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Journal articles on the topic 'Corporations – Growth – Mathematical models'

Author: Grafiati

Published: 10 March 2023

Last updated: 31 July 2025

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1

Glushchenko, V., and A. Falaleeva. "Paradigm of increasing employee loyalty of high-tech corporations." Bulletin of Science and Practice 5, no. 3 (2019): 272–91. https://doi.org/10.33619/2414-2948/40/33.

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The subject of the article is the development of the paradigm of increasing the loyalty of staff of high-tech corporations; the object of the article is the loyalty of staff of high-tech corporations; the relevance of the article is connected with the need to increase the loyalty of staff of high-tech corporations in the interests of increasing the effectiveness and efficiency of their innovation; the purpose of the article is the growth of the level of loyalty of staff of high-tech corporations through the formation and implementation of the paradigm of increasing the loyalty of staff; t

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2

Sofiko Dzhvarsheishvili, Sofiko Dzhvarsheishvili. "Developing Tendencies of Foreign Direct Investments." New Economist 16, no. 03 (2022): 41–47. http://dx.doi.org/10.36962/nec62-6303-042021-41.

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The formation process of foreign direct investment theories began in the second half of the twentieth century, it was period that the importance of foreign direct investment (FDI) in international capital movement increased, and this period was characterized by the rapid growth of multinational enterprises, which, in turn, is a major source of FDI. Scientific and technological progress has become the basis for decisions of transnational companies to invest capital in to different parts of the world and to coordinate and control its many branches from one country. During this period scientists

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Et.al, D. Priyadarshini. "A Novel Technique for IDS in Distributed Data Environment Using Merkel Based Security Mechanism for Secure User Allocation." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 4284–97. http://dx.doi.org/10.17762/turcomat.v12i3.1720.

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Multiple corporations and people frequently launching their data in the cloud environment. With the huge growth of data mining and the cloud storage paradigm without checking protection policies and procedures that can pose a great risk to their sector. The data backup in the cloud storage would not only be problematic for the cloud user but also the Cloud Service Provider (CSP). The unencrypted handling of confidential data is likely to make access simpler for unauthorized individuals and also by the CSP. Normal encryption algorithms need more primitive computing, space and costs for storage.

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4

Du, Yuping, Rongping Kang, and Yinbin Ke. "Understanding the growth models of Chinese multinational corporations." International Journal of Chinese Culture and Management 1, no. 4 (2008): 451. http://dx.doi.org/10.1504/ijccm.2008.020010.

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5

Dolganova, Olga, and Valeriy Lokhov. "Mathematical models of growth deformation." PNRPU Mechanics Bulletin 1 (March 30, 2014): 126–41. http://dx.doi.org/10.15593/2224-9893/2014.1.06.

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6

Pavankumari, V. "Mathematical and Stochastic Growth Models." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1576–82. http://dx.doi.org/10.22214/ijraset.2021.39055.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world that involve many research problems in the different fields of applied statistics. Nevertheless, still, there is an equally large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicte

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7

Kumari, V. Pavan, Venkataramana Musala, and M. Bhupathi Naidu. "Mathematical and Stochastic Growth Models." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 987–89. http://dx.doi.org/10.22214/ijraset.2022.42330.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world involves many research problems in the different fields of applied statistics. Nevertheless, still, there are an equally a large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted

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8

Oliveri, Hadrien, and Alain Goriely. "Mathematical models of neuronal growth." Biomechanics and Modeling in Mechanobiology 21, no. 1 (2022): 89–118. http://dx.doi.org/10.1007/s10237-021-01539-0.

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AbstractThe establishment of a functioning neuronal network is a crucial step in neural development. During this process, neurons extend neurites—axons and dendrites—to meet other neurons and interconnect. Therefore, these neurites need to migrate, grow, branch and find the correct path to their target by processing sensory cues from their environment. These processes rely on many coupled biophysical effects including elasticity, viscosity, growth, active forces, chemical signaling, adhesion and cellular transport. Mathematical models offer a direct way to test hypotheses and understand the un

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9

Leung, C. H. C. "Mathematical Models of Fire Growth." Computer Journal 28, no. 2 (1985): 179–83. http://dx.doi.org/10.1093/comjnl/28.2.179.

