died, 42 were infected with Trichinella, and 40 contracted cysticercosis. 382 people suffering from toxoplasmosis were registered, among them 3 died. The infection was caused by ingestion of poorly cooked meat (tissue cysts) which had not undergone diagnostic testing before being supplied to retail trade system. For purposes of the country’s food safety in the field of controlling livestock inventory, products obtained from livestock and health security, the annual monitoring (forecast) is becoming relevant for helminth-contaminated areas of the Russian Federation among livestock.
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Pugachevska, K. Y., A. H. Lyzanets, and M. V. Gomba. "Determinants of Domestic Trade Development in Ukraine." Business Inform 10, no. 525 (2021): 240–46. http://dx.doi.org/10.32983/2222-4459-2021-10-240-246.
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Intensification of globalization processes and transition of economically developed countries to the post-industrial stage of development determine the modern vector of structural and institutional transformation of the domestic market as a whole and trade in particular. The article is aimed at estimating the determinants of the development of domestic trade in Ukraine. The indicators of internal trade development are analyzed. The regional structure of retail turnover of Ukraine is provided. The risks and threats of foreign trade liberalization for domestic producers are characterized. The share of imported food and non-food products sold through the trade network of enterprises is computed. The commodity structure of imports by wide economic categories is provided. The risks of growing import dependence of the Ukrainian economy in terms of goods for final and intermediate consumption are identified. It is substantiated that one of the important vectors of improving the efficiency of the national economy is structural changes in the sphere of domestic trade. The prospects for the development of domestic trade in Ukraine are generalized, including those caused by the impact of the COVID-19 pandemic. It is argued that the coronavirus crisis is one of the key challenges for business in modern conditions, covering all its aspects – from sectoral to global supply chains. The priority of digital transformation of enterprises in order to protect their own position from high technologies of competitors and the opportunity to take advantage of greater functionality of digital business models with their adaptability and performance is determined. It is substantiated that the processes of globalization in the context of the coronavirus crisis have slowed down, which can lead to significant changes in the structure of the market, affect the distribution of online and offline trading. The prospect of further research in this direction is the forecasting of challenges and threats of the post-pandemic development for the domestic market of Ukraine.
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Nizamutdinov, М. M., and V. V. Oreshnikov. "Economic and Mathematical Models and Tools Development for Forecasting the Level of Attractiveness of Russian Cities." Economics, taxes & law 12, no. 4 (September 6, 2019): 68–79. http://dx.doi.org/10.26794/1999-849x-2019-12-4-68-79.
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The subject of the research is the factors influencing the attractiveness of Russian cities for the population, business and tourism. The objects of the research via economic and mathematical methods are the cities of the Russian Federation with population over 100 thousand people and the parameters of their social-economic development. The purpose of the research is economic and mathematical modeling of the attractiveness change level of Russian cities. In the course of the research a system of regressive equations has been formed, and a corresponding dispersion analysis has been conducted. As the factors influencing the attractiveness of cities for people the authors detected the following ones: the number of residents, housing, payroll rate, crime rate, and medical service density. To evaluate the attractiveness of cities for businesses the authors study the production volume, the volume of retail trade turnover, and the number of people living in the city. On the whole, the regression equations obtained meet the case and can be used henceforward with the aim of forecasting the change of indicators under study. Functional blocks of tools for monitoring and forecasting attractiveness levels of cities are proposed. The key ones are the blocks of forming the task, creating scenarios, forecasting, information analysis, regions rating forming, results visualization. It is concluded that being an integral system, models of cities’ attractiveness for people, business and tourism supplement each other and make it possible to fulfill a comprehensive approach to solving the problem. The results obtained can be used by the authorities in order to solve problems concerning integrated territorial development of the Russian Federation.
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Ilyash, Olha, Taras Vasyltsiv, Ruslan Lupak, and Volodymyr Get’manskiy. "Models of efficiency of functioning in trading enterprises under conditions of economic growth." Bulletin of Geography. Socio-economic Series 51, no. 51 (March 1, 2021): 7–24. http://dx.doi.org/10.2478/bog-2021-0001.
