Exploring buyer persona of luxury brands: a comparison of compelling stories in the framework of consumer psychology

Abstract

Algorithmic management has become a significant tool in modern times for improving efficiency and productivity at work by automating procedures and analyzing data (Gritsenko et al., 2022). This thesis investigates the overall impact, benefits, and possible risks of algorithmic management in modern workplaces. The primary goal is to analyze how these systems affect operational efficiency, employee experiences, corporate culture, and organizational dynamics. Through a systematic review of literature, the study investigates the effects of algorithmic management in different areas like recruitment, financial performance tracking, and employee supervision (Lee, 2018). Case studies from top multinational companies like Uber, Facebook, and Amazon offer practical insights into how algorithmic management systems are put into use and the results they produce. These instances underscore important problems like employee rights, transparency, data privacy, and the ethical implications of automated decision- making processes. The results indicate that algorithmic management can greatly improve operations and decision-making processes, yet it also prompts notable worries regarding fairness, bias, and employee freedom. The research offers strategic guidance to tackle these obstacles, highlighting the significance of transparent data, ethical algorithm creation, ongoing monitoring, and input from employees. This thesis seeks to enhance responsible and efficient technology usage in today's workplace by offering a fair assessment of the benefits and possible challenges of algorithmic management. By doing this, advantages can be optimized while reducing any adverse effects on workers and company culture. iv