When preparing students for the industry’s global context, publishing degrees aim to provide them with experience of cooperating and doing business with colleagues internationally. In order to achieve this, Oxford Brookes University and Amsterdam University of Applied Sciences have designed a module on trading in translation rights that gives students both a theoretical framework and real-world insights into book fairs and intercultural collaboration.In this module, students of both universities work collaboratively in a game that simulates the trading of intellectual property rights at an international event designed to resemble a major book fair. They team up in international groups of five or six students that each represent a publishing company in order to prepare for and to participate in an event called the Oxdam Book Fair. Preparation for the fair involves the development of plans and appropriate materials to sell translation rights for the company’s titles and to buy rights to titles which fit the company’s profile and strategy. During the event students partake in several rounds of rights trading activities, including pitching, strategy meetings, making offers, and networking.In this proposed paper, that contributes to the best practices-strand of the conference, lecturers of Oxford Brookes University and Amsterdam University of Applied Sciences will provide a ‘behind the scenes’-look at this collaborative module. They will talk about the simulation game that is the core of the module, provide background on the theoretical framework, address educational design challenges they encountered, and share outcomes of the collaborative module.
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Our paper investigates the microfoundations of sustainable entrepreneurship and aims to shed light on trade-offs made in decisions about social, ecological and economic sustainability. Balancing the three dimensions of sustainability (social, ecological and economic) inherently requires choices in which one dimension or another has less optimal outcomes. There is not much known about the rationale that sustainable entrepreneurs use for making such trade-offs. Thus, we ask how does entrepreneurial orientation affect decisions and trade-offs on sustainability impact? Our study is an exploratory, qualitative study of 24 sustainable entrepreneurs. We collected data about entrepreneurial orientation and sustainability trade-offs and held in-depth interviews with a subsample of six firms. We conducted a cluster analysis based on four entrepreneurial orientations (innovativeness, proactiveness, riskiness and futurity) and three sustainability trade-off dimensions (environmental, social and economic). From the findings, we derive a typology of three types of sustainable entrepreneurs: green-conflicted, humanitarian-oriented and holistically-oriented. We uncover salient characteristics and aspects of entrepreneurial orientation in relation to trade-off decisions. We find that the entrepreneurs accept slower economic growth or lower performance in order to maintain the integrity of their social and ecological principles and values.
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.
Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.
Organisations are increasingly embedding Artificial Intelligence (AI) techniques and tools in their processes. Typical examples are generative AI for images, videos, text, and classification tasks commonly used, for example, in medical applications and industry. One danger of the proliferation of AI systems is the focus on the performance of AI models, neglecting important aspects such as fairness and sustainability. For example, an organisation might be tempted to use a model with better global performance, even if it works poorly for specific vulnerable groups. The same logic can be applied to high-performance models that require a significant amount of energy for training and usage. At the same time, many organisations recognise the need for responsible AI development that balances performance with fairness and sustainability. This KIEM project proposal aims to develop a tool that can be employed by organizations that develop and implement AI systems and aim to do so more responsibly. Through visual aiding and data visualisation, the tool facilitates making these trade-offs. By showing what these values mean in practice, which choices could be made and highlighting the relationship with performance, we aspire to educate users on how the use of different metrics impacts the decisions made by the model and its wider consequences, such as energy consumption or fairness-related harms. This tool is meant to facilitate conversation between developers, product owners and project leaders to assist them in making their choices more explicit and responsible.
