Sustainability Performance Research Articles

ESG in the shipping industry: a literature review

Purpose This study aims to review the literature on sustainability and corporate governance in the shipping industry, outline suggestions for future research and put forward directions for policy makers. Design/methodology/approach Using a semi-systematic literature review, 94 papers are analyzed. The analysis focuses on sustainability performance and reporting in the shipping industry, the relationship between shipping companies and their external and internal stakeholders and corporate governance and the market for corporate control. Findings The paper documents that a) research on sustainability focuses more on environmental rather than social sustainability in the shipping industry, b) research on sustainability rarely includes corporate governance considerations and vice versa, c) board structure and ownership structure affect the financial performance of shipping companies, d) causality between ESG policies and realized impact is elusive, e) ESG reporting differs substantially across shipping companies and f) the design and implementation of ESG policies must rely on a diverse blend of stakeholder interests. Furthermore, the paper introduces a new model that can serve as navigator in the analysis of ESG in the shipping industry. Originality/value This paper is the first to jointly review corporate governance and sustainability performance and reporting in the shipping industry, thereby highlighting ESG challenges in the context of an industry like shipping which is uniquely global and bears distinct importance for the attainment of sustainability policy objectives.

The causal and interactive approach to drive sustainability: role of green dynamic capabilities, ambidextrous green innovation strategy and resource orchestration capability

PurposeGrounded in dynamic capabilities and ambidexterity theories, this study investigates how causal and interactive mechanisms promote sustainable outcomes via the prisms of green dynamic capabilities (GDC), ambidextrous green innovation strategy (AGIS) and resource orchestration capability (ROC).Design/methodology/approachThe study employed partial least squares-structural equation modelling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) to assess data gathered from 304 respondents from Chinese manufacturing firms.FindingsThe findings show that GDC significantly impacts different aspects of sustainable performance and AGIS serves as a significant mediating mechanism. High ROC amplifies GDC’s indirect impact on sustainable performance via AGIS. FsQCA results reveal multiple synergistic pathways of how GDC, AGIS and ROC can bring about better sustainability outcomes.Practical implicationsThe research offers valuable insights and a novel strategy for manufacturing firms and policymakers to mitigate environmental degradation and attain sustainable performance by stimulating AGIS through GDC.Originality/valueThis paper contributes to sustainability research by integrating dynamic capabilities and ambidexterity theories. It provides actionable insights for manufacturing firms to engage in appropriate green innovation strategies and resource orchestration for sustainable growth.

Optimizing Space Heating in Buildings: A Deep Learning Approach for Energy Efficiency

Building energy management is crucial in reducing energy consumption and maintaining occupant comfort, especially in heating systems. However, achieving optimal space heating efficiency while maintaining consistent comfort presents significant challenges. Traditional methods often fail to balance energy consumption with thermal comfort, especially across multiple zones in buildings with varying operational demands. This study investigates the role of deep learning models in optimizing space heating while maintaining thermal comfort across multiple building zones. It aims to enhance heating efficiency by developing predictive models for building temperature and heating consumption, evaluating the effectiveness of different deep learning architectures, and analyzing the impact of model-driven heating optimization on energy savings and occupant comfort. To address this challenge, this study employs Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Transformer models to forecast area temperatures and predict space heating consumption. The proposed methodology leverages historical building temperature data, weather station measurements such as atmospheric pressure, wind speed, wind direction, relative humidity, and solar radiation, along with other weather parameters, to develop accurate and reliable predictions. A two-stage deep learning process is utilized: first, temperature predictions are generated for different building zones, and second, these predictions are used to estimate global heating consumption. This study also employs grid search and cross-validation to optimize the model configurations and custom loss functions to ensure energy efficiency and occupant comfort. Results demonstrate that the Long Short-Term Memory and Transformer models outperform the Gated Recurrent Unit regarding heating reduction, with a 20.95% and 20.69% decrease, respectively, compared to actual consumption. This study contributes significantly to energy management by providing a deep learning-driven framework that enhances energy efficiency while maintaining thermal comfort across different building areas, thereby supporting sustainable and intelligent building operations.

