Why We Cannot Know Complex Things Completely

In a world seemingly committed to more complex systems, design science should be embracing the 'sciences of complexity'. Otherwise, its usefulness will be limited to those 'tame' problems amenable to its current methods, unable to address the 'wicked' problems which increasingly populate our world. There is already a large body of practical experience with complexity theory on which design scientists can draw. Placing complexity theory in an evolutionary context, based on General Evolution Theory (GET), could be the next frontier for design science. GET enriches time perspectives and 'patterns' in complexity theory, both elements useful to design practice. A particular benefit of Complexity and General Evolution Theories is that they span all dynamic systems, and thereby diminish the disciplinary barriers between the physical, biological and social sciences which have for so long bedevilled practice. The methodological issues in broadening design science to incorporate reductivist, systemic, and evolutionary perspectives are considered, and a meta-methodology based on Participatory Action Research is proposed as a way to integrate these very different epistemologies.

1. Using Complexity Theory for Research and Program Evaluation Michael Wolf-Branigin (author), Oxford University Press, 2013, ISBN: 9780199829460 (paperback) 2. Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use Michael Quinn Patton (author), The Guilford Press, 2011, ISBN: 9781606238721 (paperback) 3. Evaluating the Complex: Attribution, Contribution, and Beyond Kim Forss, Mita Marra and Robert Schwartz (eds), Transaction Publishers, 2011, ISBN: 9781412818469 (hardback)

Every emerging industry has the following unique characteristics: strong technological uncertainty, imperfect industry construct, many in embryonic companies and spin-offs, first time buyers with information asymmetry, and government intervention. All these characteristics result in the diversification and complexity of an emerging industry s development. This is quite different from traditional industries; therefore we must examine the subject with a different theoretical perspective. In order to acquire an in-depth understanding of the development of emerging industries, this research is conducted from the perspective of complexity theory. In this research, the complexity adaptive system is employed to serve as a framework for industry analysis which reviews the behaviors and strategies adopted by the firms in the E-Learning industry. By studying the novel E-Learning industry, this paper aims to seek out the developmental model of emerging industries and to present the concrete implications for management. This paper first discusses the origin of chaos science and the development of complexity theory. These are then followed by the background of the E-Learning industry in Taiwan. In the third section, methodologies adopted in this research, including data collection and analytical methods are explained in detail. The acquired data is then analyzed using the complexity adaptive system which ultimately reveals the dynamic developmental process of the E-Learning industry in Taiwan. Finally this paper concludes with some implications derived from the research. Taking a comprehensive look at the E-Learning industry in Taiwan, there are several observed phenomena which are quite different from those experienced in the past. This indicates the ever increasing developmental diversity and complexity of emerging industries in today marketplace. Due to a minimal level of entry barriers, it is relatively easy for new players to enter the E-Learning industry. In 2000, almost 20 companies entered into the E-Learning industry. The scale of investments made by these companies was not very large and depending on the market situation, the size of the firms could be flexibly adjusted. It is also relatively simple for these new entrants to withdraw from the E-learning industry. As a result, there are frequent and significant shj/is in market positions, particularly when small firms explore and seize opportunities which larger-scale firms fail to spot. From a technical aspect, firms in the E-learning industry are required to integrate a variety of technology spanning different fields. These technologies include networking, multimedia, computer-mediated teaching and others, This is quite different from traditional industries and thus the innovation curve of the E-Learning industry quite disparate. This research is a qualitative case study which entails a 28-month period for acquiring data and information. The datacollection period occurred between August 2000 and December 2002 and personal interviews were the primary sources for data collection. Interviews were conducted using the semi-structured questionnaires and the duration of each interview was between one and two hours. In total, 18 interviews were carried out and interviewees included both middle and high management professionals as well as technical consultants. All targeted interviewees were considered crucial strategy makers to the firms involved. In order to judiciously analyze the data collected, all interviews were first tape recorded and the contents were subsequently transcribed, thoroughly studied and analyzed. Having repeatedly scrutinized the transcripts, we also composed business cases for each of the 8 firms interviewed. We endeavored to analyze the data by means of graphic reorganization. Once further questions or information gaps were uncovered, we would conduct further research in order to quest for additional information and would ultimately discover the answers. This is an iterated process, which reflects the conscientiousness and accuracy of this research. It is almost guaranteed that every emerging industry has the following unique characteristics: high technological uncertainty, lack of industry standards, high involvement of start-up companies and spin-offs, first time buyers with inconsistent information, and government intervention. All these characteristics result in the diversification and complexity of an emerging industry s development. This is quite different from traditional industries. Therefore, we must examine the subject with a different, yet innovative theoretical approach. Our research adopted the Complexity Theory perspective to study the nonlinear dynamic developments of E-Learning industry in Taiwan. We discovered that the emerging industry c characteristics correspond to the four elements of the Complex Adaptive Systems (CAS) 1) Agents with varied schemas, 2) Punctuated equilibrium of environment, 3) Emerging orders of system, and 4) Intricate networks and convolution. The implications derived from this research induce scholars and managers to rethink the traditional strategic management theories, which may mislead contemporary businesses' development. Finally, we present four new strategic elements that will accelerate the development of an emerging industry. 1. Competition. A business's competitive strategies in the emerging industry do not raise the entry barriers for competitors. In actual fact, strong competitions build up the integration mechanisms for the particular industry. 2. Growth: A business s growth does not rely on long-term strategic planning, but on short-term creative action planning, and will dominate in the industry with luck coming. 3. Survival: A business c survival is not dependent upon an optimal strategic position but on strategic options. 4. Profits: The source of a business's profits does not fully rely on the economic-technical competitions, but on ”legitimacy” created through cooperation between businesses.

