INFORMATIONAL TECHNOLOGIES AND COMMUNICATIONS IN THE ROMANIAN LOCAL PUBLIC ADMINISTRATION
Armenia Androniceanu [1]
Irina Georgescu[2]
Abstract
The paper contains the results of one study developed by the authors during the year 2007 in the Romanian local public administration. This study examines the diffusion of information technologies in the public management system in the Romanian local public administration. A questionnaire was drawn up intending to answer to the main objectives of the study. Based on the statistical analysis, we identified the main strong points and the weaknesses and following them we presented and explained the key and urgent actions needed for increasing the Romanian local public administration capacity using the advantages of the informational technologies and communications.
This study examines the diffusion of information technologies inside the public organizations from the Romanian local public administration. The researchers used a special questionnaire for a representative sample. All the data obtained has been analyzed using quantitative methods, mainly statistical analysis. The results of the analysis are important not only for knowing the real status of the Romanian local public administration, but mainly for interpretation and for discovering the reasons and the next urgent steps forward. Based on the findings of the research, the most important and urgent actions needed for the Romanian local public administration has been set up and described shortly in the last part of thispaper.
1. Introduction
Information is one of the defining paradigms of the modern society. The efficiency of decision making process is determined by the quality of the information (degree of precision, relevance, completeness, etc.). The presence of more and more complex economic and social phenomena characterized by numerous parameters (Eagles M, 1999) being in a complicated structural relation lead to the organization of the information in a modern informational systems (Anderson D, 1991). The function of these informational systems is indissolubly related to the actual developments in informational technology, communications and in science. (Rocheleau B., 1999; Hamelimk, C. , 1986; Flecher D. 1992; Giovannini 2007). The proliferation of computers and the Internet make access to various source data very conveniently.
Data, information, data processing and the flows of information are influenced by several factors and variables which exist inside and outside the public organization.(Blair D, 1991; Alter S, 1980; Hamid N, 1990) .Modern information technology (IT) has outspaced human ability to process, utilize and store data. According to (Fayyad & Uthurusamy 2002), computer’s capacity of digital data storage has doubled twice as fast every nine months. Modern managers and decision makers have access to larger amounts of facts than the managers of the past.
The tendency in public administration is to increase the integration of the new instruments based on informational technologies and communications (IT&C) in the content of the public services. In the modern society it’s considered that the quality of these services is directly related with their integration in producing and delivering processes. The nature of the public management based on the integration of the IT&C determines major changes inside the public institutions and also in his relations with the citizens and the business environment. This allows that the collection, processing, transmission and storage of information be realized rapidly and efficiently. Also the quality of the public services will be significantly improved and the satisfaction of the stakeholders will increase too.
As in many countries, in Romania the system of public administration is divided in two components: the central public administration and the local public administration. Mainly, both of them have the same functions, with the difference that the central public administration acts nationally and the local public administration, in some limits of competences, satisfies the needs of the local community. Both components are complementary and the local public administration depends many times by the financial support of central level. In 2006, in Romania the weight of the central public administration was 43,35% and the weight of the local public administration was 54,65%. Statistical analysis seems to be the best tool to support policy making systems.
This paper is based on a special investigation included in a complex research study and will show us the level of modern technologies integrated in the public management at the Romanian local public administration. Based on these results, will be identified the key and urgent actions needed for increasing the Romanian local public administration capacity for using the advantages of the IT&C. The authors used a special questionnaire. Elaboration of the questionnaire and its analysis make part of a special research project financed by the Romanian Government through the International Centre for Public Management.
The paper represents one important result of the main part of this complex research project which has one of the most important objectives to identify and to investigate the extent to which the Romanian local public administration use the informational and communications technologies and to analyze the status of implementing IT&C at the level of Romanian local public administration. In order to do this, we use several statistical methods. The background for the methods of statistical analysis can be found in (e.g. Andreica et al., 1998; Salvatore & Reagle, 2002; Andreica et al., 2002; Gujarati, 2003; Voineagu et al., 2006; Voineagu et al., 2007 ).In the statistical analysis of the responses of the questions in the questionnaire a model from (Andreica et al. 1998; Voineagu et al. 2007)is used. The obtained indicators have been discussed and the main conclusions are presented in this article.
Finally, it was hoped to discover whether the Romanian local public administration might be motivated to make use of them in the near future and also, in the next research stage we intend to design a new public management model for the Romanian local public administration based on a modern public management, more transparent, interactive, more efficient and much more flexible and client oriented using the IT&C.
2.Methodology
The statistical study of this paper required the elaboration of classifications and simple groups, taking into consideration one or two numerical characteristics comprised in the study. The variables considered in this paper are either numerical ( “number of computers/computer facilities related to the number of employees”, “number of servers”, “electronic mail”) or qualitative (“applications”, “document management applications”, “Internet connections”, “telephonic communications”, “call-center”, “e-mail documents”, “communications”, “received information”, “website”, “actualization period”, “offered information/services”).
