Purpose: This study investigates whether three decades of EU procurement harmonisation have created unified administrative practices or whether document-observable patterns persist, demonstrating proof-of-concept for transforming procurement documents into strategic intelligence addressing cross-border B2B information asymmetry. Design/Methodology/Approach: This study analyses 2,370 software packages and information systems public procurement notices (CPV 48000000) from 17 European countries (2023-2024) using an automated Cultural Intelligence Extraction System (CIES), achieving 95.4% expert validation accuracy. One hundred one parameters across twelve dimensions are extracted. ANOVA with effect-size prioritisation (η²) and hierarchical multi-level clustering are employed. Findings: Document-observable patterns demonstrate extreme variation despite harmonisation: 8.8× verbosity range, 10.1× technical specification range, 5.6× scope range, with country explaining 50% of transparency variance (η² = 0.500). Multi-level clustering identifies five procurement strategies: Extreme Verbosity (Hungary), Multi-Domain Integration (Romania), Efficient Minimalism (a cross-regional cluster of Czech, Finland, and Switzerland), Western/Nordic Mainstream (comprising nine countries), and Eastern/Southern Moderate Complexity (Bulgaria, Greece, and Poland). Economic analysis reveals a multi-lot value paradox: 20% of tenders capture 72% of contract value, with a 294-fold variation in value concentration. Research Implications: The results validate the institutional theory's formal/informal distinction: EU directives harmonise legal procedures, while administrative practices diverge. Findings enable a document-to-intelligence transformation, providing suppliers with market selection guidance, authorities with efficiency benchmarking, and policymakers with frameworks to distinguish harmonizable dimensions from legitimate diversity. Originality/Value: Large-scale automated administrative pattern extraction demonstrating systematic document-to-intelligence transformation for B2B strategic positioning. A hybrid LLM-rule-based system with anti-hallucination validation establishes a methodological blueprint for extracting procurement intelligence at scale.

Purpose: This paper will discuss the way in which the Mongolian yak jerky could be re-packaged as a high-end sustainably-positioned snack to the Chinese market that is traditionally consumed as a pastoral item. It is proposed to determine the strategic, value-chain, consumer, and territorial branding variables that allow launching the product at the premium market, and overcome the structural deficiencies in the livestock industry of Mongolia. Methodology/Approach: The study has an integrative qualitative approach that involves a systematic literature review, strategic market intelligence analysis, cross-border regulatory analysis, and value-chain diagnostic report. The secondary sources were supplemented by the synthetic dataset that needed to reflect indicative patterns at the consumer perceptions, processing quality, export preparedness, and benchmark competition. Originality/Relevance: The study is the first to develop a comprehensive framework of the association between sustainable value-chain upgrading, strategic intelligence, and territorial branding to the premiumization of a pastoral meat product in a foreign market. It provides a way forward based on evidence of emerging economies aiming to modernize the traditional livestock systems and establish high value niches in the form of Sustainable Competitive Intelligence. Key Findings: The findings indicate that purity, healthiness, and cultural authenticity are the product attributes based on sustainability that the Chinese consumers value highly. Value-chain diagnostics indicates a high level of positive relationships between hygienic compliance, packaging quality and export preparedness. This means that as indicated by benchmarking, the Mongolian yak jerky is in a potential premium position but needs better packaging, flavors, and brand communication. The partnership between the sustainability, modernization, strategic intelligence, and territorial identity proves to be the key to the successful establishment in the market. Theoretical/Methodological Contributions: The research contributes to the Sustainable Competitive Intelligence theory by showing how the use of intelligence in decision-making can aid in cross-border value-chain upgrading and sustainable market alignment. It is also a contribution to the literature of COO and territorial branding because it demonstrates how ecological authenticity and nomadic identity might be developed into market strength when backed by quality control and processing standardization. In terms of methodology, the research depicts the (analytical) usefulness of synthetic data in conducting exploratory research in under-reported industries.

