Selection Of Key Performance Indicators Research Articles

Towards sustainable manufacturing: A comprehensive analysis of circular economy key performance indicators in the manufacturing industry

In the pursuit of sustainable development, the concept of Circular Economy (CE) has emerged as a transformative alternative to the traditional linear economic model characterized by take, make, use, and dispose practices. However, there is a growing recognition of the limitations of the linear economy in addressing contemporary global challenges, leading to a pressing need for a more regenerative approach. This study aims to explore and analyze Key Performance Indicators (KPIs) associated with the circular economy, particularly focusing on the manufacturing industry, to provide a valuable guide for enterprises looking to integrate CE principles effectively and reinforce sustainability. The novelty of this study lies in its comprehensive examination of KPIs that embrace sustainability's triple bottom lines - environmental, economic, and social dimensions. The systematic selection of relevant KPIs and the utilization of Social Network Analysis (SNA) to identify the most influential CE KPIs within the manufacturing industry add depth to the research. By identifying and upgrading significant KPIs representing various facets of CE development, this study contributes to a more meticulous understanding of how enterprises can measure their progress towards circularity. In each of the triple bottom lines of sustainability, five significant KPIs were recognized and upgraded to the second assessment process, where these 15 KPIs are analyzed using SNA to obtain 5 aggregated KPIs. The comprehensive analysis of the obtained fifteen KPIs culminates in aggregated CE indicators, primarily strategies and initiatives (SI), material efficiency (ME), productivity of remanufacturing (OR), technology investment (ROR), and eco-innovation (EI). The aggregated Key Performance Indicators (KPIs) displayed an extreme value of the weighted average index attributed to strategies and initiatives KPI with a value of 0.067. These aggregated KPIs provide a practical framework for manufacturers to assess and optimize their circular economy practices. It's essential to note that all binary values incorporated in the proposed approach are derived from an extensive literature review. These values may vary depending on the specific objectives of individual manufacturing firms or focus groups. As a result, the proposed approach is adaptable to diverse manufacturing industries, allowing customization to suit the unique input criteria of each firm or group. Significantly, the current work emphasizes the influential role of manufacturers in shaping a sustainable future in alignment with development goals.

Utilizing Design Objectives and Key Performance Indicators as a Means for Multi-Species Building Envelopes

Population growth, urbanization, and climate change have significantly contributed to environmental degradation, posing severe consequences for humans and other species. By integrating ecological objectives with human-centric goals, a path towards a sustainable, multi-species future is possible. Current sustainable design principles have shown positive environmental impacts by addressing human-centric objectives such as enhancing green infrastructure, energy efficiency, thermal comfort, and more. However, the incorporation of multi-species design criteria remains unresolved. This paper proposes a conceptual framework in which human-centric and ecological design objectives are defined and associated through the selection of key performance indicators (KPIs) represented by numerical thresholds. But, while the objective-KPI relationship is an established path in architectural design, the same does not apply for preserving and promoting biodiversity. The proposed conceptual framework identifies, defines, and associates the relevant objective-KPI relationships for all stakeholders and becomes the basis for evaluating the project computationally. Such an approach is currently lacking.

The concept and the state of research on the performance of family businesses

Purpose: This study's primary goal is to present the theoretical concept of family enterprises. Specifically, the results of earlier studies and the issues facing this field of research now will be described. The article also examines the underlying impacts that family control has on business management in order to fill the research gap left by earlier studies on the performance differences between family and non-family enterprises. A thorough analysis of the literature revealed that family firms place equal value on non-financial performance as they do on financial performance. Design/methodology/approach: The study's survey focuses on critical analysis methods used in the literature. Critical theoretical analysis will also be accompanied by comparative, analytical and monographic methods implied to draw conclusions on further research directions in the family business sector. Findings: The current work makes a significant contribution by broadening the theoretical foundation for family business research. Therefore, a sound foundation for the explanation of distinctive strategic management components may be established using the behavior-oriented approach, stakeholder theory, target composition, and balanced scorecard approach. Research limitations/implications: Unconfirmed theories may be examined more closely, particularly in a modified setting. Practical implications: The findings of this theoretical study are not only important for business research but also for business practice. The study is primary addressed to the top management of family and non-family businesses. Moreover, potential investors, banks and consultants could benefit from the results of this study. Originality/value: This study aims to provide a better understanding of the relationship between the variables of family influence, goal setting and selection of key performance indicators and organizational performance and business success. That is how a contribution can be made to the ongoing discussion about the success of family businesses and its underlying factors. Keywords: Family business, Goal setting, Business performance, Small and medium-sized enterprises. Category of the paper: literature review