Even ownership in business groups and member firms’ environmental and social performance

ABSTRACT Numerous studies investigate how firm-level characteristics and country-level institutional attributes affect a firm’s environmental and social (ES) performance. However, little evidence exists on whether and how organizational characteristics affect a firm’s ES activities. Based on a sample of 5,105 firm-years across 768 listed firms and 267 business groups in the Taiwanese stock market, this study examines the relationship between even ownership in business groups and member firms’ ES performance by ordinary least squares regressions. The results show that even ownership in business groups is positively associated with member firms’ social and overall performance, and that ownership disparity weakens the positive impact on environmental performance. These findings highlight the important role of business group ownership across affiliates in sustainable performance and show that group controllers have significant control preferences for investing in environmental activities.

Strategies for Sustainable Employee Performance in the Post-Pandemic Era: A Qualitative Approach

The COVID-19 pandemic has fundamentally changed workplace dynamics, placing employee mental health and well-being at the forefront of Human Resource Management (HRM) priorities. As organizations navigate the post-pandemic era, ensuring continued employee performance requires a strategic emphasis on psychological resilience, work-life balance, and organizational support systems. This study uses a Systematic Literature Review (SLR) approach following the PRISMA framework to identify effective HRM strategies that promote workplace mental health and well-being. The study’s findings highlight key strategies, including flexible work arrangements, Employee Assistance Programs (EAPs), leadership-driven well-being initiatives, and the promotion of a supportive organizational culture. These strategies not only reduce mental health risks but also improve employee engagement, productivity, and retention. This study presents a comprehensive framework for HR practitioners to integrate well-being into organizational policies, ensuring long-term resilience and competitiveness in an increasingly volatile work environment.

Pharmacological and Non-Pharmacological Strategies for Enhancing Sleep Quality in Athletes

Sleep is a critical determinant of recovery, performance, and overall well-being in athletes. Despite its importance, sleep disturbances—including insomnia, delayed sleep onset, and circadian rhythm disruption—are common in athletic populations, driven by both primary factors (e.g., overtraining, evening workouts, jet lag) and secondary factors (e.g., stress, injury, metabolic conditions). These disturbances can impair physical restoration, hormonal balance, and cognitive functioning. This review explores the physiological foundations of sleep in athletes, outlines the multifactorial causes of insomnia, and evaluates pharmacological strategies—including melatonin, non-benzodiazepine hypnotics, cannabidiol (CBD), and certain antidepressants—for managing sleep disorders. While pharmacotherapy may provide short-term benefits in select situations, non-pharmacological approaches such as Cognitive Behavioral Therapy for Insomnia (CBT-I) remain the gold standard due to their long-term efficacy and minimal side effects. An integrated, personalized approach that combines behavioral, physiological, and pharmacological strategies offers the greatest potential for optimizing sleep and supporting sustainable athletic performance.

Seismic Resilience and Sustainability: A Comparative Analysis of Steel and Reinforced Structures

This study presents a comprehensive comparative analysis of seismic resilience and sustainability between steel and reinforced concrete structures. With growing demand for environmentally responsible and disaster-resilient infrastructure, evaluating the life cycle performance of construction materials has become critical. Three building typologies—10-, 20-, and 30-story residential structures—are analyzed using a life cycle assessment (LCA), life cycle costing (LCC), and incremental dynamic analysis (IDA) to assess environmental, economic, and seismic performance. The results reveal that reinforced concrete structures tend to exert greater environmental impacts, particularly in categories such as carcinogenic emissions, ecotoxicity, and acidification, primarily due to cement production. Steel structures, while associated with higher energy consumption and mineral resource depletion, demonstrated superior seismic performance across all building heights, characterized by a greater level of ductility and collapse capacity. For instance, the 30-story reinforced concrete structure generated approximately 6.93 million kg CO2 eq, compared to 6.79 million kg CO2 eq for its steel counterpart. Steel structures, while associated with higher energy consumption and mineral resource depletion, demonstrated superior seismic performance across all building heights, sustaining up to a 15% greater spectral acceleration before collapse. Additionally, the LCC analysis showed that reinforced concrete is more cost-effective in high-rise construction, especially during the construction stage. These findings offer valuable insights for engineers and decision makers aiming to balance sustainability and structural performance in urban development.

A Study of Stock Performance and Subscription Rate of Selected IPOs in India

The study of stock performance and subscription rates of selected IPOs in India reveals a significant relationship between investor interest and market outcomes. 1 Higher subscription rates often indicate strong market confidence, leading to initial listing gains. 2 However, the long-term performance varies, with some IPOs experiencing volatility despite high subscription rates. 3 The findings suggest that while over-subscription can be a positive signal, it does not always guarantee sustained stock performance. 4 Investors must consider other factors, such as company fundamentals and market conditions when evaluating IPOs. 5 This research emphasizes the need for improved pricing strategies and better market transparency to enhance the IPO process and investor decision-making.