Egyptian universities face a series of rapidly evolving and complex challenges, most notably limited financial resources, intensifying competition at the regional and global levels, rapid digital transformations, and academic quality and accreditation requirements. Based on these challenges, this research seeks to develop a conceptual framework for strategies for sustainability in Egyptian universities, based on Nafee’s integrative model of institutional excellence and smart transformation (N. IMOE). The research employed a descriptive-analytical approach, supported by a conceptual review of existing policies and prior studies, and incorporated comparisons with prominent international models such as EFQM. The proposed framework illustrates mechanisms for integrating key model components—strategic intelligence, strategic agility, leadership, innovation and digital learning management, artificial intelligence capabilities, and talent management—with the phased transformation cycle comprising abandonment, adoption, adaptation, excellence, competition, and smart transformation. This integration facilitates the translation of strategic objectives into actionable, measurable, and sustainable practices. The results revealed a gap between the level of awareness of the importance of sustainability and the level of its actual implementation, highlighting the need for an integrated institutional framework that links policies, resources, and digital infrastructure to ensure sustainable performance and enhance institutional excellence in Egyptian universities. Based on this, the research proposes a set of recommendations, most notably integrating sustainability into university policies, developing digital infrastructure, building human capacity, allocating stable financial resources, expanding community and international partnerships, and adopting pilot projects supported by accurate performance indicators to measure progress toward smart transformation.

Indonesia’s 40% biodiesel (B40) mandatory policy, which came into effect in early 2025, represents a strategic initiative to enhance energy security and reduce carbon emissions. However, behind its official objectives, the policy entails significant fiscal, environmental, and social risks that threaten its long-term sustainability. While most analyses have focused on its economic or environmental dimensions, the role of state intelligence in navigating these multidimensional risks remains an underexplored area. This article argues that the success and sustainability of the B40 policy depend not only on technical feasibility or political commitment, but also on the effective application of strategic intelligence functions to provide foresight, mitigate threats, and deliver objective assessments to policymakers, free from partisan and corporate influence. This study adopts a conceptual framework that integrates the intelligence cycle with energy security theory, this article analyses how early detection, early warning, and problem-solving functions can be applied to manage systemic risks such as subsidy traps, feedstock supply deficits, and social tensions. The analysis finds that intelligence plays a crucial role in transforming energy risk management from reactive to proactive. Accordingly, the formal integration of intelligence into the energy policy cycle is a prerequisite to ensure that strategic initiatives such as B40 contribute substantively to sustainable energy, rather than merely serving as economic buffers for entrenched industrial interests.

This article presents a comprehensive stakeholder analysis within the context of opioid overdose prevention in Boston, showcasing the development and application of an integrated framework designed to address the complex dynamics of the opioid crisis. Utilizing a modified Agency for Healthcare Research and Quality stakeholder analysis tool, this study categorized key stakeholders into four main groups: healthcare providers, law enforcement officers, health policy officials, and community leaders. Through in-depth, semistructured interviews with 15 stakeholders recruited from Boston's Mayor's Task Force for Opioid Remediation, we synthesized insights to map out strategic intelligence essential for policy formulation and enhanced stakeholder engagement. The analysis highlighted the necessity of multisector collaboration and identified critical leverage points that could influence future interventions. The findings underscored the potential of tailored interventions that consider the unique needs and contributions of different stakeholder groups, advocating for policy reforms that support comprehensive public health strategies. The integrated framework represents a proposed implementation model for Boston, demonstrating adaptability for other urban settings. The framework introduces innovative strategies for continuous improvement and adaptation, informed by stakeholder feedback. This research contributes to the field by demonstrating the effectiveness of stakeholder analysis in developing actionable and sustainable public health policies, providing a replicable model for other urban settings facing similar public health challenges.

Digital sovereignty has emerged as a critical geopolitical concept defining national autonomy in the digital realm, while competitive intelligence serves as an essential tool for understanding technological competition dynamics. This comprehensive review examines the intersection of digital sovereignty frameworks and competitive intelligence methodologies in analyzing global technological dominance patterns. The analysis synthesizes diverse theoretical approaches, policy mechanisms, and intelligence gathering techniques across various national contexts and technological sectors. This examination identifies significant advancements in integrated assessment methodologies that combine regulatory frameworks, technological capabilities, economic indicators, and strategic intelligence systems. Key findings indicate that hybrid competitive intelligence approaches, particularly combinations of open- source intelligence (OSINT) with economic espionage detection and technological trend analysis, yield robust predictive models for technological dominance patterns with improved accuracy compared to single source approaches. Advanced technologies including artificial intelligence driven intelligence analysis, blockchain-based sovereignty verification, and quantum-resistant security systems are transforming large-scale competitive intelligence capabilities, enabling real-time strategic assessment. However, significant gaps remain in standardization of sovereignty metrics, integration of cultural factors, and ethical frameworks for intelligence gathering. This review provides evidence-based recommendations for future research directions and practical implementation strategies for policymakers and intelligence professionals seeking to navigate the complex landscape of technological competition and digital autonomy.

