Search Results (441)

Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will collaborate with learning algorithms in the Neural Adaptive Artificial Intelligence Leadership Model, which is informed by the transformational literature on leadership and socio-technical systems, as well as the literature on algorithmic governance. We assessed the model with thirty in-depth interviews, system-level traces of behavior, and a verified survey, and we explored six hypotheses that relate to algorithmic delegation and ethical oversight, as well as human judgment versus machine insight in terms of agility and performance. We discovered that decisions are made quicker, change is more effective, and interaction is more vivid where agile practices and good digital understanding exist, and statistical tests propose that human flexibility and definite governance augment those benefits as well. It is single-industry research that contains self-reported measures, which causes research to be limited to other industries that contain more objective measures. Practitioners are provided with a practical playbook on how to make algorithmic jobs meaningful, introduce moral fail-safes, and build learning feedback to ensure people and machines are kept in line. Socially, the practice is capable of minimizing bias and establishing inclusion by visualizing accountability in the code and practice. Filling the gap between the theory of leadership and the reality of algorithms, the study provides a model of intelligent systems leading in organizations that can be reproduced. Full article

This study proposes a fuzzy logic-based approach to better manage supply chain uncertainty and improve decision-making flexibility. The developed framework categorizes supply chain activities into procurement, production, distribution and reverse logistics and integrates Lean, Agile, Resilient, and Green (LARG) KPIs within a hierarchical structure. The tool was implemented using Microsoft Excel^TM to enhance usability for practitioners. To test its applicability, the model was applied to a real case study. The results show that lean and resilient practices are consistently well-established across all supply chain phases, while agility and green practices vary significantly depending on the operational area—particularly between internal function (i.e., production and reverse logistics) and external ones (i.e., procurement and distribution). These findings help to better understand how the LARG capabilities are distributed across the different operational areas of the supply chain and offer practical guidance for managers seeking targeted performance improvement. Although the numerical results are context-specific, the framework’s adaptability makes it suitable for diverse supply chain environments. Full article

Decision management is the systems engineering life cycle process for making program/system decisions. The purpose of the decision management process is: “…to provide a structured, analytical framework for objectively identifying, characterizing and evaluating a set of alternatives for a decision at any point in the life cycle and select the most beneficial course of action”. Systems engineers and systems analysts need to inform decisions in a digital engineering environment. This paper describes a Decision Analysis Data Model (DADM) developed in model-based systems engineering software to provide the process, methods, models, and data to support decision management. DADM can support digital engineering for waterfall, spiral, and agile development processes. This paper describes the decision management processes and provides the definition of the data elements. DADM is based on ISO/IEC/IEEE 15288, the INCOSE SE Handbook, the SE Body of Knowledge, the Data Management Body of Knowledge, systems engineering textbooks, and journal articles. The DADM was developed to establish a decision management process and data definitions that organizations and programs can tailor for their system life cycles and processes. The DADM can also be used to assess organizational processes and decision quality. Full article

The 5G network’s commercialization has revealed challenges in providing customized and personalized deployment and services for diverse vertical industrial use cases, leading to high cost, low resource efficiency and management efficiency, and long time to market. Although the 5G core network (CN) has adopted a service-based architecture (SBA) to enhance agility and elasticity, the radio access network (RAN) keeps the traditional integrated and rigid architecture and suffers the difficulties of customizing and personalizing the functions and capabilities. Open RAN attempted to introduce cloudification, openness, and intelligence to RAN but faced limitations due to 5G RAN specifications. To address this, this paper analyzes the experience and insights from 5G SBA and conducts a systematic study on the service-based RAN, including service definition, interface protocol stacks, impact analysis on the air interface, radio capability exposure, and joint optimization with CN. Performance verification shows significant improvements of service-based user plane design in resource utilization and scalability. Full article