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10

Dmitriev, V. I., E. S. Kurkina, and O. E. Simakova. "Mathematical models of urban growth." Computational Mathematics and Modeling 22, no. 1 (2011): 54–68. http://dx.doi.org/10.1007/s10598-011-9088-8.

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11

Suzuki, Takashi. "Mathematical models of tumor growth systems." Mathematica Bohemica 137, no. 2 (2012): 201–18. http://dx.doi.org/10.21136/mb.2012.142866.

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12

Roose, Tiina, S. Jonathan Chapman, and Philip K. Maini. "Mathematical Models of Avascular Tumor Growth." SIAM Review 49, no. 2 (2007): 179–208. http://dx.doi.org/10.1137/s0036144504446291.

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13

Pletnev, D. A., and E. V. Kozlova. "Institutional Structure of Corporations (the Case of Large Russian Corporations)." Zhurnal Economicheskoj Teorii 18, no. 1 (2021): 87–102. http://dx.doi.org/10.31063/2073-6517/2021.18-1.6.

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Modern corporation is the main form of social production but its activity and development still remain a largely underex-plored question. Economic theory predominantly relies on simplified approaches based on mathematical modeling to study cor-porations, which gives us little in-depth understanding of the essence of this phenomenon. On the other hand, applied research on corporations does not rise to the level of theoretically significant generalizations. This paper proposes the following theoretical and methodological approach to analyzing the phenomenon of corporation: we identify institutio

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14

Buschang, P. H., R. Tanguay, L. LaPalme, and A. Demirjian. "Mandibular growth prediction: mean growth increments versus mathematical models." European Journal of Orthodontics 12, no. 3 (1990): 290–96. http://dx.doi.org/10.1093/ejo/12.3.290.

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15

Werhane, Patricia H. "Exporting Mental Models: Global Capitalism in the 21st Century." Business Ethics Quarterly 10, no. 1 (2000): 353–62. http://dx.doi.org/10.2307/3857720.

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Abstract:The most serious ethical challenge facing multinational corporations in the next century is their exportation of the mental model of Western-style capitalism. This model promises that industrialized free enterprise in a free trade global economy, where businesses and entrepreneurs can pursue their interests competitively without undue regulations or labor restrictions, will produce growth and well-being, i.e., economic good, in every country or community where this phenomenon is allowed to operate. This paper points to some limitations to this model and illustrates how multinational c

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16

Brondoni, Silvio M., and Mario Risso. "Ouverture de ‘New Horizons in Global Management’." Symphonya. Emerging Issues in Management, no. 1 (November 30, 2023): 1–8. http://dx.doi.org/10.4468/2023.1.01ouverture.

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The Russian-Ukrainian War introduced new elements into the strategic assessments of large global corporations, changing competitive horizons and developing new models of competition. The impact of the recent BRICS expansion on the global corporations management and on the growth of sustainability goals reflects a growing global new competitive landscape that places global corporations in a delicate position as a possible counterweight to the EU, to the U.S and to the Asian World.

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17

Cannell, Melvin G. R. "Mathematical Models of Crop Growth and Yield." Crop Science 43, no. 3 (2003): 1145. http://dx.doi.org/10.2135/cropsci2003.1145.

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18

Buschini, MLT, MAP Abuabara, and Miguel Petrere-Jr. "Mathematical models for Isoptera (Insecta) mound growth." Brazilian Journal of Biology 68, no. 3 (2008): 529–33. http://dx.doi.org/10.1590/s1519-69842008000300009.

