scholarly journals Investigating the Impact of Network Effects on Content Generation: Evidence from a Large Online Student Network

2015 ◽  
Author(s):  
Prasanta Bhattacharya ◽  
Tuan Q. Phan ◽  
Xue Bai ◽  
Edoardo M. Airoldi
Keyword(s):  
Network Effects ◽  
Online Student ◽  
The Impact ◽  
Content Generation

Transformation of education as a metatrend of the digital economy

2020 ◽  
Vol 16 (10) ◽  
pp. 1960-1979
Author(s):  
N.A. Egina ◽  
E.S. Zemskova
Keyword(s):  
Human Capital ◽  
Social Transformation ◽  
Network Effects ◽  
Digital Economy ◽  
Network Education ◽  
Economic Progress ◽  
Positive Externalities ◽  
Communication Processes ◽  
Education Network ◽  
The Impact

Subject. The study focuses on the impact of the digital economy determinants of the education transformation. Objectives. The article provides our own approach treating the education capital as a specific asset of the digital economy, which has an acceleration effect and sets up new trends in education through integrative networks. Methods. The study is based on principles of the systems integration, cross-disciplinary and multidisciplinary approaches. Results. The socio-economic progress was found to be determined with properties of human capital, which are solely specific to the digital economy. In new circumstances, it gets more important for actors of global, national, corporate and social networks to more actively cooperate within distributed networks in order to train high professionals, who would have skills in information networks. Thus, they would raise a new form of human capital – the capital of network education (network-based education capital). We describe positive externalities that arise when the educational sector joins communication processes. We illustrate how educational forms evolves, which are typical of a certain phase of the socio-economic development. The education capital was discovered to grow into a specific asset generating the quasi-rent and working as a social ladder only provided more actors are involved into the network. Conclusions and Relevance. Studying the evolution of educational forms through the cross-disciplinary method, we discovered the need for a system approach, which would help substantiate its transformation in the time of the digital economy, and the emergence of network-based education. These are technologies and tools of the digital economy that become unique factors generating the acceleration effect of the educational capital and ensuring the use of diverse network effects for the formation of intellectual capital and their social transformation.

Principles for sharing economy formation in the digital society

2020 ◽  
Vol 16 (5) ◽  
pp. 800-821
Author(s):  
E.V. Popov ◽  
K.A. Semyachkov
Keyword(s):  
Network Effects ◽  
Sharing Economy ◽  
Network Effect ◽  
Industrial Society ◽  
Economic Activities ◽  
Digital Platforms ◽  
Digital Society ◽  
Modern Economy ◽  
Characteristic Features ◽  
The Impact

Subject. The article addresses economic relations that are formed in various areas of economic application of digital platforms. The target of the research is the modern economy of digital platforms across different economic activities. Objectives. The aim is to systematize principles for share economy formation in the context of the digital society development. Methods. We employ general scientific methods of research. Results. The study shows that the development of digital platforms is one of the most important trends in the development of the modern economy. We classified certain characteristic features of modern digital platforms, analyzed principles for their creation. The paper emphasizes that the network effects achieved through the use of digital platforms are an important factor in the development of the share economy. The network effect describes the impact of the number of the platform users on the value created for each of them. The paper also considers differences in the organization of traditional economy companies and companies that are based on the digital platform model, reveals specifics of changes in socio-economic systems caused by the development of digital platforms, systematizes principles of the sharing economy formation in the context of the digital society development. Conclusions. The analyzed principles for sharing economy development on the basis of digital platforms can be applied to create models for the purpose of forecasting the transformation of economic activity in the post-industrial society.

scholarly journals Pengaruh Game Online Terhadap Cara Belajar Mahasiswa Jurusan Pendidikan Teknik Mesin Universitas Negeri Manado

