Description
Decision Support System Interface With Business Intelligence Solution For Romanian Small And Medium-sized Enterprises
DECISION SUPPORT SYSTEM INTERFACE WITH
BUSINESS INTELLIGENCE SOLUTION FOR ROMANIAN
SMALL AND MEDIUM-SIZED ENTERPRISES
Rocsana ?ONI?, Radu BUCEA-MANEA
INTERFA?A SISTEMULUI INFORMATIC DE ASISTARE A
DECIZIEI CU SOLU?II BUSINESS INTELIGENTE PENTRU
IMM-urile DIN ROMÂNIA
Globalization is a new challenge for small and medium-sized
enterprises. On one hand pose a threat, because new companies are going to
enter the domestic market, but, on the other hand, represent an opportunity to
enter the new emerging and growing markets.
In order to win this challenge SMEs must focus on the inter-network
connection; in fact, is well recognized that SMEs forming networks can improve
the efficiency and effectiveness absolutely necessary to win the globalization
battle.
Cuvinte cheie: SIAD, IMM, tablou de bord, indicatori economico-
financiari
Keywords: DSS, SME, dashboard, financial-economical indicators
1. Introduction
This article present a decision support system dedicated to the
small and medium size enterprises from Romania, containing SMEs
economic and financial data that they submit it annual to Register of
Commerce. These data are then processed and integrated into a data
warehouse, one component of the developed DSS. SMEs access to the
data warehouse is possible through a DSS interface.
39
The article focuses on distributed services applications
philosophy (SOA) and more on fundamenting and implementing a
virtual environment dedicated DSS of cloud type. In that respect the
interface is published through a service with graphic (ASP.NET) and
command line interface. Communication between application modules
is ensured by .NET Removing technology which involves serialized
transmission of the objects. The objects are created starting from a
generic type which implements a common interface. The access to its
members is obtained through reflection. The generic type results by
mapping various heterogenic external data sources followed by making
dynamic conversion between data types. In order to obtain dynamic
views aggregation onto objects, a client language is used, that provides
parameters and tokens to an original dedicated API interface.
If we take the case of one SME, it may find its economic and
financial data collected in the DSS. It has also access to different types
of analyses:
- sales analyses (preferences, periodicity, budget cycles,
appetite for buying etc.);
- operations analysis and searching for alternative sources of
profit;
- asset management analysis;
- what IF analyses;
- forecast analyses etc.
The mentioned SME has access to the same type of analysis
about other SMEs, which it considers competitors or potential business
partners. This creates a network business environment in which
competition is fair; in which SMEs enter the business based on
compatibility.
2. DSS components
It is desirable that the data warehouse access to be free of
charge, but dedicated only for members: any SME wishing to join and
provide additional information about its business. Other potential
members would be institutions, state or private organizations, which
support SMEs activity, such as CNIPMMR- National Council of Small
and Medium Sized Private Enterprises in Romania, AIPPIMM - the
Agency for Implementation of Projects and Programmes for SMEs etc.
The DSS developed contains:
- data management module, represented by the date warehouse
conducted in SQL Server 2008 Express Edition; the data
40
warehouse was populated from the list of Romanian companies
[1] and Finance Minister [2];
- decision management model module allows assisting decision;
as a main model we chose ID3 decision tree, but we
implemented other models as well, such as linear regression
model, what-IF models, forecast models; we have also
calculated indicators often used in company financial situation
analysis (rates of assets, liabilities, financial stability, solvency,
economic profitability, financial profitability, commercial
profitability etc.);
- user interface developed in Microsoft C#and Express Edition
- communication module with other types of applications or
components software e.g decision component, Reporting
Services, SOAP, QlikView etc.
Figure 1 present data trace in DSS and its conversion process
into knowledge.
Fig. 1 DSS with BI solution for Romanian SMEs
Within this article we present especially the DSS interface and
examples of analysis that can be achieved.
3. DSS interface
The interface is emulated on data warehouse structure and on
decision module, responding to the data reporting requirements. Thus
in the C#development environment is created a container, in which it
operates four tabs: SQL generator, Decision, Dashboard, Report.
41
The SQL code generator allows selecting dimensions, attributes,
measures in data warehouse and selecting the query type: cube or
rollup (Figure 2), the result being displayed in Report tab.
