ABSTRACT Sustainable tourism policy in Indonesia is nominally inclusive but operationally exclusionary, as community‐based enterprises across Yogyakarta, Bali and Lombok are systematically denied eco‐certification, green financing and market access despite already meeting the sustainability standards these instruments reward. This paper attributes this failure to a governance legitimacy deficit, produced when governance instruments draw motivation, control, knowledge and legitimation boundaries that exclude community operators by design, compounded by prior research treating operators as informants rather than worldview holders. The study integrates Soft Systems Methodology with Action Research (SSM‐AR) dual imperatives framework, engaging 24 intensive and 89 broader community participants across three inquiry phases. Phase 1 surfaced community worldviews through rich pictures converging on a shared wall metaphor across sites; Phase 2 developed seven contrasting root definitions locating the deficit structurally; Phase 3 produced three pilot interventions addressing the knowledge, motivation and control boundaries, achieving outcomes formal instruments had failed to deliver. The study contributes the governance legitimacy deficit as a generalisable analytical category, an SSM‐AR application protocol grounded in the Indonesian SSM‐AR tradition, and the Community‐Centred Sustainable Tourism Architecture (CCSTA), a four‐component intervention framework with empirical pilot evidence.
ABSTRACT Organization is widely recognized as a fundamental concept in complex systems science, yet it rarely appears as an explicit object of scientific representation. Existing approaches successfully represent components, interactions, mechanisms, dynamical states, networks, or functions, but organizational properties are generally inferred from these representations rather than represented directly. As a consequence, systematic comparison of organization across heterogeneous systems remains difficult and often relies on domain‐specific descriptions or informal analogies. This paper proposes an intermediate structural representational framework in which organization becomes an explicit representational object situated between local mechanisms and global system behaviour. The framework introduces Structural Configurations as elementary organizational representations, criterion‐relative Structural Equivalence as the basis for comparison, Structural Signatures as equivalence classes of organizational configurations and Signature Space as the representational environment in which these signatures are organized. A formal construction based on equivalence relations and quotient spaces establishes the mathematical foundations of the framework while distinguishing empirical structural extraction from formal organizational composition. A complete methodological workflow is developed, linking empirical observations to Structural Configurations and Structural Signatures through explicit organizational coding and declared comparison criteria. The framework is illustrated through independently constructed representations of heterogeneous systems, demonstrating how organizational similarities, partial correspondences, and criterion‐dependent equivalence can be represented transparently without requiring common physical substrates or mechanistic explanations. Rather than proposing a new theory of organization, the paper establishes the conceptual, formal, and methodological foundations of a representational framework through which organizational structures can become explicit objects of scientific observation, comparison, and cumulative investigation across domains.
ABSTRACT Against the backdrop of the rapid expansion of the digital economy, aerospace data asset transactions have emerged as a strategically consequential and systemically complex domain. Existing research has accumulated insights into five dimensions—technological innovation, market demand, policy support, data assets and enterprise performance—yet systematic modelling of their dynamic coupling mechanisms remains underexplored. Drawing on complex systems theory and synergy theory, this study integrated systematic literature review, semistructured expert interviews and case study evidence to identify key variables. A second‐order system dynamics model was subsequently constructed in Vensim 10.3.1 and used to simulate the co‐evolutionary process of the five subsystems over 2018–2035, with 2018–2024 data serving for model calibration and 2025–2035 outputs representing simulation projections. Four findings emerge from the analysis. First, the five subsystems exhibit a phased co‐evolutionary pattern characterised as technology‐led, market‐following, system‐converging: The compound annual growth rate (CAGR) of digital technology innovation (20.17%) consistently outpaced both aerospace data demand (7.92%) and policy support (6.87%), generating endogenous structural tension and a persistent growth differential between technology innovation and enterprise performance (CAGR = 7.79%). Second, the influence of technological innovation on enterprise performance is subject to an approximately 4‐year lag effect, attributable to the role of R&D accumulation as an intermediate buffer stock. Third, policy support exhibits a threshold effect: Once the policy support stock crosses a critical level, its stabilising effect on market demand becomes increasingly pronounced. Fourth, a structural imbalance exists between data asset creation (CAGR = 0.67%) and technological innovation (CAGR = 20.17%), reflecting a competitive constraint in resource allocation. These findings extend the explanatory dimension of data asset value creation from static factor analysis to dynamic coupling mechanisms and offer a quantitative basis for both enterprise strategic planning and policy design.
