List Of Key Performance Indicators Research Articles

Evaluating the impact of nature-based solutions on the provision of water-related and water-dependant ecosystem services

Water scarcity is a pressing issue in the Mediterranean region, exacerbated by overuse of resources for agriculture and the impacts of climate change. Addressing this challenge requires improved water cycle management and the adoption of Nature-based Solutions (NbS) to enhance infrastructure efficiency and sustainability. With the aim of promoting the implementation and assessment of NbS, we have developed a monitoring framework that integrates the assessment of ecological, socio-economic and cultural aspects under the umbrella of the IUCN Global Standard for NbS. A list of Key Performance Indicators (KPIs) was selected following standard methodologies. We have applied the framework to five case studies in the Mediterranean region to evaluate its efficiency to assess NbS tailored to local challenges and contexts. As part of the monitoring framework, we used the IUCN self-assessment tool for the Global Standard for NbS, demonstrating adherence of 50–75 % across all case studies. Common KPIs were identified, streamlining monitoring efforts and providing guidance from the design phase onwards. Our monitoring framework offers a comprehensive approach to evaluating NbS interventions, ensuring alignment with global standards and enhancing resilience in water management. By integrating the IUCN Global Standard, it provides robust guidance for future execution, contributing to sustainable water resource management in the Mediterranean and beyond.

Measuring the Influence of Industrialization in Deep Energy Renovations: A Three-Case Study Utilizing Key Performance Indicators (KPIs)

Existing buildings in the European Union account for 40% of its energy consumption. To significantly reduce this impact, annual deep energy renovation rates should triple by the end of the 2020s. However, the lack of automation in the construction industry has hindered energy renovation efforts. Horizon Europe’s INPERSO project (Industrialised and Personalised Renovation for Sustainable Societies) aims to create a user-centered energy rehabilitation method based on industrialized technologies and systems, enhancing efficiency and building performance. To bridge the gap between predictions and real-world outcomes, the 22 project partners—using a multi-criteria decision analysis (MCDA) process—devised a list of key performance indicators (KPIs) for evaluating rehabilitation based on economic, energy, environmental, social, and technological factors. Adopting a human-centric approach, these project partners aim to minimize the technologies’ environmental impact while optimizing users’ comfort and experience. The indicators are designed to evaluate performance at every stage of the renovation process, enabling continuous feedback and user engagement and ultimately ensuring that projected energy savings are met throughout the building’s lifespan. The KPIs selected for INPERSO provide a solid framework for evaluating and monitoring sustainable renovation. However, challenges such as administrative reluctance and user disruption must be addressed to further boost the adoption of deep energy renovations.

Identification of Key Drivers for Performance Measurement in Sustainable Humanitarian Relief Logistics: An Integrated Fuzzy Delphi-DEMATEL Approach

Sustainable humanitarian relief logistics (SHRL) is gaining attention due to increased disasters, unpredictable demand, large volumes, high delivery stakes, and limited resources, evaluated through adaptable performance drivers. This study presents a novel hybrid framework for SHRL, combining the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). Initially, FDM is utilized to reach a consensus among experts concerning key performance indicators (KPIs) for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze the interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and are the main cause in a cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas.

ІННОВАЦІЙНІ ІНСТРУМЕНТИ ЗЕЛЕНОГО ФІНАНСУВАННЯ ДЛЯ УКРАЇНИ

The expansion of financing sources holds particular importance in the context of implementing the European Green Deal in Ukraine. Given the escalating climate and environmental threats, the pursuit of new green financing mechanisms for countries burdened with high levels of debt persists. Amidst the full-scale war in Ukraine, the options for state financing of environmental projects and programs are significantly restricted. The article examines the formation of additional financing sources aimed at restoring ecosystems and ecological infrastructure damaged by the war in Ukraine. Drawing upon an overview of international practices, this study elucidates innovative approaches to environmental financing, which involve exchanging a part of the state's external debt for commitments to invest in nature conservation programs and achieve climate neutrality. The analysis highlights significant variations in the implementation of green debt swaps across different countries, underscoring the need to assess the feasibility of adopting such mechanisms in Ukraine, especially given its heightened reliance on debt. Utilizing multi-criteria analysis, a comparative evaluation of key "green debt conversion" instruments was conducted, encompassing Bilateral Debt-for-Nature Initiatives, Debt-for-Nature Swaps, and Debt-for-Climate Swaps. A comparative table has been compiled to illustrate the key characteristics of these instruments and to assess the potential impact of their use in Ukraine. The benefits of exchanging debt for investments in environmental recovery, as outlined in Ukraine's National Recovery Plan, are delineated. The primary sources for accumulating funds to meet the state's obligations resulting from the adoption of green debt swaps have been identified. Recommendations for the implementation of green debt swaps in Ukraine have been provided. It has been concluded that green debt swaps could be employed in Ukraine to finance specific environmental or climate-related projects and initiatives, establishing conservation and climate funds through contributions from both domestic and international ESG investors. To protect against “greenwashing”, it is advisable to bolster oversight of financial transactions and to expand the list of key performance indicators (KPI) used to evaluate investment decisions, considering ESG factors.