The paper examines the evolution in international commercial marriage migration from Southeast Asia to South Korea from a Complexity Theory (CT) framework, originally from natural sciences but vastly entering the field of social sciences. CT stresses the non-linear nature of complex systems that are composed of a large number of individual components operating within a conditioned boundary whose interactions lead emergent properties in an unpredictable way. The study is based on the author’s fieldwork interviews and participatory observations of marriage migrants, government officers, and social workers in South Korea in 2010-2013, which establishes five phases of brokered marriages, namely, (1) Outsourcing Brides (mid 1980s-), (2) Emerging Anti-Trafficking Norms (early 2000s-), (3) Institutionalizing Multiculturalism (2006- ), (4) Regulating Brokers (2008-), and 5) Sham Marriages and Emerging Nationalism (2010-). She explains the key elements of marriage migration as a complex adaptive system such as feedback loops, adaptation, emergence, self-organisation and agency, and suggests persistent observation and CT as an alternative methodology to study migration.

A central question in complexity theory is how large-scale phenomena, such as such as self-organisation, perpetual novelty, and sustained diversity, emerge. Complex systems can be understood as networks of interacting components. The focus of this research is the role that the properties of such networks play in self-organisation and emergence in complex systems. Based on the previously known concept of Dual Phase Evolution (DPE), I propose a theoretical framework, within which recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. This DPE framework extends and refines the original concept. Networks can exist in two general connectivity phases: well connected and poorly connected. DPE relates each of the two connectivity phases and the transition events between them to typical system dynamics. I analyse empirical and experimental evidence from published studies in areas as diverse as physics, biology, socio-economics, mathematics and computer science. The analysis implies that DPE is widespread and operates in many kinds of complex systems, where it drives emergence and self-organisation. What is more, the analysis uncovers hitherto unstudied deep similarities and common underlying processes between different complex systems. To further understand the theoretical concepts of the DPE framework, I apply DPE in studies of mechanisms behind particular emergent properties in several types of complex systems: Seeking to better understand the emergence of novelty and diversity in ecosystems, I develop and study an individual-based simulation model of adaptive radiation (speciation) in landscapes. Simulation results imply that recurrent external disturbances facilitate perpetual novelty and diversity in landscape populations through two complementary mechanisms: One mechanism constitutes recurrent DPE phase changes in landscape connectivity on several levels. The other mechanism is alteration of the environment in disturbed areas leading to modified selection regimes. As a result of the simulation studies of landscape evolution, I develop a new genetic model that combines the advantages of two existing genetic models. The new model allows individual-based simulation studies of genetics on holey fineness landscapes (HFLs). Such fitness landscapes result from biochemical constraints to genetic viability and have previously only been studied analytically. Simulation studies of reproductive isolation uncover that when HFLs are considered, common predictions about maintenance of reproductive isolation in migrating populations change. Results also show that HFL-genetics can facilitate the emergence of stable hybrid populations, and the evolution of social selection though reinforcement. Continuing to study and apply DPE, I investigate how DPE processes can lead to the emergence of important network topologies. Using simulations models, I demonstrate two possible mechanisms behind emergent connectivity phase transitions without facilitation by external stimuli. A study of social network models reveals simple mechanisms that lead to structures typical of some real social networks and points towards general principles for emergence of important topologies such as modularity. A study of a network model of co-operations in markets reveals further mechanisms behind the emergence of complex and hierarchical modularity. Generative models for scale-free networks, that are ubiquitous in many natural systems, are well known, however, such models apply to growing networks. I propose and examine a generative model for scale-free topologies that can account for some scale-free networks of constant size found in nature. A wider context for DPE as a framework for reasoning about complexity is provided by examining the relationship between DPE and other established concepts such as Self-Organised Criticality and the Adaptive Cycle. In conclusion, DPE complements other established theories. In general, network-theoretical approaches, such as DPE, are powerful paradigms in understanding complexity. This thesis shows that recurrent changes in connectivity of component interaction networks constitute a broad mechanism for emergence and self-organisation in complex systems, and demonstrates this mechanism in several specific biological and socio-economic systems.

