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The Gender Equality Strategy and the Pay Transparency Directive (Directive (EU) 2023/970) underscore the persistent issue of gender inequality in workplaces, particularly regarding the gender pay gap and the undervaluation of jobs predominantly occupied by women. While regulatory efforts aim to promote transparency and fairness, internal organizational mechanisms, including performance measurement and management control systems (MCS), often play a critical role in reinforcing or mitigating gender biases.
Management control systems (MCS) are integral to shaping organizational practices and behaviors, encompassing performance evaluations, reward structures, and decision-making processes. However, these systems often embed implicit biases, leading to disparities in pay, career progression, and job valuation, thereby reinforcing traditional stereotypes and undervaluing roles typically occupied by women. Understanding these biases and reconfiguring MCS to promote inclusivity is important for achieving gender equity.
Key Research Themes & Questions
Key Research Themes & Questions
Influence of Performance Measurement Systems on Gender Disparities:
Influence of Performance Measurement Systems on Gender Disparities:
How do traditional performance metrics contribute to the gender pay gap and the underrepresentation of women in leadership roles?
In what ways do subjective evaluations in performance appraisals disadvantage female employees compared to their male counterparts?
What modifications in performance measurement systems can effectively reduce gender disparities?
Role of Management Control Systems (MCS) in Reinforcing or Mitigating Gender Bias:
How do existing MCS practices reinforce traditional gender roles and stereotypes in the workplace?
What is the relationship between MCS and the allocation of high-visibility projects or leadership opportunities to male versus female employees?
How can MCS be redesigned to promote gender-neutral decision-making processes?
Impact of Organizational Culture and Leadership on Gender Equality:
How does the presence of women in leadership positions affect the prevalence of gender discrimination within teams?
What role does organizational culture play in either perpetuating or challenging the "double bind" faced by female leaders?
How can leadership development programs be structured to support and advance women into senior roles?
Generative AI's Impact on Gender Bias in Performance Evaluations:
How can organizations ensure that generative AI systems used in performance evaluations do not perpetuate existing gender biases present in historical data?
What measures can be implemented to detect and mitigate algorithmic biases in AI-driven performance assessment tools?
How can the inclusion of diverse perspectives in the development of AI systems enhance fairness and reduce gender bias in performance evaluations?
Practical Implications and Expected Impact
This research will provide evidence-based recommendations for organizations and policymakers to:
Develop gender-neutral performance evaluation tools aligned with pay transparency requirements.
Reduce gender bias in performance appraisals, job evaluations, and promotions.
Foster inclusive organizational cultures through MCS-driven interventions.
Enhance compliance with the EU Pay Transparency Directive by establishing clear, gender-sensitive evaluation metrics.
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