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Journal articles on the topic 'Activity indicators'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Obzhirov, Anatoly. "Gasgeochemical indicators seismic activity." E3S Web of Conferences 20 (2017): 03003. http://dx.doi.org/10.1051/e3sconf/20172003003.

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2

Bolic, Dragan. "Indicators in intelligence activity." Vojno delo 68, no. 7 (2016): 114–28. http://dx.doi.org/10.5937/vojdelo1607114b.

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3

Luo, Fang, Yin Wei, Ziyue Wang, Minmin Luo, and Ji Hu. "Genetically Encoded Neural Activity Indicators." Brain Science Advances 4, no. 1 (2018): 1–15. http://dx.doi.org/10.26599/bsa.2018.9050007.

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Recent years have witnessed the fascinating development of imaging approaches to studying neural activities; this progress has been based on an influx of ideas and methods from molecular biology and optical engineering. Here we review the design and application of genetically encoded indicators for calcium ions, membrane potential and neurotransmitters. We also summarize common strategies for the design and optimization of genetically encoded neural activity indicators.

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4

de Assis Lahoz, Manoela, and João Alberto Camarotto. "Performance indicators of work activity." Work 41 (2012): 524–31. http://dx.doi.org/10.3233/wor-2012-0207-524.

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5

Ackerman, M. S., and B. Starr. "Social activity indicators for groupware." Computer 29, no. 6 (1996): 37–42. http://dx.doi.org/10.1109/2.507630.

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6

Looger, Loren L., and Oliver Griesbeck. "Genetically encoded neural activity indicators." Current Opinion in Neurobiology 22, no. 1 (2012): 18–23. http://dx.doi.org/10.1016/j.conb.2011.10.024.

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7

Li, YiYin, LiPing Zhou, and HaiTing Cui. "Pollen indicators of human activity." Science Bulletin 53, no. 9 (2008): 1281–93. http://dx.doi.org/10.1007/s11434-008-0181-0.

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8

Trachuk, A. V., and N. V. Linder. "INNOVATIVE ACTIVITY OF INDUSTRIAL ENTERPRISES: MEASUREMENT AND EFFECTIVENESS EVALUATION." Strategic decisions and risk management 10, no. 2 (2019): 108–21. http://dx.doi.org/10.17747/2618-947x-2019-2-108-121.

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The paper considers the indicators and multi-scale assessment of innovative activity of industrial companies. The research methodology consistently includes the analysis of the factors of innovative activity; collection and analysis of information about the indicators for assessing the innovative activity of industrial enterprises taking into account the defined factors of innovative activity; compiling of the short and aggregated lists of indicators for assessing the innovation activity taking into account the determined factors; defining an aggregate indicator of the innovative activity of an industrial enterprise. To define the aggregate indicator of the innovative activity we analysed the published reports of 57 companies, which have been the leaders in the industrial sectors for the last 15 years. Moreover, we analysed 40 scholarly publications focused on the assessment of the innovative activities and interviewed 16 experts, which are heads of large industrial companies. In addition, we analysed key performance indicators (KPI) of innovative activity recommended by the American Productivity & Quality Center (APQC). As a result of the research, we have proposed a methodology of the multi-scale assessment of the innovative activity of industrial companies. We have selected 5 key performance indicators to calculate the integral indicator. Furthermore, we have developed an algorithm to calculate the integral indicator of innovative activity. In addition to the integral indicator, we recommend to use 3 indicative values, which influence the integral indicator: a) comprehensive indicator of the development of scientific research, research institutes, academic organisations, technology platforms, per cent; b) number of proposals to generate new technologies, technical and technological solutions from affiliated companies over the year; c) number of new competences acquired by a company from innovative activities.The production of this integral indicator of the innovative activity will allow to the industrial enterprises a more informative assessment of their innovative activities and innovation behaviour transformations.

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9

Puhachova, M. V. "Using International Ranks and Business Activity Indicators for Economic Development Forecasting." Statistics of Ukraine 83, no. 4 (2018): 34–43. http://dx.doi.org/10.31767/su.4(83)2018.04.04.

