In the knowledge economy knowledge productivity is the main source of competitive advantage and thus the biggest management challenge. Based on a review of the concept from two distinct perspectives, knowledge productivity is defined as the process of knowledge-creation that leads to incremental and radical innovation. The two main elements in this definition are „the process of knowledge creation‟ and „incremental and radical innovation‟. The main aim of this chapter is to contribute to a better understanding of the concept of knowledge productivity in order to support management in designing policies for knowledge productivity enhancement. After elaborating on the concept of knowledge productivity, the two main elements are combined in a conceptual framework – the knowledge productivity flywheel. This framework appeared to be an effective model for supporting initiatives that aim for enhancing knowledge productivity.
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Purpose: The purpose of this study is to find determinants about risk resilience and develop a new risk resilience approach for (agricultural) enterprises. This approach creates the ability to respond resiliently to major environmental challenges and changes in the short term and adjust the management of the organization, and to learn and transform to adapt to the new environment in the long term while creating multiple value creation. Design/methodology: The authors present a new risk resilience approach for multiple value creation of (agricultural) enterprises, which consists of a main process starting with strategy design, followed by an environmental analysis, stakeholder collaboration, implement ESG goals, defining risk expose & response options, and report, learn & evaluate. In each step the organizational perspective, as well as the value chain/area perspective is considered and aligned. The authors have used focus groups and analysed literature from and outside the field of finance and accounting, to design this new approach. Findings: Researchers propose a new risk resilience approach for (agricultural) enterprises, based on a narrative about transforming to multiple value creation, founded determinants of risk resilience, competitive advantage and agricultural resilience. Originality and value: This study contributes by conceptualizing risk resilience for (agricultural) enterprises, by looking through a lens of multiple value creation in a dynamic context and based on insights from different fields, actual ESG knowledge, and determinants for risk resilience, competitive advantage and agricultural resilience.
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The focus of this project is on improving the resilience of hospitality Small and Medium Enterprises (SMEs) by enabling them to take advantage of digitalization tools and data analytics in particular. Hospitality SMEs play an important role in their local community but are vulnerable to shifts in demand. Due to a lack of resources (time, finance, and sometimes knowledge), they do not have sufficient access to data analytics tools that are typically available to larger organizations. The purpose of this project is therefore to develop a prototype infrastructure or ecosystem showcasing how Dutch hospitality SMEs can develop their data analytic capability in such a way that they increase their resilience to shifts in demand. The one year exploration period will be used to assess the feasibility of such an infrastructure and will address technological aspects (e.g. kind of technological platform), process aspects (e.g. prerequisites for collaboration such as confidentiality and safety of data), knowledge aspects (e.g. what knowledge of data analytics do SMEs need and through what medium), and organizational aspects (what kind of cooperation form is necessary and how should it be financed).Societal issueIn the Netherlands, hospitality SMEs such as hotels play an important role in local communities, providing employment opportunities, supporting financially or otherwise local social activities and sports teams (Panteia, 2023). Nevertheless, due to their high fixed cost / low variable business model, hospitality SMEs are vulnerable to shifts in consumer demand (Kokkinou, Mitas, et al., 2023; Koninklijke Horeca Nederland, 2023). This risk could be partially mitigated by using data analytics, to gain visibility over demand, and make data-driven decisions regarding allocation of marketing resources, pricing, procurement, etc…. However, this requires investments in technology, processes, and training that are oftentimes (financially) inaccessible to these small SMEs.Benefit for societyThe proposed study touches upon several key enabling technologies First, key enabling technology participation and co-creation lies at the center of this proposal. The premise is that regional hospitality SMEs can achieve more by combining their knowledge and resources. The proposed project therefore aims to give diverse stakeholders the means and opportunity to collaborate, learn from each other, and work together on a prototype collaboration. The proposed study thereby also contributes to developing knowledge with and for entrepreneurs and to digitalization of the tourism and hospitality sector.Collaborative partnersHZ University of Applied Sciences, Hotel Hulst, Hotel/Restaurant de Belgische Loodsensociëteit, Hotel Zilt, DM Hotels, Hotel Charley's, Juyo Analytics, Impuls Zeeland.
Many lithographically created optical components, such as photonic crystals, require the creation of periodically repeated structures [1]. The optical properties depend critically on the consistency of the shape and periodicity of the repeated structure. At the same time, the structure and its period may be similar to, or substantially below that of the optical diffraction limit, making inspection with optical microscopy difficult. Inspection tools must be able to scan an entire wafer (300 mm diameter), and identify wafers that fail to meet specifications rapidly. However, high resolution, and high throughput are often difficult to achieve simultaneously, and a compromise must be made. TeraNova is developing an optical inspection tool that can rapidly image features on wafers. Their product relies on (a) knowledge of what the features should be, and (b) a detailed and accurate model of light diffraction from the wafer surface. This combination allows deviations from features to be identified by modifying the model of the surface features until the calculated diffraction pattern matches the observed pattern. This form of microscopy—known as Fourier microscopy—has the potential to be very rapid and highly accurate. However, the solver, which calculates the wafer features from the diffraction pattern, must be very rapid and precise. To achieve this, a hardware solver will be implemented. The hardware solver must be combined with mechatronic tracking of the absolute wafer position, requiring the automatic identification of fiduciary markers. Finally, the problem of computer obsolescence in instrumentation (resulting in security weaknesses) will also be addressed by combining the digital hardware and software into a system-on-a-chip (SoC) to provide a powerful, yet secure operating environment for the microscope software.
Renewable energy, particularly offshore wind turbines, plays a crucial role in the Netherlands' and EU energy-transition-strategies under the EU Green Deal. The Dutch government aims to establish 75GW offshore wind capacity by 2050. However, the sector faces human and technological challenges, including a shortage of maintenance personnel, limited operational windows due to weather, and complex, costly logistics with minimal error tolerance. Cutting-edge robotic technologies, especially intelligent drones, offer solutions to these challenges. Smaller drones have gained prominence through applications identifying, detecting, or applying tools to various issues. Interest is growing in collaborative drones with high adaptability, safety, and cost-effectiveness. The central practical question from network partners and other stakeholders is: “How can we deploy multiple cooperative drones for maintenance of wind turbines, enhancing productivity and supporting a viable business model for related services?” This is reflected in the main research question: "Which drone technologies need to be developed to enable collaborative maintenance of offshore wind turbines using multiple smaller drones, and how can an innovative business model be established for these services? In collaboration with public and private partners, Saxion, Hanze, and RUG will research the development of these collaborative drones and investigate the technology’s potential. The research follows a Design Science Research methodology, emphasizing solution-oriented applied research, iterative development, and rigorous evaluation. Key technological building blocks to be developed: • Morphing drones, • Intelligent mechatronic tools, • Learning-based adaptive interaction controllers and collaborations. To facilitate the sustainable industrial uptake of the developed technologies, appropriate sustainable business models for these technologies and services will be explored. The project will benefit partners by enhancing their operations and business. It will contribute to renewing higher professional education and may lead to the creation of spin-offs/spinouts which bring this innovative technology to the society, reinforcing the Netherlands' position as a leading knowledge economy.