Research on Fleet Size of Demand Response Shuttle Bus Based on Minimum Cost Method

Demand-responsive connector services (DRC) are an important means to improve the current mobility connection problem. In this study, we develop a hybrid model for the minimization of total system cost for demand response shuttle buses, which includes operating cost and user cost, with fleet size per hour as the optimization variable of the model. The relevant variables are analyzed and numerically modeled by Matlab, and the relationship between fleet size, vehicle capacity and demand density and waiting time, onboard time, vehicle travel distance, and total system cost is analyzed. The results indicate that introducing financial subsidies markedly lowers the critical demand density necessary to ensure system viability. Moreover, subsidy intensity is positively associated with the service’s operational robustness. Through parametric examination, we observe a strictly monotonic relationship between subsidy magnitude and demand thresholds: as subsidy levels increase, the minimum demand requirements for sustainable operation decrease in a consistent, progressive manner; meanwhile, the optimal fleet size exhibits an approximately linear relationship with travel demand per unit area across varying vehicle capacities. Notably, an increase in vehicle capacity corresponds to a decrease in the growth rate of the required fleet size. This model demonstrates robust adaptability across diverse operational scenarios and serves as an effective tool for evaluating the efficiency of resource allocation in demand-responsive transit (DRT) services. Furthermore, it provides valuable theoretical support for the scheduling and planning of public transportation systems, particularly in low-density urban environments.

Linking organizational intangibles to sustainable performance: A mediated-moderated model from the hospitality industry

The hospitality sector in Batam drives the local economy by creating jobs, increasing incomes, and supporting local businesses through collaboration with vendors. While maintaining service quality remains challenging, competition among hotels encourages innovation. Adapting to technology and sustainability trends helps the sector thrive in tourism development. This research examines how organizational culture, knowledge management practices, and organizational learning impact human resource management practices, job satisfaction, and sustainable organizational performance, with organizational climate as a moderator. The study surveyed 233 out of 557 employees from star-rated hotels in Batam, using structural equation modeling with AMOS 20 for data analysis. The results show that organizational culture and knowledge management practices significantly influence human resource management practices (HRMP), while organizational learning does not. Organizational culture does not significantly affect job satisfaction, but knowledge management practices and organizational learning do. Organizational culture does not significantly impact sustainable organizational performance, whereas knowledge management practices and organizational learning positively do. HRMP significantly affects sustainable organizational performance, while job satisfaction does not. Organizational climate does not moderate the effect of HRMP on sustainable organizational performance but moderates the effect of job satisfaction on it. HRMP mediates the influence of organizational culture and knowledge management practices on sustainable organizational performance but does not mediate the effect of organizational learning. Job satisfaction does not mediate the effects of organizational culture, knowledge management practices, or organizational learning on sustainable organizational performance.

Virtue Ethics, Corporate Sustainability, and Tax Disclosure: Evidence From Global Fortune 500

ABSTRACTDrawing on virtue ethics, this paper explores how corporate virtues influence sustainability performance and whether this, in turn, affects tax disclosure. Using a sample of 339 companies from the 2021 Fortune Global 500 list, our findings indicate that corporate virtues significantly drive sustainability performance. Furthermore, companies with higher sustainability performance are more likely to include tax disclosures in their sustainability reports. The findings suggest that tax transparency is not merely a compliance‐driven practice but a reflection of a company's commitment to the common good. By positioning tax disclosure as an extension of corporate virtues, this research enriches the discourse on sustainability reporting, offering valuable insights for policymakers, investors, and corporate leaders striving to align business success with societal impact.