Decision tab allows choosing various decision trees,
implemented within application. The figure 3 displays the second type
of decision tree, allowing companies classification into profitable (tree
output value 1), or unprofitable (tree returns value 0), according to
profitability economic ratio, profitability financial ratio and interest ratio.
Fig. 2 SQL CUBE MAKER interface:
SQLgenerator tab
Fig. 3 SQL CUBE MAKER interface:
Decision tab
Dashboard tab allows choosing and displaying various types of
analytical reports (enterprise turnover value on geographical region, on
unit time - criteria chosen by the user), synthetic reports (profitability
rates, solvency, financial autonomy of all SMEs, or for certain SME
chosen by the user) and forecast reports. We keep in mind a web
implementation for this DSS. In this respect there have been developed
reports web, using Reporting Service technology, after a service
oriented architecture.
DSS dynamic reports have been carried out by QlikView BI
solution available at [3]. For downloading the package (free trial) is
enough to register with personal data.
In figure 4 we notice a graphic, a map tree for SMEs turnover in
the representative sample amounted on years, counties and CAEN.
Notice that the counties with highest turnover were: Bucure?ti, Bra?ov,
Arad, Arge?, Alba. Choosing one of these counties will change the
other two graphs that display the turnover for years and CAEN for all
SMEs in the representative sample, only for the selected county.
Similar the selection of year will change the other two graphs, returning
all SMEs turnover in the data source for all categories of activity
(CAEN), for all counties in the year selected. And the CAEN selection
42
will change the other two graphs, returning all SMEs turnover in the
data source for all counties, of all the years for the category of activity
selected. Notice that in 2008 the SMEs turnover in the sample has
come to value 1.340.997.748 Ron, more than in the 2009 or 2010 year
when it amounted to 1.114.387.808 Ron, because of the world
economic crisis influence. The categories of activity with the highest
turnover for the period 2008-2010 have been 5139- Non-specialized
wholesale of food, beverages and tobacco, 6024 - Freight transport by
road, 5119 - Agents involved in the sale of a variety of goods, 6330 -
Activities of travel agencies and tour operators; tourist assistance
activities, 5153 - Wholesale of wood, construction materials and
sanitary equipment. Thus the DSS becomes useful for institutions that
assist or coordinate the SMEs activities (such as CNIPMMR - National
Council of Small and Medium Sized Private Enterprises in Romania,
AIPPIMM - Agency for Implementation of Projects and Programmes for
SMEs). They may create policies for the development of certain niches
of activity with potential, but insufficiently supported. Practically user
can achieve countless queries with the mentioned selected criteria. The
DSS allows successive queries, with several criteria. It can be chosen,
for example, first year, county and then finally CAEN and DSS will take
account all three criteria.
Fig. 4 Dashboard regarding turnover for all SMEs from the representative
sample, grouped by county, year and CAEN
BI interface can be further improved by adding statistics.
Selecting the year 2010 and Bucharest, notice the categories of activity
on the combo list (only the companies with white background are
specific to Bucharest). Among these the most frequent are 6330 -
Activities of travel agencies and tour operators; tourist assistance
activities, 5144 - Wholesale of china and glassware, wallpaper and
cleaning materials, 5134- Wholesale of alcoholic and other beverages.
The statistics cover the minimum values, the maximum, the amount,
43
the average and kurtosis and skewness tests for net profit and the
number of employees from Bucharest in 2010. It has been taken into
account 31 companies whose net profit summed has a value of
2.573.465 Ron, with an average of 83,015, a minimum of 963542 and a
maximum of 1598877. Skewness and Kurtosis tests show the chart
asymmetry comparing with "chart of gauss's normal curve”, for which
Skewness=0 and Kurtosis=3. The skewness value for Bucharest 2010
is 1.44 and indicates a right positive asymmetry and the value of
Kurtosis 3.77 indicate a positive distribution curve that is higher than
Gauss curve.
Similar are interpreted the values of number of employees, for
which chart curve is flattened and moved to the right. The values are
close to the normal curve, being an indicator that the sample is
representative.