Environmental-Economic Analysis for Decarbonising Ferries Fleets

Several countries heavily depend on their domestic ferries, the decarbonisation of which are required following the prevailing and forthcoming international and national carbon reduction targets. This study aims to conduct an environmental-economic analysis to identify the impact of three decarbonisation measures, specifically, hybridisation, liquified natural gas (LNG) and methanol use, for two ferries of different size of a developing country fleet. The study is based on several methodological steps including the selection of key performance indicators (KPIs), the pre-processing of acquired data to identify representative operating profiles, the environmental and economic KPIs calculation, as well as the comparative appraisal of the investigated measures. The required investments for decarbonising the whole domestic fleet of a case country are subsequently estimated and discussed. All the three investigated measures have the potential to reduce CO2 emissions, however, not beyond the IMO 2030 carbon emissions reduction target. This study provides insights to the involved stakeholders for supporting their decisions pertinent to the domestic ferries sector decarbonisation.

Selection of Key Performance Indicators for Your Sport and Program: Proposing a Complementary Process-Driven Approach

ABSTRACT Key performance indicators (KPIs) are commonplace in business and sport. They offer an objective means to link data and processes with performance outcomes. Yet, their application in sports performance, particularly team sports, is not without issue. Here, we review 4 key issues relating to KPI application in team sports; lack of a universal definition, complexity of performance, drifting from on-field performance goals with off-field targets, and agency issues across different key stakeholders. With these issues relating to sports performance KPIs in mind, we propose a complementary approach to help practitioners focus on implementing the conditions that create performance environments and opportunities for success in a complex sporting environment. Ongoing process trackers (OPTs) are quantifiable measures of the execution of behaviors and processes that create the environments, cultures, and conditions for successful performance outcomes. This approach equips sports science practitioners with key questions they can ask themselves and their team when starting to select and use OPTs in their program.

Steam allocation for SAGD: Multi-pad multi-criteria short and long-term real-time performance management

Optimizing steam allocation is critical for long-term performance goals in Steam-Assisted Gravity Drainage (SAGD) recovery. The steam supply mainly contributes to the economics, steam chamber conformance, greenhouse gas emissions, and ultimate bitumen recovery. Therefore, SAGD real-time optimization (RTO) must balance steam chamber development and economics to achieve long-term goals. However, in RTO, general-purpose optimization algorithms decide based on short-term responses, unlike long-term optimization processes. Using economic Key Performance Indicators (KPI) such as Net Present Value (NPV) in a single objective, the RTO determines the smallest amount of steam that results in the highest economic returns. Injecting a small amount of steam reduces steam chamber heat loss, growth, and long-term ultimate bitumen recovery. As a result, a suitable selection of critical KPIs is required to balance the development and economics of the steam chamber.This work presents a study of multiple combinations of SAGD KPIs for a multi-pad real-time steam allocation. The KPI combinations used in this study are NPV, cumulative steam-oil-ratio (cSOR), recovery factor (RF), and average pad temperature (aveTemp). A Box-Jenkins-based data-driven model simulates the SAGD recovery process, and a first principle simulator is used as a substitute for an actual reservoir. The Alternating Direction Method of Multipliers (ADMM) is proposed for multi and many-objective optimization for real-time steam allocation across multiple pads. A compromise programming approach guides the decision-makers choice of the optimum control setpoints of the non-dominated solutions on each horizon. At the end of three and half years of RTO, the optimal KPI combination is ranked based on the aggregated performance of NPV, cSOR, and RF of SAGD multi-pad steam allocation. A synthetic Western Canadian reservoir model with four pads and 33 well pairs developed from publicly available data is used for this study.The aggregated performance of this study's results showed that joint optimization of an economic and a steam chamber growth KPIs of two is better than a combination of three or four. The choice of the joint economic and steam chamber growth KPIs depends on the average pad temperature at the start of RTO to achieve optimal fluid balance in the long term. cSOR or NPV with RF joint KPI performs optimally at average pad temperatures above 90 °C, while cSOR or NPV with aveTemp below 90 °C at the start of RTO to achieve injected and produced fluid balance. Optimum economic return, recovery, and greenhouse gas emission of the SAGD process are achieved with cSOR KPI as the primary economic objective.

