scholarly journals TAX SUPPORT EVALUATION FOR R&D ACTIVITIES OF COMPANIES

2021 ◽  
Vol 27 (5) ◽  
pp. 1057-1071
Author(s):  
Martina Cernikova ◽  
Sarka Hyblerova

The article evaluates the impact of tax support for R&D on the volume of R&D outputs generated by companies. The number of patent applications was chosen as the R&D metric for business output. Both linear dependence using linear regression and non-linear dependence using decision trees were used within the research. The significance of indirect support in the context of other sources of funding R&D activities of companies was primarily assessed. The dependence of the number of patent applications on individual sources of financing of the Business Enterprise Expenditure on R&D was examined. Even after scaling variables, the research in the period under review confirmed the strongest dependence between the number of patent applications and the financial resources provided by the Business enterprise sector for all countries surveyed. Subsequently, the model reduced by the impact of Business enterprise sector resources was created. Of the three remaining variables considered, the analysis showed the strongest dependence of the number of patent applications on the amount of indirect support. The research points to the fact that impact of tax support on the volume of relevant R&D outputs is relatively significant.

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 299
Author(s):  
Jaime Pinilla ◽  
Miguel Negrín

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.


2021 ◽  
Vol 46 (1) ◽  
Author(s):  
C. E. Chigbundu ◽  
K. O. Adebowale

Dyes are complex and sensitive organic chemicals which exposes microbial populations, aquatic lives and other living organisms to its toxic effects if their presence in water bodies or industrial effluents are not properly handled. This work therefore, comparatively studied the adsorption efficiencies of natural raw kaolinite (NRK) clay adsorbent and dimethyl sulphoxide (DMSO) faciley intercalated kaolinite clay (DIK) adsorbent for batch adsorption of Basis Red 2 (BR2) dye. The impact of varying the contact time, temperature and other operating variables on adsorption was also considered. The two adsorbents were characterized using SEM images, FTIR and XRD patterns. Linear and non-linear regression analysis of different isotherm and kinetic models were used to describe the appropriate fits to the experimental data. Error analysis equations were also used to measure the goodness-of-fit. Langmuir isotherm model best described the adsorption as being monolayer on homogenous surfaces while Kinetic studies showed that Elovich model provides the best fit to experimental data. The adsorption capacities of NRK and DIK adsorbents for the uptake of BR2 were 16.30 mg/g and 32.81 mg/g, respectively (linear regression) and 19.30 mg/g and 30.81 mg/g, respectively (non-linear regression). The thermodynamic parameter, ∆G showed that BR2 dye adsorption onto the adsorbents were spontaneous. DIK adsorbent was twice efficient compared with NRK for the uptake of BR2 dye.


Author(s):  
Yuanbing Zhu ◽  
Xueying Chen ◽  
Gang Wang ◽  
Zuchang Zhong ◽  
Meier Zhuang

From the practice of developed countries, countries with higher patent applications and PCT patent applications (such as the United States, China, Japan, the United Kingdom, Germany, etc.) have relatively higher outward foreign direct investment, and the actual data of provinces in China also show that with the improvement of the patent level in various provinces and cities, the intensity of outward foreign direct investment in each province and city has also increased. At present, there are relatively few research data and the research method is relatively single. Therefore, collecting panel data on China’s 31 provinces from 2003 to 2016, this paper conducts an empirical analysis on the influence of patent level on outward foreign direct investment via analytical method of equal part linear regression and Grey Computing. By comparing analysis results with the model and the results with conventional linear regression model, the difference of different regression models is observed. Furthermore, the impact of China’s patent level on China’s inter-provincial outward foreign direct investment is further analyzed.


2012 ◽  
Vol 57 (1) ◽  
pp. 3-21
Author(s):  
Nikodem Szlązak ◽  
Czesław Kubaczka

