When Google sold 3D geo-modeling software Sketch-up, a dedicated community of Google Earth developers were left behind. Is this a case of digital labor and exploitation or just an agreement based on mutual consent that ended, like relationships so often do?
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This paper presents work aimed at improved organization and performance of production in housing renovation projects. The purpose is to explore and demonstrate the potential of lean work organization and industrialized product technology to improve workflow and productive time. The research included selected case studies that have been found to implement lean work organization and industrialized product technology in an experimental setting. Adjustments to the work organization and construction technology have been implemented on site. The effects of the adjustments have been measured and were reviewed with operatives and managers. The data have been collected and analyzed, in comparison to traditional settings. Two projects were studied. The first case implied am application of lean work organization in which labor was reorganized redistributing and balancing operations among operatives of different trades. In the second case industrialized solution for prefabricated installation of prefabricated roofs. In both cases the labor productivity increased substantially compared to traditional situations. Although the limited number of cases, both situations appeared to be representative for other housing projects. This has led to conclusions extrapolated from both cases applicable to other projects, and contribution to the knowledge to improve production in construction. Vrijhoef, R. (2016). “Effects of Lean Work Organization and Industrialization on Workflow and Productive Time in Housing Renovation Projects.” In: Proc. 24 th Ann. Conf. of the Int’l. Group for Lean Construction, Boston, MA, USA, sect.2 pp. 63–72. Available at: .
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Cooperation is more likely upheld when individuals can choose their interaction partner. However, when individuals differ in their endowment or ability to cooperate, free partner choice can lead to segregation and increase inequality. To understand how decision-makers can decrease such inequality, we conducted an incentivized and preregistered experiment in which participants (n=500) differed in their endowment and cooperation productivity. First, we investigated how these individual differences impacted cooperation and inequality under free partner choice in a public goods game. Next, we calculated if and how decision-makers should restrict partner choice if their goal is to decrease inequality. Finally, we studied whether decision-makers actually did decrease inequality when asked to allocate endowment and productivity factors between individuals, and combine individuals into pairs of interaction partners for a two-player public goods game. Our results show that without interventions, free partner choice, indeed, leads to segregation and increases inequality. To mitigate such inequality, decision-makers should curb free partner choice and force individuals who were assigned different endowments and productivities to form pairs with each other. However, this comes at the cost of lower overall cooperation and earnings, showing that the restriction of partner choice results in an equality-efficiency trade-off. Participants who acted as third-parties were actually more likely to prioritize inequality reduction over efficiency maximization, by forcing individuals with unequal endowment and productivity levels to form pairs with each other. However, decision-makers who had a ‘stake in the game’ self-servingly navigated the equality-efficiency trade-off by preferring partner choice interventions that benefited themselves. These preferences were partly explained by norms on public good cooperation and redistribution, and participants’ social preferences. Results reveal potential conflicts on how to govern free partner choice stemming from diverging preferences ‘among unequals’.
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Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
Agricultural/horticultural products account for 9% of Dutch gross domestic product. Yearly expansion of production involves major challenges concerning labour costs and plant health control. For growers, one of the most urgent problems is pest detection, as pests cause up to 10% harvest loss, while the use of chemicals is increasingly prohibited. For consumers, food safety is increasingly important. A potential solution for both challenges is frequent and automated pest monitoring. Although technological developments such as propeller-based drones and robotic arms are in full swing, these are not suitable for vertical horticulture (e.g. tomatoes, cucumbers). A better solution for less labour intensive pest detection in vertical crop horticulture, is a bio-inspired FW-MAV: Flapping Wings Micro Aerial Vehicle. Within this project we will develop tiny FW-MAVs inspired by insect agility, with high manoeuvrability for close plant inspection, even through leaves without damage. This project focusses on technical design, testing and prototyping of FW-MAV and on autonomous flight through vertically growing crops in greenhouses. The three biggest technical challenges for FW-MAV development are: 1) size, lower flight speed and hovering; 2) Flight time; and 3) Energy efficiency. The greenhouse environment and pest detection functionality pose additional challenges such as autonomous flight, high manoeuvrability, vertical take-off/landing, payload of sensors and other equipment. All of this is a multidisciplinary challenge requiring cross-domain collaboration between several partners, such as growers, biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. In this project a co-creation based collaboration is established with all stakeholders involved, integrating technical and biological aspects.
This pre-study anticipates to a SIA call focussing on circular and bio-based economy in Brazil. It is linked to the Living Lab Brazil managed by Avans University of Applied Sciences. Although the dairy value chain will benefit from both circular and bio-based principles, this pre-study will be limited to circular systems. There is a vast potential for investment by the Dutch and Brazilian private sector in the dairy value chain in Minas Gerais (MG), Brazil. There is also ample room to improve production efficiency towards a more circular system. Notwithstanding the business opportunities in the Brazilian dairy sector, there are challenges in attracting and consolidating partnerships along the circular-based value chain. A better understanding of the demands, challenges and opportunities of the interested Dutch companies is highly relevant to develop sustainable circular-based dairy value chains. Therefore, the goal of our project proposal is the exploration of a potential Dutch business network that is interested to invest in the Brazilian circular dairy value chain, and an exploration of the potential business opportunities for the Dutch and Brazilian dairy sector. The consortium in our proposal is conformed as follows: (a) Van Hall Larenstein University of Applied Sciences (VHL). VHL is the leading knowledge institute. Vilentum University of Applied Sciences and the Federal University of Viçosa will participate through VHL. (b) Alta Genetics BV; (c) Groasis BV. To achieve our goal we focus on the following questions: What is the potential and what are the bottlenecks for the Dutch private sector (SME’s) to increase business opportunities in the dairy sector of MG? What are the business opportunities to develop and innovate circular-based dairy value chains through the Dutch and Brazilian private sector with dairy breeding and agro-silvopastoral farming as pilots? The outputs of this study will be: A list of potential Dutch private investors, both interested but hesitating and/or already successful. Basically we would like to identify “partners” and to build up a business network where we could match-make the Dutch companies with the Brazilian companies or clients; A pre-proposal including intentions for further collaboration; Three detailed reports with marketing and investment opportunities and/or research strategy in relation to circular-based economy in: general dairy chain, dairy breeding and agro-silvopastoral farming. The latter two topics must be considered as pilots for the entire dairy value chain.
