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The study aims to examine the role of green learning orientation, green knowledge acquisition and green knowledge management in fostering corporate environmental performance of small and medium-sized enterprises (SMEs) in China. In addition, this research assesses the moderating role of chief executive officer (CEO) gender between green knowledge management and corporate environmental performance. Finally, this study examines the sequential mediating role of green knowledge acquisition and green knowledge management.

The study collected the data of 300 SMEs’ CEOs taken from five different provinces in China. The study used a partial least squares regression-based structural equation modelling technique.

The findings revealed that green learning orientation plays an important role in increasing SMEs’ corporate environmental performance. The results showed that green knowledge acquisition and green knowledge management serially and completely mediate the relationship between green learning orientation and corporate environmental performance.

To the best of the authors’ knowledge, this is the first study addressing the sequence of knowledge orientation, acquisition, management and results in terms of corporate environmental performance. Meanwhile, this study is the first to examine the indirect role of CEO gender on the relationship between green knowledge management and corporate environmental performance. As decisions are taken by the top management and CEO, especially in the case of SMEs, the role of top management and how well top management uses the knowledge acquired by the organization matters significantly.

Remote working has brought forward many challenges for employees as the phenomenon is still new for most employees across the globe. Some of these challenges may be addressed by the recent adoption of digital technologies by organizations. In this vein, our study explores the impact of digital platform capability on the creativity of employees through the mediating mechanism of explicit and tacit knowledge sharing.

The data were gathered from higher education institutes (HEIs) in a developing country, Pakistan which recently saw a major disruption during the Covid-19 pandemic. The proposed hypotheses were tested through Structural Equational Modeling (SEM) and the results confirmed our hypotheses.

The findings confirmed that the digital platform capabilities impact both tacit and explicit knowledge sharing among these remote employees. Likewise, the results also supported the mediating role of both explicit and tacit knowledge sharing on the creativity of these remote workers.

Our results are significant as they confirm the impact of digitalization on remote workers’ creativity predisposition. We thus advance the academic debate on the problems of knowledge sharing in remote working. We prove that digital capabilities outweigh the challenges created due to new forms of work driven by the pandemic. It further highlights the important areas to focus on while planning human resource policies in the new normal.

This paper aims to (1) unveil how artificial intelligence (AI) can be implemented in growth-hacking strategies; and (2) identify the challenges and enabling factors associated with AI’s implementation in these strategies.

The empirical study is based on two distinct groups of analysis units. Firstly, it involves 11 companies (identified as F1 to F11 in Table 1) that employ growth-hacking principles and use AI to support their decision-making and operations. Secondly, interviews were conducted with four businesses and entrepreneurs providing consultancy services in growth and digital strategies. This approach allowed us to gain a broader view of the phenomenon. Data analysis was performed using the Gioia methodology.

The study firstly uncovers the principal benefits and applications of AI in growth hacking, such as enhanced data analysis and user behaviour insights, sales augmentation, traffic and revenue forecasting, campaign development and optimization, and customer service enhancement through chatbots. Secondly, it reveals the challenges and catalysts in AI-driven growth hacking, highlighting the crucial roles of experimentation, creativity and data collection.

This research represents the inaugural scientific investigation into AI’s role in growth-hacking strategies. It uncovers both the challenges and facilitators of AI implementation in this domain. Practically, it offers detailed insights into the operationalization of AI across various phases and aspects of growth hacking, including product-market fit, user acquisition, virality and retention.