Complexity Science Perspective Research Articles

Exploring psychedelic-assisted therapy in the treatment of functional seizures: A review of underlying mechanisms and associated brain networks.

Functional seizures (FS), the most common subtype of functional neurological disorder (FND), cause serious neurological disability and significantly impact quality of life. Characterized by episodic disturbances of functioning that resemble epileptic seizures, FS coincide with multiple comorbidities and are treated poorly by existing approaches. Novel treatment approaches are sorely needed. Notably, mounting evidence supports the safety and efficacy of psychedelic-assisted therapy (PAT) for several psychiatric conditions, motivating investigations into whether this efficacy also extends to neurological disorders. Here, we synthesize past empirical findings and frameworks to construct a biopsychosocial mechanistic argument for the potential of PAT as a treatment for FS. In doing so, we highlight FS as a well-defined cohort to further understand the large-scale neural mechanisms underpinning PAT. Our synthesis is guided by a complexity science perspective which we contend can afford unique mechanistic insight into both FS and PAT, as well as help bridge these two domains. We also leverage this perspective to propose a novel analytic roadmap to identify markers of FS diagnostic specificity and treatment success. This endeavor continues the effort to bridge clinical neurology with psychedelic medicine and helps pave the way for a new field of psychedelic neurology.

The association between urbanization and depression in the elderly: A network analysis from the complexity science perspective

ImportanceThe global increase in urbanization has coincided with a rise in depression prevalence. However, the effect of urbanization on depression remains controversial, especially for the elderly. ObjectiveTo clarify how urbanization impacts depression in the elderly from a network perspective. Design, setting, and participantsThis sectional cohort study used data from China Health and Retirement Longitudinal Study (CHARLS). Main outcomes and measuresThe occurrence of depressive symptoms in urban and rural elderly residents. Network metrics of depressive symptoms. ResultsOf the 13,993 participants, lower incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 24.7 %–27.8 %) than in rural (40.4 %, 95 % CI, 39.5 %–41.3 %, P < 0.0001) residents. However, higher incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 25.2 %–28.4 %) than in rural (17.5 %, 95 % CI, 16.1 %–18.9 %, P < 0.0001) residents in a subset of 2898 pairs of participants after PSM. No difference in the network structure and metrics between urban and rural residents before (M = 0.071, p = 0.054, S = 0.037, p = 0.80) and after (M = 0.085, p = 0.133, S = 0.086, p = 0.47) PSM was detected. The networks structure revealed that negative affect was strongly connected to somatic symptoms and that the two anhedonic symptoms were also strongly connected. ConclusionsThe current study indicated the homogeneity of the ultimate nature of depression between rural and urban residents from the network perspective, supporting the viewpoint that urbanization might not impose influence on depression. Further researches delving deeper into the complexity of the issue may provide new insights into our understanding of depression in an urban environment among the elderly.

Complexity in Military Intelligence

Intelligence studies missed social science’s “complexity turn” more than twenty years ago. The aim of this article is to examine military intelligence from a complexity science perspective and discuss related concepts such as sensemaking and reflexivity. For this, military and intelligence theory, doctrine, and practice are studied. Complexity insights from military sciences are used to review mental models and current thinking in military intelligence. Rather than viewing it as a clearly defined and autonomous field or function embodied by a closed intelligence cycle, military intelligence is best seen as a situated practice. This situatedness is illustrated in two cases regarding vertical and horizontal contextual influences. First, a discussion of North Atlantic Treaty Organization deployments in Afghanistan shows important vertical influences: the impact of (political) context and task. Second, a review of United Nations missions exemplifies the horizontal dimension: the need for informal collaboration, ad hoc organization, and a holistic approach. However, both cases show vertical and horizontal influences. Overall, this article stresses the applicability of sensemaking rather than the intelligence cycle and makes suggestions for further incorporating complexity research into intelligence.

