Business, Economics and Management

Abstract: Running a vocational training program requires connected decisions, not merely a published course. This conceptual framework article combines design-science research with a tutorial format to show how AI-supported decisions can be linked without confusing model advice with organizational authority. Nine decision models (M1–M9) support program features, price and class size, demand, learner journeys, partners, service coverage, three resource types, cohort economics, and the next permitted action. Across them, four shared mechanisms clarify decision objects, put required conditions before preference, reconstruct realistic action spaces, and permit abstention. An optional tenth model (M10) reviews whether the model set should continue, change, simplify, pause, or stop. Each model has a stated basis, input–output contract, procedure, adaptation, checkable design property, and stop condition. The models sit within a nine-stage service journey, while people and authorized bodies retain responsibility for approval, examination, and certification. Evidence consists of a directed narrative review, a design-conformance check, and researcher-generated synthetic mechanism checks. The findings are intentionally mixed: some prototypes enforce stated conditions at an economic cost; the demand model improves only half of the synthetic paths; joint price–capacity planning loses profit after conditions change; and model-set review fails when assumptions about corrective action are wrong. These illustrations reveal rule behavior, trade-offs, and failure modes, not field performance or universal superiority. The contribution is an adaptable decision framework and tutorial that organizations can examine, simplify, and later test with their own evidence.

Abstract: Sovereign wealth funds (SWFs) have evolved from passive stewards of commodity windfalls into active, state-directed catalysts of structural economic transformation and fiscal income diversification. This study examines the institutional mechanisms, capital deployment strategies, governance architectures, and macroeconomic effects through which SWFs finance non-resource development, focusing on the Saudi Public Investment Fund (PIF) under Saudi Vision 2030. Employing an embedded mixed-methods comparative design, the analysis benchmarks the PIF against four funds embodying distinct operational models: Norway's Government Pension Fund Global (GPFG), Singapore's Temasek Holdings, Abu Dhabi's Mubadala Investment Company, and Malaysia's Khazanah Nasional. The qualitative strand synthesizes thematic content analysis of official disclosures, strategy programs, and credit assessments, while the quantitative strand estimates panel fixed-effects models linking SWF domestic investment intensity to multidimensional diversification indicators over 2000–2025. The findings indicate that active strategic development SWFs (SDSWFs) generate positive but non-linear spillovers on non-oil gross domestic product (GDP) growth, employment, and foreign direct investment. Domestic capital deployment exhibits diminishing returns beyond an estimated threshold of approximately 10.7% of GDP, past which risks of private-sector crowding-out, asset inflation, and bank credit absorption intensify. Governance quality significantly moderates whether domestic deployment translates into tradable export complexity. The comparative evidence positions the PIF as distinctive in scale, speed, and breadth of giga-project development, with its long-term success conditional on arm's-length governance, market-rate commercial hurdles, and institutionalized capital recycling. The paper contributes an integrated model connecting SWF mandate design, institutional governance, and domestic absorption capacity to sustainable transformation.

Abstract: This study investigates the structural determinants of e-commerce adoption across the 27 European Union Member States during the period 2020–2025, a phase marked by accelerated digital transformation following the COVID-19 shock. Using harmonised Eurostat data and a country-level panel framework with fixed effects and clustered standard errors, the analysis examines the relative contribution of digital infrastructure, digital human capital, and macroeconomic dynamics to variations in online purchasing participation. The baseline results indicate that household broadband penetration remains the most consistent and economically meaningful predictor of e-commerce adoption. Even at high levels of connectivity, incremental increases in broadband access are associated with significant rises in the share of individuals purchasing goods and services online. Digital skills exhibit a positive and complementary role, with evidence suggesting stronger marginal effects in EU-13 economies, consistent with partial convergence dynamics within the European digital single market. In contrast, short-run purchasing power fluctuations, measured through annual log-differences in GDP per capita (PPS), display limited explanatory power once structural digital factors are controlled for. The findings support a structural readiness interpretation of digital consumption, whereby infrastructure and human capital investments, rather than cyclical macroeconomic conditions, underpin sustained online market participation. The study contributes recent comparative panel evidence for the EU during the post-pandemic acceleration phase and offers policy-relevant insights for advancing digital convergence across Member States.

