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This research employed two neurophysiological techniques (electroencephalograms (EEG) and galvanic skin response (GSR)) and machine learning algorithms to capture and analyze relationship-oriented leadership (ROL) and task-oriented leadership (TOL). By grounding the study in the theoretical perspectives of transformational leadership and embodied leadership, the study draws connections to the human body's role in activating ROL and TOL styles.

EEG and GSR signals were recorded during resting state and event-related brain activity for 52 study participants. Both leadership styles were assessed independently using a standard questionnaire, and brain activity was captured by presenting subjects with emotional stimuli.

ROL revealed differences in EEG baseline over the frontal lobes during emotional stimuli, but no differences were found in GSR signals. TOL style, on the other hand, did not present significant differences in either EEG or GSR responses, as no biomarkers showed differences. Hence, it was concluded that EEG measures were better at recognizing brain activity associated with ROL than TOL. EEG signals were also strongest when individuals were presented with stimuli containing positive (specifically, happy) emotional content. A subsequent machine learning model developed using EEG and GSR data to recognize high/low levels of ROL and TOL predicted ROL with 81% accuracy.

The current research integrates psychophysiological techniques like EEG with machine learning to capture and analyze study variables. In doing so, the study addresses biases associated with self-reported surveys that are conventionally used in management research. This rigorous and interdisciplinary research advances leadership literature by striking a balance between neurological data and the theoretical underpinnings of transformational and embodied leadership.

In the past decade, intellectual capital (IC) measurement and reporting have been feeding scientific debate; however, only few studies address these issues together. The present research aims to provide an integrated view of the topics covered by the existing literature and to highlight the emerging research trends and set the agenda for future research.

This study develops a structured literature review (SLR) of the extant research concerned with IC measurement and reporting, using a comprehensive sample of 1,021 articles extracted from the Scopus database.

The findings of the SLR show that the existing literature focuses on seven research areas: IC and public sector; IC university and education; IC evaluation method; internal and external IC disclosure; IC and CSR; management of IC in organizations; other. Overall, findings indicate that IC measurement and reporting are highly researched topics that continue to attract the interests of scholars. Finally, the SLR analysis has allowed outlining a future research agenda, with particular reference to the IC evaluation method and internal and external IC disclosure research areas.

The main limitation of this research lies in the manual screening of relevant studies, which entails some degree of subjectivity. Furthermore, another limitation research could be considered the use of a single database (Scopus).

The present study brings potential contributions for scholars and practitioners. From a scholarly perspective, the paper provides a systematization of scientific contributions that have dealt with IC measurement and reporting. In particular, it contributes to the scholarly debate bringing into focus various IC measurement and reporting issues in the landscape of private and public organizations. Referring to practical implications, our research supports the strategic use of IC measurement and reporting as a key lever for improving the management of firms. Using an analytical framework that combines insights from the agency, stakeholder and legitimacy theories, this study highlights that IC reporting activity should be used strategically as a means to engage with all firm's stakeholders, in particular with a view to reducing information asymmetry and improving firm reputation.