Indian School of Business

Abstract As multi-agent AI systems scale to production, the protocols connecting them constrain their capabilities. Current protocols such as Google's A2A and Anthropic's MCP omit model-level metadata, preventing quality-aware routing, efficient communication, and governance. We present the LLM Delegate Protocol (LDP), which introduces five AI-native primitives: rich delegate identity cards, progressive payload negotiation, governed sessions, structured provenance, and trust domains. We implement LDP as a plugin adapter for the JamJet agent runtime and evaluate it against A2A and random baselines. Identity-aware routing achieves 12x lower latency on easy tasks; semantic frame payloads reduce token count by 37 percent with no quality loss; governed sessions eliminate 39 percent token overhead; and noisy provenance degrades quality below the no-provenance baseline, showing that confidence metadata is harmful without verification. Trust domain and fallback analyses demonstrate architectural advantages in security and resilience. This paper contributes a protocol design, reference implementation, and initial evidence that AI-native protocol primitives enable more efficient and governable multi-agent delegation.

Thrips (Pseudodentrothrips mori) infestation is an emerging constraint in mulberry cultivation, causing subtle yet significant deterioration in leaf quality that adversely affects silkworm growth and cocoon productivity. Early detection of thrips damage using conventional field scouting is difficult due to the inconspicuous nature of initial symptoms. The present study evaluated the potential of hyperspectral radiometry for non-destructive detection and quantification of thrips-induced stress in mulberry (Morus spp.). The present study evaluated the potential of hyperspectral radiometry for detection, discrimination, and quantification of thrips-induced stress in mulberry through band sensitivity analysis, vegetation index sensitivity analysis, regression analysis and linear correlation intensity analysis. Field experiments were conducted in a V1 mulberry garden using naturally infested and protected control plots in Tamil Nadu Agricultural University, Coimbatore during 2018. Spectral reflectance data were collected using a field-portable hyperspectral spectroradiometer (350–1050 nm) at different crop stages, and vegetation indices including NDVI, Simple Ratio (SR), and GRVI were derived. Thrips infestation resulted in increased reflectance in the visible region and reduced reflectance in the near-infrared region, indicating chlorophyll degradation and internal tissue disruption. Vegetation indices were consistently lower in damaged plants compared to healthy plants, with SR and NDVI showing higher sensitivity to thrips-induced stress. Linear regression analysis revealed strong negative relationships between percent leaf damage and NDVI (R² = 0.886) and SR (R² = 0.791), whereas GRVI exhibited poor predictive capability. Linear correlation intensity analysis identified diagnostically important wavelengths, with the highest positive correlation observed at 689.45 nm (r = 0.94) in the red region and the strongest negative correlation at 763.26 nm (r = −0.10) in the NIR region. Overall, the study demonstrates that hyperspectral radiometry combined with correlation intensity analysis and vegetation indices provides a robust, non-invasive approach for early detection and assessment of thrips damage in mulberry, supporting precision pest management in sericulture systems.

