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This paper aims to conceptually unite an ontology of cybernetics, bridging living and technical systems, to facilitate future epistemological and theoretical advancements applicable to highly technical societies by crafting a set of definitions that elucidate the nature of the world in which these systems operate.

The research uses a thematic synthesis of two systems/cybernetic traditions: complex adaptive systems and mechanology. The primary sources for this research were the main theses and correlated papers published in the Simondon case for mechanology, and the seminal literature preselected by the Santa Fe Institute for complex adaptive systems.

The study proposes the following concepts: Individuation: the emergence of new properties in an individual composed of synergistically related parts; Technical evolution: the notion that technical objects evolve into living beings; circular causality: the notion that feedback and feedforward processes shape the organisation and structure of systems and their relationship with the environment; The milieu refers to the part of the environment that has a relationship of co-production, co-dependency, and co-evolution with systems. Metastability is a state that transcends stability and instability and motivates changes in the system. Transduction is the cumulative process of individuation in which systems change structure and organization to maintain operational coherence with their surroundings.

The concepts the paper identifies can serve as a starting point for an extended study on the ontology of cybernetics or as the basis for an evolutionary epistemology both in humans and machines.

Aiming to resolve cross-cultural paradoxes in combining artificial intelligence (AI) with human intelligence (HI) for international humanitarian logistics, this paper aims to adopt an unorthodox Yin–Yang dialectic approach to address how AI–HI interactions can be interpreted as a sophisticated cross-cultural knowledge creation (KC) system that enables more effective decision-making for providing humanitarian relief across borders.

This paper is conceptual and pragmatic in nature, whereas its structure design follows the requirements of a real impact study.

Based on experimental information and logical reasoning, the authors first identify three critical cross-cultural challenges in AI–HI collaboration: paradoxes of building a cross-cultural KC system, paradoxes of integrative AI and HI in moral judgement and paradoxes of processing moral-related information with emotions in AI–HI collaboration. Then applying the Yin–Yang dialectic to interpret Klir’s epistemological frame (1993), the authors propose an unconventional stratified system of cross-cultural KC for understanding integrative AI–HI decision-making for humanitarian logistics across cultures.

This paper aids not only in deeply understanding complex issues stemming from human emotions and cultural cognitions in the context of cross-border humanitarian logistics, but also equips culturally-diverse stakeholders to effectively navigate these challenges and their potential ramifications. It enhances the decision-making process and optimizes the synergy between AI and HI for cross-cultural humanitarian logistics.

The originality lies in the use of a cognitive methodology of the Yin–Yang dialectic to metaphorize the dynamic genesis of integrative AI-HI KC for international humanitarian logistics. Based on system science and knowledge management, this paper applies game theory, multi-objective optimization and Markov decision process to operationalize the conceptual framework in the context of cross-cultural humanitarian logistics.

In this study, we investigate how capability in managing intellectual property may be treated as a type of “dynamic capability,” and we seek to understand how, when it is linked to the new technology development capability of a complex technological organization, these two types of dynamic capabilities may coevolve.

We conducted a longitudinal empirical case study of Airbus, incorporating an abductive research methodology that required investigating theory and empirical data concurrently and iteratively. The data, ranging over a period of two decades from 2000 to 2021, was collected from four different sources, including interviews, internal company documents, publicly available information and patent data.

Our main findings are that the capabilities and roles of the Intellectual Property function in Airbus and their interaction with the company's Technology function have indeed influenced the overall innovation strategy of the organization, and that three coevolutionary phases may be identified in the interactive development of the two functions.

Our investigation into how new technology development and intellectual property (IP) management capabilities coevolve within complex technological organizations, exemplified by Airbus, provides significant theoretical and practical implications. Theoretically, it enhances understanding of capability co-development dynamics in complex organizations, particularly in strategic IP management. Practically, it suggests aligning IP strategy with overall corporate objectives and optimizing organizational structures to promote collaboration and efficiency across IP and technology teams. This alignment may foster innovation, maximize the value of intellectual assets and strengthen collaborations, positioning organizations for long-term success in competitive landscapes.

This study makes a fresh contribution to the innovation studies literature by showing how if intellectual property management is treated as a core function of a complex technological organization – rather than simply as a vehicle for protecting new inventions and products after the fact or simply as a constituent part of the organization's legal function – it may contribute proactively to the organization's technological innovation performance. We also address the current gap in the academic literature for a clear understanding of the processes by which different function-specific dynamic capabilities may coevolve in a complex organization operating as part of a dynamic and complex adaptive system.