A framework for exploring futures of complex urban energy systems

In order to address the climate crisis and provide citizens with clean, secure and affordable energy, urban energy systems need to transition. This is significant as urban energy systems are increasingly seen as complex systems for their close interactions with local urban society, while being interdependent with higher levels of governance. Decisions taken today will continue to influence the inhabitants of our cities for well over 50 years, locking in energy consumption patterns of the future. How, then, do we make decisions on the interventions needed to bring about a desirable future, and prepare for the probable and possible futures? In this paper, we consider the key characteristics of urban energy systems from a complexity science perspective in order to explore what methodologies in futures and foresight scholarship could be beneficial in supporting urban energy decision-making. To do this we have undertaken an integrative review—a method that allows review, synthesis, critique, and analysis of new and emerging topics across multiple disciplines and multiple literature types—and consider the findings in light of their usefulness in understanding complex systems, which are inherently uncertain. We consider how futures and foresight theories and methods can be applied in urban and energy studies, highlighting examples of where around the world these have been applied by organizations seeking to shape transitions. The many methods and approaches that exist under the futures' umbrella have not been applied to anywhere near their full potential in urban energy studies, despite the limitations of many of the planning and modeling exercises currently used. We use key learnings from existing futures and foresight scholarship, along with our understanding of urban energy systems as complex adaptive systems, to propose a theoretical and practical framework for exploring their futures. The framework encompasses concepts of futures, contextualization, mapping uncertainty, participatory processes, and futures governance. Although there is much further research work needed to test and operationalize this framework in an applied way with city stakeholders, we hope this charts a way forward in addressing the critical challenges faced by urban energy planners and their partners.

CRIME HOTSPOT EMERGENCE IN MEXICO CITY: A COMPLEXITY SCIENCE PERSPECTIVE

We present a dynamic model based on the theories proposed by environmental criminologists to explain the emergence of crime hotspots within cities; a pervasive phenomenon that is largely independent of cities size and cultural differences. The model is defined on a multiplex network that represents a city spatial tiling with its corresponding urban transport infrastructure, allowing to explore the relation between crime hotspot locations and the network topological features. It also allows to explore the effects that cities time evolution and police checkpoints might have on the emergence of crime hotspots. For Mexico City, the model shows that heterogeneous distributions of criminal activity arise from a diffusion-driven instability, as a self-organizing process. The results obtained for this city are in line with several insights from environmental criminology, such as the relationship between urban layout and crime hotspots locations, or the conceptual label assigned to specific locations as crime generators. They also uncover new relationships between cities design and crime hotspot locations, and suggest that routine activity theory alone cannot explain the emergence of heterogeneous crime distributions.

A Complexity Science Account of Humor

A common assumption of psychological theories of humor is that experienced funniness results from an incongruity between stimuli provided by a verbal joke or visual pun, followed by a sudden, surprising resolution of incongruity. In the perspective of complexity science, this characteristic incongruity-resolution sequence is modeled by a phase transition, where an initial attractor-like script, suggested by the initial joke information, is suddenly destructed, and in the course of resolution replaced by a less probable novel script. The transition from the initial to the enforced final script was modeled as a succession of two attractors with different minimum potentials, during which free energy becomes available to the joke recipient. Hypotheses derived from the model were tested in an empirical study where participants rated the funniness of visual puns. It was found, consistent with the model, that the extent of incongruity and the abruptness of resolution were associated with reported funniness, and with social factors, such as disparagement (Schadenfreude) added to humor responses. The model suggests explanations as to why bistable puns and phase transitions in conventional problem solving, albeit also based on phase transitions, are generally less funny. We proposed that findings from the model can be transferred to decision processes and mental change dynamics in psychotherapy.

Order and disorder in the evolution of online knowledge community: an investigation of the chaotic behavior in social tagging systems with evidence of stack overflow

PurposeOnline question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.Design/methodology/approachThe authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.FindingsThere are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.Originality/valueThis study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

Exploring a framework for solidarity entrepreneurship in the context of the confluence of the fourth industrial revolution, covid-19, and climate change

Introduction: Since the beginning of the last decade, the number and scope of studies on the impact of the Fourth Industrial Revolution have intensified, particularly in Artificial Intelligence, Automation, Robotics, and other related disciplines regarding the future of work. These studies discuss relevant changes in the employment and entrepreneurship ecosystem with significant socioeconomic and cultural implications. As a result of the global pandemic of COVID-19, it is essential to review the transformations that will further affect that ecosystem. Objective: This article aims to identify the implications of the confluence of the Fourth Industrial Revolution, COVID-19, and Climate Change in terms of the challenges and opportunities faced by entrepreneurs during this remarkable global metamorphosis. Methodology: In our exploration, we use a complexity science perspective to offer a framework for the management of Solidarity Entrepreneurship. Results: We developed a framework to identify the elements that, under the new global context, must be considered to provide alternative perspectives of entrepreneurship oriented to preventing or mitigating the effects caused by the confluence described above. Conclusions: Our proposal recommends an entrepreneur’s skill set that considers the ethical, moral, regulatory, and other innovation and cognitive concerns to optimize entrepreneurial ventures focused on the requirements of the pressing global scenario in progress.

