Strategy Execution Research Articles

Financial forecasting models tend to be based on past market action trends. While such methods are very good under steady-state conditions, financial markets tend to change abruptly due to a change in liquidity, macroeconomic news, or leverage imbalances. Such models trained on past price action are too sluggish in responding to regime changes and therefore make the wrong and not to be relied upon predictions at the worst possible moment when accurate advice is most required. To address this challenge, this paper proposes a funding-rate driven routing model that dynamically switches between forecasting models depending on inferred market states. Funding rates and spot–perpetual basis signs are used to detect volatility and sentiment changes that cause shock regimes. In ordinary times, a light univariate LSTM is used to ensure forecasting efficacy. As volatility rises, the system pushes forecasting to a multi-source deep learning model that incorporates price, volume, and sentiment background. The architecture uses an edge–cloud hybrid execution strategy that compromises on latency, privacy, and scalability. This work demonstrates that, through the integration of regime detection and model switching, one can obtain more accurate forecasting without sacrificing computational responsibility. The model introduces an additional more adaptive, context-aware methodology for real-world financial forecasting environments that must operate under continuously varying risk levels.

Project management benefits from mathematical models that enhance resource allocation, scheduling, and cost efficiency while managing uncertainties. Although optimization is well-studied in construction, its use in sequencing petroleum project activities remains unexplored. This study develops an integrated simulation and optimization model to refine scheduling in refinery upgrades, minimizing project duration and addressing operational complexities. This paper presents a simulation-based optimization model designed to improve scheduling efficiency in a refinery upgrade project, where multiple tasks must be executed concurrently without extending the overall project duration. The model accounts for interdependencies among activities and resource requirements across internal and external work teams, ensuring optimal coordination and utilization. Developed using AnyLogic®, the simulation framework employs a random number generator to systematically explore task sequencing variations, leading to a refined execution strategy. The optimization results indicate a 20% reduction in the project's total duration. While resource utilization was assessed, it was not the model's primary objective. The utilization of resources has shown mixed outcomes; specific resources demonstrated an improvement of nearly 50%, yet the overall average utilization significantly decreased to just 0.12%, falling below the typical baseline of 40% observed in most resources. The model's performance and the optimization outcomes are analyzed, offering a decision-support tool for complex project management scenarios.

Blockchain technology has transformed decentralized data exchange and digital payments but the consistently high gas prices pose a significant challenge to its scalability and efficiency. This research explores the role of AI-driven gas price prediction and data compression methods on gas utilization in blockchain systems with special emphasis on Ethereum transactions. Using actual Ethereum transaction history, we compare the performance of compressed versus uncompressed payloads with three different compression algorithms: Zlib, Brotli, and Gzip. Beyond that, a linear regression model is also trained to forecast hourly gas Price fluctuations given past transaction history. The methodology includes thorough statistical analysis to provide accurate and reproducible results. Our results show that compressing text data over 141 bytes using the Zlib algorithm prior to making transactions on the Ethereum network decreases the amount of gas Used without altering system time. This validates the efficiency of combining data compression with gas price forecasting in minimizing transaction costs without affecting performance. Moreover, our study further encompasses investigation of actual gas Price trends and provides real-world insights for optimizing timing strategies for economic transaction execution. These results enhance the knowledge of Ethereum gas dynamics and provide valuable solutions for enhancing economic efficiency and resource utilization in applications based on blockchain. Future efforts will involve applying the framework to the Ethereum mainnet, using deep learning models for increased prediction accuracy, and adaptive compression dependent on network state and transaction size.

In today’s dynamic business environment, strategy implementation remains a critical challenge for organizations. This study examines the role of organizational culture in facilitating effective strategy execution. The research aims to explore how corporate culture influences strategic outcomes and provides a competitive advantage. A theoretical review was conducted, analyzing existing literature from a managerial perspective. The study identifies key cultural factors that impact the success of strategy implementation, emphasizing the need for alignment between corporate culture and strategic goals. Studies indicate that strategy implementation faces various challenges, and organizational culture plays a pivotal role in determining success (Nderitu et al., 2021). Additionally, Ritala et al. (2021) argue that strategy implementation is more effective in organizational cultures that empower employees to navigate execution challenges. Findings suggest that organizations fostering a strong, adaptive culture are more likely to overcome strategic hurdles and achieve their objectives. The study concludes that organizational culture is a fundamental determinant of strategy execution, offering managerial insights to enhance internal communication and employee engagement. By recognizing culture as a key driver of strategic success, organizations can optimize their performance and long-term sustainability. This research contributes to the ongoing discussion on strategy implementation by providing practical recommendations for managers and executives seeking to improve organizational effectiveness.

