Agility Index Research Articles

Modelling Neutrosophic Agility Index: A Mathematical Framework

Introduction: This study uses a fuzzy-based methodology that combines agility score and certainty functions to assess the values of learning mathematics quickly. The paper emphasises the need of understanding the value of learning mathematics through tools like the Neutronosophic Agility Index in addition to discussing the usage of surveys to assess it. Objective: The aim of this study is to evaluate the values of learning mathematics’ agility by employing a fuzzy based methodology that integrates score and certainty functions. Finding out how agile the values are now and looking into ways to make them more agile are the objectives. Method: A paradigm for assessing the values of learning mathematical skills agility is established using a neutrosophic fuzzy method. The agility score is calculated to evaluate the level of agility. Additionally, the article recommends carrying out additional research using particular performance assessment standards. Result: The findings show that, according to its agility score, the benefit of knowing mathematics is "fairly agile". It implies the possibility of more progress by putting improvement recommendations into practice. It also emphasises the relationship between performance, agility, and organisational culture, underscoring the necessity for additional research employing a variety of fuzzy methodologies. Conclusion: In conclusion, the study is represented by agility scores corresponding to specific values. Self-confidence, with an agility score of 0.5377, ranks first, indicating reasonable confidence in decision-making. Perseverance (score: 0.5356) reflects resilience and determination. Decision-making (score: 0.5239) suggests a balanced approach. Tolerance (score: 0.5185) relates to handling diversity. Higher Order Thinking (score: 0.5166) involves cognitive abilities. The average agility score (0.5265) falls within the ‘Fairly Agile’ range. Enhancing these values can lead to higher agility categories.

Exploring the impacts of IT service management on the business agility index: an AHP simulation-based decision-making approach

Exploring the impacts of IT service management on the business agility index: an AHP simulation-based decision-making approach

Psychometric Properties and Norming of Learning Agility Index: Online Assessment to Measure Fluid Intelligence

The Learning Agility Index (LAI) is an online assessment used to assess Fluid Intelligence, the pure intellectual speed and power evaluated by the ability to solve new problems creatively. Using a battery of five sub-tests, LAI can deliver a global trainability quotient (GTQ) indicating how well an individual performs in a training context. This study aims to analyze psychometric properties and norming for LAI. The research data comprised 28,980 subjects from the online test database for employees selection owned by PT Global Talentlytica Indonesia. The research approach used in this study is classical test theory. Psychometric property analysis utilized Cronbach's alpha reliability estimation method and collected validity evidence based on internal structure. The reliability analysis results showed that the five sub-tests had strong reliabilities with Cronbach's alpha values ranging from 0.92 to 0.97. Confirmatory factor analysis confirmed the measurement model of the Learning Agility Index with CFI 0.988, RMSEA 0.022, and SRMR 0.20. The intelligence levels represented by the measurement results were divided into five levels, ranging from “below average” to “far above average.” These findings prove that LAI is a reliable and valid online assessment for measuring fluid intelligence in the context of employees selection or evaluation.

Assessment framework for workforce agility in higher education institutions

PurposeThe higher education sector has been lately facing new challenges. The ease and speed with which the workforce adapts to these changes determine their agility level. This study attempts to develop a conceptual model to measure workforce agility in higher education.Design/methodology/approachAn extensive literature review revealed limited research on workforce agility assessment. This study addresses the research gap by developing a workforce agility assessment framework and testing the model in a higher education institution (HEI). The study applied the fuzzy logic method for the assessment.FindingsThe computed value of the fuzzy-workforce agility index (3.72, 5.27, 6.86) indicates that the HEI chosen for the assessment is Agile. The fuzzy performance importance index helped identify the six-weak attributes that require immediate attention and improvement.Practical implicationsThe proposed framework would help the institution's management understand the current agility level of their workforce and take corrective actions to improve the identified weak attributes.Originality/valueThe study has contributed to the literature of workforce agility assessment by creating a conceptual model for evaluating workforce agility in higher education. This model can be applied to any HEI.