According to the variation of the pursued characteristics, the groupings can be done on options or on intervals of variation.
In case when the pursued characteristic has a reduced number of variants, we did the grouping on variants. The operation of processing data consists of the identification by counting the units (frequencies) at which the same variant of the characteristics is recorded. The grouping of data on intervals of variations is used when the numerical characteristic presents a great number of individual values.
The tables corresponding to the numerical characteristics contain: interval of variation, absolute frequencies, centre of intervals and increasingly cumulated absolute frequencies. The tables corresponding to the qualitative variables contain: options, number of units/percentage and increasingly cumulated absolute frequencies.
In the statistical analysis of the questionnaire we used some indicators:
The indicators of central tendency. Their main function is to synthesize the individual values of the pursued characteristics. The indicators of the central tendency are determined in general as mean indicators or indicators of position (the mode and the quartiles). They point out the tendency of crowd, of concentration of the units towards the studied characteristic.
The mean value of the individual values of a characteristic is the value obtained as if all factors of influence have the same intensity at the level of each unit. The mean is the sum of the observations divided by the number of observations. The mean describes the central location of the data.
The mode of the characteristic, also called dominant value, is the value of the characteristic which corresponds to the greatest number of units or which has the greatest frequency of occurrence.
The quartiles are indicators which describe some positions occupying a certain place in the distribution series. They indicate a partition of the distribution into a number of parts.
The median is the middle of a distribution; half the scores are above the median and half are below the median.
The standard deviation is a simple measure of the variability or dispersion of a data set. A low standard deviation indicates that all of the data points are very close to the same value (the mean), while high standard deviation indicates that the data are “spread out” over a large range of values. The coefficient of variation is computed as a fraction between the mean square deviation and the mean value. It measures the homogeneity of the statistical distributions after a certain characteristic and it takes values in the interval [0; 100%].
The asymmetry coefficient is usually called the coefficient of skewness. One correspondingly speaks of the skewness of a distribution and of positive, respectively negative, skewness.
The excess coefficient is more often called thecoefficient of kurtosis.
The Pearson coefficient of asymmetry applies in the case of the slightly asymmetrical distributions. It is determined by relating the difference between average and mode to the average square deviation. The indicator provides information on both the direction of asymmetry and its intensity.
3. The sample of the survey and the questionnaire analysis
In order to do their work, public managers need a great amount of information. According to McLeod & Jones (1986)it was noticed that information was critical in situations where public managers have to handle disturbances. In an environment becoming more and more complex, public managers and knowledge of the civil servants should use modern, informational technologies in order to collect information, to communicate and to make efficient decisions. This is the rationale for this study. In other words, it was hoped that the questionnaire itself might act as an information tool, encouraging the use of these technologies. It was also hoped that the introduction of the informational and communications technologies makes a change in public institutions.
This paper is the product of a special survey undertaken across 221 representatives of institutions of the Romanian local public administration (town halls and prefectures) from 39 districts. This is a representative segment for the Romanian local public administration.
As we mentioned already, the study was made in 2007 -2008 on a random sample of institutions of the Romanian local public administration. The institutions included in the research were among: towns with less than 20,000 inhabitants, towns with 20,000-100,000 inhabitants, towns with more than 100,000 inhabitants and few villages. The institutions gave information related to the structure of services and available IT&C infrastructure.
In order to fulfill the purpose of the research, a questionnaire was drawn up with a range of questions addressed to each of the main objectives of the study. The information provided by the respondents was captured into an excel file for later analysis. The questionnaire contained 13 key questions. The majority of questions had answers of type “Yes/No” or answers from a defined range of choices; there were no open-ended questions. The respondent filled in the questionnaire by form. The actual responses are not included here. In the statistical analysis we identified 16 variables: number of computer facilities, servers, types of used applications, management documents applications types, internet connection, phone communication, call center, e-mail address, e-mail documents archives rule, computers communication, information received, information reported, institution website, institution website update, institution website information and use of the call center.
In the following, we make a statistical analysis of the survey population and their answers to the questions. Descriptive statistics are used to describe the basic features of the data gathered from the experimental study (Davidson, 2000; Guajarati, 2003; Klein, 1974).
For every variable we determine its structure by computing the weights. For variables which are divided on intervals, we compute the mean value, the variance, the coefficient of variation, the principal indicators of position and the asymmetry of the frequency distribution. The data obtained for questions 3, 4, 5, 6, 7, 9, 10, 11, 12, 13 represent series of frequency distributions on versions and the analyzed variables are qualitative.
4. The statistical analysis for question 1 is presented below.
As it shows in Table no.1, we used different intervals for grouping the responses obtained from the investigated public organizations.