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The majority of countries use several well-known integral indicators for economic forecasting purposes, on which basis these countries’ ranks in the global economic community are computed. Apart from allowing investors to make investment decisions, such indicators and ranks help in forecasting economic development in forthcoming periods. The best known of them is Ease of Doing Business Index and Global Competitiveness Index. The less known ones are indicators of Business Tendency Surveys (BTS), computed on the basis of data obtained from questionings of enterprise managers in various economic sectors and from studies of consumer sentiments. Yet, specialists tend to use the data from these conjuncture surveys to analyze the current economic situation in a country (total or by industry) and build short-term forecasts. Apart from the survey indicators depicting quite clearly a situation in the economy, the most popular ones in Europe are Confidence Indicators for enterprises by economic activity, and Economic Sentiment Indicator incorporating the indicators from BTS of enterprises and consumer sentiments. These indicators are computed by the European Commission for EU member countries on monthly basis. The article shows changes in Doing Business ranks for selected EU member countries and Ukraine. BTS indicators for industrial enterprises (estimate of production capacities; estimate of change in the production orders; estimate of the competitive position of enterprises at the internal market) are analyzed for some of these countries. A comparison of the dynamics of production capacities utilization, business confidence indicators and Doing Business rank is made for Ukraine and Bulgaria. The prognosticating capacities of BTS indicators compared with Doing Business indicator are analyzed.

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10

Kozachenko, Ganna, Taina Zavora, and Liudmyla Shapoval. "Lombard activities and social security of the country: interrelation and interdependence." Independent Journal of Management & Production 11, no. 8 (2020): 587. http://dx.doi.org/10.14807/ijmp.v11i8.1219.

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The place and value of pawnshops in the financial market are considered in the article. The main indicators of activity of pawnshops are analyzed. The advantages and disadvantages of using the pawnshop services by the population are substantiated. The growth rate of pawnshop activity in Ukraine is determined on the basis of the method of estimating the integral indicator. The nature and specifics of the influence of social security indicators on the activity of pawnshops in Ukraine by means of correlation analysis are revealed. In the constructed econometric model, the factors that influence are the social security indicators of the country and the dependent values are indicators of pawnshop activity. The obtained results revealed a significant correlation between the social security indicators of the country and the indicators of pawnshop activity. The detail of the analysis showed the greatest correlation between the pawnshops' performance and the social security indicator – the ratio of the average monthly nominal wage to the subsistence level for one able-bodied person.

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11

Nabijonovna, Bayboboeva Firuza. "Business activity and its economic indicators." ACADEMICIA: An International Multidisciplinary Research Journal 10, no. 3 (2020): 151. http://dx.doi.org/10.5958/2249-7137.2020.00064.6.

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12

Ramesh, K. B., and N. Vasantharaju. "Temporal offsets among solar activity indicators." Astrophysics and Space Science 350, no. 2 (2014): 479–87. http://dx.doi.org/10.1007/s10509-014-1804-3.

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13

Dukas, Stephen, and Jinwoo Park. "Trading activity indicators and market timing." Applied Financial Economics 5, no. 5 (1995): 337–44. http://dx.doi.org/10.1080/758522761.

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14

Kõlli, Raimo, Tiina Köster, Kaire Rannik, and Tõnu Tõnutare. "Complex indicators reflecting soil functioning activity§." Journal of Plant Nutrition and Soil Science 172, no. 5 (2009): 630–32. http://dx.doi.org/10.1002/jpln.200900031.

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15

Lin, Michael Z., and Mark J. Schnitzer. "Genetically encoded indicators of neuronal activity." Nature Neuroscience 19, no. 9 (2016): 1142–53. http://dx.doi.org/10.1038/nn.4359.

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16

Kováč, Daniel, Alexander Ač, Ladislav Šigut, Karel Klem, and Otmar Urban. "Optical indicators of plant physiological activity." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, no. 3 (2012): 101–10. http://dx.doi.org/10.11118/actaun201260030101.

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Retrieving information on the plant physiological status from spectral reflectance is a challenging task in many ways. The easiest way to get the information is through normalized vegetation indices, that are based on a normalization of reflectance in specific wavebands. Beside the most common spectral indices such as Photochemical Reflectance Index PRI or Normalized Difference Vegetation Index NDVI, several new indices has been proposed during the past decade as potential physiological indicators. In this paper, the performance of several of them for determining the physiological status of the foliage is evaluated on an experimental Norway spruce needles (Picea abies (L.) Karst) plot. Four needle classess of 27 years old spruce have been sampled throughout cloudy and sunny day. Needle classes were represented by the needles of the branchlets of the 4th, 7th, 9th and 12th whorls. Study was conducted on one-year old needles and sampling ran over several times a day to separate influence of dynamic processess on parameters. Results show that the ratio of reflectance in the green and red region (presented as ratio of reflectance at 560 nm and 694 nm) outperforms the others examinated vegetation indices, and suggest that it would be best suited for the characterization of the leaf status. Being always the highest in the uppermost part of the crown and the lowest in shaded part of the crown, parameter is strictly stratificated throughout the crown. Furthermore, parameter values correspond with intensity of physiological processess ongoing in needles during midday. The values of the other indicators seem to be affected by leaf pigment content and morphology too much. Neither PRI nor NDVI were able to distinguish differences in needle properties sufficiently.