Este artículo tiene por objeto subyacente abordar un nuevo diálogo entre derecho y ciencia basado en la aplicación de las teorías del caos y de la complejidad al ámbito jurídico. Para ello se sirve, a modo introductorio, de los diversos artículos en los que el estadounidense John B. Ruhl se ha ocupado de esta materia. Así, además de una descripción breve de las teorías, se discute acerca de la aplicabilidad directa o analógica de las mismas y se presentan los elementos que, a juicio del Ruhl, permiten considerar al derecho como un sistema adaptativo complejo, además de su propuesta normativa.

Descriptive complexity theory is the area of theoretical computer science that is concerned with the abstract characterization of computations by means of mathematical logics. It shares the approach of complexity theory to classify problems on the basis of the resources that are needed to solve them. Instead of computational resources, however, descriptive complexity theory considers the expressiveness necessary for a logic to define classes of problems. Its primary goal is to provide alternative characterizations of computational complexity that give us a way to reason about the strengths and limitations of computational procedures without reference to the underlying machine model. This thesis is making contributions to three strands of descriptive complexity theory. First, we consider an incongruence between machine computations, which receive ordered strings as their input, and logics, whose abstract view on input structures omits the ordering. We show that a combinatorial, singly exponential-time graph canonization algorithm of Corneil and Goldberg (1984) can be extended to edge-colored directed graphs. The algorithm’s input invariance allows us to implement it in the logic Choiceless Polynomial Time with Counting (CPT+C) if we restrict our attention to logarithmic-sized fragments of such graphs. This means that on structures whose relations are of arity at most 2, the polynomial-time (PTIME) properties of logarithmic-sized fragments are precisely characterized by CPT+C. The second contribution investigates the descriptive complexity of PTIME computations on restricted classes of graphs. We present a novel canonical form for the class of interval graphs which is definable in fixed-point logic with counting (FP+C), resulting in FP+C capturing PTIME on this graph class. The methods developed for this result may serve as the foundation for a systematic study of the interrelation of logics and complexity classes on the basis of modular decompositions of graphs. Then we introduce the notion of non-capturing reductions that lead us to a wide variety of graph classes on which computational problems are equally hard to characterize as on the class of all graphs. We finally mold our methods into a canonical labeling algorithm for interval graphs which is computable in logarithmic space (LOGSPACE) and we draw the conclusion that interval graph isomorphism is complete for LOGSPACE. In this way, our methods developed for the logical domain make a contribution to classical complexity theory. In the final part of this thesis, we take aim at the open question whether there exists a logic which generally captures polynomial-time computations. We introduce a variety of rank logics with the ability to compute the ranks of matrices over (finite) prime fields. We argue that this introduction of linear algebra makes for a robust notion of a logic and that it increases the expressiveness of FP+C and many other logics considered in the context of capturing PTIME. By adapting a construction of Hella (1996), we establish that rank logics strictly gain in expressiveness when we increase the number of variables that index the matrices we consider. Rank computations are the first natural operation for which this property is shown in the presence of recursion. Our particular choice of rank computations is justified by showing that most classic problems in linear algebra can either be defined by rank logics or are already definable in FP+C. Then we establish a direct connection to standard complexity theory by showing that in the presence of orders, a variety of complexity classes between LOGSPACE and PTIME can be characterized by suitably defined rank logics. Our exposition provides evidence that rank logics are a natural object to study and establishes the most expressive of our rank logics as a viable candidate for capturing PTIME, suggesting that rank logics need to be better understood if progress is to be made towards a logic for polynomial time.