How to make intelligent automation projects agile? Identification of success factors and an assessment approach

PurposeOrganizations are fast adopting new technologies such as automation, analytics and artificial intelligence, collectively called intelligent automation, to drive digital transformation. When adopting intelligent automation, there is a need to understand the success factors of these new technologies and adapt agile software development (ASD) practices to meet customer expectations. The purpose of this paper is to explore the success factors of intelligent automation and create a framework for managers and practitioners to meet dynamic business demands. Total interpretive structural modeling (TISM) framework is a suitable approach to integrate quantitative measurement with qualitative semi-structured interviews capturing the context of the individual organization environment.Design/methodology/approachThis paper identified agility factors and their interrelationships using a TISM framework. TISM results were validated using a one-tailed t-test to confirm the interrelationships between factors. Furthermore, the agility index of a case project organization was assessed using a graph-theoretic approach (GTA) to identify both the triggering factors for agility success and improvement proposals.FindingsResults showed that leadership vision, organization structure and program methodology were driving factors. The TISM model was validated statistically and the agility index of the intelligent automation case project organization was calculated to be79.5%. Here, a GTA was applied and the triggering factors for improvement of the agility index were identified.Research limitations/implicationsThe limitations of the study are described along with the opportunities for future research as the field evolves through the rapid innovation of technology and products.Practical implicationsThe increasing role of digital transformation in enterprise strategy and operations requires practitioners to understand how ASD practices must be planned, measured and/or improved over time through the implementation of automation, analytics and artificial intelligence programs. The TISM digraph provides a framework of hierarchical structure to organize the influencing factors, which assists in achieving organizational goals. This study highlights the driving factors which contribute to the success of intelligent automation projects and project organizations.Originality/valueThis is a first attempt to analyze the interrelationships among agility factors in intelligent automation projects (IAP) using TISM and the assessment of the agility index of a case IAP organization using a GTA.

Operational coordination and mass customization capability: the double-edged sword effect of customer need diversity

PurposeThis study aims to explore how operational coordination affects mass customization capability (MCC) via organizational agility, the double-edged sword effect of customer need diversity and the moderating effect of competitive intensity based on dynamic capabilities perspective.Design/methodology/approachThis study examines the research hypotheses using hierarchical regression analysis by collecting data from 277 Chinese firms.FindingsThe results reveal that organizational agility partially mediates the impacts of operational coordination on product-oriented and service-oriented MCC. Customer need diversity is positively related to operational coordination, whereas negatively moderates the relationship between operational coordination and organizational agility. Moreover, competitive intensity negatively moderates the relationship between organizational agility and service-oriented MCC.Research limitations/implicationsThis study mainly used perceptual scales to measure organizational agility. There is a need to measure agility through Agility Index which consists of features' combination that enables agility.Practical implicationsManagers would thus do well to integrate business activities with supply chain partners and strive to foster an agile organization. Additionally, managers should take the leadership to assess the customer need and invest time and resources to respond to it when needed even though the response may be difficult.Originality/valueAlthough the importance of MCC in meeting personalized customer needs has been recognized, whether and how customer need diversity affects MCC remains unclear. This study provides a framework to study the relationships between customer need diversity and MCC, which deepens our understanding of how to enhance MCC to respond to diverse customer needs.

A foundational framework for agile enterprise architecture

PurposeThe application of agility principles and methodologies on Enterprise Architecture (EA) is a promising field. This paper aims to provide an in-depth study of the Agile Enterprise Architecture (AEA) by studying EA practitioners’ perspectives to propose a foundational framework for AEA.Design/methodology/approachThe authors formulate a foundational framework that defines the AEA motivators, enablers and blockers using the agile manifesto as one of the AEA enablers where a total of 156 EA stakeholders with at least one year of experience in enterprise architecture were surveyed, and a set of hypotheses was analyzed and tested based on the proposed framework. The authors also develop a quantitative method to evaluate the agility index of the EA based on the introduced framework.FindingsThe research results show with significance that enterprise architects perceive positively the application of the agility methodologies on the enterprise architecture. This perception is primarily affected by the enterprise size, the EA dependency and the agile methodologies awareness. The findings also indicate that AEA is primarily motivated by the Business and IT Change Ready and Responsive EA. Finally, an EA Agility Index (EAAI) was designed to assess the agility application of the EA based on the three forces, i.e. motivators, enablers and blockers.Research limitations/implicationsBecause of the chosen research approach and the sample size, the research results may lack generalizability. Also, EAAI designed was not thoroughly tested.Practical implicationsThe paper includes implications for the design and development of an EA Agility Index, and the need to increase the awareness of the agility methodologies to overcome the blocker of the unfamiliarity with the agile methodologies implying that the current business models in enterprise must be more aligned with the agile methodologies.Originality/valueWhile there are efforts to develop AEA frameworks, one of the major findings of the literature review conducted is that there is evident research gap in the literature on the perception and associated factors of the EA stakeholders on having an agile enterprise architecture. This paper attempts to fill this gap.