Mulberry (Morus spp.) serves as the primary food source for silkworms (Bombyx mori L.). Sucking pests form a major group of destructive fauna affecting mulberry crops. Among these, sap-sucking pests are the most destructive, causing greater losses to mulberry compared to other pest groups. Early identification of pest damage is essential for selecting effective control methods, thereby reducing production costs and minimising crop losses. In contrast, modern techniques such as remote sensing enable rapid and efficient detection over large areas. The study aims to perform spectral analysis of spiralling whitefly-damaged Mulberry plants using hyperspectral radiometry. A randomised block design was employed to analyse the vegetative indices, namely RVI, NDVI, and GRVI, with means compared using the Least Significant Difference method. Furthermore, linear regression models were constructed to assess the relationship between the percentage of damage and each of the vegetation indices. Linear correlation intensity analysis was conducted to identify the wavelengths with the highest positive and negative correlation with spiralling white fly damage. Hyperspectral radiometry, which analyses plant spectral reflectance, is particularly effective in assessing pest-induced stress. In the experiments, the mulberry variety V1, known for its different crop duration and susceptibility to insect pests, was chosen. The damage caused by spiralling whitefly (Aleurodicus disperses) was studied. The percentage of damage was recorded in both healthy and infested plots at 15-day intervals during the active damage stage. Spectral reflectance across various bands was also recorded using a hyperspectral radiometer. Sensitivity analysis of spectral bands and vegetation indices (VIs) was carried out. Different analyses, including correlation and regression of pest damage with VIs, and correlation intensity curve analysis, were conducted in order to detect and discriminate individual pest damage and to estimate the extent of damage caused by this pest. These studies were carried out at the mulberry garden of the Department of Sericulture, Tamil Nadu Agricultural University (TNAU), Coimbatore, during 2018. The results revealed that the spectral reflectance curves of mulberry plants damaged by spiralling whitefly differed from those of healthy plants. In general, damaged plants showed a decrease in near-infrared (NIR) reflectance (770–860 nm), along with an increase in green (520–590 nm) and red reflectance (620–680 nm). The mean values of NDVI, GRVI, and RVI for damaged plants were significantly lower than those of healthy plants. For spiralling whitefly damage, the red band was found to be more sensitive than other bands. Among the vegetation indices, GRVI was most sensitive to spiralling whitefly damage. A significant negative correlation was observed between spiralling whitefly damage and NDVI and GRVI across all observations. The R² values of RVI, NDVI, and GRVI with spiralling whitefly damage were significant, indicating the capability of these indices to estimate damage. To further quantify damage, linear regression equations were developed based on spectral indices. Correlation analysis revealed the highest positive correlation (r = 0.62) in the NIR band at 743 nm, while the least negative correlation (r = –0.40) occurred in the red band at 676.75 nm. The combined use of red-band reflectance and GRVI provides a reliable, non-destructive tool for early detection and monitoring, enabling timely pest management in sericulture.

This study moves beyond the traditional atomistic view of firms engaged in alliance agreements. By integrating current research on internal organizational design with research on interfirm collaboration, we investigate the implications of the organizational design of parent firms for the design and governance of technology partnerships. More specifically, we propose that in a research and development (R&D) alliance between a client firm and an R&D firm, the client firm’s internal organizational structure in R&D plays an important role in alliance design and governance. Centralized firms are better able to integrate knowledge in the organization compared with decentralized firms, and hence, we theorize that they will design their technology partnerships for greater knowledge access. Empirical findings from alliances in the biopharmaceutical industry offer support for our predictions: firms with centralized R&D decision making are more likely to capture intellectual property rights. Further, these firms tend to engage in alliances with broader vertical and horizontal scope and greater technological interdependence in order to access, recombine, and distribute knowledge. This study extends research on alliance design and governance by underscoring the important influence of a partner firm’s organizational structure.

Abstract This chapter examines the contextuality characterizing entrepreneurial marketing in adopting specific marketing techniques to overcome South Asian cultural, economic and technological barriers. The South Asian region, with its unique and diverse culture and rapidly progressing start-up environment, offers challenges and benefits for aspiring start-ups. The roles of entrepreneurship marketing are highlighted in this chapter as a tool central to creating sustainable businesses in environments of resource scarcity and competition. A discussion of the synergies of ‘conventional’ and emerging forms of marketing explores how a company uses technology and social media to increase the breadth of its market and communicate with its consumers. In this chapter, the authors use cases and research findings to emphasize promoting sustainable and socially responsible entrepreneurship marketing in South Asia. Finally, this chapter offers valuable information for academicians, especially scholars, who are inclined to comprehend the research agenda and opportunities and threats of South Asian entrepreneurship marketing within the context of entrepreneurship in emerging economies.

Even though research on organizational resilience has advanced significantly, it often overlooks the varying resilience of different organizational forms in response to external shocks. To address this gap, we analyse resilience heterogeneity of family-owned, family- managed businesses and their counterparts in the context of a global crisis event. Grounded in stewardship theory and leveraging the socioemotional wealth perspective, we operationalize organizational resilience by examining deviations in firm performance relative to counterfactual performance across three critical phases: the “steady state” pre-shock, post-shock, and shock periods. We posit that family ownership and management act as key enablers of organizational resilience. Using a proprietary longitudinal dataset of 2,202 listed companies in India, we find robust evidence that both family ownership and family management significantly enhance organizational resilience. However, our analysis reveals that the positive impact of family management on organizational resilience diminishes in the presence of business group affiliation. Furthermore, we categorize firms into four cohorts based on performance trajectories – antifragile, robust, scarred, and fragile – and assess how family involvement influences resilience within each group. Finally, our study has policy implications, by highlighting the resilience and importance of providing support to family enterprises, given their ubiquity and economic importance, as they play a critical role in economic stability.