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This chapter wants to understand under which circumstances and conditions non-traditional aids are effective in the strategic process. This study builds an agent-based computational simulation model – the S-uFUNK 2.1.0 – to explore the research question. The model features a group of managers that seeks to interpret environmental cues using both traditional and non-traditional tools. When interpretations converge, the group then settles on different focus areas to define a business strategy for their organization. The process is set in a way such that 11 parameters can be manipulated to explore the different conditions under which non-traditional aids are of use. Results suggest that non-traditional aids differ from traditional aids only in limited circumstances and that social dynamics and dispositions within the group are crucial. In general, the simulation helps us reflect on the way in which we consider traditional aids to strategy. In fact, if they are no different than non-traditional aids, their effectiveness is directly challenged.

Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

How do we make sense of urban life in the past? What do we do when we study urban history, and to what extent do our methods fully capture the complexities of historical city living? These are crucial questions for any scholar interested in the historical dimensions of urban experience. Notwithstanding the interest of most urban historians in the relationship between the physical form of urban space and its experience by inhabitants and visitors, very few scholars have written histories that systematically integrate these two areas of inquiry. In this chapter, we argue that such research requires a method and an accompanying tool that can analyze historical urban life in a more integrated, holistic way. We propose a way forward by introducing the Time Machine platform as a scalable data visualization and analysis tool for researching everyday urban experience across space and time. To illustrate the potential we focus on a case study: the area of the Bloemstraat in early modern Amsterdam. Unpacking a section of the Bloemstraat, house by house and room by room, we show how the Time Machine forms an instrument to connect spatial layouts to the arrangement of objects and to the practical and social use of the space by the inhabitants and visitors. We also sketch how this tool illuminates more dynamic spatial and temporal practices such as how people, goods, and activities are connected to locations in the wider city and beyond.

In this chapter, we reflect on cognitive aids and their role in strategy work. Strategy research and practice abound with frameworks, models, tools, and processes meant to describe and guide the strategy work of managers. These are all examples of cognitive aids. These aids guide and support managerial cognition, the way managers make sense of the world. What we collectively call the cognitive aids of strategy have a profound impact on the way managers learn about, conceptualize, share, and enact strategy work and strategies in their organizations. Despite the importance of their cognitive role, many cognitive aids in strategy are presented without reference to the underlying cognitive theory that explains why and how the aid might be useful. Tools are presented as useful for management thinking, but without any substantive reflection or exploration of the cognitive reasons. In this chapter, we provide a definition of cognitive aids in strategy and begin exploring the landscape of cognitive theories that can explain why something might be a cognitive aid. We then briefly outline the contributions to the edited volume “Cognitive Aids in Strategy,” and end with an invitation to expand your exploration beyond.