ABSTRACT Environmental impact assessment (EIA) scholarship is commonly framed as a tension between efficiency and comprehensiveness paradigms. These paradigms describe a persistent tension but cannot explain how EIA operates through it. Drawing on social systems theory, this analysis traces that operation. A hypothetical tidal power EIA anchors the thought experiment. Three archetypal lenses guide the analysis: map follower, explorer and navigator. The map follower, efficiency‐leaning, follows predetermined routes. The explorer, comprehensiveness‐leaning, ventures into unmapped territory. The navigator finds paths through contradictions. Each lens foregrounds distinct problem‐solution dynamics that organise EIA's operations. The article therefore asks: How do these recurring dynamics sustain EIA over time? Conventional EIA scholarship often treats problems as obstacles to be overcome. This article reverses the framing: Problems are not overcome but recognised as conditions of operation. Each archetype's seasoned form renders its characteristic problem a working resource that sustains EIA's decision capacity over time.
ABSTRACT Sustainable agriculture faces interconnected challenges including pest pressure, soil degradation and waste accumulation, requiring integrative approaches under the One Health (OH) framework. This study explored the synergies between vegetable‐integrated push–pull (VIPP) systems and black soldier fly (BSF) farming for sustainable agroecosystem management. A systems thinking approach combining causal loop diagram (CLD) and network analysis (NA) was applied to map interactions among 77 determinants across plant, animal, human and environmental health subsystems. The analysis identified 43 reinforcing and 7 balancing feedback loops that regulate productivity, nutrient cycling and ecosystem stability. Soil fertility (betweenness = 2572.03; PageRank = 0.051) and crop damage emerged as structurally central variables linking productivity and pest dynamics, whereas BSF–VIPP adoption represented important intervention areas for future testing. Integrating BSF based waste valorisation and VIPP ecological pest management promotes circular nutrient flows, strengthens OH outcomes and provides a foundation for system dynamics modelling toward sustainable, climate‐resilient agriculture in sub‐Saharan Africa.
ABSTRACT To address the question of the individual's position in modern society, it is necessary to move beyond the traditional opposition between methodological individualism and holism. Drawing on the social systems theory of Niklas Luhmann, this paper reassesses the relationship between the individual and society through the system/environment paradigm. It argues that the individual is not a constituent part of society but exists in the environment of the social system. Only when an individual's bodily behaviour transforms the structural device constructed by the system within communication—the person—can the individual be perceived by the social system as an irritation, thereby influencing its autopoietic operations. On this basis, the paper further identifies four dimensions of individual irritation of social systems: direct individual irritation, indirect individual irritation, direct emergent irritation and indirect emergent irritation. These correspond to distinct mechanisms through which social systems, while fulfilling their fundamental function of stabilizing expectations, either maintain existing structures or undergo structural transformation.
ABSTRACT Public policy analysis has long been organized around the idea that governing consists in defining and solving public problems. Yet decades of debate on problem definition, framing and wicked problems have shown that policy problems are unstable, contested and rarely amenable to definitive solutions. I argue in this article that this difficulty does not stem merely from technical or political obstacles, but from a deeper ontological confusion about what public policy actually intervenes in. Drawing on social systems theory as a theoretical frame of reference, I contend that policy problems are not the objects of intervention but decision‐oriented constructions that make complex situations governable. Because public policy cannot act directly upon social systems, it operates instead on the social management system: the emergent pattern of interdependent management decisions through which societies collectively respond to publicly problematized situations. Public policy is thus reconceptualized as a second‐order form of governance that reorients social management rather than ‘solving’ substantive social problems.