Key nitrogen and phosphorus performance indicators derived from farm-gate mass balances on dairies

Efficient management of N and P on dairy farms is critical for farm profitability and environmental stewardship. Annual farm-gate nutrient mass balance (NMB) assessments can be used to determine the nutrient-use efficiency of farms, set efficiency targets, and monitor the effect of management changes with minimal inputs required. In New York, feasible N and P balances have been developed as benchmarks for dairy farm NMB, alongside key performance indicators (KPI) that serve as predictors for high NMB. Here, 3 yr of NMB data from 47 farms were used to evaluate the main drivers of N and P balances and identify additional KPI. From the 141 farm records, 26% met both the feasible N balances per hectare and per megagram of milk produced. For P, 53% of the records met both benchmarks. Imports, rather than exports, drove NMB primarily by feed and fertilizer purchases, consistent with earlier findings. Linear regression analysis showed that a selection of KPI currently used, particularly animal density, nutrient-use efficiency, and the amount of home-grown feed, explained a large portion of variation in NMB. Heifer-to-cow ratio and the relative proportion of various forage crops may provide further insight into the drivers of feed and fertilizer imports and ultimately farm-gate NMB. This study provides avenues toward a better assessment of whole-farm nutrient management and means for farms to communicate progress to stakeholders and consumers.

Leveraging thoughtful quality metric selection for individual and system improvements: the atypical category and use of dashboards.

Quality management is integral to the practice of cytopathology, especially given the heavily manual workflows and expanding ancillary testing requirements inherent to the cytopathology laboratory. Monitoring quality data like turnaround time, specimen unsatisfactory rates, and diagnostic category utilization rates allows for better understanding of performance with opportunities for targeted improvement if there are variations from that which is expected. However, there are costs to quality monitoring including the time and resources needed, and, in already taxed systems, quality management risks being viewed as just another box to check. While there are mandated quality metrics that must be collected by cytology laboratories, thoughtful selection of key performance indicators can be of tremendous benefit in helping to better understand complex laboratory processes and directing improvement endeavors where needed. The following short communication is a discussion on quality management in the cytopathology laboratory from 3 Cytopathology Quality Management Directors. The discussion focuses on monitoring the atypical reporting category with an emphasis on how trending and visualizing quality metrics can provide laboratories with key data.

КЛЮЧОВІ ПОКАЗНИКИ ЕФЕКТИВНОСТІ (КПЕ) ДЛЯ ОЦІНКИ ПЕРСПЕКТИВИ ВНУТРІШНІХ БІЗНЕС-ПРОЦЕСІВ НА СУЧАСНОМУ ВИРОБНИЦТВІ

The article defines the methodology of process control based on key performance indicators (KPI) in the business environment and its importance for the management of manufacturing facilities. The important aspects of the implementation of the system for measuring the efficiency of manufacturing and related to manufacturing areas of enterprises are described. It is noted that such control will contribute to timely response to threats of reduced production efficiency and further adjustment of the development strategy. The main goal of the article is the selection and justification of those indicators that are relevant for modern production and allow to assess its effectiveness. The authors substantiated that the process control method based on KPI is one of the most common methods of managing business units. Which involves finding and implementing a system of key performance indicators for most important elements of the manufacturing process. The details of some basic KPIs and their interdependence are described in the article. The main focus of authors is on the selection of appropriate KPIs and their impact on the goals achievement. Authors stating, that for the successful implementation of KPE, key factors are simplicity, comprehensibility and transparency for employees responsible for achieving of defined metrics. Equally important are the methods of evaluating the performance of related or supporting functions of the enterprise (personnel department, building maintenance service, information technology department, etc.). The authors emphasize the important criteria of the KPE system, which will allow to objectively evaluate effective work, manage it and motivate personnel. It is also noted that KPIs should have an impact on the financial motivation of employees, that’s why transparency and reach-ability are critical for their effective implementation. Equally important is the ability to track progress in achieving goals, create a foundation for an objective assessment of effectiveness, make operational decisions, compare results and form a responsible environment.

