Evolution, Emergence, and Learning in Complex Systems

McCarthy I., Leseure M., Ridgway K., Fieller N.

This article presents the findings of an investigation into the classification of manufacturing systems based on cladistics and the theory of natural selection. The article describes the benefits and application of cladistic classifications for those concerned with manufacturing advancement and technology management. The information presented provides researchers and consultants who have no prior knowledge of classification theory, with an introduction to this school of classification, along with rules and guidelines on how to construct, validate and analyse a manufacturing system cladogram.

McCarthy I.

Provides a fresh and novel approach to an established problem; the classification of manufacturing systems. Reviews existing manufacturing classifications and biological taxonomy. Proposes a consistent vocabulary and preliminary guidelines for the successful development of other classifications (FMS types, levels of technology, etc.). Aims to aid the construction of competent classifications that will advance the understanding of manufacturing system modelling and design. Supports proposals by novel comparisons drawn from the “science of diversity”, systematics, and the 200 years of experience that biological taxonomy has to offer.

McKelvey B.

Eigen M., Schuster P.

Allen P.M.

By treating mutant populations as fluctuations relating to the structural stability of the equations of population dynamics, a criterion is developed permitting the prediction of long-term population trends in an evolving eco-system. As an illustration it is shown that the ratio of predator to prey biomass increases under the effects of their combined evolution.

Patil A., Srivastava S., Paul S.K., Dwivedi A.

PurposeProduction systems occupy geographically dispersed organizations with limited visibility and transparency. Such limitations create operational inefficiencies across the Supply Chain (SC). Recently, researchers have started exploring applications of Digital Twins Technology (DTT) to improve SC operations. In this context, there is a need to provide comprehensive theoretical knowledge and frameworks to help stakeholders understand the adoption of DTT. This study aims to fulfill the research gap by empirically investigating DTT readiness to enable transparency in SC.Design/methodology/approachA comprehensive literature survey was conducted to develop a theoretical model related to Supply Chain Transparency (SCT) and DTT readiness. Then, a questionnaire was developed based on the proposed theoretical model, and data was collected from Indian manufacturers. The data was analyzed using Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) to confirm the proposed relationships.FindingsThe findings from the study confirmed a positive relationship between DTT implementation and SCT. This study reported that data readiness, perceived values and benefits of DTT, and organizational readiness and leadership support influence DTT readiness and further lead to SCT.Originality/valueThis study contributes to the literature and knowledge by uniquely mapping and validating various interactions between DTT readiness and sustainable SC performance.

Abbasi M., Varga L.

PurposeThe purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.Design/methodology/approachThe research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.FindingsThe main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.Originality/valueRecognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

Massari G.F., Giannoccaro I.

Today supply chain operations are continuously threatened by frequent and unpredictable disruptions. To survive in such complex and fast-changing environments, firms need to develop resilient strategies for their supply chains. To this regard, previous studies in literature have shown that cooperative relationships play a relevant role. However, there are evidence that firms more often prefer a coopetition strategy, where both cooperative and competitive relationships are simultaneously adopted to manage supply chain relationships. Despite the relevance of this topic, how coopetitive relationships influence resilience has been less investigated so far. In this paper, we use a complex adaptive system approach to conceptualize horizontal coopetition in supply chains and develop a novel agent-based model to simulate its effect on supply chain resilient performance in different environmental conditions, characterized by increasing level of complexity and frequency of disruptions. Results show that coopetition can be beneficial for supply chain resilience and that environmental complexity (turbulence) positively (negatively) moderates this relation. Theoretical contributions and managerial implications are finally discussed.

Hazy J.K.

This paper applies concepts from complexity science to describe corruption risk in the context of various types of uncertainty intrinsic to social interaction systems [12]. This is in contrast to typical approaches that focus on individual ethics and agency issues that are observed during human organizing (cf. [23]). More specifically, this article argues that disequilibrium conditions in organizations [15, 16] emerge as opportunity tension [7] creates value potential which perturbs the alignment of attention among the agent population related to their expectations about the benefits of participating in the organizational system.

Scott S., Hughes M., Ribeiro-Soriano D.

We conceptualize entrepreneurial ecosystems as fundamentally reliant on networks and explore how and under what conditions inter-organizational networks lead an entrepreneurial ecosystem to form and evolve. It is widely accepted that entrepreneurial ecosystems possess a variety of symbiotic relationships. Research has focused considerable efforts in refining the structure and content of resources found within these networked relationships. However, merely focusing on actor-level characterizations dilutes the notion that social relationships change and are complex. There has been little conceptual treatment of the behavioral and governance factors that underpin how quality interactions composing an entrepreneurial ecosystem develop and change over time. In response, we provide a longitudinal ethnographic study examining how ecosystems are managed and evolve in their relational configurations and governance at critical junctures. Using mixed methods and data collected over 3 years, we reveal a cyclical process of relational development central to the initiation, development, and maintenance phases of a valuable entrepreneurial ecosystem. We contribute to a conceptualization of effective ecosystems as reliant on networks, we reveal the behavior and governance characteristics at play in the entrepreneurial ecosystem during each phase of its evolution.