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17

García-Villar, C., and J. M. García-Santos. "Bibliometric indicators to evaluate scientific activity." Radiología (English Edition) 63, no. 3 (2021): 228–35. http://dx.doi.org/10.1016/j.rxeng.2021.01.002.

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18

Yudina, Tatyana Nikolaevna. "Street Protest Activity in Modern Russian Society: Patterns and Dynamics of Indicators." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (2020): 1694–701. http://dx.doi.org/10.5373/jardcs/v12sp4/20201651.

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19

Shen, C., and H. Qiang. "Analysing the influence of human activity on runoff in the Weihe River basin." Proceedings of the International Association of Hydrological Sciences 368 (May 7, 2015): 269–74. http://dx.doi.org/10.5194/piahs-368-269-2015.

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Abstract. Changing runoff patterns can have profound effects on the economic development of river basins. To assess the impact of human activity on runoff in the Weihe River basin, principal component analysis (PCA) was applied to a set of 17 widely used indicators of economic development to construct general combined indicators reflecting different types of human activity. Grey relational analysis suggested that the combined indicator associated with agricultural activity was most likely to have influenced the changes in runoff observed within the river basin during 1994–2011. Curve fitting was then performed to characterize the relationship between the general agricultural indicator and the measured runoff, revealing a reasonably high correlation (R2 = 0.393) and an exponential relationship. Finally, a sensitivity analysis was performed to assess the influence of the 17 individual indicators on the measured runoff, confirming that indicators associated with agricultural activity had profound effects whereas those associated with urbanization had relatively little impact.

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20

Shahverdiyeva, Roza. "Development of a system of indicators characterizing innovation and innovative activity in technoparks." Drukerovskij Vestnik, no. 5 (October 2020): 61–66. http://dx.doi.org/10.17213/2312-6469-2020-5-61-66.

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21

Martináková, Radka, and Svatopluk Kapounek. "Economic sentiment indicator and its information capability in the Czech Republic." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 61, no. 7 (2013): 2491–98. http://dx.doi.org/10.11118/actaun201361072491.

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The paper focuses on the indicators of economic agents’ perceptions in the Czech Republic. We assume that these information are provided by economic sentiment indicator surveys based on the Joint Harmonised EU Programme. The aim of this paper is to offer the alternate methodology of qualitative data transformation (balance statistic data) in relation with the macroeconomic quantitative indicators. In the empirical analysis we distinguished between the indicators of confidence in industry, construction, retail and consumer confidence indicator. We found link between the aggregate economic sentiment indicator and economic activity. Especially, aggregate economic sentiment indicator copies the development of the GDP. However, partial indicators does not follow changes in the specific sectors of the economy. We also found that economic agents underestimate the intensity of the economic recession after the year 2007.Finally, we cannot recommend the economic sentiment indicator as the leading indicator of the future economic activity in the Czech Republic. Our methodological contribution is in quantifying of the consumer survey results by standardization.

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22

Musaev, Magomed Kantashovich. "MAIN INDICATORS BY TYPE OF ACTIVITY "MANUFACTURING"." Economy. Business. Computer science, no. 2 (May 12, 2016): 43–58. http://dx.doi.org/10.19075/2500-2074-2016-2-43-58.

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23

Sitash, Tatyana. "EXCHANGE INDICES AS ACTIVITY INDICATORS STEEL MARKET." JOURNAL OF EUROPEAN ECONOMY Vol 17, Vol 17, No 1 (2018) (2018): 100–115. http://dx.doi.org/10.35774/jee2018.01.100.

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The stock indices are investigated as indicators of stock market activity. It is proved that the stock market is one of the most attractive instruments for investing. It is accepted that an open stock market in a country characterized by a stable, strong economy, encourages the attraction of foreign investors. It is noted that indicators of the Ukrainian stock market such as the capitalization and the PFTS stock index (First Stock Trading System), as a result of the inadequate exchange rate prices for the real state of the issuing companies and the economy of the state, can’t be as representative, especially when compared with foreign markets. It has been outlined that the development of the domestic stock market is restrained by the imperfection of legislative and regulatory regulation of the market participants, the lack of optimality of the market infrastructure, the lack of a fully functioning, fully functioning national depository system. The introduction of a new stock index describing the state of business activity of a separate sector of the market is proposed, which will serve as a benchmark for the formation and optimization of investment strategy of investors, will promote transparency of the Ukrainian securities market.