An E2E Network Slicing Framework for Slice Creation and Deployment Using Machine Learning

Network slicing shows promise as a means to endow 5G networks with flexible and dynamic features. Network function virtualization (NFV) and software-defined networking (SDN) are the key methods for deploying network slicing, which will enable end-to-end (E2E) isolation services permitting each slice to be customized depending on service requirements. The goal of this investigation is to construct network slices through a machine learning algorithm and allocate resources for the newly created slices using dynamic programming in an efficient manner. A substrate network is constructed with a list of key performance indicators (KPIs) like CPU capacity, bandwidth, delay, link capacity, and security level. After that, network slices are produced by employing multi-layer perceptron (MLP) using the adaptive moment estimation (ADAM) optimization algorithm. For each requested service, the network slices are categorized as massive machine-type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low-latency communications (uRLLC). After network slicing, resources are provided to the services that have been requested. In order to maximize the total user access rate and resource efficiency, Dijkstra’s algorithm is adopted for resource allocation that determines the shortest path between nodes in the substrate network. The simulation output shows that the present model allocates optimum slices to the requested services with high resource efficiency and reduced total bandwidth utilization.

Responsive FLEXibility: A smart local energy system

The transition towards a more decarbonised, resilient and distributed energy system requires local initiatives, such as Smart Local Energy Systems (SLES), which lead communities to gain self-sufficiency and become electricity islands. Although many SLES projects have been recently deployed, only a few of them have managed to be successful, mostly due to an initial knowledge gap in the SLES planning and deployment phases. This paper leverages the knowledge from the UK’s largest SLES demonstrator in the Orkney Islands, named the Responsive FLEXibility (ReFLEX) project, to propose a framework that will help communities to successfully implement a SLES. First, this paper describes how the multi-services electrical SLES implemented in Orkney reduces the impact of the energy transition on the electrical infrastructure. We identify and discuss the main enablers and barriers to a successful SLES, based on a review of SLES projects in the UK. Second, to help future communities to implement SLES, we extend the Smart Grid Architecture Model (SGAM) into a comprehensive multi-vector Smart Local Energy Architecture Model (SLEAM) that includes all main energy services, namely power, heat and transport. This extended architecture model describes the main components and interaction layers that need to be addressed in a comprehensive SLES. Next, to inform successful deployment of SLES, an extensive list of key performance indicators for SLES is proposed and implemented for the ReFLEX project. Finally, we discuss lessons learnt from the ReFLEX project and we list required future technologies that enable communities, energy policy makers and regulatory bodies to best prepare for the energy transition.

Clinical and laboratory key performance indicators in IVF: A consensus between the Italian Society of Fertility and Sterility and Reproductive Medicine (SIFES-MR) and the Italian Society of Embryology, Reproduction and Research (SIERR)

PurposeInfertility is increasing worldwide, and many couples seek IVF. Clinical management and laboratory work are fundamental in the IVF journey. Therefore, the definition of reliable key performance indicators (KPIs) based on clinical and laboratory parameters, is essential for internal quality control (IQC). Laboratory performance indicators have been identified and a first attempt to also determine clinical ones has been recently published. However, more detailed indicators are required.MethodsAn Italian group of experts in Reproductive Medicine from both public and private clinics on behalf of SIFES-MR and SIERR was established to define IVF indicators to monitor clinical performance.ResultsThe working group built a consensus on a list of KPIs, performance indicators (PIs) and recommendation indicators (RIs). When deemed necessary, the reference population was stratified by woman age, response to ovarian stimulation and adoption of preimplantation genetic testing for aneuploidies (PGT-A). Each indicator was scored with a value from 1 to 5 and a weighted average formula – considering all the suggested parameters—was defined. This formula generates a center performance score, indicating low, average, good, or excellent performance.ConclusionThis study is intended to provide KPIs, PIs and RIs that encompass several essential aspects of a modern IVF clinic, including quality control and constant monitoring of clinical and embryological features. These indicators could be used to assess the quality of each center with the aim of improving efficacy and efficiency in IVF.