An integrated identification approach of agile engineering characteristics considering sensitive customer requirements

Under the effects of internal factors and the external environment, some customer requirements can be extremely sensitive to change; these are known as sensitive requirements. These requirements drive the identification and design of the relevant engineering characteristics. This study defines such characteristics as agile engineering characteristics (AECs), which are crucial for redesigning products and prolonging their service life but attract limited research and practice attention. The research question of identifying the product AECs is answered in this study, and three key issues are solved in the proposed methodology. First, the contribution of product engineering characteristics to customer requirements is calculated using an orthogonal experimental design, and the optimal level combination of engineering characteristics to satisfy the customer requirements is determined through the analysis of variation. Subsequently, the relative importance of engineering characteristics is calculated based on data envelopment analysis. Next, an agility index is defined by integrating the customer satisfaction degree, the relative importance degree of engineering characteristics, and the variation of the level of engineering characteristics, to identify the AECs. Finally, based on the identification of the AECs of an electric vehicle air-conditioning heat pump scroll compressor, the results are analysed and compared to illustrate the feasibility and effectiveness of the proposed method.

Assessment of organizational agility in response to disruptive innovation: a case of an engineering services firm

PurposeThe purpose of this paper is to develop a framework to manage the strategy to counter disruptive innovation by identifying stronger attributes and key strategic areas for improvements in an engineering services context with less freedom to orchestrate product innovation. The authors also validate the combined use of multi-grade fuzzy, Importance-Performance Analysis (IPA) and gap analysis in developing the strategy to mitigate turbulence.Design/methodology/approachThe paper presents a framework using a combination of Dynamic Capabilities and Organizational Agility to develop the strategy. The study uses data gathered from a 60-member engineering project team working on an Aircraft Engine Controller design to identify 50 attributes and the related importance and performance ratings. The research study is designed using a three-tier approach. First, multi-grade fuzzy is utilized to measure the overall firm response agility index. In the second step, the IPA is used to analyze the strength and weaknesses of the firm and to identify the attributes where the firm needs to focus. In the past step, gap analysis is used to prioritize the identified attributes. The findings are validated by panel discussions with a different group of experts from the project team and action points were arrived at.FindingsThis research work finds that the firms’ response agility index of 6.97 is comparable to that of the Original Equipment Manufacturers (OEMs) from previous literature, but still needs a better agility score to effectively counter turbulence from disruptive innovations. It also identifies seven key areas for improvement and their relative priority to effectively improve the response agility by utilizing the least number of resources, the reasons for the gap and the mitigation strategy to close the gap. The findings highlight a few key differences between an engineering services firm in comparison to OEMs and Software Services firms.Practical implicationsThe findings help the practitioners with a comparative agility score of an engineering services firm, and an effective way of measuring agility, identify key focus areas and prioritize the actions using a simple set of data that could be collected regularly to keep track of the improvements. The provided strategic framework to improve the agility score can be used for continuous improvement.Originality/valueThis paper contributes to the existing literature by developing a framework for outsourcing services companies to cope with the turbulence by using dynamic capabilities and organizational agility. It also adds to the literature by extending the validity of IPA and gap analysis in making strategic decisions in an industrial set-up.

Assessment of Team Agility in Internet of Things Projects

Internet of Things (IoT) projects are special kind of Research and Development (R&D) projects. Team agility plays an important role in determining the agility of IoT project organizations. Thus the paper aims to evaluate the team agility level of IoT projects using multi-grade fuzzy and Importance Performance Analysis (IPA).The team agility index is computed using multi-grade fuzzy for the case IoT project is 7.63 which is between the ranges (6-8) which specifies as ‘Highly Agile’. The IPA is applied to identify the weaker attributes to improve the team agility of case IoT project. The framework can be used on a periodic basis to help IoT project managers to improve continuously their team agility level.

Assessment of Organizational Agility in Software Projects

In the current context of business, agility refers to the dynamic capability of an organization to adapt itself to market and industry demands in a productive and cost-effective manner. Organizational Agility focuses on both stability and dynamism, is more people centric in its approach towards efficient output through faster decision cycles and leveraging technology to manage risks and produce the desired output for its customers. This paper aims at evaluating the organizational agility level from the perspective of people and culture in a software project organization using the multi-grade fuzzy approach. Findings from the case study indicate that the case organization agility index is 6.79 which specifies as ‘agile’. Importance Performance Analysis is used to identify the weaker attributes of case organization. Furthermore, recommendations for the improvisation of weaker attributes of the case organization are discussed.