The conclusions summarize the main empirical evidence that emerged in the book and put forward final reflections and some recommendations for scholars and policymakers. First, the reader is reminded that the book focuses on how a desirable and ambitious agenda that contemplates a progress-oriented policy system is feasible when confronted with the challenges of its implementation and the related problem of coordination between the goals it postulates. The purpose of the concluding chapter is to extrapolate the findings from the individual analyses and synthesize them into a single interpretative proposal centered on two analytical pillars. The first is the analysis and management of the complexity generated by wickedness, through the reconstruction of types of complexity and consequences that the policymaker must acquire in terms of problem setting. The second is the analysis of the skills needed to manage said complexity, distinguishing between linear and nonlinear skills. These are the skills that the policymaker must acquire in terms of problem-solving. Both problem setting and problem solving are summarized in some final recommendations on what to do to improve the feasibility and effectiveness of sustainable development policies: the pragmatic culture of government and some supporting institutional tools, the importance of training as a lever of change, and the building of knowledge infrastructures in terms of evidence-based policymaking.

Electrification is a promising solution for decarbonising the road freight transport system, but it is challenging to understand its impact on the system. The purpose of this research is to provide a system-level understanding of how electrification impacts the road freight transport system. The goal is to develop a model that illustrates the system and its dynamics, emphasising the importance of understanding these dynamics in order to comprehend the effects of electrification.

The main methodological contribution of the study is the combination of the multi-layer model with system dynamics methodology. A mixed methods approach is used, including group model building, impact analysis, and literature analysis.

The study presents a conceptual multi-layer dynamic model, illustrating the complex causal relationships between variables in the different layers and how electrification impacts the system. It distinguishes between direct and induced impacts, along with potential policy interventions. Moreover, two causal loop diagrams (CLDs) provide practical insights: one explores factors influencing electric truck attractiveness, and the other illustrates the trade-off between battery size and fast charging infrastructure for electric trucks.

The study provides stakeholders, particularly policymakers, with a system-level understanding of the different impacts of electrification and their ripple effects. This understanding is crucial for making strategic decisions and steering the transition towards a sustainable road freight transport system.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

Service organizations operate in an increasingly complex and uncertain context that makes decision-making challenging. Despite well-recognized changes in the operational context of government as service organization, service literature has given surprisingly limited attention to what these changes imply for organizational decision-making. This study aims to face with the lack of fit of decision-making theorizing with the reality, within which most service practitioners operate, in order to foster the relevance of decision-making in service research and properly approach the false assumptions and misguided instructions for action.

To rectify the situation, the purpose of this paper is to advance a more holistic understanding of decision-making in government as service organization. The authors do so by reviewing the sparse, though insightful, prior literature on decision-making in service research and identifying four foundational assumptions of decision-making in the service context, that radically differ from the traditional assumptions of decision-making within the wider management literature.

The authors contribute to service research by further advancing the emerging dynamic understanding of decision-making by developing eight systems thinking-informed research propositions and a connected research agenda. In doing so, the paper offers the essential ground work that can revitalize the field of service management and equip it for facing the challenges that government as service organization is encountering in the 21st century.

The formulated eight research propositions demonstrate that decision-making in a government as service organization occurs within complex adaptive systems composed of multiple subsystems and is characterized by a high degree of unpredictability. It is a process influenced by multiple actors part of the system and subsystems, through multiple feedback loops, where the implications of prior decisions inform the future decisions.

This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.

The purpose of this study is to investigate the integrated application of business process modeling and notation (BPMN) and value stream mapping (VSM) to improve knowledge work performance and productivity in police services. In order to explore the application of the hybrid BPMN-VSM approach in police services, this study uses the department of digital crime investigation (DCI) in one Norwegian police district as a case study.

Service process identification was the next step after selecting an appropriate organizational unit for the case study. BPMN-VSM-based current state mapping, including time and waste analyses, was used to determine cycle and lead time and identify value-adding and nonvalue-adding activities. Subsequently, improvement opportunities were identified, and the current state process was re-designed and constructed through future state mapping.

The study results indicate a 44.4% and 83.0% reduction in process cycle and lead time, respectively. This promising result suggests that the hybrid BPMN-VSM approach can support the visualization of bottlenecks and possible causes of increased lead times, followed by the systematic identification and proposals of avenues for future improvement and innovation to remedy the discovered inefficiencies in a complex knowledge-work environment.

This study focused on one department in a Norwegian police district. However, the experience gained can support researchers and practitioners in understanding lean implementation through an integrated BPMN and VSM model, offering a unique insight into the ability to investigate complex systems.

Complex knowledge work processes generally characterize police services due to a high number of activities, resources and stakeholder involvement. Implementing lean thinking in this context is significantly challenging, and the literature on this topic is limited. This study addresses the applicability of the hybrid BPMN-VSM approach in police services with an original public sector case study in Norway.

Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.