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In this research we proposed two mathematical models for Isoptera mound growth derived from the Von Bertalanffy growth curve, one appropriated for Nasutitermes coxipoensis, and a more general formulation. The mean height and the mean diameter of ten small colonies were measured each month for twelve months, from April, 1995 to April, 1996. Through these data, the monthly volumes were calculated for each of them. Then the growth in height and in volume was estimated and the models proposed.

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19

Kondratyev, A., A. Lyaptsev, and I. Mikhailova. "Mathematical modeling of thrombus growth phenomenological models." Applied Mathematical Sciences 9 (2015): 429–46. http://dx.doi.org/10.12988/ams.2015.49771.

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20

FUJIKAWA, Hiroshi, and Takeshi ITOH. "Mathematical Models for Microbial Growth in Foods." Japanese Journal of Food Microbiology 12, no. 4 (1996): 203–8. http://dx.doi.org/10.5803/jsfm.12.203.

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21

Villacorta, José A., Jorge Castro, Pilar Negredo, and Carlos Avendaño. "Mathematical foundations of the dendritic growth models." Journal of Mathematical Biology 55, no. 5-6 (2007): 817–59. http://dx.doi.org/10.1007/s00285-007-0113-7.

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22

Feinberg, Alec. "Accelerated Reliability Growth Models." Journal of the IEST 37, no. 1 (1994): 17–23. http://dx.doi.org/10.17764/jiet.2.37.1.f2u73m8022207868.

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Extending reliability growth so that it can be applied in the area of accelerated testing will enable one to apply all the reliability growth tools and their planning advantages. This paper describes linking these two areas together into what is termed accelerated reliability growth testing (ARGT). Mathematical equations of ARGT for both iso-stress and step-stress accelerated testing are modelled.

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23

Pavlov, Alexander, and Mykyta Kyselov. "MATHEMATICAL MODELS AND METHODS OF COORDINATED PLANNING." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (10) (December 19, 2023): 3–8. http://dx.doi.org/10.20998/2079-0023.2023.02.01.

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Modern processes of globalization and economic competition require a significant increase in the requirements for the professional degree of top-level managers who manage the activities of international corporations, regional economies, branch ministries, etc. Their efficient operation is impossible without the use of basic scientific developments and appropriate software which implement the main qualitative law of complex organizational and production systems management: the law of coordinated management (planning), when management decisions at the top level take into account interests that m

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24

Lampl, Michelle. "Perspectives on modelling human growth: Mathematical models and growth biology." Annals of Human Biology 39, no. 5 (2012): 342–51. http://dx.doi.org/10.3109/03014460.2012.704072.

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25

Hoang, Chau, Tuan Anh Phan, and Jianjun Paul Tian. "Stochastic Models for Ontogenetic Growth." Axioms 13, no. 12 (2024): 861. https://doi.org/10.3390/axioms13120861.

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Based on allometric theory and scaling laws, numerous mathematical models have been proposed to study ontogenetic growth patterns of animals. Although deterministic models have provided valuable insight into growth dynamics, animal growth often deviates from strict deterministic patterns due to stochastic factors such as genetic variation and environmental fluctuations. In this study, we extend a general model for ontogenetic growth proposed by West et al. to stochastic models for ontogenetic growth by incorporating stochasticity using white noise. According to data variance fitting for stocha

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26

Babák, Libor, P. Šupinová, and R. Burdychová. "Growth models of Thermus aquaticus and Thermus scotoductus." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, no. 5 (2012): 19–26. http://dx.doi.org/10.11118/actaun201260050019.

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Members of the genusThermusfamily are signifiant producers of secondary metabolites, which are very commonly used in industry. Beside the productivity, it is also important to study the growth curve of each strain. The mathematical models which are commonly used to describe behavior of microbial strains under different physical and chemical conditions can reduce measured data.In this study, the mathematical models which describe only the microbial count were used. For analysis, Verhulst model, von Bertalanffy model and Richards model were chosen.During the cultivation ofThermus aquaticusandThe

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27

Bhattachar, Atanu, and B. Satheesan. "Applications of Mathematical Models on Tumor Growth Rate." Asian Journal of Mathematics & Statistics 7, no. 2 (2014): 60–67. http://dx.doi.org/10.3923/ajms.2014.60.67.