WITHDRAWN: Agility assessment in retail store environment using multi-grade fuzzy

Abstract Agility in store environment inside the mall is characterized by the ease with which the retail stores are able to anticipate the market changes and proactively restructures its interior environment, their practices, technological capability and process to compete the market. Assessing the agility would help the retail stores to understand their current position and capabilities. This study focuses on assessing retail store agility using multi-grade fuzzy approach. The overall agility index was calculated 7.29 which indicate that the case retail store is agile and has areas for improvement. To identify the weaker attributes for improvement an Importance Performance Analysis (IPA) was conducted. The results found that the weaker attributes of the case retail store were merchandise, seasonal offers, ease of access to the location and zoning inside the store. The proposed framework helps for retail store managers to evaluate their agility level and focus on weak attributes to improve agility level.

Who is agile? An investigation of the psychological antecedents of workforce agility

Understanding the precursors of workforce agility is crucial for organizations that wish to detect and foster agility in their employees. This research investigates the psychological antecedents of workforce agility, and develops a scale to measure them. First, in a qualitative study, we interviewed 11 professionals to identify the core processes of workforce agility, and the psychological resources needed to support them. Second, through a quantitative study of 808 members of the US‐based Microworkers online labor market, we developed and tested our agility index, a psychometric measure of the potential for agility, which was based on the resources identified in the first study. We believe our research offers managers valuable insights into the psychological antecedents of workforce agility, which will help them assess, train, and guide employees.

Assessing the Readiness Level of Healthcare for Implementing Agility Using Fuzzy Logic Approach

An agile strategy in healthcare would authorize organizations to provide efficient, customized and standard service on time at an optimized cost. To implement agility, the management of the healthcare organization needs to know the mechanisms and how to make the whole organization ready for change process. Thus, the current study assesses the readiness level of healthcare utilizing fuzzy logic approach to implement agility. The conceptual readiness model is framed with five enablers, twenty criteria and fifty-six attributes. The proposed model is applied in to a case hospital to assess the readiness level. The Fuzzy readiness for the implementation of agility index (FRAI) and fuzzy performance importance index (FPII) are computed to determine the readiness level of the case hospital and its weaker attributes in the implementation of agility. FRAI is computed as average ready with (3.00, 4.78, 6.56), and FPII identifies 15 weaker attributes from 56 attributes. It constructs the conceptual model which analyses the current readiness of healthcare and weaker attributes are denoted and required corrective actions should be carried by the management of healthcare organization to improve the readiness. The continuation of assessment readiness model over a period of time would help to improve the readiness level of healthcare for agile implementation.

Firefly enabled agility assessment in manufacturing systems

The manufacturing processes have now evolved from dinosaur type of enterprise to lizard type known as agile manufacturing. Agility can be enhanced with some trivial change in firm's processes. In this study, an effort has been made to obtain the agility index of two different firms with their currently implemented agile enablers'. The two industries were identified based on the demand pattern, i.e., seasonal and volatile demand. The methodology of AHP is used to obtain effectiveness of the agile enablers'. These effectiveness values are given as input to the FA to obtain the agility index in terms of 'response time' between market and industry. Based on the results, the firms' can focus on the enabler with least response time to improve business performance through appropriate strategies. The response time of fashion firm is less than that of core-manufacturing firm. Hence fashion firms are more agile than core firms.

Firefly Enabled Agility Assessment in Manufacturing Systems

The manufacturing processes have now evolved from dinosaur type of enterprise to lizard type known as agile manufacturing. Agility can be enhanced with some trivial change in firm's processes. In this study, an effort has been made to obtain the agility index of two different firms with their currently implemented agile enablers'. The two industries were identified based on the demand pattern, i.e., seasonal and volatile demand. The methodology of AHP is used to obtain effectiveness of the agile enablers'. These effectiveness values are given as input to the FA to obtain the agility index in terms of 'response time' between market and industry. Based on the results, the firms' can focus on the enabler with least response time to improve business performance through appropriate strategies. The response time of fashion firm is less than that of core-manufacturing firm. Hence fashion firms are more agile than core firms.