Abstract: Insurance supervisors worldwide confront the same technology, artificial intelligence deployed in pricing, underwriting, reserving and claims, but they confront it from radically different institutional positions, and the templates most visible to late-moving regulators emerge from institutional settings unlike their own. This paper asks whether supervisory responses to a common technology converge on the technology's properties or diverge along institutional lines, and what the answer implies for supervisors that have not yet acted. Using a structured, focused comparison on a most-different-systems design, the paper analyses three supervisory responses across six dimensions, legal form and bindingness, regulatory philosophy, institutional carrier, accountability locus, enforcement mechanism and market context: the Swiss Financial Market Supervisory Authority's Guidance 08/2024, the United States NAIC model bulletin and AI Systems Evaluation Tool, and Ghana's National Insurance Commission, which supervises under a modernised statute and a national artificial intelligence strategy but without, as yet, an insurance-specific instrument. The comparison finds convergence at the level of risk taxonomy and systematic divergence at the level of instrument design, supporting an institutionalist rather than functionalist reading: the three responses constitute distinct equilibria, not points on a maturity curve, and, strikingly, the jurisdiction without an instrument possesses the strongest statutory named-person accountability infrastructure of the three. The paper extends the framework of institutionally contingent technology adoption hierarchies from firms to supervisors and translates the findings into a four-part guideline architecture for capacity-constrained regulators, illustrated for Ghana, that routes delegation-aware, condition-based obligations through enforcement channels the supervisor already controls.

Abstract: Digital markets create value through platform ecosystems that integrate complementary technologies, resources, and organizational capabilities. Existing research explains platform governance, ecosystem orchestration, and collaborative value creation but provides limited explanation of the organizational processes that establish strategic relationships and support ecosystem expansion. This study develops a conceptual architecture of ecosystem coordination from a business development perspective. A conceptual theory development approach integrates digital ecosystem research with business development research, while an analytical model provides a formal representation of the structural relationships among business development capability, ecosystem coordination, ecosystem expansion, and collective value creation. The proposed conceptual architecture comprises four complementary components: opportunity identification, partner evaluation, strategic alignment, and resource mobilization. Integration of these components supports strategic relationship development, ecosystem coordination, ecosystem expansion, and collective value creation. Illustrative applications across cloud computing, digital commerce, and artificial intelligence ecosystems illustrate the applicability of the proposed conceptual architecture. Findings establish a business development perspective for explaining ecosystem coordination in digital markets, extend digital ecosystem research through recognition of strategic relationship development as an essential organizational process preceding ecosystem coordination and ecosystem expansion, and provide a conceptual foundation for future empirical research.

Abstract: This paper introduces the Governance Inversion Hypothesis (GIH) to explain a growing paradox in artificial intelligence (AI) governance: under conditions of increasing regulatory expansion and technological complexity, organisations may become more formally governed while simultaneously experiencing a decline in operational control over AI systems. Existing AI governance frameworks generally assume that stronger regulation improves accountability, oversight, and organisational control. This paper challenges that assumption by arguing that governance formalisation contributes to the erosion of control in AI-intensive environments. Drawing on institutional theory, organisational governance research, accountability scholarship, and emerging AI governance literature, the paper develops a conceptual framework that explains how regulatory expansion weakens operational authority through four interconnected mechanisms: authority fragmentation, symbolic governance expansion, externalisation of control, and authority paralysis. As governance systems become increasingly layered and procedurally dense, organisations may struggle to maintain coherent authority, technical visibility, escalation capability, and meaningful intervention power over opaque and externally mediated AI infrastructures. The paper extends institutional decoupling theory by introducing governance inversion as a structural condition in which governance expansion actively undermines operational coherence rather than strengthening it. It concludes that the central risk in AI governance may not be the absence of governance structures but the emergence of institutions that appear increasingly governed while progressively losing the capacity to govern effectively.