Agents often execute complex strategies, adapting their response to each input stimulus depending on past observations and actions. Here, we derive the minimal energetic cost for classical agents to execute a given strategy, highlighting that they must dissipate a certain amount of heat with each decision beyond Landauer's limit. We then prove that quantum agents can reduce this dissipation below classical limits. We establish the necessary and sufficient conditions for a strategy to guarantee quantum agents have energetic advantage, and illustrate settings where this advantage grows without bound. Our results establish a fundamental energetic advantage for agents utilizing quantum processing to enact complex adaptive behavior.

This study examines the impact and role of Yazdibandi painting on Iranian architectural decorations. First, Yazdibandi painting and its features are introduced and then the impact of this type of decoration on Iranian architecture is investigated. This study emphasizes the cultural and artistic relationship between Yazdi painting and Iranian architecture, and examines the influential factors and its role in beautifying and decorating buildings¬Finally, this article discusses the importance of preserving and promoting this valuable art to preserve the cultural identity and Iranian architecture, and examines the executive strategies for preserving and expanding the Yazdi Bandi painting in Iranian architecture, and in addition, shows how the Yazdi Bandi dome was formed and executed

The modern service atmosphere, characterized by value co-creation between employees and customers, raises the strategic importance of the employees. For better service delivery employee engagement and satisfaction with the firm is necessary, which can be attained by internal marketing. Though internal marketing is widely understood for its role in evolving a customer-oriented, service-focused staff and is constantly associated to positive outcomes like employee satisfaction and commitment, the literature suffers from three significant gaps such as empirical categorization of specific internal marketing practices, shortage, insufficient research validating Internal marketing’s role as a Job Resource, and most important, a failure to study internal marketing as a potential Job Demand linked to the health impairment process. This study addresses these deficiencies by examining the dual effects of internal marketing in a novel approach using the Job DemandsResources (JD-R) paradigm. For this purpose, the current study used a comprehensive review to explore interrelated literature in different research databases. The study applied search strings, inclusion, and exclusion criteria to find related articles, which resulted in more than forty papers were found. By examining internal marketing's dual ability to function as a resource (supporting well-being and positive outcomes) and a demand (perhaps leading to burnout and value co-destruction), this study advances theoretical understanding and practical expertise. The results provide organisations with a critical understanding of the factors that contribute to the success or failure of internal marketing strategies, which can be used to guide strategy execution.

This article presents a stimulation plan for higher brain functions (HBF)—gnosias, praxias, language, and executive functions—aimed at enhancing academic performance in university and school contexts. Based on a neuroeducational approach, it integrates perceptual, motor, linguistic, and executive strategies that promote cognitive development, emotional self-regulation, and meaningful learning. The plan includes functional activities such as multisensory perceptual training, fine motor tasks adapted to the academic environment, structured written production, academic planning techniques, and mindfulness practices. These interventions are grounded in principles of neuroplasticity and seek to consolidate complex cognitive skills through structured educational experiences. It is concluded that systematic stimulation of HBF in educational settings can improve students' autonomy, organization, and academic performance, offering a practical tool for professionals in education, psychology, and occupational therapy.

ESCAN: Efficient GPU sharing for cascade neural network inference.