ABSTRACT Research on business development systems provides limited explanation of how governance structures adapt to structural misalignment under turbulent conditions. Conventional regulatory approaches rely on fixed control parameters that constrain adaptive response under nonstationary conditions. This study develops a computational state space modelling framework for adaptive regulatory architecture within a business development system. The framework specifies governance intensity, coordination coherence and strategic misalignment as coupled state variables and connects them through recursive feedback dynamics. Monte Carlo simulations evaluate alternative regulatory topologies under repeated disturbance conditions. Results indicate that proportional endogenous scaling shortens recovery intervals, strengthens corrective feedback alignment and reduces long‐run structural variance relative to fixed‐gain and exogenous adjustment structures. Regulatory topology thus shapes resilience performance in dynamic business development systems. Findings contribute a computational explanation of adaptive governance and provide design principles for scalable governance intensity under environmental turbulence.
ABSTRACT This study develops and empirically examines the Digital Paradox Navigation (DPN) framework, which integrates second‐order cybernetics with digital transformation theory to explain how organisations manage paradoxical tensions through reflexive self‐observation. Using a mixed‐methods design, this study draws on data from 45 senior executives of 12 leading Indian organisations and analyses 156 digital transformation initiatives undertaken during 2023–2024. The DPN framework reconceptualises digital transformation as an autopoietic organisational process governed through reflexive self‐observation. Four recursive capability dimensions are delineated: technological self‐reference, cultural autopoiesis, strategic paradox management and environmental boundary spanning. Significant positive correlations are observed between digital reflexivity and transformation success ( r = 0.73, p < 0.001); organisations with higher digital reflexivity achieved substantially higher revenue growth (15.7% vs. 8.2%) than low‐reflexivity counterparts. The framework offers a theoretically grounded extension relative to dynamic capabilities, organisational ambidexterity and institutional theory and proposes practitioner‐oriented tools including a maturity assessment instrument and a phased implementation roadmap.
ABSTRACT This research note reframes escalation as a threshold‐induced regime transition in coupled systems. Traditional escalation theory explains conflict intensification through strategic choice, misperception or organizational dynamics but generally assumes a stable decision environment. Drawing on systems theory, resilience engineering and critical transitions research, the note argues that this assumption can break down in tightly coupled, high‐uncertainty environments. Escalation can emerge when disturbance propagation outpaces a system's capacity to stabilize within available response time, even when actors behave rationally and follow established procedures. The framework introduces four interacting variables—disturbance rate, interaction density, feedback stabilization capacity and response time—to explain how systems move toward or away from critical thresholds. This perspective clarifies how locally rational actions can collectively produce destabilizing outcomes and distinguishes ordinary instability within a controlled regime from structural regime transition. The note outlines implications for analysis and practice, suggesting that escalation risk depends not only on actor behaviour but also on the underlying system conditions that shape the limits of control.
ABSTRACT Systems research has long examined how feedback, delay, accumulation and regulation generate dynamic behaviour, yet less attention has been given to when system behaviour remains causally guided. This paper develops causal guidance as a viability‐dependent system‐level property, referring to the condition under which relations among actions, feedback and consequences remain interpretable over time. Building on systems research, system dynamics, causal reasoning and viability‐oriented traditions, it proposes a framework organized around four enabling dimensions: activation, coherence, delay and damping. The paper argues that causal guidance is not guaranteed by causal relations, feedback structures or functional viability alone, but depends on the mutual calibration of these dimensions. It then translates the dimensions into diagnostic indicators for distinguishing strong, weakened and degraded causal guidance. The framework contributes a diagnostic vocabulary for assessing when causal reasoning, feedback learning and intervention remain behaviourally meaningful in complex systems.
ABSTRACT This paper addresses a gap in the application of systems thinking to higher education programme design. We use the Complexity Theory of Outcome Creation (CTOC), a structured model for working in complexity, to analyse Simon Fraser University's Semester in Dialogue (SiD)—an innovative undergraduate programme applying the ideas of dialogic pedagogy and community‐engaged teaching and learning. Drawing on our experience, we reflect on how systems thinking shaped SiD's design and student experiences. We applied CTOC's four types of human complexity to understand our student cohorts, which led to a course design that attempted to match their complexity. Furthermore, we demonstrate how CTOC's three dynamic capabilities—coordination, stewardship and adaptation—provide a viable design logic that empowers student agency. This application of systems thinking, particularly CTOC, offers a practical, process‐focused approach for educational innovation.