Background/Objectives: Generating real-world data on the efficacy of multidisciplinary care in cardiometabolic risk management is essential to ensure that guidelines are both applicable and effective, especially in public healthcare settings, where organizational structures may impede healthcare professionals’ agility. This study aimed to generate data on patient follow-up and cardiometabolic risk management during the early years of a public university family medicine group in Québec (Canada) that provides multidisciplinary care to adults with cardiometabolic conditions, in order to evaluate the implementation and effectiveness of its care model. Methods: This was a retrospective longitudinal study. Patients treated at the clinic from 31 January 2020 (clinic opening) to 8 May 2024 (n = 96) were invited to consent to the use of their medical data for research. Results: A total of 52 patients consented and were included in the study. Upon entry at the clinic, >90% of patients had anthropometry and blood pressure (BP) measured, but plasma glucose and lipids were assessed among 50% and 79% of patients, respectively. A total of 36 patients completed the personalized multidisciplinary care program. No evidence of associations between the total number of appointments or appointments with the registered dietitian specifically with changes in BMI, waist circumference, and BP was found. However, each pharmaceutical intervention was associated with a −0.51 cm (95%CI: −1.03, 0.02; p = 0.06) change in waist circumference and a −1.49 mm Hg (95%CI: −2.56, −0.43, p = 0.01) change in diastolic BP. Conclusions: These data highlight the challenges of implementing a research-oriented clinic within Québec’s public healthcare system. Full article

In the management of cholangiocarcinoma, effective biliary drainage and accurate diagnosis are vital to allow further treatment. Confirmation of tissue diagnosis and molecular characterization is also required to guide future treatment options including surgery and chemotherapy as well as the possible use of personalized treatments that target specific mutations present within individual tumours. Initial CT or MRI scans may be followed by endoscopic ultrasound (EUS) or endoscopic retrograde cholangiopancreatography (ERCP) to obtain tissue samples. However, these methods often fall short due to difficulty in accessing entire bile duct strictures. SpyGlass cholangioscopy can improve diagnosis, yet may fail to provide sufficient tissue for molecular characterization. Here we present a perspective on the development of snake-like agile robots with integrated optical imaging and Raman spectroscopy. These robots could improve the mapping of the biliary tree and the precision of biopsy collection and allow tissue analysis in situ, as well as facilitating stenting to restore the flow of bile. A multidisciplinary approach that brings together clinicians, pathologists, and engineers is required to develop these new robotic technologies and improve patient outcomes. Full article

Disaster waste management (DWM) has gained much attention due to the issues associated with the enormous amount of disaster waste generated by natural disasters. However, moving beyond ad hoc and champion-based take-up by practitioners, there is generally a lack of momentum towards mainstreaming such DWM practices to achieve resilient outcomes. This study aims to explore the characteristics of DWM practices, drawing on the lived experiences of industry practitioners and government decision-makers. An interpretive case study method was used to investigate how local government organisations could readily engage in effective DWM processes using the “Resilient disaster management framework” previously established by the research team. Insights include a lack of documented plans for DWM and at best a moderate focus on recovery processes for disaster waste. With these issues counterproductive to community resilience outcomes, there is an urgent need to better manage disaster waste, which we propose can be enabled and supported through DWM plans. The extended ‘resilient DWM framework’ proposed in this study provides a useful reference to prepare practical, agile, and comprehensive DWM plans. Full article

As organizations become increasingly projectified, safeguarding the resilience of project professionals and teams emerges as a critical organizational challenge. Adopting a systems lens, we investigate how agile mindsets and agile practices function as systemic antecedents of resilience at the individual and team levels. Eleven semi-structured interviews with experienced project managers, product owners, and team members from diverse industries were analyzed through inductive thematic coding and system mapping. The findings show that mindset supplies psychological resources—self-efficacy, openness and a learning orientation—while practices such as team autonomy, iterative delivery and transparent communication provide structural routines; together they trigger five interlocking mechanisms: empowerment, fast responsiveness, holistic team dynamics, stakeholder-ecosystem engagement and continuous learning. These mechanisms reinforce one another in feedback loops that boost a project system’s adaptive capacity under volatility. The synergy of mindset and practices is especially valuable in hybrid or traditionally governed projects, where cognitive agility offsets structural rigidity. This study offers the first multi-level, systems-based explanation of agile antecedents of resilience and delivers actionable levers for executives, transformation leaders, project professionals, and HR specialists aiming to sustain talent performance in turbulent contexts. Full article

