Publications

Generative Large Language Models have emerged as useful tools, reshaping professional workflows. However, their efficacy in inherently complex and human-centric tasks such as leadership and strategic planning remains under-explored. In this interdisciplinary study, we present a novel dataset and compare LLMs and human leaders in the context of work-place action planning, specifically focusing on translating the abstract idea of inclusion into actionable SMART goals. We developed the Leader Success Bot, a script-based chat-bot co-designed with domain experts, to guide more than 250 real-life leaders in generating inclusive workplace action plans. We systematically prompted seven state-of-the-art chat-based LLMs to perform the same task using the socio-demographic data of real-life leaders and instructions co-developed with domain experts. Our publicly released dataset enables direct comparison between human and LLM-generated workplace action plans, offering in-sights into their respective strengths, biases, and limitations. Our findings highlight critical gaps and opportunities for LLMs in leadership applications, fostering interdisciplinary collaboration and NLP applications.

Immersive platforms like the Metaverse have gained attention in information systems (IS) research, yet the diverse needs of people with disabilities (PWD) remain underexplored. This research examines the experiences of PWD using inclusive avatars that represent disabilities. Through an exploratory mixed-methods approach, combining qualitative interviews with an experience sampling study, we develop a framework informed by Affective Events Theory and voices of PWD to better understand how social interactions in the Metaverse impact PWD’s emotions and outcomes. Findings suggest that when PWD use inclusive avatars, inclusive and exclusionary social interactions shape their emotional responses, which in turn influence engagement, avatar connection and satisfaction, and perceptions of inclusion in the Metaverse. Although adopting inclusive avatars can be challenging, especially in the face of exclusionary interactions, the benefits can outweigh the costs. The role of disability identity is critical; PWD who identify strongly with their disability experience less negative emotional impact from exclusion. This research contributes to IS literature by conceptualizing the Metaverse as a relational, emotion-driven environment shaped by social interactions as well as a platform for authentic self-representation. Practical implications include supporting avatar-based disability representation, involving PWD in co-designing virtual reality technologies, and providing training to foster inclusive interactions in the Metaverse. These strategies can help organizations build more inclusive and engaging digital workplaces for an often underrepresented workforce segment.

Diversity drives innovation and creativity, directly contributing to scientific excellence. However, achieving equity in academia, including in experimental biology fields such as biomechanics and comparative physiology, remains a significant challenge, with women and other historically marginalized groups underrepresented, especially in more senior roles. When considering gender, the disparity is often linked to difficulties in balancing family responsibilities with demanding careers, along with lower ‘academic visibility’, as evidenced by fewer professional awards for women scientists. Many successful women who balance career and family keep their family lives private, making these aspects invisible to early career scholars, and thus depriving them of role models. To help close the gender gap, in this Perspective, we propose 10 actionable strategies for scholars at all career stages to promote gender diversity and inclusion through active allyship. Although we focus on gender diversity, these strategies can be broadly applied to harness the benefits of other diversity dimensions (e.g. age or ethnicity). We argue that embracing allyship benefits individual scientists, their research groups, the quality of their research, the broader research community and society at large by enhancing collective scientific output and inspiring the next generation of scientists.

Inclusion is a cornerstone of success for organizations and society, yet inclusion is not guaranteed. Building on inclusive leadership research and relational models theory, we argue that inclusion cannot manifest without systematic effort and planning by leaders. Unfortunately, few resources exist to help leaders plan and enact specific inclusion behaviors. To address this, we introduce the “Leader Success Bot,” an innovative conversational chatbot designed to help leaders develop daily inclusion action plans. Through our immersive longitudinal design and mixed methods data, we advance the taxonomy of inclusive leader behaviors and test the impact of inclusion planning on leaders and followers. We demonstrate how equality matching is an overlooked relational model that is a pivotal relational dynamic for inclusion. Across two studies, our quantitative and qualitative findings show that equitable exchanges by leaders can foster a deeper sense of belonging and community. As leaders interact with the chatbot, both leaders and followers are more likely to accomplish their goals. Additionally, followers' inclusion climate and psychological safety benefited, leading to a decrease in turnover intentions. Our findings underscore the potential of chatbots to support inclusive leadership training and development by providing leaders with a structured, scalable platform for continuous reflection and growth. This research advances theoretical understanding of relational inclusion dynamics and offers practical insights and a scalable tool for HR managers seeking to build more inclusive, psychologically safe cultures.