Spatial decision support system for low-carbon sustainable cities development: An interactive storytelling dashboard for the city of Turin

The evaluation of city sustainability considering economic, social, and environmental subsystems is a fundamental field in urban planning. It directly affects the quality of urban economies toward efficiency and innovation with minimal resource consumption. This requires the use of appropriate SDSS (Spatial Decision Support Systems) which take into account inclusive approaches to engage local stakeholders. The study aims at developing an interactive dashboard to aid decision-makers in sustainable urban planning processes to co-create future transition strategies with the employment of spatialized outputs. The dashboard enables the evaluation of the sustainability performance of the city by the selection and assessment of KPIs (Key Performance Indicators) as a part of the MOLOC European Interreg Project. The study proposes a multidisciplinary GIS-based framework for the spatial evaluation of KPIs which can support scenario development by providing targeted suggestions for local development planning. Outcomes represent a useful interactive SDSS tool within a storytelling dashboard which is combinable with multi-criteria decision models at the city scale. The spatial distribution of results evidences the strengths and weaknesses of the city and facilitates the implementation of low-carbon action plans, avoiding unnecessary investments. The methodology illustrated was applied to the city of Turin as the case study, however, it can be implemented in other European urban contexts intending to achieve sustainable spatial planning since the methodological framework modulates to the territorial specificities of a place, always including all aspects of sustainability to be assessed.

Quality Performance Indicators Evaluation and Ranking by Using TOPSIS with the Interval-Intuitionistic Fuzzy Sets in Project-Oriented Manufacturing Companies

Project-oriented manufacturing companies aim to produce high-quality products according to customer requirements and a minimum rate of complaints. In order to achieve this, performance indicators, especially those related to product quality, must be measured and monitored by managers. This research proposes a fuzzy multi-criteria model for the selection of key performance indicators that are critical to product quality. The uncertainties in the relative importance of decision-makers, performance indicators, and their values are described by sets of natural language words that are modeled by the interval-valued intuitionistic fuzzy numbers. The assessment of the relative importance of the decision-makers and the determination of their weights are based on the inclusion comparison probability between the closeness intuitionistic fuzzy sets. The determination of the weights vector of performance indicators is based on the integration of an interval-value fuzzy weighted geometric operator and the inclusion comparison probability between the closeness intuitionistic fuzzy sets. TOPSIS expanded with interval-valued intuitionistic fuzzy numbers for ranking performance indicators is proposed. The developed model was tested on the real data collected from three manufacturing companies in the Republic of Serbia. Based on the obtained results, the top-ranked performance indicators were marked as critical for product quality and selected as quality key performance indicators.

AHP and SMART Criteria for KPI Selection in Higher Education

Identifying and choosing the most pertinent Key Performance Indicators (KPIs) has a crucial impact on decision making: if the wrong KPIs are measured, or if they are measured in the wrong way, the information may be misleading and the quality of decisions can be significantly affected. Choosing appropriate KPIs requires a deep understanding of the organization. Moreover, a successful selection of appropriate KPIs relies on a number of well-defined criteria. We propose in this paper a new approach to facilitate the structuring, and/or synthesis of a set of specific, measurable, attainable, realistic and timebased KPIs (SMART KPIs) based on the Analytic Hierarchy Process (AHP) method. The approach steps are illustrated and validated with a real case study. This case study is related to the candidates’ selection process in a Tunisian higher education institute.