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28

Mugarab-Samedi, Fuad, Sahbaz Heir, and Saboor Ul-Bashar. "Mathematical Models and their Application in Cancer Growth." Acta Scientific Cancer Biology 5, no. 7 (2021): 35–41. http://dx.doi.org/10.31080/ascb.2021.04.0323.

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29

MARUŠIĆ, M., and S. VUK-PAVLOVIĆ. "PREDICTION POWER OF MATHEMATICAL MODELS FOR TUMOR GROWTH." Journal of Biological Systems 01, no. 01 (1993): 69–78. http://dx.doi.org/10.1142/s0218339093000069.

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We compared the Gompertz model, the generalized Gompertz model, the Piantadosi model, the autostimulation model and the polynomials for the power to predict growth of multicellular tumor spheroids as paradigms of the prevascular phase of tumor growth. For the comparison of models we developed a criterion that established the Gompertz model as the model with the best prediction power. The prediction power of the remaining models was ranked in declining order: the generalized Gompertz model; the mutually indistinguishable Piantadosi model and the autostimulation model; and the polynomials. The r

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30

Ledford, A. W., and T. J. Cole. "Mathematical models of growth in stature throughout childhood." Annals of Human Biology 25, no. 2 (1998): 101–15. http://dx.doi.org/10.1080/03014469800005482.

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31

Lei, Jinzhi, Wing-Cheong Lo, and Qing Nie. "Mathematical models of morphogen dynamics and growth control." Annals of Mathematical Sciences and Applications 1, no. 2 (2016): 427–71. http://dx.doi.org/10.4310/amsa.2016.v1.n2.a6.

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32

López, S., M. Prieto, J. Dijkstra, M. S. Dhanoa, and J. France. "Statistical evaluation of mathematical models for microbial growth." International Journal of Food Microbiology 96, no. 3 (2004): 289–300. http://dx.doi.org/10.1016/j.ijfoodmicro.2004.03.026.

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33

Konovalchikova, Elena Nikolaevna, and Evgenii Evgenevich Ivashko. "Fitting growth model parameters for rainbow trout." Vestnik of Astrakhan State Technical University. Series: Fishing industry 2024, no. 2 (2024): 42–48. http://dx.doi.org/10.24143/2073-5529-2024-2-42-48.

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The purpose of the presented work is to assess the adequacy and selection of optimal parameters of mathematical models of fish growth in application to forecasting the growth of aquaculture trout in closed water supply installations (CWSI). To perform the assessment and comparison, 8 nonlinear mathematical models of fish growth were considered. Tabular (parametric) models of feed for trout cultivation in the CWSI were taken as a standard, and on their basis the selection of optimal parameters was carried out, bringing each of the mathematical models closer to the standard one. The results were

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34

San Vicente Portes, Luis. "Aggregate Gains of International Diversification through Foreign Direct Investment: An Inquiry into the Moderation of U.S. Business Cycles." Global Economy Journal 7, no. 4 (2007): 1850120. http://dx.doi.org/10.2202/1524-5861.1284.

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Over the last 20 years the U.S. economy has experienced a strong reduction in the volatility of GDP growth. This paper documents and models the rapid growth of multinational corporations as a source of gradual decline in output and investment volatility. The paper introduces internationally diversified multinational firms into the financial accelerator framework; where international operations provide multinational firms with smoother paths of net worth that result in less volatile financing costs, investment and production. Model simulations suggest that larger multinational corporations can

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35

Piccone, Ashley. "Improving urban growth models with fractional calculus." Scilight 2022, no. 43 (2022): 431105. http://dx.doi.org/10.1063/10.0014416.

