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This study aims to find the key drivers of green innovation in family firms by examining firm characteristics and geographical factors. It seeks to develop a conceptual framework that explains how internal resources and external environments influence environmental innovation practices in these businesses.

Using machine learning (ML) methods, this study develops a predictive model for green innovation in family firms, drawing on data from 3,289 family businesses across 27 EU Member States and 12 additional countries. The study integrates the Resource-Based View (RBV) and Location Theory to analyze the impact of firm-level resources and geographical contexts on green innovation outcomes.

The results show that both firm-specific resources, such as size, digital capabilities, years of operation and geographical factors, like country location, significantly influence the likelihood of family firms engaging in environmental innovation. Larger, technologically advanced firms are more likely to adopt sustainable practices, and geographic location is crucial due to different regulatory environments and market conditions.

The findings reinforce the RBV by showing the importance of firm-specific resources in driving green innovation and extend Location Theory by emphasizing the role of geographic factors. The study enriches the theoretical understanding of family businesses by showing how noneconomic goals, such as socioemotional wealth and legacy preservation, influence environmental innovation strategies.

Family firms can leverage these findings to enhance their green innovation efforts by investing in technology, fostering sustainability and recognizing the impact of geographic factors. Aligning innovation strategies with both economic and noneconomic goals can help family businesses improve market positioning, comply with regulations and maintain a strong family legacy.

This research contributes a new perspective by integrating the RBV and Location Theory to explore green innovation in family firms, highlighting the interplay between internal resources and external environments. It also shows the effectiveness of machine learning methods in predicting environmental innovation, providing deeper insights than traditional statistical techniques.

Information and communication technologies (ICT) are indispensable tools for Knowledge Management (KM) practices in today’s knowledge-intensive and globally interconnected marketplace. This paper seeks to investigate the impact of family ownership on ICT investments in an emerging economy (EE) context.

This empirical paper uses data from 300 large Indian listed firms with 2,650 observations in the period 2008–2017, to test its hypothesis.

The results indicate that family firms are not favourably inclined towards ICT investments for formalizing their KM practices. However, under certain contexts, such as higher foreign institutional ownership or business group affiliation, they are more willing to invest in ICT resources.

This study establishes a nuanced understanding of how family firms approach ICT investments and KM practices. This research can help family owners/managers to commit sufficient resources on ICT projects.

Literature on KM has largely emanated from developed countries. This is one of the first papers from an EE context that studies the impact of family ownership on ICT investments and subsequent KM practices. In this way, this paper offers specific insights into the context of Indian family firms and offers some interesting findings that can contribute to the literature, policy and practice.