Researcher in human resource management and the future of work; MA, University of Hertfordshire

Flexible for Whom? Caregiving Visibility, I-Deals, and Gendered Career Progression in Hybrid Work

Flexible work is often presented as a way to include, retain and achieve gender equality. However, there exist alternative pathways to creating new forms of inequality when an employee is visibly associated with care giving. This study investigates the interaction between caring visibility and flexibility i-deals and career advancement in Hybrid workplaces. It is based on the concepts of i-deals theory, flexibility stigma and gendered organizations theory. By proposing to connect visibility of c

2026

Datafied Ageism at Work: How AI-Based Performance Visibility Shapes Dignity and Late-Career Sustainability

Performance systems based on AI are becoming increasingly used to monitor, compare, and evaluate workers, but the question is when supposedly age-neutral data does lead to age-based disadvantage. The introduction of datafied ageism: an unfair form of disadvantage because the algorithmic performance visibility does not appropriately reflect the occupational advantage or disadvantage, or because the algorithm uses proxies that are age-correlated, or because it is based on non-representative benchm

2026

Algorithmic Management and Fair Work: How Contestability Shapes Employee Voice under Digital Control

Algorithmic management is not only used to assign duties, but it's also utilized to analyse behaviour, assess staff members, and bestow rewards or penalties without any evident human supervisor. The study identifies and evaluates a contestability-based theory of the effects of digital control on employee voice and fair employment. To achieve this, a cross-sectional quantitative survey of 225 records of ride-hailing drivers and food delivery riders in the Chattogram Metropolitan Area was carried

2026

From Automation to Augmentation: How Expertise Complementarity Converts Generative AI into Team-Level Productivity

Generative artificial intelligence has diffused rapidly across knowledge work, yet adoption does not reliably translate into collective performance. This study investigates how generative AI usage and team productivity are connected through the lens of expertise complementarity. This cross-sectional secondary analysis combines the results of published findings from the 2025 Stack Overflow Developer Survey, based on the responses of 11,202 individuals from the workflow module, distributed across

2026