2022 ◽  
Vol 2 (2) ◽  
pp. 83-89
Author(s):  
Partonduhan aritonang Partonduhan aritonang ◽  
Parsaoran Tamba ◽  
Jemmy Charles Kewas
Keyword(s):  
Student Learning ◽  
Mechanical Engineering ◽  
Online Games ◽  
Learning Ability ◽  
State University ◽  
Online Student ◽  
Quantitative Descriptive ◽  
The Many ◽  
The Impact ◽  
E Mail

PENGARUH GAME ONLINE TERHADAP CARA BELAJAR MAHASISWA JURUSAN PENDIDIKAN TEKNIK MESIN UNIVERSITAS NEGERI MANADO Partonduhan Aritonang1, I. P. Tamba2, Jemmy Charles Kelas3 1,2,3Jurusan Pendidikan Teknik Mesin, Universitas Negeri Manado, Kab. Minahasa e-mail: [email protected], [email protected], [email protected]   ABSTRAK Mahasiswa Pendidikan Teknik Mesin Universitas Negeri Manado yang merupakan anak-anak perantau kini telah mendapatkan dampak yang sangat nyata dari permainan game online. Terbukti dari banyaknya mahasiswa yang ikut ambil bagian dalam permainan ini, dari hasil pengamatan peneliti selaku mahasiswa yang aktif mendapatkan banyak data bahwa mahasiswa Pendidikan Teknik Mesin Universitas Negeri Manado yang aktif bermain memiliki kemampuan cara belajar yang kurang aktif dalam pembelajaran. Penelitian ini menggunakan metode penelitian deskriptif kuantitatif. Metode pengumpulan data yang digunakan yakni kuisioner atau angket. Teknik analisi data yang digunakan dalam penelitian ini yaitu analisis statistik deskriptif, Teknik Analisis Regresi dan pengujian hipotesis.Hasil dari penelitian ini yakni : bahwa pengaruh game online (X) terhadap cara belajar mahasiswa (Y) pada taraf t hitung > t tabel dan hasil uji korelasi rxy 0849. Game online berpengaruh signifikan terhadap cara belajar. Ini dapat dibuktikan dari hasil nilai Fhitung sebesar 4.113 dan nilai signifikansi Ftabel 0.00 < 0.05. Besarnya koefisien determinasi sebesar 0.79 atau 79%. Hal ini berarti 79% pengaruh game online terhadap cara belajar mahasiswa sedangkan untuk selebihnya 21% dipengaruhi oleh variabel lain yang tidak diteliti oleh penelitian ini.   Kata kunci : Game Online, Cara Belajar Mahasiswa THE INFLUENCE OF ONLINE GAMES ON HOW STUDENTS STUDYING MECHANICAL ENGINEERING AT MANADO STATE UNIVERSITY ABSTRACT Manado university's advanced mechanical engineering student who is a migrant child has now had a very real impact on online gaming. It is evident from the many students participating in the game that researchers as active university students have received a wealth of data that students studying engineering at manado state university who actively play have a learning ability that is less active in learning. The study USES a quantitative descriptive study method. The data collection method used was "questionnaire or angket." The data analysis used in the study are descriptive statistical analysis, regression analysis and hypothetical testing. The results of this study are: that how online games affect students' learning (y) at a level of t count > t tables and rxy 0849 cordating results. Online games significantly affect how to learn. This can be verified from the results of the ftable value of 4,113 and the significance of ftable 0.00. Critical coefficiencies by 0.79 or 79%. This means 79% of the impact online games have on student learning while for the rest 21% are affected by other variables not examined by this study. Key words : Game Online, student learning

PMP-Based Optimization Method for Determining Airline Fleet Composition

2014 ◽  
Vol 505-506 ◽  
pp. 645-649
Author(s):  
Yu Wang
Keyword(s):  
Network Effects ◽  
Optimization Method ◽  
Numerical Example ◽  
Fleet Planning ◽  
Decision Variables ◽  
Proposed Model ◽  
Fleet Composition ◽  
Aircraft Type ◽  
Airline Fleet ◽  
The Impact