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24

Eremenko, Tatiana. "Indicators of regional scientific community publication activity." Scientific and Technical Libraries, no. 1 (January 1, 2018): 43–50. http://dx.doi.org/10.33186/1027-3689-2018-1-43-50.

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The relevancy of the problem of specifying and probating the system of measurable indicators for publication activities in regional scientific societies is proved. Contemporary scientometric works contemplating publication activities analysis for Russian regions are re viewed. In particular, the articles by V. Markusova, A. Libkind, A. Terekhov, D. Rubvalter, I. Libkind, T. Krylova, mentioned. These authors review the regions’ contribution into competition research projects and analyze research activities of Russian universities based on the Web of Knowledge statistical data. Bibliometric data on fundamental research in Novosibirsk region are revealed. Bibliometric analysis is suggested as the basic method for evaluating and interpreting the flow of scientific publication by the authors affiliated with territorial institutions. Expected findings of such study are discussed: data on the regions’ publication activities being introduced to science agenda, possibility to establish creative correlation between parameters and indicators of the publication flow generated by the regional academic community and dependent on the regional academic potential specific features. The publication is prepared under the Research Project № 17-13-62001 of the Russian Foundation for Basic Research.

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25

Aristarkhova, M. K., O. K. Zueva, and M. S. Zueva. "Indicators of tax reliability of innovative activity." IOP Conference Series: Materials Science and Engineering 659 (October 31, 2019): 012030. http://dx.doi.org/10.1088/1757-899x/659/1/012030.

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26

Armienta, M. A., S. De la Cruz-Reyna, A. Gómez, et al. "Hydrogeochemical indicators of the Popocatépetl volcano activity." Journal of Volcanology and Geothermal Research 170, no. 1-2 (2008): 35–50. http://dx.doi.org/10.1016/j.jvolgeores.2007.09.006.

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27

Balybina, A. S., and A. A. Karakhanyan. "Climatic variables as indicators of solar activity." Geomagnetism and Aeronomy 52, no. 7 (2012): 931–36. http://dx.doi.org/10.1134/s001679321207002x.

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28

Justo, Rachida, Julio O. De Castro, and Alberto Maydeu Olivares. "Indicators of entrepreneurship activity: some methodological contributions." International Journal of Entrepreneurship and Small Business 6, no. 4 (2008): 604. http://dx.doi.org/10.1504/ijesb.2008.019504.

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29

Fine, Daniel H., and Irwin D. Mandel. "Indicators of periodontal disease activity: an evaluation." Journal of Clinical Periodontology 13, no. 5 (1986): 533–46. http://dx.doi.org/10.1111/j.1600-051x.1986.tb01502.x.

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30

Chandler, Colin Orion, Anthony M. Curtis, Michael Mommert, Scott S. Sheppard, and Chadwick A. Trujillo. "SAFARI: Searching Asteroids for Activity Revealing Indicators." Publications of the Astronomical Society of the Pacific 130, no. 993 (2018): 114502. http://dx.doi.org/10.1088/1538-3873/aad03d.

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31

Carrion, Carlos, Annesha Enam, Varun Pattabhiraman, Maya Abou-Zeid, and Moshe Ben-Akiva. "Activity Pattern Models with Well-Being Indicators." Transportation Research Record: Journal of the Transportation Research Board 2493, no. 1 (2015): 58–69. http://dx.doi.org/10.3141/2493-07.

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32

Frasca, A., J. Molenda-Żakowicz, P. De Cat, et al. "Activity indicators and stellar parameters of theKeplertargets." Astronomy & Astrophysics 594 (October 2016): A39. http://dx.doi.org/10.1051/0004-6361/201628337.

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33

Fritz, Richard G., and W. Warren McHone. "Forecasting local business activity from aggregate indicators." Annals of Regional Science 22, no. 1 (1988): 63–74. http://dx.doi.org/10.1007/bf01286402.

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34

Yuthavong, Yongyuth. "Bibliometric indicators of scientific activity in Thailand." Scientometrics 9, no. 3-4 (1986): 139–43. http://dx.doi.org/10.1007/bf02017237.

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35

TKACHENKO, Serhii, Olena POTYSHNIAK, and Yevheniia POLIAKOVA. "Definition of generalized indicators of activity units." Economics. Finances. Law, no. 6 (June 21, 2021): 14–17. http://dx.doi.org/10.37634/efp.2021.6.3.

