Internet Penetration’s Impact on Gross Domestic Product per Capita of African Countries

The internet has become an essential part of everyday life and is impacting various aspects of society. One field of interest is how internet usage affects economic growth, particularly in terms of GDP per person. This article aims at highlighting the effect of internet penetration on Africa countries gross domestic product per capita (GDP per capita). To achieve this, we used panel data for African countries over the period 1996 to 2019. The study conducted various statistical tests, such as causal effect, co-integration, and mediation tests, to identify which variables are useful in predicting GDP per capita. The findings show that the internet has a significant impact on the economy of African countries. Findings suggest that internet significantly impacts GDP per capita in African countries, whether evaluating within-effect (over time) or between-effect (across countries at a given time).  In addition, the result reveals that Secure internet servers are fundamental if a country is to rely on the internet to boost its economy. The study highlights the need to invest in internet infrastructure and increase internet penetration to promote economic growth in Africa, due to the importance of the internet in today's world. Keywords: Internet penetration, GDP per capita, Africa countries, Panel model. DOI: 10.7176/JESD/14-5-03 Publication date:March 31st 2023

Value Creation and Capture with Big Data in Smart Phones Companies

With the advent of social media, the volume of data generated on the internet has exploded due to the growing number of social network users and their interactions on the internet. Given that, in the age of the digital economy, data has become raw material in terms of decision making, it is important and urgent to conduct a study to understand the effect of big data on value creation and value capture. The goal of the current research is to study the share of big data in value creation and capture in the companies Apple and Samsung. The main question addressed by this article is whether the increasing volumes of data in the digital age can improve the creation and capture of value. To achieve this goal, we considered active users of the three main social networks that Samsung and Apple companies use for their advertising to describe “big data”. We measure the “value creation” through the hardware component of the smartphone, such as the battery, camera, CPU speed, RAM (Random-Access Memory), screen size, and storage. Profit, satisfaction, and unit of phone sold are the three manifest variables considered to measure “Value capture”. As a methodology, we used partial least squares and structural equation modeling to obtain the results. The pattern enables us to measure the effect of big data on value creation and value capture. The results indicate that CPU speed, RAMs, and battery capacity are the principal variables that impact the “value creation” in terms of customer need and satisfaction

Value Creation and Capture with Big Data in Smart Phones Companies

With the advent of social media, the volume of data generated on the internet has exploded due to the growing number of social network users and their interactions on the internet. Given that, in the age of the digital economy, data has become raw material in terms of decision making, it is important and urgent to conduct a study to understand the effect of big data on value creation and value capture. The goal of the current research is to study the share of big data in value creation and capture in the companies Apple and Samsung. The main question addressed by this article is whether the increasing volumes of data in the digital age can improve the creation and capture of value. To achieve this goal, we considered active users of the three main social networks that Samsung and Apple companies use for their advertising to describe “big data”. We measure the “value creation” through the hardware component of the smartphone, such as the battery, camera, CPU speed, RAM (Random-Access Memory), screen size, and storage. Profit, satisfaction, and unit of phone sold are the three manifest variables considered to measure “Value capture”. As a methodology, we used partial least squares and structural equation modeling to obtain the results. The pattern enables us to measure the effect of big data on value creation and value capture. The results indicate that CPU speed, RAMs, and battery capacity are the principal variables that impact the “value creation” in terms of customer need and satisfaction