Accelerated learning about institutions, economics, and the environment in the Anthropocene – the Zhejiang Summer Workshop case

ABSTRACT Accelerated learning for the Anthropocene is a recursive process of receiving, processing, and deliberating about the changing state of human-nature relationships in a world, which is characterised by economic growth, social tensions, environmental stress, and increasing interconnectivity. It requires a basic understanding of the role of economics, institutions, and values from a complexity science perspective. This paper is an example of an accelerated learning case. As a response to a 36 hours summer workshop on ‘Institutions, Economics and the Environment in the Anthropocene’ we reflect on the role of economics, institutions, and values for making intelligent decisions in increasingly complex environments and provide an outlook for the future format of learning. An essential insight is that we need more transdisciplinary knowledge exchange at academic institutions, as it is a tool that helps navigating through an increasingly complex world.

Primary health care case management through the lens of complexity: an exploratory study of naturopathic practice using complexity science principles

BackgroundAdvances in systems science creates an opportunity to bring a complexity perspective to health care practices and research. While medical knowledge has greatly progressed using a reductionist and mechanistic philosophy, this approach may be limited in its capacity to manage chronic and complex illness. With its holistic foundation, naturopathy is a primary health profession with a purported alignment with a complexity perspective. As such this pilot study aimed to investigate the application of complexity science principles, strategies, and tools to primary health care using naturopathy as a case study.MethodsA network mapping and analysis of the naturopathic case management process was conducted. Mind maps were created by naturopathic practitioners to reflect their clinical conceptualisation of a common paper clinical case. These mind maps were inputed into Gephi, a network mapping, exploration, and analysis software. Various layouts of the data were produced, and these were analysed using exploratory data analysis and computational network analysis.ResultsSeven naturopathic practitioners participated in the study. In the combined network mapping, 133 unique elements and 399 links were identified. Obesity, the presenting issue in the case, was centrally located. Along with obesity, other keystone elements included: systemic inflammation, dysbiosis, diet, the liver, and mood. Each element was connected on average to 3.05 other elements, with a degree variation between one and 36. Six communities within the dataset were identified, comprising: the nervous system and mood, gastroinstetinal and dietary factors, systemic inflammation and obesity, the endocrine system and metabolism.ConclusionsThis pilot study demonstrates that it is feasible to apply a complexity science perspective to investigating primary health care case management. This supports a shift to viewing the human organism as a complex adaptive system within primary health care settings, with implications for health care practices that are more cognisant with the treatment of chronic and complex conditions and research opportunities to capture the complex clinical reasoning processes of practitioners.

The Future of Burn Care From a Complexity Science Perspective.

Health care is undergoing a profound technological and digital transformation and has become increasingly complex. It is important for burns professionals and researchers to adapt to these developments which may require new ways of thinking and subsequent new strategies. As Einstein has put it: "We must learn to see the world anew." The relatively new scientific discipline "Complexity science" can give more direction to this and is the metaphorical open door that should not go unnoticed in view of the burn care of the future. Complexity science studies "why the whole is more than the sum of the parts." It studies how multiple separate components interact with each other and their environment and how these interactions lead to "behavior of the system." Biological systems are always part of smaller and larger systems and exhibit the behavior of adaptivity, hence the name complex adaptive systems. From the perspective of complexity science, a severe burn injury is an extreme disruption of the "human body system." But this disruption also applies to the systems at the organ and cellular levels. All these systems follow the principles of complex systems. Awareness of the scaling process at multilevel helps to understand and manage the complex situation when dealing with severe burn cases. This paper aims to create awareness of the concept of complexity and to demonstrate the value and possibilities of complexity science methods and tools for the future of burn care through examples from preclinical, clinical, and organizational perspectives in burn care.

Scar formation from the perspective of complexity science: a new look at the biological system as a whole.