Table no. 1 Frequency distribution of the variable “number of computers/computer facilities related to the number of employees” (Question 1)
Interval in percents (%) / Absolute frequencies (number of institutions)/percentage / Centre of interval
/ / / Increasingly
cumulated absolute frequencies /
under 40 / 9 (4,05%) / 20 / 180 / 3600 / 9 / 13878588
40-80 / 65 (29,27%) / 60 / 3900 / 234000 / 74 / 195819.4
80-100 / 89 (40,09%) / 90 / 8010 / 720900 / 163 / 6456.548
100 / 59 (26,57%) / 100 / 5900 / 590000 / 222 / 129335.1
Total / 222 / - / 17990 / 1548500 / - / 14210199
As we can see in Annex 1, especially in table no. 1, 40,09% of the respondents answered that the computer facilities/computers related to the numbers of employees are between 80-100%, 29,27% - between 49-80%, 26,57% -100% and 4,05% -under 40%.
For the statistical analysis we use the model of Andreica et al. (1998); Voineagu et al. (2007). We compute the weighted mean value of the percentage of the number of computer facilities/computers related to the number of employees with help of the absolute frequencies.
-the mean value: 81,03=81,03%
Therefore, in one institution from the 222 taken into consideration, the number of computer facilities/computers related to the number of employees is 81,03%.
The degree of dispersion of the values of variable “the computer facilities/computers” with respect to the mean value is given by the variance.
-the variance: =-=408,38
It follows that the standard deviation is s(x)=20,20
The interval in which the mean value is included is .
To verify the representativeness of the mean value obtained above we compute the coefficient of variation “v”:
- ==24,93%<35% which means that the mean value of the variable “computer facilities / computers” is representative, the collectivity being homogeneous.
Next, we compute the following mean indicators of position:
a) the first quartile:
For its computation we proceed as it’s presented below:
Determination of the position of the first quartile:
loc ()===55,75
Finding the interval to which the first quartile belongs to (the first interval whose increasingly cumulated frequency overcomes the place of the first quartile), this is 40-80;
Computation of the first quartile, by the formula:
===68,76%
where:
=the inferior limit of the interval of the first quartile;
k=the length of the quartile interval;
=the cumulated frequency of the interval anterior to the quartile interval;
=the absolute frequency of the interval of the first quartile;
Therefore in 75% of the institutions, the number of computer facilities/computers related to the number of employees is more than 68,76%, which is a good percentage but is under the need and the estimated expectations, if we compare with the standards of other developed countries.
b) the median (Me)
locMe===111,5
The median belongs to the interval 80-100.
Me==80+20=88,42%
Therefore in 50% of institutions the number of computer facilities/computers related to the numbers of employees is more than 88,42%, and in 50% less.
c) the third quartile ()
loc===167,25
The third quartile belongs to the interval 100%, therefore we can consider that =100%.
Therefore in 25% of institutions the computer facilities/computers related to the number of employees is about 100% and in 75% of institutions it is less.
d) Asymmetry of a frequency distribution can be measured by specific coefficients. We give now the most significant ones.
We analyze the asymmetry of the distribution by means of the coefficient of asymmetry of Pearson:
Cas=
The mode is defined by: Mo=
where =the lower limit of the modal interval; k=the length of the modal interval.
The modal interval has the maxim frequency: [80, 100).
=the frequency of the modal interval minus the frequency of the interval anterior to the modal interval;
=the frequency of the modal interval minus the frequency of the interval following the modal interval.
We obtain =89-65=24; =89-59=30
The mode Mo=80+20=88,88%
In most of institutions the number of computer facilities/computers related to the numbers of employees is 88,88%.
Cas==-0,3752<0 which shows a slight, negative asymmetry . In the series of data the small values prevail.
Kurtosis measures the height, i. e, the elongation or the flattening of the curve, compared with the normal one. Kurtosis can be measured with the Pearson coefficient of skeweness=. This indicator is determined by means of the centered moment of order 2 and the centered moment of order 4.
Since it follows that =408,38.
=656,94
==1,60
Kurtosis can be also measured with the indicator =-3 =1,60-3= -1,4<0, therefore the frequency distribution is platykurtic. There is a slightly higher middle point and the curve is still symmetrical, but scores are spread out rather evenly from the lowest to the highest points.
Referring to the question 2: “In your institution, the necessary of servers in order to completely cover the needs is assured in proportion of ……”, table no.2 contains the frequency distribution of the variable “number of servers” in the investigated public institutions.
Table no. 2 Frequency distribution of the variable “number of servers” (Question 2)
Interval in percents (%) / Absolute frequencies/percentage / Centre of interval
/ / / Increasingly
cumulated absolute frequencies
under 40 / 45(20,36%) / 20 / 900 / 18000 / 45
40-80 / 68(30,76%) / 60 / 4080 / 244800 / 113
80-100 / 45(20,36%) / 90 / 4050 / 364500 / 158
100 / 63(28,50%) / 100 / 6300 / 630000 / 221
Total / 221 / - / 15330 / 1257300 / -
As shown in table no.2, 30,76% of the respondents answered that in their institution the necessary of servers is assured in proportion of 40-80%, 28,50% answered that the proportion of servers is totally covered, 20,36% answered that the proportion is between 80-100% and 20,36% answered that that the necessary of servers is covered under 40%.