Collective Intelligence Under a Volatile Task Environment: a Behavioral Experiment Using Social Networks and Computer Simulations

Collective intelligence in our highly-connected world is a topic of interdisciplinary interest. Previous research has demonstrated that social network structures can affect collective intelligence, but the potential network impact is unknown when the task environment is volatile (i.e., optimal behavioral options can change over time), a common situation in modern societies. Here, we report a laboratory experiment in which a total of 250 participants performed a “restless” two-armed bandit task either alone, or collectively in a centralized or decentralized network. Although both network conditions outperformed the solo condition, no sizable performance difference was detected between the centralized and decentralized networks. To understand the absence of network effects, we analyzed participants’ behavior parametrically using an individual choice model. We then conducted exhaustive agent-based simulations to examine how different choice strategies may underlie collective performance in centralized or decentralized networks under volatile or stationary task environments. We found that, compared to the stationary environment, the difference in network structure had a much weaker impact on collective performance under the volatile environment across broad parametric variations. These results suggest that structural impacts of networks on collective intelligence may be constrained by the degree of environmental volatility.

Unpacking Transnational Social Capital and its Effects: Insights from an International Study Experience in Belgium

This paper studies (trans)national social capital gained through an international study experience in Belgium. Drawing upon a multi-method alumni study, we explore different types of (inter)national networks of male and female graduates, the extent to which different networks remained after graduation as well as effects on personal and professional development and organizational performance. Findings show that graduates have particularly gained networks with non-co-nationals which evolve from bridging relations at the outset to bonding relations while particularly networks with the host population remain limited. After returning home, bonding social interaction relations remain most important, irrespective of the nationality of the graduates, whereas information sharing and collaboration networks survive better among co-nationals, particularly when these are triggered through national alumni chapters. Our study finds network effects on individual's intercultural skills, knowledge and attitudes, their professional career and organizational performance, with intercultural gains being particularly high for networks with non-co-nationals from other continents.

Digital Platforms for the Common Good: Social Innovation for Active Citizenship and ESG

The platform business model has attracted significant attention in business research and practice. However, much of the existing literature studies commercial platforms that seek to maximize profit. In contrast, we focus on a platform for volunteers that aims to maximize social impact. This business model is called a platform for the common good. The article proposes a Causal Loop Diagram (CLD) model that explains how a platform for the common good creates value. Our model maps the key strategic feedback loops that constitute the core structure of the platform and explains its growth and performance through time. We show that multiple types of network effects create interlocking, reinforcing feedback loops. Overall, the article contributes towards a dynamic theory of the platforms for the common good. Moreover, the article provides insights for social entrepreneurs who seek to build, understand, and optimize platforms that maximize social value and managers of companies that seek to participate in such platforms. Social entrepreneurs should seek to leverage the critical feedback loops of their platform.

Complex climate and network effects on internal migration in South Africa revealed by a network model

Climate variability and climate change influence human migration both directly and indirectly through a variety of channels that are controlled by individual and household socioeconomic, cultural, and psychological processes as well as public policies and network effects. Characterizing and predicting migration flows are thus extremely complex and challenging. Among the quantitative methods available for predicting such flows is the widely used gravity model that ignores the network autocorrelation among flows and thus may lead to biased estimation of the climate effects of interest. In this study, we use a network model, the additive and multiplicative effects model for network (AMEN), to investigate the effects of climate variability, migrant networks, and their interactions on South African internal migration. Our results indicate that prior migrant networks have a significant influence on migration and can modify the association between climate variability and migration flows. We also reveal an otherwise obscure difference in responses to these effects between migrants moving to urban and non-urban destinations. With different metrics, we discover diverse drought effects on these migrants; for example, the negative standardized precipitation index (SPI) with a timescale of 12 months affects the non-urban-oriented migrants’ destination choices more than the rainy season rainfall deficit or soil moisture do. Moreover, we find that socioeconomic factors such as the unemployment rate are more significant to urban-oriented migrants, while some unobserved factors, possibly including the abolition of apartheid policies, appear to be more important to non-urban-oriented migrants.

Payment Systems as a Driver for Platform Growth in E-Commerce

This chapter visits some of the fundamental concepts from platform economics, network effects, and network externalities. Further on, it discusses definitions of two-sided and multi-sided markets, how they are treated as business models. These concepts are further compared to the concept service ecosystem. A case of a payment service provider whose business model contributes to the growth of e-commerce is included. The purpose is to tease out how research on platforms has developed since e-commerce was in its infancy. The fundamental concepts developed in network economics are still valid and have been translated into different fields with a focus on value creation, information, and interaction. How platforms within platforms spur each other's growth is an area that has the potential to reach new insights on the platform economy.

Transforming Competitiveness by Introducing Digital Platforms

The purpose of the proposed paper is to study the specific factors shaping the benefits of information platforms as an innovative institutional form and model of doing business. Active dissemination of the business model of online platforms radically transforms the competitive landscape of the market environment. The task of determining the sources and mechanisms for studying the changes that are taking place is being updated. New areas of competition include competition between hierarchical and network structures, between global «structuring» platforms, competition in dominant platform ecosystems, the interaction between platforms operating in competitive markets, competition between organizers and users, and between platform users. The impact of platforming on cross-industry, regional and international competition is determined. The sources of competitive advantages of platforms are investigated. These include reliance on data as the main factor of production, changing the cost structure of entering the market; the possibility of building large-scale networks, niche specialization, combining the effects of increasing the scale of production and demand, multihoming, multi productivity, network effects.