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In managing the quality of products, it is necessary that the economic mechanism of production (profit, profitability, prices, and so on) is a lever of influence on the level of quality. Hence, it is obvious that it is necessary to study the issues of the relationship between economic indicators and indicators of the level of product quality. Moreover, for a scientifically grounded solution of such problems, economic and mathematical models are also needed. Considerable attention was paid to the study of this issue before. The studies consider the operating systems, taking into account the influence of quality indicators, without focusing on the fact that the volume and quality characteristics of products, being the final and resulting indicators of production activities, determine the productivity of production, since they are characterized by net profit, rational use of resources, property, funds. An attempt is made to establish the relationship between economic indicators and quality indicators in such a way as to evaluate the production activity not according to the principle of better or worse, but according to quantitative criteria. The paper deals with the issues of product quality analysis, which are solved by mathematical and statistical methods. Attention is paid to the development of algorithms for processing statistical information on quality and the relationship between product quality indicators and production factors. The conducted research is intended for specialists engaged in the development, implementation and operation of complex quality management systems in industries with continuous production of finished products. As a result of solving this key issue, the general goal was achieved, to show that it is possible to plan indicators, criteria for assessing the quality and volumes of finished products, its structure, which ensures the best use of production assets, that is, the maximum return on each invested hryvnia, as well as the achievement of high-quality indicators in an optimal way.

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36

Pauwels, Kevin, Luc De Meester, Ellen Decaestecker, and Robby Stoks. "Phenoloxidase but not lytic activity reflects resistance against Pasteuria ramosa in Daphnia magna." Biology Letters 7, no. 1 (2010): 156–59. http://dx.doi.org/10.1098/rsbl.2010.0634.

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The field of ecological immunology strongly relies on indicators of immunocompetence. Two major indicators in invertebrates, the activity of phenoloxidase (PO) and lytic activity have recently been questioned in studies showing that, across a natural range of baseline levels, these indicators did not predict resistance against a manipulated challenge with natural parasites. We confirmed this finding by showing that baseline levels of PO and lytic activity in the host Daphnia magna were not related to spore load of the parasite Pasteuria ramosa . Yet, PO levels in infected hosts did predict spore load, indicating PO activity can be useful as an indicator of immunocompetence in this model parasite–host system.

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37

Hon, Suat Hoon, A. C. Er, and Nurul Fadilah Mohd. Nawi. "FACTORS ANALYSIS OF TOURISM SUSTAINABILITY INDICATORS." Journal of Tourism, Hospitality and Environment Management 5, no. 21 (2020): 143–62. http://dx.doi.org/10.35631/jthem.521009.

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Sustainable tourism is a type of tourism activity that continues to conserve, provide various facilities in areas that have tourist attractions, whether related to the environment or culture, as well as modernize the social structure in the area to become an economic activity that can contribute to national income, improving the living standards of the local community. This study aims to identify the factors of sustainability indicators. Interviews based on a set of questionnaires were conducted with 125 respondents in Ranau, Sabah. Factor analysis yielded five factors of economic sustainability indicators (indicators of tourist spending on accommodation, indicators of job creation and income generation, indicators of tourist attraction, indicators of tourist origin, as well as indicators of related industries and support), three factors of indicators of social sustainability (indicators of infrastructure and infrastructure, traditional and cultural conservation indicators, as well as management and conservation indicators), and two environmental sustainability indicator factors (environmental education indicators and training courses and research and enforcement indicators).

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38

Ledeneva, Marina Viktorovna, and Natalia Amirovna Mishura. "Factor analysis of innovation activity of companies in the Russian Federation." Теоретическая и прикладная экономика, no. 4 (April 2020): 95–105. http://dx.doi.org/10.25136/2409-8647.2020.4.34785.

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This research is aimed at determination and interpretation of the factors that influence the indicator values of innovation activity of enterprises in the Russian Federation. The author sets the following goals: carry out factor analysis of innovation activity of companies in the Russian Federation using the method of principal components and maximum likelihood; determine and interpret the factors; compare the acquired results; develop recommendations on improvement the composition of statistical indicators used for efficiency assessment of innovation activity of companies on meso- and macro levels. The empirical basis contains the data provided by Rosstat on 10 indicators for the period from 2009 to 2016 (657 observations). The scientific novelty consists in identification of latent generalizing characteristics and correlations between the indicators used for assessing the innovation activity of companies in the Russian Federation. Both methods, of principal components and principal factors, allowed similarly distinguishing the two factors: via the method of principal components: development of science in the region and specialization of the region in high-tech industries; via the method of principal factors: research organizations in the region, their number and indicators; specialization of the region in high-tech industries. The second factor reflects commercialization of research and development. A relatively small number of indicators is used for assessing commercialization of research and development. The author notes the lack of statistical data for assessing the efficiency of innovation activity of companies. The statistical indicators of innovation activity of enterprises should include the economic effect indicators. This would allow using the performance indicators of research and development not only on micro-, but also meso - and macro-levels in elaboration and assessment of measures stimulating innovation activity of businesses at the country level.