Methodology for Consequence Analysis of Future Mobility Scenarios: The SPROUT Framework

The various social, political, environmental, and economical mega-trends together with the rapid rise of digitalization are shaping cities worldwide including the way that citizens and products move within the urban environment. New mobility services are popping up which are showing the path toward more on-demand and personalized mobility patterns. The transformation of the urban mobility environment though constitutes a great challenge for policy-makers, as little is known about the impact of these trends on the city’s current mobility environment while the assessment of the future state of a mobility system can be considered a quite complex process taken its multi-parametric and multi-dimensional nature. This paper aims to simplify this process by presenting a coherent multi-actor consequence analysis framework as a tool for assessing future mobility scenarios which was developed in the framework of the H2020 SPROUT. This paper presents in detail the main components of this framework together with the list of key performance indicators used for assessing the performance in terms of sustainability of future mobility scenarios as well as indicative results from its use by the city of Padua.

Identify Key Performance Indicators for Designing Emergency Department dashboard in a referral Cardiac Hospital

Background: Today, organization management in healthcare organizations needs to monitor and evaluate performance for better decision and policy making. Objectives: This study aimed at determining the Key Performance Indicators (KPIs) using software and a management dashboard. Methods: This study searched several articles discussing KPIs of emergency departments. A comprehensive list of indicators was obtained and presented to an expert panel with a wide range of experiences. The experts finalized the KPIs. A second round was performed to confirm the performance using Smart Pilates software. Based on the final panel’s rating, a list of KPIs was developed to be used. The extracted data was prepared to be entered into the computer system to design the dashboard using QlickView software. Subsequently, according to the type of indicator, the dashboard was designed with special software. Results: The extracted 14 KPIs of emergency departments were determined in three dimensions of input, process, and output. Following that, the project team designed a dashboard with 14 KPIs. Conclusion: To design and develop a dashboard, the management of information was essential for organizations. It is recommended that managers use KPIs for evaluating and monitoring emergency departments. Moreover, it can be used for planning and evaluating the performance in emergency departments.

نموذج مُقترَح لتصميم بيئة تعلُّم إلکترونية قائمة على التلعيب في ضوء معايير تصميم التلعيب

يهدف البحث الحالي إلى وضع وتبني قائمة بمعايير تصميم بيئات التعلم الإلکترونية القائمة على التلعيب، إضافة إلى وضع نموذج مقترح لتصميم بيئة تعلم إلکترونية، وذلک في ضوء قائمة المعايير المعدة سلفا، وقد اعتمد البحث على المنهج الوصفي التحليلي. ومن أهم وأبرز النتائج التي تم التوصل إليها: قائمة بمعايير رئيسية تتضمن مؤشرات الأداء اللازمة والضرورية لتصميم بيئات التعلم الإلکترونية القائمة على التلعيب، بالإضافة إلى نموذج مقترح لتصميم بيئة تعلم إلکترونية قائمة على معايير تصميم التلعيب بما تحويه من مؤشرات أداء. وتم التوصل إلى عدد من التوصيات والمقترحات أهمها: ضرورة الاستفادة من قائمة معايير تصميم بيئات التعلم الإلکترونية والنموذج المبني في ضوئها عند تصميم بيئات تعلم إلکترونية قائمة على التلعيب من أجل إنتاج بيئة تعلم فعالة تسعى إلى تحقيق الأهداف المنشودة والمرغوبة منها. الکلمات المفتاحية:التلعيب، معايير تصميم، نموذج تصميم تعليمي Abstract: The aim of this paper is twofold. First, it attempts to create a list of standards for designing electronic educational environments that utilize gamification. Second, it presents a proposal model for designing an educational electronic environment drawing upon these suggested standards. The methodological approach adopted in this research is descriptive and analytical. The significant results presented in this paper are a list of key performance indicators for standards required in designing educational electronic environments based on gamification, as well as a model of an educational electronic environment designed according to this list. The researcher recommends benefitting from these results in creating an effective learning environment capable of achieving optimal educational goals. Key Words: Gamification, design standards, Instructional Design Model

