Het onderzoek in het artikel is geïnspireerd door de casus 'platooning' uit de Grand Cooperative Driving Challenge. Er is een PreScan®/Sumulink® model opgesteld met daarin twee auto's. De voorste auto volgt een vastgesteld snelheidsprofiel, de tweede auto volgt de eerste auto waarbij de tweede auto de snelheid van de eerste meet met behulp van een AIR-sensor. De besturing van het gaspedaal in beide auto's vindt plaats met Fuzzy Logic Control in plaats van met een klassieke regelaar. Concluderend mag worden gesteld dat in dit verkennend onderzoek gebleken is dat de Fuzzy Logic Control techniek in principe werkt.
The aim of this study is to understand how governance mechanisms in cross-sector collaborations (CSCs) for sustainability affect value creation and capture and subsequently the survival of this organizational form. Drawing on a longitudinal, participatory, single-case study of collaborative action in the textile industry, we identify three governance mechanisms—safeguarding, bundling and connecting—that coevolve with the rising and waning of collaborative tensions and the shifting levels of action in the CSC we studied. These mechanisms aided value creation and helped facilitate private value capture. We integrate these insights into a process model that visualizes the interplay between governance mechanisms of tensions and systems of value creation and capture in CSCs for sustainability. Our study contributes to the cross-sector collaboration literature by providing a dynamic and nuanced understanding of how governance mechanisms influence outcomes in CSCs for sustainability. We also add to the business model for sustainability literature by theorizing the value creation and capture system of collaborative rather than individual organizations. Our findings have important implications for policymakers who fund collaborative organizations and practitioners who manage or participate in them.
Inter-organizational arrangements that aim to address social and environmental “grand challenges” often take the form of multi-stakeholder initiatives (MSIs) (also cross-sector partnerships or collaborations). Grand challenges -- problems characterized by knowledge uncertainty, dynamic complexity and value conflict -- require diverse organizations to join forces to resolve them. MSIs are complex and dynamic arrangements due to the constant change occurring in the external environment and in the dynamics of the collaboration, as each participating organization may have very different frames of reference and interests that impede action and continuity. Scholars have long recognized the tensions of conflicting logics that are inherent in MSIs and the challenges that MSIs face in reconciling incongruent organizational identities, goals or shared visions. Accordingly, MSIs need facilitators (i.e., ‘orchestrators’) to navigate the persistent and pervasive challenges of both reconciling conflicting logics and using complementary logics in such a way that the collaboration achieves collective goals. Our study examines how MSI orchestrators work to meet this challenge by shaping and shifting cognitive frames in the context of a mature organizational field. We investigate the mechanisms used to enable cognitive shifts in logic and highlight the role of orchestration in enacting frame shifts. Empirically, we examine an MSI in the apparel industry that aims to guide retailers and fashion brands in the implementation of recommerce and rental business models, thereby pushing the textile and apparel industry from linear to regenerative and circular use of textile resources. We identify several frames from the perspective of diverse stakeholders and uncover the four mechanisms that orchestrators use to influence frame shifts. We also see from our findings that orchestrators efforts to influence and navigate frame shifting is both emergent and planned as they attempt to navigate and manage the tensions and complexity that arise in multi-stakeholder initiatives focused on sustainability challenges.