An increase in concentration of coal output in Polish hard coal mines contributes to a significant increase in absolute methane-bearing capacity in mining areas. Measurements of methane concentration were taken in selected longwall faces in order to estimate the influence of coal output on methane hazard. The measurements were taken from 2006 to 2008 in 8 longwalls in mines with high methane hazard. The parameters for longwalls where measurements were taken are presented in table 1. Average daily output ranged from 1380 to 2320 Mg: however the maximum daily output amounted to 5335 Mg. Absolute methane-bearing capacity ranged from 4.44 to 56.41 m3/min. Longwalls were ventilated with a U and Y system and their ventilation schemes are presented in figure 1. The period of measurements ranged from 29 to 384 days. The results obtained were used to determine the influence of changes in output on methane hazard. For each longwall under research statistical estimation of parameters, such as: ventilation air methane (VAM) emission, amount of methane captured by a drainage system, absolute methane-bearing capacity and an advance of longwall face was conducted. In order to determine the influence of a longwall face advance on methane-bearing capacity the probabilistic model of the distribution of those parameters on the basis of the measurement results was used. In order to determine the dependence between ventilation air methane emission, methane drainage, absolute methane-bearing capacity and longwall advance, the distribution of analysed variables was checked by means of Kolmogorow-Smirnov normality test. The results of this test are presented in table 2. Table 3 presents values for correlation co-efficient r(x,y). When analyzing the results presented in table 3 it must be observed that in case of most longwalls there is a high correlation between ventilation air methane emission, absolute methane-bearing capacity and longwall advance. However, in longwalls N-10 i W-5 the correlation between methane drainage capture and longwall advance is equally strong. In all other longwalls the correlation is average. In all cases the correlations were positive, which means that together with an increase in advance, there is also an increase in ventilation air methane emission, methane drainage capture and absolute methane-bearing capacity On the basis of determination co-efficient it can be concluded that in cases under consideration at least half (about 50%) of results, ventilation air methane emission, methane drainage capture and absolute methane-bearing capacity can be explained linearly by an influence of longwall advance, while this statement can be assumed with the probability close to 100%. It should also be added that the lack of very high or full correlations means that examined parameters do not fully show linear dependence; however there might be other functional correlations. Because of a complex character of phenomena happening during mining it is not possible to determine full correlations. However, the interpretation of results allows us to claim that an influence of wall advance on methane emission amounts to 30 to 70% depending on a given case. Therefore, other factors, for example geological ones, which were not taken into consideration, will contribute to the level of methane hazard. Table 4 presents determined co-efficients of linear regression. On the basis of the data in table 4, an equation describing the dependence of absolute methane-bearing capacity in a longwall on a longwall advance in the form (11) can be formed. Table 5 presents determined co-efficients of non-linear regression. On the basis of the data in table 5, an equation describing the dependence of absolute methane-bearing capacity in a longwall on a longwall advance in the form (13) can be formed. When comparing co-efficient R2 of the contribution of the explained variance in tables 4 and 5 it can be obcserved that non-linear dependence explains better the results of mining measurements. The similar dependence presenting methane emission as dependent on output is suggested by Myszor (1985). The conditions for safe mining can be given for a determined methane emission.


Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 590
Author(s):  
Alexis Lozano ◽  
Pedro Cabrera ◽  
Ana M. Blanco-Marigorta

Technological innovations are not enough by themselves to achieve social and environmental sustainability in companies. Sustainable development aims to determine the environmental impact of a product and the hidden price of products and services through the concept of radical transparency. This means that companies should show and disclose the impact on the environment of any good or service. This way, the consumer can choose in a transparent manner, not only for the price. The use of the eco-label as a European eco-label, which bases its criteria on life cycle assessment, could provide an indicator of corporate social responsibility for a given product. However, it does not give a full guarantee that the product was obtained in a sustainable manner. The aim of this work is to provide a way of calculating the value of the environmental impacts of an industrial product, under different operating conditions, so that each company can provide detailed information on the impacts of its products, information that can form part of its "green product sheet". As a case study, the daily production of a newspaper, printed by coldset, has been chosen. Each process involved in production was configured with raw material and energy consumption information from production plants, manufacturer data and existing databases. Four non-linear regression models have been trained to estimate the impact of a newspaper’s circulation from five input variables (pages, grammage, height, paper type, and print run) with 5508 data samples each. These non-linear regression models were trained using the Levenberg–Marquardt nonlinear least squares algorithm. The mean absolute percentage errors (MAPE) obtained by all the non-linear regression models tested were less than 5%. Through the proposed correlations, it is possible to obtain a score that reports on the impact of the product for different operating conditions and several types of raw materials. Ecolabelling can be further developed by incorporating a scoring system for the impact caused by the product or process, using a standardised impact methodology.


2018 ◽  
Vol 22 (2) ◽  
pp. 65
Author(s):  
Manuela Escobar-Sierra ◽  
Mauricio Antonio Bedoya-Villa

<p><strong>Purpose:</strong> The innovation management linked to social responsibility is considered a strategy of organizational growth promoted by the creativity of employees framed in economic, ethical and legal issues. This study analyses socially responsible innovation management base on employee’s attitudes and leader’s role, from a case study of a company in the Colombian automotive sector.</p><p><strong>Methodology/Approach:</strong> We began with the review of theories about innovation and social responsibility. Then we collected data through creative techniques, surveys to classify the leader’s role, attitudes scale, participant observation and interviews. To finally analyse data with multiple linear regression and other techniques, such as decision trees.</p><p><strong>Findings:</strong> Finally, the initial concept of socially responsible innovation and its management is complemented by five self-determined employees’ attitudes, and one behavior and three perceptions of the leader.</p><p><strong>Research Limitation/implication:</strong> The choice of the single case study as a research strategy determines the practical scope of the research as analytical. In this sense, the need to replicate the study and analyse the impact of other personal and organizational factors is highlighted.</p><p><strong>Originality/Value of paper:</strong> It is important to summarise the value of our paper, in relation to the following aspects: the opportunity that represents for companies the correct socially responsible innovation management, the importance of the Enterprise–University integration and, finally, the relevance of hybrid models in this case, a multiple linear regression and decision trees.</p>


2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.


1991 ◽  
Vol 60 (6) ◽  
pp. 877-890 ◽  
Author(s):  
Martino Grandolfo ◽  
Maria Santini ◽  
Paolo Vecchia ◽  
Adalberto Bonincontro ◽  
Cesare Cametti ◽  
...  

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