Analytical Research on Agility Index of a Manufacturing System

Agility level of any organisation portrays the degree of flexibility of the organisation in responding to customer needs. Hence, knowledge of agility level assumes its importance for developing the competitive strategies for any organisation including the manufacturing firms. In this line monitoring the level of agility and flexibility in a manufacturing organisation could be considered to be an important element for meeting the business objectives. However, proper evaluation of this agility metrics becomes deceptive to define owing to its vague nature and application in non-manufacturing related systems. In this regard an attempt has been made in this research to develop agility index of 3 types of plants. The results of this study revealed the Polyethylene plant has the highest agility index of 9.51 out of the three case plants. The results also revealed that the agility index of the Olefins plant is 7.32 and that of the Polypropylene plant is 6.37. Plants with a high agility index reflects its higher degree of agility level.

Lower rotational inertia and larger leg muscles indicate more rapid turns in tyrannosaurids than in other large theropods.

SynopsisTyrannosaurid dinosaurs had large preserved leg muscle attachments and low rotational inertia relative to their body mass, indicating that they could turn more quickly than other large theropods.MethodsTo compare turning capability in theropods, we regressed agility estimates against body mass, incorporating superellipse-based modeled mass, centers of mass, and rotational inertia (mass moment of inertia). Muscle force relative to body mass is a direct correlate of agility in humans, and torque gives potential angular acceleration. Agility scores therefore include rotational inertia values divided by proxies for (1) muscle force (ilium area and estimates of m. caudofemoralis longus cross-section), and (2) musculoskeletal torque. Phylogenetic ANCOVA (phylANCOVA) allow assessment of differences in agility between tyrannosaurids and non-tyrannosaurid theropods (accounting for both ontogeny and phylogeny). We applied conditional error probabilities a(p) to stringently test the null hypothesis of equal agility.ResultsTyrannosaurids consistently have agility index magnitudes twice those of allosauroids and some other theropods of equivalent mass, turning the body with both legs planted or pivoting over a stance leg. PhylANCOVA demonstrates definitively greater agilities in tyrannosaurids, and phylogeny explains nearly all covariance. Mass property results are consistent with those of other studies based on skeletal mounts, and between different figure-based methods (our main mathematical slicing procedures, lofted 3D computer models, and simplified graphical double integration).ImplicationsThe capacity for relatively rapid turns in tyrannosaurids is ecologically intriguing in light of their monopolization of large (>400 kg), toothed dinosaurian predator niches in their habitats.

Agility in small sized pump manufacturing companies - an exploration in an Indian scenario

Today, companies are required to imbibe agility characteristics. Agility of a company refers to its capability in producing innovative products by reacting quickly in accordance with the dynamic demands of the customers. In this paper, a research has been reported in which the agility level prevailing in three small size pump manufacturing companies located in India was measured by using a model called 20 criteria agile manufacturing measurement model. By using this model, the agility of these companies was measured by using a measure called agility index. The agility index of one of them was found to be higher than that of the other two. Further, it was explored to identify the weak agility criteria practiced in the three small size pump manufacturing companies. This exploration indicated that poor adoption of technology prevents the small sized pump manufacturing companies from speeding up of the agile manufacturing journey in an Indian scenario.

Design of a Wireless Sensor System with the Algorithms of Heart Rate and Agility Index for Athlete Evaluation.

Athlete evaluation systems can effectively monitor daily training and boost performance to reduce injuries. Conventional heart-rate measurement systems can be easily affected by artifact movement, especially in the case of athletes. Significant noise can be generated owing to high-intensity activities. To improve the comfort for athletes and the accuracy of monitoring, we have proposed to combine robust heart rate and agility index monitoring algorithms into a small, light, and single node. A band-pass-filter-based R-wave detection algorithm was developed. The agility index was calculated by preprocessing with band-pass filtering and employing the zero-crossing detection method. The evaluation was conducted under both laboratory and field environments to verify the accuracy and reliability of the algorithm. The heart rate and agility index measurements can be wirelessly transmitted to a personal computer in real time by the ZigBee telecommunication system. The results show that the error rate of measurement of the heart rate is within 2%, which is comparable with that of the traditional wired measurement method. The sensitivity of the agility index, which could be distinguished as the activity speed, changed slightly. Thus, we confirmed that the developed algorithm could be used in an effective and safe exercise-evaluation system for athletes.