The impact of robotic working patterns on employee work life and job satisfaction: evidence from ethnic minority businesses in the UK

Abstract

Purpose

By aligning the “Small is beautiful” and “Bleak house” theories, this study aims to examine how robotic working patterns affect employees’ working life and job satisfaction (JS) in Bangladeshi-owned ethnic minority businesses.

Design/methodology/approach

The study uses information from 40 face-to-face interviews of employees from 20 Bangladeshi restaurants in Greater London.

Findings

The findings suggest that workers are treated as “robots”, consistent with the “Bleak house” view of small businesses in this segment of the restaurant and hospitality industry. Owners expect employees to perform multiple tasks, to assume many responsibilities, to work long shifts, without any holiday allowances. Consistent with the “Small is beautiful model”, the findings underscore the lack of written employment contracts and the emergence of acute staff shortages.

Practical implications

The findings can inform owner-managers’ decisions to refine their HR strategies and improve the work conditions of employees in ethnic minority-owned restaurants. The “Small is beautiful” model highlights five key interventions for improving ethnic minority business work quality: recruit employees with first preferences for restaurant jobs, introduce flexible work arrangements, formalise work, improve market research and tackle acute staff shortages.

Originality/value

The study contributes novel insights into the small- and medium-sized enterprises (SMEs) and job quality literature by offering new qualitative-based findings on the negative impact of robotic work patterns on work quality and JS in ethnic minority SMEs.

Citation

Razzak, B.M., Saridakis, G. and Georgellis, Y. (2024), "The impact of robotic working patterns on employee work life and job satisfaction: evidence from ethnic minority businesses in the UK", Journal of Entrepreneurship in Emerging Economies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEEE-06-2024-0215