The Income Groups of Countries: An Approach of Management Information Systems via Networked Readiness Index

The main aim of this study is to utilize discriminant analysis to explain the relationship between the income groups, which was determined by the World Bank for 148 countries, and the Networked Readiness Index (NRI) values calculated for the same 148 countries given in the "Global Information Technology" report 2014, which is published by the World Economic Forum since 2001. In addition, it is aimed to put forward the administrative uses necessary to increase the income levels of countries through utilization of the NRI, which is a performance analysis on the use of information technologies in a country and hence is an index that comparatively measures the level of readiness of countries to use Information and Communication Technologies (ICTs), according to the findings obtained by comparing the NRI 2013 and NRI 2014 values of these countries. In this study, July 2014 World Bank Income groups (low income, lower middle income, upper middle income, high income:Non-OECD and high income:OECD) were used as the dependent variables, and 4 main Indicators of the NRI 2014 values, and 54 sub-index values were used as independent variables. The hypothesis of this study investigates whether the income groups of each country can be predicted by the components of the NRI index correctly. For this purpose, five different Fischer discriminant analyses were carried out by using the sub-indexes of the NRI both individually and in combination to calculate the extent which these components explain the income groups, and the results were presented in tables and graphs. In addition, the data analysis was supported with ANOVA, MANOVA and Post Hoc Tukey's test. The accuracy rate was found to be 94.0% in explaining the income groups of the countries when all sub-index values of the NRI were taken into account with the help of the discriminant functions which can be formed in accordance with the findings of the study. Among these groups, it explained the most of the variance in the High income:Non-OECD - High income:OECD - Low income group (100%), and the least of the variance in the Upper middle income group (88.2%). Considering the differences between the NRI 2014 and NRI 2013, the differences in the High income:OECD, high income:Non-OECD and upper middle income groups were statistically significant. The Territorial map created by the NRI 2014 values revealed that the Upper middle income group is located at the center. Besides other few methods, the NRI is a completely effective criterion for a country in this group to rise into the high income:OECD and high income:Non-OECD groups, which are the next upper economic groups. This map also helps to determine which income group rises or falls to which income groups when they increase or decrease their NRI values. And, the NRI values that converge or diverge the countries or the NRI values common among the countries in the income groups are determined with the help of a network graph created. Keywords: Global Information Technology Report, management, Networked Readiness Index (NRI), income group, Information and Communication Technologies (ICTs), discriminant analysis, big dat

How to Increase E-Commerce Incomes: A Correlation and a Cluster Analysis

Our objective in this study  to reveal the relations between  population size, e-commerce sales penetration, internet user, penetration of population with Internet, gross national income (Atlas Method), gross national income per capita, purchasing power parity gross national income, purchasing power parity gross national per income, networked readiness index and its environment,  readiness, usage, impacts indexes, global competitiveness index, logistic performance index factors and which factor(s) should be prioritized by countries in order for a country to increase its e-commerce.   In the study, e-commerce sales penetration was used as dependent variable and others were used as independent variables. Relations among variants were studied with pearson correlation analysis. According to the result of Pearson Correlation Analysis, positive strong relations were found between e-commerce sales penetration and usage, gross national income per capita, penetration of population with Internet and purchasing power parity gross national per income. Variants with effect on e-commerce were analysed by using multi linear regression analysis and e-commerce description amounts were examined in %. When these values are taken in multi linear regression model; gross national income per capita and purchasing power parity gross national income per capita were found significant in the model.  In addition, cluster analyses of 25 selected countries with different economic, social and geographic qualities with respect to these variants in order to reveal the similarity and differences of a country with other countries with respect to e-commerce structure. In cluster analyses, our analysis to differentiate one country from other countries demonstrated China and India with respect to population and e-commerce sales amounts, Norway with respect to e-trade sales penetration, Norway with respect to groups of national income per capita when divided into income groups using e-commerce sales penetration; and China and USA with respect to national income groups only. According to these results, it was found that logistic index has a lower effect than expected, that it is not sufficient merely to prepare the required infrastructure and increase number of internet users and that purchasing power should increase too and that the national income and therefore population of the country were effective. The most obvious example of that was revealed in this study as the similarities and differences between USA, China and Norway. Keywords: E-commerce, Internet user, penetration of population with Internet, Gross National Income Atlas Method, Gross national income per capita, Purchasing power parity gross national income, Purchasing power parity gross national income per capita, Networked readiness inde

The Elderly in the Digital World and Digital Inclusion of the Elderly: An Exemplary Mobile Application for the Elderly