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36

Heaps, Aaron J., Tyler D. Dawson, Jace C. Briggs, Megan A. Hansen, and Jamie L. Jensen. "Deriving Population Growth Models by Growing Fruit Fly Colonies." American Biology Teacher 78, no. 3 (2016): 221–25. http://dx.doi.org/10.1525/abt.2016.78.3.221.

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Population growth presents a unique opportunity to make the connection between mathematical and biological reasoning. The objective of this article is to introduce a method of teaching population growth that allows students to utilize mathematical reasoning to derive population growth models from authentic populations through active learning and firsthand experiences. To accomplish this, we designed a lab in which students grow and count populations of Drosophila over the course of 12 weeks, modifying abiotic and biotic limiting factors. Using the data, students derive exponential and logistic

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37

Kovacova, Maria, and Tomas Kliestik. "Logit and Probit application for the prediction of bankruptcy in Slovak companies." Equilibrium 12, no. 4 (2017): 775–91. http://dx.doi.org/10.24136/eq.v12i4.40.

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Research background: Prediction of bankruptcy is an issue of interest of various researchers and practitioners since the first study dedicated to this topic was published in 1932. Finding the suitable bankruptcy prediction model is the task for economists and analysts from all over the world. forecasting model using. Despite a large number of various models, which have been created by using different methods with the aim to achieve the best results, it is still challenging to predict bankruptcy risk, as corporations have become more global and more complex. Purpose of the article: The ai

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38

Venu, Vaisakh, Sreenath B., and Ramdas E. R. "Various Mathematical Models in Agricultural Engineering." Current Journal of Applied Science and Technology 42, no. 41 (2023): 13–20. http://dx.doi.org/10.9734/cjast/2023/v42i414263.

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This paper investigates the important role of mathematics in the solution of complicated issues in the field of agricultural engineering and technology. It shows examples of mathematical modelling and analytical techniques that are used in agriculture, such as Crop Growth, Irrigation Management, Soil Moisture Modeling , Environmental management, Pest and Disease Management, Fertilizer Applications, Watershed Management etc.

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39

Karev, Georgy P., and Faina S. Berezovskaya. "Mathematical Models for the "Schmalhgausent Law"." Journal of Biological Systems 11, no. 03 (2003): 245–64. http://dx.doi.org/10.1142/s0218339003000865.

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The empirical formula of growth (decrease) of biological objects, corresponding to polygonal line in double logarithmic scale is discussed. Leslie-type models producing solutions similar to some specific cases of this formula (including logistic-like curve) are studied. As an example, a model of tree stand self-thinning is derived and investigated; the model allows fitting empirical data with high accuracy.

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40

Skufina, Tatiana, Ekaterina Bazhutova, Vera Samarina, and Natalia Serova. "CORPORATE SOCIAL RESPONSIBILITY AS A RESERVE FOR THE GROWTH OF ENTREPRENEURIAL ACTIVITY IN THE RUSSIAN ARCTIC." Humanities & Social Sciences Reviews 7, no. 6 (2019): 1024–31. http://dx.doi.org/10.18510/hssr.2019.76151.

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Purpose of the study: To explore the consists of studying the opportunities for unlocking the potential of carrying out an entrepreneurial activity of big business within the Russian Arctic as a part of corporate social responsibility policy conducted by it. Methodology: The leading approach identified is the integrated approach which includes theoretical generalizations, analysis of practical activities of the corporations, and sociological methods of obtaining the information. Main Findings: The main concepts of big business management that contribute to boosting its entrepreneur

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41

Nuryaman, A., M. A. A. F. Pamungkas, and S. Saidi. "Forecasting of Bandar Lampung’s Population Using Growth Mathematical Models." Journal of Physics: Conference Series 1338 (October 2019): 012037. http://dx.doi.org/10.1088/1742-6596/1338/1/012037.

