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Drawing on signalling and impression management theories, this study aims to examine a bidirectional association between managerial tone in earnings conference calls and financial performance.

The sample includes non-financial firms listed in the FTSE 350 index during the period 2010–2015. Managerial tone was measured using positive and negative keywords based on the Loughran-McDonald Sentiment Word Lists, while return on assets was used as a proxy for firms’ financial performance.

The findings indicate that current financial performance positively affects the managerial tone in earnings conference calls. Likewise, the results also show that there is a positive relationship between managerial tone in earnings conference calls and firms’ future financial performance.

The results have important implications for top management to use more virtual communication media (i.e. earnings conference calls) to continue managing their relationships with financial stakeholders and helping them better understand financial performance, especially in countries where holding such calls is not yet part of firms’ policy.

To the best of the authors’ knowledge, this is one of the first studies that explore the relationship between managerial tone in earnings conference calls and financial performance. Overall, this study contributes to managerial tone literature and holds significant theoretical and practical implications.

India’s rapid economic growth has triggered a significant transformation in its logistics sector, fueled by comprehensive reforms and digital initiatives outlined in the National Logistics Policy. Smart warehouses, equipped with cutting-edge technologies such as IoT, AI and automation, have taken center stage in this evolution. They play a pivotal role in India’s digital journey, revolutionizing supply chains, reducing costs and boosting productivity. This AI-driven transformation, in alignment with the “Digital India” campaign, positions India as a global logistics leader poised for success in the industry 4.0 era. In this context, this study highlights the significance of smart warehouses and their enablers in the broader context of supply chain and logistics.

This paper utilized the ISM technique to suggest a multi-tiered model for smart warehouse ecosystem enablers in India. Enablers are also graphically categorized by their influence and dependence via MICMAC analysis.

The study not only identifies the 17 key enablers fostering a viable ecosystem for smart warehouses in India but also categorizes them as linkage, autonomous, dependent and independent enablers.

This research provides valuable insights for practitioners aiming to enhance technological infrastructure, reduce costs, minimize wastage and enhance productivity. Moreover, it addresses critical academic and research gaps contributing to the advancement of knowledge in this domain, thus paving the way forward for more research and learning in the field of smart warehouses.

The qualitative modeling is done by collecting experts' opinions using the ISM technique solicits substantial value to this research.