Vindhya Singh

Vindhya Singh

PhD Candidate at IMPRS-IS and University of Stuttgart

Posts by Collection

portfolio

publications

Beyond and Behind Platforms and Algorithms: Exploring the Lived Experiences of Gig Workers

Published in Academy of Management Proceedings, 2024

Recommended citation: Vindhya Singh, Aizhan Tursunbayeva, Ksenia Keplinger, and Stefano Di Lauro. 2024. Beyond and Behind Platforms and Algorithms: Exploring the Lived Experiences of Gig Workers. In Academy of Management Proceedings (2024-08). Academy of Management, Chicago, USA, 14769. doi:10.5465/AMPROC.2024.14769symposium.

Gig work in organizations: Demystifying the perspectives of Human Resource Management professionals

Published in itAIS Conference, 2024

The gig economy has expanded beyond platform-based work and is also transforming standard organizations that are accustomed to stable employment arrangements and long-term-oriented HRM practices. The shift towards gig workers and blended teams disrupts standard HR practices due to the short-term, transactional nature of gig work. This research investigates the implications of gig work on HRM practices in standard organizations. Specifically, we 1) examine the trends and perspectives of HR professionals on the use of gig work in standard organizations, 2) investigate whether HR professionals apply standard HRM practices for gig workers, and 3) conduct a longitudinal analysis of HRM perspectives applicable to gig workers before and post-COVID-19 pandemic. To achieve these research objectives, we employ natural language processing techniques to analyze more than 500 YouTube videos of HR professionals offering their opinions about gig work. The findings suggest that despite the widely conceived notion that gig workers are ‘self-managed’, various HRM practices are utilized in the context of gig work.

Recommended citation: Singh V, Tursunbayeva A, Keplinger K, Di Lauro S (2024) Gig work in organizations: Demystifying the perspectives of Human Resource Management professionals. Proceedings of Conference of the itAIS 2024 (Piacenza, Italy).

Chatbot-Induced Workplace Intervention for Team Inclusion by Leveraging Natural Language Processing Techniques

Published in itAIS Conference, 2025

Emerging technologies like chatbots are employed across multiple domains to support both external and internal stakeholders and impact organizational cultures. In our research, we explore how a chatbot designed for leadership training facilitates actionable insights on inclusion, a core challenge in digital transformation, translating abstract concepts into tangible practices. We designed a chatbot to guide leaders in practicing inclusive behaviors, then tested it with real-world leaders. Using Natural Language Processing (NLP) methods on responses from leaders who interacted with the chatbot, we uncover multi-level discourse on inclusion and examine how these exchanges shape team inclusion climate and, by extension, impact organizational culture, providing data-driven insights into whether and how technology can foster inclusion in teams. Our findings contribute to the growing research by investigating whether “digital” tools like chatbots enable transformative change. Additionally, we redefine the “user” as an active participant in co-creating inclusive cultures. Furthermore, by guiding leaders through structured interaction, our chatbot helps develop concrete, actionable skills that can be applied across different settings to strengthen diversity, equity, and inclusion efforts in organizations. This study bridges the gap between emerging technologies and team inclusion by demonstrating how chatbot applications can be effectively integrated into existing HRM practices, particularly in leadership training and development, to provide systematic, empirically validated support for digital transformation initiatives.

Recommended citation: Singh V and Keplinger K (2025) Gig work in organizations: Demystifying the perspectives of Human Resource Management professionals. Proceedings of Conference of the itAIS 2025 (Castellanza, Italy).

Inclusive Leadership in the Age of AI: A Dataset and Comparative Study of LLMs vs. Real-Life Leaders in Workplace Action Planning

Published in Conference on Empirical Methods in Natural Language Processing, 2025

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 underexplored. In this interdisciplinary study, we present a novel dataset and compare LLMs and human leaders in the context of workplace action planning, specifically focusing on translating the abstract idea of inclusion into actionable SMART goals. We developed the Leader Success Bot, a script-based chatbot 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 insights 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.

Recommended citation: TBD.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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