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Abstract The socio-economic situation in Ukraine suggests that there is insufficient research into the applicability of the model of economic development in forecasting the economic environment in which trade enterprises function. Researchers into issues relating to the efficiency of enterprises’ functioning focus their interest on comprehensively describing efficiency indicators and determining the factors influencing it. There continues to be insufficient work on measuring efficiency and the extent to which it is limited by types of economic growth (development), based on the theory of marginal product of George Clark and the results of multiple models of production and trade functions (P. Douglas, R. Solow, E. Denison, Harrod, Samuelson-Hicks, Domar and others). Therefore, this study focuses on the process of assessing the effectiveness of trading enterprises in the trade sector in 2010–18 in conditions of economic growth and an economic downturn. This article aims to examine the models of efficient functioning of trading enterprises in conditions of economic growth. It is evidenced that the criterion for measuring efficiency is the evaluation of static and dynamic efficiency of trade activities, which allows changes in the used assets to be taken into account and testifies to the integration of diminishing returns and economic fluctuations in macro and microsystems. The article shows that in order to qualitatively and completely evaluate the efficiency of the functioning of trading enterprises, it is necessary to consider all possible factors. According to Clark's law, the authors substantiate an approach to evaluating performance based on simple one-factor models; the approach evidences that future studies seeking ways to improve efficiency, but that focus on changes in resources, will be erroneous, unjustified, and will most likely reduce the effectiveness of the resource under study. This model will help: determine and forecast the efficiency of enterprises at any point in the economic cycle; provide the necessary information on the required amount of investment, on depreciation rates, and on the optimal amount of labour potential of an enterprise; and define the volume of expected income during economic crisis or recovery. Some applied recommendations in terms of managing the efficiency of trading enterprises are aimed at solving the methodological problem of constructing isoquant maps for a particular product line group and at selecting the optimal predictor for forecasting trade processes. The practical value of the proposed model also lies in improving the parameters of positioning of the enterprise's goods in target market segments, reducing operating costs, accelerating the turnover of inventories and withdrawing illiquid current assets, and increasing the efficiency of retail areas.
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Chernukhina, Galina G., and Оlga Yu Ermolovskaya. "Development of Dark Stores as a Competitive Form of Delivery of Goods." Journal of Modern Competition 15, no. 4 (November 16, 2021): 50–59. http://dx.doi.org/10.37791/2687-0657-2021-15-4-50-59.
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The aim of the scientific article is to study the transition of retail entities from the store format to the e-commerce format using the competitive advantages of dark stores. The subject of the research is competitive advantages when using high-tech and flexible forms of supply chains and in the delivery of goods. The relevance of the scientific article is due to the fact that the pace of development of online trade in 2018-2020 testifies to the growth of the largest companies in the e-commerce sector annually. This growth is due to high-tech trend trends that have been actively developing in recent years. They are structurally formed into a single system, the elements of which are: the use of Big data, the digital transformation of trade business processes, the integration of global marketing technologies, the use of smart forecasting and analysis of consumer behavior, personalization, orientation towards virtual content. This system is inherently aimed at the globalized development of trade relations. The authors investigate the essence of the concept of “dark store”, analyze the competitiveness of this phenomenon in e-commerce in modern conditions. Dark stores promote the development of a new generation of commerce, with competitive advantages, they do not interfere with existing production and distribution processes, but rather complement them. Currently, all large trade organizations of the food and non-food sectors are engaged in electronic commerce. First of all, online commerce is organized through online stores and marketplaces, but there are still many other electronic means of making a transaction - this is a page on a social network or a chatbot of a messenger, dark stores that require additional research. It is appropriate to characterize such marketplaces as aggregator sites playing the role of specialized structural intermediaries with a stable base engaged in the sale and distribution of the products of commercial agents. E-commerce in the dark store format thus contributes to the high-quality and competitive development of global economic ties.
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Murdoch, Brock, Bruce Dehning, and Paul Krause. "Further Evidence On The Ability Of FIFO And LIFO Earnings To Predict Operating Cash Flows: An Industry Specific Analysis." Journal of Applied Business Research (JABR) 29, no. 4 (June 28, 2013): 1231. http://dx.doi.org/10.19030/jabr.v29i4.7929.
