Modelling technician agility to improve service responsiveness: a productivity framework for multi-brand automobile garages

Purpose The purpose of this paper is to develop a graph theoretical framework for qualitative assessment of the agility of maintenance technicians in multi-brand automobile garages. The intention also includes linking the agility with service responsiveness and performance outcomes in garages, thereby developing insights for the enhancement of productivity in such decentralized service operations. Design/methodology/approach Anchored on literature review and drawing of opinion of experts from garages, seven crucial factors that influence agility, which range from technician skills, job scheduling, etc. up to autonomy, are identified. The interrelationships among these are modelled using a graph theory and matrix approach (GTMA), leading to the formulation of a maintenance technician agility index (MTAI) and a corresponding maintenance technician agility ratio (MTAIR). A sensitivity analysis was performed to identify influential agility factors. Findings The research identified technician agility as a key factor for service responsiveness and customer satisfaction in the growing network of India's multi-brand car garages, which is dynamic. The empirical application of the developed framework in two Indian multi-brand garages discovered the disparities existing in the agility of technicians and highlighted actionable areas for productivity enhancement. The sensitivity analysis revealed that the garage environment as well as decision-making autonomy are the prominent agility influential factors. Practical implications The framework assists garage managers in planning their workforces and benchmarking their agility through MTAI/MTAIR. It also helps them schedule technicians based on their performance and target training, make infrastructure investments based on dimensions that affect agility and redesign the garage layout and digital systems to boost overall productivity. Originality/value While the underlying graph theory and matrix approach are established, their application to human-centric service agility in multi-brand automobile garages and the development of a MTAI represent a novel contribution. The study empirically shows how workplace environmental factors and decision-making autonomy affect technician agility and service production, expanding performance management literature in decentralized and labour-intensive service ecosystems.