ABSTRACT Although artificial intelligence (AI) has been increasingly applied to project optimization tasks, its influence on project managers' behavioural responses during decision‐making for the control of project execution remains underexplored. This study addresses this gap by evaluating the integration of AI in project management through the theoretical lens of Behavioural Operational Research (BOR). Drawing on qualitative data from interviews with 22 project managers, we investigate behavioural patterns that emerge when AI models are employed as decision‐support tools. Our findings reveal a tendency toward Escalation of Commitment (EoC) in project control decisions, which we theorize is driven by a dynamically complex behavioural mechanism we term the wait effect. This construct captures managers' inclination to delay corrective actions while awaiting further confirmation from AI outputs, with such delays moderated by the level of trust in the AI model. The study advances BOR literature by introducing the wait effect as a novel behavioural mechanism and by illustrating its dynamics through a Causal Loop Diagram. These insights have significant implications for the design of AI‐enabled project management systems, highlighting the need to account for behavioural biases that may undermine timely intervention and project performance.
ABSTRACT The management of livestock enterprises has traditionally relied on reductionist approaches separating biological and organizational components. This study proposes a theoretical model based on autopoiesis and self‐referentiality, integrating communicative membranes and dual cores to explain system persistence and evolution. The objective was to propose and empirically validate this model in family pig farming systems in Mexico. A structured questionnaire using a Likert‐type scale was applied to 30 units, generating indices for the knowledge core (KCI), biological core (BCI), communicative permeability (GCPI) and organizational response capacity (ORCI). Three systemic configurations were identified: loss of stability, static survival, and systemic evolution. Results showed that communicative permeability ( r = 0.76; p < 0.001) and the knowledge core ( r = 0.64; p < 0.001) were the main determinants of response capacity, while the biological core had a weaker effect. The model explained 58% of variance ( R 2 = 0.58), highlighting communication and knowledge as key drivers of adaptive capacity.
ABSTRACT Problem solving in complex domains requires approaches that encourage systems thinking, collaboration, and recognize multiple simultaneous solutions. Building from principles of General Systems Theory and existing problem structuring methods, we present a new method for supporting system partners working to address complex problems called GOSR. The model's phases include generating a superordinate goal statement (G), identifying obstacles (O) and potential solutions (S), and mapping existing resources (R). GOSR combines distributed decision‐making, self‐alignment of system actions, future orientation, interorganizational scope, and focus on solutions and existing resources. Its implementation entails human facilitation with rapid data collection and sensemaking from generative artificial intelligence, enabling widescale problem structuring. Its contribution lies in helping system partners increase awareness of others' efforts and opportunities for alignment without the constraints of central orchestration.
ABSTRACT User experience (UX) research on AI feedback typically treats response variability as noise to be minimized rather than as a phenomenon requiring explanation. Yet this variability is persistent—ranging from integration to dismissal—even when feedback procedure is held constant. This study examines this divergence through a controlled interaction in which 20 expert participants (doctoral/master's professionals) received AI‐generated critiques of their own texts, produced under the same feedback methodology. Treating AI output as linguistic perturbation generated under a standardized procedure, we conducted a four‐stage qualitative analysis tracing initial orientation, feedback features, reported stance and interactional trajectories. We identified three recurrent trajectories: congruent uptake (integration), pragmatic filtering (instrumental use) and defensive conservation (dismissal). These trajectories did not align with discipline or gender but reflected human–AI comparisons regulating receptivity. Drawing on Maturana's structural determinism, we reframe variability not as design failure but as a lawful outcome of history‐shaped organization, shifting design goals from persuasion towards perturbation calibration and interpretive autonomy.
ABSTRACT Organizational communication plays a pivotal role in enabling learning and decision‐making within complex adaptive systems. Rather than functioning solely as information transfer, communication in organizations constitutes a recursive process that shapes meaning, coordination and adaptive behaviour. This article introduces a systemic meta‐methodology for designing and analysing organizational communication architectures by integrating principles from cybernetics, cyber‐systemics and systemic action research (SAR). The approach employs soft systems methodology (SSM) as a flexible organizing framework that combines both systemic and nonsystemic tools to investigate communication flows, decision‐making processes and emergent knowledge structures. The architecture articulates both systemic and nonsystemic tools across nested levels of observation: Social network analysis and participatory diagnostic instruments are employed empirically to examine relational and structural properties of communication networks and organizational worldviews, whereas systemic modelling tools such as system dynamics and the viable system model are proposed as complementary heuristic components when appropriate to the problem context. A case study conducted in a private manufacturing firm contrasts organizational worldviews with actual communicative practices, revealing tensions and synergies between hierarchical and emergent structures. The findings present communication as an emergent, learning‐oriented process, offering a practical and theoretically grounded framework for enhancing organizational adaptability and collective intelligence.