Advancing Sustainable Medical Waste Management: A Case Study on Waste Generation and Classification in a University Hospital Microbiology Laboratory

Effective medical waste management is crucial for minimizing environmental contamination, protecting occupational health, and advancing sustainability goals in healthcare systems. However, microbiology laboratories remain underexplored in waste characterization studies, despite their potential to contribute to sustainable healthcare operations. This study assessed waste generation patterns, classification accuracy, and the impact of training on regulatory compliance in a university hospital microbiology laboratory. Over 45 days, waste from six specialized units was categorized and weighed daily. A survey of 304 healthcare professionals evaluated their knowledge of medical waste handling. Statistical analyses revealed that training frequency (R2 = 0.72, p < 0.01) was the most significant predictor of compliance, while years of experience had no measurable impact. On average, the laboratory generated 22.78 kg/day of medical waste, 11.67 kg/day of liquid waste, and 5.61 kg/day of sharps waste, with the bacteriology unit being the largest contributor. Despite adequate general awareness, 15% of staff misclassified hazardous waste—particularly expired pharmaceuticals and cytotoxic vials—indicating critical gaps in practice. The findings support the need for recurring training programs, stricter monitoring systems, improved waste labeling, and the integration of digital tracking tools. These interventions can reduce environmental burdens, enhance healthcare sustainability, and support the development of more resilient waste management systems in medical institutions. Future research should explore how AI and automation can further strengthen sustainable healthcare waste strategies.

A Comprehensive Data Monitoring and Logging System for Lithium-Ion Battery Packs in Agricultural Robotics

This paper presents the development and evaluation of a monitoring and data capture system designed to track critical parameters of a lithium-ion battery pack used in an agricultural robot. Agricultural robots rely heavily on battery performance to operate efficiently and reliably in the field. As a result, ensuring that the battery is well-managed and monitored can significantly improve the robot’s operating time, reduce downtime, and extend overall battery life. Given the growing emphasis on energy efficiency in modern agricultural practices, optimizing battery usage and storage plays a crucial role in reducing energy waste and improving sustainability. Our approach integrates both hardware and software elements to collect, store, and present key battery parameters. We utilize a Battery Management System (BMS) that communicates vital data such as voltage, current, temperature, and State of Charge (SoC) through a Controller Area Network (CAN) bus. A dedicated microcontroller reads and processes these signals, and then transfers them into a central database for long-term logging and analysis. This enables precise tracking of battery health and performance, ultimately supporting more energy-efficient robotic operations. To make this information accessible to users, we developed a clear and intuitive interface. Operators can view the data on a built-in display located directly on the robot, as well as remotely through a web-based interface and an API. This dual-access approach supports on-site monitoring during field operations, as well as remote diagnostics and decision-making. Such flexibility aids in timely maintenance, better charging strategies, and overall improved resource management – key factors in maximizing energy efficiency and minimizing unnecessary power consumption. Preliminary tests performed under realistic field conditions indicate that our system reliably captures and records the critical battery parameters. The data collected facilitates early detection of potential issues, preventing unexpected breakdowns and saving valuable time and costs. In future work, we plan to implement advanced analytics and machine learning algorithms to predict battery failures and optimize charging schedules. By providing a robust and accessible tool for battery management, this system contributes to more efficient, sustainable, and productive agricultural robotic operations while reinforcing the importance of energy storage and utilization in modern farming.

Reduced-Order Modeling (ROM) of a Segmented Plug-Flow Reactor (PFR) for Hydrogen Separation in Integrated Gasification Combined Cycles (IGCC)

