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Purpose The literature on entrepreneurial ecosystems is fragmented, and yet, no studies have paid attention to integrating the available studies. The purpose of this study is to provide a systematic review of contributions related to entrepreneurial ecosystems. Design/methodology/approach This literature review evaluates studies that are covered in the Web of Science index. Findings In addition to the recent state of research (covering industries, geographical scopes, methodologies, etc.), this study provides an extension of Isenberg’s (2011) model of entrepreneurial ecosystems. Research limitations/implications A new avenue arises for both conceptual and empirical research by emphasizing crowdsourcing as a contributing element for the entrepreneurial ecosystem. Future studies can evaluate the effectiveness of different types of crowdsourcing profoundly to make sure whether creating a promising ecosystem all types of crowdsourcing have a similar value or impact. Practical implications For public policy and local decision-makers, both collaboration opportunities and interaction interfaces between the stakeholders of the entrepreneurial need to be reconsidered in the design of entrepreneurial ecosystems. Social implications Higher degrees of collaboration, information exchange and innovation are likely to yield favorable entrepreneurship environments. Originality/value Novelty of this study arises from integrating crowdsourcing theory in the systematic review of entrepreneurial ecosystems.

Purpose Big data analytics (BDA) is recognized as a turning point for firms to improve their performance. Although small- and medium-sized enterprises (SMEs) are crucial for every economy, they are lagging far behind in the usage of BDA. This study aims to provide a single and unified model for the adoption of BDA among SMEs with the integration of the technology–organization–environment (TOE) model and resource-based view. Design/methodology/approach A survey of 112 manufacturing SMEs in Iran was conducted, and the data were analysed using structural equation modelling to test the model of this study. Findings The results offer evidence of a BDA mediation effect in the relationship between technological, organizational and environmental contexts, and SMEs performance. The findings also demonstrated that technological and organizational elements are the more significant determinants of BDA adoption in the context of SMEs. In addition, the result of this study confirmed that BDA adoption could enhance the financial and market performance of SMEs. Practical implications Providing a single unified framework of BDA adoption for SMEs enables them to appreciate the importance of most influential elements (technology, organization and environment) in the adoption of BDA. Also, this study may encourage SMEs to be more willing to use BDA in their businesses. Originality/value Although there are studies on BDA adoption and firm performance among large companies, there is a lack of empirical research on SMEs, in particular, based on the TOE model. SMEs differ from large companies in terms of the availability of resources and size. Therefore, this study aimed to initiate a conceptual framework of BDA adoption for SMEs to assist them to be able to take advantage of the adoption of such technology.

The literature on big data analytics and firm performance is still fragmented and lacking in attempts to integrate the current studies’ results. This study aims to provide a systematic review of contributions related to big data analytics and firm performance. The authors assess papers listed in the Web of Science index. This study identifies the factors that may influence the adoption of big data analytics in various parts of an organization and categorizes the diverse types of performance that big data analytics can address. Directions for future research are developed from the results. This systematic review proposes to create avenues for both conceptual and empirical research streams by emphasizing the importance of big data analytics in improving firm performance. In addition, this review offers both scholars and practitioners an increased understanding of the link between big data analytics and firm performance.

PurposeThe study challenges the assumption of independence among Technological, Organizational and Environmental (TOE) factors and investigates the influence of TOE factors on Big Data Analytics (BDA) adoption among Small and Medium Enterprises (SMEs). Top management support was proposed as a mediator between technological and organizational factors and BDA adoption. Furthermore, the moderating effect of environmental factors on the association between relative advantage, compatibility, competitiveness, organizational readiness and BDA adoption was evaluated.Design/methodology/approachData were collected from 171 SME manufacturing firms and analyzed using the partial least squares technique.FindingsThe findings confirmed the interrelationships among the TOE factors. The effects of compatibility, competitiveness and organizational readiness on BDA adoption were mediated by top management support. Furthermore, environmental factors moderate the influences of compatibility and organizational readiness on top management support.Originality/valueThe findings contribute to the TOE model by challenging the assumption of independence among TOE factors, and future studies should use this model with more caution and consider the potential relationships between TOE factors.

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