Network Externalities and Compatibility Among Standards: A Replicator Dynamics and Simulation Analysis

Standard wars, tied standards, and network externality induced path dependence in the ICT sector

Word-of-mouth marketing is increasingly influencing customer purchase decisions, especially with the rise of social media apps that facilitate digital marketing dynamics. While some studies have examined word-of-mouth marketing in physical networks, few have explored it in digital networks. This research tests the effects of digital-word-of-mouth under different levels of advertising intensity and fees in a newsvendor setting together with different network and cost structures. An agent-based simulation, based on the Susceptible-Infected-Recovered model, is used to simulate the spread of information through direct advertising on a digital network. This simulation helps in determining the demand generated based on the specific costs and network structures under consideration, which is then used to optimize the order quantity in the classical newsvendor problem. The results of the tested scenarios were evaluated using decision trees, the aim being to provide a decision support system. The results showed that the network structure has the largest significant impact on outcomes. In networks with a high number of connections, a marketing campaign that starts slowly typically yields higher returns than the amount spent. On the other hand, campaigns that aggressively target networks with low average degree values perform the worst.

Lack of knowledge about the true quality of alternative products (ambiguous innovations), social pressure through information bandwagon effects based on word-of-mouth, and the existence of network externalities can entail socially undesirable lock-in effects, often leading to the persistence of products in the market even if superior alternatives have become available. But can also ex ante inferior innovations win standard-battles over superior ones? We implement an agent-based computer simulation model to support our claim that a strong variance in the evaluation of the ambiguous innovations by customers can favor the diffusion of ex ante inferior innovations in the presence of local network externalities, even if there is no systematic bias in the estimation of the innovation’s true stand-alone value.

Homophily, Preferential Attachment or Triadic Closure? How the Topology of Acquaintance Networks is Determined by Processes of Link Creation

We look at the structure and evolution of an information and communication technology (ICT) global innovation network (GIN) by mapping the locations of R&D centres belonging to a group of multinational ICT enterprises. We found that the number of countries and connections have increased in a very short time, and that most of the newcomers have come from Africa, Asia and South America. We show that a country’s network position affects the creation and intensity of R&D linkages with other countries in the network. This suggests that the evolution of the ICT GIN is driven by, among other things, the preferential attachment mechanism, i.e. countries tend to connect to those countries which have more links. A country’s position in the network also moderates the effect of standard determinants of innovation i, such as geographic distance. Hence, network position explains the creation of R&D linkages between such distant countries as the US, China or India.

This study investigates the influence of homophily rooted in institutional rankings on the structure and dynamics of international research collaboration networks among Southeast Asian universities and examines its implications for regional academic stratification and inequality. Utilizing bibliometric data from 175 universities certified by the ASEAN University Network, we employed social network analysis (SNA) to map collaboration patterns using centrality metrics (eigenvector, betweenness, closeness, and degree) and clique analysis. Our findings reveal a pronounced ‘rich-get-richer’ dynamic, in which top-ranked institutions, predominantly from Malaysia and Singapore, dominate collaboration networks, controlling 75.69% of the connections. Elite universities, such as Universiti Malaya (eigenvector centrality: 0.989) and the National University of Singapore (degree centrality: 0.224), function as structural brokers, reinforcing exclusivity and marginalizing lower-ranked institutions. Conversely, despite their numerical predominance, Indonesian universities exhibit a fragmented influence, whereas those in Cambodia, Laos, and Myanmar remain peripheral with near-zero centrality metrics. Clique analysis further underscores regional fragmentation, with large collaborative clusters (≥21) dominated by Indonesian institutions, reflecting inward-oriented networks. This study identifies a stark core-periphery divide exacerbated by preferential attachment mechanisms and resource disparities that perpetuate academic inequality. These findings challenge the presumed egalitarian benefits of internationalization, highlighting how institutional ranking homophily entrenches stratification.

The Relevance of Network Structure for the Diffusion of New Products with Network Externalities: An Agent Based Simulation

There has so far been no shared understanding of validity in agent-based simulation. We here conceptualise validation as systematically substantiating the premises on which conclusions from simulation analysis for a particular modelling context are built. Given such a systematic perspective, validity of agent-based models cannot be ensured if validation is merely understood as an isolated step in the modelling process. Rather, valid conclusions from simulation analysis require context-adequate method choices at all steps of the simulation analysis including model construction, model and parameter inference, uncertainty analysis and simulation. We present a twelve-step protocol to highlight the (often hidden) premises for methodological choices and their link to the modelling context. It is designed to aid modelers in understanding their context and in choosing and documenting context-adequate and mutually consistent methods throughout the modelling process. Its purpose is to assist reviewers and the community as a whole in assessing and discussing context-adequacy.

The impact of pollution transmission networks in a transboundary pollution game

This article explores the potential of liquid democracy as a mechanism for enhancing regional governance in the context of Ukraine’s digital transformation. Combining a conceptual analysis of the model with an agent-based simulation, the study aims to examine the conditions under which flexible delegation and direct civic participation can improve responsiveness and legitimacy in public decision-making. The theoretical part outlines the institutional logic of liquid democracy, including its four core components: direct participation, flexible delegation, meta-delegation, and revocability. Special attention is paid to its relevance for local governance, where proximity, social trust, and lower informational asymmetries create favorable conditions for implementation. The agent-based simulation was developed using Python (Mesa framework) and involved 10,000 agents distributed across urban socio-geographic clusters. The model tested four scenarios: baseline, crisis, recovery, and an optimistic «epidemic-like» diffusion with digital superinfluencers. The results demonstrate that the adoption of liquid democracy tools is highly sensitive to local social influence, digital literacy, and the emergence of trust bridges between clusters. Crisis scenarios revealed strong systemic vulnerability when central «hubs» (agents with many delegated votes) are removed, while recovery depends on the timely emergence of new local leaders. The model suggests that liquid democracy is not a technologically neutral tool: its diffusion depends on behavioral logic, socio-political context, and network structures. These findings have practical implications for the design of municipal e-participation strategies and highlight the importance of fostering socially embedded digital engagement infrastructures in large urban environments. Moreover, the study underlines the need for hybrid approaches that integrate digital innovation with social capital development, ensuring more inclusive and resilient democratic practices adapted to volatile socio-political environments.