ABSTRACT Healthcare systems face increasingly complex challenges that defy linear, reductionist approaches to improvement. Traditional quality improvement methods commonly used in healthcare systems often fail to address the multidimensional, adaptive nature of complex problem situations. This paper argues that critical systems thinking (CST) and its practical application through critical systems practice (CSP) provide a more suitable foundation for navigating such complex challenges. Using the EPIC framework— Explore , Produce , Intervene , Check —CSP offers a structured yet flexible approach for systemic sensemaking and multimethodological action. Drawing on a case study in NHS mental health and primary care, the paper demonstrates how the Explore stage enabled stakeholders to make sense of complexity through systemic perspectives, visual methods and collaborative problem structuring. Findings indicate that CSP broadens the conception of improvement and offers a pragmatic pathway for healthcare leaders, professionals and practitioners to achieve contextually grounded systemic improvements in complex healthcare environments.
Generative AI is reshaping the paradigm of knowledge creation, shifting it from a single human-centred mode to a human-machine co-creative process. However, cognitive differences, fragmented interactions and lack of contextual resonance between humans and machines make traditional human-centred knowledge creation theory, as exemplified by the SECI model, insufficient for explaining this process. Drawing on decision field theory and using the SECI model as a process framework, this study develops a dynamic model of human-machine knowledge co-creation. Simulation results show that the effective unfolding of co-creation depends on sustained interaction and timely feedback. In routine tasks, the formation of shared judgement structures is influenced more by computational capacity, whereas in creative tasks it depends more on knowledge stock. This study responds to the boundary limitations of traditional knowledge creation theory, incorporates machine actors into knowledge creation analysis, and provides a mechanism-level basis for augmented intelligence in human-machine co-creation.
ABSTRACT Persistent patterns of confinement, sensitivity to initialization and diminishing qualitative returns from increasingly sophisticated tuning strategies are widely reported across heuristic search and optimization contexts. These phenomena are commonly interpreted as algorithmic shortcomings, motivating successive layers of stochasticity, parameter refinement or hybridization. This paper frames persistent heuristic behaviour as an emergent property of admissibility structures and boundary judgements defined ex ante in constructed systems, rather than as a failure of local search dynamics. Instead of treating heuristics as the primary object of analysis, the paper places the structure of constructed search spaces defined ex ante at the centre of inquiry. We introduce a minimal, deliberately simple search space in which a boundary separating locally accessible regions is identifiable prior to any algorithmic intervention. This boundary (termed an energetic barrier) arises from the joint specification of the state space, locality assumptions and admissible transitions, and is independent of operator design choices. The paper further formalizes the distinct, stronger notion of a structural frontier, arising directly from the admissibility mapping rather than from the cost structure, and clarifies the conditions under which each applies. Using this construction, we analyse three classes of responses commonly observed in practice: baseline local exploration, epistemological refinement through parameterized stochastic search and landscape transformation via objective deformation. The analysis shows that refinement‐based responses systematically preserve the set of admissible transitions, improving exploration only within regions already accessible under the assumed structure. Apparent resolution of confinement emerges only when the admissibility structure or effective representation of the space is altered, thereby redefining the problem rather than traversing the original barrier. Persistence under refinement and apparent success under transformation constitute complementary diagnostic signals of underlying structural constraints. The contribution of this work is not a new optimization method, but a diagnostic framework for distinguishing algorithmic difficulty from structural inadmissibility in constructed systems. By shifting attention from operators to admissibility boundaries, the paper offers implications for the design, interpretation and governance of optimization systems, and contributes to broader discussions in systems thinking concerning boundary setting, problem representation and the limits of intervention.