Bazan C., Gaultois H., Shaikh A., Gillespie K., Frederick S., Amjad A., Yap S., Finn C., Rayner J., Belal N.

This systematic literature review aims at understanding the influence of the university’s environment and support system (ESS) in shaping the social entrepreneurial intention (SEI) of post-secondary education students. Social entrepreneurs play an important role in the economic and social developments of the communities in which they operate, thus many post-secondary institutions are starting to encourage more students to engage in social entrepreneurial behaviour. Consequently, there is a need for systematic approaches to evaluate the impact of various motivational factors related to the university’s entrepreneurial ecosystem that could affect the SEI of students. Based on a systematic literature review and narrative synthesis of the antecedents of the SEI of post-secondary education students, the authors proposed a customized SEI model that modifies and extend the one proposed by Hockerts (Entrepreneurship: Theory and Practice, 2017) and Mair and Noboa (Social entrepreneurship, 2006). This study fills a gap in the literature by providing a methodology grounded in theory that can help universities to design their educational and other interventions aimed at encouraging more students to consider social entrepreneurship as a viable career choice after graduation.

Desai S., Blackler A., Popovic V.

Intuitive features could make complex products and interfaces easier to use for children, and designing for embodied interactions is considered as one of the ways to make products and interfaces intuitive to use. However, there is lack of empirical study to validate this relationship and to determine how embodiment could be integrated in the design of products and interfaces. This study has explored embodiment for intuitive interaction in children. The research question for the study was: what is the role of design aspects of embodiment in facilitation of intuitive interaction in children in the context of tactile interactions. The study identified the extent to which design aspects of embodiment facilitate intuitive interaction in children. An observational study with 108 children (55 girls and 53 boys) was carried out. Half of them played with physical Jenga and the other half played with a virtual Jenga. The physical Jenga demonstrated more intuitive interactions than the equivalent virtual interface. Physical affordance is the prime contributor to children’s intuitive interaction with physical products while perceived affordance is the prime contributor to children’s intuitive interaction with virtual interfaces. Embodied interactions can be achieved through the following design aspects of embodiment - physical affordances, perceived affordances, scaffolding, emergence and cooperative activity. The study has further provided recommendations to make interfaces embodied and intuitive through the Enhanced Framework for Intuitive Interaction. These findings are significant as they provide insights into children’s embodied and intuitive interactions, which contribute to the broader context of children’s interaction with physical products and virtual interfaces.

Nilsson F.R.

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.

Hazy J.K.

This chapter suggests an analytical framework that researchers can use to explore the dual relationship connecting intentional fine-grain interaction with course-gain structures and outcomes. On the one hand, it identifies a potential causal link between individual fine-grain action and resulting course-grain outcomes, and on the other hand, it clarifies the dual link that describes the influence of coarse-grain structure on fine-grain interactions. To do this, it introduces a putative force called structural attraction that influences behavior of individuals in consistent patterns within populations. The chapter posits that a mean-field model of structural attraction reflects a biasing force that influences the behavior of individuals as they use information that they decode from the ordered structure itself. It further describes three types of structural attractors, each exploiting a distinct conceptual symmetry that signals underlying simplicity in the environment. Physical structural attractors exploit translational symmetry to reduce spatial complexity. By doing so, these attractors make physical action more efficient and predictable. Dynamic structural attraction exploits periodic symmetries to reduce temporal complexity and make iterative dynamic processes more effective and adaptive. Finally, social structural attractors exploit symmetry within equivalence classes. This reduces social complexity by sorting people into formal categories as a means to make social interactions and task coordination within and among groups more understandable and predictable. Leaders can construct each of these attractor types from the fine-grain to the coarse-grain as a means to serve various individual and organizational purposes. The chapter closes with a discussion of the benefits and risks that arise from the construction and emergence of structural attractors and an exploration of the implications that scale-crossing properties of structural attractors imply for individuals and organizations.

Kiridena S., Sense A.

The current understanding of project complexity is limited in that there is neither a widely recognized conceptualization of project complexity nor a convergent view on how to deal with its effects. Drawing on the extant literature concerning project complexity and complexity science, this article develops a coherent and holistic profile of project complexity and provides reflections on its implications for project management theory and practice. This profile serves as a touchstone for practitioners to better understand, assess, and address complexity in their projects and as an aid to researchers in framing their research efforts.

Giannoccaro I.