Thus a SME which wants to learn how is situated in
comparison with other SME will choose as criteria its own CUI, the year
and the county if has activity in several county. (Figure5)
Fig. 5 Dynamic dashboard on turnover of the SMEs representative sample, or a
specified SME having as criteria company, CAEN, year, locality
In the panel in figure 5 it may be seen how selecting a
company name fill all the objects in the dashboard with information
relating to the company, such as CUI, CAEN, We notice that the
44
company had a small solvency of 2.01 in 2010, but this value is linked
with other indicators (Figure 7). Also are returned the profit net and the
turnover. They appear in green, when they have a value above all
companies Net Profit average, or Turnover, or in red if the value is
below the average (it is our case, too).
In the panel in figure 6 is analyzed the influence of total
revenue variations on net profit. The model designs the polynomial
regression of second degree for net profit. The determination coefficient
R
2
takes the maximum value 1, meaning that the regression model
adjusts very well the data series.
Fig. 6 What IF Analysis on the Net Profit value of certain SME chosen
by the user under the influence of Net Income
The interface is dynamic: any selection update properly values
in the interface objects. Company name may be selected from a
dynamic list, or from the searching module by filling it in. Selecting a
county results in showing the entire active companies name in that
county, of which one can select the firm he is interested in. It is similar
when selecting the year or total assets, for example.
The DSS allows complex analyses such as "What if". In the
figure 6 it can be observed as a variation of total revenue growth with 5
percent, would determine an increase in net profit, in case of
maintaining constant total expenditure (curved red superior in graph). In
the graphic is observed that in 2010 the net profit dropped to about half
the amount profit in the year 2009, the difference is growing more for
2008. The chart is similar to that of a polynomial function of the second
45
degree, whose equation of regression is observed in the image. The R
2
coefficient takes the maximal value 1, meaning that regression equation
adjusts very well data series.
Further information on economic and financial profitability,
overall solvency ratio overall debt, financial stability and the autonomy
rates, the rates of assets for a SME chosen by the user are presented
to the figure 7. Like other dashboard and this one is dynamic too, and is
updated in real time on any selection of objects contained
Fig. 7 Economical-financial indicators for a SME chosen by the user
According to these values it can be seen whether a company is
profitable or not. For the selected company the economic profitability
ratio RE (18.51) is not very high, but financial profitability ratio RF is
very small (0.93). Total assets profitability ratio is not very high, too,
having the value of 15.79. The company is not profitable because they
are not met concurrently conditions RE>interest ratio and RF>RE. The
company must review their activity and increase the net profit, which is
too small having in mind the capital and increase the gross profit, which
is too small having in mind total assets, resulting a small economic
profitability.
The company should pay attention to the general solvency who
is very small, 1.36, by reducing debt total. Financial autonomy ratio is
46
16.08: the company can increase own capital, which is small compared
with total liabilities. Financial lever has the value 5.94, above the
threshold of 5, indicates an undercapitalized company. Financial
stability is not very good, too, its ratio having a value of 26.74. This may
be increased by an increase of working capital value. Overall ratio of
debt of 73.27 is high and is recommended lowering total debt, having in
mind the weak financial stability and autonomy. Profitability ratio of its
own capital - ROE is 93.94 and exceeds current interest ratio, which
means that the company may invest.
The ratio of the fixed assets for the selected company is 19.25,
and that of current assets is 80.75. It may be considered that the
company doesn’t pay attention on capital investment, and it is advisable
to review its investment policy. According to the company activity
characteristics further conclusions and decisions may be taken.
The stocks ratio is 8.21 having a small amount, unfavorable
situation for the company. The debts ratio is 0.73 what favors creditors,
because the lower the ratio is the more protected is the company to
creditors losses, in case of liquidation.
An What IF analysis simulates the operating result variations
influence on economic profitability and financial profitability. (Figure 8) It
can be calculated how must increase gross profit so that the company
have a high economic profitability and to be profitable. However there
are companies with greater economic profitability than financial
profitability, when the analysis is based on the net profit and capital.
The company analyzed in previous example is in the same situation.
The same interface BI allows defining new types of reports,
without being necessary knowledge about the business model or
economical context.
These reports may be accessed according to user requests.
After defining reports models, users will only have to call the report, to
choose different criteria for query, to interpret the results and
fundament their decisions.
This interface allows defining new type of reports, without being
necessary IT insight.
It is enough knowing the objects that can be activated in the
interface and knowing how they are associated with different
warehouse data attributes or measures.
In order that the warehouse not be overloaded it is used the
volatile memory area for the data to be temporary loaded.
Thus the data warehouse may be used for making concurrent
ad-hoc queries.