Traditional methods for determining airline fleet composition could not reflect the impact of network effects on fleet composition. To solve this problem for airlines operating in the mode of Hub & Spoke network, the passenger mix problem was incorporated into the model of determining airline fleet composition. The purchasing number of aircrafts in each fleet type, the frequencies of each aircraft type flying on legs and the spilling number of passengers from each itinerary were treated as decision variables. The limitations including maximum flying frequencies on each leg, available flying time each fleet type can provide and maximum passengers spilled from each flight leg were considered as constraints. A model to minimize the fleet planning cost was constructed. The numerical example shows that the fleet planning cost derived from this proposed model is 46266381.64 Yuan and reduces by 3914969.70 Yuan compared to the result from the traditional leg-based model. In hence, this proposed model is effective and feasible.

Multiple Firing Patterns in Deep Dorsal Horn Neurons of the Spinal Cord: Computational Analysis of Mechanisms and Functional Implications

2010 ◽  
Vol 104 (4) ◽  
pp. 1978-1996 ◽  
Author(s):  
Yann Le Franc ◽  
Gwendal Le Masson
Keyword(s):  
Spinal Cord ◽  
Dorsal Horn ◽  
Information Transfer ◽  
Network Effects ◽  
Neuronal Response ◽  
Sensory Information ◽  
Firing Patterns ◽  
Dorsal Horn Neurons ◽  
The Impact

Deep dorsal horn relay neurons (dDHNs) of the spinal cord are known to exhibit multiple firing patterns under the control of local metabotropic neuromodulation: tonic firing, plateau potential, and spontaneous oscillations. This work investigates the role of interactions between voltage-gated channels and the occurrence of different firing patterns and then correlates these two phenomena with their functional role in sensory information processing. We designed a conductance-based model using the NEURON software package, which successfully reproduced the classical features of plateau in dDHNs, including a wind-up of the neuronal response after repetitive stimulation. This modeling approach allowed us to systematically test the impact of conductance interactions on the firing patterns. We found that the expression of multiple firing patterns can be reproduced by changes in the balance between two currents (L-type calcium and potassium inward rectifier conductances). By investigating a possible generalization of the firing state switch, we found that the switch can also occur by varying the balance of any hyperpolarizing and depolarizing conductances. This result extends the control of the firing switch to neuromodulators or to network effects such as synaptic inhibition. We observed that the switch between the different firing patterns occurs as a continuous function in the model, revealing a particular intermediate state called the accelerating mode. To characterize the functional effect of a firing switch on information transfer, we used correlation analysis between a model of peripheral nociceptive afference and the dDHN model. The simulation results indicate that the accelerating mode was the optimal firing state for information transfer.

Integration of Multiple Regression Model in an Epidemiological Decision Support System

2019 ◽  
Vol 18 (06) ◽  
pp. 1755-1783
Author(s):  
Fatima-Zohra Younsi ◽  
Ahmed Bounnekar ◽  
Djamila Hamdadou ◽  
Omar Boussaid
Keyword(s):  
Regression Analysis ◽  
Multiple Regression ◽  
Health Care Services ◽  
Network Effects ◽  
Social Contact ◽  
Public Health Care ◽  
Human Populations ◽  
Influenza Epidemic ◽  
Mortality And Morbidity ◽  
The Impact

Prevention and control of influenza epidemics are major challenges for public health care services. Early identification of flu outbreak is an important step towards implementing effective disease interventions for reducing mortality and morbidity in human populations. Indeed, health officials need a real geo-making tool for monitoring and prediction. The aim of the current study is to discuss a novel spatiotemporal tool for monitoring and predicting the phenomenon of the seasonal influenza epidemic spread in the human population using multiple regression analysis. The suggested tool is mainly based on three sub-systems. It allows generating simulation data by the use of a simulation system, integrating data sources in a data warehouse (DW) system and performing a specific online analysis Spatial On-Line Analytical Processing (SOLAP). Our proposal enables also to illustrate evolution of disease through visualizations in time and space. It can examine social network effects to better understand the topological structure of social contact and the impact of its properties. A regression analysis is performed on the influenza epidemic to examine the main factors influencing flu incidence number and therefore to predict and track influenza epidemic.

