Multiple Criteria Evaluation and Ranking of Social Penetration of Information Society Technologies Jan Grzegorek TP SA, Andrzej P. Wierzbicki National Institute of Telecommunications, Warsaw, Szachowa 1 Contents: Issues of Research Nework Readiness Indicators NRI with Objective Ranking Dynamic Ranking of Regional IS Penetration Conclusions

Issues of Research -1 Contemporary evaluations of social or socio-economic penetration of information society technologies concern many statistical measures, such as households with access to Internet at home, households with broadband access to Internet, individuals regularly using Internet, individuals who ordered goods or services over Internet for private use, schools equipped with computer laboratories, schools with broadband access to Internet, etc. If we evaluate the penetration of information society technologies generally in a country, region, or a district, we must use a multiple criteria aggregation. Typically, a simple weighted sum aggregation with subjectively defined weighting coefficients is used for this purpose.

Issues of Research - 2 This presentation presents a comparison of such simple aggregation with a more advanced method based on achievement functions and statistically determined reference points thus related to so called objective ranking. Moreover, the paper addresses the question of a dynamic ranking – changing in time due to different speeds of advancements of information society in diverse regions or districts, together with possible forecasts of such changes based on diverse approximations of socio-economic penetration curves. These methods are applied to data of information society advancement concerning regions in Finland, Italy and Poland as well as to districts in Poland. It is shown that ranking of districts in the advancements of information society gives more insights if so called objective ranking is used, and that dynamic ranking is more useful for the development of regional policies.

Network Readiness Indicators (NRI): Structure The following indicators are assesed subjectively by experts, later simply aggregated (…): Environment 1. Market environment 2. Political and regulatory environment 3. Infrastructure environment Readiness 4. Individual readiness 5. Business readiness 6. Government readiness Usage 7. Individual usage 8. Business usage 9. Government usage Soumitra Dutta, INSEAD Irene Mia, World Economic Forum. The Global Information Technology Report 2010–2011. The Global Information Technology Report 2010–2011 is a special project within the framework of World Economic Forum’s Centre for Global Competitiveness and Performance and the Industry Partnership Programme for Information Technology and Telecommunications Industries. It is the result of a collaboration between the World Economic Forum and INSEAD.

NRI - method of aggregation NETWORK READINESS INDEX Network Readiness Index = 1/3 Environment subindex + 1/3 Readiness subindex + 1/3 Usage subindex Environment subindex Environment subindex = 1/3 Market environment + 1/3 Political and regulatory environment + 1/3 Infrastructure environment Readiness subindex Readiness subindex = 1/3 Individual readiness + 1/3 Business readiness + 1/3 Government readiness Usage subindex Usage subindex = 1/3 Individual usage + 1/3 Business usage + 1/3 Government usage The final NRI score is a simple average of the three composing subindex scores, while each subindex’s score is a simple average of those of the composing pillars. In doing this, we assume that all Index components give a similar contribution to a national network readiness index.

The Concept of Objective Ranking Introduced by Andrzej P. Wierzbicki, see: The problem of objective ranking: foundations, approaches and applications. Journal of Telecommunications and Information Technology 3/2008. Consist in: Counting overall average of a given partial indicator (such as market environment subindex); Counting the worst under-achievement among all partial indicators; Correcting slightly this worst under-achievement by the sum of under-achievements (or over-achivements) In detail, we might transform the partial indicators into partial achievement indicators (comparing them to statistical averages), then aggregate these partial achievement indicators into an overall achievement indicator determined by the worst under-achievement with slight correction by the sum. The advantage of objective ranking is that the parameters of aggregation depend on statistical averages, not on subjectively determined weighting coefficients. The objective ranking is obviously not fully objective (we choose the method of aggregation), but as objective as possible.

Here we compare the position of Poland in the world – according to NRI 2011 data: Objective ranking (red) and WEF ranking (black) Poland Ranking  WEF Objective Pillar 1 Market environment 74 68 Pillar 2 Political and regulatory environment 81 59 Pillar 3 Infrastructure environment 43 46 Pillar 4 Individual readiness 83 126 Pillar 5 Business readiness 54 42 Pillar 6 Government readiness 103 107 Pillar 7 Individual usage Pillar 8 Business usage 60 55 Pillar 9 Government usage 93 100 Subindex A Environment component 63 Subindex B Readiness component 73 112 Subindex C Usage component 57 50 NRI   62 67

NRI Objective and WEF

General comparison of Objective and WEF rankings: some countries change their positions:

Dynamic (objective) ranking using Eurostat data Three indexes of information society defvelopment were analysed in regional focus: Households with access to the Internet at home Households with broadband access Individuals regularly using the Internet The analysis concerned regions of Poland, Italy and Finland, while the method of objective ranking was used on past data and data predicted by statistically estimated sigmoidal curves.

GUS woj. Polskie Dynamic ranking of Polish voivodeships (they are smaller than European regions). The method of objective ranking was used on past Eurostat data and data predicted by statistically estimated sigmoidal curves for the years 1992 - 2024 We see that Kujawsko-Pomorskie voivodeship has large chances to become the best one, while Podlaskie voivodeship might become the last

GUS data, dynamic ranking When applied to European regions of Poland, the dynamic ranking shows more stable positions of regions, but confirms the worst position of the Eastern Region Generally, GUS data are not quite consistent with Eurostat data. However, the above examples show that dynamic ranking can give more interesting information than just static one. An alternative way to dynamic ranking is counting delay or advancement times (how many years it takes to achieve the avereage level of an indicator or of aggregated indicators).

Conclusions There are many indicators of socio-economic penetration of information society technologies, thus any evaluation of them requires multicriteria aggregation. Simple aggregation is subjective and gives less interesting results than so-called objective ranking. Much more important conclusions for regional policy can be drawn by applying dynamic ranking – a method of objective ranking usingon past data and data predicted by statistically estimated sigmoidal curves leading to a change of ranking in time. Other method of incorporating dynamic phenomena might be to compute delay or advancement times.