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39

Dymchenko, Olena, Olha Rudachenko, Valeriya Yesina, and Iurii Tararuiev. "Economic potential of Ukraine: assessment and forecasting." SHS Web of Conferences 111 (2021): 01014. http://dx.doi.org/10.1051/shsconf/202111101014.

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Based on the results of the open statistical data analysis, the paper justifies indicators for an integral assessment of the economic potential of Ukraine by types of economic activity of business entities. Since the potential is implemented in the future, the paper uses trend analysis to determine the prospective values of previously selected indicators. At the same time, some relative indicators were decomposed into absolute elements (as each of the absolute indicators has its own dynamics of changes). Stepwise, logarithmic, exponential, and other dependencies are used to predict indicators. In addition, the prospective values of indicators were normalized in order to get the correct calculation of the integral indicator in the paper. The integral indicator of the economic potential of Ukraine for each type of economic activity of business entities for the year 2022 is calculated as a result of generalizing the normalized values of prospective indicators. The calculation results can be used to distribute budget funds that are planned to be used for ensuring the long-term development of the Ukrainian economy sectors.

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40

Lin, Chiuhsiang Joe, Tariku Tamiru Belis, Dino Caesaron, Bernard C. Jiang, and Tsai Chi Kuo. "Development of Sustainability Indicators for Employee-Activity Based Production Process Using Fuzzy Delphi Method." Sustainability 12, no. 16 (2020): 6378. http://dx.doi.org/10.3390/su12166378.

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Production process sustainability refers to a manufacturing system in which manufacturing industries produce products in a sustainable way. In recent years, sustainability has become a major concern and challenge for manufacturing systems because of growing consciousness of the effects of their activities on the environment, society, and economy. Different organizational reports and the academic literature have proposed indicators of sustainable manufacturing that help to measure product and process sustainability. However, little of the previous research is related to employee-activity based indicators for production process sustainability. To bridge the gap, this study identified a set of indicators of production process sustainability based on direct and indirect impacts of manufacturing activities on employees, who are key resources in the entire production process, for efficiently applying a sustainability perspective. In addition, the paper provides an evaluation model for selecting relatively important indicators based on expert opinions. A fuzzy Delphi method was applied for the screening process of the decision makers (experts). A Delphi questionnaire prepared with a nine-point linguistic scale corresponding to respective linguistic variables was utilized to assess expert opinions on the importance of each indicator. These expert opinions were aggregated for each indicator by using an adopted algorithm that considers the degree of importance allocated to the decision makers, and the similarity and distance among decision maker opinions. Lastly, the key employee-activity based indicators were chosen based on the threshold value set.

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41

Barnes, Joel D., Rachel C. Colley, and Mark S. Tremblay. "Results from the Active Healthy Kids Canada 2011 Report Card on Physical Activity for Children and Youth." Applied Physiology, Nutrition, and Metabolism 37, no. 4 (2012): 793–97. http://dx.doi.org/10.1139/h2012-033.

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The Active Healthy Kids Canada 2011 Report Card on Physical Activity for Children and Youth assesses how Canada is doing as a country at promoting and facilitating physical activity opportunities for children and youth. The aim of this brief communication is to provide a summary of the results. Twenty-three physical activity indicators were graded. The physical activity levels indicator received an “F” for the fifth consecutive year, and little improvement was seen across most indicators.

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42

Vasiljeva, Marina, Vadim Ponkratov, Tatyana Volkova, et al. "The Development of Scientific Activity in Russian Universities." Journal of Open Innovation: Technology, Market, and Complexity 6, no. 4 (2020): 110. http://dx.doi.org/10.3390/joitmc6040110.

