Document Type : Research Paper

Authors

• Nahid Foroughi ¹
• Mahmoud Moradi ²
• Keikhosro Yakideh ³
• MohammadRahim Ramazanian ⁴

¹ Ph.D. Candidate in Industrial Management, Management Department, Faculty of Management and Economics, University of Guilan, Rasht, Iran

² Associate Professor, Management Department, Faculty of Management and Economics, University of Guilan, Rasht, Iran

³ Assistant Prof., Management Department, Faculty of Management and Economics, University of Guilan, Rasht, Iran

⁴ Associate Prof., Management Department, Faculty of Management and Economics, University of Guilan, Rasht, Iran

Abstract

Abstract
This study investigated the impact of improvement strategies on key performance indicators in the water and wastewater sector using a system dynamics approach. The main objective was to develop models for simulating the complex interactions between strategies and performance variables to enhance sustainability and performance management. Performance indicators were categorized as input indicators (including accounts receivable period, per-capita subscriber debt, non-revenue water, and labor cost share of sales) and output indicators (such as asset turnover ratio, per-capita subscriber coverage, market growth, and employee professionalism). Based on the literature, policy documents, company reports, and expert opinions, 14 improvement strategies were identified and incorporated into two system dynamics models. Results indicated that implementing these strategies reduced accounts receivable periods and labor costs while improving asset turnover, service coverage, market growth, and employee skills. These findings demonstrate that system dynamics modeling is an effective tool for strategic decision-making and performance improvement in the water and wastewater sector.
Introduction
ith the increasing complexity and rapid changes in competitive environments, organizations require innovative approaches to enhance performance and achieve sustainable competitive advantage. Performance management is a fundamental approach that, in addition to evaluation, encompasses continuous feedback, goal setting, training, and incentive systems (Aguinis & Pierce, 2008). Prior research has emphasized that analyzing causal relationships and dynamic interactions within organizations, particularly under multi-factor conditions, can enhance decision-making (Tseng & Levy, 2019). In this context, systems thinking and simulation models have gained importance as tools for predicting policy impacts and designing improvement strategies (Shafiee et al., 2021; Eidin et al., 2024). Nevertheless, many studies have primarily focused on ranking and benchmarking performance rather than addressing operational interventions (Kameli et al., 2023). In the Iranian water and wastewater sector, limited resources and deteriorating infrastructure further highlight the necessity of adopting advanced analytical approaches (Hejazi et al., 2024). Accordingly, this study applies system dynamics modeling to examine how improvement strategies influence key input and output indicators in the water and wastewater sector, while providing a framework for enhancing sustainability and supporting strategic decision-making.
Literature Review
The system dynamics approach, introduced by Forrester (1961), is a framework grounded in systems science and computer-based simulation that enables the analysis of complex system behavior and the prediction of long-term policy effects. Features such as feedback loops, stocks and flows, nonlinear relationships, and mutual interactions make it an effective tool for modeling organizational and infrastructural systems (Mustafee et al., 2010; Mielczarek, 2016). Numerous studies have demonstrated that system dynamics is an effective method for performance analysis and strategic decision-making, including in wastewater network asset management, automotive supply chains, urban and water resource management, and complex projects (Mohammadifardi et al., 2019; Norouzian-Maleki et al., 2022; Calderon-Tellez et al., 2024). However, most studies have focused only on partial analyses of performance indicators, and integrated evaluations of multiple strategies and both input and output indicators remain scarce. In the water and wastewater sector, the development of separate models for resource-related input indicators and performance-related output indicators, along with the simulation of their interactions, remains limited. The present study addresses this gap by introducing two distinct models and analyzing the combined effects of improvement strategies, thereby providing an innovative and context-specific framework for comprehensive performance assessment in this sector.
Methodology
This descriptive-analytical study employed a system dynamics approach to examine the long-term effects of 14 improvement strategies on key performance indicators in water and wastewater companies. Eight input indicators (accounts receivable period, per-capita subscriber debt, non-revenue water, and labor cost share) and output indicators (asset turnover ratio, per-capita subscriber coverage, market growth, and employee professionalism) were identified based on the literature and expert opinions. Two system dynamics models were developed, encompassing financial, operational, and human resource subsystems. Reinforcing loops represented the positive effects of network expansion, reduction of non-revenue water, and employee motivation, while balancing loops captured the moderating effects of accounts receivable management and constraints associated with sales growth. These models enabled the simulation of improvement scenarios and the identification of key leverage points affecting system performance.
Results
Using Sterman’s five-step modeling process (2000), input and output system dynamics models were simulated for the selected indicators. Variable relationships were established based on financial data, industry standards, water and wastewater regulations, and the opinions of ten experts to evaluate the long-term effects of improvement strategies on key company performance metrics.
Structural and behavioral tests confirmed the validity of the models, and sensitivity analysis showed that the provincial pricing coefficient had the greatest impact on net sales, with a ±20% change resulting in approximately a 20% change in sales. In contrast, other key parameters, such as the conversion rate of unauthorized connections and government funding allocation, had minimal effects (less than 0.1%) on the growth rate of service units. These results indicate that the models are stable with respect to input variations, with the primary sensitivity associated with pricing policies.
Eight scenarios were developed: four aimed at improving operational efficiency and reducing financial constraints, and four targeting productivity enhancement and market growth. Simulation of the input model showed that the simultaneous implementation of incentive/punitive strategies, private sector involvement, and network expansion reduced accounts receivable issues, controlled resource losses, and optimized labor costs. The output model demonstrated that a combination of developmental actions, tariff adjustments, and human resource empowerment improved asset productivity and service coverage, stabilized market growth, and enhanced employee skills and expertise. Overall, the results indicate that the coordinated and targeted application of strategies creates an optimal balance between short-term efficiency, financial sustainability, and long-term development. The developed models provide water and wastewater managers with a systematic tool to support strategic decision-making and evaluate long-term impacts.
Discussion
This study demonstrated that, through system dynamics modeling, the simultaneous interaction of managerial, financial, and infrastructure strategies significantly affects the efficiency and sustainability of water and wastewater companies. Separating input and output indicators and designing distinct models enabled the analysis of the combined effects of 14 improvement strategies, showing that enhancements in accounts receivable management, reduction of resource losses, and optimization of labor costs were accompanied by increased asset productivity, network expansion, and improved employee skills. The results confirmed that a combination of incentive-based strategies, financing of smart technologies, and infrastructure development can effectively balance short-term objectives with long-term goals. Financial resource constraints and external factors, such as inflation and demand fluctuations, emphasize the importance of active management and complementary policies. Overall, the findings indicate that successful management in these companies requires an integrated and synergistic approach across human capital, financial structure, and infrastructure.
Conclusion
This study confirmed the effectiveness of the system dynamics approach in analyzing and predicting the long-term effects of improvement strategies in water and wastewater companies. The developed models, by simulating the complex interactions among 14 strategies and key performance indicators, enable evidence-based decision-making with a systems perspective. The results showed that a combination of managerial actions, infrastructure development, and human capital empowerment not only enhances operational efficiency but also strengthens financial sustainability and service accessibility. This study recommends that companies focus on integrated strategies and continuous performance monitoring, while future research should consider the impact of external factors such as climate change and emerging technologies in future models. Overall, this study offers a practical and context-specific framework for comprehensive performance improvement in water and wastewater companies.

Keywords

• System dynamics
• Simulation:
• Performance indicators:
• Improvement strategies:
• Performance management

Main Subjects

• modeling and simulation