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The purpose of this paper is to deepen the understanding of adaptive governance, which is advocated for as a manner to deal with dramatic changes in society and/or environment. To re-think the possible contributions of organizations and organization theory, to adaptive governance.

Based on social systems theory this study makes a distinction between “governance organizations” and “governance communities.” Organizations are conceptualized as the decision machines which organize and (co-)steer governance. Communities are seen as the social environments against which the governance system orients its operations. This study considers the adaptive mechanisms of organizations and reflect on the roles of organizations to enhance adaptive governance in communities and societies.

Diverse types of organizations can link or couple in different ways to communities in their social environment. Such links can enhance the coordinative capacity of the governance system and can also spur innovation to enable adaptation. Yet, linking with communities can also slow down responses to change and complexify the processes of deliberation in governance. Not all adaptive mechanisms available to organizations can be used in communicating with communities or can be institutionalized, but the continuous innovation in the field of organizations can inspire continuous testing of small-scale adaptive mechanisms at higher levels. Society can thus enhance its adaptive capacity by managing the role of organizations.

The harnessing of insights in organization theory and systems theory for improving understanding of adaptive governance. The finding that both experiment and coordination at societal level are needed, toward adaptive governance, and that organizations can contribute to both.

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

There are four categories of ABM in economics.

This paper suggests a methodological categorization of ABM works in economics.

Tourism areas are challenged to become adaptive areas in the context of a dynamic networked society and globalizing economy. The purpose of this paper is to contribute to an enhanced understanding and conceptualization of adaptive tourism areas by drawing attention to “fitness landscapes,” a metaphor that is used in complexity theories to visualize development trajectories of adaptive systems.

Fitness landscapes, and its underlying theories, are useful to conceptualize tourism area development as a stepwise movement through a dynamic landscape with peaks and valleys. Doing so allows us to highlight why adaptation is a crucial property for tourism areas that are embedded in dynamic contexts and offers a frame of thought for how tourism areas can be managed.

The article raises awareness about and draws attention to a set of factors and conditions that support tourism planners and managers in enhancing the capacity of tourism areas to adaptively respond to changing circumstances.

Introducing fitness landscapes contribute to the discussion on adaptive capacity building – a topic that contributes to managing uncertain futures and is likely to gain importance in the dynamic society. Moreover, it helps as well as stimulates tourism scholars to further develop this topic. Finally, it helps tourism planners to build adaptive capacity in practice.

Time headway (THW) is an essential parameter in traffic safety and is used as a typical control variable by many vehicle control algorithms, especially in safety-critical ADAS and automated driving systems. However, due to the randomness of human drivers, THW cannot be accurately represented, affecting scholars’ more profound research.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified.

The results show that the proposed model has a 62.7% performance improvement over the distribution model with fixed parameters. Moreover, the parameter function of the distribution model can be regarded as a quantitative analysis of the degree of influence of the traffic flow state on THW.

Business process re-engineering (BPR) initiatives are complex endeavours which require many factors to ensure success. However, most studies focus on the organisational processes and improvement within the organisation itself and less on the project team and management dynamics. The study aimed to identify factors that enabled the completion of a BPR, in a technical firm, based on reflections on the project management style.

The study entailed a descriptive and interpretive case study with reflections from project team members. Data were analysed using descriptive statistics and content analysis.

Findings revealed that critical success factors for BPR in a technical firm include project leadership and sponsorship, organisational culture and attributes, team dynamics and the nature (activities), and duration of the process.

The findings will benefit project managers in improving their competence and project success through reflective practice. The identified factors could be used in future projects of a similar nature and size to improve how organisations execute BPR projects.

The study used reflections to identify success factors for BPR in a technical firm.