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42

Borges, KOR, BVR Almeida, GMR Almeida, and CB Junior. "LITERATURE REVIEW ON MATHEMATICAL MODELS OF PLASMA CELL GROWTH." Hematology, Transfusion and Cell Therapy 46 (October 2024): S521. http://dx.doi.org/10.1016/j.htct.2024.09.875.

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43

Chowell, Gerardo, Lisa Sattenspiel, Shweta Bansal, and Cécile Viboud. "Mathematical models to characterize early epidemic growth: A review." Physics of Life Reviews 18 (September 2016): 66–97. http://dx.doi.org/10.1016/j.plrev.2016.07.005.

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44

KING, J. R., and S. J. FRANKS. "Mathematical analysis of some multi-dimensional tissue-growth models." European Journal of Applied Mathematics 15, no. 3 (2004): 273–95. http://dx.doi.org/10.1017/s0956792504005480.

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Mathematical models for the growth of nutrient-rich tissue are presented and a number of properties of the resulting models outlined. The focus is on obtaining broadly applicable results for the simplest appropriate formulations by using matched-asymptotic, moving-boundary and thin-film approaches; the relevance of the results to a variety of specific biological applications will be addressed elsewhere, as will the inclusion of additional physical phenomena.

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45

Racsko, P., and M. Semenov. "Analysis of mathematical principles in crop growth simulation models." Ecological Modelling 47, no. 3-4 (1989): 291–302. http://dx.doi.org/10.1016/0304-3800(89)90007-0.

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46

Booker, B. M., A. Forrest, and P. F. Smith. "Novel mathematical models for bacterial growth, death & pharmacodynamics." Clinical Pharmacology & Therapeutics 73, no. 2 (2003): P24. http://dx.doi.org/10.1016/s0009-9236(03)90442-5.

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47

Ortega, J. K. E., and S. W. J. Welch. "Mathematical Models for Expansive Growth of Cells with Walls." Mathematical Modelling of Natural Phenomena 8, no. 4 (2013): 35–61. http://dx.doi.org/10.1051/mmnp/20138404.

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48

Mantzaris, Nikolaos V., Prodromos Daoutidis, Friedrich Srienc, and Arnold G. Fredrickson. "Growth processes in a cascade of bioreactors: Mathematical models." AIChE Journal 45, no. 1 (1999): 164–76. http://dx.doi.org/10.1002/aic.690450114.

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49

Kumar, Nand Kishor, and Suresh Kumar Sahani. "G-Calculus in Economic Growth Models: A Mathematical Framework." ALSYSTECH Journal of Education Technology 3, no. 2 (2025): 270–77. https://doi.org/10.58578/alsystech.v3i2.5727.

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Economic growth models are essential for understanding the long-term dynamics of economies, yet traditional models often rely on classical differential and integral calculus, which may inadequately represent discrete, nonlinear, or growth-oriented phenomena. This study aims to introduce G-Calculus (Geometric Calculus), an extension of non-Newtonian calculus, as an alternative analytical framework that is particularly effective for modeling multiplicative and exponential growth systems. We present the theoretical underpinnings of G-Calculus and apply it to established economic growth frameworks

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50

Mukushev, B. A., S. B. Mukushev, A. B. Myrzagalieva, B. A. Prmantayeva, and N. M. Omarov. "Ecological chains and their mathematical and computer models." BULLETIN of the L.N. Gumilyov Eurasian National University. BIOSCIENCE Series 143, no. 2 (2023): 54–65. http://dx.doi.org/10.32523/2616-7034-2023-143-2-54-65.

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The article deals with the problem of studying the structures and evolutions of ecological chains at the level of microorganisms using mathematical and computer models. Several mathematical models have been constructed based on the laws of biological kinetics. Computer experiments were developed using these models. Mathematical models describing the dependence of the concentration of bacterial biomass, substrates and protozoa on time have been created. With the help of the Mathcad package, graphical solutions of mathematical models were obtained and analyzed. Graphs of the states of ecological

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