Similarities between recent strategic intelligence analysis failures and “historic” ones suggest that problems stem not from organizational, processual, or technological issues, all of which have improved over the last decades, but from an unchanging factor—human cognition. There are three interwoven reasons. First, strategic intelligence analysis requires the suppression of human cognitive traits developed during human evolution, such as conformity and heuristics, which lead to biases. Second, it lies outside the “performance envelope” of human cognition because, until historical times, there was no demand or selection process for the cognitive abilities required for this task. Third, memory and computation technologies, which augment human cognition, offer limited benefits in strategic intelligence analysis. Several avenues for addressing this reality are presented.

The evolving landscape of global business management demands an integrated framework that aligns sustainability principles, technological innovation, and strategic decision-making. This research explores the dynamic intersection of these three pillars: sustainability, technology, and strategy within the broader context of modern management practices. The study recognizes that contemporary organizations no longer operate in isolation from environmental responsibility or technological advancement; rather, they must navigate a complex ecosystem shaped by economic globalization, digital transformation, and increasing social expectations for ethical governance. This paper adopts a multidisciplinary perspective, combining insights from strategic management, environmental economics, and information systems to develop a conceptual model that emphasizes balance between profit-driven and purpose-driven outcomes. Empirical analysis is drawn from multiple industry case studies spanning manufacturing, healthcare, and information technology, demonstrating how firms leverage emerging technologies such as artificial intelligence, data analytics, and automation to foster sustainable operations and long-term value creation. The research further investigates how integrating sustainability metrics into strategic frameworks influences organizational performance, innovation capabilities, and stakeholder trust. The findings indicate that the convergence of sustainability and technology not only enhances operational efficiency but also transforms the strategic orientation of firms towards resilience, adaptability, and inclusivity. Moreover, leadership commitment and cultural alignment emerge as critical enablers in bridging the gap between sustainability objectives and technological execution. The study highlights that organizations embracing this integrated approach are better positioned to achieve competitive differentiation, mitigate risk, and ensure enduring stakeholder engagement. Ultimately, the research contributes to the expanding body of knowledge on modern management by articulating a cohesive model that synthesizes strategic foresight with technological agility and sustainable development goals. It underscores that the future of management lies not in isolated excellence but in systemic coherence where technological tools are guided by sustainable intent and strategic intelligence. The implications of this study extend beyond academia, offering actionable insights for policymakers, corporate leaders, and entrepreneurs seeking to cultivate organizations that are both technologically progressive and socially responsible in an increasingly uncertain global environment.

This study investigated the influence of strategic intelligence on the non-financial performance of insurance companies in South-East Nigeria. A survey research design was employed, and the study population comprised seventy-seven employees of the selected insurance companies, who also constituted the sample size. The hypotheses were tested using simple linear regression analysis. The empirical findings indicated that business intelligence exerted a significant positive effect on the non-financial performance of insurance companies in South -East Nigeria. Similarly, competitive intelligence demonstrated a significant positive influence on their non-financial performance. Consequently, the study concluded that strategic intelligence has a significant positive impact on the non-financial performance of insurance companies in the region. It was therefore recommended that insurance companies in South-East Nigeria adopt advanced business and competitive intelligence systems to strengthen non-financial outcomes, particularly in areas such as customer experience, operational efficiency, decision-making, market analysis, competitor tracking, and innovation.