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The continuingconvergence of U.S. GAAP with International Accounting Standards has broughtinto question the future use of the LIFO inventory method in the U.S. Since theFinancial Accounting Standards Board (2010) has stipulated that earnings shouldaid investors and creditors in their quest to forecast future cash flows to theenterprise, this research examines whether FIFO earnings or LIFO earnings ispreferable, for this purpose, as an aid to ex ante operating cash flow itself,over a three-year forecast horizon. We conclude that ex ante operating cashflows are quite useful in forecasting operating cash flows across industries forup to three years-ahead.We find differingresults with respect to the incremental predictive content of LIFO versus FIFO earnings,depending on industry and the forecast horizon. For the Manufacturing industry andthe Services industry, LIFO earnings is superior to FIFO earnings forforecasting operating cash flows across the entire three year forecast horizon.In contrast, for the Retail Trade industry and the Finance, Insurance, and RealEstate industry, FIFO earnings is preferable for all three forecasts ofoperating cash flows.For firms in the Transportation,Communications, Electric, Gas, and Sanitary Services industry and in the WholesaleTrade industry, mixed results are observed. Insufficient LIFO data areavailable for evaluations of the Agriculture, Forestry, and Fishing industry,the Mining industry, the Construction industry, and the Public Administrationindustry.
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Borodin, V. A., and O. A. Shunina. "Regional Market of Education Services: Development Problems." Vestnik of the Plekhanov Russian University of Economics, no. 4 (July 29, 2018): 173–83. http://dx.doi.org/10.21686/2413-2829-2018-4-173-183.
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Economy of the Altay territory is a diversified complex, where key types of economic activity are manufacturing industry, agriculture, wholesale and retail trade. A specific feather of the territory is a high proportion of the rural population – 39.3% of the total number of employed people (23% in Russia) and a low number of students of primary, secondary vocational and higher education as compared with all – Russian figures. According to the strategy of social and economic development of the Altay territory up to 2025 the priority lines in the territory economy are bio-technology, pharmaceutics, certain branches of machine building and food industry, tourismrecreation and transportation complexes, high-profit services of the service sector, including finance services, as well as services in the field of high technologies. The level of training specialists and skilled workers for this diversified labour market in general is sufficient, training is conducted by more than 200 specializations in all priority lines however, the training in the vocational education system fell down by 20% during the last 5 years. The demographic situation in the territory seriously influenced these figures. Changes in the structure of the GRP of the Altay territory caused the reduction in the proportion of manufacturing industry and agriculture, which affected negatively the level of population employment in production industries. The authors studied the key trends of the system of vocational education development in the territory in 2012–2016 and showed that the misbalance of education service supply with the real need in them on the labour market was caused both by the absence of reliable methods of labour market forecasting by quantity and structure and the impact of population preferences assessing subjectively the demand for labour resources proceeding from personal ideas about the demand for this or that profession. It can lead to the excess number of specialists of ‘popular’ professions and difficulties with their employment and, on the other hand – to the shortage of needed professional staff.
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Qin, Juanjuan, Liguo Ren, and Liangjie Xia. "Carbon Emission Reduction and Pricing Strategies of Supply Chain under Various Demand Forecasting Scenarios." Asia-Pacific Journal of Operational Research 34, no. 01 (February 2017): 1740005. http://dx.doi.org/10.1142/s021759591740005x.
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This study incorporates consumer’s low carbon awareness (CLA) and demand forecasting into supply chains that adopt the cap-and-trade system. Three demand forecasting scenarios are discussed, namely, information sharing, full information sharing, and retailer-only forecasting. Strategies for pricing and reduction of equilibrium of carbon emission are derived. We also compare the decisions and profits in the three cases and present numerical analysis.
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V. Akberdina, Victoria, Oksana V. Tretyakova, and Andrey I. Vlasov. "A methodological approach to forecasting spatial distribution of workplaces in an industrial metropolis." Problems and Perspectives in Management 15, no. 4 (December 19, 2017): 50–61. http://dx.doi.org/10.21511/ppm.15(4).2017.05.