Evaluation of innovative solutions for e-mobility

This paper presents a methodology for the evaluation of innovative solutions designed by the GreenCharge project to advance electric mobility. The methodology is based on the CIVITAS evaluation framework and it is specialised according to the GreenCharge requirements. In particular, this paper provides an extensive list of Key Performance Indicators (KPIs) and which of them will be evaluated in three pilots to provide a quantitative estimation of impact of technology innovation. Evaluation will use automatic computation of data collected in pilots, simulation techniques and analysis of surveys and interviews. The paper describes how to deliver and how to present evaluation results. The detailed schedule of data collection and evaluation activities has been planned in collaboration with implementation activities. Finally, a preliminary requirement analysis of simulation and a dashboard design for KPIs presentation are discussed.

A toolbox for conducting an online OSCE

This toolbox highlights the lessons learned and the tools used to run the online OSCE at the College of Medicine and Medical Sciences, Arabian Gulf University (CMMS-AGU) using Zoom™️. The examiners considered the examination to be valid in assessing all clinical skills except for psychomotor skills and students found it to be highly acceptable. We describe three phases. Planning and preparation phase in which situation analysis, aligning stakeholders, mobilizing resources, creating a shared vision, and ownership of the exam project take place. For successful implementation of examinations, detailed plans are needed including manpower, timings, number of stations and detailed description of the steps of the examination process. We provide a set of guiding questions for proper decision making related to online clinical exams. Implementation Phase in which piloting is very useful to apply improvements to the original plan and to outline the needed capacity building of the participating staff. We give a detailed description of the guiding documents, means of communication and features of ZOOM that were used. Evaluation phase we provide a guide for evaluating the process and outcome, including a list of key performance indicators.

Energy consumption and improvement of energy efficiency for the European agricultural-food system

This work addresses the subjects of reducing fossil energy consumption and the interventions to improve energy efficiency in the European agricultural-food sys-tem. Following an overview on both such subjects, the results of European projects TESLA and SCOoPE are also analysed with attention to best practices and technologies available to improve energy efficiency in order to reduce the fossil energy use in agri-food systems of Mediterranean countries. A list of Key Performance Indicators for the fruit and vegetable sector, useful for comparative analyses aimed at selecting best methods of energy management and technologies for improving energy efficiency, is reported. Finally, a brief focus on European policies concerning the solutions adopted by the new European Commission to make the agri-food system more sustainable from an energy and environmental point of view is also discussed.

From a Comprehensive Pool to a Project-Specific List of Key Performance Indicators for Monitoring the Positive Energy Transition of Smart Cities—An Experience-Based Approach

As cities grow rapidly and energy needs increase, shaping an effective energy transition is a top priority towards urban sustainability and smart development. This study attempts to answer three key research questions that can help city authorities, planners and interested agents simplify and increase the transparency of Key Performance Indicators (KPIs) selection for smart city and communities (SCC) projects focusing on energy transition and creation of Positive Energy Districts (PEDs): Question 1: “What resources are available for extracting such KPIs?”; Question 2: “Which of those KPIs are the most suitable for assessing the energy transition of smart city projects and PED-related developments?” and Question 3: “How can a project-specific shortlist of KPIs be developed?”. Answering these questions can also serve as a major first step towards a “universal” KPI selection procedure. In line with this purpose, an experiential approach is presented, capitalizing on knowledge and lessons learned from an ongoing smart city project in Europe (POCITYF) that focuses on PED deployment. Under this framework, a) a review of smart city KPI frameworks has been conducted, resulting in a pool of 258 indicators that can potentially be adopted by smart city projects; b) eight key dimensions of evaluations were extracted, setting a holistic performance framework relevant to SCCs; c) a detailed evaluation process including pre-determined criteria and city-needs feedback was applied to shortlist the KPI pool, leading to a ready-to-be-used, project-specific list of 63 KPIs and d) KPIs were sorted and analyzed in different granularity levels to further facilitate the monitoring procedure. The experiential procedure presented in this study can be easily adapted to the needs of every smart city project, serving as a recommendation guide.

