Measurement of the Intersectoral Digital Divide with the Gini Coefficients: Case Study Turkey and Lithuania

Abstract

The digital divide, which arises from the usage differences of the information systems and appears as a new inequality is a concept which affects negatively the business processes. This concept which is in general scrutinized personally, regionally and globally and which is neglected by the sectors and the enterprises is one of the major factors affecting the sectoral and economic structure. Thus, determining the inequality level which results from the intensifying digital divide along with developing technology gains importance. In general the computer and internet usage rates are used as indexes for determination of the digital divide levels and the analyses are carried out with statistical methods according to the demographic variables. Gini method, one of the standard tools of inequality measurement, is rarely encountered in the digital divide studies. The purpose of this study is to determine the intersectoral digital divide by Gini method. The usage differences of the Turkish and Lithuanian sectoral information systems were analyzed in order to determine the digital divide by Gini method. The data was obtained from the reports published by Tuik and Eurostat between 2010 and 2013 based on the studies of the usage of the information systems by the enterprises. Gini values, which show the sectoral digital divide, were calculated using the data regarding the computer, internet, social media usages, having web page and selling over web which belong to the sectors classified according to the Nace Rev.2 system. The analysis revealed that both Turkey and Lithuania have low levels of sectoral digital divide. The highest level of digital divide was observed in the case of the selling over web and an increasing trend of the sectoral differences has been identified. Although Lithuania had high rates of information systems usage, it has been determined that the intersectoral differences are more than those in Turkey, in terms of usage of the information systems.

Optimization of Gini Coefficient Affected by Imperfect Input Data

“…Evidence for this for instance derives from the measurements of the intersectoral digital divide, which result from differences in the use of information systems (Fidan, 2016). Therefore, to insure that the results reflect the real state of affairs and not just the optimal situation based on optimal input data, the form of the Gini coefficient and Lorenz curve must be defined as precisely as possible.…”

Participation in heritage crowdsourcing

“…Gini coefficient and Lorenz curve are measures of inequality, frequently applied in the social sciences and especially in economics (e.g. Fidan, 2016;Brown, 2017);…”

Türkiye Bölgesel Sayısal Bölünme Düzeylerinin Belirlenmesinde Gini Yaklaşımı

“…Bu araştırmalarda ICT Development Index (IDI), Digital Evolution Index (DEI) ve Networked Readiness Index (NRI) gibi indeksler kullanılmaktadır. Bu indekslerde bilgisayar, internet ve mobil telefon sahiplilikleri parametre olarak yer almaktadır (Fidan, 2016).…”

“…Çalışmada, BİT sahiplilik yüzdelerinin Litvanya'da yüksek olmasına karşın, sektörler arası sayısal bölünmenin Türkiye'ye nazaran daha yüksek olduğu tespit edilmiştir. Bu bağlamda çalışmada, sayısal bölünme düzeyini belirlemek için kullanılan IDI ve NRI gibi indekslerin sayısal bölünme ile ilgili gerçek durumu yansıtmadığı kanıtlanmıştır (Fidan, 2016).…”

“…Uluslararası kuruluşlar ise farklı BİT göstergelerinin bileşiminden oluşan indeksler kullanmaktadırlar. Sayısal bölünme düzeylerinin ölçülmesinde bileşik ve ayrık olmak üzere iki yaklaşımın kullanıldığını vurgulayan Fidan, her iki yöntemin de sayısal bölünme düzeyini belirlenmesinde yetersizlikleri olduğunu ileri sürmektedir (Fidan, 2016). Corrocher ve Ordanini'ye göre BİT kullanımında sadece durum tespiti gerçekleştiren bu indeksler, sayısal bölünmenin ölçülmesine uzak yaklaşımlardır (Corrocher ve Ordanini, 2002).…”