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The aim of this article was to develop scientific activity in Russian universities. Using the survey method, a sample of quantitative indicators of research output for the years 2011–2019 was formed. The respondents were comprised of 934 lecturers from 13 universities in Russia with different work experience, academic degrees, and indicators of scientific activity. The main components method was used to study the structure of scientific activity productivity indicators. Using the method of additive convolution, a five-factor integral model of the structure of scientific activity of a teacher was formed to evaluate the individual and collective productivity of scientific activity. The factor values and the integral indicator of scientific activity output were calculated, showing that the individual growth rates of the young lecturers’ output exceeded the growth rates of the older lecturers. Destructive factors relating to the scientific activity output of the lecturers and researchers in Russian universities (divided into two groups of young scientists and senior scientists) were determined and systematized based on the level of dominant influence. The features of the influence of the factor of emotional burnout on the scientific productivity of university teachers were revealed.

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UDOVYCHENKO, Olga. "CRITERIA AND INDICATORS OF LEVELS OF FUTURE COMPUTER SCIENCE TEACHERS’ READINESS FOR PROFESSIONAL ACTIVITY." Cherkasy University Bulletin: Pedagogical Sciences, no. 2 (2020): 142–47. http://dx.doi.org/10.31651/2524-2660-2020-2-142-147.

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Introduction. Criteria and their indicators of levels of future computer science teachers’ readiness for professional activities are identified to determine the effectiveness of the model of future computer science teachers’ training.The purpose of the article is to substantiate the choice of criteria and indicators to characterize the levels of future computer science teachers’ readiness for profe-?sional activities. Methods. To achieve this goal, such methods as analysis and systematization of the results of scientific and pedagogical research on the future computer science teachers’ preparation of for professional activities; generalization of different approaches to the choice and substantiation of criteria and indicators of future computer science teachers’ readiness for professional activity were used. Results. To establish the level of computer science teachers’ readiness for professional activity, the following criteria have been developed. Theoretical criterion determines the formation of a system of knowledge (professional, psychological, pedagogical, methodological) about the essence of computer science teacher, where indicators are the depth and scope of students' knowledge. Technological criterion determines the presence of future computer science teachers ability to perform professional tasks necessary for productive activities in the specialty, an indicator is the level of performance of procedural actions by students. Personal criterion assumes the presence of the formation of personal qualities of the student for future pedagogical activities, where the indicators are the motivation of future professional activity and the ability to self-analysis. The corresponding indicators of computer science teachers’ readiness for professional activity characterized each of the criteria. Indicators of the theoretical criterion are "volume of knowledge" (set of facts, concepts, rules, judgments, conclusions, phenomena and processes mastered by future computer science teachers) and "depth of knowledge» (the correct ratio of the structure and elements of knowledge, understanding of the system of educational material, its most important ideas and patterns, characterizes the ability of students to use EER in cognitive and practical activities). The indicator of the technological criterion is "procedural actions" (the presence of future computer science teachers’ ability to perform professional tasks necessary for productive activities in the specialty. The indicator of the personal criterion is "motivation" (motivation to use EER) and introspection" (ability to reflect on professional activities). The originality and novelty of the work are in the development of the author's diagnostic apparatus to determine the levels of future computer science teachers’ readiness for professional activities. Conclusions. Criteria and indicators of computer science teachers’ professional readiness allow to cha-racterize the levels of readiness for professional activity. Depending on the degree of computer science teachers’ readiness, there are four levels: factual, operational, analytical-synthetic, and creative.

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Puhachova, M. V. "Peculiarities of Predicting Business Cycles in the Ukrainian Economy." Statistics of Ukraine 87, no. 4 (2020): 28–35. http://dx.doi.org/10.31767/su.4(87)2019.04.04.

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It is argued in the article that any common person is able to get an idea about the economy’s conditions and its forthcoming change, if he/she learns information Business Tendency Surveys (BTS), i. e. with combination indicators computed on the basis of indicators from these surveys. A review of the methods for constructing several types of integral composite indicators, based on indicators of BTS of enterprises by selected economic activities, is provided. Indicators of business climate, computed by the methodology of ifo-Institute and European Commission, and indicators of confidence by economic activity are analyzed. Being ahead of the curve, these indicators give good signals on change in the phases of business activity cycles in European economies and allow one to have rather precise short-term predictions of change in GDP and output by economic activity.  The analysis covers dynamic series of these indicators for the Ukrainian economy, with making the conclusion that now only the indicators of confidences for four economic activities can be used for predicting the business cycle for 2 to 3 quarters. The Business Climate Indicator, computed by the European methodology, has good correlation with GDP, but it is only one quarter ahead of it. The Business Climate Indicator, computed by the methodology of ifo-Institute, did show rather good correlation with GDP, but could not demonstrate its good qualities as for the German economy. Unfortunately, this indicator could be computed only for the period before 2013, because subsequently its components were withdrawn from survey questionnaires.  One of the main recommendations given in the article is as follows: an organization performing BTS of enterprises (namely, the State Statistics Service of Ukraine) needs to more actively propagate the information about various composite indicators that can obviously be demanded by a broad range of statistical information users. These indicators should be, inter alia, displayed on the home page of the official web-site of the State Statistics Service of Ukraine together with hot news (probably, in a graph form together with macroeconomic indicators).

