The Role of Quantitative and Qualitative Network Effects in B2B Platform Competition

2012 ◽  
Author(s):  
Zhiwen Li ◽  
Thierry Pénard
Keyword(s):  
Network Effects ◽  
Platform Competition

scholarly journals Global dynamics of international migration systems across South–South, North–North, and North–South flows, 1990–2015

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Diego F. Leal ◽  
Nicolas L. Harder
Keyword(s):  
International Migration ◽  
Network Effects ◽  
Global Dynamics ◽  
Core Set ◽  
Migration Dynamics ◽  
Key Drivers ◽  
Migration Flows ◽  
And Migration ◽  
Migration Systems

AbstractEvidence from 184 countries over the span of 25 years is gathered and analyzed to understand North–North, South–South, and North–South international migration flows. Conceptually, the analysis borrows from network theory and Migration Systems Theory (MST) to develop a model to characterize the structure and evolution of international migration flows. Methodologically, the Stochastic Actor-oriented Model of network dynamics is used to jointly model the three types of flows under analysis. Results show that endogenous network effects at the monadic, dyadic, and triadic levels of analysis are relevant to understand the emergence and evolution of migration flows. The findings also show that a core set of non-network covariates, suggested by MST as key drivers of migration flows, does not always explain migration dynamics in the systems under analysis in a consistent fashion; thus, suggesting the existence of important levels of heterogeneity inherent to these three types of flows. Finally, evidence related to the role of political instability and countries’ care deficits is also discussed as part of the analysis. Overall, the results highlight the importance of analyzing flows across the globe beyond typically studied migratory corridors (e.g., North–South flows) or regions (e.g., Europe).

scholarly journals The Role of Coordination Bias in Platform Competition

2016 ◽  
Vol 25 (2) ◽  
pp. 274-312 ◽  
Author(s):  
Hanna Hałaburda ◽  
Yaron Yehezkel
Keyword(s):  
Platform Competition

scholarly journals Network Effects on the Robustness of Dynamic Systems

2020 ◽  
Vol 3 (1) ◽  
pp. 115-149
Author(s):  
Ketan Savla ◽  
Jeff S. Shamma ◽  
Munther A. Dahleh
Keyword(s):  
Network Flow ◽  
Network Effects ◽  
Cascading Failure ◽  
Economic Networks ◽  
Worst Case ◽  
Linear Dynamics ◽  
Physical Constraints ◽  
Small Gain ◽  
Network Properties

We review selected results related to the robustness of networked systems in finite and asymptotically large size regimes in static and dynamical settings. In the static setting, within the framework of flow over finite networks, we discuss the effect of physical constraints on robustness to loss in link capacities. In the dynamical setting, we review several settings in which small-gain-type analysis provides tight robustness guarantees for linear dynamics over finite networks toward worst-case and stochastic disturbances. We discuss network flow dynamic settings where nonlinear techniques facilitate understanding the effect, on robustness, of constraints on capacity and information, substituting information with control action, and cascading failure. We also contrast cascading failure with a representative contagion model. For asymptotically large networks, we discuss the role of network properties in connecting microscopic shocks to emergent macroscopic fluctuations under linear dynamics as well as for economic networks at equilibrium. Through this review, we aim to achieve two objectives: to highlight selected settings in which the role of the interconnectivity structure of a network in its robustness is well understood, and to highlight a few additional settings in which existing system-theoretic tools give tight robustness guarantees and that are also appropriate avenues for future network-theoretic investigations.

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.

scholarly journals Platform Competition: A Systematic and Interdisciplinary Review of the Literature

2020 ◽  
pp. 014920632096979
Author(s):  
Joost Rietveld ◽  
Melissa A. Schilling
Keyword(s):  
Network Effects ◽  
Future Research ◽  
Review Of The Literature ◽  
Influence Strategies ◽  
Platform Competition ◽  
User Groups ◽  
Common Interests ◽  
Research Questions ◽  
Winner Takes All ◽  
Complementary Goods

Over the past three decades, platform competition—the competition between firms that facilitate transactions and govern interactions between two or more distinct user groups who are connected via an indirect network—has attracted significant interest from the fields of management and organizations, information systems, economics, and marketing. Despite common interests in research questions, methodologies, and empirical contexts by scholars from across these fields, the literature has developed mostly in isolated fashion. This article offers a systematic and interdisciplinary review of the literature on platform competition by analyzing a sample of 333 articles published between 1985 and 2019. The review contributes by (a) documenting how the literature on platform competition has evolved; (b) outlining four themes of shared scholarly interest, including how network effects generate “winner-takes-all” dynamics that influence strategies, such as pricing and quality; how network externalities and platform strategy interact with corporate-level decisions, such as vertical integration or diversification into complementary goods; how heterogeneity in the platform and its users influences platform dynamics; and how the platform “hub” orchestrates value creation and capture in the overall ecosystem; and (c) highlighting several areas for future research. The review aims to facilitate a broader understanding of the platform competition research that helps to advance our knowledge of how platforms compete to create and capture value.

scholarly journals The Role of Artificial Intelligence and Data Network Effects for Creating User Value

2020 ◽  
Author(s):  
Robert Wayne Gregory ◽  
Ola Henfridsson ◽  
Evgeny Kaganer ◽  
Harris Kyriakou
Keyword(s):  
Artificial Intelligence ◽  
Network Effects ◽  
Data Network ◽  
User Value

scholarly journals On the role of consumer expectations in markets with network effects

2011 ◽  
Vol 105 (2) ◽  
pp. 101-127 ◽  
Author(s):  
Irina Suleymanova ◽  
Christian Wey
Keyword(s):  
Network Effects ◽  
Consumer Expectations
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