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In a context where the process of creation of technology and innovation for agriculture is being disrupted at a fast pace, the authors proposed to study one of the most prominent agtech innovation ecosystems. Therefore, this paper aims to identify key characteristics that make California’s agtech innovation ecosystem remarkable.

The paper is an exploratory and descriptive research carried out in a twofold. First, data were collected through documental research focusing on actors such as universities, R&D centers and programs, business accelerators and venture capital platforms, agtechs, as well as multinational companies. Second, structured interviews were carried out to complement the secondary data collected and to obtain experts’ perception on the relationships between actors of the ecosystem and on the characteristics that make this ecosystem remarkable.

The paper provides empirical insights about the relevance of California's agtech innovation ecosystem to creation of radical innovations in agriculture. It has a differentiated environment, where educational and research institutions play a key role in developing new knowledge. It also shows how important funding is to allow new business to succeed. Additionally, it shows that actors interact in a complex network, with multiple roles. All these key characteristics allow this agtech innovation ecosystem to be so remarkable.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to survey a larger number of actors of this and other agtech innovation ecosystems to test the identified key characteristics further.

The paper includes indication of characteristics necessary to develop a prominent agtech innovation ecosystem, which may contribute to decision makers to develop policies aiming to promote this type of ecosystem.

This paper fulfils an identified need to open the “black-box” of agtech innovation ecosystems, which may then allow radical innovations within the sector to be developed and taken to the market.

This paper aims to identify and analyze the agtech classification and categorization systems in the Brazilian context.

The systematic literature review (SLR) was carried out according to the protocol of Kitchenham and Charters (2007). The classification systems found in literature were evaluated using the thinking aloud protocol, as proposed by Ericsson and Simon (1993). The responses obtained were evaluated through lexicographic analysis, described by Bécue-Bertaut (2019) and content analysis, described by Bardin (2011).

SLR identified four agtech classification systems. The model proposed by Dias, Jardim, and Sakuda (2019) was the one with the highest adherence to classify Brazilian agtechs. From the analysis of the systems found in literature, the authors proposed a new categorization model of agricultural startups (agtechs).

The study has limitations in relation to the theoretical and empirical validation of the model proposed by the authors. This limitation can be the subject of subsequent research.

The SLR study considers the evolution of the classification systems of a new agribusiness reality, the agtechs. In addition, there is a practical contribution in proposing a new classification system that attempts to address some of the limitations found in previous studies.

Agtechs are startups focused on developing solutions for agriculture and have shown a significant increase in recent years. However, there are few studies focused on this type of company. Even rarer are the studies that seek to classify and categorize them. The present work opens the horizon for future studies focused on this new reality.

The study aimsto analyze the main elements associated with the evolution of Brazilian agtechs from the initial conception of the business model to becoming companies in the scale-up stage.

The exploratory research was conducted based on data collected through in-depth interviews. The answers were analyzed quantitatively using descending hierarchical classification (DHC) and correspondence factor analysis (CFA) and qualitatively using content analysis.

Five main elements were identified as responsible for the evolution of the companies up to their entering the scale-up phase: (1) governance, (2) decisions inherent to resource allocation, (3) monitoring of strategic, tactical and operational activities, (4) fostering human capital development and (5) business model validation. Each element presents a set of performance indicators that show the scalability of these companies.

The model developed can help companies that have not yet advanced from the conception of the business model to the scalability of different sectors, in addition to agribusiness.

Proposal of a model that presents the main elements that impact on scalability and respective indicators that contributed to the scalability process of Brazilian agtechs.

This study contributed to advancing the knowledge on the organizational life cycle (OLC) of agricultural startups, particularly regarding the factors responsible for their scalability.

This paper aims to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship.

The authors used a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase data sets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship.

Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity.

The results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship.

Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements.

Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels.

Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, as it allows to identify priority areas for resource allocation.

The purpose of this paper is to investigate how new technology-based firms (NTBFs) overcome established notions of scale and scope through business model innovation, leveraging the value from digitalization.

The study adopts an exploratory research design, drawing on a novel data set of 50 publicly available interviews with vertical farming (VF) industry leaders and insiders who represent 36 different organizations from North America and Europe.

The study develops a framework showing how NTBFs leverage the value from digitalization via a paradoxical approach combining both efficiency and novelty value drivers.

The study extends current theorizing on the desirability of a combined business model approach leveraging both efficiency and novelty from digitalization. Furthermore, the study is among the first to investigate the unique and highly technological context of VF.

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.

The purpose of this article is to develop a model to assess entrepreneurial ecosystems. Specifically, the authors examine how to measure value creation and value capture mechanisms from a single participant's perspective and at the ecosystem level through a strategic value network-based approach.

Building on extant research on strategic networks, value networks and business models and leveraging a qualitative survey, the authors develop and test an assessment tool to measure value creation and capture within the entrepreneurial ecosystem of the San Francisco Bay Area.

The authors show that value-based measures on entrepreneurial ecosystems provide a systemic approach to assess how ecosystems operate, which can guide policymakers, entrepreneurs and all the other stakeholders of entrepreneurial ecosystems in their strategic decision-making process.

The authors provide an original model grounded in the strategic management and entrepreneurship literature for entrepreneurial ecosystems' assessment as few studies have done before. Besides, the authors provide an illustrative attempt to show how to empirically apply the original model by assessing the San Francisco Bay Area's entrepreneurial ecosystem.

This study aims to present the Chinese entrepreneurial environment and explore Chinese tertiary students’ online-startup motivation on live streaming platforms. Based on the COM-B behaviour changing theory, this paper discovers various influencing factors from environmental opportunity and personal capability aspects. It analyses their effects under the cooperative system established among official departments, industries and universities. Meanwhile, considering social and cultural control, it also refers to the uncertainty-avoidance dimension from the Hofstede cultural theory and re-evaluates its influence on Chinese tertiary students’ online-startup motivation.

The authors analyse 474 responses from online questionnaires through partial least squares path modelling and variance-based structural equation modelling. The paper claims that environmental opportunity and personal capability factors positively affect students’ online-startup motivation, but uncertainty-avoidance thinking plays a negative role. The study also measures the importance-performance map analysis to explore additional findings and discuss managerial implications.

Both platform support and official department support positively impact Chinese tertiary students’ online-startup motivation and entrepreneurial skills learned from universities are beneficial for them to build online-startup confidence. Meanwhile, influenced by the cooperative system implemented among official departments, industries and universities, official department support positively affects platform support and entrepreneurial skills. Conversely, influenced by Chinese traditional Confucian culture, uncertainty-avoidance thinking negatively affects tertiary students’ online-startup motivation.

This paper demonstrates the analysis of Chinese tertiary students’ online-startup motivation drawing on the COM-B behaviour changing and Hofstede cultural theories. Specifically, this study divides influencing factors into three specific aspects as follows: environmental opportunity, personal capability and social and cultural control. Unlike existing research applying traditional research models, the combination of the COM-B behaviour changing theory and the Hofstede cultural theory could be conducive to making the research model reflect influencing factors and present their different relationships.