<p>Besides being a buzzword, machine learning finds new areas of application in organizational decision-making processes by the day. We map the field's intellectual structure, thematic evolution, and application domains through a bibliometric analysis of 1,803 Web of Science and Scopus articles (1990-2024) to elucidate its strategic and operational roles. Six clusters, spanning risk modeling, predictive analytics, strategic intelligence, and human-centered AI, are revealed by co-authorship, keyword co-occurrence, and bibliographic coupling. The findings reveal a fragmented but methodologically diverse landscape, with algorithm adoption differing by decision type and industry. By connecting machine learning methods (like deep learning, natural language processing, and explainable AI) with decision functions (like forecasting, optimization, and classification), we can identify the situations in which machine learning has the biggest influence. We go beyond descriptive enumeration with our integration of conceptual and practical insights.</p>

This article analyzes how principles and practices of police intelligence can be applied to decision-making in corporate environments, giving rise to the concept of organizational strategic intelligence. The research, qualitative and exploratory in nature, was based on bibliographic review and documentary analysis of business cases, enabling the identification of parallels between police and corporate methodologies. The results revealed that practices such as rigorous information validation, predictive analysis, and systems integration can be adapted to the private sector, contributing to uncertainty reduction and competitiveness enhancement. Tools such as Business Intelligence and Big Data Analytics proved to be operationally equivalent to software used in public security, fostering greater agility and reliability in business decision-making. The study also highlighted the ethical and legal challenges related to intensive data use, emphasizing the need for governance and compliance policies. It is concluded that strategic intelligence should be incorporated into organizational culture not merely as support, but as a central axis of the decision-making process, capable of anticipating risks, increasing institutional resilience, and sustaining corporate legitimacy in highly competitive markets.

The development of information technology has changed the paradigm of access to intelligence resources globally, including in the field of Geospatial intelligence (Geoint). Geoint integrates Imaginary intelligence (Imint) and Geospatial data (Geoinfo) in the context of strategic intelligence for comprehensive collection and analysis of geographic conditions and enemy activities. This paper highlights the utilization of Geoint in supporting the role of state intelligence in Indonesia in the intelligence cycle. The result of this paper shows the potential of Geoint to be utilized in supporting the role of intelligence organizations, especially in Indonesia, in dealing with dynamic threats that are evolving into new-style warfare. In the intelligence cycle, Geoint provides the necessary geospatial data and information and facilitates the process of planning, collecting, processing, and distributing information to support national security policy.

The Role of Strategic Intelligence in Achieving Sustainable Education

Global supply chains have become highly vulnerable to disruptions caused by pandemics, geopolitical conflicts, trade wars, and sustainability pressures. This narrative review synthesizes existing research on risk management strategies with a focus on resilience, collaboration, sustainability, and strategic intelligence. Literature searches were conducted in Scopus, Web of Science, and Google Scholar, covering studies published between 2010 and 2024. The findings highlight resilience strategies—such as redundancy, agility, and digitalization—as essential mechanisms for mitigating disruptions. Redundancy reduces operational vulnerabilities through buffer inventories and multiple sourcing, while agility enables rapid adjustments to volatile conditions. Digitalization further enhances resilience by improving real-time monitoring and decision-making. Collaborative governance and risk-sharing contracts strengthen supply chain networks by fostering trust and distributing risks equitably. Geopolitical events and the COVID-19 pandemic illustrate the fragility of global networks, emphasizing the importance of supplier diversification, localization, and technological preparedness. Sustainability-related risks, including environmental, social, and governance (ESG) issues, require integrated frameworks that align resilience strategies with ethical and regulatory imperatives. Strategic intelligence emerges as a dynamic capability that supports proactive adaptation and recovery. This review concludes that effective supply chain risk management requires integrated and adaptive frameworks combining resilience, collaboration, and intelligence. Policy support, investment in logistics infrastructure, and targeted strategies for small and medium-sized enterprises (SMEs) are critical for building sustainable and competitive global supply chains in an increasingly uncertain environment,

ABSTRACTIn the EU blueprint project FLAMENCO (Forward Looking Approaches for Green Mobility Ecosystem Network Collaboration), an innovation agent task force has been founded, which acts as an expert panel to elaborate a skills set of an innovation agent for automotive and establishes an innovation capability assessment model based on the ISO 560xx Innovation Management Systems norm series. In 2024, a new EU project TRIREME (Digital & Green Skills Towards Future of the Mobility Ecosystem, 2024–2027) started, which builds on this existing innovation agent task force and provides resources to elaborate MOOcs (Massive Open Online Courses) per chapter of the ISO 5600x norm applying new tools like AI. The MOOC is then configured in a European Skills Hub of the ASA (Automotive Skills Alliance). ASA represents the pact for skills partner in the EU Erasmus+ program for the automotive sector. The research work about the use of AI (artificial intelligence) for the implementation of specific ISO 560xx chapters will be published. This paper is about the results of the work on the ISO 56006 Strategic Intelligence Management implementation using AI in the TRIREME project.