MULTIFILE
De synergie tussen Robotica en AI biedt vele oplossingsmogelijkheden voor (internationale) maatschappelijke opgaven waarvoor we staan (SDG’s, de EU Grand-Challenges, KIA’s). Een consortium van thans 9 Hogescholen, TKI-HTSM en Holland Robotics (community >600 organisaties) slaan de handen ineen om de ontwikkeling van praktijkkennis te versnellen, kennis te delen en betekenisvolle oplossingen te realiseren voor allehande vraagstukken op het gebied van de zorg, het klimaat, onze veiligheid, duurzame energievoorziening, het verdienvermogen van de Nederlandse (maak)industrie en het onderwijs. Robotisering en AI biedt publiek/private organisaties nieuwe mogelijkheden om taken, diensten en processen meer efficiënt, veilig en (kosten)effectief uit te voeren. Robots werken (steeds meer) samen met mensen en kunnen gevaarlijke en/of moeilijke taken overnemen. Ze creëren ook nieuwe mogelijkheden, die anders niet mogelijk zijn. Dit platform, aansluitend bij de KIA-Sleuteltechnologieën, heeft ambities om praktijkkennis sneller te ontwikkelen, deze te bundelen en toe te passen in relevante applicatiedomeinen. Alle mooie ontwikkelingen ten spijt, is het lerende vermogen en/of het autonoom handelen van robots nog minder dan dat van mensen. Robots hebben bijvoorbeeld moeite met het omgaan met onvoorziene omstandigheden en werken in ongestructureerde omgevingen. Om robots te kunnen laten denken en doen als mensen, is er nog een lange weg te gaan. De echte synergie tussen Robotica & AI, waarop dit platform zich richt, heeft een veelbelovend potentieel om de volgende sprong te maken om de bovengenoemde uitdagingen aan te gaan. Platformdeelnemers willen, op basis van een gezamenlijk roadmap, nieuwe praktijkkennis delen, ontwikkelen en toepassen in relevante (applicatie)domeinen. Zo worden betekenisvolle bijdragen geleverd aan urgente maatschappelijk vraagstukken. Het platform heeft als doel om in de quintuple helix kennis duurzaam te laten circuleren, een wenkend perspectief te bieden voor alle stakeholders, Applied Smart Robotica & AI-onderzoek beter landelijk en internationaal te positioneren, te focussen op meervoudige waardecreatie en gezamenlijk te werken aan iconische projecten.
In the past decades, we have faced an increase in the digitization, digitalization, and digital transformation of our work and daily life. Breakthroughs of digital technologies in fields such as artificial intelligence, telecommunications, and data science bring solutions for large societal questions but also pose a new challenge: how to equip our (future)workforce with the necessary digital skills, knowledge, and mindset to respond to and drive digital transformation?Developing and supporting our human capital is paramount and failure to do so may leave us behind on individual (digital divide), organizational (economic disadvantages), and societal level (failure in addressing grand societal challenges). Digital transformation necessitates continuous learning approaches and scaffolding of interdisciplinary collaboration and innovation practices that match complex real-world problems. Research and industry have advocated for setting up learning communities as a space in which (future) professionals of different backgrounds can work, learn, and innovate together. However, insights into how and under which circumstances learning communities contribute to accelerated learning and innovation for digital transformation are lacking. In this project, we will study 13 existing and developing learning communities that work on challenges related to digital transformation to understand their working mechanisms. We will develop a wide variety of methods and tools to support learning communities and integrate these in a Learning Communities Incubator. These insights, methods and tools will result in more effective learning communities that will eventually (a) increase the potential of human capital to innovate and (b) accelerate the innovation for digital transformation
Climate change is one of the most critical global challenges nowadays. Increasing atmospheric CO2 concentration brought by anthropogenic emissions has been recognized as the primary driver of global warming. Therefore, currently, there is a strong demand within the chemical and chemical technology industry for systems that can covert, capture and reuse/recover CO2. Few examples can be seen in the literature: Hamelers et al (2013) presented systems that can use CO2 aqueous solutions to produce energy using electrochemical cells with porous electrodes; Legrand et al (2018) has proven that CDI can be used to capture CO2 without solvents; Shu et al (2020) have used electrochemical systems to desorb (recover) CO2 from an alkaline absorbent with low energy demand. Even though many efforts have been done, there is still demand for efficient and market-ready systems, especially related to solvent-free CO2 capturing systems. This project intends to assess a relatively efficient technology, with low-energy costs which can change the CO2 capturing market. This technology is called whorlpipe. The whorlpipe, developed by Viktor Schauberger, has shown already promising results in reducing the energy and CO2 emissions for water pumping. Recently, studies conducted by Wetsus and NHL Stenden (under submission), in combination with different companies (also members in this proposal) have shown that vortices like systems, like the Schauberger funnel, and thus “whorlpipe”, can be fluid dynamically represented using Taylor-Couette flows. This means that such systems have a strong tendency to form vortices like fluid-patterns close to their air-water interface. Such flow system drastically increase advection. Combined with their higher area to volume ratio, which increases diffusion, these systems can greatly enhance gas capturing (in liquids), and are, thus, a unique opportunity for CO2 uptake from the air, i.e. competing with systems like conventional scrubbers or bubble-based aeration.