Agent-Based Simulation (ABS), an interdisciplinary area embracing both the computer science and the social science, has attracted much attention and aided the understanding of socially complex phenomena. A current important issue in this research area is how to improve ABS effectiveness and comprehension, which makes further mutual influence between the computer science and the social sciences indispensable - e.g., (1) agent modeling involving learning mechanisms in the computer science and (2) social dynamics analysis needed in the social science. Such integration of these two areas would help fulfill the great potential of ABS, first in solving complex engineering problems using agent-based technology and second in developing and testing new theories on socially complex systems. This special issue features ABS papers from both of these important areas exploring new trends in ABS. The 10 papers composing this special issue start with papers by Nobutada Fujii and Hiroyasu Inoue analyzing the relationship between the network structure and system dynamics. In these papers, an agent-based computational economics approach has been active in applying agent-based technologies to financial and economic systems. Papers by Biliana Alexandrova-Kabadjova, Isamu Okada, TomokoOhi, and Nariaki Nishino cover consumer and financial markets using agent-based models. They test economic theory and examine market phenomena for market design. Agent-based simulation is increasingly used in application fields in the social sciences. Papers by Kiyoshi Izumi, Hideki Fujii, Hiromitsu Hattori, and Shigeo Sagai propose solutions for actual social problems such as injury prevention, traffic, and electrical power. Models are created based on behavior data, and the integration of an agent-based model and real data is a hot topic in this area. As the beginning of these technical papers, this issue starts by a position paper to give an ABS overview for understanding important issues in ABS from an overall viewpoint and for understanding state-of-the-art ABS. The information presented is invaluable in helping readers grasp the important features of ABS.

We investigate how homophily in adherence to anti-epidemic measures affects the final size of epidemics in social networks. Using a modified SIR model, we divide agents into two behavioral groups-compliant and non-compliant-and introduce transmission probabilities that depend asymmetrically on the behavior of both the infected and susceptible individuals. We simulate epidemic dynamics on two types of synthetic networks with tunable inter-group connection probability: stochastic block models (SBM) and networks with triadic closure (TC) that better capture local clustering. Our main result reveals a counterintuitive effect: under conditions where compliant infected agents significantly reduce transmission, increasing the separation between groups may lead to a higher fraction of infections in the compliant population. This paradoxical outcome emerges only in networks with clustering (TC), not in SBM, suggesting that local network structure plays a crucial role. These findings highlight that increasing group separation does not always confer protection, especially when behavioral traits amplify within-group transmission.

Role of update dynamics in the collective cooperation on the spatial snowdrift games: Beyond unconditional imitation and replicator dynamics

Spreading (diffusion) of innovations is a stochastic process on social networks. When the key driving mechanism is the peer effect (word of mouth), the rate at which the aggregate adoption level increases with time depends strongly on the network structure. In many applications, however, the network structure is unknown. To estimate the aggregate adoption level as a function of time for such innovations, we show that the minimal and maximal adoption levels are attained on a homogeneous two-node network and on a homogeneous infinite complete network, respectively. Solving the Bass model on these two networks yields explicit lower and upper bounds for the expected adoption level on any network. These bounds are tight, and they also hold for the individual adoption probabilities of nodes. The gap between the lower and upper bounds increases monotonically with the ratio of the rates of internal and external influences.

Strengthening the water rights trading market is crucial for sustainable development. At present, water rights trading shows a weak marketization trend. This article analyzes the pricing strategy of a water rights trading platform in the water rights trading market, with the two-sided market theory as the core analytical framework. The Hotelling game model is used as the core analytical tool, and the article systematically analyzes the interaction mechanism between sellers and buyers on the platform. It also explores the impact of two-sided network externalities on the platform’s pricing behavior. We adopt MATLAB-based parameter analysis for numerical simulation. This simulation verifies the validity of the constructed pricing model based on the Hotelling game model. This research makes an innovative contribution by integrating the Hotelling game model with the theory of two-sided markets. The study shows that under the one-sided pricing model, the platform’s profit is positively correlated with the cross-network externality coefficient of the fee-paying party. As the intra-group network externality associated with the fee-paying party intensifies, the platform tends to reduce its optimal pricing for the fee-paying party. Furthermore, the platform’s optimal pricing strategy and core operational parameters under the two-sided fee-charging model exhibit non-monotonic relationships. Accordingly, expediting the construction of a two-sided market-oriented water rights trading platform will lay a solid foundation for implementing pricing regulation and attaining profit maximization goals. These findings provide targeted references for water resource managers and contribute to the sustainable development of China’s water rights trading market.ernality coefficient of the fee-paying party. As the intra-group network externality associated with the fee-paying party intensifies, the platform tends to reduce its optimal pricing for the fee-paying party. Furthermore, the platform’s optimal pricing strategy and core operational parameters under the two-sided fee-charging model exhibit non-monotonic relationships. Accordingly, expediting the construction of a two-sided market-oriented water rights trading platform will lay a solid foundation for implementing pricing regulation and attaining profit maximization goals. These findings provide targeted references for water resource managers and contribute to the sustainable development of China’s water rights trading market.