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Innovation ecosystems can emerge and grow organically, but the process can also be managed through conscious intervention. Therefore, this study observes different motivations and expectations for each group of actors. The lack of alignment between actors could have a negative influence on the development of innovation ecosystems. This study aims to analyze the coordination strategies of the actors throughout the life cycle of innovation ecosystems.

This study develops and proposes a model for coordinating innovation ecosystems based on the theoretical backgrounds of the ecosystem life cycle and ecosystem coordination.

This study argues that each stage of an innovation ecosystem’s life cycle – inception, launching, growth and maturity – demands different coordination strategies. Initially, networks are simpler and thus the coordination issues are less difficult. However, as the ecosystem evolves and the complexity of the networks increases, a more sophisticated strategy, such as orchestration or choreography, is needed.

This is a theoretical study that recommends further research to test this model.

The understanding of coordination and stages of the life cycle of an innovation ecosystem can guide actors in the design of strategies for developing of ecosystems.

The proposed framework could support strategies to engage civil society in actions to develop innovation ecosystems.

This study presents a framework to understand the coordination strategies better, considering the stages of an innovation ecosystem’s life cycle.

This study aims to investigate the synergies between the economic environment and the smart living dimension embedded in the current smart city initiatives, focusing on the localization of female entrepreneurship in contemporary cities. This interaction is under-investigated and controversial as it includes cities' practices enabling users and citizens to develop their potential and build their own lives, affecting entrepreneurial and economic outcomes. Building upon the perspective of the innovation ecosystems, this study focuses on the impact of smart living dimensions and R&D investments on the localization of female entrepreneurial activities.

The study uses a Generalized Method of Moments (GMM) and a panel dataset that considers 30 Italian smart city projects for 12 years to demonstrate the relationship between smart living practices in cities and the localization of female entrepreneurship. The complementary effect of public R&D investment is also included as a driver in the “smart” city transition.

The study found that the advancement of smart living practices in cities drives the localization of female entrepreneurship. The study highlights the empirical results, the interaction over the years and a current overview through choropleth maps. The public R&D investment also affects this relationship.

This study advances the theoretical discussion on (1) female entrepreneurial intentions, (2) smart city advancement (as a context) and (3) smart living dimension (as a driver) and offers valuable insight for governance and policymakers.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship. The findings provide valuable insights into the localization of female entrepreneurship in the context of smart cities.

This paper aims to test three hypotheses in city growth literature documenting the poverty reduction observed in Brazil and exploring a rich spatial dataset for 5,564 Brazilian cities observed between 1991 and 2010. The large sample and the author's improved econometric methods allows one to better understand and measure how important income growth is for poverty reduction, the patterns of agglomeration and population growth in all Brazilian cities.

The author identifies literature gaps and use a sizeable spatial dataset for 5,564 Brazilian cities observed in 1991, 2000 and 2010 applying instrumental variables methods. The bias-corrected accelerated bootstrap percentile interval supports the author's point estimates.

This manuscript finds that Brazilian data for cities does not support Gibrat's law, raising the scope for urban planning and associated policies. Second, economic growth on a sustainable basis is still a vital source of poverty reduction (The author estimates the poverty elasticity at four percentage points). Lastly, agglomeration effects positively affect the city's productivity, while negative externalities underlie the city's development patterns.

Data for cities in Brazil possess unique characteristics such as spatial autocorrelation and endogeneity. Applying proper methods to find more reliable answers to the above three questions is a desirable procedure that must be encouraged. As the author points out in the manuscript, dealing with endogenous regressors in regional economics is still a developing matter that regional scientists could more generally apply to many regional issues.

The purpose of this study is to analyze the relationship between dynamic service innovation capabilities (DSICs) and startup growth in an emerging country.

This paper used a theoretical DSIC model to process data on 137 Brazilian startups, using a stepwise regression.

Service startup growth is related to the capability of enterprises to understand market signals, learn from customers and design a scalable, repetitive and profitable business model.

Despite the innovative nature of startups, this paper found that technological and networking capacities are not a determinant of growth.

Managers should commit themselves to improve their competence in terms of understanding market signals, even when they already have a consolidated business model, products and service offerings. The findings also function as a warning about the dangers of an excessive focus on technological capabilities.

Innovative startups, which achieve high growth create a disproportionate number of new jobs. Hence, by indicating the dynamic capabilities that are more conducive to firm growth, this paper contributes to society and the economy at large.

The findings challenge the myth of technological capacity and networking skills as the main sources of startup growth. This paper shows that founders and managers of service startups who want to achieve rapid growth should concentrate more effort on other skills. Marketing competence and building scalable business models – abilities that are common to successful traditional firms – are more relevant for short-term growth than technological innovation.

Simulation is a well-known technique for using computers to imitate or simulate the operations of various kinds of real-world facilities or processes. The facility or process of interest is usually called a system, and to study it scientifically, we often have to make a set of assumptions about how it works. These assumptions, which usually take the form of mathematical or logical relationships, constitute a model that is used to gain some understanding of how the corresponding system behaves, and the quality of these understandings essentially depends on the credibility of given assumptions or models, known as VV&A (verification, validation and accreditation). The main purpose of this paper is to present an in-depth theoretical review and analysis for the application of VV&A in large-scale simulations.

After summarizing the VV&A of related research studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations (such as crowd network simulations).

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations (such as crowd network simulations).

This paper will help researchers to provide support of a recommendation for formulating VV&A in large-scale simulations (such as crowd network simulations).