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Many world cities retain their unique industrial status. Such a feature of the economy of an industrial metropolis imposes additional requirements on the development of the forecast of spatial distribution of workplaces. The article highlights the contradictions of the long-term development of an industrial megalopolis, which become scenic forks, when forecasted. These include optimization of the industrial and trade-service sectors of the economy, the ratio of inertial and innovative development vectors, variability of migration flows and the choice of the agglomeration model type. The article is devoted to the problem of forecasting the development of a large metropolis, where the industrial sector plays a significant role in the economy. At the methodological level, the article justifies principles of spatial development of an industrial metropolis. The article describes forecasting tools for spatial location of workplaces, based on a combination of several models. The study was performed through the example of Ekaterinburg – the industrial capital of Russia; the metropolis scenarios were justified until 2035; the forecast of spatial distribution was calculated through the example of the two sectors competing for investments – industrial and trade-service. The authors substantiate spatial distribution of workplaces taking into account the projected number of people employed, the number of population of working age and distinguishing features of transport behavior of citizens. The paper demonstrates that the number of large industrial enterprises in a historically industrial center and its first zone decreases, and the modern industry in the form of small and medium-sized businesses located in industrial parks commence gradually forming a circuit with nodes on transport routes towards the largest consumer territories.
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Oliveira, José Manuel, and Patrícia Ramos. "Assessing the Performance of Hierarchical Forecasting Methods on the Retail Sector." Entropy 21, no. 4 (April 24, 2019): 436. http://dx.doi.org/10.3390/e21040436.
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Retailers need demand forecasts at different levels of aggregation in order to support a variety of decisions along the supply chain. To ensure aligned decision-making across the hierarchy, it is essential that forecasts at the most disaggregated level add up to forecasts at the aggregate levels above. It is not clear if these aggregate forecasts should be generated independently or by using an hierarchical forecasting method that ensures coherent decision-making at the different levels but does not guarantee, at least, the same accuracy. To give guidelines on this issue, our empirical study investigates the relative performance of independent and reconciled forecasting approaches, using real data from a Portuguese retailer. We consider two alternative forecasting model families for generating the base forecasts; namely, state space models and ARIMA. Appropriate models from both families are chosen for each time-series by minimising the bias-corrected Akaike information criteria. The results show significant improvements in forecast accuracy, providing valuable information to support management decisions. It is clear that reconciled forecasts using the Minimum Trace Shrinkage estimator (MinT-Shrink) generally improve on the accuracy of the ARIMA base forecasts for all levels and for the complete hierarchy, across all forecast horizons. The accuracy gains generally increase with the horizon, varying between 1.7% and 3.7% for the complete hierarchy. It is also evident that the gains in forecast accuracy are more substantial at the higher levels of aggregation, which means that the information about the individual dynamics of the series, which was lost due to aggregation, is brought back again from the lower levels of aggregation to the higher levels by the reconciliation process, substantially improving the forecast accuracy over the base forecasts.
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Sardar, Suman Kalyan, Biswajit Sarkar, and Byunghoon Kim. "Integrating Machine Learning, Radio Frequency Identification, and Consignment Policy for Reducing Unreliability in Smart Supply Chain Management." Processes 9, no. 2 (January 29, 2021): 247. http://dx.doi.org/10.3390/pr9020247.
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Adopting smart technologies for supply chain management leads to higher profits. The manufacturer and retailer are two supply chain players, where the retailer is unreliable and may not send accurate demand information to the manufacturer. As an advanced smart technology, Radio Frequency Identification (RFID) is implemented to track and trace each product’s movement on a real-time basis in the inventory. It takes this supply chain to a smart supply chain management. This research proposes a Machine Learning (ML) approach for on-demand forecasting under smart supply chain management. Using Long-Short-Term Memory (LSTM), the demand is forecasted to obtain the exact demand information to reduce the overstock or understock situation. A measurement for the environmental effect is also incorporated with the model. A consignment policy is applied where the manufacturer controls the inventory, and the retailer gets a fixed fee along with a commission for selling each product. The manufacturer installs RFID technology at the retailer’s place. Two mathematical models are solved using a classical optimization technique. The results from those two models show that the ML-RFID model gives a higher profit than the existing traditional system.
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Hasin, M. Ahsan Akhtar, Shuvo Ghosh, and Mahmud A. Shareef. "An ANN Approach to Demand Forecasting in Retail Trade in Bangladesh." International Journal of Trade, Economics and Finance, 2011, 154–60. http://dx.doi.org/10.7763/ijtef.2011.v2.95.
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Harasym, Ivan, Ihor Yaskal, and Inna Lopashchuk. "USE OF THE EXTRAPOLATION METHOD FOR FORECASTING OF WHOLESALE AND RETAIL TRADE DEVELOPMENT." Market Infrastructure, no. 38 (December 2019). http://dx.doi.org/10.32843/infrastruct38-13.