47
4. Conclusions
A constructive trend in the context of globalization is
associating SMEs within a virtual networks business, to promote
communication and making business in real time. This virtual business
environment bases on a data warehouse with economic and financial
data for Romanian SMEs stored on a server. Virtual business
environment allows access to a BI solution through a friendly interface
described in the article, solution that allows complex economic and
financial analysis. Analyses above demonstrate the utility of online
business association, for both SMEs and to institutions that assist theirs
activity.
Fig. 8 What IF analysis regarding gross profit influence on economic
profitability for a company chosen by the user
BIBLIOGRAPHY
[1] * * * List of Romanian enterpriseshttp://www.listafirme.ro/
[2] * * * Public Finance Minister, Romaniahttp://www.mfinante.ro/agenticod.html?pagina=domenii
[3] * * *Instal QlikView:http://global.qlikview.com/download/
Rocsana ?ONI?,
Radu BUCEA-MANEA
Center for European Studies and Mobility
48
METODA ELEMENTULUI DE FRONTIER? CU
ELEMENTE LINIARE,
PENTRU O RE?EA AXIAL? ÎN ”S”
Partea I
Ionel Doru BACIU, Ilare BORDEA?U
BEM WITH LINIARE ELEMENTS, FOR AN
AXIAL”S” CASCADE
First part
This paper presents boundary element method (BEM), with linear
elements, for the numerical simulation of ideal incompressible fluid, for a
reversible cascade”S” axial profiles. BEM apply for Laplace's equation
depending on flow and hydrodynamic field, speed and pressure are obtained,
inside of domain analysis.
Cuvinte cheie: elemente liniare, BEM, ecua?ia lui Laplace, puncte
unghiulare
Keywords: linear elements, BEM, Laplace equation, angular points
1. Introducere
Pentru exploatarea eficient? a poten?ialului hidroenergetic în
regim de func?ionare ?i de stocare a energiei hidraulice, este necesar
ca centralele hidro-electrice, s? fie echipate cu ma?ini hidraulice
reversibile, numite pompe-turbine.
Cu ajutorul metodei elementului de frontier?, se pot crea astfel
de profile.
49
doc_673738513.pdf
Decision Support System Interface With Business Intelligence Solution For Romanian Small And Medium-sized Enterprises
DECISION SUPPORT SYSTEM INTERFACE WITH
BUSINESS INTELLIGENCE SOLUTION FOR ROMANIAN
SMALL AND MEDIUM-SIZED ENTERPRISES
Rocsana ?ONI?, Radu BUCEA-MANEA
INTERFA?A SISTEMULUI INFORMATIC DE ASISTARE A
DECIZIEI CU SOLU?II BUSINESS INTELIGENTE PENTRU
IMM-urile DIN ROMÂNIA
Globalization is a new challenge for small and medium-sized
enterprises. On one hand pose a threat, because new companies are going to
enter the domestic market, but, on the other hand, represent an opportunity to
enter the new emerging and growing markets.
In order to win this challenge SMEs must focus on the inter-network
connection; in fact, is well recognized that SMEs forming networks can improve
the efficiency and effectiveness absolutely necessary to win the globalization
battle.
Cuvinte cheie: SIAD, IMM, tablou de bord, indicatori economico-
financiari
Keywords: DSS, SME, dashboard, financial-economical indicators
1. Introduction
This article present a decision support system dedicated to the
small and medium size enterprises from Romania, containing SMEs
economic and financial data that they submit it annual to Register of
Commerce. These data are then processed and integrated into a data
warehouse, one component of the developed DSS. SMEs access to the
data warehouse is possible through a DSS interface.
39
The article focuses on distributed services applications
philosophy (SOA) and more on fundamenting and implementing a
virtual environment dedicated DSS of cloud type. In that respect the
interface is published through a service with graphic (ASP.NET) and
command line interface. Communication between application modules
is ensured by .NET Removing technology which involves serialized
transmission of the objects. The objects are created starting from a
generic type which implements a common interface. The access to its
members is obtained through reflection. The generic type results by
mapping various heterogenic external data sources followed by making
dynamic conversion between data types. In order to obtain dynamic
views aggregation onto objects, a client language is used, that provides
parameters and tokens to an original dedicated API interface.