This paper investigates the relationship between learning and adaptation in supply chains located within industrial districts, with the aim of identifying the best adaptive supply chain. It is motivated by the increasing attention that the design of adaptive supply chains has been receiving in recent years, as it is considered one of the most important critical factors in gaining sustainable competitive advantage in the current hypercompetitive environment. Focusing on two learning processes (i.e., by imitation and by interacting), diverse types of adaptive supply chains recognizable within industrial districts are compared by means of an agent-based simulation on the basis of their adaptive performance in environments characterized by different level of complexity and turbulence. The results confirm that the supply chain type influences the relationship between learning and adaptation and that both the product complexity and the turbulence of the environment moderate this effect. Finally, the best adaptive supply chain in each type of context is identified.

Liang T.Y.

Abstract Recognizing the inherent strengths and weaknesses of human agents and organizations, as well as changing characteristics and behavior of the interacting agents is the key fundamental to better adaptation, leadership, governance, resilience and sustainability. In all human organizations, the agents are human beings each embedded with an intrinsic intense intelligence source that could easily transform their behavioral schemata. Thus, contradictory to the Newtonian/design paradigm, the group/organizational dynamic of human agents is complex, nonlinear, constantly/continuously changing, and can be unpredictable. In addition, complexity in the human world can be relativistic. Consequently, human agent/organization may perceive certain spaces of complexity as spaces of relativistic order – relativistic complexity. In particular, due the presence of the intense mental dimension in humanity – complexity is in the mind of the beholder. In human existence, leadership and governance are spontaneously emerging key requirements – a primary trait for collective survival. Currently, with more knowledge-intensive and participative new agents (self-powered intrinsic leadership) who possess modified beliefs, values, norms, and expectations that are dissimilar from the older generations, governance and leadership need deeper analysis and redefinition. Traditional governance systems in all categories of organization are manifesting their constraint, vulnerability, and incompetency, in particular, incoherency due to new values and cultural pressure, and their associated self-organizing networks – especially informal networks that demand change, a more commonly observed worldwide phenomenon. In this respect, special attend has to be focus on the highly nonlinear relational parameter is beneficial. This study adopts the intelligence mindset that concurrently focuses on intelligence/consciousness-centricity, complexity-centricity, and network-centricity as the new strategic path towards better adaptive governance and the new leadership. It concentrates on the self-powered agents that are also intrinsic leaders/actors. The new intelligence leadership focal point include nurturing intense collective intelligence (more actors), the critical ability of self-organizing communications, immersion of leadership nodes in networks/clusters (including e-governance), increasing coherency of complex networks (interdependency of network of networks, network management), exploiting selected spaces of complexity (complexity management), and intelligence-driven self-transcending constructions that better facilitates emergence through ‘multi-lateral’ dynamics (minimizing ‘direct’ governance). This intelligence governance strategy emphasizes that mass lateral collectivity rather than selective enforced hierarchical empowerment is the more effective approach in the present contact. Fundamentally, optimizing the ‘everybody is in charge’ phenomenon frequently is a more viable option.

Allen P.M.

Complexity science provides a general mathematical basis for evolutionary thinking. It makes us face the inherent, irreducible nature of uncertainty and the limits to knowledge and prediction. Complex, evolutionary systems work on the basis of on-going, continuous internal processes of exploration, experimentation and innovation at their underlying levels. This is acted upon by the level above, leading to a selection process on the lower levels and a probing of the stability of the level above. This could either be an organizational level above, or the potential market place. Models aimed at predicting system behaviour therefore consist of assumptions of constraints on the micro-level – and because of inertia or conformity may be approximately true for some unspecified time. However, systems without strong mechanisms of repression and conformity will evolve, innovate and change, creating new emergent structures, capabilities and characteristics. Systems with no individual freedom at their lower levels will have predictable behaviour in the short term – but will not survive in the long term. Creative, innovative, evolving systems, on the other hand, will more probably survive over longer times, but will not have predictable characteristics or behaviour. These minimal mechanisms are all that are required to explain (though not predict) the co-evolutionary processes occurring in markets, organizations, and indeed in emergent, evolutionary communities of practice. Some examples will be presented briefly.

Allen P.M.

Complexity science provides a general mathematical basis for evolutionary thinking. It makes us face the inherent, irreducible nature of uncertainty and the limits to knowledge and prediction. Complex, evolutionary systems work on the basis of on-going, continuous internal processes of exploration, experimentation and innovation at their underlying levels. This is acted upon by the level above, leading to a selection process on the lower levels and a probing of the stability of the level above. This could either be an organizational level above, or the potential market place. Models aimed at predicting system behaviour therefore consist of assumptions of constraints on the micro-level – and because of inertia or conformity may be approximately true for some unspecified time. However, systems without strong mechanisms of repression and conformity will evolve, innovate and change, creating new emergent structures, capabilities and characteristics. Systems with no individual freedom at their lower levels will have predictable behaviour in the short term – but will not survive in the long term. Creative, innovative, evolving systems, on the other hand, will more probably survive over longer times, but will not have predictable characteristics or behaviour. These minimal mechanisms are all that are required to explain (though not predict) the co-evolutionary processes occurring in markets, organizations, and indeed in emergent, evolutionary communities of practice. Some examples will be presented briefly.

van Geert P.