In the context of accelerating digital transformation and growing sustainability imperatives, entrepreneurial ecosystems increasingly rely on open innovation and strategic collaboration to foster resilient, knowledge-driven growth. This study aims to examine how leadership behaviors and strategic alliances interact as enablers of sustainable innovation across macro (systemic), meso (organizational), and micro (individual) levels. To achieve this, this study employs a literature review, supported by bibliometric analysis, as its core methodological approach. Drawing on 86 influential publications from 1992 to 2024, two major thematic streams emerge: leadership dynamics in entrepreneurial settings and the formation and governance of strategic alliances as vehicles for innovation. The findings underscore the pivotal role of transformational and ethical leadership in cultivating trust-based inter-organizational relationships, facilitating digital knowledge sharing, and catalyzing sustainable value creation. Simultaneously, strategic alliances enhance organizational agility and innovation capacity through co-creation mechanisms, digital platforms, and crowdsourcing, especially in small and medium-sized enterprises (SMEs). This paper highlights a mutually reinforcing relationship: effective leadership strategies empower alliances, while alliance participation enhances leadership capabilities through experiential learning in diverse, digitalized environments. By bridging leadership theory, open innovation practices, and digital transformation, this study offers critical insights for entrepreneurs, managers, and policymakers seeking to drive inclusive and sustainable innovation within interconnected global markets. Therefore, this study provides practical guidance for business leaders aiming to strengthen alliance performance through adaptive leadership and for policymakers seeking to foster innovation ecosystems through supportive regulatory and institutional frameworks. Full article

Global supply chains have faced unprecedented disruptions in recent years, ranging from the COVID-19 pandemic to geopolitical tensions and climate-induced shocks. These events have exposed structural vulnerabilities in operational models overly optimized for efficiency at the expense of resilience and sustainability. This conceptual paper proposes an integrated framework linking resilience enablers, post-pandemic operational strategies, and sustainability outcomes. Through a synthesis of the interdisciplinary literature across operations management, sustainability science, institutional theory, and organizational behavior, we develop typologies of operational responses—including agile, lean–green, circular, and decentralized models—and connect them to broader Sustainable Development Goals (SDGs). Drawing on systems thinking and the Triple Bottom Line framework, we present a conceptual model that outlines causal relationships between resilience drivers, adaptive operational strategies, and long-term sustainable performance. The paper further discusses policy implications for public and private sectors, offering insights for global sustainability governance. We conclude by outlining a research agenda to empirically test and refine the model through multi-method approaches. This study contributes to theory by reconceptualizing sustainable operations in the context of compound global disruptions and offers a normative direction for future scholarship and practice. Full article

This study explores the application potential of a lean–Agile hybrid method in complex construction project management. By integrating Scrum iterative development, the Last Planner System, and a BIM collaboration platform, a dual-engine model is established to optimize the dynamic priority mechanism (MoSCoW 2.0) and interface conflict entropy algorithm (ICE model). Through a combination of theoretical and practical approaches, the study elucidates the implementation pathway of this hybrid method and evaluates its benefits in enhancing project efficiency, reducing waste, and accelerating digital transformation. The study provides a replicable management framework for the construction industry and proposes a blockchain-based decentralized knowledge management framework based on blockchain technology. Full article

The continuous evolution of technology compels higher education leaders to adapt to VUCA (volatile, uncertain, complex, and ambiguous) and BANI (brittle, anxious, non-linear, and incomprehensible) environments through innovative strategies that ensure institutional relevance. While VUCA emphasizes the challenges posed by rapid change and uncertain decision-making, BANI underscores the fragility of systems, heightened anxiety, unpredictable causality, and the collapse of established patterns. Navigating these complexities requires agility, resilience, and visionary leadership to ensure that institutions remain adaptable and future ready. This study presents a bibliometric analysis of digital academic leadership in higher education transformation, examining empirical studies, reviews, book chapters, and proceeding papers published from 2014 to 2024 (11-year period) in the Web of Science—Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI). Using CiteSpace software (version 6.3. R1-64 bit), we analyzed 5837 documents, identifying 24 key publications that formed a network of 90 nodes and 256 links. The reduction to 24 publications occurred as part of a structured bibliometric analysis using CiteSpace, which employs algorithmic thresholds to identify the most influential and structurally significant publications within a large corpus. These 24 documents form the core co-citation network, which serves as a conceptual backbone for further thematic interpretation. This was the result of a multi-step refinement process using CiteSpace’s default thresholds and clustering algorithms to detect the most influential nodes based on centrality, citation burst, and network clustering. Our findings reveal six primary research clusters: “Enhancing Academic Performance”, “Digital Leadership Scale Adaptation”, “Construction Industry”, “Innovative Work Behavior”, “Development Business Strategy”, and “Education.” The analysis demonstrates a significant increase in publications over the decade, with the highest concentration in 2024, reflecting growing scholarly interest in this field. Keywords analysis shows “digital leadership”, “digital transformation”, “performance”, and “innovation” as dominant terms, highlighting the field’s evolution from technology-focused approaches to holistic leadership frameworks. Geographical analysis reveals significant contributions from Pakistan, Ireland, and India, indicating valuable insights emerging from diverse global contexts. These findings suggest that effective digital academic leadership requires not only technical competencies but also transformational capabilities, communication skills, and innovation management to enhance student outcomes and institutional performance in an increasingly digitalized educational landscape. Full article