Is RateMyProfessors.com Unbiased? A Look at the Impact of Social Modelling on Student Online Reviews of Marketing Classes

2017 ◽  
Vol 40 (3) ◽  
pp. 188-195 ◽  
Author(s):  
David Ackerman ◽  
Christina Chung
Keyword(s):  
Online Reviews ◽  
Student Ratings ◽  
Course Selection ◽  
Online Student ◽  
Potential Sources ◽  
Online Ratings ◽  
Online Rating ◽  
Social Modelling ◽  
The Impact

This article looks at how marketing student ratings of instructors and classes on online rating sites such as RateMyProfessor.com can be biased by prior student ratings of that class. Research has identified potential sources of bias of online student reviews administered by universities. Less has been done on the sources of bias inherent in a ratings site where those doing the rating can see prior ratings. To measure how student online ratings of a course can be influenced by existing online ratings, the study used five different prior ratings experiment conditions: mildly negative prior ratings, strongly negative prior ratings, mildly positive prior ratings, strongly positive prior ratings, and a control condition of no prior ratings. Results of this study suggest prior online ratings, both positive and negative, do affect subsequent online ratings and bias them. There are several implications. First, both negative and positive ratings can have an impact biasing subsequent ratings. Second, sometimes negative prior ratings must be strong in valence in order to bias subsequent ratings whereas even mildly positive ratings can have an impact. Last, this bias can potentially influence student course selection.

Promoting Regional Economic Growth in Greece by Investing in Public Infrastructure

10.1068/c9761 ◽  
2002 ◽  
Vol 20 (3) ◽  
pp. 393-419 ◽  
Author(s):  
Antonis Rovolis ◽  
Nigel Spence
Keyword(s):  
Network Effects ◽  
Development Process ◽  
Regional Scale ◽  
Private Investment ◽  
Public Capital ◽  
Positive Contribution ◽  
Social Infrastructure ◽  
Public Infrastructure ◽  
The Impact

The role of public infrastructure capital in the development process, either at national or at regional levels, was a relatively neglected area of research until recently. The innovatory work of Aschauer, and the ensuing debate between himself, Munnell, and Holtz-Eakin regarding the role of infrastructure in the development process in the USA, has spawned much interest in the issue. The authors aim to assess the impact of public capital on Greek manufacturing industries, especially focused at the regional scale. Capital stocks were estimated for the private and public sectors and Cobb—Douglas production functions were used in the analytical framework. The results suggest that the role of private capital in economic development in recent times has been marginal, as private investment has declined, whereas the role of labour and public capital has been both positive and significant. The authors segregate public capital into ‘productive’ and ‘social’ infrastructure; they argue that when productive infrastructure makes a positive contribution to production output, the impact of social infrastructure is insignificant and/or negative in most cases. The network effects of infrastructure are also estimated.

scholarly journals Network Intensity: Assessing The Strategic Value of Installed Base

1970 ◽  
Vol 28 (2) ◽  
pp. 177-195
Author(s):  
David McIntyre
Keyword(s):  
Network Effects ◽  
Application Software ◽  
Growth Effects ◽  
Strategic Value ◽  
The Impact

The purpose of this research is to explore variation in the influence of networkeffects across competitive settings. Specifically, this study tests for significantdifferences in the impact of a product’s installed base on its growth in an industryinfluenced by network effects, application software. Variation in size-on-growth effectsacross industry segments is conjectured to be a function of the network intensity,or degree of consumer interdependence, of the segments. The results illustratesignificant variation in the magnitude of size-on-growth effects across segments,consistent with the notion of network intensity. Implications for strategy in hightechnologysettings are discussed.

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