In the modern day, technological developments are advancing exponentially, improving technology brings innovations in every corner of our lives, and with such innovations, the digital world is becoming more and more central to people’s lives. It is particularly important that the elderly also take part in this digital world, where especially young and middle-aged people are more likely to be involved. Our elders are our dearest and most respected family members whom we dote on and want to take care of with utmost attention. It is one of the noblest duties to increase their welfare, happiness, and life satisfaction by providing them with a safe, secure, and comfortable living environment. The elderly need to be actively involved in the digital world in order to benefit from the developments brought about by the digital world in a way to make their lives easier, such as maintaining social connections, following up on their health, staying healthy, making financial, banking and e-government transactions, using applications that facilitate their daily lives and remind them of important appointments or medication times. By the end of 2023, approximately 10 out of every 100 people living in the world will be elderly, and this figure is expected to increase to 12 in 2030 and 16 in 2050. Of all the applications developed in our constantly aging world; the necessity for mobile applications specifically for the elderly has also gradually increased and become more and more crucial in the world of applications. The applications to be developed for the elderly will facilitate the lives of both the elderly and those who are obliged to take care of them. The aim of this research is to contribute to the advancement of knowledge in the field of mobile application design for the elderly and to create a more inclusive and user-friendly technology for this growing user group. This article is analyzed in three parts. In the first section; the elderly population statistics of the Turkish Statistical Institute (TurkStat) for the year 2022 are studied on a detailed basis and the attributes of the elderly population aged 65 and over in Türkiye are examined by introducing a statistical overview of the subject. The second section deals with the topics about the elderly population; namely, what are the dangers ahead of the increasing elderly population, what are the challenges for families and individuals who are responsible for caring for the elderly, what are the most frequently diagnosed diseases in the elderly, what are the expectations of the elderly from their family members, what do the elderly feel most lonely about, and how should the city life be in order to facilitate the lives of the elderly. In light of the information put forth in the first part, the following topics are discussed in the second part: Why the elderly should be included in digitalization, what are the factors that increase the digital inclusion of the elderly, the obstacles to their digitalization, the dangers of their digitalization, the obstacles to the use of technology by the elderly, digital learning of the elderly, smart homes and wearable technologies. Although these issues may seem to be related to old age, they have been addressed because they are considered essential for understanding the elderly and identifying their needs for the mobile application to be developed. Finally, in the third part of the article, various applications developed for the elderly are reviewed and an exemplary mobile application for elderly is suggested. Keywords: Old Age, Elderly, Elderly in the digital world, Mobile application for the elderly DOI: 10.7176/JIEA/13-2-05 Publication date:August31st 202

New Management Approaches in Business: Learning Organization Concept

In the rapidly changing world, knowledge becomes the most important source for the organizations to survive. Therefore, organizations need to learn faster and faster to adapt to the changing environment and to take competitive advantage. As a result of industrial revolution, organizations have to face many terms due to the accelerating change in the world. This case forced either organizations or employees improve and learn continuously themselves. Learning organization is a sort of organizations which renovates itself by learning. These organizations change by learning and learn to change themselves. Learning can be at the level of individual, group or institution. The concept of Learning Organizations has become more popular recently, due to the rapidly changing environments of today. Today, learning organizations philosophy is important for the following reasons: reaching high performance, quality improvement, meeting customer expectations, gaining advantage in competition, providing energized workforce, becoming conscious about the affection of individuals each other, managing change and time's requirement. Organizations need to catch the pace of the change, and even take the advantage of this change, in order to survive in this very turbulent environment. It is even more vital to use this advantage as a tool for competition, and success. Keywords: Learning organization, organizational learning, total quailty management, organization, management, knowledge managemen

The Global Innovation Index: Insight for Turkey with time series analysis

The aim of this study is to both to discuss the realized assets with the expected values and to decide for the needs of  2015 and foretell the precautions to be taken in necessary fields by using the data related with Turkey that are given in  all indicators in  “The Global Innovation Index” which is being  published since 2007 and covers all the countries all over the world by The Business School for the World (INSEAD) that is related with innovation, the most important concept in the survival of enterprises. Innovation concept and being innovative have recently become an important concern in the fields of business and management as in every other. During the last 20 years innovation has found itself a significantly effective investigation area in various social sciences and have become the center of attraction by the executive committees. Our expectations to be derived from this study is to bring forward the innovation status of Turkey, predict for the 2015 and by informing the government, enterprises and individuals to create awareness among governors, business world, executives, information world, investors, academicians and universities and be a guide for their future plans, strategies and development of executive means and tools. In this study we are examining to forecast a time series model based on Innovation Ranks for Turkey among 132 countries in 2010, 125 countries in 2011, 141 countries in 2012, 142 countries in 2013 and 144 countries in 2014 by using the ARIMA model statistical analysis. Rank values and expected rank values for each indicator between 2010-2014 and forecasting values for 2015 and their confidence intervals have been given. The statistics of the study were performed by using SPSS 20.0 package program. The expected and realized positions of Turkey over the world in terms of each indicator have been debated and parameters strengthened, weakened or did not show development have been tried to be established. P values of the indicators in the forecasting ARIMA model and the direction of the graphics were taken into consideration and the status with respect to innovation basic indicators and sub indicators was given in a table. As a result of the study, it was determined that among the basic indicators, the human capital&research indicator (2) shows that policies are correct and it is necessary to keep the system the same way; market sophistication indicator (4) has a positive impact but needs to be supported with respect to the criteria in the sub indicators for 2015; the institutions indicator (1) and the creative outputs indicator (7) show that current policies have no use, there is no negative or positive progress and comprehensive new action plans need to be implemented; business sophistication indicator (5) shows that there may be negative progress due to wrong policies and that urgent action plans are required; infrastructure indicator (3) shows that there is negative progress due to wrong policies and urgent action plans are necessary. Keywords: Innovation, Turkey Innovation Value, Global Innovation Index, Innovative, managemen