Abstract: Job preparation, engagement, and retention are crucial processes for retaining and supporting a quality workforce, and realistic job previews (RJPs), along with simulation-based training, play a crucial role in this process. In this paper, we bring together four sources of literature to review the translation of experiential and simulation-based training into tangible positive outcomes for organizations, most notably employee retention. This paper, relying on the foundational thinking of Kolb's (1984) experiential learning cycle, Issenberg et al.'s (2005) review of the features of high-fidelity simulation training programs, Jun and Eckardt's (2023) social exchange perspective on training and turnover, as well as Albtoosh, Ngah, & Yusoff's (2022) meta-analytic findings, demonstrates that high-quality simulation-based training not only enhances skill attainment but also fosters organizational identification and lower voluntary turnover. Research shows that quality training and development (with its features of feedback, repetition, variability, and integration) is a more important driver of turnover than quantity. By providing employees with structured simulation-based onboarding and real job previews, employers are likely to foster psychological readiness, loyalty, and retention among employees. The findings have implications for human resource strategies, training for industrial safety, and within other industries.

Abstract: International trade is undergoing a growing transformation driven by geopolitical ten-sions, the adoption of stringent regulatory frameworks, and the increasing incorporation of sustainability criteria; therefore, explaining bilateral trade flows regains importance when analyzed through the gravity model. This study analyzed trends in international trade from geopolitical, regulatory, and sustainability perspectives to propose an expand-ed conceptual gravity model that comprehensively incorporates these dimensions. The re-search was grounded in the hermeneutic paradigm, employing a qualitative-interpretive method that synthesized a systematic literature review with grounded theory procedures for an interactive analysis of 83 scientific articles indexed in Scopus, selected using the PRISMA method and published between 2014 and 2026, which included conceptual op-erationalization as a systematization exercise. The results confirm the convergence among the dimensions identified in the literature, and based on the synthesis of the scientific lit-erature, an expanded gravity model is proposed that strengthens the explanatory power of the gravity model and establishes an agenda for future research aimed at application in various trade contexts using econometric evidence.

Abstract: The aim of this scientific article is to identify the key aspects of the concept of corporate social responsibility (CSR) and to quantify their impact on employee stability (ES). The subject of the research was selected aspects of CSR (strategic CSR management; effective implementation & communication; financial commitment; internal use & employee satisfaction; internal dissemination) and ES (organizational image; ethical corporate culture; safety and health protection; rewards, KPI and loyalty; growth through training). The quantitative research was carried out using a uniquely created questionnaire. The research sample contained 442 key managers from the business environment of the Czech Republic. The statistical hypotheses were evaluated using the structural equation modeling (SEM) method. The quantitative research revealed interesting findings. There are direct positive effects of the use of the aspects of the CSR concept on employee stability. Effective implementation & communication, together with financial commitment, are the most significant determinants that directly influence employee stability. A surprising finding is that growth through training has no links to employee stability. On the contrary, organizational image, together with rewards and loyalty, are the key aspects with links to employee stability. The findings bring new impulses for owners and top managers, who are the key persons responsible for the management and sustainable growth of the enterprise and its activities.

Abstract: The insurance industry is moving rapidly from generative artificial intelligence as a drafting assistant to agentic artificial intelligence as an autonomous performer of technical work, including loss reserving, pricing and capital analysis. This shift collides with a foundational institution of insurance regulation: the statutory opinion of a named, professionally accountable actuary. Existing professional standards define the actuary's responsibility for work performed by others in terms of supervision and review, concepts developed for human delegates whose reasoning can be interrogated. This paper asks what those concepts mean when the delegate is an artificial agent whose work is fluent, fast, voluminous and only partially reproducible. Drawing on the regulatory architecture of the actuarial signature across jurisdictions, on the documented failure modes of large language models, and on the human-factors literature on automation complacency, the paper argues that the tacit assumptions underlying professional reliance standards, interrogability, error legibility and normative alignment, fail for artificial delegates. It develops three conditions under which professional sign-off on agent-produced work remains meaningful: reproducibility of the quantitative core, traceability of every material judgement to an identifiable locus, and contestability, meaning the reviewing actuary's practical ability to challenge and override the agent before the opinion is issued. The paper further proposes a five-level delegation hierarchy for actuarial artificial intelligence, a reference architecture that separates deterministic computation from linguistic interpretation, and an evaluation protocol through which the three conditions can be tested against any deployed system. The central claim is that the accountability boundary does not break where the technology fails; it breaks where the technology succeeds so smoothly that review quietly degrades into ratification. Implications are drawn for supervisors, for the professional bodies whose reliance standards require amendment, and for capacity-constrained markets where agentic tools are most attractive and reviewing capacity is thinnest.