Facial aging is a multifaceted process arising from changes in skin quality, soft-tissue volume, underlying bony anatomy, and the cumulative impacts over time of factors such as expressive animation, environmental exposures, and gravity. Although historically facial rejuvenation focused primarily on surgical correction of tissue descent, enhanced understanding of volume loss as a major contributor to aging has led to the widespread adoption of soft-tissue fillers as a nonsurgical adjunct-or stand-alone treatment-for signs of facial aging. These treatments are popular with patients due to their low risk profile; minimal downtime; avoidance of scarring; and, often, reversibility. The modern aesthetic surgeon must develop strategies for managing patients across their lifetime, integrating nonsurgical and surgical approaches while maintaining natural-appearing results. This includes understanding how to plan filler for longevity and safety, modifying filler placement in previously treated areas, determining optimal timing for surgical intervention, and managing the transition between different treatment modalities. The integration of these various approaches requires not only product and technical expertise but also careful attention to patient education and long-term planning. This article provides a comprehensive framework for managing facial aesthetic patients throughout their treatment journey, with particular focus on the role of hyaluronic acid fillers at different life stages. We present strategies for assessment, treatment selection, and technical execution across different age groups and anatomical zones, supported by long-term case examples. Special attention is given to the interaction between injectable fillers and surgical procedures, as well as considerations for maintaining natural-appearing results over time.

Comparison of students' use of cognitive and metacognitive strategies between live demonstration and complementary immersive virtual reality simulation in fundamental skills learning: A mixed-methods study.

The COVID-19 pandemic exposed the cruise line industry to an unprecedented crisis. Recovery required sustained discretionary effort from employees, simultaneously balancing safety concerns and extreme financial hardship. However, not all firms in the industry were affected equally. From January 2019 to January 2025, among the three dominant players in the industry, Norwegian Cruise Lines (NCLH) and Carnival Cruise Lines (CCL) saw their stock prices drop by approximately half. During the same period, Royal Caribbean Cruise Lines (RCL) achieved extraordinary stock market performance, more than doubling their 2019 valuation. This inductive study explores whether generous executive pay increases awarded during the COVID-19 crisis may have diminished managers’ abilities to engage in authentic leadership (AL). Conceptual findings raise questions about whether the absence of rigorous AL may undermine employee motivation, resulting in depressed firm performance. Emergent themes primarily conform with the rent extraction and signaling views of executive compensation. Little support for the efficient contracting view is detectable. Inauthentic executive messaging and perceived executive opportunism at NCLH and CCL were associated with reduced employee motivation and poor share price performance, despite a full market rebound. In contrast, RCL’s more congruent executive actions and communications were accompanied by a stronger recovery aided by higher employee productivity. This analysis contributes to the AL literature by illustrating how compensation practices can constrain authentic communication and leadership efficacy in crisis situations. Implications for corporate governance, organizational resilience, and leadership development are discussed.

This study investigates the contribution provided by inclusive leadership and business culture management in establishing inclusion and flexibility mechanisms and thereby facilitating the inclusion of veterans in the work force. Carrying out a survey among Ukrainian companies and comparative data on selected sectors, it gives an indication on the principal challenges confronting organizations and sets out basic conditions for success in generating inclusive business cultures. Under the endorsement of the Cultural Integration and Inclusive Resilience System (CIIRS), in my research I confirm that development and training activity supplemented by cultural management practices and leadership behaviors are capable of producing workplace inclusion, raising human capital, and obtaining a competitive advantage. While many strengths of veterans in terms of reliability, flexibility, and leadership are documented, ongoing systemic deficiencies are apparent in their practical application. Data obtained from Poltava Drilling Company, Beiken Energy Ukraine, and DTEK Pavlogradugol JSC reflect a lack of systematic development of leadership, narrow inclusion plans, and deficient psychological support. The CIIRS approach offers a systemic way of bridging the gaps by fostering leadership activism, building psychological safety, and aligning cultural management toward sustained inclusion and adaptability. From a practical perspective, the study presents CIIRS as a framework usable by both business organizations and government institutions seeking to develop their diversity initiatives, educational access, leadership accountably, and adaptability in the workplace. Through blending inclusive leadership philosophies and management of business culture into the organizational infrastructure, CIIRS guides organizations in shifting from compliance-driven meeting expectations in matters of diversity to execution of strategies sustaining long-term inclusion and flexibility. The methodology benefits veterans as well as helps build inclusive, robust, and competitive organizations in post-crisis environments. The paper's contribution is in framing CIIRS as a new conceptual model of workplace inclusion of veterans. Where previous work considered veteran recruitment as business social responsibility or compliance, CIIRS reframes inclusion as a long-term issue of workplace culture management and resilience. Through linking survey evidence and diversity, equity, and inclusion (DEI) research, the paper shows how veteran recruitment can be a wellspring of organizational flexibility, competitiveness, and long-term success through efficacious strategic inclusion.

