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.

Mobile phones have entered our lives through technological developments, becoming the most commonly used technological device. In the last decade, they can now process almost every task that can be done with a computer. In particular, people who have been provided several advantages with their smart phones through an Internet connection are spending more and more time on mobile phones. Excessive use of mobile phones has become an addiction in society. The ability to access the Internet anytime on mobile phones, in addition to social applications and online games, increases Internet and mobile phone addiction. This study is based on the components model approach, developed within the scope of behavioral addictions to actualize the mobile phone addiction scale. Structural analysis was performed on this model, which proved it to be applicable as a mobile addiction scale. In the study, data from 284 participants was used, and mobile addiction was determined to relate to withdrawal, relapse, tolerance, and salience.

No abstract

No abstract

No abstract