If we take the case of one SME, it may find its economic and
financial data collected in the DSS. It has also access to different types
of analyses:
- sales analyses (preferences, periodicity, budget cycles,
appetite for buying etc.);
- operations analysis and searching for alternative sources of
profit;
- asset management analysis;
- what IF analyses;
- forecast analyses etc.
The mentioned SME has access to the same type of analysis
about other SMEs, which it considers competitors or potential business
partners. This creates a network business environment in which
competition is fair; in which SMEs enter the business based on
compatibility.
2. DSS components
It is desirable that the data warehouse access to be free of
charge, but dedicated only for members: any SME wishing to join and
provide additional information about its business. Other potential
members would be institutions, state or private organizations, which
support SMEs activity, such as CNIPMMR- National Council of Small
and Medium Sized Private Enterprises in Romania, AIPPIMM - the
Agency for Implementation of Projects and Programmes for SMEs etc.
The DSS developed contains:
- data management module, represented by the date warehouse
conducted in SQL Server 2008 Express Edition; the data
40
warehouse was populated from the list of Romanian companies
[1] and Finance Minister [2];
- decision management model module allows assisting decision;
as a main model we chose ID3 decision tree, but we
implemented other models as well, such as linear regression
model, what-IF models, forecast models; we have also
calculated indicators often used in company financial situation
analysis (rates of assets, liabilities, financial stability, solvency,
economic profitability, financial profitability, commercial
profitability etc.);
- user interface developed in Microsoft C#and Express Edition
- communication module with other types of applications or
components software e.g decision component, Reporting
Services, SOAP, QlikView etc.
Figure 1 present data trace in DSS and its conversion process
into knowledge.
Fig. 1 DSS with BI solution for Romanian SMEs
Within this article we present especially the DSS interface and
examples of analysis that can be achieved.
3. DSS interface
The interface is emulated on data warehouse structure and on
decision module, responding to the data reporting requirements. Thus
in the C#development environment is created a container, in which it
operates four tabs: SQL generator, Decision, Dashboard, Report.
41
The SQL code generator allows selecting dimensions, attributes,
measures in data warehouse and selecting the query type: cube or
rollup (Figure 2), the result being displayed in Report tab.
Decision tab allows choosing various decision trees,
implemented within application. The figure 3 displays the second type
of decision tree, allowing companies classification into profitable (tree
output value 1), or unprofitable (tree returns value 0), according to
profitability economic ratio, profitability financial ratio and interest ratio.
Fig. 2 SQL CUBE MAKER interface:
SQLgenerator tab
Fig. 3 SQL CUBE MAKER interface:
Decision tab
Dashboard tab allows choosing and displaying various types of
analytical reports (enterprise turnover value on geographical region, on
unit time - criteria chosen by the user), synthetic reports (profitability
rates, solvency, financial autonomy of all SMEs, or for certain SME
chosen by the user) and forecast reports. We keep in mind a web
implementation for this DSS. In this respect there have been developed
reports web, using Reporting Service technology, after a service
oriented architecture.
DSS dynamic reports have been carried out by QlikView BI
solution available at [3]. For downloading the package (free trial) is
enough to register with personal data.
In figure 4 we notice a graphic, a map tree for SMEs turnover in
the representative sample amounted on years, counties and CAEN.
Notice that the counties with highest turnover were: Bucure?ti, Bra?ov,
Arad, Arge?, Alba. Choosing one of these counties will change the
other two graphs that display the turnover for years and CAEN for all
SMEs in the representative sample, only for the selected county.
Similar the selection of year will change the other two graphs, returning
all SMEs turnover in the data source for all categories of activity
(CAEN), for all counties in the year selected. And the CAEN selection
42
will change the other two graphs, returning all SMEs turnover in the
data source for all counties, of all the years for the category of activity
selected. Notice that in 2008 the SMEs turnover in the sample has
come to value 1.340.997.748 Ron, more than in the 2009 or 2010 year
when it amounted to 1.114.387.808 Ron, because of the world
economic crisis influence. The categories of activity with the highest
turnover for the period 2008-2010 have been 5139- Non-specialized
wholesale of food, beverages and tobacco, 6024 - Freight transport by
road, 5119 - Agents involved in the sale of a variety of goods, 6330 -
Activities of travel agencies and tour operators; tourist assistance
activities, 5153 - Wholesale of wood, construction materials and
sanitary equipment. Thus the DSS becomes useful for institutions that
assist or coordinate the SMEs activities (such as CNIPMMR - National
Council of Small and Medium Sized Private Enterprises in Romania,
AIPPIMM - Agency for Implementation of Projects and Programmes for
SMEs). They may create policies for the development of certain niches
of activity with potential, but insufficiently supported. Practically user
can achieve countless queries with the mentioned selected criteria. The
DSS allows successive queries, with several criteria. It can be chosen,
for example, first year, county and then finally CAEN and DSS will take
account all three criteria.