Safety is a major concern in the oil and gas industry due to accidents with the potential for catastrophic consequences. One of these was the Piper Alpha drilling platform disaster in 1988, which resulted in the loss of the Piper Alpha platform and the subsequently 167 lives; the worst disaster in the oil and gas industry. To foster a proactive approach in the prevention of workplace injuries, organisations have turned towards key predictors of safety, such as leadership. However, simply practising leadership behaviours is not enough to improve safety, especially in safety-critical organisations. An inability to move beyond the formal control inherent in traditional bureaucratic mindsets limits the applicability of mainstream leadership theories for safety-critical organisations. To address this challenge, this research study adopts a different paradigm for leadership, one which frames leadership as a complex interactive dynamic from which adaptive outcomes emerge as complexity science. Hence, the aim of this research study was to investigate the direct relationship between leadership behaviours and safety outcomes, and the mediating effect of complexity science principles. To accomplish this, a conceptual model was developed using theoretical foundation built from the literature review. The model comprises three main components: 1) leadership behaviours, 2) five complexity science principles (connectivity, interdependence, feedback, exploration-of-the-space-of-possibilities and co-evolution) and 3) three safety outcomes (safety participation, safety compliance and safety climate). These components were linked by the proposed hypotheses that were established based on assumed theoretical relationships. To assess and validate the conceptual model and test the hypotheses, a series of quantitative approaches were employed. A multivariate statistical approach was utilised for data collection through a questionnaire survey; 173 project managers participated in the survey. These individuals are responsible for emergency commands, as well as the day-to-day management of safety. Principal component analysis/Exploratory factor analysis was performed to identify the factor structures representing each underlying construct. Confirmatory factor analysis was conducted to validate the results obtained from the exploratory factor analysis, followed by multiple regression analysis. Next, structural equation modelling was applied to test the structural models for hypotheses testing. The regression analyses demonstrated that all three identified leadership behaviours — 1) empowering & engaging, 2) modelling & reinforcing, and 3) promoting & enabling — directly influenced the level of safety participation and safety compliance. Additionally, all five principles of complexity science mediated the relationship between empowering & engaging leadership behaviour, and safety participation and safety compliance. As for the hypothesised relationship between modelling & reinforcing leadership behaviour and safety outcomes, apart from the co-evolution principle, all other complexity science principles arbitrated the relationship with safety participation and safety compliance. Furthermore, the relationships between promoting & enabling leadership behaviour, and safety participation and safety compliance were mediated by all five principles of complexity science. Finally, structural equation modelling was used to refine and confirm the findings of the regression analysis, verifying both empowering & engaging, and promoting & enabling leadership behaviours have direct and indirect influences on safety participation and safety compliance levels as a result of all five complexity science principles. And established that modelling & reinforcing leadership behaviour has direct and indirect effects on safety participation and safety compliance levels under the influence of only four complexity science principles — namely, connectivity, interdependence, feedback and exploration-of-the-space-of-possibilities. On the basis of the research results, this study provides insight into the understanding of safety leadership by the empirical evidence that displayed the relationships between the three leadership behaviour constructs and their contribution to the effect of complexity science principles and safety outcomes within the oil and gas industry. From these results, the study provides a list of recommendations for research on the effect of leadership behaviours on complexity science principles and safety outcomes.