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Safarov, Bakhtiyor. "Priority Guidelines Of The Service Sphere Development In Uzbekistan." European Journal of Business and Economics 2 (April 1, 2011). http://dx.doi.org/10.12955/ejbe.v2i0.95.
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The present research article is devoted to study the priorities of service sphere development in Uzbekistan. The comparative analysis of service sphere development during 1996-2009 were presented, survey of disperse territories, analysis and generalization methods used to identify trends in services sphere. Disperse markets were grouped into markets with high, medium and low development level. Retail trade is identified one of the most important components of service sphere in Uzbekistan. Retail turnover figures were predicted until 2013 used retrospective data for forecasting. Linear trend - trends of increase or decrease of index, visual analysis of time series dynamics(graphic presentation) were used to solve the studied problem. Main priorities and targets in service sphere in Uzbekistan and it’s role in economy were determined.
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Раимбеков, Ж. С., Б. У. Сыздыкбаева, О. РыскуловаЖ, Б. А. Жуматаева, Z. Raimbekov, B. Syzdykbayeva, B. Syzdykbayeva, Z. Ryskulova, and B. Zhumatayeva. "ASSESSMENT OF THE EFFICIENCY OF THE FUNCTIONING OF THE COMMODITY NETWORK." Вестник Казахского университета экономики, финансов и международной торговли, no. 4(45) (February 10, 2022). http://dx.doi.org/10.52260/2304-7216.2021.4(45).15.
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На основе предварительно отобранных систем показателей, с использованием статистических материалов и современных экономико-математических методов анализа и прогнозирования, проведен всесторонний анализ состояния функционирования деятельности сферы торговли. Для комплексного эконометрического анализа эффективности отрасли торговли были использованы методы анализа временных рядов, корреляционно-регрессионного и факторного анализов.Для математической оценки влияния социальныхых, экономических, финансовых, организационных, производственных и инфраструктурных факторов на показатели эффективности деятельности сферы торговли в процессе товародвижения были предложены 23 факторов, рассматриваемые в качестве независимых переменных и 17 факторов в качестве критериев эффективности деятельности торговли.На основе комплексной эконометрической оценки деятельности торговли выявлены основные закономерности и тенденции, присущие процессу развития торговли Казахстана; проанализированы факторы, влияющие на эффективность финансово-хозяйственной деятельности отрасли торговли; предложены практические рекомендации по совершенствованию финансово-хозяйственной деятельности сферы торговли; выделены основные направления повышения эффективности сферы торговли в Казахстане; определены основные приоритетные направления развития в торговле - рост социально-экономических показателей населения (доходы, занятость и т.д.), а также показателей торговли: товарных запасов, торговой площади магазинов, складских площадей. On the basis of pre-selected systems of indicators, using statistical materials and modern economic and mathematical methods of analysis and forecasting, a comprehensive analysis of the state of functioning of the activity of the trade sphere was carried out. For a comprehensive econometric analysis of the efficiency of the trade sector, the methods of time series analysis, correlation-regression and factor analyzes were used.For a mathematical assessment of the influence of social, economic, financial, organizational, production and infrastructural factors on the performance indicators of the trade in the process of commodity circulation, 23 factors were proposed, considered as independent variables and 17 factors as criteria for the effectiveness of trade.On the basis of a comprehensive econometric assessment of trade activities, the main patterns and trends inherent in the development of trade in Kazakhstan have been identified; the factors influencing the efficiency of financial and economic activity of the trade sector are analyzed; suggested practical recommendations for improving the financial and economic activities of the trade sector; the main directions of increasing the efficiency of the trade sphere in Kazakhstan are highlighted; the main priority directions of development in trade are determined - the growth of socio-economic indicators of the population (income, employment, etc.), as well as indicators of trade: commodity stocks, retail space of stores, warehouse space.
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Górecki, Krzysztof, Grzegorz Jaworski, and Tomasz Kurowski. "Planowanie przychodów ze sprzedaży na przykładzie przedsiębiorstw z branży- handel hurtowy i detaliczny pojazdami samochodowymi; naprawa pojazdów samochodowych (Forecasting Sales Revenue of Companies in the Industry-Wholesale and Retail Trade of Motor Vehicles and Repair of Motor Vehicles)." SSRN Electronic Journal, 2013. http://dx.doi.org/10.2139/ssrn.2251497.
