Business process modeling and system dynamics are different approaches that are used in the design and management of organizations. Both approaches are concerned with the processes in, and around, organizations with the aim to identify, design and understand their behavior as well as potential improvements. At the same time, these approaches differ considerably in their methodological focus. While business process modeling specifically takes the (control flow of) business processes as its primary focus, system dynamics takes the analysis of complex and multi-faceted systems as its core focus. More explicitly combining both approaches has the potential to better model and analyze (by way of simulation) complex business processes, while specifically also including more relevant facets from the environment of these business processes. Furthermore, the inherent ability for simulation of system dynamics models, can be used to simulate the behavior of processes over time, while also putting business processes in a broader multi-faceted context. In this paper, we report on initial results on making such a more explicit combination of business process modeling and system dynamics. In doing so, we also provide a step-by-step guide on how to use BPMN based models and system dynamics models together to model and analyze complex business processes, while illustrating this in terms of a case study on the maintenance of building facades.
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Business process modeling and system dynamics are different approaches that are used in the design and management of organizations. Both approaches are concerned with the processes in, and around, organizations with the aim to identify, design and understand their behavior as well as potential improvements. At the same time, these approaches differ considerably in their methodological focus. While business process modeling specifically takes the (control flow of) business processes as its primary focus, system dynamics takes the analysis of complex and multi-faceted systems as its core focus. More explicitly combining both approaches has the potential to better model and analyze (by way of simulation) complex business processes, while specifically also including more relevant facets from the environment of these business processes. Furthermore, the inherent ability for simulation of system dynamics models, can be used to simulate the behavior of processes over time, while also putting business processes in a broader multi-faceted context. In this paper, we report on initial results on making such a more explicit combination of business process modeling and system dynamics. In doing so, we also provide a step-by-step guide on how to use BPMN based models and system dynamics models together to model and analyze complex business processes, while illustrating this in terms of a case study on the maintenance of building facades.
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In recent years, there have been significant changes in weather patterns, mainly caused by sharp increases in temperature, increases in carbon dioxide, and fluctuations in precipitation levels, negatively impacting agricultural production. Agricultural systems are characterized by being vulnerable to the variation of biophysical and socioeconomic factors involved in the development of agricultural activities. Agent-based models (ABMs) enable the study, analysis, and management of ecosystems through their ability to represent networks and their spatial nature. In this research, an ABM is developed to evaluate the behavior and determine the vulnerability in the sugarcane agricultural system; allowing the capitalization of knowledge through characteristics such as social ability and autonomy of the modeled agents through fuzzy logic and system dynamics. The methodol-ogy used includes information networks for a dynamic assessment of agricultural risk modeled by time series, system dynamics, uncertain parameters, and experience; which are developed in three stages: vulnerability indicators, crop vulnerability, and total system vulnerability. The development of ABM, a greater impact on the environmental contingency is noted due to the increase in greenhouse gas emissions and the exponential increase in extreme meteorological phenomena threatening the cultivation of sugarcane, making the agricultural sector more vulnerable and reducing the yield of the harvest.
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Wikipedia is often considered as an example of ‘collaborative knowledge’. Researchers have contested the value of Wikipedia content on various accounts. Some have disputed the ability of anonymous amateurs to produce quality information, while others have contested Wikipedia’s claim to accuracy and neutrality. Even if these concerns about Wikipedia as an encyclopaedic genre are relevant, they misguidedly focus on human agents only. Wikipedia’s advance is not only enabled by its human resources, but is equally defined by the technological tools and managerial dynamics that structure and maintain its content. This article analyzes the sociotechnical system – the intricate collaboration between human users and automated content agents – that defines Wikipedia as a knowledge instrument.
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Symbiotic Urban Agriculture Networks (SUANs) are a specific class of symbiotic networks that intend to close material and energy loops from cities and urban agriculture. Private and public stakeholders in SUANs face difficulties in the implementation of technological and organisational design interventions due to the complex nature of the agricultural and urban environment. Current research on the dynamics of symbiotic networks, especially Industrial Symbiosis (IS), is based on historical data from practice, and provides only partly for an understanding of symbiotic networks as a sociotechnical complex adaptive system. By adding theory and methodology from Design Science, participatory methods, and by using agent-based modelling as a tool, prescriptive knowledge is developed in the form of grounded and tested design rules for SUANs. In this paper, we propose a conceptual Design Science method with the aim to develop an empirically validated participatory agent-based modelling strategy that guides sociotechnical design interventions in SUANs. In addition, we present a research agenda for further strategy, design intervention, and model development through case studies regarding SUANs. The research agenda complements the existing analytical work by adding a necessary Design Science approach, which contributes to bridging the gap between IS dynamics theory and practical complex design issues.
