This paper frames the process of designing a level in a game as a series of model transformations. The transformations correspond to the application of particular design principles, such as the use of locks and keys to transform a linear mission into a branching space. It shows that by using rewrite systems, these transformations can be formalized and automated. The resulting automated process is highly controllable: it is a perfect match for a mixed-initiative approach to level generation where human and computer collaborate in designing levels. An experimental prototype that implements these ideas is presented.
The importance of leadership is increasingly recognized in relation to digital transformation. Therefore, middle management and top management must have the competencies required to lead such a transformation. The purpose of this paper is to investigate the relationship between the digital leader competencies as set out by the European e-competence framework (e-CF) and the digital transformation of organizations. Also, the relationship between digital leadership competency (DLC) and IT capability is examined. An empirical investigation is presented based on a sample of 433 respondents, analyzed using PLS-SEM. The results strongly support our hypotheses. DLC has a strong impact on organizational digital transformation. A post-hoc analysis showed this is predominantly the case for the e-CF competencies of business plan development, architecture design, and innovating while business change management and governance do not seem to affect organizational digital transformation. This is the first empirical study to conceptualize, operationalize and validate the concept of DLC, based on the e-competence framework, and its impact on digital transformation. These findings have significant implications for researchers and practitioners working on the transformation toward a digital organization.
MULTIFILE
Author supplied: "This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices and correlation between epochs can be handled. The determination of transformation parameters between two or more coordinate sets, determined by geodetic monitoring measurements, can be handled as a least squares adjustment problem. It can be solved without linearisation of the functional model, if it concerns an affine, similarity or congruence transformation in one-, two- or three-dimensional space. If the functional model describes more than such a transformation, it is hardly ever possible to find a direct solution for the transformation parameters. Linearisation of the functional model and applying least squares formulas is then an appropriate mode of working. The adjustment model is given as a model of observation equations with constraints on the parameters. The starting point is the affine transformation, whose parameters are constrained to get the parameters of the similarity or congruence transformation. In this way the use of Euler angles is avoided. Because the model is linearised, iteration is necessary to get the final solution. In each iteration step approximate coordinates are necessary that fulfil the constraints. For the affine transformation it is easy to get approximate coordinates. For the similarity and congruence transformation the approximate coordinates have to comply to constraints. To achieve this, use is made of the singular value decomposition of the rotation matrix. To show the effectiveness of the proposed adjustment model total station measurements in two epochs of monitored buildings are analysed. Coordinate sets with full, rank deficient covariance matrices are determined from the measurements and adjusted with the proposed model. Testing the adjustment for deformations results in detection of the simulated deformations."
MULTIFILE
The primary objective of the project is to identify policies for the transformation of the Norwegian tourism sector to become resilient to climate change and carbon risks; to maintain and develop its economic benefits; and to significantly reduce its emissions-intensity per unit of economic output. Collaborative partnersStiftinga Vestlandforsking, Stiftelsen Handelshoyskolen, Stat Sentralbyra, Norges Handelshoyskole, Stiftelsen Nordlandsforskning, Fjord Norge, Hurtigruten, Neroyfjorden Verdsarvpark, Uni Waterloo, Uni Queensland, Desinasjon Voss, Stift Geirangerfjorden Verdsarv, Hogskulen Pa Vestlandet.
Collaborative networks for sustainability are emerging rapidly to address urgent societal challenges. By bringing together organizations with different knowledge bases, resources and capabilities, collaborative networks enhance information exchange, knowledge sharing and learning opportunities to address these complex problems that cannot be solved by organizations individually. Nowhere is this more apparent than in the apparel sector, where examples of collaborative networks for sustainability are plenty, for example Sustainable Apparel Coalition, Zero Discharge Hazardous Chemicals, and the Fair Wear Foundation. Companies like C&A and H&M but also smaller players join these networks to take their social responsibility. Collaborative networks are unlike traditional forms of organizations; they are loosely structured collectives of different, often competing organizations, with dynamic membership and usually lack legal status. However, they do not emerge or organize on their own; they need network orchestrators who manage the network in terms of activities and participants. But network orchestrators face many challenges. They have to balance the interests of diverse companies and deal with tensions that often arise between them, like sharing their innovative knowledge. Orchestrators also have to “sell” the value of the network to potential new participants, who make decisions about which networks to join based on the benefits they expect to get from participating. Network orchestrators often do not know the best way to maintain engagement, commitment and enthusiasm or how to ensure knowledge and resource sharing, especially when competitors are involved. Furthermore, collaborative networks receive funding from grants or subsidies, creating financial uncertainty about its continuity. Raising financing from the private sector is difficult and network orchestrators compete more and more for resources. When networks dissolve or dysfunction (due to a lack of value creation and capture for participants, a lack of financing or a non-functioning business model), the collective value that has been created and accrued over time may be lost. This is problematic given that industrial transformations towards sustainability take many years and durable organizational forms are required to ensure ongoing support for this change. Network orchestration is a new profession. There are no guidelines, handbooks or good practices for how to perform this role, nor is there professional education or a professional association that represents network orchestrators. This is urgently needed as network orchestrators struggle with their role in governing networks so that they create and capture value for participants and ultimately ensure better network performance and survival. This project aims to foster the professionalization of the network orchestrator role by: (a) generating knowledge, developing and testing collaborative network governance models, facilitation tools and collaborative business modeling tools to enable network orchestrators to improve the performance of collaborative networks in terms of collective value creation (network level) and private value capture (network participant level) (b) organizing platform activities for network orchestrators to exchange ideas, best practices and learn from each other, thereby facilitating the formation of a professional identity, standards and community of network orchestrators.
The objective of DIGIREAL-XL is to build a Research, Development & Innovation (RD&I) Center (SPRONG GROUP, level 4) on Digital Realities (DR) for Societal-Economic Impact. DR are intelligent, interactive, and immersive digital environments that seamlessly integrate Data, Artificial Intelligence/Machine Learning, Modelling-Simulation, and Visualization by using Game and Media Technologies (Game platforms/VR/AR/MR). Examples of these DR disruptive innovations can be seen in many domains, such as in the entertainment and service industries (Digital Humans); in the entertainment, leisure, learning, and culture domain (Virtual Museums and Music festivals) and within the decision making and spatial planning domain (Digital Twins). There are many well-recognized innovations in each of the enabling technologies (Data, AI,V/AR). However, DIGIREAL-XL goes beyond these disconnected state-of-the-art developments and technologies in its focus on DR as an integrated socio-technical concept. This requires pre-commercial, interdisciplinary RD&I, in cross-sectoral and inter-organizational networks. There is a need for integrating theories, methodologies, smart tools, and cross-disciplinary field labs for the effective and efficient design and production of DR. In doing so, DIGIREAL-XL addresses the challenges formulated under the KIA-Enabling Technologies / Key Methodologies for sectoral and societal transformation. BUas (lead partner) and FONTYS built a SPRONG group level 4 based on four pillars: RD&I-Program, Field Labs, Lab-Infrastructure, and Organizational Excellence Program. This provides a solid foundation to initiate and execute challenging, externally funded RD&I projects with partners in SPRONG stage one ('21-'25) and beyond (until' 29). DIGIREAL-XL is organized in a coherent set of Work Packages with clear objectives, tasks, deliverables, and milestones. The SPRONG group is well-positioned within the emerging MINDLABS Interactive Technologies eco-system and strengthens the regional (North-Brabant) digitalization agenda. Field labs on DR work with support and co-funding by many network organizations such as Digishape and Chronosphere and public, private, and societal organizations.