A two-phase approach to efficiently support product recovery systems in a circular economy context

PurposeThe execution of product recovery strategies and the definition of an adequate system to manage its performance are crucial to move toward the employment of a successful circular economy (CE) concept. Defining strategies for the efficient management of product recovery requires product data that is difficult to obtain, making it harder to handle. However, efficient product recovery management can play a key role in shifting companies from a linear economy model to a more sustainable CE model, providing economic benefits and increasing customer satisfaction by recovering and adding value to the discarded product. Therefore, this study aims to provide better models to support decision-making and to evaluate product recovery performance.Design/methodology/approachThe present study highlights a comprehensive two-stage decision approach to identify and examine the relevant key performance indicators (KPIs) for performance improvement of an information facilitated product recovery system (IFPRS) in a CE context. In the first phase, a structural equation modeling (SEM) methodology is adopted to categorize the KPIs by employing exploratory factor analysis and measurement of the model fit is obtained using the confirmatory factor analysis. Further, in the second phase, the KPIs are ranked and prioritized on the basis of expert’s recommendations adopting fuzzy-technique for order of preference by similarity to ideal solution (FTOPSIS).FindingsEmpirical investigation is conducted by compiling data from an association of six decision-makers (DMs) and two DMs from a respective prospect. The results highlight that “Technology Capacity” is ranked as the highest and is the most prominent KPI for successful employment of IFPRS practices. The results of the study would benefit policy makers and company directors in the selection of KPIs based on their importance in a context of high competition and greater pressure to adopt sustainable practices in the management of their companies.Originality/valueAs far as the authors know, no study has been performed till date to identify and construct a structural KPIs model for IFPRS performance improvement in the context of CE. The paper, therefore, proposes a two-phase SEM-TOPSIS technique to measure the impact of KPIs which is a new integration in the existing literature. The results of the study would benefit policy makers and company directors in the selection of KPIs based on their importance in a context of high competition and greater pressure to adopt sustainable practices in managing their organizations.

Sustainable Development Model of EU Cities Compliant with UN Settings

Nowadays, the globally accepted UN concept of sustainable development (SD) is gradually transferred to the city level, including small and medium-sized cities. The implementation of SD settings requires regular measurement of developmental progress to monitor the level achieved in statics and dynamics, and to make strategic decisions for the next period. The existing urban SD indicator systems and indices are not well-suited for the monitoring of specific cities. Benchmarking algorithms and mathematical modelling procedures were applied to create a methodology and mathematical model for measuring the achieved urban SD level and to ensure the most objective selection and proportions of key performance indicators (KPIs) to be included in the model. The model (1) complies with the UN concept, (2) is usable for any EU city, (3) reflects the level of quality of life achieved, and (4) includes a limited number of KPIs related to municipal functionality. Mathematical computation of the (1) causality between the KPIs, (2) selection and proportions of KPIs, and (3) the general level of urban SD, as well as the reasonable combination of universality, accuracy, stability, and simplicity are strong advantages of the model. Using the published mathematical expressions of the model, calculation of the SD level does not require specific skills; the performed stability test also confirms that annual calibration of the model is not necessary. The index will help municipalities in planning and managing SD, and in the rational use of their usually limited resources. As a pilot project, SD level values are calculated for several cities.

Quantifying the value of on-farm measurements to inform the selection of key performance indicators for livestock production systems

The use of key performance indicators (KPIs) to assist on-farm decision making has long been seen as a promising strategy to improve operational efficiency of agriculture. The potential benefit of KPIs, however, is heavily dependent on the economic relevance of the metrics used, and an overabundance of ambiguously defined KPIs in the livestock industry has disincentivised many farmers to collect information beyond a minimum requirement. Using high-resolution sheep production data from the North Wyke Farm Platform, a system-scale grazing trial in southwest United Kingdom, this paper proposes a novel framework to quantify the information values of industry recommended KPIs, with the ultimate aim of compiling a list of variables to measure and not to measure. The results demonstrated a substantial financial benefit associated with a careful selection of metrics, with top-ranked variables exhibiting up to 3.5 times the information value of those randomly chosen. When individual metrics were used in isolation, ewe weight at lambing had the greatest ability to predict the subsequent lamb value at slaughter, surpassing all mid-season measures representing the lamb’s own performance. When information from multiple metrics was combined to inform on-farm decisions, the peak benefit was observed under four metrics, with inclusion of variables beyond this point shown to be detrimental to farm profitability regardless of the combination selected. The framework developed herein is readily extendable to other livestock species, and with minimal modifications to arable and mixed agriculture as well.