This article examines complexity theories and their applicability for social studies. Once these theories revealed complex system of autopoietic self-organization, nonlinearity and far from equilibrium social theoretics were encouraged to apply complexity methodology to investigate social complexity in a frame of political studies, sociology, international relations and other social disciplines. As a particular case, the article studies John Urry’s profound contributions to complexity theoretical shifts in social science. He was not only one of the most important British sociologists, but also a scholar network builder and public intellectual who changed the face of British, and indeed global, social theory. Known as a creator of the new mobility paradigm associated with a ‘Lancaster School’, he stands in contrast to the empiricist traditions in American and British social sciences, while struggling for post-disciplinary approach against the hierarchies of academic departments, and their disciplinary closure. This also explains his critique of conventional sociology and its division from the natural sciences. J. Urry was primarily a macro-level thinker concerned with systems and global processes. Therefore, his project starts with complexity theory and its implications in terms of global complexity, complexity of social sciences in opposition to its previous linearity and structure/agent duality. J. Urry argues for breaking down the division between ‘natural’ and ‘social’ sciences, since both are characterized by complexity This complexity turn led Urry directly into his conceptualization of mobilities as a second theoretical turn, which deals with dynamic urban forms and automobility. Finally, a third theoretical turn in his thinking is geo-ecological. Here J. Urry is acting as a micro-level theorist of the body, leisure, consuming, tourism and nature. Tracing this trajectory of his theoretical evolution is more informative for it moves us from his early recognition of large-scaled complexity into reconsidered human-scaled problems of how we ought to live in the world. Key words: social and natural sciences, theory of complex systems, chaos theory, mobility, John Urry.

Con seguridad, las ciencias sociales o humanas son las más complejas de todas las ciencias y disciplinas. Esta es una verdad que va de suyo. En ciencia, sin embargo, La intuición no es suficiente, pues, en numerosas ocasiones, hay que demostrarla. Con este artículo, basado en una revisión bibliográfica sobre el tema, me propongo demostrar que las ciencias sociales o humanas son complejas en el mismo sentido que se dice, por ejemplo, que la física, la biología o las matemáticas son ciencias complejas. Hacia el final, me enfoco, de manera particular, en algunas contribuciones que la antropología puede hacer a las ciencias de la complejidad. Key Words: Non-linearity, artificial social sciences, natural social sciences, human social sciences, philosophy of science

In this text I am going to argue that unless it opens itself to discussions that dominate contemporary social and human sciences, and unless protection of the specificity of historical research is undertaken, there is a real risk that history might be reduced to the status of an auxiliary science of other human and social sciences that have thus far been more successful in interpreting contemporary events and phenomena which have traditionally been consigned to the field of history. I claim that the weak points of contemporary historical studies are methodology and theory separated from empirical research in such a way that they are unable to capture complex phenomena which have emerged with the advent of modernity. In order to link practice and theory, I propose to appropriate for historical research what has been called ”grounded theory”-theory developed out of data, and which uses comparative approaches and case studies as its main methods. The text contains two parts: in part one, I indicate ways in which theories in contemporary human and social science have failed to deal with historical change and in part two, I sketch a methodology of grounded theory.