A burn wound is a complex systemic disease at multiple levels. Current knowledge of scar formation after burn injury has come from traditional biological and clinical studies. These are normally focused on just a small part of the entire process, which has limited our ability to sufficiently understand the underlying mechanisms and to predict systems behaviour. Scar formation after burn injury is a result of a complex biological system-wound healing. It is a part of a larger whole. In this self-organising system, many components form networks of interactions with each other. These networks of interactions are typically non-linear and change their states dynamically, responding to the environment and showing emergent long-term behaviour. How molecular and cellular data relate to clinical phenomena, especially regarding effective therapies of burn wounds to achieve minimal scarring, is difficult to unravel and comprehend. Complexity science can help bridge this gap by integrating small parts into a larger whole, such that relevant biological mechanisms and data are combined in a computational model to better understand the complexity of the entire biological system. A better understanding of the complex biological system of post-burn scar formation could bring research and treatment regimens to the next level. The aim of this review/position paper is to create more awareness of complexity in scar formation after burn injury by describing the basic principles of complexity science and its potential for burn care professionals.

A complexity science perspective on the impact of adverse socioeconomic conditions on chronic stress

Abstract Chronic stress increases chronic disease risk and may underlie the association between adverse socioeconomic conditions and adverse health outcomes. The relationship between such conditions and chronic stress is complex due to feedback loops between stressor exposure and psychological processes, encompassing different temporal (acute stress response to repeated exposure over the life course) and spatial (biological/psychological/social) scales. We examined this relationship from a complexity science perspective. We developed a causal loop diagram to interpret available evidence. Literature evidence was used to confirm/contest the variables and causal links included in the conceptual framework and refine their conceptualisation. Our findings were evaluated by 8 independent researchers. Adverse socioeconomic conditions imply an accumulation of stressors and increase the likelihood of exposure to uncontrollable childhood and life course stressors. Repetition of such stressors may activate mechanisms that can affect coping resources and coping strategies and stimulate appraisal of subsequent stressors as uncontrollable. We identified 5 feedback loops describing these mechanisms: progressive deterioration of access to coping resources because of repeated insolvability of stressors; perception of stressors as uncontrollable due to learned helplessness; tax on cognitive bandwidth caused by stress; stimulation of problem avoidance to provide relief from the stress response and free up cognitive bandwidth; susceptibility to appraising stimuli as stressors against a background of stress. The complexity science perspective revealed that adverse socioeconomic conditions imply recurrent stressor exposure which impacts chronic stress via amplifying feedback loops that together could be conceptualised as one vicious cycle. Therefore, in order for individual-level psychological interventions to be effective, the context of adverse socioeconomic conditions also needs to be addressed. Key messages We examined the mechanisms underlying the relationship between adverse socioeconomic conditions and chronic stress from a complexity science perspective, focusing on amplifying feedback loops. The complexity science perspective illustrates that interventions are unlikely to be successful if they focus only on individual-level psychological factors.

Understanding the impact of exposure to adverse socioeconomic conditions on chronic stress from a complexity science perspective

BackgroundChronic stress increases chronic disease risk and may underlie the association between exposure to adverse socioeconomic conditions and adverse health outcomes. The relationship between exposure to such conditions and chronic stress is complex due to feedback loops between stressor exposure and psychological processes, encompassing different temporal (acute stress response to repeated exposure over the life course) and spatial (biological/psychological/social) scales. We examined the mechanisms underlying the relationship between exposure to adverse socioeconomic conditions and chronic stress from a complexity science perspective, focusing on amplifying feedback loops across different scales.MethodsWe developed a causal loop diagram (CLD) to interpret available evidence from this perspective. The CLD was drafted by an interdisciplinary group of researchers. Evidence from literature was used to confirm/contest the variables and causal links included in the conceptual framework and refine their conceptualisation. Our findings were evaluated by eight independent researchers.ResultsAdverse socioeconomic conditions imply an accumulation of stressors and increase the likelihood of exposure to uncontrollable childhood and life course stressors. Repetition of such stressors may activate mechanisms that can affect coping resources and coping strategies and stimulate appraisal of subsequent stressors as uncontrollable. We identified five feedback loops describing these mechanisms: (1) progressive deterioration of access to coping resources because of repeated insolvability of stressors; (2) perception of stressors as uncontrollable due to learned helplessness; (3) tax on cognitive bandwidth caused by stress; (4) stimulation of problem avoidance to provide relief from the stress response and free up cognitive bandwidth; and (5) susceptibility to appraising stimuli as stressors against a background of stress.ConclusionsTaking a complexity science perspective reveals that exposure to adverse socioeconomic conditions implies recurrent stressor exposure which impacts chronic stress via amplifying feedback loops that together could be conceptualised as one vicious cycle. This means that in order for individual-level psychological interventions to be effective, the context of exposure to adverse socioeconomic conditions also needs to be addressed.

