▪ Abstract We explore the social dimension that enables adaptive ecosystem-based management. The review concentrates on experiences of adaptive governance of social-ecological systems during periods of abrupt change (crisis) and investigates social sources of renewal and reorganization. Such governance connects individuals, organizations, agencies, and institutions at multiple organizational levels. Key persons provide leadership, trust, vision, meaning, and they help transform management organizations toward a learning environment. Adaptive governance systems often self-organize as social networks with teams and actor groups that draw on various knowledge systems and experiences for the development of a common understanding and policies. The emergence of “bridging organizations” seem to lower the costs of collaboration and conflict resolution, and enabling legislation and governmental policies can support self-organization while framing creativity for adaptive comanagement efforts. A resilient social-eco...

/pdf/adaptive-governance-of-social-ecological-systems-4doqvfxaqg.pdf

Adaptive governance of social-ecological systems

https://dialnet.unirioja.es/descarga/articulo/4511387.pdf

The origins of order. Self-organization and selection in evolution

There has been considerable academic interest in recent years in supply chain resilience (SCRES). This paper presents a timely review of the available literature on SCRES based on a three-stage systematic search that identified 91 articles/sources. We provide a comprehensive definition of SCRES before strategies proposed for improving resilience are identified and the contributions to the literature are critiqued, e.g. in terms of research method and use of theory. We take stock of the field and identify the most important future research directions. A wide range of strategies for improving resilience are identified, but most attention has been on increasing flexibility, creating redundancy, forming collaborative supply chain relationships and improving supply chain agility. We also find that only limited research has been conducted into choosing and implementing an appropriate set of strategies for improving SCRES. Much of the literature is conceptual, theoretical and normative; the few available empirical studies are mainly cross-sectional and confined to a large firm, developed country context; and, there has been limited use of theory frames to improve understanding. We propose Complex Adaptive Systems (CAS) theory as an appropriate lens for studying SCRES. We demonstrate that SCRES mirrors many characteristics of a CAS – including adaptation and coevolution, non-linearity, self-organisation and emergence – with implications for the direction of both future research and practice.

/pdf/supply-chain-resilience-definition-review-and-theoretical-532twafa2j.pdf

Supply chain resilience: definition, review and theoretical foundations for further study

Traditionally, frequency dependent evolutionary dynamics is described by deterministic replicator dynamics assuming implicitly infinite population sizes. Only recently have stochastic processes been introduced to study evolutionary dynamics in finite populations. However, the relationship between deterministic and stochastic approaches remained unclear. Here we solve this problem by explicitly considering large populations. In particular, we identify different microscopic stochastic processes that lead to the standard or the adjusted replicator dynamics. Moreover, differences on the individual level can lead to qualitatively different dynamics in asymmetric conflicts and, depending on the population size, can even invert the direction of the evolutionary process.

/pdf/coevolutionary-dynamics-from-finite-to-infinite-populations-45s7dzas9c.pdf

Coevolutionary dynamics: from finite to infinite populations.

Grounded Theory (GT) has proved an extremely useful research approach in several fields including medical sociology, nursing, education and management theory. However, GT is a complex method based on an inductive paradigm that is fundamentally different from the traditional hypothetico-deductive research model. As there are at least three variants of GT, some ostensibly GT research suffers from method slurring, where researchers adopt an arbitrary subset of GT practices that are not recognizable as GT. In this paper, we describe the variants of GT and identify the core set of GT practices. We then analyze the use of grounded theory in software engineering. We carefully and systematically selected 98 articles that mention GT, of which 52 explicitly claim to use GT, with the other 46 using GT techniques only. Only 16 articles provide detailed accounts of their research procedures. We offer guidelines to improve the quality of both conducting and reporting GT studies. The latter is an important extension since current GT guidelines in software engineering do not cover the reporting process, despite good reporting being necessary for evaluating a study and informing subsequent research.

Grounded theory in software engineering research: a critical review and guidelines

The field of Complex Adaptive Systems (CAS) is approximately 20 years old, having been established by physicists, economists, and others studying complexity at the Santa Fe Institute in New Mexico, USA. The field has spawned much work, such as Holland's contributions of genetic algorithms, classifier systems, and his ecosystem simulator, which assisted in provoking the fields of evolutionary computation and artificial life. The framework of inducted principles derived from many natural and artificial examples of complex systems has assisted in the investigation in such diverse fields of study as psychology, anthropology, genetic evolution, ecology, and business management theory, although a unified theory of such complex systems still appears to be a long way off. This work reviews the principles of complex adaptive systems as a framework, providing a number of interpretations from eminent researches in the field. Many example works are cited, and the theory is used to phrase some ambiguus work in the field of artificial immune systems and artificial life. The methodology of using simulations of CAS as the starting point for models in the field of biological inspired computation is postulated as an important contribution of CAS to that field.

https://researchbank.swinburne.edu.au/file/70b56318-1381-4eb7-9166-fd8ecc9c7968/1/PDF (6 pages).pdf

Complex adaptive systems

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Complex adaptive systems