Identification and prioritization of stage-level KPIs for BOT projects – evidence from Turkey

PurposeThe purpose of this paper is to identify and prioritize key performance indicators (KPIs) that can be used for stage-based performance assessment of build-operate-transfer (BOT) projects.Design/methodology/approachThis research was conducted through focus group discussions and face-to-face questionnaires. Firstly, stage-level KPIs for BOT projects were identified by conducting a literature survey. The list of KPIs that can be used for measuring performance at different stages of a BOT project was finalized by conducting focus group discussions with 12 participants. The data related to the importance of identified KPIs were collected via a face-to-face questionnaire in which 30 high-level managers participated. Based on these data, KPIs were prioritized considering eight different stages of a BOT project by using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).FindingsThe research findings reveal that 63 stage-level KPIs can be used for measuring the performance of BOT projects at eight different stages, which are “feasibility study and preliminary plan,” “announcement and submission of application,” “evaluation and selection,” “negotiation and signing of concession agreement,” “design,” “construction,” “operation” and “transfer.” The most important KPIs were determined as “comprehensiveness of project technical feasibility,” “detailed tendering procedure,” “effectiveness of concessionaires' technical knowledge/capability evaluation,” “good relationships between government and concessionaire,” “technology transfer,” “effectiveness of quality control,” “effectiveness of facility management” and “effectiveness of hand-back management” for each stage. The findings can be used by companies to evaluate performance at each stage of a BOT project and, if necessary, take the necessary actions for performance improvement at the stage level.Research limitations/implicationsThe main limitation is the size of the sample, which represents the perspectives of 30 Turkish high-level managers on KPIs in BOT projects. Besides, the selected method, namely, TOPSIS, does not provide quality measures related to the outputs; therefore, it is difficult to see the inconsistencies among the experts.Practical implicationsThe study findings will help in devising appropriate performance evaluation practices for BOT projects to overcome the shortfalls of the existing practices and systems proposed in the literature and help in achieving the superior performance while developing infrastructure through the BOT route.Originality/valueThis paper proposes a process-based approach for measuring the performance of a BOT project considering eight different stages. It fills a research gap in the public–private partnership literature by focusing on stages rather than phases. The results can be used by practitioners to establish stage-level performance management systems for BOT projects.

Key performance indicators for Smart Campus and Microgrid

Attempts have been made to enhance the smartness of a campus from various perspectives such as obtaining real-time statistics on reduction in energy consummation, increased percentage of power generation from renewable resources, improved campus traffic flow, air quality, and monitoring buildings health etc. However, to the best of our knowledge a comprehensive list of Key Performance Indicators (KPIs) for smart campus and smart microgrid is yet to be developed. In this work, we study smart cities, smart microgrids, city ranking systems, and literature on smart campuses for extracting a list of relevant KPIs as well as propose new KPIs where needed to support the main business process of a university campus. Accordingly, 74 KPIs have been listed which are measurable, achievable, relevant, and time phased. We divide these KPIs among 15 service areas consisting of smart microgrid, smart buildings, intelligent transportation, economic growth, smart governance, propagation model, pollution & waste management, climate resilience, water resource management, financial sustainability, entrepreneurial leadership, enhanced teaching and learning, security and privacy mechanisms, health care provision, and public participation. In addition, we present an example of a university campus from energy consumptions and carbon footprint perspectives. We also highlight the need for long distance, low power communication architecture to support 2-way communication of microgrid and infrastructure with devices installed at remote locations. The aim of this work is to establish a mechanism that allows campus management to monitor the smartness of their university campus in general, and microgrid in particular.

Development of triple bottom line indicators for life cycle sustainability assessment of residential bulidings

The growth of the building sector represents the progress of civilizations. There are environmental, social and economic implications, impeding the sustainability performance of buildings. A holistic life cycle sustainability assessment (LCSA) framework is inevitable to address the integrated sustainability performance of residential buildings. This paper aims to develop triple bottom line indicators to assess the sustainability performance of buildings, including sustainability objectives, impact categories and key performance indicators (KPIs) to implement in the life cycle sustainability assessment framework. The indicators have been developed through the consensus survey involving area experts from four key stakeholders' categories including, government and Engineers Australia, academia, practitioners, and structural engineers. A list of KPIs was compiled through a literature review, followed by an online census survey to collect feedback from the participants in terms of relevance and importance of initally selected KPIs. Secondly, a modified list of triple bottom line (TBL) KPIs and their weights was developed based on respondents’ feedback. Finally, the threshold values were assigned to the selected KPIs and the LCSA framework was tested using a hypothetical case study. The LCSA framework using these scientifically valid KPIs would assist stakeholders to assess the sustainability performance of residential buildings and to identify the hotspots for proposing well-informed industry strategies in Western Australia.