Fig. 4 Dashboard regarding turnover for all SMEs from the representative
sample, grouped by county, year and CAEN
BI interface can be further improved by adding statistics.
Selecting the year 2010 and Bucharest, notice the categories of activity
on the combo list (only the companies with white background are
specific to Bucharest). Among these the most frequent are 6330 -
Activities of travel agencies and tour operators; tourist assistance
activities, 5144 - Wholesale of china and glassware, wallpaper and
cleaning materials, 5134- Wholesale of alcoholic and other beverages.
The statistics cover the minimum values, the maximum, the amount,
43
the average and kurtosis and skewness tests for net profit and the
number of employees from Bucharest in 2010. It has been taken into
account 31 companies whose net profit summed has a value of
2.573.465 Ron, with an average of 83,015, a minimum of 963542 and a
maximum of 1598877. Skewness and Kurtosis tests show the chart
asymmetry comparing with "chart of gauss's normal curve”, for which
Skewness=0 and Kurtosis=3. The skewness value for Bucharest 2010
is 1.44 and indicates a right positive asymmetry and the value of
Kurtosis 3.77 indicate a positive distribution curve that is higher than
Gauss curve.
Similar are interpreted the values of number of employees, for
which chart curve is flattened and moved to the right. The values are
close to the normal curve, being an indicator that the sample is
representative.
Thus a SME which wants to learn how is situated in
comparison with other SME will choose as criteria its own CUI, the year
and the county if has activity in several county. (Figure5)
Fig. 5 Dynamic dashboard on turnover of the SMEs representative sample, or a
specified SME having as criteria company, CAEN, year, locality
In the panel in figure 5 it may be seen how selecting a
company name fill all the objects in the dashboard with information
relating to the company, such as CUI, CAEN, We notice that the
44
company had a small solvency of 2.01 in 2010, but this value is linked
with other indicators (Figure 7). Also are returned the profit net and the
turnover. They appear in green, when they have a value above all
companies Net Profit average, or Turnover, or in red if the value is
below the average (it is our case, too).
In the panel in figure 6 is analyzed the influence of total
revenue variations on net profit. The model designs the polynomial
regression of second degree for net profit. The determination coefficient
R
2
takes the maximum value 1, meaning that the regression model
adjusts very well the data series.
Fig. 6 What IF Analysis on the Net Profit value of certain SME chosen
by the user under the influence of Net Income
The interface is dynamic: any selection update properly values
in the interface objects. Company name may be selected from a
dynamic list, or from the searching module by filling it in. Selecting a
county results in showing the entire active companies name in that
county, of which one can select the firm he is interested in. It is similar
when selecting the year or total assets, for example.
The DSS allows complex analyses such as "What if". In the
figure 6 it can be observed as a variation of total revenue growth with 5
percent, would determine an increase in net profit, in case of
maintaining constant total expenditure (curved red superior in graph). In
the graphic is observed that in 2010 the net profit dropped to about half
the amount profit in the year 2009, the difference is growing more for
2008. The chart is similar to that of a polynomial function of the second
45
degree, whose equation of regression is observed in the image. The R
2
coefficient takes the maximal value 1, meaning that regression equation
adjusts very well data series.
Further information on economic and financial profitability,
overall solvency ratio overall debt, financial stability and the autonomy
rates, the rates of assets for a SME chosen by the user are presented
to the figure 7. Like other dashboard and this one is dynamic too, and is
updated in real time on any selection of objects contained
Fig. 7 Economical-financial indicators for a SME chosen by the user
According to these values it can be seen whether a company is
profitable or not. For the selected company the economic profitability
ratio RE (18.51) is not very high, but financial profitability ratio RF is
very small (0.93). Total assets profitability ratio is not very high, too,
having the value of 15.79. The company is not profitable because they
are not met concurrently conditions RE>interest ratio and RF>RE. The
company must review their activity and increase the net profit, which is
too small having in mind the capital and increase the gross profit, which
is too small having in mind total assets, resulting a small economic
profitability.