ABSTRACT In the summer of 1944, the Soviet strategic offensive Bagration launched in Belorussia led to the collapse of the German Army Group Center and brought the Red Army closer to the Third Reich’s territory. Among the enablers of this Soviet success, the historiography of World War II mentions Moscow’s ability to create a false image of the Red Army’s deployment and thereby mislead the Germans into believing that the main Soviet blow would come in Ukraine. This article, based on German and British intelligence reports, discusses the hypothesis that Soviet strategic intelligence was also involved in the deception effort that paved the way for Bagration. According to it, back in the spring of 1944, Soviet spies managed to convince Berlin of the growing general fatigue of the Red Army and its desire to concentrate its summer offensive on the southern, Ukrainian sector of the Eastern Front.

The convergence of Artificial Intelligence (AI) and data analytics is revolutionizing traditional business strategy by enabling predictive intelligence, accelerated decision-making, and agile responses to dynamic market conditions. This paper investigates the pivotal role of AI-powered analytics in strategic planning and execution, illustrating how organizations leverage these technologies to gain competitive advantage, personalize customer engagement, and streamline operations. Through a qualitative content analysis of recent academic literature and illustrative case studies from leading firms such as Amazon, Unilever, and Netflix, the study examines AI's strategic impact across domains including market segmentation, resource optimization, risk assessment, and competitive intelligence. The research underscores the significance of machine learning, natural language processing, and prescriptive analytics in fostering strategic foresight. The paper concludes by proposing a structured framework for the integration of AI-driven analytics into corporate strategy, offering actionable insights for both scholars and practitioners.

Technology roadmapping is conducted by systematic mapping of technological evolution through patent analytics to inform innovation strategies. This study proposes an integrated framework combining hierarchical Latent Dirichlet Allocation (LDA) modeling with multiphase technology lifecycle theory, analyzing 113,449 Derwent patent abstracts (2008–2022) across three dimensions: technological novelty, functional applications, and competitive advantages. By segmenting innovation stages via logistic growth curve modeling and optimizing topic extraction through perplexity validation, we constructed dynamic technology roadmaps to decode latent evolutionary patterns in AI-powered programmable manipulators (B25J classification) within an innovation trajectory. Key findings revealed: (1) a progressive transition from electromechanical actuation to sensor-integrated architectures, evidenced by 58% compound annual growth in embedded sensing patents; (2) application expansion from industrial automation (72% early stage patents) to precision medical operations, with surgical robotics growing 34% annually since 2018; and (3) continuous advancements in adaptive control algorithms, showing 2.7× growth in reinforcement learning implementations. The methodology integrates quantitative topic modeling (via pyLDAvis visualization and cosine similarity analysis) with qualitative lifecycle theory, addressing the limitations of conventional technology analysis methods by reconciling semantic granularity with temporal dynamics. The results identify core innovation trajectories—precision control, intelligent detection, and medical robotics—while highlighting emerging opportunities in autonomous navigation and human–robot collaboration. This framework provides empirically grounded strategic intelligence for R&D prioritization, cross-industry investment, and policy formulation in Industry 4.0.

This study aims to identify the impact of strategic intelligence in supporting the sustainable competitive advantage of employees in organizations. Strategic intelligence was explained as the organization’s ability to find leaders who possess the intelligence, knowledge, and experience to build a future vision, strategic focus, creativity, and strategic implementation. Organizational excellence was explained as the organization’s ability to focus on the consumer and the market by collecting and analyzing relevant data accurately. This study also shows that strategic intelligence is one of the most important requirements for making more successful organizational decisions. It discovered that there is a relationship between strategic intelligence and the decision-making process, and it is crucial in helping organizations and managers to make appropriate decisions quickly and effectively for their organizations. This study recommends developing an annual work program that focuses on enhancing strategic intelligence and clarifying the different dimensions for employees to achieve competitive advantage.

The Relationship between Strategic Intelligence and Organizational Excellence: A Theoretical Study