This research concerning the experience and future of zoos was carried out from 2011-2012 and takes regional ideas concerning Zoo Emmen as well as global visions into account. The research focuses partly on Zoo Emmen, its present attractions and visitors while also comparing and contrasting visions on the future in relationship to other international zoos in the world. In this way, remarkable experiences and ideas will be identified and in the light of them, it can serve as inspiration for stakeholders of zoos at large. The main research subject is a look at the future zoos in view of: The Zoo Experience – an international experience benchmark; The Zoo of the Future – a Scenario Planning approach towards the future; The virtual zoo - zoo’s in the internet domain.
By use of a literature review and an environmental scan four plausible future scenarios will be created, based on the research question: How could the future of backpack tourism look like in 2030, and how could tourism businesses anticipate on the changing demand. The scenarios, which allow one to ‘think out of the box’, will eventually be translated into recommendations towards the tourism sector and therefore can create a future proof company strategy.
Digital technologies permeate and transform organisational practices. As a society, we need means to explore the uncharted terrain that lies ahead and the desirability and consequences of possible courses of action to move forward. We investigate a design approach, called ‘future probing’, to envision and critically analyse possible futures around digital technologies. We first reconstruct our journey and describe related insights on the process, content and context level. Reflecting on the journey, we then extract a key insight revolving around the challenge for participants to link back from exploring the future to their present practice. In a first attempt at theorizing these difficulties, we see future probing as a practice that opens up adaptive space (Uhl-Bien & Arena, 2017) in which people from different backgrounds engage in dialogue about possible futures of digital technologies. We found that adaptive processes, like semi structuring, temporary decentralisation, and collaboration (Uhl-Bien & Arena, 2018) were supported by the future probing practices and seemed to create space for employees to engage in exploration. There was still a lack of compelling acts of brokering and network cohesion (Uhl-Bien & Arena, 2018). This may indicate why linking back to daily practice is challenging. We assume that organising for adaptability requires a deliberate act of connecting far future explorations with present action, and propose that besides explorative skills, ‘adaptive anticipating’ action is needed to make the connection and that linking back through near future experiments might be a way to achieve this.
Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.
Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as opposed to how it was envisioned. This model can subsequently be analyzed and stress-tested to explore possible causes of production prob-lems and to analyze what-if scenarios, without disrupting the production process itself. It has been shown that such models can successfully be used to diagnose possible causes of production problems, including scrap products and machine defects. Ideally, they can even be used to model and analyze production processes that have not been implemented yet, based on data from existing production pro-cesses and techniques from artificial intelligence that can predict how the new process is likely to be-have in practice in terms of data that its machines generate. This is especially important in mass cus-tomization processes, where the process to create each product may be unique, and can only feasibly be tested using model- and data-driven techniques like the one proposed in this project. Against this background, the goal of this project is to develop a method and toolkit for mining, mod-elling and analyzing production processes, using the time series data that is generated by machines, to: (i) analyze the performance of an existing production process; (ii) diagnose causes of production prob-lems; and (iii) certify that a new – not yet implemented – production process leads to high-quality products. The method is developed by researching and combining techniques from the area of Artificial Intelli-gence with techniques from Operations Research. In particular, it uses: process mining to relate time series data to production processes; queueing networks to determine likely paths through the produc-tion processes and detect anomalies that may be the cause of production problems; and generative adversarial networks to generate likely future production scenarios and sample scenarios of production problems for diagnostic purposes. The techniques will be evaluated and adapted in implementations at the partners from industry, using a design science approach. In particular, implementations of the method are made for: explaining production problems; explaining machine defects; and certifying the correct operation of new production processes.
In the Glasgow declaration (2021), the tourism sector promised to reduce its CO2 emissions by 50% and reduce them to zero by 2050. The urgency is felt in the sector, and small steps are made at company level, but there is a lack of insight and overview of effective measures at global level.This study focuses on the development of a necessary mix of actions and interventions that the tourism sector can undertake to achieve the goal of a 50% reduction in greenhouse gases by 2030 towards zero emissions by 2050. The study contributes to a better understanding of the paths that the tourism sector can take to achieve this and their implications for the sector. The aim of the report is to spark discussion, ideas and, above all, action.The study provides a tool that positively engages the sector in the near and more distant future, inspires discussion, generates ideas, and drives action. In addition, there will be a guide that shows the big picture and where the responsibilities lie for the reduction targets. Finally, the researchers come up with recommendations for policymakers, companies, and lobbyists at an international and European level.In part 1 of the study, desk research is used to lay the foundation for the study. Here, the contribution of tourism to global greenhouse gas emissions is mapped out, as well as the image and reputation of the sector on climate change. In addition, this section describes which initiatives in terms of, among other things, coalitions and declarations have already been taken on a global scale to form a united front against climate change.In part 2, 40 policies and measures to reduce greenhouse gas emissions in the sector are evaluated in a simulation. For this simulation, the GTTMdyn simulation model, developed by Paul Peeters from BUAS, is used which works on a global scale and shows the effect of measures on emissions, tourism, transport, economy, and behaviour. In this simulation, the researchers can 'test' measures and learn from mistakes. In the end one or more scenarios will; be developed that reach the goals of 50% reduction in 2030 and zero emissions in 2050. In part 3, the various actions that should lead to the reduction targets are tested against the impacts on the consequences for the global tourism economy, its role in providing leisure and business opportunities and the consequences for certain destinations and groups of industry stakeholders. This part will be concluded with two workshops with industry experts to reflect on the results of the simulation.Part 4 reports the results of the study including an outline of the consequences of possibly not achieving the goal. With this, the researchers want to send a warning signal to stakeholders who may be resistant to participating in the transition.