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Abstract The emergence of new technologies such as mp3 and music streaming, and the accompanying digital transformation of the music industry, have led to the shift and change of the entire music industry’s value chain. While music is increasingly being consumed through digital channels, the number of empirical studies, particularly in the field of music copyright in the digital music industry, is limited. Every year, rightsholders of musical works, valued 2.5 billion dollars, remain unknown. The objectives of this study are twofold: First to understand and describe the structure and process of the Dutch music copyright system including the most relevant actors within the system and their relations. Second to apply evolutionary economics approach and Values Sensitive Design method within the context of music copyright through positive-empirical perspective. For studies of technological change in existing markets, the evolutionary economics literature provides a coherent and evidence-based foundation. The actors are generally perceived as being different, for example with regard to their access to information, their ability to handle information, their capital and knowledge base (asymmetric information). Also their norms, values and roles can differ. Based on an analysis of documents and held expert interviews, we find that the collection and distribution of the music copyright money is still based on obsolete laws, neoclassical paradigm and legacy IT-system. Finally, we conclude that the rightsholders are heterogenous and have asymmetrical information and negotiating power. The outcomes of this study contribute to create a better understanding of impact of digitization of music copyright industry and empower the stakeholders to proceed from a more informed perspective on redesigning and applying the future music copyright system and pre-digital norms and values amongst actors.
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The professional growth of midwives, essential for optimizing midwifery leadership globally, can be enhanced through twinning collaborations. How twinning promotes growth is unclear. This case study explores how professional growth is affected by cultural differences between twins. We used a longitudinal qualitative design including data from open-ended questionnaires and focus groups. These data were analyzed using a content analysis. Our findings show that cultural differences were capable of both hindering and facilitating professional growth. Within the complex dynamics of twinning, professional growth was facilitated by twins’ preparedness to bridge cultural differences. Common goals positively influenced this process. Friction was more likely, and professional growth was hindered, when midwives were unprepared to bridge cultural differences. To optimize professional growth through twinning, we recommend a clear focus on common goals and consideration of the interaction between the length of a project and the extent of the cultural differences between twins.
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In the aftermath of the systemic financial crises of 2007-9, several scholars argued that the problem of systemic financial crises is not well understood. At the same time, the introduction of digital technologies led to new threats and opportunities for the design of the monetary and financial system. For example, thousands of private cryptocurrencies have been implemented and hundreds of research papers on the (possible) introduction of public digital currencies have been published. It is often not explained why these new forms of digital money are needed and which (systemic) problems they (can) solve. In addition, the literature does not provide requirements nor guidelines to shape the development of the monetary and financial system in the digital age. This thesis applies design science to the monetary and financial system as a whole. The application of this novel methodology offers new possibilities to examine this complex system. The contribution of this thesis is threefold. First, different theories on money, banking and systemic financial crises have been researched through an extensive literature review and balance sheets. Second, those theories have been used to develop design requirements and guidelines. Finally, the consensus and pivotal dissensions about the systemic problem(s) of the current monetary and financial system, requirements and guidelines among experts have been identified through semistructured interviews. This research process results in widely supported requirements that demarcate the design space and widely supported guidelines that aim to give direction within the design space, that is, to the future development of the monetary and financial system.
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This research investigates growth inhibitors for smart services driven by condition-based maintenance (CBM). Despite the fast rise of Industry 4.0 technologies, such as smart sensoring, internet of things, and machine learning (ML), smart services have failed to keep pace. Combined, these technologies enable CBM to achieve the lean goal of high reliability and low waste for industrial equipment. Equipment located at customers throughout the world can be monitored and maintained by manufacturers and service providers, but so far industry uptake has been slow. The contributions of this study are twofold. First, it uncovers industry settings that impede the use of equipment failure data needed to train ML algorithms to predict failures and use these predictions to trigger maintenance. These empirical settings, drawn from four global machine equipment manufacturers, include either under- or over-maintenance (i.e., either too much or too little periodic maintenance). Second, formal analysis of a system dynamics model based on these empirical settings reveals a sweet spot of industry settings in which such inhibitors are absent. Companies that fall outside this sweet spot need to follow specific transition paths to reach it. This research discusses these paths, from both a research and practice perspective.
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