Abstract: This article redefines risk in the financial sector, specifically concerning life insurance, by focusing on the behavioral determinants of stakeholder decisions. Under conditions of high information asymmetry, characteristic of credence goods, traditional qualitative models demonstrate significant cognitive gaps, failing to adequately address the mechanisms of building institutional trust. The primary objective of the article is to analyze the "authenticity gap," defined as the behavioral dissonance between an organization's declarative strategies (e.g., in the area of ESG) and the subjective perception of their credibility by clients. The study utilizes the Integrated Relational Service Quality (IRSQ) model, which serves as a tool for measuring behavioral risk, representing a further stage of development from the SERVQUAL model and the Customer Service Quality Index (WJOK). The IRSQ model enables the mathematical parameterization of cognitive dissonances that lead to the erosion of social capital. Based on empirical research conducted on a sample of 647 respondents, it was demonstrated that in the face of crises (including the COVID-19 pandemic), it is the behavioral dimension of relational quality that functions as a key moderator of institutional resilience. The results prove that the proactive use of IRSQ tools allows for the mitigation of greenwashing risk by addressing cognitive mechanisms of authenticity verification. The article provides novel evidence that, in the era of the information society, reputational risk management must be inextricably linked to a behavioral model of relational quality, thus constituting an essential element supporting the management of financial enterprises (property and life insurance). This study is a continuation of research [Przybytniowski, 2020, 2022, 2023, 2024, 2026]

Abstract: The rapid expansion of livestream e-commerce has propelled the adoption of AI-driven virtual streamers. Drawing upon the Stimulus-Organism-Response (S-O-R) framework and the Computers Are Social Actors (CASA) paradigm, this study investigates how the technical and social stimuli of AI streamers—namely persona, anthropomorphism, and interactivity—shape consumer purchase intentions. The research focuses on the context of an MNC’s Vietnam AI virtual streamer (Vinamilk) on TikTok platform, utilizing a valid sample of 163 predominantly Generation Z consumers. To capture both linear net effects and causal complexity, this study employs a dual-methodological approach integrating Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM results reveal that an AI streamer’s persona and interactivity significantly enhance both consumers’ parasocial relationships (PSR) and perceived credibility (PC). Interestingly, while anthropomorphism successfully fosters PSR, it fails to significantly improve PC. Furthermore, within the highly entertainment-driven environment of TikTok, emotional connection (PSR) acts as the primary driver of Brand TikTok Engagement (COBRAs), which subsequently leads to actual purchase intentions. Complementing these linear findings, the fsQCA uncovers the principle of equifinality, identifying three distinct configurational pathways that sufficiently lead to high purchase intentions, indicating that no single condition is absolutely necessary. The findings suggest that digital marketing strategies should prioritize interactive capabilities and emotional resonance over mere visual realism to optimize AI-mediated commerce.

Abstract: Digitalisation can improve manufacturing continuity, but technology adoption does not by itself create supply-chain resilience. Drawing on recent Malaysian manufacturing evidence and closely related studies, this perspective argues that resilience depends on a conversion process through which digital resources generate trustworthy visibility, visibility reaches authorised decision-makers, and decisions trigger coordinated adaptation across firms and supply networks. Four research priorities follow: governance conditions for actionable visibility; affordable capability pathways for small and medium-sized manufacturers; sectoral and environmental contingencies; and multi-tier resilience linked to economic, environmental and social outcomes. The agenda calls for longitudinal, multi-informant and network-level designs that distinguish technology adoption, digital capability, information quality, decision authority and resilience outcomes. For policy, the implication is to evaluate digital programmes by improvements in interoperability, data quality and response speed rather than software adoption alone. The perspective positions digital supply-chain resilience as a visibility-to-action conversion problem and offers a focused agenda for Malaysian manufacturing research and policy.