In an integrated gasification combined cycle (IGCC), a gasification process produces a gas stream from a solid fuel, such as coal or biomass. This gas (syngas or synthesis gas) resulting from the gasification process contains carbon monoxide, molecular hydrogen, and carbon dioxide (other gaseous components may also be present depending on the gasified solid fuel and the gasifying agent). Separating hydrogen from this syngas stream has advantages. One of the methods to separate hydrogen from syngas is selective permeation through a palladium-based metal membrane. This separation process is complicated as it depends nonlinearly on various variables. Thus, it is desirable to develop a simplified reduced-order model (ROM) that can rapidly estimate the separation performance under various operational conditions, as a preliminary stage of computer-aided engineering (CAE) in chemical processes and sustainable industrial operations. To fill this gap, we present here a proposed reduced-order model (ROM) procedure for a one-dimensional steady plug-flow reactor (PFR) and use it to investigate the performance of a membrane reactor (MR), for hydrogen separation from syngas that may be produced in an integrated gasification combined cycle (IGCC). In the proposed model, syngas (a feed stream) enters the membrane reactor from one side into a retentate zone, while nitrogen (a sweep stream) enters the membrane reactor from the opposite side into a neighbor permeate zone. The two zones are separated by permeable palladium membrane surfaces that are selectively permeable to hydrogen. After analyzing the hydrogen permeation profile in a base case (300 °C uniform temperature, 40 atm absolute retentate pressure, and 20 atm absolute permeate pressure), the temperature of the module, the retentate-side pressure, and the permeate-side pressure are varied individually and their influence on the permeation performance is investigated. In all the simulation cases, fixed targets of 95% hydrogen recovery and 40% mole-fraction of hydrogen at the permeate exit are demanded. The module length is allowed to change in order to satisfy these targets. Other dependent permeation-performance variables that are investigated include the logarithmic mean pressure-square-root difference, the hydrogen apparent permeance, and the efficiency factor of the hydrogen permeation. The contributions of our study are linked to the fields of membrane applications, hydrogen production, gasification, analytical modeling, and numerical analysis. In addition to the proposed reduced-order model for hydrogen separation, we present various linear and nonlinear regression models derived from the obtained results. This work gives general insights into hydrogen permeation via palladium membranes in a hydrogen membrane reactor (MR). For example, the temperature is the most effective factor to improve the permeation performance. Increasing the absolute retentate pressure from the base value of 40 atm to 120 atm results in a proportional gain in the permeated hydrogen mass flux, with about 0.05 kg/m2.h gained per 1 atm increase in the retentate pressure, while decreasing the absolute permeate pressure from the base value of 20 bar to 0.2 bar causes the hydrogen mass flux to increase exponentially from 1.15 kg/m2.h. to 5.11 kg/m2.h. This study is linked with the United Nations Sustainable Development Goal (SDG) numbers 7, 9, 11, and 13.

Corporate Social Responsibility Activities in Small and Medium Enterprises and Their Contribution to Sustainable Development: A Study on Traditional Food Processing Industries in Indonesia

This study explores the Corporate Social Responsibility (CSR) activities implemented by Small and Medium Enterprises (SMEs) in the traditional food processing industry in Cirebon, Indonesia. The research focuses on the impact of CSR on sustainable development, highlighting the ethical business practices and community involvement of SMEs producing traditional Indonesian foods such as tempe, wajik, kerupuk, and emping. Through observations and interviews, the study reveals that these SMEs prioritize the use of quality raw materials, maintain food safety standards, and recycle waste products for alternative uses. The businesses demonstrate significant contributions to the local economy by providing job opportunities and promoting local employment. Moreover, the research underscores the importance of legal compliance and consumer protection, particularly in ensuring product quality and hygiene. These SMEs also engage in eco-friendly practices, such as recycling and reducing waste, supporting a circular economy. This study emphasizes the role of CSR in promoting sustainable business operations and fostering positive social and environmental outcomes. In conclusion, the CSR practices of these traditional food SMEs serve as a model for other small businesses, contributing to both economic growth and environmental sustainability in rural areas. The findings suggest that continued support for CSR initiatives can further enhance the development of SMEs in Indonesia’s food industry.

Internal audit functions and environmental, social and governance (ESG): a systematic literature review

PurposeSustainable development always highly appreciates the role of internal audit (IA) in environmental, social and governance (ESG). This study explores research lines on the relationship between IA functions and ESG, thereby opening up further research trends.Design/methodology/approachAccessing systematic literature review through the dataset from Scopus source, 34 articles were included in the analysis after complying with PRISMA screening principles. The data analysis process is supported by the VOSviewer tool.FindingsWe clarify the effects of IA on ESG (positive, negative, or insignificant) using the theory and context of prior studies, as well as provide difficulties for future research. In addition, this paper discusses limits and future research ideas. The findings indicate a favorable link between IA functions and ESG. IA functions are actively involved in ESG concerns, ranging from ESG practices and performance to ESG disclosure. Furthermore, there is a link between IA functions and ESG disclosure that improves organizational effectiveness (for example, firm value). As a result, these perspectives offer substantial support for business managers, keeping employees, and future scholars in this context.Research limitations/implicationsThe perspectives of this study emphasize the positive role of IA functions and their sensitivity to sustainable performance by stressing ESG practices, performance, and reporting in businesses, hence boosting the firm’s value and competitive position. As a result, business managers can make decisions to increase IA functions (for example, supporting the usage of recently integrated digital systems or tools) as a method of achieving long-term growth by improving performance and disclosing ESG practices. Furthermore, these ideas are advantageous to policymakers since they promote the establishment of rules and procedures for IA functions in businesses, hence increasing the levels of sustainable development that they seek to achieve. This study also provides prospective research subjects that might be pursued by assessing the issues experienced in previous research projects.Originality/valueThis study provides a comprehensive and reliable view of research lines on the relationship between IA functions and ESG using a systematic literature review method.