The pluralistic and often competing goals of myriad constituents, the changing demographics of students, the uncertainty of funding, and the growing demands for accountability from stakeholders have increased the complexity of systems which community college leaders must manage. Emerging from the recent literature on community colleges is a call for new models of leadership in the context of leading in an increasingly uncertain and complex environment. Systems thinking offers a means to help leaders respond to these growing organizational complexities and move leadership from a traditional bureaucratic model to a more adaptive model better suited for today's dynamic community colleges. Despite a robust body of literature on systems thinking in myriad fields, there is comparatively scant evidence of systems thinking's application to organizational management or leadership per se in higher education and even less in community colleges. Hence, a systematic review of literature on systems thinking and complexity theory and their application in higher education was bolstered with evidence from healthcare. Findings reveal three reoccurring ways in which leaders apply systems thinking processes for improving organizational performance. A conceptual model for systems thinking leadership is proposed in which the three processes, characterized as discovery , framing , and action , can be enacted either individually or sequentially for enhancing organizational performance. The model draws upon boundary critique, critical systems thinking, systemic intervention, total systems intervention, systems dynamics, soft systems methodology, complexity theory and complex adaptive systems, yet uses language more readily identifiable and accessible to community college practitioners to encourage the use of these systemic practices. Systems Thinking Leadership, as proposed in this paper, provides a framework for community college leaders-presidents, chief academic officers, deans, department chairs, and faculty-to view their organization through a systems lens, and to enact and engage the adaptive and participatory practices of discovery, framing, and action for improving organizational performance.

The approach to environmental complexity in this text dissociates itself from the notions of physis generativity, the ecologization of the mind, the sciences of complexity, interdisciplinary methods and complex thought. Environmental complexity is conceived from the perspective of a crisis of knowledge, the objectification of the world, the intervention of knowledge about nature, and the appearance of hybrid entities that go beyond the traditional meaning of ontology and epistemology. Environmental rationality is based on a new meeting of the real and the symbolic, on the resignification of the world and nature, on a network of relationships of otherness among beings, and on a dialogue of knowledge, where the being is reconfigured, its identities are reconstituted, and new social actors are created within a policy of difference guided by the desire for knowledge and justice in the social reappropriation of the world and nature.

El paradigma epistemológico basado en el reduccionismo y el determinismo está en un momento de quiebre, provocado entre otras cosas, por el paradigma de la complejidad. El objetivo del presente artículo de revisión es identificar las contribuciones y/o cooperaciones que las ciencias de la complejidad (CC) y el pensamiento complejo (PC) realizan a la psicoterapia (PSIT), y establecer los avances significativos, controversias y vías de investigación. Se realiza una investigación descriptiva basada en una revisión bibliográfica especializada sobre las relaciones entre tres categorías nucleares: CC, PC, y PSIT. El tamaño final de la muestra fue de 18 documentos de los 46 que arrojó la búsqueda inicial. Se discuten los posibles peligros en la investigación entre complejidad y PSIT, a saber: la hiper-instrumentalización y la superficialidad, señalando los desafíos que el psicoterapeuta debe asumir para trabajar desde y hacia la complejidad. Se identifican los tipos de aportaciones que hace la complejidad a la PSIT y se agrupan en cinco vértices: técnico, pedagógico, conceptual, terapéutico y epistémico. A partir de ellos se concluye que las CC y el PC problematizan, amplían y profundizan el horizonte científico y ético de la psicoterapia, en esa misma dirección la epistemología compleja se configura en marco de referencia teórico para enseñar/aprender y pensar/investigar PSITs críticas y para realizar procesos de integración entre diferentes modelos psicoterapéuticos.

Tagore's anti-absolutist and anti-statist stand is predicated primarily on his vision of global peace and concord'a world of different peoples and cultures united by amity and humanity. While this grand vision of a brave new world is laudable, it is, nevertheless, constructed on misunderstanding and misreading of history and of the role of the nation state in the West since its rise sometime during the late medieval and early modern times. Tagore views state as an artificial mechanism, indeed a machine that thrives on coercion, conflict, and terror by subverting people's freedom and culture. This paper seeks to argue that the state also played historically a significant role in enhancing and enriching culture and civilization. His view of an ideal human society is sublime, but by the same token, somewhat ahistorical and anti-modern.,