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Fundamental changes in the organisational processes
Published in Carolina Machado, J. Paulo Davim, Industry 4.0, 2020
Vasja Roblek, Ivan Erenda, Maja Mesko
In the context of a research of a particular system, we explore a living system that has its own “will”, regardless of the level of development of organisms. A paradox is that living systems are organised organically and, on the other hand, information is open. Consequently, living systems are more challenging to manage. Their interactions with their environment are complicated, and it is impossible to predict more than a few steps in advance. Here the control capability, developed by second-order cybernetics, arises. The cybernetics is focused on the understanding of biological and social complexity as well as its control. For this reason, it is understandable that the cybernetics is focused on creating new forms (morphogenesis) and on a positive feedback loop. Despite the fact that first-order cybernetics involved influential biologists such as Bertalanffy (1975), one of the founders of the general system theory, the incentive for the development of cybernetics of the second-order came mainly from biology and neurophysiology, and later from epistemology in the framework of whose second-order cybernetics focuses on the very nature of knowledge, languages, cognition and communication.
Enterprise Dynamics Methods and Models
Published in Kenneth C. Hoffman, Christopher G. Glazner, William J. Bunting, Leonard A. Wojcik, Anne Cady, Enterprise Dynamics Sourcebook, 2013
Kenneth C. Hoffman, William J. Bunting, Christopher G. Glazner, Leonard A. Wojcik
Specific modeling approaches and state- space descriptors are highly dependent on the position of the enterprise on this landscape. This sourcebook emphasizes the upper- right social complexity domain involving ad hoc operations (rugged landscape) and situationally dependent decisions, although other regimes of the matrix are addressed as well by tailoring and perhaps simplifying the methods. Much of the modeling and simulation literature deals with the lower- left quadrant, process engineering of highly repetitive and rule- based enterprise operations, and is not readily adaptable to the social complexity domain characterized by emergent behavior and complex adaptive systems theory.
Applying Design Thinking Principles on Major Infrastructure Projects
Published in Edward Ochieng, Tarila Zuofa, Sulafa Badi, Routledge Handbook of Planning and Management of Global Strategic Infrastructure Projects, 2020
Design thinking and systems thinking show how the pulls of technical complexity, social complexity and wicked problems can be addressed. As an academic discipline and a management tool, design thinking has increased in awareness in the last 40 to 50 years. In the 1950s, creative thinking theories were brought to Stanford Engineering by John E. Arnold. The previous linear nature of analytical approaches were not sufficient to solve wicked problems Rittel and Weber (1973): they had to be explored through an experimental approach that explored multiple solutions. Liedtka, et al (2013) concurs that design thinking is a problem-solving process as well as an innovation process. Buchanan (2001) noted that the question of whose values matter and who ought to participate in the design process has changed over time evolving from 1950s' beliefs about the “ability of experts to engineer socially acceptable results” toward a view of audiences as “active participants in reaching conclusions.” Recently design thinking has been held at the forefront of organisational thinking by international design and innovation firms such as IDEO. Its founder, David Kelley, stated, “The main tenet of design thinking is empathy for the people you're trying to design for (see Figure 15.3). Leadership is exactly the same thing – building empathy for the people that you're entrusted to help.” Also influential, the Institute of Design at Stanford University, firmly connected the value of design thinking to successful innovative organisations. Design thinking could be the shift that is needed from the linear, top-down infrastructure projects and the way to solve the problems which arise from the new design principles of major infrastructures. This shift will be the change necessary to move from projects which proceed with very little input from the people to projects which engage with communities from the outset on what is really required: “How are they actually living and working and moving around and how do they see that changing in the future and engaging as a source of ideas around which you then build the appropriate infrastructure” Fisher (2016).
Complexity analysis of manufacturing service ecosystem: a mapping-based computational experiment approach
Published in International Journal of Production Research, 2019
Xue Xiao, Shufang Wang, Lejun Zhang, Cheng-zhi Qin
MSE is a complex social system, which is composed of all kinds of dynamic entities. In order to study its macro evolution, high-level model abstraction is necessary, which can facilitate us to focus on the core research question. However, most of existing applications focus on specific problems, but ignore the refining of computational experiment method. There is neither a general application specification of computational experiment, nor a computational model available for analysis of MSE with internal complexities (i.e. individual complexity, organisation complexity and social complexity, as mentioned in the first section).
Managing strategic resources in petroleum industry projects
Published in Production Planning & Control, 2022
Moosa Ali Mas’oud Al-Hanshi, Udechukwu Ojiako, Terry Williams
The first is ‘Unique historical conditions’. An understanding of the idiosyncratic nature of the attributes of an organization is important to have an imperfectly imitable resource, and the ability of the firm to exploit and acquire resources will depend on their place in time. Academic literature suggests that such performance does not only depend on the economic industry structure at a particular point in time, but also on the path from past history, and how the organization reached this point in time. Therefore, when an organization obtains valuable and rare resources because of its unique path in history, it will be better able to exploit those resources, which cannot be duplicated by other competitors. History thus affects all types of resources and makes them more imperfectly imitable. The second element leading to imperfectly imitable resources is ‘Causal ambiguity’. This implies that the relationship between the resources controlled by an organization and the source of competitive advantage is not always understood either by the controlling organization, or by other competing organizations (Kull, Mena, and Korschun 2016). If that relationship is fully understood by the controlling organization, then it is just a matter of time before others will understand it. The third element leading to imperfectly imitable resources is ‘Social complexity’. A resource can be imperfectly imitable if it is a socially complex phenomenon, and if the organization cannot manage or influence it in a systematic way (Barney 1991). This makes it difficult for other firms to imitate. Examples of socially complex resources are the interpersonal relationships between managers. Bingham and Eisenhardt (2008) opine that inimitability represents the most significant resource attribute for competitive advantage.
Institutions, Nations, Enterprises and Distributed Organisation (the Westphalian Dilemma)
Published in Cybernetics and Systems, 2022
Centralization in society has dominated the design of much complexity management in organizational systems. The aim has been attenuating social complexity through hierarchical structures (see Figure 3). But also we find decentralization as a strategy to implement policies. This is a strategy to proliferate social complexity through reducing undesirable controls and assuming that self-organization will, in one form or another, do the job.