Purpose: The 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/approach: Data were collected from 171 SME manufacturing firms and analyzed using the partial least squares technique.Findings: The 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/value: The 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.

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.

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.

Background: Recent data from several studies and surveys confirm that our society has entered the digital transformation era. The crucial role of this digital trend is becoming increasingly more evident during the COVID-19 pandemic. Hence, a bunch of technologies, such as artificial intelligence, have the potential to change the present enhancing people’s power to act, to live and to promote equal citizen participation. In this scenario, Smart Cities with its smart technology innovative components are challenging for excluded people. Method: The general objective of this article is to identify and understand the dimensions that must be taken into account to promote the digital participation/inclusion of people with ID. The model is based on a qualitative analysis of people’s perceptions related to how Smart Cities can promote social Inclusion. Results: The challenges associated with social inclusion were identified in the social, economic and political as well as cultural dimensions of the countries investigated: Italy and Malaysia. The results constitute a first step to shape and understand how smart cities can promote social inclusion in different contexts. Conclusion: The outcomes of our research suggest that, starting from standard technologies, smart cities in different countries need tailored solutions. The results reveal that the Smart City strategy is, in general, and in terms of social Inclusion, in particular, a local phenomenon changing in each country. This outcome has important implications for practitioners and future scholarly research alike. The current study contributes to both social inclusion and smart city literature in many ways.