Do corporate social responsibility practices improve financial performance? A case study of airline companies

With the growing emphasis on corporate social responsibility (CSR) practices, airlines are beginning to question whether the implementation of CSR activities will increase costs or affect corporate financial performance. Some researchers argue that CSR is positively associated with corporate financial performance, while others oppose this view. This study tracked the environmental, social, and governance (ESG) performance indicators and the short-term financial performance of 30 airlines worldwide for five years with data from the Thomson Reuters Eikon ESG database. A multilevel quadratic growth model was used to investigate the impact of airlines’ disclosure of ESG performance indicators. The results revealed that in the initial stages of implementation of ESG-based practices, airlines demonstrate a downward trend in return on assets. However, it gradually increases after a period of incorporation and implementation. Based on this result, airlines should prioritize the selection of key performance indicators for the implementation of CSR toward sustainability.

A methodology for energy key performance indicators analysis

With the advent of the smart grid era, the electrical grid is becoming a complex network in which different technologies coexist to bring benefits to both customers and operators. This paper presents a methodology for analyzing Key Performance Indicators (KPIs), providing knowledge about the performance and efficiency of energy systems, focusing on the demand side. In the first stage of the methodology, the baseline KPIs are calculated. In the second stage, all KPIs are updated to be compared with the baseline ones. In fact, due to the dynamic nature of players in a smart grid, this methodology plays a crucial role in the performance assessment. Moreover, the proper definition and selection of KPIs is usually a challenging task since KPIs can be applied to evaluate diverse areas within a smart grid. Such areas include building energy efficiency, home communications, and smart metering deployment, just to mention a few. In the proposed methodology, the information obtained from a KPI can be driven to distinct aspects such as efficiency, environment, reliability, power quality, safety, security, or cost reduction. Through a case study from a real implementation of an energy system, we show how to assess energy consumption efficiency, thus improving energy management.

Framework to support the Data Science of smart city models for decision‐making oriented to the efficient dispatch of service petitions

The evolution of Smart Cities conveys continuous changes involving a great number of variables, which might hamper the development of evaluation tools and methodologies. Most of the metric models for Smart City are based on the selection of key performance indicators (KPI) according to the specific model objectives. As different organisations propose their own indicators generating different models, it is difficult to get a straightforward comparison among models. With the aim of dealing with this and other disadvantages, in this study, a framework based on the application of Data Science to the KPIs is proposed. This framework represents an infrastructure that goes through the treatment of Open Data, facilitating the evaluation of different models comparison intended for decision-making, and to the final stage of dispatching service reports. There are four components that integrate this framework (i) a tree structure to manage the KPIs; (ii) a designed JavaScript Object Notation document for service dispatch; (iii) Web applications for evaluations based on Smart People with four scenarios and; (iv) the infrastructure for reception and attention of reports.

Methodical Comparison of Alternative Powertrain Technologies for Long-Distance Mobility Using Germany as an Example

The main barriers to the wide acceptance of electric vehicles, such as the limited driving range or the high acquisition costs, are to be countered by various technology alternatives for the powertrain of the future. Promising developments include improved battery technologies, fuel cell technologies or a constant power supply of the vehicle while driving, for example through dynamic inductive charging. In this context, a holistic technology comparison would contribute to a comprehensive and understandable information situation by making the heterogeneous technological concepts comparable with regard to different evaluation criteria. Therefore, this work describes the basic assumptions of the proposed holistic comparison of alternative powertrain technologies for long-distance mobility. Relevant framework conditions are structured and a procedure for the evaluation of infrastructure expenditures is shown. Building on this, a selection of key performance indicators is defined and explained. The proposed KPI framework is applied to a passenger car in the economic area Germany. The results show that by using electrified roadways, ecological as well as economic advantages against other alternative powertrain designs can be derived.

Development of a longlist of healthcare quality indicators for physical activity of patients during hospital stay: a modified RAND Delphi study

ObjectiveTo develop a longlist of healthcare quality indicators for the care of hospitalised adults of all ages with (or at risk of) low physical activity during the hospital stay.DesignA modified...