Conspiracy of Corporate Networks in Corruption Scandals

Corruption in public procurement transforms state institutions into private entities where public resources get diverted for the benefit of a few. On this matter, much of the discussion centers on the legal fulfillment of the procurement process, while there are fewer formal analyses related to the corporate features which are most likely to signal organized crime and corruption. The lack of systematic evidence on this subject has the potential to bias our understanding of corruption, making it overly focused on the public sector. Nevertheless, corruption scandals worldwide tell of the importance of taking a better look at the misuse and abuse of corporations for corrupt purposes. In this context, the research presented here seeks to contribute to the understanding of the criminal conspiracy of companies involved in public procurement corruption scandals under a network and complexity science perspective. To that end, we make use of a unique dataset of the corporate ownership and management information of four important and recently documented cases of corruption in Mexico, where hundreds of companies were used to embezzle billions of dollars. Under a bipartite network approach, we explore the relations between companies and their personnel (shareholders, legal representatives, administrators, and commissioners) in order to characterize their static and dynamic networked structure. In terms of organized crime and using different network properties, we describe how these companies connect with each other due to the existence of shared personnel with role multiplicity, leading to very different conspiracy networks. To best quantify this behavior, we introduce a heuristic network-based conspiracy indicator that together with other network metrics describes the differences and similarities among the networks associated with each corruption case. Finally, we discuss some public policy elements that might be needed to be considered in anti-corruption efforts related to corporate organized crime.

Intra-Urban Scaling Properties Examined by Automatically Extracted City Hotspots from Street Data and Nighttime Light Imagery

A country can be well-comprehended through its core cities. Similarly, we can learn about a city from its hotspots, as they manifest the concentration of urban infrastructures and human activities. Following this philosophy, this paper studies the intra-urban form and function from a complexity science perspective by exploring the power law distribution of hotspot sizes and related socio-economic attributes. To detect hotspots, we rely on spatial clustering of geospatial big data sets, including street data from OpenStreetMap platform and nighttime light (NTL) data from the visible infrared imaging radiometer suite (VIIRS) imagery. Unlike conventional spatial units, which are imposed by governments or authorities (such as census block), the delineation of hotspots is done in a totally bottom-up manner and, more importantly, can help us examine precisely the scaling pattern of urban morphological and functional aspects. This results in two types of urban hotspots—street-based and NTL-based hotspots—being generated across 20 major cities in China. We find that Zipf’s law of hotspot sizes (both types) holds remarkably well for each city, as do the city-size distributions at the country level, indicating a statistically self-similar structure of geographic space. We further find that the urban scaling law can be effectively detected when using NTL-based hotspots as basic units. Furthermore, the comparison between two types of hotspots enables us to gain in-depth insights of urban planning and urban economic development.

A Study on the Evolution Characteristics and Key Drivers of Urban Entrepreneurial Ecosystem: From the Perspective of Complexity Science

activity is a typical complex social system with significant regional heterogeneity. Most of the existing studies focus on explaining a certain aspect of entrepreneurial activities or exploring the extent to which regional entrepreneurial activities promote regional economic growth. However, examining regional entrepreneurial activities from a systematic rather than fragmented perspective may be able to reflect their internal and external quality more comprehensively and accurately. The purpose of this paper is to study the key factors affecting the quality of entrepreneurial activities in large Chinese cities based on the theories of Entrepreneurial and Complexity System, and put forward corresponding recommendation on policy design and policy implementation. Based on a systematic review of studies on city-level entrepreneurial ecosystems and the application of complexity science in entrepreneurial research, The Urban Entrepreneurship Ecosystem Index (UEEI) system is constructed, which consists of three dimensions of synergy, emergence and phase change, 10 first-level indicators and 40 second-level indicators. The cross-section data of 2018 are used to make quantitative analysis on China's top ten quasi-first-tier cities such as Wuhan and Chengdu. The results show that the urban entrepreneurial ecosystem is characterized by coordination, emergence and phase transformation, and the more balanced the three characteristics are, the higher the quality of the urban entrepreneurial ecosystem will be. In terms of specific indicators, employment, technological innovation and education are the key order parameters, and the performance of a key order parameter is particularly excellent, which is a common characteristic of high-quality urban entrepreneurial ecosystem.