Abstract: Resource-dependent, spatially polarised, post-Soviet regional innovation systems remain under-studied, and are rarely analysed with the spatial-econometric and explaina-ble-machine-learning toolkit now standard in smart-city research. This paper uses an eleven-year official panel (2014-2025, 17 regions of Kazakhstan) covering R&D expendi-ture, innovation-active enterprises, the innovation-activity rate, innovative product output, and patenting. We triangulate five methods: Principal Component Analysis, Entropy Weight and TOPSIS integral indices; cluster analysis; panel econometrics; Random Forest and Gradient Boosting with SHAP; and spatial econometrics (Moran's I, Geary's c, LM diagnostics for SAR/SEM/SDM choice). We find extreme, persistent concentration of inno-vation inputs in Almaty and Astana (65.1% of national R&D expenditure, 2025), signifi-cant divergence on three of four indicators over 2014-2025, and a robust structural dis-connect between innovation inputs and outputs - a 'productivity-driven diffusion para-dox' - confirmed independently by correlation, factor analysis, panel regression, machine learning, and spatial econometrics. A robust three-tier regional typology is corroborated by an independent external study, and spatial analysis identifies peripheral-anomaly regions failing to absorb proximity benefits from more developed neighbours. We interpret these findings through Regional Innovation Systems, Smart Specialisation, New Economic Ge-ography, and Mission-Oriented Innovation Policy theory, and propose an evidence-based, AI-ready regional innovation governance framework - a unified data layer, explainable analytics, spillover corridors, and cluster-differentiated policy -transferable to other re-source-dependent, spatially polarised transition economies.

Abstract: The article explores the evolution of research on the energy transition through a biblio-metric co-occurrence analysis of author keywords extracted from 146 scientific publica-tions. Rather than analysing publication content directly, the study examines the rela-tionships among keywords related to the energy transition and intelligent deci-sion-support technologies. Recent research (2022-2024) increasingly focuses on renewable energy, sustainable development, and intelligent systems, which reflects the shift towards the digitalization of energy systems and the growing importance of sustainable develop-ment. Between 2018 and 2021, research shifted toward a broader understanding of the en-ergy transition, emphasizing climate change, decarbonization, renewable energy, invest-ments, and energy policy within the context of sustainable development. In contrast, pre-vious studies (2014-2018) have mainly focused on the technical aspects of energy systems and traditional decision-support approaches. The study focuses on demonstrating the outcomes of such evolution and considers the decision-making process for building an methodological concept integrated with expert systems to optimize and manage car-bon-reduction strategies under dynamic energy transition conditions. In this study, the concept of a DT is considered as a methodological direction for extending the capabilities of modern expert systems rather than as a fully implemented digital twin. Accordingly, an algorithmic model of an expert system is proposed, in which the analytical core is based on engineering (η), economic (F), and optimization models that are consistent with the digital twin concept. Particular emphasis is placed on the economic module, which ena-bles the assessment of the economic value of CO₂ capture, break-even carbon price, mini-mum functional point, optimal operating conditions, and the sensitivity of results to key economic parameters. The proposed approach contributes to the development of intelli-gent tools to support decarbonization and the transition to sustainable energy supply.

Abstract: Enterprise processes involve many interacting objects whose behavior depends on operational states. Object-centric process mining with OCEL 2.0 captures interactions between objects, and state-aware object-centric process mining adds the state evolution of selected objects. Identifying recurring local behavioral patterns that contribute to entering, maintaining, or recovering from undesired states is essential for process analysis and for designing improvement measures. However, detecting these patterns currently relies on manual inspection of state-aware directly-follows graphs, which is complex and does not scale. This paper presents an automated pattern detection approach for state-aware object-centric process mining. Given a leading object type, the method segments its state evolution, represents each segment as an object-centric graph, and aggregates structurally equivalent segments into ranked patterns. The method distinguishes patterns that occur inside a state from patterns that span state changes. In a real-life case study conducted with Europe’s leading pet retailer, the analysis reveals the behavioral patterns most strongly associated with understock and overstock states, providing a finer-grained diagnostic view of process behavior.

