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The purpose of this paper is to develop a holistic understanding for the shaping of resilient service ecosystems that considers tactics that act as stabilizing forces, and tactics that promote diversity and change and act as destabilizing forces – both central for service ecosystems to bounce forward in times of crises and beyond.

This conceptual paper draws on theory on complex adaptive service ecosystems and work on organizational resilience and resilient systems. With a focus on Australia and New Zealand, stalwarts of the top three economies in Bloomberg’s COVID Resilience Ranking before the arrival of the Delta variant, this study illustrates how resilient service ecosystems can be shaped.

This study explicates complexity related to navigating service ecosystems toward a new order in response to the pressures of major crises. It points to the importance of understanding both, how service ecosystems stabilize and change over time. It documents a portfolio of tactics that service organizations can use to influence resilience in the service ecosystems of which they are part. It further reflects on the potential downside of resilient service ecosystems, as they tilt toward rigid structures, failure to learn and an inability to transform or alternatively chaos.

Service research has made progress in explicating how a service ecosystems perspective can inform crises management. This paper extends this work and explains how service ecosystems can be shaped to bounce not only back from the imposed pressures of a disruptive event but also forward toward a new order.

The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics.

A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model.

The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods.

This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.

Do business owners hold capitalist beliefs – relative to non-business owners? Using Latinobarómetro survey in Latin America, we find that business owners tend to see the market economy as the only system by which a country can become developed. They also tend to give a lower rank to Fidel Castro, and tend to believe that sole private investment in sectors like hospitals and pensions are good for the country to develop as soon as possible. But, business owners do not see foreign capital as good in industries such as mining, electronics, household appliances, automobile, telecommunication services, and infrastructure. They also do not see foreign investment as beneficial for economic development of the country. In addition, they are less willing to adopt some new technologies.