Improve the Design and Implementation of Metrics From the Perspective of Complexity Science Comment on "Gaming New Zealand's Emergency Department Target: How and Why Did It Vary Over Time and Between Organisations?"

From the perspective of complexity science, this commentary addresses Tenbensel and colleagues’ study, which reveals varied gaming behaviours to meet the New Zealand Emergency Department (ED) metric. Seven complexityinformed principles previously published in this Journal are applied to formulate recommendations to improve the design and implementation of metrics. (1) Acknowledge unpredictability. When designing a metric, policy-makers need to leave room for flexibility to account for unforeseen situations. When implementing a metric, they need to promote sense-making of relevant stakeholders. (2) Sense-making shall be encouraged because it is a social process to understand a metric, align values and develop a coherent strategy. Sense-making is important to (3) cope with self-organised gaming behaviours and to (4) facilitate interdependencies between ED and other departments as well as organisations. (5) We also need to attend to the relationship between senior management and frontline staff. Additionally, to address one of the methodological weaknesses in Tenbensel and colleagues’ study, (6) adaptive research approach is needed to better answer emerging questions. (7) Conflict should be harnessed productively. I hope these recommendations could limit gaming in future metrics and encourage stakeholders to view inevitable gaming as an improvement opportunity.

Hard Science and "Soft" Skills: Complex Relational Leading.

Since the 1990s, complexity science has been utilized as a metaphor for understanding health care organizations and new ways of leading within them. In this article, 3 principles of complexity leadership put forth by Porter-O'Grady and Malloch in the text Quantum Leadership are explored: (1) wholes are not just the sum of their parts; (2) all health care is local; and (3) value is now the centerpiece of service delivery. Each of these principles is discussed from a 20th-century "organization as machine" perspective, a complexity science perspective, and a complex relational processes (CRP) view. The CRP lens provides a useful bridge from the hard science (nonhuman) systems metaphor to what we often think of as the soft skills of relationship building and communication. CRP does this by drawing on philosophy and the social sciences of sociology and psychology as a way to humanize the nonhuman metaphors of complexity science. This opens up new ways of understanding and talking about leadership in organizations. This shifts our traditional thinking of individuals as leaders to a more relational process of complex relational leading that occurs between people within organizations.

A complexity perspective on logistics management

Purpose The purpose of this paper is to elaborate on how perspectives and assumptions embedded in the complexity paradigm contribute to make logistics management research better aligned with real-life logistics. This is necessary, due to increasing supply chain complexity caused by an increasing request for sustainable development (SD). Design/methodology/approach The research is exploratory and based on a narrative literature review of logistics and supply chain management (SCM) from a complexity science perspective. Qualitative research interviews have been conducted with 12 logistics and supply chain managers in international companies and have focussed on their daily experiences and the underlying assumptions related to their actual work. Findings Logistics and SCM research is embedded in the functionalistic paradigm with reductionistic assumptions as the dominant logic. These do not sufficiently align with the complexity related, for example, to the daily work of SD in logistics management practice. Research limitations/implications It is proposed that the inclusion of complexity-based assumptions in logistics management research can increase realism in the advancement of the discipline. A key result is that the recognition of logistics as complex means inclusion of human and social aspects – which is apparent in any logistics process or phenomenon – in logistics knowledge creation processes. Practical implications Increased realism in logistics management research by addressing complexity, instead of merely reducing it, will provide logistics and supply chain managers with increased understanding and appropriate knowledge when they deal with emerging challenges such as SD. Originality/value Based on Boulding’s levels of complexity, this paper challenges the underlying assumptions of logistics management in research and practice, and provides reflective frameworks for advancing the discipline and aligning it to the complexity of contemporary challenges in logistics management.