The company should pay attention to the general solvency who
is very small, 1.36, by reducing debt total. Financial autonomy ratio is
46
16.08: the company can increase own capital, which is small compared
with total liabilities. Financial lever has the value 5.94, above the
threshold of 5, indicates an undercapitalized company. Financial
stability is not very good, too, its ratio having a value of 26.74. This may
be increased by an increase of working capital value. Overall ratio of
debt of 73.27 is high and is recommended lowering total debt, having in
mind the weak financial stability and autonomy. Profitability ratio of its
own capital - ROE is 93.94 and exceeds current interest ratio, which
means that the company may invest.
The ratio of the fixed assets for the selected company is 19.25,
and that of current assets is 80.75. It may be considered that the
company doesn’t pay attention on capital investment, and it is advisable
to review its investment policy. According to the company activity
characteristics further conclusions and decisions may be taken.
The stocks ratio is 8.21 having a small amount, unfavorable
situation for the company. The debts ratio is 0.73 what favors creditors,
because the lower the ratio is the more protected is the company to
creditors losses, in case of liquidation.
An What IF analysis simulates the operating result variations
influence on economic profitability and financial profitability. (Figure 8) It
can be calculated how must increase gross profit so that the company
have a high economic profitability and to be profitable. However there
are companies with greater economic profitability than financial
profitability, when the analysis is based on the net profit and capital.
The company analyzed in previous example is in the same situation.
The same interface BI allows defining new types of reports,
without being necessary knowledge about the business model or
economical context.
These reports may be accessed according to user requests.
After defining reports models, users will only have to call the report, to
choose different criteria for query, to interpret the results and
fundament their decisions.
This interface allows defining new type of reports, without being
necessary IT insight.
It is enough knowing the objects that can be activated in the
interface and knowing how they are associated with different
warehouse data attributes or measures.
In order that the warehouse not be overloaded it is used the
volatile memory area for the data to be temporary loaded.
Thus the data warehouse may be used for making concurrent
ad-hoc queries.
47
4. Conclusions
A constructive trend in the context of globalization is
associating SMEs within a virtual networks business, to promote
communication and making business in real time. This virtual business
environment bases on a data warehouse with economic and financial
data for Romanian SMEs stored on a server. Virtual business
environment allows access to a BI solution through a friendly interface
described in the article, solution that allows complex economic and
financial analysis. Analyses above demonstrate the utility of online
business association, for both SMEs and to institutions that assist theirs
activity.
Fig. 8 What IF analysis regarding gross profit influence on economic
profitability for a company chosen by the user
BIBLIOGRAPHY
[1] * * * List of Romanian enterpriseshttp://www.listafirme.ro/
[2] * * * Public Finance Minister, Romaniahttp://www.mfinante.ro/agenticod.html?pagina=domenii
[3] * * *Instal QlikView:http://global.qlikview.com/download/
Rocsana ?ONI?,
Radu BUCEA-MANEA
Center for European Studies and Mobility
48
METODA ELEMENTULUI DE FRONTIER? CU
ELEMENTE LINIARE,
PENTRU O RE?EA AXIAL? ÎN ”S”
Partea I
Ionel Doru BACIU, Ilare BORDEA?U
BEM WITH LINIARE ELEMENTS, FOR AN
AXIAL”S” CASCADE
First part
This paper presents boundary element method (BEM), with linear
elements, for the numerical simulation of ideal incompressible fluid, for a
reversible cascade”S” axial profiles. BEM apply for Laplace's equation
depending on flow and hydrodynamic field, speed and pressure are obtained,
inside of domain analysis.
Cuvinte cheie: elemente liniare, BEM, ecua?ia lui Laplace, puncte
unghiulare
Keywords: linear elements, BEM, Laplace equation, angular points
1. Introducere
Pentru exploatarea eficient? a poten?ialului hidroenergetic în
regim de func?ionare ?i de stocare a energiei hidraulice, este necesar
ca centralele hidro-electrice, s? fie echipate cu ma?ini hidraulice
reversibile, numite pompe-turbine.
Cu ajutorul metodei elementului de frontier?, se pot crea astfel
de profile.
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doc_673738513.pdf