Mitigating Student Cynicism for Sustainable Academic Performance: University Identification and Academic Self-Efficacy

This study explores the complex relationships among student cynicism, student–university identification, academic self-efficacy, and academic performance within the context of Turkish higher education. Drawing on social identity and social cognitive theories, student cynicism is examined through four dimensions: academic, policy-related, institutional, and social. Survey data were collected from 630 university students in Ankara, Türkiye, using a cross-sectional design and self-reported measures. The results indicate that institutional cynicism is the strongest negative predictor of student–university identification, while academic cynicism shows a curvilinear (U-shaped) relationship with academic performance, suggesting that extreme cynicism may paradoxically be linked to modest performance rebounds. Contrary to expectations, student–university identification does not significantly predict academic performance, nor does it mediate the relationship between cynicism and performance. However, academic self-efficacy moderates the relationship between identification and performance, amplifying the benefits of identification for students with higher levels of self-efficacy. These findings offer culturally grounded insights into student disengagement and highlight the importance of fostering trust, transparency, and self-efficacy to support student well-being and academic resilience, key elements in advancing Sustainable Development Goals 4 (Quality Education) and 8 (Decent Work and Economic Growth).

PENGAMANAN ASET PRASARANA JALAN DAN BANGUNAN PT X

Asset security encompasses control and regulation activities in asset management to ensure proper utilization.. The security of road infrastructure and building assets at PT X is crucial for maintaining sustainable public transportation operations in DKI Jakarta Province. This research aims to understand asset security based on theory by (Agus Puji & Riyanto, 2012) using three main indicators: administrative security, physical security, and legal security. The research employs a descriptive qualitative method with data collected through observation, interviews, and document analysis. The results show that PT X has implemented administrative security through comprehensive asset recording and ownership documentation. However, challenges exist in asset utilization that is still under discussion for utilization schemes to ensure benefits for both parties. Physical security has been implemented with advanced technology security systems and regular guarding. Legal security shows that local government regulations and internal regulations are already running side by side. PT X needs to highlight improvements in administrative systems and physical security standards, as well as strengthening legal policies in PT X asset management. With an integrated security strategy, PT X infrastructure assets are expected to continue benefiting the public and supporting Jakarta's development as a global city with modern and sustainable transportation systems.

Sustainable Tourism Management: Balancing Economic Growth and Environmental Preservation

Objectives: To explore the connections between tourism expansion, economic development, and environmental sustainability in touristic communities. To investigate the drivers of sustainable tourism and its impact on destinations. Methods: Using mixed research techniques, including: Case studies of tourism destinations, Interviews with key stakeholders, Quantitative analyses across multiple destinations Results: Positive outcomes from sustainable tourism management include: Unified governance systems, New economic motivation, Community development-focused planning models, Adaptive management systems to address visitor density limits, Destinations that follow integrated planning models achieve: 37% higher sustainability performance scores, Maintenance of economic competitiveness Conclusion: The study proposes a comprehensive sustainable management framework that emphasizes: Collaborative multistakeholder partnerships, Long-term planning and tailored implementation methods, The research advances both theoretical knowledge on sustainable tourism and provides practical frameworks applicable to various global contexts. The study underscores the importance of destination management, carrying capacity monitoring, stakeholder involvement, and governance structures in achieving sustainable tourism.

The Role of Absorptive Capacity and Technological Innovation Capabilities in IT Project Success: Does Strategic Agility Matter?

This study aims to explore the role of absorptive capacity (AC) on project success (PS) through the mediating roles of technological innovation capabilities (TIC) and the moderating role of strategic agility (SA). A convenience sampling technique was used to collect data from 225 respondents working as project managers in small- to medium-sized Pakistani software companies in Islamabad and Rawalpindi. Data was collected from and distributed on several online channels (Gmail, LinkedIn, WhatsApp). Smart PLS-SEM, version 4, was used for data analysis. The results obtained suggested that AC has a direct positive effect on PS and an indirect impact through the mediating role of TIC. However, the moderating role of SA showed an insignificant impact on the relationship between TIC and PS. The current study's findings highlight the importance of various factors to achieve sustainable performance for small-medium software enterprises, which are the backbone of developing economies in today's highly turbulent economic conditions.