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Kumari, Dr N. Vinaya, A. Mokshit, Vineet, and Yashwanth. "Stock Price Prediction Using Machine Learning." Emperor Journal of Applied Scientific Research 04, no. 07 (2022). http://dx.doi.org/10.35338/ejasr.2022.4704.
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Shares in publicly traded companies, or equity shares, can be purchased and sold on the stock market. There are three basic types of stock market investors. All three types of investors: FII (foreign institutional investors), DII (domestic investors), and retail investors. Foreign Institutional Investors, such as mutual funds and banks, who have the experience and knowledge necessary to make their investment. Non-professional investors are known as retail investors. Machine learning is used to make an accurate prediction with less risk management in the stock market because there is a lot of uncertainty there. Through forecasting and LSTM (Long/Short Term Memory), we can theoretically predict stock prices through the use of machine learning. Effective stock market prediction gives us some suggestions on trading strategies, which is why stock market prediction is so important when it comes to investments. There is, however, no way to guarantee that the data will be 100% accurate because of future uncertainty in the field of study. For stock price prediction, this paper reviews studies on machine learning techniques and algorithms.
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Duan, H. W., M. T. Wang, and Y. S. Ye. "Financing and information sharing in capital-constrained supply chain." Advances in Production Engineering & Management, September 30, 2022, 263–78. http://dx.doi.org/10.14743/apem2022.3.435.
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This paper focuses on financing choices and information-sharing strategies in the capital-constrained supply chain. We model four scenarios with the capital constraints of the respective manufacturer and retailer using bank credit financing (BCF) and trade credit financing (TCF) approaches to address financing problems, and investigate the retailer’s willingness to share demand forecasting information. We find that TCF is an equilibrium financing choice for a capital-constrained supply chain. However, when a capital-constrained member chooses TCF, sharing demand information over the supply chain becomes more difficult. The interactions between the choices of financing approach and information sharing based on the game equilibriums, as well as the conditions that encourage the well-funded member to offer TCF in the capital-constrained supply chains, have also been analytically explored and numerically verified. Additional managerial insights are provided for discussions.
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"Commodities into food." Philosophical Transactions of the Royal Society of London. B, Biological Sciences 310, no. 1144 (September 12, 1985): 317–25. http://dx.doi.org/10.1098/rstb.1985.0122.
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It is not surprising that past predictions of the extent of adoption of new technology by the food and agricultural industries have only been partly realized. This is a result of the difficulty of forecasting the take-up of technology that is capable of being transferred from other industries, for example, process control methods and the advent of new packaging materials. Most technology that is adopted is normally incremental over the existing technology and forecasting of this type is best done by specific experts within the industry. Factors which influence uptake of technology in the food industry include not only the available technology, but also the supply of raw materials, economics and disposable income, food habits, health and nutrition and market requirements. In addition to these there is legislation, which imposes compositional, labelling and trade requirements on grower, processor and retailer. New products and processes are determined by all these factors, the overriding influence being the consumer’s requirement for palatable and nutritious foods that provide value for money. In the cereals-processing industry significant developments have taken place in the provision of U.K. wheat varieties for breadmaking. The U.K. is now in the position where the bulk of its breadmaking wheats are homegrown. Further advances can be made by investing in applied research into those characteristics of bread wheats which are determinants of good bread flours, that in turn will help in the provision of suitable bread wheat varieties. A less traditional area is that of flour fractionation. With the massive wheat surpluses now available to us there is potential for further uses, both food and non-food, for wheat starch and gluten. An example of the way in which biotechnology will play a role in the 1990s is the use of wheat starch, or other plant starch, as biomass for the conversion of carbohydrate into a protein-rich food — myco-Protein — by using a sophisticated fermentation process. The effects of future requirements of the food industry on primary production will result in greater flexibility and in crops that are of consistently high quality to supply the new computer-controlled food processes under development. To the consumer there will often be little apparent qualitative change: unseen technology will enable the production and distribution of foods which have a much greater perceived freshness and lower real cost than at present. The 1990s will bring new pressures on farmer and food manufacturer alike, in the form of increased competition both nationally and internationally. It is necessary to follow up government initiatives already made to ensure a collaborative effort by producers and food manufacturers to identify the optimal balance of primary production; also to support research to identify and apply new technology to the efficient and competitive conversion of commodities into food products.