A MIXED INTERVAL TYPE-2 FUZZY BEST-WORST MACBETH APPROACH TO CHOOSE HUB AIRPORT IN DEVELOPING COUNTRIES: CASE OF IRANIAN PASSENGER AIRPORTS

Hub airports are the ones that model networks in which most journeys go via a few central points. Famous hub airports deliver positive social and environmental impact to the communities along with economic effects. This paper is about to investigate indicators related to hub performance excellence from various angles, considering leading hub airports performance while determining the priorities in order to help airports especially in developing countries to find the way of progress. A list of Key Performance Indicators (KPIs) is prepared from the literature, which is prioritized using Best-Worst Method (BWM). The weights of these criteria are specified via application of interval type-2 fuzzy BWM. Then using five most important criteria, MACBETH (Measuring Attractiveness by a Categorical Based Evaluation TecHnique) ranking approach is used to analyse 19 Iranian international airports and find the most appropriate one for being hub airport. The results show Kish airport with the International Civil Aviation Organization (ICAO) code “OIBK” is prior to other airports and can be chosen as the hub airport that means Iran airports holding company is suggested to focus more investments in this airport to gain fastest possible benefits of an international hub airport.

Key performance indicators for the evaluation of academic and research laboratory facilities

PurposeThe purpose of this paper is to develop a comprehensive list of key performance indicators (KPIs) that can be employed in determining the functional performance of academic and research laboratory facilities.Design/methodology/approachThe study employed a two-phase approach. First, a thorough literature review was conducted to identify potential KPIs specific to the performance of laboratory facilities. This was followed by an assessment of the KPIs by 12 respondents including 6 professionals and 6 users. The KPIs were arranged in the form of a questionnaire survey containing response columns for agree/disagree, and importance rating scales for evaluation. The relative importance index values were also computed.FindingsThe result of the study was a comprehensive list of 161 KPIs classified into nine categories including: space, access/circulation, utilities and waste, environmental conditions, furniture, appearance/finishes/image, communications, storage within the space and special building features. These KPIs were perceived to be at varying levels of importance by the respondents.Originality/valueThough previous studies developed KPIs for the performance of facilities, these KPIs are not universal. Thus, the originality of this study is in its identification of a comprehensive set of KPIs unique to the design, evaluation and management of research and academic laboratory facilities.

KEY PERFORMANCE INDICATORS OF A CREWING COMPANY ACTIVITY

Topicality. Enterprises must inculcate modern economic tools in the management practice to provide efficiency of their work. The universal set of parameters that can be used equally well for all kinds of activity without the exception is absent. The complexity of forming financial results of a crewing company activity and necessity of taking into account the specific features of its functioning require to research the key parameters of effectiveness concerning specifically crewing activity. Aim and tasks. Identification of performance indicators (qualitative and quantitative) of the company, which will cover all aspects of the crewing company activity without any exceptions, taking into consideration the specifics of their activities and the peculiarities of formation of incomes and expenses for various types of crewing. Research results. Most companies use traditional techniques to assess the competitive position on the market. Besides today, more and more attention is paid to valuing the company. In our view, to assess the work of a crewing company, it is necessary to focus on the so-called key performance indicators (KPIs). They are an element of a balanced system of parameters, which should have a set of indicators that can clearly identify the company's goals and the extent to which they are achieved. In particular, it is necessary to use both financial and non-financial indicators, to determine quantitative and qualitative KPIs, as well as perspective and actual indicators. A list of KPIs must be developed for each employee of a crewing company. Their number should not exceed 5-7 indicators. They all should be simple, understandable, clear and achievable. All KPIs should be known to all employees in order to ensure proper transparency, stimulate competition and motivate employees to develop. Conclusion. Today, more emphasis is placed on traditional quantitative financial indicators that reflect the results achieved. In turn, promising indicators as KPIs provide a benchmark for company employees to the place of application of effort and reflect key improvements in the work of the crewing company. Therefore, it is necessary to make efforts and develop promising KPIs in order to determine what factors and how they affect the actual KPIs. This will help identify the specific services and processes that are key factors to the success of the company.