This study empirically analyzes the market entry, survival, and growth strategies of early-stage FinTech startups in the context of accelerated digital transformation following the COVID-19 pandemic. A focus group interview (FGI) was conducted with three founders, three accelerators (AC), and three venture capitalists (VC). The findings reveal that customer problem definition, execution-based strategies, regulatory responses, financing methods, and ecosystem collaboration function in an integrated manner. Moreover, under the oligopolistic structure dominated by large platform companies, startups were found to pursue survival through collaboration strategies. By examining execution strategies and ecosystem structures from the dual perspectives of investors and founders, this study provides practical implications for policy design and the improvement of private investment linkage models.

The exponential growth of mobile device connectivity and mission-critical operational dependencies has transformed airports into exceptionally demanding wireless environments requiring comprehensive infrastructure modernization. This technical review presents the complete architectural transformation of wireless networking infrastructure at a major aviation hub, addressing the fundamental inadequacies of legacy systems that prioritized coverage over capacity optimization. The initiative encompasses foundational design principles implementing centralized, policy-driven management frameworks that eliminate configuration complexity while ensuring scalable, resilient operations across complex terminal environments. Radio frequency engineering methodologies incorporate predictive modeling with empirical validation, high-density cell planning strategies, and advanced protocol implementations leveraging next-generation wireless standards to optimize spectrum utilization. The comprehensive Zero-Trust Security architecture leaves traditional perimeter-based designs behind, implementing micro-segmentation of the networks in line with certificate-based authentication and authorization models and advanced wireless intrusion prevention systems. Artificial intelligence-based network management solutions take the traditional model of reactive maintenance to a more proactive, predictive analytics and prediction, adding machine learning to analyze and measure behaviors, identify anomalies, and automate the process of remediation. Location-based services are also enabling the development of passenger-flow analytics and inventory tracking of assets through advanced signal processing. This reorganization produces significant economic impacts through new revenue lines, operational efficiencies, and the generation and design of new business models. At the same time, the advancements improve passenger experiences and generate positive, environmentally sustainable benefits through energy-efficient technology and infrastructure investments. The advancement in technology indicates how investment in technology can also positively contribute to achieving operational excellence, improving user experiences, and meeting responsible environmental targets in complex transport environments. As the Network Engineering Lead, I personally led the architectural design and end-to-end deployment of the airport wireless modernization project at the largest International Airport in California. I led a team of 15 network engineers, ensuring the successful execution of advanced RF engineering strategies, Zero-Trust security implementation, and AI-powered lifecycle management.

In 2019, the University of Arkansas for Medical Sciences (UAMS) embarked on a 10-year journey toward an ambitious vision to become the healthiest state in the region. The strategic plan, christened UAMS Vision 2029, outlining how that and other goals would be achieved, has been carefully tracked and monitored since it was launched. In this article, the authors describe how UAMS is executing on the plan; share progress and lessons learned through specific examples and model processes; and provide guidance and practical advice to health care leaders on strategy execution and monitoring.

