Blockchain adoption has grown rapidly across emerging markets, particularly within financial institutions, yet the factors driving this adoption remain underexplored. This study aims to (i) identify the factors that determine blockchain adoption in emerging markets and (ii) examine how these factors influence the perceived impact of blockchain on stakeholders. Using a systematic literature review (SLR) of n = 44 articles, the analysis identifies three categories of influencing factors: (i) technological, (ii) organizational, and (iii) institutional. Technological factors include tool availability, infrastructure, system compatibility, automation, and security. Organizational factors include management support, training, culture, and resource availability. Institutional factors include government measures, competitive pressure, stakeholder trust, and market demand. The findings have practical implications for emerging-market practitioners and offer evidence-based guidance for policymakers and financial institutions seeking to support sustainable blockchain implementation in their respective contexts.

Generative artificial intelligence (GenAI) applications hold transformative potential for non-governmental organizations (NGOs) in addressing social issues. However, the integration of GenAI applications in NGOs is challenging due to the presence of several barriers. Contemporary research has not investigated barriers to GenAI adoption within the context of NGOs. Thus, this study aims to explore and prioritize these barriers to GenAI adoption in NGOs. Our study adopts a three-phase mixed methods research approach. First, GenAI adoption barriers were identified through a comprehensive review of extant literature. Second, a deductive approach was used to finalize the most relevant barriers in context of NGOs. Finally, these barriers were prioritized using a level-based weight assessment method. Results reveal fourteen barriers to GenAI adoption in NGOs. The key barriers include lack of awareness about benefits of GenAI, lack of trust in AI, inadequate training opportunities, limited digital infrastructure, and lack of technical expertise. These barriers reflect sociocultural and ethical challenges that prevent NGOs from realizing benefits of GenAI. Our study is one of the first to provide insights into GenAI adoption barriers among NGOs in India. Prioritization of these barriers provides a systematic approach to overcome them and improve NGOs’ efficiency. Findings highlight the need for a forward-thinking mindset duly supported by a bold and strategic approach to change management in order to promote the GenAI adoption in NGOs. Finally, the study contributes to limited literature on intersection of NGOs and GenAI and provides useful implications for practitioners and policymakers.

The innovation value of open government data (OGD) drives firms to the participation in OGD-driven innovation. However, to fully excavate the innovation value of OGD for firms, it is essential to explore the factors and mechanisms that affect OGD-driven innovation capacity. On the basis of the technology–organization–environment (TOE) framework, a theoretical model affecting OGD-driven innovation capacity is proposed for analysis by partial least squares structural equation modeling with 236 sample data from China. The results indicate that top leaders’ support positively impacts on OGD-driven innovation capacity in firms. And we also prove that technical competence, organizational arrangement, and innovation support partially mediate the relationship between top leaders’ support and OGD-driven innovation capacity on the basis of the TOE framework. Consequently, the findings provide new research perspectives and practical guidance for promoting OGD-driven innovation capacity in firms.