Background: This study conceptualizes supply chain ambidexterity through two capabilities, supply chain adaptability and agility. Accordingly, it investigates the impact of supply chain adaptability and agility on green product innovation (GPI) and supply chain sustainability in Jordanian manufacturing firms. It also examines the mediating role of GPI in these relationships. The study is based on dynamic capabilities theory (DCT) as the theoretical foundation. Methods: A quantitative research approach was employed, with data collected from 346 supply chain managers using a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for analysis. Results: The findings reveal that supply chain adaptability does not directly influence sustainability but significantly enhances GPI, which positively impacts sustainability. Supply chain agility, however, directly and significantly improves both GPI and sustainability, highlighting its importance in achieving sustainable supply chain performance. Additionally, GPI mediates the relationship between supply chain ambidexterity and sustainability, reinforcing its role as a key enabler of eco-friendly supply chain management. These findings provide theoretical and managerial implications. Conclusions: The study extends DCT by confirming the role of GPI in linking supply chain ambidexterity to sustainability. Managers should prioritize agility, invest in sustainable products, and adopt green practices to enhance competitiveness. Full article

Defective phononic crystals (PnCs) have garnered significant attention for their ability to localize and amplify elastic wave energy within defect sites or to perform narrowband filtering at defect-band frequencies. The necessity for continuously tunable defect characteristics is driven by the variable excitation frequencies encountered in rotating machinery. Conventional tuning methodologies, including synthetic negative capacitors or inductors integrated with piezoelectric defects, are constrained to fixed, offline, and incremental adjustments. To address these limitations, the present study proposes an active feedback approach that facilitates online, wide-range steering of defect bands in a one-dimensional PnC. Each defect is equipped with a pair of piezoelectric sensors and actuators, governed by three independently tunable feedback gains: displacement, velocity, and acceleration. Real-time sensor signals are transmitted to a multivariable proportional controller, which dynamically modulates local electroelastic stiffness via the actuators. This results in continuous defect-band frequency shifts across the entire band gap, along with on-demand sensitivity modulation. The analytical model that incorporates these feedback gains has been demonstrated to achieve a level of agreement with COMSOL benchmarks that exceeds 99%, while concurrently reducing computation time from hours to seconds. Displacement- and acceleration-controlled gains yield predictable, monotonic up- or down-shifts in defect-band frequency, whereas the velocity-controlled gain permits sensitivity adjustment without frequency drifts. Furthermore, the combined-gain operation enables the concurrent tuning of both the center frequency and the filtering sensitivity, thereby facilitating an instantaneous remote reconfiguration of bandpass filters. This framework establishes a new class of agile, adaptive ultrasonic devices with applications in ultrasonic imaging, structural health monitoring, and prognostics and health management. Full article

One of the fundamental challenges in managing software and information technology projects is monitoring and predicting project status at the end of each sprint, release or project. Agile project management has emerged over the past two decades, significantly impacting project success. However, no comprehensive approach based on the features of this approach has been found in studies to monitor and predict the status of a sprint, release or project. This study aims to develop a data-driven approach for predicting the status of software projects based on agility features. For this purpose, 22 agility features were first identified to evaluate and predict the status of projects in four aspects: Endurance, Effectiveness, Efficiency, and Complexity. The findings indicate that the aspects of Effectiveness and Efficiency have the greatest impact on project success. Additionally, the results show that features related to team work, team capacity, experience and project objectives have the most significant impact on project success. An artificial neural network algorithm was then used, and a model was developed to predict project status, which was optimized using the Neural Architecture Search algorithm with a 93 percent accuracy rate. The neural network model was interpreted using the SHapley Additive exPlanations (SHAP) algorithm, and sensitivity analysis was performed on the important components. Finally, the behavior of the projects in each category was analyzed and evaluated using the Apriori algorithm. Full article