Artificial Intelligence (AI) has emerged as a catalyst for achieving operational excellence in the twenty-first century. This study examines the impact of AI-enabled technologies on strategy execution, decision-making, and process efficiency across various global industries. Using an extensive literature review methodology, peer-reviewed studies from 2015 to 2024 were analyzed to identify the mechanisms through which AI contributes to performance improvement and sustainable competitiveness. The findings reveal that AI reinforces the seven pillars of operational excellence—strategy, metrics, culture, processes, methodology, project management, and tools—by embedding predictive analytics, automation, and real-time learning throughout the enterprise. Companies such as Toyota, Amazon, Siemens, and IBM demonstrate that when AI is aligned with human expertise and ethical governance, it enhances quality, speed, and innovation simultaneously. However, barriers such as data privacy, algorithmic bias, integration complexity, and workforce skill gaps continue to constrain widespread adoption. The paper argues that achieving operational excellence in the age of AI requires not only investment in digital infrastructure but also the cultivation of a data-driven culture, transparent leadership, and adaptive organizational design. The synthesis contributes to both theory and practice by presenting a comprehensive model that links AI capabilities to operational performance outcomes. Future research should empirically examine sector-specific success factors and develop quantitative frameworks to assess the long-term return on investment in AI-driven transformation initiatives. Artificial intelligence technologies have enabled the organizations.

ABSTRACT Digital transformation puts new demands to the companies’ information technology (IT) functions as traditional systems delivery approaches are no longer appropriate. The firms are thus also transforming their IT functions to new Operating Models (OMs; ITOMs). Despite the wide adoption of different ITOMs for various transformation initiatives and strategy execution, they have not been thoroughly studied in the information system literature. For example, there is no consensus on the ITOM definition, and little is known why and how the ITOMs are designed, how they execute IT/digital strategy, and what are the ITOM core components. In this paper, we systematically review both academic and practitioner literature to understand the discourses on ITOMs. Our findings show 5 ITOM themes and 13 components that foster the IT function transformation. The ITOM definition and the themes help researchers and practitioners to understand ITOM patterns and develop their own contextualized ITOM. We also propose that the ITOM design and implementation process, ITOM renewal challenges, or the management role in ITOM renewal need more research.

This study explores the influence of transformational leadership on organizational health and its implications for institutional accreditation quality management in private universities (PTS). In the context of global competition and the Fourth Industrial Revolution, leadership and organizational quality are crucial for higher education sustainability. A mixed-methods approach was employed, integrating quantitative data from structured questionnaires with qualitative insights through interviews. Respondents included lecturers and academic staff from private universities in West Java and Banten. Data analysis was conducted using Structural Equation Modeling (SEM) via SmartPLS to evaluate the relationships among variables. The findings demonstrate that transformational leadership significantly and positively influences both organizational health and the quality management of institutional accreditation. Key leadership dimensions—idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration—are instrumental in shaping a healthy academic environment. Moreover, organizational health acts as a mediating variable, enhancing the impact of leadership on accreditation outcomes through improved internal alignment, strategy execution, and organizational renewal. This study highlights the strategic role of transformational leadership in strengthening institutional quality frameworks. The integration of leadership and organizational health offers a practical paradigm for accreditation excellence. The findings are particularly relevant for resource-constrained private universities seeking competitive positioning in a globalized education landscape. Transformational leadership, supported by a healthy organizational environment, plays a critical role in advancing accreditation quality management in private universities. These insights offer theoretical and practical contributions to higher education leadership and quality assurance.

In this paper, we present an explicit solution for a continuous optimal trade execution problem, considering deterministic instantaneous, permanent, and temporary market impacts. Using a calculus of variations approach, we solve a system of ordinary differential equations. The unified model draws connections to benchmark optimal trade execution models proposed by Almgren and Chriss (2001. “Optimal execution of portfolio transactions.” Journal of Risk 3:5–40) and Obizhaeva and Wang (2013. “Optimal trading strategy and supply/demand dynamics.” Journal of Financial Markets 16:1–31. https://doi.org/10.1016/j.finmar.2012.09.001), treating them as special cases. We introduce a methodology to estimate parameters for implementing order-splitting strategies, leveraging limit order book data instead of proprietary datasets. We posit that instantaneous impact is shaped by market depth through limit order arrivals and cancellations, whereas permanent and temporary impacts arise from mid-price shifts, driven by the anticipation of forthcoming order flows. To validate the utility of our framework, we calibrate market impacts for 100 NASDAQ stocks and compute order-splitting strategies using real data. Numerical evaluations indicate potential cost savings of up to 8.760% compared to other optimal strategies. This research provides valuable insights into understanding and optimizing liquidation strategies in financial markets, emphasizing the role of market impacts and the importance of limit order book data.