Abstract: Against the intertwined strategic backdrop of China’s “dual carbon” initiative and high-quality urbanization drive, this paper systematically investigates the coupling coordination relationship and evolutionary trends between urbanization development and carbon emission efficiency across the 11 provincial-level administrative regions of the Yangtze River Economic Belt (YREB). Based on a constructed multi-dimensional comprehensive evaluation index system for urbanization and carbon emission systems, three mainstream econometric and simulation methods are adopted, including the entropy weight method, coupling coordination degree model, and system dynamics model to empirically examine the spatiotemporal evolution characteristics of urbanization-carbon emission coupling coordination during the period 2000–2021 and further predict its dynamic development trajectories for 2022–2032. The empirical results indicate that, first, the overall urbanization level of the YREB presents a fluctuating upward trend over the study period, with spatial urbanization serving as the core driving pillar. Meanwhile, the comprehensive carbon emission index increases steadily with pronounced and persistent regional heterogeneity across the region. Second, the regional coupling coordination degree demonstrates a continuous improving trend, while the developmental gaps among the eastern, central, and western sub-regions gradually diminish over time; Shanghai consistently maintains a pioneering level of coupling coordination throughout the whole period. Third, the upward evolution of coupling coordination is projected to sustain from 2022 to 2032. By 2032, all provincial-level regions in the YREB will achieve notable progress in coordinated development, with the majority entering the stage of good or superior coordination. On this basis, this study puts forward targeted policy implications for accelerating the low-carbon transformation of urbanization and promoting balanced and coordinated regional development in the YREB, which provides practical references for advancing the region’s sustainable transition and facilitating the realization of national “dual carbon” goals.

Abstract: A capital-constrained manufacturer sells a durable product to replacement consumers (consumers with a used product) and primary consumers (consumers without a used product) through a retail platform under agency selling, financing production from either the platform or a bank, with the trade-in program implemented by either the manufacturer or the platform. In this setting, four supply chain models are formulated and corresponding optimal decisions are obtained. Comparing the equilibrium decisions and demands, the rankings across the two financing channels are generally cost-dependent, whereas several comparisons across the two trade-in implementers are stable or structurally pinned down. Introducing financing reshapes the trade-in preferences of the manufacturer and the platform relative to agency selling without financing: under platform financing, both prefer to implement the trade-in themselves; under bank financing, their preferences fragment with the parameters. In addition, the manufacturer largely prefers platform financing, and the bank always prefers platform implementation. Consumers prefer platform financing when the manufacturer implements the trade-in, and prefer manufacturer implementation under platform financing; in the other two comparisons, their preference depends on the commission rate.

Abstract: This study assessed the Entrepreneurial Intentions and Actions of youth within the City of Tshwane, post-COVID-19 pandemic, using the Theory of Planned Behaviour. The study focused on the influence of COVID-19 on Attitudes Towards Entrepreneurship, Subjective Norms, as well as Self-Efficacy, leading to Entrepreneurial Intentions and later Entrepreneurial Actions. Data were collected from 326 youths from five regions in the City of Tshwane, through convenience sampling, using a self-administered questionnaire. The findings were generated from results analyzed through Microsoft Excel, IBM SPSS v29 and STATA v13. The results provide evidence that COVID-19 positively influenced the antecedents of the Theory of Planned Behaviour. Moreover, the results revealed that Subjective Norms is not an important antecedent towards the formation of Entrepreneurial Intentions. Furthermore, Self-Efficacy had a direct relationship with both youth Entrepreneurial Intentions and actions. The findings thus add to the advancement of the Theory of Planned Behaviour. Based on this research, establishing institutions that focus on entrepreneurial growth and support to promote entrepreneurship can be the government’s goal in addressing the issues of youth unemployment. Additionally, an entrepreneurship environment that allows the exercise of entrepreneurship from a fundamental age is very crucial in the country.

Abstract: The international system has witnessed a fundamental transformation in economic relations among major powers during the second decade of the twenty-first century. Global supply chains have shifted from instruments of economic integration and peace promotion—consistent with the liberal approach—to geopolitical weapons deployed in pursuit of strategic and security objectives. This study addresses a critical research gap: the absence of an integrated theoretical framework explaining the mechanisms through which economic interdependence transforms into systematic economic weaponization. It does so through a critical review of the complex interdependence theory developed by Keohane and Nye and the proposal of a new conceptual model that introduces “logistical security” as a pivotal dimension in the structure of the multipolar global system. The study employs an integrative analytical methodology combining theoretical analysis with applied case studies of three principal cases: the semiconductor war between the United States and China, the weaponization of energy supplies in the Russian European context, and the global food crisis following the Russo-Ukrainian war. The study concludes that the current structure of global supply chains produces what can be termed “structural asymmetry in interdependence,” which enables parties occupying central nodal positions within these chains to deploy them as instruments of pressure and coercion. The study culminates in proposing the Multi-Level Logistical Security (MLLS) model as an analytical and applied framework that transcends existing theoretical shortcomings.