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DANCHENKO, O. О. "KEY PERFORMANCE INDICATORS OF A CREWING COMPANY ACTIVITY." Economic innovations 21, no. 1(70) (2019): 28–36. http://dx.doi.org/10.31520/ei.2019.21.1(70).28-36.

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Topicality. Enterprises must inculcate modern economic tools in the management practice to provide efficiency of their work. The universal set of parameters that can be used equally well for all kinds of activity without the exception is absent. The complexity of forming financial results of a crewing company activity and necessity of taking into account the specific features of its functioning require to research the key parameters of effectiveness concerning specifically crewing activity. Aim and tasks. Identification of performance indicators (qualitative and quantitative) of the company, which will cover all aspects of the crewing company activity without any exceptions, taking into consideration the specifics of their activities and the peculiarities of formation of incomes and expenses for various types of crewing. Research results. Most companies use traditional techniques to assess the competitive position on the market. Besides today, more and more attention is paid to valuing the company. In our view, to assess the work of a crewing company, it is necessary to focus on the so-called key performance indicators (KPIs). They are an element of a balanced system of parameters, which should have a set of indicators that can clearly identify the company's goals and the extent to which they are achieved. In particular, it is necessary to use both financial and non-financial indicators, to determine quantitative and qualitative KPIs, as well as perspective and actual indicators. A list of KPIs must be developed for each employee of a crewing company. Their number should not exceed 5-7 indicators. They all should be simple, understandable, clear and achievable. All KPIs should be known to all employees in order to ensure proper transparency, stimulate competition and motivate employees to develop. Conclusion. Today, more emphasis is placed on traditional quantitative financial indicators that reflect the results achieved. In turn, promising indicators as KPIs provide a benchmark for company employees to the place of application of effort and reflect key improvements in the work of the crewing company. Therefore, it is necessary to make efforts and develop promising KPIs in order to determine what factors and how they affect the actual KPIs. This will help identify the specific services and processes that are key factors to the success of the company.

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Nikitenko, Sergey M., and Maria A. Mesyats. "INVENTIVE ACTIVITY AND COST INDICATORS OF REGIONAL PRODUCTION." Economics and innovation management 10, no. 3 (2019): 49–61. http://dx.doi.org/10.26730/2587-5574-2019-3-49-61.

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Savenkov, Andrei. "Indicators of efficiency of the Russian business activity." Public Administration 20, no. 2 (2018): 109–13. http://dx.doi.org/10.22394/2070-8378-2018-20-2-109-113.

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Syrchyn, Oleksandr. "Methodology for planning of bank’s credit activity indicators." Socio-Economic Research Bulletin, no. 2-3(63-64) (July 17, 2017): 127–34. http://dx.doi.org/10.33987/vsed.2-3(63-64).2017.127-134.

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Rousseau, Ronald, and Liying Yang. "Reflections on the activity index and related indicators." Journal of Informetrics 6, no. 3 (2012): 413–21. http://dx.doi.org/10.1016/j.joi.2012.01.004.

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Wedemeyer, Sven, and Hans-Günter Ludwig. "Synthetic activity indicators for M-type dwarf stars." Proceedings of the International Astronomical Union 11, S320 (2015): 303–8. http://dx.doi.org/10.1017/s1743921316000077.

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AbstractHere, we present a set of time-dependent 3D RMHD simulations of a M-dwarf star representative of AD Leo, which extend from the upper convection zone into the chromosphere. The 3D model atmospheres are characterized by a very dynamic and intermittent structure on small spatial and temporal scales and a wealth of physical processes, which by nature cannot be described by means of 1D static model atmospheres. Artificial observations of these models imply that a combination of complementary diagnostics such as Ca II lines and the continuum intensity from UV to millimeter wavelengths, probe various properties of the dynamics, thermal and magnetic structure of the photosphere and the chromosphere and thus provide measures of stellar activity, which can be compared to observations. The complicated magnetic field structure and its imprint in synthetic diagnostics may have important implications for the understanding and characterization of stellar activity and with it possibly for the evaluation of planetary habitability around active M-dwarf stars.

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